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8. A method for providing searchable call indexes, comprising: receiving call information associated with each of a plurality of telephone conversations between at least one customer and at least one vendor, the call information including at least an audio recording; identifying, by a server executing a software application configured to provide searchable call indexes, one or more errors comprising at least a failure to identify words from audio recordings; determining, by the server, a cause of the one or more errors; generating, by the server, improvement data configured to correct the one or more errors; identifying one or more keywords based at least on the improvement data; indexing the call information associated with each telephone conversation based on the one or more keywords into a first index associated with the customer and a second index associated with the vendor; and determining search results from the first and second indexes responsive to a search query.

8. A method for providing searchable call indexes, comprising: receiving call information associated with each of a plurality of telephone conversations between at least one customer and at least one vendor, the call information including at least an audio recording; identifying, by a server executing a software application configured to provide searchable call indexes, one or more errors comprising at least a failure to identify words from audio recordings; determining, by the server, a cause of the one or more errors; generating, by the server, improvement data configured to correct the one or more errors; identifying one or more keywords based at least on the improvement data; indexing the call information associated with each telephone conversation based on the one or more keywords into a first index associated with the customer and a second index associated with the vendor; and determining search results from the first and second indexes responsive to a search query. 9. The method of claim 8 , wherein the call information further includes a voiceprint of the telephone conversation, and wherein the one or more processors is configured to index the call information based on at least one stress feature identified in the voiceprint.

1. An audio signal segmentation algorithm comprising: providing an audio signal; applying an audio activity detection (AAD) step to divide the audio signal into at least one first audio segment and at least one second audio segment, wherein the audio activity detection step further comprises: dividing the audio signal into a plurality of frames; applying a frequency transformation step to signals in each of the frames to obtain a plurality of bands in each frame; performing a likelihood computation step to the bands and a noise parameter to obtain a likelihood ratio therebetween; performing a comparison step to the likelihood ratio and a noise threshold, if the noise threshold is greater than the likelihood ratio, the bands belonging to a first frame, and if the likelihood ratio is greater than the noise threshold, the bands belonging to a second frame wherein the first frame belongs to the first audio segment and the second frame belongs to the second audio segment; and when a distance between two adjacent second frames is smaller than a predetermined value, combining the two adjacent second frames to compose the second audio segment, performing an audio feature extraction step on the second audio segment to obtain a plurality of audio features of the second audio segment; applying a smoothing step to the second audio segment after the audio feature extraction step; and discriminating a plurality of speech frames and a plurality of music frames from the second audio segment wherein the speech frames and the music frames compose at least one speech segment and at least one music segment, respectively.

1. An audio signal segmentation algorithm comprising: providing an audio signal; applying an audio activity detection (AAD) step to divide the audio signal into at least one first audio segment and at least one second audio segment, wherein the audio activity detection step further comprises: dividing the audio signal into a plurality of frames; applying a frequency transformation step to signals in each of the frames to obtain a plurality of bands in each frame; performing a likelihood computation step to the bands and a noise parameter to obtain a likelihood ratio therebetween; performing a comparison step to the likelihood ratio and a noise threshold, if the noise threshold is greater than the likelihood ratio, the bands belonging to a first frame, and if the likelihood ratio is greater than the noise threshold, the bands belonging to a second frame wherein the first frame belongs to the first audio segment and the second frame belongs to the second audio segment; and when a distance between two adjacent second frames is smaller than a predetermined value, combining the two adjacent second frames to compose the second audio segment, performing an audio feature extraction step on the second audio segment to obtain a plurality of audio features of the second audio segment; applying a smoothing step to the second audio segment after the audio feature extraction step; and discriminating a plurality of speech frames and a plurality of music frames from the second audio segment wherein the speech frames and the music frames compose at least one speech segment and at least one music segment, respectively. 14. The audio signal segmentation algorithm according to claim 1 , further comprising segmenting the speech segment and the music segment from the second audio segment.

1. A method for operating a knowledge market comprising: creating a knowledge base comprising a plurality of knowledge assets; assigning a strike value to each of the knowledge assets; and computing, by a processor, an earned value for each of the knowledge assets based on corresponding usage of each of the plurality of knowledge assets, wherein the assigning the strike value to each of the knowledge assets occurs before use of the knowledge asset, and wherein the strike value is determined for each of the plurality of knowledge assets using an estimate of importance of the knowledge asset and an estimate of replaceability of the knowledge asset.

1. A method for operating a knowledge market comprising: creating a knowledge base comprising a plurality of knowledge assets; assigning a strike value to each of the knowledge assets; and computing, by a processor, an earned value for each of the knowledge assets based on corresponding usage of each of the plurality of knowledge assets, wherein the assigning the strike value to each of the knowledge assets occurs before use of the knowledge asset, and wherein the strike value is determined for each of the plurality of knowledge assets using an estimate of importance of the knowledge asset and an estimate of replaceability of the knowledge asset. 7. The method of claim 1 , further comprising periodically computing a return on knowledge asset for each of the plurality of knowledge assets, wherein the return on knowledge asset for each of the plurality of knowledge assets equals its strike value divided by its earned value.

1. A computer-implemented method comprising: receiving, by a search engine and from a classifier, topic information indicating that, based at least on information about a user that was provided by the search engine to the classifier, the user is likely interested in a set of one or more topics; receiving, by the search engine, a search query with one or more terms that correspond to a subset of the topics in which the user is likely interested; identifying, by the search engine, the subset of the topics in which the user is likely interested that correspond to one or more terms in the search query; generating, by the search engine, a search results page that includes a link (i) to a particular resource that the search engine identifies as responsive to the search query, and (ii) that is encoded with topic information for the subset of topics that were indicated to the search engine by the classifier as topics in which the user is likely interested and identified by the search engine as topics that correspond to one or more terms in the search query; and providing the search results page for display.

1. A computer-implemented method comprising: receiving, by a search engine and from a classifier, topic information indicating that, based at least on information about a user that was provided by the search engine to the classifier, the user is likely interested in a set of one or more topics; receiving, by the search engine, a search query with one or more terms that correspond to a subset of the topics in which the user is likely interested; identifying, by the search engine, the subset of the topics in which the user is likely interested that correspond to one or more terms in the search query; generating, by the search engine, a search results page that includes a link (i) to a particular resource that the search engine identifies as responsive to the search query, and (ii) that is encoded with topic information for the subset of topics that were indicated to the search engine by the classifier as topics in which the user is likely interested and identified by the search engine as topics that correspond to one or more terms in the search query; and providing the search results page for display. 2. The computer-implemented method of claim 1 , wherein the information about the user that was received by the search engine indicates a likelihood, for each topic of the set of one or more topics, that the user is interested in the topic, and wherein the information, encoded with the link, that references the subset of topics that were indicated to the search engine by the classifier as topics in which the user is likely interested indicates the likelihood, for each topic of the subset of the topics, that the user is interested in the topic.

10. One or more non-transitory computer-readable media storing instructions which, when executed on one or more computing devices, cause the one or more computing devices to perform a method comprising: obtaining information that indicates the play personality of the user; wherein the information indicates which play type, of a plurality of play types, satisfies the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; determining that the user is using the computing device; and during execution of software that generates output displayed on the computing device while the user is using the device, adapting operation of the software based, at least in part, on the play personality of the user.

10. One or more non-transitory computer-readable media storing instructions which, when executed on one or more computing devices, cause the one or more computing devices to perform a method comprising: obtaining information that indicates the play personality of the user; wherein the information indicates which play type, of a plurality of play types, satisfies the user's need for play; wherein the plurality of play types includes two or more of: Object, Pretend, Social, Rough and Tumble, Body, Exploratory, Celebratory, Competitive, Ritual, Narrative, Fantasy or Games/Gaming; determining that the user is using the computing device; and during execution of software that generates output displayed on the computing device while the user is using the device, adapting operation of the software based, at least in part, on the play personality of the user. 12. The one or more non-transitory computer-readable media of claim 10 wherein adapting operation of the software includes: making a determination that a particular place is associated with an activity; determining one or more play types that are associated with the activity; comparing the one or more play types to the play personality of the user to determine whether the one or more play types are play types that satisfy the user's need for play; and responsive to determining that the one or more play types are play types that satisfy the user's need for play, adapting operation of the software based, at least in part, on the determination that the particular place is associated with an activity that is likely to satisfy the user's need for play; wherein the particular place is one of: a real-world store, a real-world building, a real-world venue, a virtual store, or a virtual venue.

20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device.

20. A method for operating an automated assistant, comprising: at a server computer system provided by a first entity, the server computer system comprising a processor and memory storing instructions for execution by the processor: receiving a voice command and contextual information from the portable electronic device; processing the voice command, using a speech recognition service provided by a second entity different from the first entity, to generate a text string from the voice command; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. 24. The method of claim 20 , wherein the contextual information includes information from one or more sensors on the portable electronic device.

10. A method for managing backup sets based on user feedback, comprising: receiving, by a first client device, from a backup set management server, a default backup set; transmitting at least one file to a backup server, by the first client device, according to the default backup set; receiving, by the first client device from the backup set management server, a recommended modification to the default backup set, the modification to the default backup set based on modifications made by one or more users to default backup sets provided to client devices associated with the one or more users, the recommended modification transmitted responsive to a number of the one or more users exceeding a predetermined threshold; and modifying the default backup set based on the recommended modification received from the server.

10. A method for managing backup sets based on user feedback, comprising: receiving, by a first client device, from a backup set management server, a default backup set; transmitting at least one file to a backup server, by the first client device, according to the default backup set; receiving, by the first client device from the backup set management server, a recommended modification to the default backup set, the modification to the default backup set based on modifications made by one or more users to default backup sets provided to client devices associated with the one or more users, the recommended modification transmitted responsive to a number of the one or more users exceeding a predetermined threshold; and modifying the default backup set based on the recommended modification received from the server. 14. The method of claim 10 , wherein the pre-defined criteria include a file type.

22. A computer storage medium encoded with computer program instructions that when executed by one or more computers cause the one or more computers to perform operations including: providing a user interface for creating a table having at least one input column and at least one output column, wherein each input column is associated with an input variable and each output column is associated with an output variable; in at least one row of the table, receiving one or more conditions on input values in respective input columns, the conditions in the at least one row identifying more than one set of potential values of the input variables, and receiving one or more output values in respective output columns, thereby defining a rule case of a rule specification; generating a function for transforming data based on the rule specification; associating the function with the functional component; receiving changes to values in the rule specification, the changes including new potential values of the input variables for a condition; confirming that the changed rule specification is valid; and associating a new function with the functional component.

22. A computer storage medium encoded with computer program instructions that when executed by one or more computers cause the one or more computers to perform operations including: providing a user interface for creating a table having at least one input column and at least one output column, wherein each input column is associated with an input variable and each output column is associated with an output variable; in at least one row of the table, receiving one or more conditions on input values in respective input columns, the conditions in the at least one row identifying more than one set of potential values of the input variables, and receiving one or more output values in respective output columns, thereby defining a rule case of a rule specification; generating a function for transforming data based on the rule specification; associating the function with the functional component; receiving changes to values in the rule specification, the changes including new potential values of the input variables for a condition; confirming that the changed rule specification is valid; and associating a new function with the functional component. 38. The computer storage medium of claim 22 further including instructions that when executed by one or more computers cause the one or more computers to perform operations that include generating the new function based on the edited rule specification, and disassociating the first function from the functional component.

1. A non-transitory machine readable storage having stored thereon a computer program for testing the display of bi-directional language script prior to translation in an application under test, the computer program comprising a routine set of instructions which when executed by a machine causes the machine to perform the steps of: using unidirectional glyphs with shaping indicators selected from the group consisting of an overbar and an underscore, to simulate right-to-left characters, the shaping indicators each indicating a shaping of a corresponding right-to-left character code point; and, displaying the characters each with a corresponding one of the shaping indicators placed over a corresponding one of the characters in a display of a computer; wherein the using step comprises the steps of: reversing an ordering of a first set of unidirectional text characters in an input string; mapping said unidirectional text characters of said input string in said reversed order to corresponding right-to-left code points in a bi-directional language code page, the mapping producing a pseudo-translated string; loading a plurality of unidirectional language glyphs, each of said glyphs corresponding to a same one of said right-to-left character code points as had been used to produce said pseudo-translated string; and, combining said pseudo-translated string and said glyphs to simulate right-to-left character rendering in an application under test such that a resultant output is visually similar to said input string.

1. A non-transitory machine readable storage having stored thereon a computer program for testing the display of bi-directional language script prior to translation in an application under test, the computer program comprising a routine set of instructions which when executed by a machine causes the machine to perform the steps of: using unidirectional glyphs with shaping indicators selected from the group consisting of an overbar and an underscore, to simulate right-to-left characters, the shaping indicators each indicating a shaping of a corresponding right-to-left character code point; and, displaying the characters each with a corresponding one of the shaping indicators placed over a corresponding one of the characters in a display of a computer; wherein the using step comprises the steps of: reversing an ordering of a first set of unidirectional text characters in an input string; mapping said unidirectional text characters of said input string in said reversed order to corresponding right-to-left code points in a bi-directional language code page, the mapping producing a pseudo-translated string; loading a plurality of unidirectional language glyphs, each of said glyphs corresponding to a same one of said right-to-left character code points as had been used to produce said pseudo-translated string; and, combining said pseudo-translated string and said glyphs to simulate right-to-left character rendering in an application under test such that a resultant output is visually similar to said input string. 2. The machine readable storage of claim 1 , further comprising an additional set of instructions which when executed by the machine further causes the machine to perform the steps of: selecting shaping indicia for said bi-directional code points; and, coordinating a combination of said selected shaping indicia with said unidirectional glyphs to produce said output that allows the detection of shaping errors.

1. A method for facilitating a workflow using a workflow template in a call center, comprising the steps of: providing a first workflow template associated with a workflow item, wherein the first workflow template includes data and scripts for rendering the workflow template and one or more routing rules and one or more trigger points defined for said workflow item, wherein said each trigger point specifies an action to be taken with respect to said workflow item, including routing and supervisor intervention, wherein said one or more routing rules include a workgroup-related threshold that triggers a routing action to be taken with respect to the workgroup, and an agent-related threshold that triggers a routing action to be taken with respect to the agent; linking said first workflow template to a project of an interaction type, wherein the interaction type is one of a phone, web callback, email, and chat, wherein the linking is performed by receiving, via a manager application, a first selection of a project template defining the interaction type from a predefined dropdown list of project templates, wherein the first selection generates a second dropdown list of one or more workflow templates including the first workflow template, and a third dropdown list of one or more additional workflow templates, receiving a second selection of the first workflow template from the second dropdown list, receiving a third selection of a third workflow template from the third dropdown list, receiving a selection of an entry and exit points for each of the workflow templates selected in the second and third selections, and storing attributes of each of the project template and workflow templates selected in the first, second and third selections and attributes of the entry and exit points, wherein each attribute is linked to at least one of a plurality of scripts used to generate logic flows for the project; routing said workflow item according to the one or more routing rules as defined in the first workflow template, via a server running on one or more microprocessors, to at least one of an agent and a knowledge worker; and receiving a score via a survey of a supervisor and the score being based on a key performance indicator (KPI) library linked to the workflow template selected in the second or third selection and selected from a KPI dropdown list associated with said at least one of an agent and a knowledge worker based on the agent's or the knowledge worker's handling of said workflow item associated with the first workflow template in the project, wherein one or more scoring values are stored in a database and are used for subsequent routing decisions.

1. A method for facilitating a workflow using a workflow template in a call center, comprising the steps of: providing a first workflow template associated with a workflow item, wherein the first workflow template includes data and scripts for rendering the workflow template and one or more routing rules and one or more trigger points defined for said workflow item, wherein said each trigger point specifies an action to be taken with respect to said workflow item, including routing and supervisor intervention, wherein said one or more routing rules include a workgroup-related threshold that triggers a routing action to be taken with respect to the workgroup, and an agent-related threshold that triggers a routing action to be taken with respect to the agent; linking said first workflow template to a project of an interaction type, wherein the interaction type is one of a phone, web callback, email, and chat, wherein the linking is performed by receiving, via a manager application, a first selection of a project template defining the interaction type from a predefined dropdown list of project templates, wherein the first selection generates a second dropdown list of one or more workflow templates including the first workflow template, and a third dropdown list of one or more additional workflow templates, receiving a second selection of the first workflow template from the second dropdown list, receiving a third selection of a third workflow template from the third dropdown list, receiving a selection of an entry and exit points for each of the workflow templates selected in the second and third selections, and storing attributes of each of the project template and workflow templates selected in the first, second and third selections and attributes of the entry and exit points, wherein each attribute is linked to at least one of a plurality of scripts used to generate logic flows for the project; routing said workflow item according to the one or more routing rules as defined in the first workflow template, via a server running on one or more microprocessors, to at least one of an agent and a knowledge worker; and receiving a score via a survey of a supervisor and the score being based on a key performance indicator (KPI) library linked to the workflow template selected in the second or third selection and selected from a KPI dropdown list associated with said at least one of an agent and a knowledge worker based on the agent's or the knowledge worker's handling of said workflow item associated with the first workflow template in the project, wherein one or more scoring values are stored in a database and are used for subsequent routing decisions. 5. The method of claim 1 , wherein said workflow item comprises a document.

9. A method for building concept knowledge in a computer system from a machine-readable dictionary for use by a search engine to facilitate quick and accurate information retrieval, the machine-readable dictionary including a plurality of words in a first language and a plurality of corresponding translated words in a second language, and a plurality of words in the second language and a plurality of corresponding translated words in the first language, said method comprising steps of: providing a seed word in the first language; forward-translating said seed word to obtain a plurality of translated words corresponding to said seed word by looking up said machine-readable dictionary; backward-translating said translated words to obtain a plurality of translated words in the first language corresponding to each of said plurality of translated words obtained by said step of forward-translating respectively, as words of the concept knowledge, by looking up said machine-readable dictionary; storing synonymous words of each translated word in said first language and in said second language; calculating frequency of each translated word in said first language and in said second language; ranking said translated words based on said stored synonymous words and said calculated frequency; presenting said ranked words to a user for allowing the user to select desired words among said ranked words and to delete irrelevant words among said ranked words; and providing the selected desired words to said search engine to perform information retrieval on a knowledge-based level instead of a keyword-based level.

9. A method for building concept knowledge in a computer system from a machine-readable dictionary for use by a search engine to facilitate quick and accurate information retrieval, the machine-readable dictionary including a plurality of words in a first language and a plurality of corresponding translated words in a second language, and a plurality of words in the second language and a plurality of corresponding translated words in the first language, said method comprising steps of: providing a seed word in the first language; forward-translating said seed word to obtain a plurality of translated words corresponding to said seed word by looking up said machine-readable dictionary; backward-translating said translated words to obtain a plurality of translated words in the first language corresponding to each of said plurality of translated words obtained by said step of forward-translating respectively, as words of the concept knowledge, by looking up said machine-readable dictionary; storing synonymous words of each translated word in said first language and in said second language; calculating frequency of each translated word in said first language and in said second language; ranking said translated words based on said stored synonymous words and said calculated frequency; presenting said ranked words to a user for allowing the user to select desired words among said ranked words and to delete irrelevant words among said ranked words; and providing the selected desired words to said search engine to perform information retrieval on a knowledge-based level instead of a keyword-based level. 13. The method for building concept knowledge in a computer system from a machine-readable dictionary for use by a search engine to facilitate quick and accurate information retrieval in accordance with claim 9 , wherein said step of forward-translating further allows a user to select and delete one or more translated words.

14. A computerized apparatus comprising: a processor which is arranged to: obtain a contextual property of a notation to be used in a diagram, wherein the diagram is visual illustration comprising notations and adhering, at least loosely, to grammar of a modeling language, wherein the contextual property defines a context of a usage of the notation in the diagram with respect to the modeling language, and wherein the notation is a graphic symbol; and search in a notation-base for notations, whereby a search result set is obtained, wherein the search result set comprises notations that were previously used in one or more diagrams in a similar context to the contextual property, wherein the one or more diagrams are visual illustrations adhering, at least loosely, to grammar of the modeling language; and wherein the computerized apparatus is operatively coupled to the notation-base.

14. A computerized apparatus comprising: a processor which is arranged to: obtain a contextual property of a notation to be used in a diagram, wherein the diagram is visual illustration comprising notations and adhering, at least loosely, to grammar of a modeling language, wherein the contextual property defines a context of a usage of the notation in the diagram with respect to the modeling language, and wherein the notation is a graphic symbol; and search in a notation-base for notations, whereby a search result set is obtained, wherein the search result set comprises notations that were previously used in one or more diagrams in a similar context to the contextual property, wherein the one or more diagrams are visual illustrations adhering, at least loosely, to grammar of the modeling language; and wherein the computerized apparatus is operatively coupled to the notation-base. 18. The computerized apparatus of claim 14 , wherein said processor is arranged to update the notation-base with usage information in response to a user's selection of a notation out of the search result set to be used in the diagram, whereby said apparatus is configured to update the notation-base to reflect that the notation is used within the contextual property.

14. A system for enhancing performance of a data-pattern recognizer for an individual, the system comprising: one or more processors; a memory; a personalization component that customizes the recognizer to the individual, the personalization being based at least in part upon a sample generated by the individual, the personalization component utilizes regularization biased to a base set of parameters of the recognizer; a base-parameter component that obtains the base set of parameters of the recognizer; and a regularization component that utilizes regularization to determine a new set of parameters for the recognizer based upon the regularization and the sample, wherein one or more of the components comprise a set of processor-executable instructions stored in the memory that, when executed by the one or more processors, perform its described operation.

14. A system for enhancing performance of a data-pattern recognizer for an individual, the system comprising: one or more processors; a memory; a personalization component that customizes the recognizer to the individual, the personalization being based at least in part upon a sample generated by the individual, the personalization component utilizes regularization biased to a base set of parameters of the recognizer; a base-parameter component that obtains the base set of parameters of the recognizer; and a regularization component that utilizes regularization to determine a new set of parameters for the recognizer based upon the regularization and the sample, wherein one or more of the components comprise a set of processor-executable instructions stored in the memory that, when executed by the one or more processors, perform its described operation. 18. The system of claim 14 , wherein the base set of parameters include a base set of weights of the recognizer and the new set of parameters include a new set of weights of the recognizer.

1. A method for assigning a content item to a content item collection under management of a content management system, comprising: at a computing device comprising a touch screen display, one or more processors and memory storing a first application executed by the one or more processors to perform the method, performing operations comprising: after the first application is opened, entering a first application state comprising a plurality of content item collection indicators displayed on the touch screen display; after entering the first application state, detecting a first touch gesture directed to one content item collection indicator of the plurality of content item collection indicators; wherein each content item collection indicator, of the plurality of content item collection indicators, represents one content item collection, of a plurality of content item collections, under management of the content management system; wherein performance of an earlier touch gesture directed to a graphical representation of a content item, displayed on the touch screen display by a second application of the computing device that is not the first application, causes the first application to open and enter the first application state; after detecting the first touch gesture, assigning a copy of the content item to the content item collection, of the plurality of content item collections, represented by the one content item collection indicator to which the first touch gesture is directed.

1. A method for assigning a content item to a content item collection under management of a content management system, comprising: at a computing device comprising a touch screen display, one or more processors and memory storing a first application executed by the one or more processors to perform the method, performing operations comprising: after the first application is opened, entering a first application state comprising a plurality of content item collection indicators displayed on the touch screen display; after entering the first application state, detecting a first touch gesture directed to one content item collection indicator of the plurality of content item collection indicators; wherein each content item collection indicator, of the plurality of content item collection indicators, represents one content item collection, of a plurality of content item collections, under management of the content management system; wherein performance of an earlier touch gesture directed to a graphical representation of a content item, displayed on the touch screen display by a second application of the computing device that is not the first application, causes the first application to open and enter the first application state; after detecting the first touch gesture, assigning a copy of the content item to the content item collection, of the plurality of content item collections, represented by the one content item collection indicator to which the first touch gesture is directed. 5. The method of claim 1 , wherein assigning the copy of the content item comprises storing the copy of the content item in a file system folder of the computing device that is configured for synchronization with the content item collection represented by the one content item collection indicator to which the first touch gesture is directed.

12. The method of claim 11 , further comprising: when a failure of a specific validation element occurs during an execution of the validation sequence, immediately terminating the execution of the validation sequence and determining the XML document to be invalid; when each validation element has been processed and determined to be valid, determining the XML document to be valid; and conveying message detailing validation results for the XML document to an originating party of the XML document.

12. The method of claim 11 , further comprising: when a failure of a specific validation element occurs during an execution of the validation sequence, immediately terminating the execution of the validation sequence and determining the XML document to be invalid; when each validation element has been processed and determined to be valid, determining the XML document to be valid; and conveying message detailing validation results for the XML document to an originating party of the XML document. 14. The method of claim 12 , wherein the at least one processing parameter comprises a document data type, the originating party of the XML document, and an XML version identifier.

9. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, causes the processors to perform operations, the operations comprising: transmitting, to a first information provider, a verbal request for information relating to a location; receiving a digital message from the first information provider in response to the transmitted verbal request, the digital message comprising a symbolic representation of content of the verbal request and an application identifier; launching, based on the application identifier, an application that is determined by the one or more processors to correspond to the application identifier; transmitting, using the application and to a second information provider different than the first information provider, a query that includes the symbolic representation, such that the second information provider generates results responsive to the verbal request.

9. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, causes the processors to perform operations, the operations comprising: transmitting, to a first information provider, a verbal request for information relating to a location; receiving a digital message from the first information provider in response to the transmitted verbal request, the digital message comprising a symbolic representation of content of the verbal request and an application identifier; launching, based on the application identifier, an application that is determined by the one or more processors to correspond to the application identifier; transmitting, using the application and to a second information provider different than the first information provider, a query that includes the symbolic representation, such that the second information provider generates results responsive to the verbal request. 10. The system of claim 9 , wherein the operations further comprise: requesting confirmation from the user that the symbolic representation is accurate.

13. The method as recited in claim 12 , wherein the expert agent communicates with one or more participants in the conversation.

13. The method as recited in claim 12 , wherein the expert agent communicates with one or more participants in the conversation. 14. The method as recited in claim 13 , wherein the expert agent communicates with a participant in the conversation without one or more other participants being aware of the communication.

1. An electronic mail apparatus, comprising: a computing device capable of being connected to a network; and an email productivity module, executed by the computing device, and configured to interact with an existing email application executed by the computing device that sends and receives email messages over the network, wherein the email productivity module includes: a content analysis engine, executed by the computing device, configured to analyze a received email message to generate content information representative of a content of the received email message; a prioritization module, executed by the computing device, having at least one prioritization knowledge base implemented on the computing device, the prioritization module being configured to apply the content information to the at least one prioritization knowledge base to determine at least one priority score for the received email message that reflects a relative priority of the received email message as a legitimate email message and to assign at least one priority level to the received email message based on the priority score that reflects a range of priority scores; a message sorting module, executed by the computing device, having at least one sorting knowledge base implemented on the computing device, the message sorting module being configured to apply the content information to the at least one sorting knowledge base to determine a set of suggested folders for the received email message that represent one or more folders in which are stored other emails having similar content and in which a user would be most likely to store the received email message; and a junkmail module, executed by the computing device, having at least one junkmail knowledge base implemented on the computing device, the junkmail module being configured to apply the content information to the at least one junkmail knowledge base to determine a junkmail score for the received email message that represents a probability that the received email message is junkmail, and the junkmail module being configured to cause a user interface of the existing email application to modify a presentation of the received email message in accordance with the junkmail score; the email productivity module being configured to attach fields for the priority score, priority level, set of suggested folders, and junkmail score to the received email message for display by the existing email application; the email productivity module being configured to receive user feedback to the existing email application indicative of a user action taken with respect to the received email message, and to cause the computing device to adapt the at least one prioritization knowledge base, the at least one sorting database, or the at least one junkmail database, in accordance with the user feedback; wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with explicit user feedback in an event that the user modifies the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display; and wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with implicit user feedback in an event that the user does not modify the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display.

1. An electronic mail apparatus, comprising: a computing device capable of being connected to a network; and an email productivity module, executed by the computing device, and configured to interact with an existing email application executed by the computing device that sends and receives email messages over the network, wherein the email productivity module includes: a content analysis engine, executed by the computing device, configured to analyze a received email message to generate content information representative of a content of the received email message; a prioritization module, executed by the computing device, having at least one prioritization knowledge base implemented on the computing device, the prioritization module being configured to apply the content information to the at least one prioritization knowledge base to determine at least one priority score for the received email message that reflects a relative priority of the received email message as a legitimate email message and to assign at least one priority level to the received email message based on the priority score that reflects a range of priority scores; a message sorting module, executed by the computing device, having at least one sorting knowledge base implemented on the computing device, the message sorting module being configured to apply the content information to the at least one sorting knowledge base to determine a set of suggested folders for the received email message that represent one or more folders in which are stored other emails having similar content and in which a user would be most likely to store the received email message; and a junkmail module, executed by the computing device, having at least one junkmail knowledge base implemented on the computing device, the junkmail module being configured to apply the content information to the at least one junkmail knowledge base to determine a junkmail score for the received email message that represents a probability that the received email message is junkmail, and the junkmail module being configured to cause a user interface of the existing email application to modify a presentation of the received email message in accordance with the junkmail score; the email productivity module being configured to attach fields for the priority score, priority level, set of suggested folders, and junkmail score to the received email message for display by the existing email application; the email productivity module being configured to receive user feedback to the existing email application indicative of a user action taken with respect to the received email message, and to cause the computing device to adapt the at least one prioritization knowledge base, the at least one sorting database, or the at least one junkmail database, in accordance with the user feedback; wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with explicit user feedback in an event that the user modifies the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display; and wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with implicit user feedback in an event that the user does not modify the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display. 16. The apparatus of claim 1 , wherein the junkmail module is further configured to automatically delete the received email message if the junkmail score for the received email message exceeds a predetermined or dynamic threshold.

40. A non-transitory computer readable storage medium for storing one or more programs to be executed by one or more processors of a computer system, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query.

40. A non-transitory computer readable storage medium for storing one or more programs to be executed by one or more processors of a computer system, the one or more programs comprising: instructions for determining a correlation, for each search context of a plurality of search contexts, for each scoring primitive of a plurality of scoring primitives, and for a set of previously executed search queries that are consistent with the search context, between the scoring primitive and actual user selections of results of the previously executed search queries by a plurality of users; instructions for performing machine learning, for each search context, on the correlations to identify a predicted performance function comprising a weighted subset of the scoring primitives that meet predefined predictive quality criteria, wherein the identified predicted performance function is associated with the search context; and instructions for receiving and executing a user submitted search query, submitted by a user, to produce a set of search results, including associating the user submitted search query with a respective search context of the plurality of search contexts, and ordering at least a portion of the search results in accordance with the identified predicted performance function for the search context associated with the user submitted search query. 47. The non-transitory computer readable storage medium of claim 40 , wherein ordering at least a subset of the search results includes evaluating the identified predicted performance function, for each of a plurality of the search results, using one or more parameters of a user profile of the user.

5. The apparatus of claim 1 , wherein, to assign the respective classifications to the topology elements, the processor is configured to: select one of the topology elements from topology element information determined from the topology information; identify, from the set of topology abstraction policies, one of the topology abstraction policies with which the one of the topology elements is associated; and assign the respective classification to the one of the topology elements based on evaluation of one or more policy rules of the one of the topology abstraction policies with which the one of the topology elements is associated.

5. The apparatus of claim 1 , wherein, to assign the respective classifications to the topology elements, the processor is configured to: select one of the topology elements from topology element information determined from the topology information; identify, from the set of topology abstraction policies, one of the topology abstraction policies with which the one of the topology elements is associated; and assign the respective classification to the one of the topology elements based on evaluation of one or more policy rules of the one of the topology abstraction policies with which the one of the topology elements is associated. 6. The apparatus of claim 5 , wherein, to identify the one of the topology abstraction policies with which the one of the topology elements is associated, the processor is configured to: compare topology element description information for the one of the topology elements with respective policy definition information of one or more of the topology abstraction policies.

9. A machine-readable storage device, storing a computer program product, comprising instructions operable to cause a computer to: receive, from an input device connected to the computer, a user input containing a text search string to be identified on a web page loaded in a web browser on the computer, the web page being displayed to the user on a computer display; determine a common substring between the text search string and a hypertext markup language representation of the web page; identify a document object model tree node that includes the common substring; verify that a remainder of the text search string and the common substring is included in one or more surrounding nodes of the document object model tree, wherein the instructions to verify includes instructions to: examine one or more nodes located to the left of the node with the common substring in the document object model tree to match characters left of the common substring in the text search string; and examine one or more nodes located to the right of the node with the common substring in the document object model tree to match characters right of the common substring in the text search string; and display to the user the location of the text search string on the web page.

9. A machine-readable storage device, storing a computer program product, comprising instructions operable to cause a computer to: receive, from an input device connected to the computer, a user input containing a text search string to be identified on a web page loaded in a web browser on the computer, the web page being displayed to the user on a computer display; determine a common substring between the text search string and a hypertext markup language representation of the web page; identify a document object model tree node that includes the common substring; verify that a remainder of the text search string and the common substring is included in one or more surrounding nodes of the document object model tree, wherein the instructions to verify includes instructions to: examine one or more nodes located to the left of the node with the common substring in the document object model tree to match characters left of the common substring in the text search string; and examine one or more nodes located to the right of the node with the common substring in the document object model tree to match characters right of the common substring in the text search string; and display to the user the location of the text search string on the web page. 15. The computer program product of claim 9 , wherein the text search string is a string of alphanumeric characters.

13. A method for performing discovery of digital information in a subject area, comprising: designating through a user interface of a computer a corpus comprising electronically-stored digital information, which are maintained in a storage device; selecting one or more topics and training material for the selected topics comprising on topic information and off topic information; building candidate topic models on the computer comprising: selecting seed words for each of the selected topics; and generating patterns from the seed words for each topic as candidate topic models for that topic; evaluating the candidate topic models for each selected topic against the training material comprising: matching the patterns in each candidate topic model to the training material; rating each candidate topic model for the selected topic comprising: assigning a higher score to each candidate topic model that matches the on topic information for the selected topic; assigning a lower score to each candidate topic model that does not match the on topic information for the selected topic; assigning a higher score to each candidate topic model that does not match the off topic information for the selected topic; and assigning a lower score to each candidate topic model that matches the off topic information for the selected topic; and building an evergreen index comprising topic models for each of the selected topics by pairing each topic to the candidate topic model that has the best overall score.

13. A method for performing discovery of digital information in a subject area, comprising: designating through a user interface of a computer a corpus comprising electronically-stored digital information, which are maintained in a storage device; selecting one or more topics and training material for the selected topics comprising on topic information and off topic information; building candidate topic models on the computer comprising: selecting seed words for each of the selected topics; and generating patterns from the seed words for each topic as candidate topic models for that topic; evaluating the candidate topic models for each selected topic against the training material comprising: matching the patterns in each candidate topic model to the training material; rating each candidate topic model for the selected topic comprising: assigning a higher score to each candidate topic model that matches the on topic information for the selected topic; assigning a lower score to each candidate topic model that does not match the on topic information for the selected topic; assigning a higher score to each candidate topic model that does not match the off topic information for the selected topic; and assigning a lower score to each candidate topic model that matches the off topic information for the selected topic; and building an evergreen index comprising topic models for each of the selected topics by pairing each topic to the candidate topic model that has the best overall score. 24. A method according to claim 13 , further comprising: biasing the candidate topic models for the selected topic that have term overlap with topic labels associated with the selected topic by assigning a higher score to the overlapping candidate topic models.

25. The system of claim 24 wherein the pattern matching system is further configured to: determine a distance between binary average rows for the at least two selected classes of text rows when the correlation value is less than the threshold correlation value; compare the distance to a threshold distance; and group the at least two selected classes of text rows into the first combined class when the distance is less than the threshold distance.

25. The system of claim 24 wherein the pattern matching system is further configured to: determine a distance between binary average rows for the at least two selected classes of text rows when the correlation value is less than the threshold correlation value; compare the distance to a threshold distance; and group the at least two selected classes of text rows into the first combined class when the distance is less than the threshold distance. 27. The system of claim 25 wherein the pattern matching system is further configured to: determine a second correlation value between the corresponding interpolation vector data for a second at least two selected classes of text rows; compare the second correlation value to the threshold correlation value; and group the second at least two selected classes of text rows into a second combined class when the second correlation value is greater than the threshold correlation value.

4. A computer interface, comprising: a digital life form having a plurality of attributes; a plurality of actions which may be accomplished by the digital life form; and a selection criteria for selecting from said plurality of actions; wherein repeated selection of actions which do not contribute to the vitality of the digital life form will result in the simulated death of the digital life form, and said digital life form perceives a plurality of objects in an environment; said objects are identified by the digital life form according to percepts; the percepts are perceived properties of the objects; and said actions are selected to optimize vitality dependant upon the particular objects perceived so as to benefit the digital life form wherein benefit is defined as serving the needs of the digital life form by keeping it alive.

4. A computer interface, comprising: a digital life form having a plurality of attributes; a plurality of actions which may be accomplished by the digital life form; and a selection criteria for selecting from said plurality of actions; wherein repeated selection of actions which do not contribute to the vitality of the digital life form will result in the simulated death of the digital life form, and said digital life form perceives a plurality of objects in an environment; said objects are identified by the digital life form according to percepts; the percepts are perceived properties of the objects; and said actions are selected to optimize vitality dependant upon the particular objects perceived so as to benefit the digital life form wherein benefit is defined as serving the needs of the digital life form by keeping it alive. 5. The computer interface of claim 4 , wherein: said actions are taken to optimize at least one of a plurality of simulated feelings.

1. A method comprising the following computer-executable acts: accessing a data repository in a computing device, wherein the data repository comprises a plurality of queries issued by users of a search engine and sets of search results selected by issuers of respective queries in the plurality of queries; determining, for each query in the plurality of queries, a click distribution over a respective set of search results for a respective query; determining measures of similarity between queries in the plurality of queries based at least in part upon click distributions over the sets of search results for each of the respective queries, wherein a measure of similarity between a first query and a second query is a cosine similarity of click distributions over respective sets of search results for the first query and the second query, the measure of similarity computed as a function of: a first probability that a first searcher that issued the first query will select a first search result; and a second probability that a second searcher that issued the second query will select the first search result, wherein the first probability and the second probability are computed based at least in part upon the click distributions over the sets of search results for each of the respective queries; from amongst unclustered queries in the plurality of queries, selecting a query that is most often submitted to the search engine as a seed query; executing a clustering algorithm over the unclustered queries in the plurality of queries utilizing the seed query, wherein queries from the unclustered queries are placed into a cluster with the seed query if measures of similarity between the seed query and respective unclustered queries are above a threshold; labeling queries in the cluster as being similar queries; and repeating acts of selecting, executing, and labeling until there are no unclustered queries.

1. A method comprising the following computer-executable acts: accessing a data repository in a computing device, wherein the data repository comprises a plurality of queries issued by users of a search engine and sets of search results selected by issuers of respective queries in the plurality of queries; determining, for each query in the plurality of queries, a click distribution over a respective set of search results for a respective query; determining measures of similarity between queries in the plurality of queries based at least in part upon click distributions over the sets of search results for each of the respective queries, wherein a measure of similarity between a first query and a second query is a cosine similarity of click distributions over respective sets of search results for the first query and the second query, the measure of similarity computed as a function of: a first probability that a first searcher that issued the first query will select a first search result; and a second probability that a second searcher that issued the second query will select the first search result, wherein the first probability and the second probability are computed based at least in part upon the click distributions over the sets of search results for each of the respective queries; from amongst unclustered queries in the plurality of queries, selecting a query that is most often submitted to the search engine as a seed query; executing a clustering algorithm over the unclustered queries in the plurality of queries utilizing the seed query, wherein queries from the unclustered queries are placed into a cluster with the seed query if measures of similarity between the seed query and respective unclustered queries are above a threshold; labeling queries in the cluster as being similar queries; and repeating acts of selecting, executing, and labeling until there are no unclustered queries. 11. The method of claim 1 , further comprising: receiving a third query from a user; determining that the third query is included in the cluster of queries; and automatically executing a search utilizing another query from the cluster of queries responsive to receiving the third query from the user.

17. The computer program product of claim 13 , where the plurality of applications are associated with the file type by rules in a set of selection rules defining conditions for selecting an application to be used to open files.

17. The computer program product of claim 13 , where the plurality of applications are associated with the file type by rules in a set of selection rules defining conditions for selecting an application to be used to open files. 18. The computer program product of claim 17 , where the selection rules include one or more of user-defined preferences associating applications with file types or administrator preferences applicable to all users of the computing environment.

1. A method of controlling a group chat, the method comprising: controlling, by a controller, a display unit to display a group chatting window for the group chat, if a request of a user of a portable device for the group chat is detected through an input unit; detecting, by the controller, a request for an extraction of a dialog for at least one certain conversation partner of conversation partners in the group chat; if the request for the extraction of the dialog is detected, extracting, by the controller, the dialog of the at least one certain conversation partner from one or more dialogs in the group chat; and controlling, by the controller, the display unit to display the extracted dialog on a sub-chatting window, wherein the controller extracts automatically the dialog of the at least one certain conversation partner during the group chatting, and controls the display unit to display the dialog on the sub-chatting window.

1. A method of controlling a group chat, the method comprising: controlling, by a controller, a display unit to display a group chatting window for the group chat, if a request of a user of a portable device for the group chat is detected through an input unit; detecting, by the controller, a request for an extraction of a dialog for at least one certain conversation partner of conversation partners in the group chat; if the request for the extraction of the dialog is detected, extracting, by the controller, the dialog of the at least one certain conversation partner from one or more dialogs in the group chat; and controlling, by the controller, the display unit to display the extracted dialog on a sub-chatting window, wherein the controller extracts automatically the dialog of the at least one certain conversation partner during the group chatting, and controls the display unit to display the dialog on the sub-chatting window. 9. The method of claim 1 , further comprising: selecting a certain conversation partner to be added if a request for an addition of the certain conversation partner is detected; extracting a dialog of the certain conversation partner to be added; and displaying the extracted dialog of the certain conversation partner to be added on the sub-chatting window.

8. The content delivery system as recited in claim 3 , further comprising: a repeater selector mechanism.

8. The content delivery system as recited in claim 3 , further comprising: a repeater selector mechanism. 9. The content delivery system as recited in claim 8 , wherein the reflector comprises the repeater selector mechanism.

10. The computer system of claim 9 , further comprising: program instructions to display, separately from any other search results, the set of results from the search of the compound search query.

10. The computer system of claim 9 , further comprising: program instructions to display, separately from any other search results, the set of results from the search of the compound search query. 11. The computer system of claim 10 , further comprising: program instructions to display the set of results received from performing the search using the compound search query in a browser tab; and program instructions to display each set of results received from performing the search for each sub-query in separate browser tabs.

65. The computer program product according to claim 40 , further comprising: computer code for receiving over a network a structured reply to the structured response from one or more members of business management.

65. The computer program product according to claim 40 , further comprising: computer code for receiving over a network a structured reply to the structured response from one or more members of business management. 70. The computer program product according to claim 65 , further comprising computer code for routing a new template to the user requesting more information about the user suggestion in response to the structured reply.

4. The method of claim 1 , wherein: the word lattice includes a beginning lattice node, an ending lattice node, and one or more node paths located between the beginning lattice node and the ending lattice node; and the calculating an optimal character sequence in the word lattice includes: for each node path of the one or more node paths, setting a token on the node path between the beginning lattice node and the ending lattice node; moving the token from the beginning lattice node to the ending lattice node along the node path; and calculating a token score of the token based on at least information associated with one or more node scores related to one or more lattice nodes on the node path and a probability related to a predetermined language model; selecting a final token with a highest token score; and selecting a combination of final candidate characters corresponding to one or more final lattice nodes on a final node path related to the final token as the optimal character sequence.

4. The method of claim 1 , wherein: the word lattice includes a beginning lattice node, an ending lattice node, and one or more node paths located between the beginning lattice node and the ending lattice node; and the calculating an optimal character sequence in the word lattice includes: for each node path of the one or more node paths, setting a token on the node path between the beginning lattice node and the ending lattice node; moving the token from the beginning lattice node to the ending lattice node along the node path; and calculating a token score of the token based on at least information associated with one or more node scores related to one or more lattice nodes on the node path and a probability related to a predetermined language model; selecting a final token with a highest token score; and selecting a combination of final candidate characters corresponding to one or more final lattice nodes on a final node path related to the final token as the optimal character sequence. 5. The method of claim 4 , wherein the calculating a token score of the token based on at least information associated with one or more node scores related to one or more lattice nodes on the node path and a probability related to a predetermined language model includes: calculating the token score of the token based on at least information associated with a current node score related to a current lattice node and the probability of the predetermined language model; detecting whether the token score is smaller than a predetermined threshold; and in response to the token score being no smaller than the predetermined threshold, moving the token to a next lattice node; and repeating the calculating the token score of the token based on at least information associated with a current node score related to a current lattice node and the probability of the predetermined language model, and the detecting whether the token score is smaller than a predetermined threshold.

17. A computer program product for generating an object oriented application for an object oriented environment, said object oriented environment comprising a programming model and a data model, said computer program product comprising: a computer readable storage medium having computer readable code means embodied in said medium, said computer readable code means comprising: computer instruction means for generating a computer program design for said object oriented model application using a modeling tool; and computer instruction means for mapping the modeling tool generated computer program design to the data model of said object oriented environment to thereby create metadata in said data model wherein said computer instruction means for mapping comprises computer instruction means for defining a first package, wherein said first package partitions the computer program design into at least two parts without requiring reference to model semantics.

17. A computer program product for generating an object oriented application for an object oriented environment, said object oriented environment comprising a programming model and a data model, said computer program product comprising: a computer readable storage medium having computer readable code means embodied in said medium, said computer readable code means comprising: computer instruction means for generating a computer program design for said object oriented model application using a modeling tool; and computer instruction means for mapping the modeling tool generated computer program design to the data model of said object oriented environment to thereby create metadata in said data model wherein said computer instruction means for mapping comprises computer instruction means for defining a first package, wherein said first package partitions the computer program design into at least two parts without requiring reference to model semantics. 36. The computer program product for generating according to claim 17, wherein said computer readable program code means for mapping comprises: computer readable program code means for identifying a class specification, said class specification comprising at least one class, relationships between the at least one class and at least a second class, an inheritance associated with the at least one class, at least one attribute associated with the at least one class and at least one method associated with the at least one class, said class specification being identified by a class name; and computer readable program code means for mapping the class specification to an interface in the data model in the object oriented environment.

1. A method comprising: logging actions taken by users of a social networking system; determining one or more story generators based on a view requested by a client device of a viewing user of the social networking system; accessing a plurality of logged actions of the viewing user or one or more other users connected to the viewing user in the social networking system; selecting one or more of the logged actions based on a relevance of each of the logged actions to the viewing user; generating a plurality of candidate stories from the logged actions using the one or more story generators, each of the plurality of candidate stories being associated with a story type of a plurality of story types, where two or more candidate stories of the plurality of candidate stories are associated with a same logged action; generating an affinity for each of the plurality of candidate stories, wherein each affinity comprises a measure of the relevance of a candidate story of the plurality of candidate stories to the viewing user; generating a ranking of the plurality of candidate stories based on the affinity generated for each the plurality of stories; identifying the two or more candidate stories that are associated with the same logged action; responsive to the identifying, updating the ranking by removing a subset of the two or more candidate stories from the ranking; selecting one or more of the plurality of candidate stories as selected stories for the view requested by the client device of the viewing user based on the updated ranking; and sending the requested view comprising displayable representations of the selected stories to the client device for display to the viewing user.

1. A method comprising: logging actions taken by users of a social networking system; determining one or more story generators based on a view requested by a client device of a viewing user of the social networking system; accessing a plurality of logged actions of the viewing user or one or more other users connected to the viewing user in the social networking system; selecting one or more of the logged actions based on a relevance of each of the logged actions to the viewing user; generating a plurality of candidate stories from the logged actions using the one or more story generators, each of the plurality of candidate stories being associated with a story type of a plurality of story types, where two or more candidate stories of the plurality of candidate stories are associated with a same logged action; generating an affinity for each of the plurality of candidate stories, wherein each affinity comprises a measure of the relevance of a candidate story of the plurality of candidate stories to the viewing user; generating a ranking of the plurality of candidate stories based on the affinity generated for each the plurality of stories; identifying the two or more candidate stories that are associated with the same logged action; responsive to the identifying, updating the ranking by removing a subset of the two or more candidate stories from the ranking; selecting one or more of the plurality of candidate stories as selected stories for the view requested by the client device of the viewing user based on the updated ranking; and sending the requested view comprising displayable representations of the selected stories to the client device for display to the viewing user. 3. The method of claim 1 , wherein updating the ranking further comprises: removing candidate stories associated with logged actions previously viewed by the viewing user.

12. The document viewing device according to claim 11 , wherein said document data includes information specifying a prescribed object of said document data, in the process of determining whether the relevant page searched is checked or unchecked, the processing device determines whether the object included in the relevant page searched is checked or unchecked, and extracts the relevant page searched whose object is determined to be unchecked, and in said process of extracting the page for which it is determined that the object is unchecked, said processing device determines based on said viewing history based on said audio input received by said input device whether each said prescribed object is checked or unchecked by said user.

12. The document viewing device according to claim 11 , wherein said document data includes information specifying a prescribed object of said document data, in the process of determining whether the relevant page searched is checked or unchecked, the processing device determines whether the object included in the relevant page searched is checked or unchecked, and extracts the relevant page searched whose object is determined to be unchecked, and in said process of extracting the page for which it is determined that the object is unchecked, said processing device determines based on said viewing history based on said audio input received by said input device whether each said prescribed object is checked or unchecked by said user. 14. The document viewing device according to claim 12 , wherein in said process of generating the viewing history, said processing device records display time as said viewing history for each page displayed on said display device, and in said process of extracting the page for which it is determined that the object is unchecked, said processing device compares said display time with reference time stored in advance for each page of said document, to determine for each said page whether the object is checked or unchecked by said user, and extract the page that includes said prescribed object determined as being unchecked and is determined as being unchecked by said user from pages each searched for as being relevant to the object displayed on said display device.

6. The method according to claim 5 including: receiving a second group of queries that cannot be matched with the identified most frequently queried intent categories; using a natural language engine and the one or more ontologies to identify concepts in the second group of non-matching queries; comparing the identified concepts for the second group of queries with natural language words or phrases for other intent categories; and providing predetermined responses to any of the second group of queries matching any of the other intent categories.

6. The method according to claim 5 including: receiving a second group of queries that cannot be matched with the identified most frequently queried intent categories; using a natural language engine and the one or more ontologies to identify concepts in the second group of non-matching queries; comparing the identified concepts for the second group of queries with natural language words or phrases for other intent categories; and providing predetermined responses to any of the second group of queries matching any of the other intent categories. 7. The method according to claim 6 including: receiving a third group of queries that cannot be matched with any of the identified most frequently queried intent categories and cannot be matched with the concepts in the ontologies; identifying keywords in the third group of queries; and using the identified keywords to search for responses associated with the third group of queries.

11. The system according to claim 10 , wherein the automatically adjusting further comprises determining whether the insertion point is within the spatial region based on evaluation of the gravity parameter.

11. The system according to claim 10 , wherein the automatically adjusting further comprises determining whether the insertion point is within the spatial region based on evaluation of the gravity parameter. 12. The system according to claim 11 , wherein the automatically adjusting aligns the insertion point with at least one portion of existing content in response to determining that the insertion point is outside of the spatial region.

16. Non-transitory computer-readable storage comprising executable code that, when executed, causes one or more computing devices to perform a process comprising: obtaining from a client device: audio input, wherein less than all of the audio input comprises audio data likely corresponding to a keyword; contextual information associated with the audio input; and information indicating a portion of audio input, of a plurality of portions of the audio input, that likely corresponds to the keyword; obtaining acoustic information and environmental information from the portion of the audio input; determining that audio data corresponding to the keyword is present in the audio input using a detection model configured to generate a detection score using the audio input, the contextual information, the environmental information, and the acoustic information, wherein a detection score satisfying a detection threshold indicates audio data corresponding to the keyword is present in the audio input; and performing an action corresponding to a request in the audio input.

16. Non-transitory computer-readable storage comprising executable code that, when executed, causes one or more computing devices to perform a process comprising: obtaining from a client device: audio input, wherein less than all of the audio input comprises audio data likely corresponding to a keyword; contextual information associated with the audio input; and information indicating a portion of audio input, of a plurality of portions of the audio input, that likely corresponds to the keyword; obtaining acoustic information and environmental information from the portion of the audio input; determining that audio data corresponding to the keyword is present in the audio input using a detection model configured to generate a detection score using the audio input, the contextual information, the environmental information, and the acoustic information, wherein a detection score satisfying a detection threshold indicates audio data corresponding to the keyword is present in the audio input; and performing an action corresponding to a request in the audio input. 18. The non-transitory computer-readable storage of claim 16 , wherein the acoustic information comprises natural language understanding results generated using the audio input.

10. The method of claim 7 , further comprising: identifying one or more common attributes associated with the subset of documents; and outputting the common attributes to a user.

10. The method of claim 7 , further comprising: identifying one or more common attributes associated with the subset of documents; and outputting the common attributes to a user. 12. The method of claim 10 , wherein the attributes are identified in response to a user request regarding a query topic.

1. A method of measuring the quality of speech communicated using packets, the method comprising: operating a plurality of N independent neural networks, each neural network processing one of N separate sets of speech signal feature measurements corresponding to a speech signal recovered from packets communicated via a communications network to generate from the processed set of speech signal feature measurements a signal feature quality score, each of the N different neural networks corresponding to a different one of the N sets of speech signal feature measurements, said N neural networks generating N signal feature quality scores, each one of the N signal feature quality scores corresponding to a different one of N speech signal features; operating a joint quality score determination neural network to generate a joint signal feature quality score from said N signal feature quality scores; adjusting said joint quality score based on packet loss information and codec type to generate a final overall quality score for said recovered speech signal wherein different types of codecs correspond to different packet loss robustness factors; and wherein said N sets of separate speech signal feature measurements include at least two sets of speech signal measurements from a group of sets of speech signal feature measurements including: a set of signal to noise ratio measurements, a set of spectral clarity measurements, a set of linear prediction skew measurements, a set of linear prediction kurtosis measurements and a set of pitch average measurements.

1. A method of measuring the quality of speech communicated using packets, the method comprising: operating a plurality of N independent neural networks, each neural network processing one of N separate sets of speech signal feature measurements corresponding to a speech signal recovered from packets communicated via a communications network to generate from the processed set of speech signal feature measurements a signal feature quality score, each of the N different neural networks corresponding to a different one of the N sets of speech signal feature measurements, said N neural networks generating N signal feature quality scores, each one of the N signal feature quality scores corresponding to a different one of N speech signal features; operating a joint quality score determination neural network to generate a joint signal feature quality score from said N signal feature quality scores; adjusting said joint quality score based on packet loss information and codec type to generate a final overall quality score for said recovered speech signal wherein different types of codecs correspond to different packet loss robustness factors; and wherein said N sets of separate speech signal feature measurements include at least two sets of speech signal measurements from a group of sets of speech signal feature measurements including: a set of signal to noise ratio measurements, a set of spectral clarity measurements, a set of linear prediction skew measurements, a set of linear prediction kurtosis measurements and a set of pitch average measurements. 6. The method of claim 1 , wherein said packet loss information includes an estimate of a number of packets lost in the communication of said speech signal via said communications network; and wherein said packet loss information includes packet loss location information.

6. A method for recognizing an utterance comprising: receiving an utterance comprising a plurality of modes; relating a first portion of the utterance comprising a first mode of the plurality of modes to a second portion of the utterance comprising a second mode of the plurality of modes, based on a first finite-state transducer; generating a second finite-state transducer, comprising a gesture and speech recognition model finite-state transducer, based on a first mode recognition lattice and the first finite-state transducer; and outputting a recognition result based on the utterance and the second finite-state transducer.

6. A method for recognizing an utterance comprising: receiving an utterance comprising a plurality of modes; relating a first portion of the utterance comprising a first mode of the plurality of modes to a second portion of the utterance comprising a second mode of the plurality of modes, based on a first finite-state transducer; generating a second finite-state transducer, comprising a gesture and speech recognition model finite-state transducer, based on a first mode recognition lattice and the first finite-state transducer; and outputting a recognition result based on the utterance and the second finite-state transducer. 9. The method of claim 6 wherein the first mode is a gesture mode.

19. A system comprising: memory; one or more processors coupled to the memory and configured to perform operations comprising: ranking indexed queries based on a respective query rank of each indexed query, the query rank calculated based on a frequency of occurrence of the indexed query and a user satisfaction score of the indexed query, the indexed queries including highly-ranked queries and nearby queries that are queries that have a statistically significant probability of being revised to one of the highly-ranked queries, wherein the user satisfaction score of a particular indexed query is determined from estimates of lengths of clicks on search results, wherein the estimates of the lengths of clicks on search results are based on a duration of time from a selection of a search result for the particular indexed query to a subsequent selection of another search result; calculating a respective revision score for each indexed query as a function of a revision probability of a first query and the respective query rank for the particular indexed query, the revision probability based on at least one of a semantic similarity or syntactic similarity between the first query and the particular indexed query; selecting one of the indexed queries as an alternative query to the first query based on the respective revision score of the selected indexed query; and providing the selected query as a suggested revision for the first query.

19. A system comprising: memory; one or more processors coupled to the memory and configured to perform operations comprising: ranking indexed queries based on a respective query rank of each indexed query, the query rank calculated based on a frequency of occurrence of the indexed query and a user satisfaction score of the indexed query, the indexed queries including highly-ranked queries and nearby queries that are queries that have a statistically significant probability of being revised to one of the highly-ranked queries, wherein the user satisfaction score of a particular indexed query is determined from estimates of lengths of clicks on search results, wherein the estimates of the lengths of clicks on search results are based on a duration of time from a selection of a search result for the particular indexed query to a subsequent selection of another search result; calculating a respective revision score for each indexed query as a function of a revision probability of a first query and the respective query rank for the particular indexed query, the revision probability based on at least one of a semantic similarity or syntactic similarity between the first query and the particular indexed query; selecting one of the indexed queries as an alternative query to the first query based on the respective revision score of the selected indexed query; and providing the selected query as a suggested revision for the first query. 27. The system of claim 19 , in which the suggested revision is displayed to a user in a location dependent upon a relative strength of a confidence measure associated with the alternative revision.

3. The method of claim 2 , wherein said first entity is a manufacturer and said second entity is a distributor.

3. The method of claim 2 , wherein said first entity is a manufacturer and said second entity is a distributor. 13. The method of claim 3 , wherein said distributor is one of a plurality of distributors.

1. A method of tuning a database query, comprising: allowing a user to select a query of a database; parsing the selected database query to determine that the database query includes a first operator; selecting an optimization mode from a plurality of available optimization modes, wherein: a first optimization mode is automatically selected if one or more statistics exist for a table identified by the database query, and a second optimization mode is selected if one or more statistics do not exist for the table identified by the database query; tuning automatically the selected database query based on the structure of the database and the selected optimization mode; and displaying the tuned database query, and wherein automatically tuning the selected database query comprises automatically rewriting the selected database query by converting the first operator to a second operator.

1. A method of tuning a database query, comprising: allowing a user to select a query of a database; parsing the selected database query to determine that the database query includes a first operator; selecting an optimization mode from a plurality of available optimization modes, wherein: a first optimization mode is automatically selected if one or more statistics exist for a table identified by the database query, and a second optimization mode is selected if one or more statistics do not exist for the table identified by the database query; tuning automatically the selected database query based on the structure of the database and the selected optimization mode; and displaying the tuned database query, and wherein automatically tuning the selected database query comprises automatically rewriting the selected database query by converting the first operator to a second operator. 11. The method of claim 1 , further comprising displaying a primary key for each table referenced in the selected database query.

1. A method of operating a mobile communication device, said method comprising: over a wireless messaging channel receiving a text message, wherein the text message contains a non-text representation of an utterance; extracting the non-text representation from the text message; synthesizing an audio representation of the spoken utterance from the non-text representation; and playing the synthesized audio representation through an audio output device on the mobile communication device.

1. A method of operating a mobile communication device, said method comprising: over a wireless messaging channel receiving a text message, wherein the text message contains a non-text representation of an utterance; extracting the non-text representation from the text message; synthesizing an audio representation of the spoken utterance from the non-text representation; and playing the synthesized audio representation through an audio output device on the mobile communication device. 7. The method of claim 1 , wherein the received text message includes an indicator identifying the text message as containing a non-text representation of the utterance.

2. The method of claim 1 , further comprising weighting the learned content preferences of the user according to at least one of a measure of recency of selection of the content item having the analyzed descriptive terms, number of selections of the content item having the analyzed descriptive terms, and time of use of the content item having the analyzed descriptive terms, wherein the act of selecting and ordering the collection of content items is further based on the weighted learned content preferences so that content items associated with descriptive terms comparable to the learned content preferences having relatively higher weights are ranked relatively more highly.

2. The method of claim 1 , further comprising weighting the learned content preferences of the user according to at least one of a measure of recency of selection of the content item having the analyzed descriptive terms, number of selections of the content item having the analyzed descriptive terms, and time of use of the content item having the analyzed descriptive terms, wherein the act of selecting and ordering the collection of content items is further based on the weighted learned content preferences so that content items associated with descriptive terms comparable to the learned content preferences having relatively higher weights are ranked relatively more highly. 5. The method of claim 2 , wherein the weights of the learned content preferences are decayed based upon the number of user selections occurring after the act of learning the content preferences of the user.

13. An apparatus comprising: a set of one or more processing units; and a deployment modeling language tool unit operable to, create a model, wherein the model comprises one or more associated profiles; read a stereotype of a first profile, wherein the stereotype defines constraints to be applied to the model associated with the first profile; determine that the stereotype indicates a second profile and a third profile; access the second profile and the third profile; and aggregate a plurality of constraints from across the second and the third profiles for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language and wherein said aggregating comprises writing references to the plurality of constraints into a definition of the stereotype of the first profile.

13. An apparatus comprising: a set of one or more processing units; and a deployment modeling language tool unit operable to, create a model, wherein the model comprises one or more associated profiles; read a stereotype of a first profile, wherein the stereotype defines constraints to be applied to the model associated with the first profile; determine that the stereotype indicates a second profile and a third profile; access the second profile and the third profile; and aggregate a plurality of constraints from across the second and the third profiles for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language and wherein said aggregating comprises writing references to the plurality of constraints into a definition of the stereotype of the first profile. 16. The method of claim 13 , wherein the deployment modeling language tool unit is further operable to aggregate attributes from across the second profile and the third profile for use as attributes for the stereotype of the first profile.

14. A system for memory conserving versioning of an electronic document, comprising: one or more processors for executing programmed instructions; memory, coupled to the one or more processors, for storing program instruction steps for execution by the computer processor; and a server memory conserving versioning engine comprising: a server document synchronizer operative to receive a client-generated update request including client edits to the electronic document; and a server memory conserving versioning analyzer that analyzes a plurality of server memory conserving versioning factors for determining whether to save the client edits as a new version of the electronic document, and that generates a derived value based on the server memory conserving versioning factors and generates a versioning score based on the derived value and the client edits, and compares the versioning score to a threshold versioning score wherein at least one of the plurality of server memory conserving versioning factors is based on an amount of storage available to a particular client user or group of client users and at least one of the plurality of server memory conserving versioning factors is based on a difficulty level of reproducing the client edits; and a server document versioner operative to: in response to the versioning score begin less than the threshold versioning score: generate a new version identifier for the electronic document; and save the client edits to a storage repository using the new version identifier; and in response to the versioning score meeting or exceeding the threshold versioning score, save the client edits to a current version of the electronic document.

14. A system for memory conserving versioning of an electronic document, comprising: one or more processors for executing programmed instructions; memory, coupled to the one or more processors, for storing program instruction steps for execution by the computer processor; and a server memory conserving versioning engine comprising: a server document synchronizer operative to receive a client-generated update request including client edits to the electronic document; and a server memory conserving versioning analyzer that analyzes a plurality of server memory conserving versioning factors for determining whether to save the client edits as a new version of the electronic document, and that generates a derived value based on the server memory conserving versioning factors and generates a versioning score based on the derived value and the client edits, and compares the versioning score to a threshold versioning score wherein at least one of the plurality of server memory conserving versioning factors is based on an amount of storage available to a particular client user or group of client users and at least one of the plurality of server memory conserving versioning factors is based on a difficulty level of reproducing the client edits; and a server document versioner operative to: in response to the versioning score begin less than the threshold versioning score: generate a new version identifier for the electronic document; and save the client edits to a storage repository using the new version identifier; and in response to the versioning score meeting or exceeding the threshold versioning score, save the client edits to a current version of the electronic document. 15. The system of claim 14 , wherein the client-generated update request includes a client request to save the client edits as a new version of the electronic document.

34. The computer-readable medium as recited in claim 26 , wherein the process further comprises assembling parts of the structured electronic document and storing the structured electronic document in a memory according to a predetermined structured format.

34. The computer-readable medium as recited in claim 26 , wherein the process further comprises assembling parts of the structured electronic document and storing the structured electronic document in a memory according to a predetermined structured format. 36. The computer-readable medium as recited in claim 34 , wherein the structured format is a format utilized by a judicial court.

1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct.

1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct. 2. A method as in claim 1 , further comprising defining a feature function that indicates when to use the at least two translation components.

7. A display-building system embodied on computer-readable storage media, the display-building system comprising: a predictive component that determines a plurality of potential topics of interest based on a log of interactions with a plurality of web sites and a probabilistic model providing degree of interest in information on the plurality of web sites, the predictive component employing a collaborative model constructed from logs of web site access patterns of a plurality of users to determine the plurality of potential topics of interest to a particular user, the plurality of users belonging to a group or association to which the particular user also belongs; an information retrieval component that dynamically selects and retrieves at least a portion of content relevant to the topics of interest from two or more of the web sites, selection is based at least in part on an expected utility determined in part from the degree of interest, and a current context; and a formatting component that aggregates and displays the retrieved portion as a singular collection of information based on a utility model, the display comprises topic-centric segmentation of information of the retrieved portion as provided by the utility model based on a navigation savings of segmented information in conjunction with the current context, the formatting component approximating a value of a web page to the particular user according to a function f, f being a function of I and S such that the value of the web page is equal to: f(I(p), S(p)), where I(p) is defined as a computed interest I of a page p, and S(p) is defined as a computed savings S in navigation derived from the aggregation and display, the function f being one of: a multiplicative model; a weighted multiplicative model; or a weighted additive multiplicative model.

7. A display-building system embodied on computer-readable storage media, the display-building system comprising: a predictive component that determines a plurality of potential topics of interest based on a log of interactions with a plurality of web sites and a probabilistic model providing degree of interest in information on the plurality of web sites, the predictive component employing a collaborative model constructed from logs of web site access patterns of a plurality of users to determine the plurality of potential topics of interest to a particular user, the plurality of users belonging to a group or association to which the particular user also belongs; an information retrieval component that dynamically selects and retrieves at least a portion of content relevant to the topics of interest from two or more of the web sites, selection is based at least in part on an expected utility determined in part from the degree of interest, and a current context; and a formatting component that aggregates and displays the retrieved portion as a singular collection of information based on a utility model, the display comprises topic-centric segmentation of information of the retrieved portion as provided by the utility model based on a navigation savings of segmented information in conjunction with the current context, the formatting component approximating a value of a web page to the particular user according to a function f, f being a function of I and S such that the value of the web page is equal to: f(I(p), S(p)), where I(p) is defined as a computed interest I of a page p, and S(p) is defined as a computed savings S in navigation derived from the aggregation and display, the function f being one of: a multiplicative model; a weighted multiplicative model; or a weighted additive multiplicative model. 11. The display-building system of claim 7 , wherein the formatting component formats a display by increasing expected utility, subject to a size of the display and a relation of the size and an amount of embedded content placed in a montage.

21. A non-transitory computer-readable medium storing instructions which, when executed by at least one processor, performs a method, the method comprising: opening a web page on a browser in response to a user selection of a link, wherein the web page includes visible content; automatically parsing the web page; obtaining at least one keyword from the parsing; generating a first query from the at least one keyword; generating a plurality of domain name suggestions based at least on the first query; determining a plurality of domain traffic scores for the plurality of domain name suggestions; providing ranked domain name suggestions that includes one or more of the plurality of domain name suggestions ranked based on the plurality of domain traffic scores associated with the plurality of domain name suggestions; displaying the ranked domain name suggestions; receiving a user-highlighted portion of the visible content of the web page displayed during the parsing; refining the first query with one or more keywords derived from the user-highlighted portion of the visible content to generate a second query, wherein the user-highlighted portion of the visible content comprises at least one of a title of the web page, text in the web page, an image in the web page, or an advertisement in the web page; generating one or more domain name suggestions based on the second query; and providing the one or more domain name suggestions.

21. A non-transitory computer-readable medium storing instructions which, when executed by at least one processor, performs a method, the method comprising: opening a web page on a browser in response to a user selection of a link, wherein the web page includes visible content; automatically parsing the web page; obtaining at least one keyword from the parsing; generating a first query from the at least one keyword; generating a plurality of domain name suggestions based at least on the first query; determining a plurality of domain traffic scores for the plurality of domain name suggestions; providing ranked domain name suggestions that includes one or more of the plurality of domain name suggestions ranked based on the plurality of domain traffic scores associated with the plurality of domain name suggestions; displaying the ranked domain name suggestions; receiving a user-highlighted portion of the visible content of the web page displayed during the parsing; refining the first query with one or more keywords derived from the user-highlighted portion of the visible content to generate a second query, wherein the user-highlighted portion of the visible content comprises at least one of a title of the web page, text in the web page, an image in the web page, or an advertisement in the web page; generating one or more domain name suggestions based on the second query; and providing the one or more domain name suggestions. 28. The computer-readable medium of claim 21 , the method further comprising using at least one of a geographical location, contents of a search history, an IP address, or other relevant information to generate the at least one domain name suggestion.

10. The system of claim 8 , wherein the first and second textual distances each comprise a sum of values corresponding to intermediary textual elements between the text portion of the document corresponding to the first parameter and the text portions of the document corresponding to the second and third parameters.

10. The system of claim 8 , wherein the first and second textual distances each comprise a sum of values corresponding to intermediary textual elements between the text portion of the document corresponding to the first parameter and the text portions of the document corresponding to the second and third parameters. 11. The system of claim 10 , wherein the intermediary textual elements include at least one word having a first corresponding value in the sum of values and at least one textual element other than a word having a second corresponding value in the sum of values, the second corresponding value being distinct from the first corresponding value.

10. A computer-readable storage media having computer-executable instructions that when executed on a computer via a microprocessor perform a method comprising: generating a tuning set from a set of provided correct ink samples of words, the tuning set comprising at least some in-dictionary words and a number of out-of-dictionary words, the number of out-of-dictionary words determined by a percentage of out-of-dictionary words expected for a typical user; running a handwriting recognizer against the tuning set to determine a set of statistics for a plurality of words in the tuning set, the set of statistics based at least in part upon a probability that a word from the tuning set matches a correct answer; and calculating a balancing factor based on the set of statistics for use in comparing an in-dictionary recognition score with an out-of-dictionary recognition score in a recognition operation, comprising one of: selecting a value for the balancing factor that is less than a resulting quotient of a probability of an in-dictionary tuning word being correct divided by a probability of an out-of-dictionary turning word being correct, if the in-dictionary tuning word is correct and the out-of-dictionary tuning word is not correct; and selecting a value for the balancing factor that is greater than a resulting quotient of the probability of the in-dictionary tuning word being correct divided by the probability of the out-of-dictionary tuning word being correct, if the in-dictionary tuning word is not correct and the out-of-dictionary tuning word is correct.

10. A computer-readable storage media having computer-executable instructions that when executed on a computer via a microprocessor perform a method comprising: generating a tuning set from a set of provided correct ink samples of words, the tuning set comprising at least some in-dictionary words and a number of out-of-dictionary words, the number of out-of-dictionary words determined by a percentage of out-of-dictionary words expected for a typical user; running a handwriting recognizer against the tuning set to determine a set of statistics for a plurality of words in the tuning set, the set of statistics based at least in part upon a probability that a word from the tuning set matches a correct answer; and calculating a balancing factor based on the set of statistics for use in comparing an in-dictionary recognition score with an out-of-dictionary recognition score in a recognition operation, comprising one of: selecting a value for the balancing factor that is less than a resulting quotient of a probability of an in-dictionary tuning word being correct divided by a probability of an out-of-dictionary turning word being correct, if the in-dictionary tuning word is correct and the out-of-dictionary tuning word is not correct; and selecting a value for the balancing factor that is greater than a resulting quotient of the probability of the in-dictionary tuning word being correct divided by the probability of the out-of-dictionary tuning word being correct, if the in-dictionary tuning word is not correct and the out-of-dictionary tuning word is correct. 11. The computer-readable media of claim 10 , the method comprising generating the tuning set randomly.

13. A speech recognition system comprising: a controller; a gesture detector coupled to provide signals to the controller, the signals corresponding to a gesture; a speech recognizer having access to a plurality of recognition sets, the speech recognizer coupled to provide recognition results to the controller; an audio user interface coupled to receive a speech input and coupled to provide audio signals to the speech recognizer, the audio signals corresponding to the speech input; and a plurality of output devices coupled to the controller, wherein a recognition set is selected from the plurality of recognition sets based on the gesture, wherein the recognition results are generated based on the speech input and the selected recognition set, wherein each recognition set in the plurality of recognition sets is associated with an output device in the plurality of output devices, and wherein the controller provides signals to the output device associated with the selected recognition set, the signals corresponding to the recognition results.

13. A speech recognition system comprising: a controller; a gesture detector coupled to provide signals to the controller, the signals corresponding to a gesture; a speech recognizer having access to a plurality of recognition sets, the speech recognizer coupled to provide recognition results to the controller; an audio user interface coupled to receive a speech input and coupled to provide audio signals to the speech recognizer, the audio signals corresponding to the speech input; and a plurality of output devices coupled to the controller, wherein a recognition set is selected from the plurality of recognition sets based on the gesture, wherein the recognition results are generated based on the speech input and the selected recognition set, wherein each recognition set in the plurality of recognition sets is associated with an output device in the plurality of output devices, and wherein the controller provides signals to the output device associated with the selected recognition set, the signals corresponding to the recognition results. 16. The system of claim 13 wherein at least one of the output devices of the plurality of output devices is a speech synthesizer that provides a verbal prompt corresponding to the gesture.

20. A method for processing natural language queries, the method comprising: receiving two or more natural language libraries from service providers via a network, the two or more natural language libraries comprising a customized natural language library, the customized natural language library comprising customized responses for natural language queries, wherein both the customized responses and the natural language queries are tailored to any of a service provider and a client application; generating an aggregated natural language library from the received natural language libraries, wherein the aggregated natural language library includes a plurality of natural language sub-libraries, wherein at least two of the natural language sub-libraries are associated with different client applications that each provide a service; receiving a search query via the network; comparing the search query to the aggregated natural language library to determine a customized response that corresponds to the search query; and providing the customized response that corresponds to the search query to a client device.

20. A method for processing natural language queries, the method comprising: receiving two or more natural language libraries from service providers via a network, the two or more natural language libraries comprising a customized natural language library, the customized natural language library comprising customized responses for natural language queries, wherein both the customized responses and the natural language queries are tailored to any of a service provider and a client application; generating an aggregated natural language library from the received natural language libraries, wherein the aggregated natural language library includes a plurality of natural language sub-libraries, wherein at least two of the natural language sub-libraries are associated with different client applications that each provide a service; receiving a search query via the network; comparing the search query to the aggregated natural language library to determine a customized response that corresponds to the search query; and providing the customized response that corresponds to the search query to a client device. 22. The method according to claim 20 , further comprising selecting the customized natural language library based upon an accuracy of the customized response relative to other customized responses generated by other customized natural language libraries.

1. An apparatus for recognizing speech in a presentation to generate a subtitle corresponding to the speech, said apparatus comprising: a text extraction unit that receives presentation text and its attributes from a presentation document, and stores said text and attributes in the text attribute database on a page-by-page basis, wherein the attributes comprise a title, character size, character underlining, or boldface character; a morphological analysis unit that morphologically analyzes the presentation text stored in the text attribute database, decomposes said presentation text into words, and stores the words in a word attribute database; a common keyword generation unit that extracts the words and their attributes from the word attribute database, determines whether or not a word has been successfully extracted, initializes attribute weights of the words and extracts the attribute weights from an attribute weight database and sums them if it is determined that the word extraction is successful, extracts keywords that are found in the presentation document and assigns weights to the keywords, then selects as an additional keyword to add to the keyword database any word that has been determined, based on time and attribute weight, to represent a high level of importance among the words contained in the presentation; a dictionary registration unit that adds the keywords registered in a keyword database to a dictionary database that is consulted at time of speech recognition; a voice recognition unit that recognizes the speech in the presentation in consultation with the dictionary database by: acquiring correspondence between a lapse of time from a start of the presentation and a result of voice recognition every moment, stores a correspondence between the time and the result of voice recognition in a subtitle database; a page-time recording unit that detects a page-changing event and stores the events as timestamps in a page-time database; a common keyword regeneration unit that initializes the keyword database, extracts a word, an attribute of the word and information about the page where the word appeared from the word attribute database, and further assigns weight depending on a number of times the keyword appeared as the voice in the presentation; a display control unit that reads a correspondence between the time and the result of speech recognition from the subtitle database, and displays said correspondence on a subtitle candidate display region, causes keywords stored in the keyword database, presentation text stored in the text attribute database, and a master subtitle stored in a master subtitle database to cooperate together for display as a subtitle to the presentation, and accesses the page-time database and specifies the page corresponding to the result of voice recognition on the basis of the time information; a display unit comprising: the subtitle candidate display region, a common keyword list display region, a presentation text display region, and a master subtitle display region; a speaker note generation unit that generates speaker notes from subtitles stored in the subtitle database and embeds them in presentation documents; the text attribute database; the word attribute database that stores the words obtained as a result of the decomposition performed by the morphological analysis unit, and their attributes; the attribute weight database that stores presentation word attributes and their assigned weights; the keyword database that stores the weighted words as keywords; the dictionary database; the subtitle database that stores, together with the time, the result of speech-recognition as the subtitle; the page-time database that records a time that the page is turned and a time when the next page is turned, and calculates the weight of the keywords in the page based on a duration during which the page in question is displayed in the presentation, when it is determined that extraction of the word has been successful; and a master subtitle database that stores master subtitles on a page-by-page basis.

1. An apparatus for recognizing speech in a presentation to generate a subtitle corresponding to the speech, said apparatus comprising: a text extraction unit that receives presentation text and its attributes from a presentation document, and stores said text and attributes in the text attribute database on a page-by-page basis, wherein the attributes comprise a title, character size, character underlining, or boldface character; a morphological analysis unit that morphologically analyzes the presentation text stored in the text attribute database, decomposes said presentation text into words, and stores the words in a word attribute database; a common keyword generation unit that extracts the words and their attributes from the word attribute database, determines whether or not a word has been successfully extracted, initializes attribute weights of the words and extracts the attribute weights from an attribute weight database and sums them if it is determined that the word extraction is successful, extracts keywords that are found in the presentation document and assigns weights to the keywords, then selects as an additional keyword to add to the keyword database any word that has been determined, based on time and attribute weight, to represent a high level of importance among the words contained in the presentation; a dictionary registration unit that adds the keywords registered in a keyword database to a dictionary database that is consulted at time of speech recognition; a voice recognition unit that recognizes the speech in the presentation in consultation with the dictionary database by: acquiring correspondence between a lapse of time from a start of the presentation and a result of voice recognition every moment, stores a correspondence between the time and the result of voice recognition in a subtitle database; a page-time recording unit that detects a page-changing event and stores the events as timestamps in a page-time database; a common keyword regeneration unit that initializes the keyword database, extracts a word, an attribute of the word and information about the page where the word appeared from the word attribute database, and further assigns weight depending on a number of times the keyword appeared as the voice in the presentation; a display control unit that reads a correspondence between the time and the result of speech recognition from the subtitle database, and displays said correspondence on a subtitle candidate display region, causes keywords stored in the keyword database, presentation text stored in the text attribute database, and a master subtitle stored in a master subtitle database to cooperate together for display as a subtitle to the presentation, and accesses the page-time database and specifies the page corresponding to the result of voice recognition on the basis of the time information; a display unit comprising: the subtitle candidate display region, a common keyword list display region, a presentation text display region, and a master subtitle display region; a speaker note generation unit that generates speaker notes from subtitles stored in the subtitle database and embeds them in presentation documents; the text attribute database; the word attribute database that stores the words obtained as a result of the decomposition performed by the morphological analysis unit, and their attributes; the attribute weight database that stores presentation word attributes and their assigned weights; the keyword database that stores the weighted words as keywords; the dictionary database; the subtitle database that stores, together with the time, the result of speech-recognition as the subtitle; the page-time database that records a time that the page is turned and a time when the next page is turned, and calculates the weight of the keywords in the page based on a duration during which the page in question is displayed in the presentation, when it is determined that extraction of the word has been successful; and a master subtitle database that stores master subtitles on a page-by-page basis. 2. The apparatus according to claim 1 , wherein the common keyword generation unit assigns the weight to the keyword in the document data according to the attribute of the keyword.

11. A method for translating event data, comprising: using at least one processor to perform steps of: receiving input information via an interface executed by the at least one processor; selecting at least one harvesting algorithm from a plurality of harvesting algorithms; performing the at least one selected harvesting algorithm on the input information to generate a result event data set; analyzing the result event data set outputted from the at least one selected harvesting algorithm; and selecting at least a portion of the result event data set based on the analysis of the result event data set as a selected result event data set by executing an analyzer; generating an event listing from the selected result event data set by executing a processing component; analyzing use of the event listing and displaying the event listing via the interface; and receiving user feedback data about the event listing, wherein the user feedback data is used to provide further information for configuring the analyzer in connection with analysis of a subsequent result event data set from the at least one harvesting algorithm and selection of a subsequent selected result event data set, and wherein the user feedback data about the event listing is used in a subsequent selection of the at least one harvesting algorithm from the plurality of harvesting algorithms; performing at least two harvesting algorithms from the plurality of harvesting algorithms on the input information to generate a plurality of result event data sets, wherein the at least two harvesting algorithms include a harvest of a first type having a first setting and a harvest of the first type having a second setting, the first setting being different from the second setting; and analyzing the plurality of result event data sets and selecting at least a portion of the plurality of result event data sets as a selected result event data set, wherein at least one of: the at least one harvester, the analyzer and the processing component is coupled to a controller for controlling at least one of: the at least harvester, the analyzer and the processing component.

11. A method for translating event data, comprising: using at least one processor to perform steps of: receiving input information via an interface executed by the at least one processor; selecting at least one harvesting algorithm from a plurality of harvesting algorithms; performing the at least one selected harvesting algorithm on the input information to generate a result event data set; analyzing the result event data set outputted from the at least one selected harvesting algorithm; and selecting at least a portion of the result event data set based on the analysis of the result event data set as a selected result event data set by executing an analyzer; generating an event listing from the selected result event data set by executing a processing component; analyzing use of the event listing and displaying the event listing via the interface; and receiving user feedback data about the event listing, wherein the user feedback data is used to provide further information for configuring the analyzer in connection with analysis of a subsequent result event data set from the at least one harvesting algorithm and selection of a subsequent selected result event data set, and wherein the user feedback data about the event listing is used in a subsequent selection of the at least one harvesting algorithm from the plurality of harvesting algorithms; performing at least two harvesting algorithms from the plurality of harvesting algorithms on the input information to generate a plurality of result event data sets, wherein the at least two harvesting algorithms include a harvest of a first type having a first setting and a harvest of the first type having a second setting, the first setting being different from the second setting; and analyzing the plurality of result event data sets and selecting at least a portion of the plurality of result event data sets as a selected result event data set, wherein at least one of: the at least one harvester, the analyzer and the processing component is coupled to a controller for controlling at least one of: the at least harvester, the analyzer and the processing component. 17. The method according to claim 11 , wherein the user feedback data is received from a user via a user interface.

12. A system for providing sporting event odds and information, for sports books, in substantially real time where the sports books, gamblers and enthusiasts want real time odds and information on the sports books computer, the system comprising: a program executed by a computer that utilizes an Internet connection to provide real time sports bet odds and information for a plurality of sports games from a plurality of sport books, said real time sports bet odds and information being downloaded and stored on the computer, wherein the program is incapable of placing bets; the program generating a display of real time sports bet odds and information including a major line move alert indicating when a number of sport books change their odds for a bet for a sports game in the same direction with a user settable period of time; and the program allowing navigation of the display in order to acquire real time sports bet odds and information wherein the program generates a menu made up of various menus, and for any particular game or bet, the program being capable of visually cycling through odds for the plurality of sport books.

12. A system for providing sporting event odds and information, for sports books, in substantially real time where the sports books, gamblers and enthusiasts want real time odds and information on the sports books computer, the system comprising: a program executed by a computer that utilizes an Internet connection to provide real time sports bet odds and information for a plurality of sports games from a plurality of sport books, said real time sports bet odds and information being downloaded and stored on the computer, wherein the program is incapable of placing bets; the program generating a display of real time sports bet odds and information including a major line move alert indicating when a number of sport books change their odds for a bet for a sports game in the same direction with a user settable period of time; and the program allowing navigation of the display in order to acquire real time sports bet odds and information wherein the program generates a menu made up of various menus, and for any particular game or bet, the program being capable of visually cycling through odds for the plurality of sport books. 16. The system of claim 12 wherein said program is written in the C++ programming language.

10. A method, comprising: receiving, through a communication interface, an access request from a client device, the access request including authentication information corresponding to a user; authenticating the access request based on the authentication information; obtaining, through a database interface, a layout template from a database library, the layout template including a data visualization panel; obtaining, through the database interface, a data visualization template from the database library, the data visualization template identifying a data source server; receiving, through the database interface, updateable data from the data source server; determining a standard data visualization structure for rendering the updateable data; rendering the updateable data into a data visualization according to the determined standard data visualization structure; controlling display of the data visualization in the data visualization panel within the layout template; generating a data visualization modification interface and accepting a client device customization input of data visualization rendering logic implemented by the data visualization; and modifying the data visualization rendering logic responsive to the client device customization.

10. A method, comprising: receiving, through a communication interface, an access request from a client device, the access request including authentication information corresponding to a user; authenticating the access request based on the authentication information; obtaining, through a database interface, a layout template from a database library, the layout template including a data visualization panel; obtaining, through the database interface, a data visualization template from the database library, the data visualization template identifying a data source server; receiving, through the database interface, updateable data from the data source server; determining a standard data visualization structure for rendering the updateable data; rendering the updateable data into a data visualization according to the determined standard data visualization structure; controlling display of the data visualization in the data visualization panel within the layout template; generating a data visualization modification interface and accepting a client device customization input of data visualization rendering logic implemented by the data visualization; and modifying the data visualization rendering logic responsive to the client device customization. 13. The method of claim 10 , wherein the standard data visualization structure is one of a tabular data structure, a geospatial data structure, a hierarchical data structure, and a time-series data structure.

1. A method comprising: analyzing, by a processor in a computer system, query logs to identify a pair of queries that are the same except that a first query, in the pair of queries, includes an extra term that is not included in a second query in the pair of queries; identifying, by a processor in the computer system, whether the pair of queries is associated with a quantity of search results that are common between the pair of queries; identifying, by a processor in the computer system, the extra term as a term that is not significant when the pair of queries is associated with at least a first threshold quantity of search results that are common between the pair of queries; processing, by a processor in the computer system, a query that includes the extra term to form a modified query when the extra term is identified as a term that is not significant; and identifying, by a processor in the computer system, search results based on the modified query when the extra term is identified as a term that is not significant.

1. A method comprising: analyzing, by a processor in a computer system, query logs to identify a pair of queries that are the same except that a first query, in the pair of queries, includes an extra term that is not included in a second query in the pair of queries; identifying, by a processor in the computer system, whether the pair of queries is associated with a quantity of search results that are common between the pair of queries; identifying, by a processor in the computer system, the extra term as a term that is not significant when the pair of queries is associated with at least a first threshold quantity of search results that are common between the pair of queries; processing, by a processor in the computer system, a query that includes the extra term to form a modified query when the extra term is identified as a term that is not significant; and identifying, by a processor in the computer system, search results based on the modified query when the extra term is identified as a term that is not significant. 4. The method of claim 1 , where, when identifying the extra term as a term that is not significant, the method further comprises: identifying the extra term as an optional term; associating, based on identifying the extra term as the optional term, a first weight with the extra term; associating a second weight with one or more other terms in the query, the second weight being different than the first weight; and processing the query, including the extra term and the one or more other terms, based on the associated first weight and the associated second weight.

36. A natural language query processing system, comprising: an interface module configured to receive a natural language query; a tokenizing module configured to generate at least one semantic token based on the received natural language query; a searching module configured to retrieve information from a knowledge base using the at least one semantic token; an interpretation module configured to: determine an intention associated with the received natural language query, wherein the intention is expressed in a personalized policy, and process the retrieved information in accordance with the intention, wherein the interpretation module processes the retrieved information by: establishing the personalized policy; applying the personalized policy in conjunction with contextual data obtained from the user to resolve an uncertainty in the natural language query, the contextual data comprising data relating to the user's location and sensor data; receiving feedback relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback; and an actuation module configured to provide the processed information to a user.

36. A natural language query processing system, comprising: an interface module configured to receive a natural language query; a tokenizing module configured to generate at least one semantic token based on the received natural language query; a searching module configured to retrieve information from a knowledge base using the at least one semantic token; an interpretation module configured to: determine an intention associated with the received natural language query, wherein the intention is expressed in a personalized policy, and process the retrieved information in accordance with the intention, wherein the interpretation module processes the retrieved information by: establishing the personalized policy; applying the personalized policy in conjunction with contextual data obtained from the user to resolve an uncertainty in the natural language query, the contextual data comprising data relating to the user's location and sensor data; receiving feedback relating to the application of the personalized policy; and re-configuring the personalized policy based on the feedback; and an actuation module configured to provide the processed information to a user. 41. The system of claim 36 , wherein the searching module is further configured to identify at least one term having a semantic relationship with the at least one semantic token.

1. A computer system for building concept knowledge from a machine-readable dictionary for use by a search engine to facilitate quick and accurate information retrieval, comprising a machine-readable dictionary including a plurality of words in a first language and a plurality of corresponding translated words in a second language, and a plurality of words in the second language and a plurality of corresponding translated words in the first language; an input device for inputting a seed word; a forward-translator for obtaining a plurality of translated words in the second language corresponding to said seed word by looking up said machine-readable dictionary; a backward-translator for obtaining a plurality of translated words in the first language corresponding to each of said plurality of translated words obtained by said translator respectively as words of the concept knowledge, by looking up said machine-readable dictionary; a synonym library for storing synonymous words of each translated word in the first language and in the second language; a frequency calculator for calculating the number of times each translated word occurs during obtaining said translated words in the second language and during obtaining said translated words in the first language; an evaluation unit for ranking said translated words in the first language and in the second language based on the synonym library and the frequency calculator; a word browser for presenting said ranked words to a user; a word selecting unit for allowing said user to select desired words among said ranked words and to delete irrelevant words among said ranked words; and means for providing said selected desired words to said search engine to perform knowledge-based information retrieval instead of keyword-based information retrieval.

1. A computer system for building concept knowledge from a machine-readable dictionary for use by a search engine to facilitate quick and accurate information retrieval, comprising a machine-readable dictionary including a plurality of words in a first language and a plurality of corresponding translated words in a second language, and a plurality of words in the second language and a plurality of corresponding translated words in the first language; an input device for inputting a seed word; a forward-translator for obtaining a plurality of translated words in the second language corresponding to said seed word by looking up said machine-readable dictionary; a backward-translator for obtaining a plurality of translated words in the first language corresponding to each of said plurality of translated words obtained by said translator respectively as words of the concept knowledge, by looking up said machine-readable dictionary; a synonym library for storing synonymous words of each translated word in the first language and in the second language; a frequency calculator for calculating the number of times each translated word occurs during obtaining said translated words in the second language and during obtaining said translated words in the first language; an evaluation unit for ranking said translated words in the first language and in the second language based on the synonym library and the frequency calculator; a word browser for presenting said ranked words to a user; a word selecting unit for allowing said user to select desired words among said ranked words and to delete irrelevant words among said ranked words; and means for providing said selected desired words to said search engine to perform knowledge-based information retrieval instead of keyword-based information retrieval. 22. A computer program product comprising a computer usable medium having computer usable program code embodied therein for causing the building of concept knowledge from a machine-readable dictionary, the computer usable program code in said computer program product comprising computer readable instructions executable by a computer for causing the computer to effect the functions of claim 1 .

1. A method for communicating structured information, between a first user and at least one second user, said method comprising: defining a document standard determining a general framework of the document comprised of: a series of fields of information comprising titles, information associated with titles and information for notifications, the information associated with titles being separate from the titles; and values authorized in fields of information, the step of defining being performed by said first user and second user, said first user providing said information, each second user receiving at least a portion of said information; the step of defining also defining at least one selection attribute associated with at least one field of information for enabling each second user to select information items from said document; inputting, by said first user, said information, the step of inputting being comprised of inputting one of text and titles to the general framework and selecting values authorized on said fields, the input information items being associated with at least one selection attribute based on the document standard; transmitting said document standard from said first user to storage for each second user; transmitting said information from said first user to storage for each secondary user; selecting, by each secondary user, a sorting criterion applicable to at least one selection attribute defined by the document standard; selecting information items of the document and re-organizing the selected information items of the document according to said sorting criterion and selection attributes associated with said information items; and supplying, to the secondary user, the selected information items of the document re-organized according to said sorting criterion; wherein each second user defines an identical document standard, and wherein each second user selects a separate sorting criterion corresponding to each second user independent from another second user.

1. A method for communicating structured information, between a first user and at least one second user, said method comprising: defining a document standard determining a general framework of the document comprised of: a series of fields of information comprising titles, information associated with titles and information for notifications, the information associated with titles being separate from the titles; and values authorized in fields of information, the step of defining being performed by said first user and second user, said first user providing said information, each second user receiving at least a portion of said information; the step of defining also defining at least one selection attribute associated with at least one field of information for enabling each second user to select information items from said document; inputting, by said first user, said information, the step of inputting being comprised of inputting one of text and titles to the general framework and selecting values authorized on said fields, the input information items being associated with at least one selection attribute based on the document standard; transmitting said document standard from said first user to storage for each second user; transmitting said information from said first user to storage for each secondary user; selecting, by each secondary user, a sorting criterion applicable to at least one selection attribute defined by the document standard; selecting information items of the document and re-organizing the selected information items of the document according to said sorting criterion and selection attributes associated with said information items; and supplying, to the secondary user, the selected information items of the document re-organized according to said sorting criterion; wherein each second user defines an identical document standard, and wherein each second user selects a separate sorting criterion corresponding to each second user independent from another second user. 8. The method according to claim 1 , further comprising: consolidating documents, wherein information of the documents linked to identical titles are juxtaposed under a unique title for different documents.

11. An apparatus comprising: a memory; and one or more processors configured to: use structural parsing to extract information from user input comprising a URL or domain name, the information comprising one or more of a protocol, a location, and a subdirectory, wherein structural parsing comprises; determining whether the domain name can be mapped to one or more concepts in the concept association map by switching term positions or changing numbers; when the domain name can be mapped and if the mapped concepts have high score, identifying the concepts as seed concepts for further querying the concept association map; when the mapped concepts do not have a high enough score, or the domain name cannot be mapped, then determining whether the input domain name can be mapped to a concept in the concept association map by typographical error correction, the correction comprising one or more of insertion, deletion, and switching or replacement of 1 or 2 characters; and when the input domain name cannot be mapped by typographical error correction, or if concepts mapped as a result of typographical error correction do not have a high score, determining how to break the domain name into URL tokens by inserting separators at correction positions and correcting the tokens; use semantic parsing of the information to identify a first one or more concepts represented by one or more tokens within the extracted information; query a concept association map to retrieve a second one or more concepts related to the first one or more concepts, each of the concepts representing a unit of thought, expressed by a term, letter, or symbol, the concept association map comprising a representation of concepts, concept metadata, and relationships between the concepts; rank the first one or more concepts and the second one or more concepts to create ranked concepts; and store the ranked concepts for displaying to one or more users of the computer platform.

11. An apparatus comprising: a memory; and one or more processors configured to: use structural parsing to extract information from user input comprising a URL or domain name, the information comprising one or more of a protocol, a location, and a subdirectory, wherein structural parsing comprises; determining whether the domain name can be mapped to one or more concepts in the concept association map by switching term positions or changing numbers; when the domain name can be mapped and if the mapped concepts have high score, identifying the concepts as seed concepts for further querying the concept association map; when the mapped concepts do not have a high enough score, or the domain name cannot be mapped, then determining whether the input domain name can be mapped to a concept in the concept association map by typographical error correction, the correction comprising one or more of insertion, deletion, and switching or replacement of 1 or 2 characters; and when the input domain name cannot be mapped by typographical error correction, or if concepts mapped as a result of typographical error correction do not have a high score, determining how to break the domain name into URL tokens by inserting separators at correction positions and correcting the tokens; use semantic parsing of the information to identify a first one or more concepts represented by one or more tokens within the extracted information; query a concept association map to retrieve a second one or more concepts related to the first one or more concepts, each of the concepts representing a unit of thought, expressed by a term, letter, or symbol, the concept association map comprising a representation of concepts, concept metadata, and relationships between the concepts; rank the first one or more concepts and the second one or more concepts to create ranked concepts; and store the ranked concepts for displaying to one or more users of the computer platform. 15. The apparatus of claim 11 wherein the one or more processors are further configured to break the URL into URL tokens by: associating a penalty with breaking a domain name into several tokens; and associating a score used to rank, prune and expand URL splitting paths.

14. The computer program product of claim 13 , the storage medium further containing computer program code for performing the steps: determining a ranking of the candidate sponsored stories for the viewing user; and selecting at least one of the candidate sponsored stories based on the ranking.

14. The computer program product of claim 13 , the storage medium further containing computer program code for performing the steps: determining a ranking of the candidate sponsored stories for the viewing user; and selecting at least one of the candidate sponsored stories based on the ranking. 19. The computer program product of claim 14 , wherein the ranking of the candidate sponsored stories for the viewing user is based at least in part on temporal factors associated with the candidate sponsored stories.

1. A method of generating a data object, the method being implemented by a computer system and comprising steps of: generating, using a processor of the computer system, a definition file of a first format for the data object; generating a database table; generating a mapping between the definition file and the database table; linking the definition file to a data source by including a path of the data source in the definition file, the data source including an attribute, wherein the data source is stored separately from the database table; executing, using the processor, a query to extract the attribute from the data source; importing the attribute into the database table using the mapping between the definition file and the database table; storing, in the memory device, the definition file, the database table, and the attribute for generation of the data object with the attribute; sending an instruction to edit the database table based on a name-value pair; selecting, from the data source, a property of the attribute; customizing the property; and setting a lifecycle of the data object, the lifecycle indicating a predetermined period of time, wherein the attribute is deleted from the database table when the period of time lapses.

1. A method of generating a data object, the method being implemented by a computer system and comprising steps of: generating, using a processor of the computer system, a definition file of a first format for the data object; generating a database table; generating a mapping between the definition file and the database table; linking the definition file to a data source by including a path of the data source in the definition file, the data source including an attribute, wherein the data source is stored separately from the database table; executing, using the processor, a query to extract the attribute from the data source; importing the attribute into the database table using the mapping between the definition file and the database table; storing, in the memory device, the definition file, the database table, and the attribute for generation of the data object with the attribute; sending an instruction to edit the database table based on a name-value pair; selecting, from the data source, a property of the attribute; customizing the property; and setting a lifecycle of the data object, the lifecycle indicating a predetermined period of time, wherein the attribute is deleted from the database table when the period of time lapses. 5. The method of claim 1 , further comprising naming the data object, wherein the query is of a predetermined syntax and includes the name of the data object and a name of the attribute.

6. A computer program product for replicating IP address assignment changes in a distributed database having a plurality of nodes, the computer program product being embodied in a computer readable medium and comprising computer instructions for: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, and wherein the semantic command is defined by one or more instructions or operations; interpreting the semantic command; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; sending the semantic command to the master node to reconcile the semantic command with the master version of the database based on any IP address assignment changes associated with the semantic command; and reconciling the semantic command with the master version of the database, wherein reconciling the semantic command with the master version of the database includes determining whether the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node.

6. A computer program product for replicating IP address assignment changes in a distributed database having a plurality of nodes, the computer program product being embodied in a computer readable medium and comprising computer instructions for: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, and wherein the semantic command is defined by one or more instructions or operations; interpreting the semantic command; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; sending the semantic command to the master node to reconcile the semantic command with the master version of the database based on any IP address assignment changes associated with the semantic command; and reconciling the semantic command with the master version of the database, wherein reconciling the semantic command with the master version of the database includes determining whether the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node. 26. A computer program product as recited in claim 6 , wherein the semantic command is determined to result in a conflict with the master version of the database and further comprising instructions for: sending conflict status information to the first node, wherein the first node manages the conflict including backing out any of the IP address assignment changes associated with the semantic command.

1. A method of editing a document, the method including: a) receiving data associated with the document, the data including mark-up language data; b) processing the received data to render at least part of the document for display in a first display area of a display, and displaying as rendered the at least part of the document in the first display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; c) processing the received data to render the at least part of the document for display in a second display area of the display, and displaying as rendered the at least part of the document in the second display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; d) receiving editing data; e) editing the at least part of the document displayed in the second display area using the editing data, and applying said editing to the at least part of the document displayed in the first display area; f) storing data associated with the at least part of the document edited in e) as a first edited version; g) receiving further editing data; h) further editing the at least part of the document displayed in the second display area using the further editing data and applying the further editing to the edited at least part of the document displayed in the first display area; and i) storing as a second edited version data associated with the further edited at least part of the document.

1. A method of editing a document, the method including: a) receiving data associated with the document, the data including mark-up language data; b) processing the received data to render at least part of the document for display in a first display area of a display, and displaying as rendered the at least part of the document in the first display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; c) processing the received data to render the at least part of the document for display in a second display area of the display, and displaying as rendered the at least part of the document in the second display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; d) receiving editing data; e) editing the at least part of the document displayed in the second display area using the editing data, and applying said editing to the at least part of the document displayed in the first display area; f) storing data associated with the at least part of the document edited in e) as a first edited version; g) receiving further editing data; h) further editing the at least part of the document displayed in the second display area using the further editing data and applying the further editing to the edited at least part of the document displayed in the first display area; and i) storing as a second edited version data associated with the further edited at least part of the document. 28. Apparatus comprising a processor, arranged to perform the method of claim 1 .

10. A computer program product, the computer program product comprising a non-transitory medium with a computer readable program code embodied therein, the computer readable program code for execution by an instruction execution platform to implement a method of providing a comprehensive coordinated electronic document system (CCEDS), the method comprising: providing a website portal, wherein a customer accesses the website portal, and wherein a financial institution stores at least one non-personalized electronic document and at least one personalized electronic document of the customer, wherein the non-personalized electronic document is selected from the group consisting of blank forms, informational documents, new account applications, transfers, payments, insurance documents, student center documents, tax documents, legal documents, disclosure statements, and agreements; accessing a database comprising non-personalized electronic documents, at least one list of actions, at least one list of customer service interaction triggers, and at least one record of document actions; providing access for the customer to the at least one non-personalized electronic document; determining at least one action from the list of actions performed by the customer with regard to the at least one non-personalized electronic document, wherein the action consists of at least one of completing a blank form, submitting a completed form, performing a document search, adding notes to a document, saving a document, emailing a document, viewing a personalized document, and initiating a customer service interaction regarding a document, wherein the non-personalized electronic document becomes a personalized document after the customer takes the at least one action on the non-personalized document; identifying a trigger from the list of customer service interaction triggers, wherein the trigger is associated with the action taken by the customer, and wherein the trigger is a predefined feature that is correlated to a customer service interaction; initiating the customer service interaction between the customer and a specialized employee of the financial institution in response to the trigger, wherein the customer service interaction is routed to the specialized employee based on the personalized document, and wherein the customer and the specialized employee access the personalized document; and creating a record of the at least one action taken, wherein the record comprises a link to a customer service history record for the customer service interactions pertaining to the personalized electronic document.

10. A computer program product, the computer program product comprising a non-transitory medium with a computer readable program code embodied therein, the computer readable program code for execution by an instruction execution platform to implement a method of providing a comprehensive coordinated electronic document system (CCEDS), the method comprising: providing a website portal, wherein a customer accesses the website portal, and wherein a financial institution stores at least one non-personalized electronic document and at least one personalized electronic document of the customer, wherein the non-personalized electronic document is selected from the group consisting of blank forms, informational documents, new account applications, transfers, payments, insurance documents, student center documents, tax documents, legal documents, disclosure statements, and agreements; accessing a database comprising non-personalized electronic documents, at least one list of actions, at least one list of customer service interaction triggers, and at least one record of document actions; providing access for the customer to the at least one non-personalized electronic document; determining at least one action from the list of actions performed by the customer with regard to the at least one non-personalized electronic document, wherein the action consists of at least one of completing a blank form, submitting a completed form, performing a document search, adding notes to a document, saving a document, emailing a document, viewing a personalized document, and initiating a customer service interaction regarding a document, wherein the non-personalized electronic document becomes a personalized document after the customer takes the at least one action on the non-personalized document; identifying a trigger from the list of customer service interaction triggers, wherein the trigger is associated with the action taken by the customer, and wherein the trigger is a predefined feature that is correlated to a customer service interaction; initiating the customer service interaction between the customer and a specialized employee of the financial institution in response to the trigger, wherein the customer service interaction is routed to the specialized employee based on the personalized document, and wherein the customer and the specialized employee access the personalized document; and creating a record of the at least one action taken, wherein the record comprises a link to a customer service history record for the customer service interactions pertaining to the personalized electronic document. 18. The computer program product of claim 10 , wherein the specialized employee and the customer take the action on a single personalized document.

13. A computing system for generating a model image of a 3D model, the computing system comprising: one or more computer-readable storage mediums storing computer-executable instructions for controlling the computing system to: access an original image along with metadata based on a view of a camera that collected the image, the metadata for determining a row number and a column number of the original image that correspond to a geospatial coordinate; identify an origin pixel of the original image, the origin pixel having an origin row number and an origin column number and an image height and an image width in pixels; identify based on the metadata an origin geospatial coordinate associated with the origin pixel; for each easting, northing, and height direction, generate a row transform factor and a column transform factor to transform geospatial coordinates of the 3D model to a clip range based on a pixel that corresponds to a geospatial coordinate that is a certain geospatial distance in that direction from the origin geospatial coordinate; generate a perspective transform matrix based on the row transform factors and the column transform factors; and apply the perspective transform matrix to the 3D model to generate the model image; and one or more processors for executing the computer-executable instructions stored in the one or more computer-readable storage mediums.

13. A computing system for generating a model image of a 3D model, the computing system comprising: one or more computer-readable storage mediums storing computer-executable instructions for controlling the computing system to: access an original image along with metadata based on a view of a camera that collected the image, the metadata for determining a row number and a column number of the original image that correspond to a geospatial coordinate; identify an origin pixel of the original image, the origin pixel having an origin row number and an origin column number and an image height and an image width in pixels; identify based on the metadata an origin geospatial coordinate associated with the origin pixel; for each easting, northing, and height direction, generate a row transform factor and a column transform factor to transform geospatial coordinates of the 3D model to a clip range based on a pixel that corresponds to a geospatial coordinate that is a certain geospatial distance in that direction from the origin geospatial coordinate; generate a perspective transform matrix based on the row transform factors and the column transform factors; and apply the perspective transform matrix to the 3D model to generate the model image; and one or more processors for executing the computer-executable instructions stored in the one or more computer-readable storage mediums. 18. The computing system of claim 13 wherein an annotation is associated with an object of the 3D model and wherein the computer-executable instructions further control the computing system to: display the original image; and when the original image includes the object, provide an indication that an annotation is associated with the object of the original image.

15. A computer-implemented method of processing mail documents returned to a financial institution, the method comprising: receiving, by a computer system, a plurality of returned mail documents in electronic form, wherein the computer system comprises at least one processor and operatively associated memory; extracting, by the computer system, metadata from the returned mail documents; correlating, by the computer system, a returned mail document selected from the plurality of returned mail documents to a first client account considering the extracted metadata; if the returned mail document comprises a forwarding address: generating, by the computer system, instructions for re-sending the returned mail document to the forwarding address; and updating, by the computer system a status of the first client account to reflect the forwarding address; identifying a branch office of the financial institution associated with the first client account; transmitting, by the computer system, information about the returned mail document to the branch office; determining, by the computer system, whether the returned mail document was sent prior to the last address change associated with the first client account; and if the returned mail document was sent prior to the last address change associated with the first client account, generating instructions for resending the returned mail document to a new address associated with the first client account; determining, by the computer system, whether any other mail documents correlated to the first client account have been returned; updating, by the computer system, the number of returned mail documents correlated to the first client account considering the mail document; conditioned upon the number of returned mail documents correlated to the first client account being greater than or equal to a predetermined number, marking the first client account undeliverable; conditioned upon the number of returned mail documents correlated to the first client account having been greater than or equal to a second predetermined number for greater than a predetermined time period, marking the first client account undeliverable, wherein the second predetermined number is less than the first predetermined number.

15. A computer-implemented method of processing mail documents returned to a financial institution, the method comprising: receiving, by a computer system, a plurality of returned mail documents in electronic form, wherein the computer system comprises at least one processor and operatively associated memory; extracting, by the computer system, metadata from the returned mail documents; correlating, by the computer system, a returned mail document selected from the plurality of returned mail documents to a first client account considering the extracted metadata; if the returned mail document comprises a forwarding address: generating, by the computer system, instructions for re-sending the returned mail document to the forwarding address; and updating, by the computer system a status of the first client account to reflect the forwarding address; identifying a branch office of the financial institution associated with the first client account; transmitting, by the computer system, information about the returned mail document to the branch office; determining, by the computer system, whether the returned mail document was sent prior to the last address change associated with the first client account; and if the returned mail document was sent prior to the last address change associated with the first client account, generating instructions for resending the returned mail document to a new address associated with the first client account; determining, by the computer system, whether any other mail documents correlated to the first client account have been returned; updating, by the computer system, the number of returned mail documents correlated to the first client account considering the mail document; conditioned upon the number of returned mail documents correlated to the first client account being greater than or equal to a predetermined number, marking the first client account undeliverable; conditioned upon the number of returned mail documents correlated to the first client account having been greater than or equal to a second predetermined number for greater than a predetermined time period, marking the first client account undeliverable, wherein the second predetermined number is less than the first predetermined number. 21. The method of claim 15 , further comprising displaying the returned mail document to a user when the correlating fails.

12. A method comprising: maintaining a plurality of pages on a social networking system; clustering the plurality of pages by a concept; ranking, by a processor, a plurality of pages of the cluster of pages based on one or more rules analyzing attributes of the plurality of pages of the cluster of pages, the one or more rules applied based on a predetermined hierarchy and profile information of a user requesting a page of the cluster of pages; selecting, based on the ranking associated with the plurality of pages of the cluster, a best page for the concept; and directing the user requesting a page of the plurality of pages of the cluster to the selected best page.

12. A method comprising: maintaining a plurality of pages on a social networking system; clustering the plurality of pages by a concept; ranking, by a processor, a plurality of pages of the cluster of pages based on one or more rules analyzing attributes of the plurality of pages of the cluster of pages, the one or more rules applied based on a predetermined hierarchy and profile information of a user requesting a page of the cluster of pages; selecting, based on the ranking associated with the plurality of pages of the cluster, a best page for the concept; and directing the user requesting a page of the plurality of pages of the cluster to the selected best page. 18. The method of claim 12 , wherein directing a user requesting a page of the plurality of pages of the cluster to the selected best page further comprises: providing for display in a profile page for a user of the social networking system, the user expressing an interest in a page of the plurality of pages, the selected best page for the cluster in place of the page in which the user expressed interest.

1. A computing device comprising: one or more input interfaces for receiving a sketch; one or more processors; and a computer-readable storage media storing instructions, which when executed by the one or more processors, cause the one or more processors to generate a model for identifying a subject of the sketch: performing an image-based search of a collection of images to identify a set of images with shape features similar to those of the sketch; filtering the set of images into a set of filtered images by removing images that have more than one subject, each image of the set of filtered images associated with at least one text-based label; deriving a shape feature for each image of the set of filtered images; generating a plurality of shape topics based on the shape features of the set of filtered images; generating a plurality of object topics based on the shape topics and associating each of the object topics with at least one of the plurality of shape topics; deriving a word distribution for each of the object topics from the text-based labels; identifying a word descriptive of the subject of the sketch from at least one of the word distributions; and applying the word as a tag to the sketch.

1. A computing device comprising: one or more input interfaces for receiving a sketch; one or more processors; and a computer-readable storage media storing instructions, which when executed by the one or more processors, cause the one or more processors to generate a model for identifying a subject of the sketch: performing an image-based search of a collection of images to identify a set of images with shape features similar to those of the sketch; filtering the set of images into a set of filtered images by removing images that have more than one subject, each image of the set of filtered images associated with at least one text-based label; deriving a shape feature for each image of the set of filtered images; generating a plurality of shape topics based on the shape features of the set of filtered images; generating a plurality of object topics based on the shape topics and associating each of the object topics with at least one of the plurality of shape topics; deriving a word distribution for each of the object topics from the text-based labels; identifying a word descriptive of the subject of the sketch from at least one of the word distributions; and applying the word as a tag to the sketch. 5. The computing device of claim 1 , wherein the sketch is added to the collection of images.

1. An apparatus comprising processing circuitry configured to execute instructions for: receiving a first threshold and a second threshold; receiving a plurality of binary reference samples; processing each reference sample of the plurality of reference samples via operations including: assigning each reference sample a respective unique identifier; producing a reference sample fingerprint for each reference sample; and registering each respective unique identifier to reference sample fingerprint pair in a reference library via operations including: scoring the reference sample fingerprint with each previously stored fingerprint in the reference library to produce a first matching score; if the first matching score meets or exceeds the first threshold for a previously stored fingerprint, determining the reference sample fingerprint to be a duplicate of the previously stored fingerprint, and recording only a unique identifier associated with the reference sample fingerprint in the reference library, the unique identifier being marked as a duplicate of the previously stored fingerprint; and otherwise, if the first matching score for each previously stored fingerprint is less than the first threshold, storing a corresponding reference sample unique identifier to reference sample fingerprint pair in the reference library; receiving a binary query sample; processing the binary query sample via operations including: producing a query sample fingerprint from the binary query sample; scoring the query sample fingerprint with each previously stored fingerprint in the reference library to produce a second matching score; for each previously stored fingerprint for which the second matching score meets or exceeds the second threshold, reporting a corresponding reference sample unique identifier associated with the previously stored fingerprint and the second matching score.

1. An apparatus comprising processing circuitry configured to execute instructions for: receiving a first threshold and a second threshold; receiving a plurality of binary reference samples; processing each reference sample of the plurality of reference samples via operations including: assigning each reference sample a respective unique identifier; producing a reference sample fingerprint for each reference sample; and registering each respective unique identifier to reference sample fingerprint pair in a reference library via operations including: scoring the reference sample fingerprint with each previously stored fingerprint in the reference library to produce a first matching score; if the first matching score meets or exceeds the first threshold for a previously stored fingerprint, determining the reference sample fingerprint to be a duplicate of the previously stored fingerprint, and recording only a unique identifier associated with the reference sample fingerprint in the reference library, the unique identifier being marked as a duplicate of the previously stored fingerprint; and otherwise, if the first matching score for each previously stored fingerprint is less than the first threshold, storing a corresponding reference sample unique identifier to reference sample fingerprint pair in the reference library; receiving a binary query sample; processing the binary query sample via operations including: producing a query sample fingerprint from the binary query sample; scoring the query sample fingerprint with each previously stored fingerprint in the reference library to produce a second matching score; for each previously stored fingerprint for which the second matching score meets or exceeds the second threshold, reporting a corresponding reference sample unique identifier associated with the previously stored fingerprint and the second matching score. 8. The apparatus of claim 1 , wherein each of the reference samples is a code binary.

65. An industrial system or the like comprising: apparatus for implementing system operations; sensor means associated with the apparatus for generating signals indicative of the state of the system; a digital computer system having a memory; signal scanning means associated with said computer system and connecting to said sensor means for scanning said sensor signals periodically and including means for transferring a digital record of the status of the signals into the memory of said digital computer system; at least one machine readable signal-related event definition defining as an event either the periodic scanning or a particular change in the state of at least one sensor signal, including a designation which serves as a name for the event and also as a name for the signal, and including a reference to the location in said memory where the status record of the corresponding signal variable is stored; at least one machine readable job definition including at least one triggering reference to a designation which serves as a name for an event and for signal and which is at least one event definition; loader means for operating said computer system to accept said event and job definitions and to store said definitions in said memory; trigger-connect means for operating said computer system to link job definitions but only those containing trigger references to designations, to locations in said memory that are in turn linked to the event definition and status data for the designated signals; means for operating said computer system to respond to the occurrence of a signal-related event by initiating execution of any and all job definitions which are linked to the status data and definition corresponding to that event; means for preliminarily translating at least some definitions from a first coding which is intelligible to and easily generatable by human beings into a second coding which is suitable for on-line interpretation and execution of the definitions; and at least one processing program which includes means for interpreting and executing definitions using said second coding.

65. An industrial system or the like comprising: apparatus for implementing system operations; sensor means associated with the apparatus for generating signals indicative of the state of the system; a digital computer system having a memory; signal scanning means associated with said computer system and connecting to said sensor means for scanning said sensor signals periodically and including means for transferring a digital record of the status of the signals into the memory of said digital computer system; at least one machine readable signal-related event definition defining as an event either the periodic scanning or a particular change in the state of at least one sensor signal, including a designation which serves as a name for the event and also as a name for the signal, and including a reference to the location in said memory where the status record of the corresponding signal variable is stored; at least one machine readable job definition including at least one triggering reference to a designation which serves as a name for an event and for signal and which is at least one event definition; loader means for operating said computer system to accept said event and job definitions and to store said definitions in said memory; trigger-connect means for operating said computer system to link job definitions but only those containing trigger references to designations, to locations in said memory that are in turn linked to the event definition and status data for the designated signals; means for operating said computer system to respond to the occurrence of a signal-related event by initiating execution of any and all job definitions which are linked to the status data and definition corresponding to that event; means for preliminarily translating at least some definitions from a first coding which is intelligible to and easily generatable by human beings into a second coding which is suitable for on-line interpretation and execution of the definitions; and at least one processing program which includes means for interpreting and executing definitions using said second coding. 66. A system in accordance with claim 65 wherein at least some of the definitions which are translated by the means for translating are definitions of variable monitoring functions including designations that serve as names for system variables which designations are not translated and which designations may be referred to by other definitions for the purpose of establishing either a trigger connection or a reference to the variable.

11. A computer-implemented system having a non-transitory computer-readable medium comprising instructions stored thereon, comprising: hardware processor configured to automatically generate, for a computer software program, both assertions that are desired to be valid, based on desired application-specific security properties, the validity of the assertions being usable to verify application-specific security properties, and assertions known to be valid, based on the computer software program and desired application-specific security properties; said or another hardware processor configured to automatically analyze the computer software program source code and determine whether the computer software program satisfies the application-specific security properties, based on the automatically generated assertions that are desired to be valid in combination with the automatically generated assertions that are known to be valid; and said or another hardware processor configured to display feedback to indicate instances of failure of the computer software program to satisfy the application-specific security properties based on said automatic analysis of the computer software program source code.

11. A computer-implemented system having a non-transitory computer-readable medium comprising instructions stored thereon, comprising: hardware processor configured to automatically generate, for a computer software program, both assertions that are desired to be valid, based on desired application-specific security properties, the validity of the assertions being usable to verify application-specific security properties, and assertions known to be valid, based on the computer software program and desired application-specific security properties; said or another hardware processor configured to automatically analyze the computer software program source code and determine whether the computer software program satisfies the application-specific security properties, based on the automatically generated assertions that are desired to be valid in combination with the automatically generated assertions that are known to be valid; and said or another hardware processor configured to display feedback to indicate instances of failure of the computer software program to satisfy the application-specific security properties based on said automatic analysis of the computer software program source code. 19. The system of claim 11 , wherein said or another hardware processor is configured to display feedback to diagnose security flaws detected in the computer software program based on said automatic analysis of the computer software program source code during code construction of the computer software program.

10. A method for transforming industrial data, comprising: executing, by an industrial device comprising at least one processor, an industrial control program, wherein the executing causes the industrial device to process input signals from input devices and to control output signals directed to output devices; generating and collecting, by the industrial device, industrial data generated via control of an industrial process via the input devices and the output devices; determining, by the industrial device, a plant site identifier and a production area identifier associated with the industrial data based on a referencing of a hierarchical organizational model of an industrial enterprise that defines at least an enterprise level, a site level, and a production area level; transforming, by the industrial device, the industrial data into refined data in accordance with a requirement of a cloud-based application, wherein the transforming comprises at least adding contextual information to the industrial data, the contextual information comprising at least an actionable tag, the plant site identifier, the production area identifier, an identity of a product being produced at a time that the industrial data was generated, and a quality indicator for the product; and transferring, by the industrial device, the refined data to the cloud-based application to facilitate notifying a user in accordance with the actionable tag.

10. A method for transforming industrial data, comprising: executing, by an industrial device comprising at least one processor, an industrial control program, wherein the executing causes the industrial device to process input signals from input devices and to control output signals directed to output devices; generating and collecting, by the industrial device, industrial data generated via control of an industrial process via the input devices and the output devices; determining, by the industrial device, a plant site identifier and a production area identifier associated with the industrial data based on a referencing of a hierarchical organizational model of an industrial enterprise that defines at least an enterprise level, a site level, and a production area level; transforming, by the industrial device, the industrial data into refined data in accordance with a requirement of a cloud-based application, wherein the transforming comprises at least adding contextual information to the industrial data, the contextual information comprising at least an actionable tag, the plant site identifier, the production area identifier, an identity of a product being produced at a time that the industrial data was generated, and a quality indicator for the product; and transferring, by the industrial device, the refined data to the cloud-based application to facilitate notifying a user in accordance with the actionable tag. 15. The method of claim 10 , further comprising at least one of compressing, aggregating, encrypting, filtering, or re-formatting the industrial data by the industrial device to yield the refined data.

1. A computer-based method for generating 3-D structural models of complex formation between a query ligand and a target macromolecule, the method comprising: a) providing a structural model of a query ligand and a structural model of a target macromolecule; wherein the structural model of the query ligand is based on data from X-ray crystallography or NMR spectroscopy, and the structural model of the target macromolecule is based on data from X-ray crystallography; b) identifying a substructure of the query ligand; c) identifying comparison ligands in a set of 3-D structural models that each share an identical substructure with the query ligand, wherein each 3-D structural model comprises a comparison ligand and a comparison macromolecule, and wherein the comparison macromolecule has structural features homologous to structural features of the target macromolecule of 20% or greater nucleic acid and/or amino acid homology; d) mapping spatial relationships between the substructure atoms of the query ligand and a comparison ligand identified in c) such that corresponding atoms are identified; e) assigning atomic coordinates to the corresponding atoms of the query ligand; f) generating and displaying one or more output models, each model comprising a 3-D structural model of the query ligand substructure and the target macromolecule, wherein the 3-D model of the query ligand substructure comprises the atomic coordinates of the query ligand from step (e).

1. A computer-based method for generating 3-D structural models of complex formation between a query ligand and a target macromolecule, the method comprising: a) providing a structural model of a query ligand and a structural model of a target macromolecule; wherein the structural model of the query ligand is based on data from X-ray crystallography or NMR spectroscopy, and the structural model of the target macromolecule is based on data from X-ray crystallography; b) identifying a substructure of the query ligand; c) identifying comparison ligands in a set of 3-D structural models that each share an identical substructure with the query ligand, wherein each 3-D structural model comprises a comparison ligand and a comparison macromolecule, and wherein the comparison macromolecule has structural features homologous to structural features of the target macromolecule of 20% or greater nucleic acid and/or amino acid homology; d) mapping spatial relationships between the substructure atoms of the query ligand and a comparison ligand identified in c) such that corresponding atoms are identified; e) assigning atomic coordinates to the corresponding atoms of the query ligand; f) generating and displaying one or more output models, each model comprising a 3-D structural model of the query ligand substructure and the target macromolecule, wherein the 3-D model of the query ligand substructure comprises the atomic coordinates of the query ligand from step (e). 21. The method of claim 1 , further comprising refining the output models.

1. A method of producing a desired digital image of at least one desired face by a computer comprising: providing to the computer a digital image of at least one original face, wherein an original face comprises a foreground region drawn according to a set of guidelines; providing at least one face image from external sources; for the original face within the digital image, selecting a corresponding face image (selected corresponding face image) from among the face images from external sources; for the original face within the digital image, modifying the selected corresponding face image (modified corresponding face image); and replacing the original face within the digital image with the selected and modified corresponding face image at a desired position and a desired size within the digital image to produce the desired digital image of the desired face, wherein the set of guidelines comprises defining the original face as the foreground region drawn within the digital image to resemble and represent the desired face, defining the original face as the foreground region surrounded by other (foreground and/or background) regions and/or edges within the digital image, defining the original face as the foreground region with a distinctive edge wherein the distinctive edge separates the original face from the other regions within the digital image, defining a position of the original face drawn within the digital image as the desired position of the desired face, defining a size of the original face drawn within the digital image as the desired size of the desired face, defining the original face as the foreground region with majority of an area in a unanimous colour, defining the original face as the foreground region containing facial features, wherein the facial features and the foreground region of the original face are separated by different colours or edges, defining the facial features as comprising two eyes and one mouth, defining the two eyes as similar in size to each other, defining each of the two eyes to be in a unanimous colour, defining the mouth as bigger in size than each of the two eyes, defining the mouth to be in a unanimous colour, defining an arrangement of the two eyes and the mouth within the original face, as similar to an arrangement of eyes and mouth of a real human face, defining the sizes of the two eyes and the mouth relative to corresponding sizes of the original face, as similar to sizes of the eyes and the mouth of a real human face relative to the corresponding sizes of the real human face, and defining an upright position of the original face as a position where the two eyes are lying horizontally, with the mouth lying below the two eyes.

1. A method of producing a desired digital image of at least one desired face by a computer comprising: providing to the computer a digital image of at least one original face, wherein an original face comprises a foreground region drawn according to a set of guidelines; providing at least one face image from external sources; for the original face within the digital image, selecting a corresponding face image (selected corresponding face image) from among the face images from external sources; for the original face within the digital image, modifying the selected corresponding face image (modified corresponding face image); and replacing the original face within the digital image with the selected and modified corresponding face image at a desired position and a desired size within the digital image to produce the desired digital image of the desired face, wherein the set of guidelines comprises defining the original face as the foreground region drawn within the digital image to resemble and represent the desired face, defining the original face as the foreground region surrounded by other (foreground and/or background) regions and/or edges within the digital image, defining the original face as the foreground region with a distinctive edge wherein the distinctive edge separates the original face from the other regions within the digital image, defining a position of the original face drawn within the digital image as the desired position of the desired face, defining a size of the original face drawn within the digital image as the desired size of the desired face, defining the original face as the foreground region with majority of an area in a unanimous colour, defining the original face as the foreground region containing facial features, wherein the facial features and the foreground region of the original face are separated by different colours or edges, defining the facial features as comprising two eyes and one mouth, defining the two eyes as similar in size to each other, defining each of the two eyes to be in a unanimous colour, defining the mouth as bigger in size than each of the two eyes, defining the mouth to be in a unanimous colour, defining an arrangement of the two eyes and the mouth within the original face, as similar to an arrangement of eyes and mouth of a real human face, defining the sizes of the two eyes and the mouth relative to corresponding sizes of the original face, as similar to sizes of the eyes and the mouth of a real human face relative to the corresponding sizes of the real human face, and defining an upright position of the original face as a position where the two eyes are lying horizontally, with the mouth lying below the two eyes. 10. The method of claim 1 , wherein the modified corresponding face image comprises acts of: being digitally resized, dependence upon a digital representation defining the original face; being digitally rotated, dependence upon rotation of the original face; and being digitally clipped, dependence upon clipping of the original face and redundant background of the modified corresponding face image.

1. A computing device having a processor and implementing a first schema for querying a first data store described by the first schema, the first schema being stored as a data structure on one or more computer-storage media accessible by the processor, the first schema comprising: a first property description element describing a first individual property of the data store including one or more static attributes and one or more contextual attributes that combine to describe the first individual property wherein each static attribute has a corresponding static attribute value and each contextual attribute has a corresponding contextual attribute value, wherein a static attribute associated with the first individual property is immutable and has the same static attribute value within all schemas that include the first individual property, wherein a contextual attribute is able to have different contextual attribute values among different schemas that include the first individual property, and wherein contextual attribute values are defined within each schema that has the contextual attribute; a property reference element that defines a second individual property in the first data store by referencing a second property description element from a second schema that includes static attributes and corresponding static attribute values wherein the property reference specifies contextual attributes and corresponding contextual attribute values, wherein the static attributes apply to all schemas that reference the second property description element, and wherein the contextual attributes apply only to the first schema; an item type description element describing an item type for at least one item in the data store, the item type description element including one or more properties that define the item type; and a kind description element describing a kind for at least one item in the data store, the kind description element including one or more properties for the kind, wherein the kind is a collection of logically related item types.

1. A computing device having a processor and implementing a first schema for querying a first data store described by the first schema, the first schema being stored as a data structure on one or more computer-storage media accessible by the processor, the first schema comprising: a first property description element describing a first individual property of the data store including one or more static attributes and one or more contextual attributes that combine to describe the first individual property wherein each static attribute has a corresponding static attribute value and each contextual attribute has a corresponding contextual attribute value, wherein a static attribute associated with the first individual property is immutable and has the same static attribute value within all schemas that include the first individual property, wherein a contextual attribute is able to have different contextual attribute values among different schemas that include the first individual property, and wherein contextual attribute values are defined within each schema that has the contextual attribute; a property reference element that defines a second individual property in the first data store by referencing a second property description element from a second schema that includes static attributes and corresponding static attribute values wherein the property reference specifies contextual attributes and corresponding contextual attribute values, wherein the static attributes apply to all schemas that reference the second property description element, and wherein the contextual attributes apply only to the first schema; an item type description element describing an item type for at least one item in the data store, the item type description element including one or more properties that define the item type; and a kind description element describing a kind for at least one item in the data store, the kind description element including one or more properties for the kind, wherein the kind is a collection of logically related item types. 2. The computing device of claim 1 , wherein the first schema further includes a second property description element describing a second property of the first data store, wherein the property description element includes both static attributes and contextual attributes to describe the second property.

11. A method of extracting universal scene descriptors (USDs) from a scene, comprising: providing a sequence of one or more unsegmented images of a scene, each image including at least one region or interest (ROI); extracting biologically-inspired visual features from at least one ROI in each scene including an object-tuned L 1 feature vector, an object-tuned spatial-layout L 2 feature vector, a ROI-to-ROI geometric L 3 feature vector, an ROI spatial-layout L 4 feature vector and a scene spatial-layout L 5 feature vector; and assembling the L 1 through L 5 feature vectors into a universal feature vector for each said ROI in the scene captured in each said image, each said universal feature vector providing a USD for the scene.

11. A method of extracting universal scene descriptors (USDs) from a scene, comprising: providing a sequence of one or more unsegmented images of a scene, each image including at least one region or interest (ROI); extracting biologically-inspired visual features from at least one ROI in each scene including an object-tuned L 1 feature vector, an object-tuned spatial-layout L 2 feature vector, a ROI-to-ROI geometric L 3 feature vector, an ROI spatial-layout L 4 feature vector and a scene spatial-layout L 5 feature vector; and assembling the L 1 through L 5 feature vectors into a universal feature vector for each said ROI in the scene captured in each said image, each said universal feature vector providing a USD for the scene. 14. The method of claim 11 , wherein ROI-to-ROI geometric features are extracted for each said ROI by, calculating a vector describing the geometric relationship to at least one other ROI in the scene; and assembling the spatial vectors into the L 3 feature vector.

1. A rule-based data processing apparatus comprising: a processor coupled with first and second memory means, said first memory means having stored therein first and second groups of agents, each group of agents being defined by respective sets of rules, said processor being arranged to run said respective sets of rules in parallel, and said second memory means having stored therein data defining a plurality of objects, at least some of the data having a respective qualifier term associated therewith, the agents of the first group being script agents and being arranged as a sequentially enabled chain, one or more of said script agents including a respective reference to one of said objects and a specified qualifier term; and each of the agents of the second group being object agents and being operable to identify an object and specified qualifier term from a script agent, to identify an instance or each instance of said object in the second memory means, to compare the specified qualifier term with the respective associated qualifier term of each identified object and, when a match occurs, to generate an identifying pointer for the identified and matched object.

1. A rule-based data processing apparatus comprising: a processor coupled with first and second memory means, said first memory means having stored therein first and second groups of agents, each group of agents being defined by respective sets of rules, said processor being arranged to run said respective sets of rules in parallel, and said second memory means having stored therein data defining a plurality of objects, at least some of the data having a respective qualifier term associated therewith, the agents of the first group being script agents and being arranged as a sequentially enabled chain, one or more of said script agents including a respective reference to one of said objects and a specified qualifier term; and each of the agents of the second group being object agents and being operable to identify an object and specified qualifier term from a script agent, to identify an instance or each instance of said object in the second memory means, to compare the specified qualifier term with the respective associated qualifier term of each identified object and, when a match occurs, to generate an identifying pointer for the identified and matched object. 2. Apparatus as claimed in claim 1, wherein every script agent including a common object reference and specified qualifier term identifies a common object from the second memory means via a single object agent, with each of those script agents having a respective marker on said object agent.

13. One or more computer storage media encoded with instructions that, when executed by a processor, perform acts comprising: accessing, from a database associated with a content service provider, logs of global positioning system (GPS) points collected by geolocation sensors associated with service vehicles; identifying geographical locations from the GPS points to represent an area where the service vehicles travelled as recorded in the logs; generating links to connect two or more regions of the area based at least in part on a number of transitions pertaining to the links for travel of the service vehicles between the two or more regions; and detecting outliers in the GPS points in the geographical locations based at least in part on the links.

13. One or more computer storage media encoded with instructions that, when executed by a processor, perform acts comprising: accessing, from a database associated with a content service provider, logs of global positioning system (GPS) points collected by geolocation sensors associated with service vehicles; identifying geographical locations from the GPS points to represent an area where the service vehicles travelled as recorded in the logs; generating links to connect two or more regions of the area based at least in part on a number of transitions pertaining to the links for travel of the service vehicles between the two or more regions; and detecting outliers in the GPS points in the geographical locations based at least in part on the links. 15. The computer storage media of claim 13 , wherein the number of transitions is associated with a departure time from at least a region of origin and an arrival time in at least a region of destination, the region of origin and the region of destination comprising at least two of the two or more regions.

7. The computer-implemented method for classifying an electronic document of claim 1 , wherein determining the at least one term vector includes building a list and a count of taxonomic nouns.

7. The computer-implemented method for classifying an electronic document of claim 1 , wherein determining the at least one term vector includes building a list and a count of taxonomic nouns. 10. The computer-implemented method for classifying an electronic document of claim 7 , wherein determining the at least one term vector includes applying a dictionary of taxonomic nouns with a dictionary building server.

1. A targeting system comprising: a targeting server comprising a processor and a memory storing a database; wherein the targeting server: obtains data from at least one server that forms part of an online social network, where the obtained data describes member profiles of members of the online social network and activities performed on the online social network that are associated with the member profiles; detects affinity data describing affinities between a member profile and one or more keywords based upon data describing activities associated with the member profile; generates a database containing the member profiles and the affinity data associating the detected affinities between member profiles and keywords; identifies member profile data describing member profiles within the database that are associated with an affinity to at least one offer keyword; identifies targeting keywords based on the at least one offer keywords and the member profile data by identifying at least one additional keyword within the at least one offer keyword based on the affinity of the member profiles within the member profile data; identifies other keywords for which the identified member profiles have an associated affinity; selects a set of keywords including at least one of the identified keywords and at least one of the targeting keywords as targeting keywords for the specific offer, where the selected keywords target the desired audience for the specific offer; generates a set of targeting keywords that target a specific offer to a desired audience based on the selected set of keywords; and provides the set of targeting keywords.

1. A targeting system comprising: a targeting server comprising a processor and a memory storing a database; wherein the targeting server: obtains data from at least one server that forms part of an online social network, where the obtained data describes member profiles of members of the online social network and activities performed on the online social network that are associated with the member profiles; detects affinity data describing affinities between a member profile and one or more keywords based upon data describing activities associated with the member profile; generates a database containing the member profiles and the affinity data associating the detected affinities between member profiles and keywords; identifies member profile data describing member profiles within the database that are associated with an affinity to at least one offer keyword; identifies targeting keywords based on the at least one offer keywords and the member profile data by identifying at least one additional keyword within the at least one offer keyword based on the affinity of the member profiles within the member profile data; identifies other keywords for which the identified member profiles have an associated affinity; selects a set of keywords including at least one of the identified keywords and at least one of the targeting keywords as targeting keywords for the specific offer, where the selected keywords target the desired audience for the specific offer; generates a set of targeting keywords that target a specific offer to a desired audience based on the selected set of keywords; and provides the set of targeting keywords. 15. The targeting system of claim 1 , wherein the set of targeting keywords is provided to an advertiser system.

13. A non-transitory computer storage device encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: identifying a click count for an image and a search query pair, the click count being based on a number of times that an image search result that includes a representation of the image has been selected when provided in response to the search query; identifying a hover count for the image and the search query pair, the hover count being based on a number of times that the representation of the image has been hovered over by a pointer when the image search result has been provided in response to the search query; adjusting the hover count using a hover weighting to determine an adjusted hover count, the hover weighting being based on a total click count for the search query; determining a quality measure for the image with respect to the search query, the quality measure being based at least on the click count and the adjusted hover count; ranking the image relative to a plurality of images for the search query based at least in part on the quality measure for the image; selecting one or more images from a set of images that includes the image and the plurality of images based on the ranking, wherein each particular image in the set of images is ranked based on a respective quality measure for the particular image; generating search results that reference the one or more images; and transmitting the search results for presentation.

13. A non-transitory computer storage device encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: identifying a click count for an image and a search query pair, the click count being based on a number of times that an image search result that includes a representation of the image has been selected when provided in response to the search query; identifying a hover count for the image and the search query pair, the hover count being based on a number of times that the representation of the image has been hovered over by a pointer when the image search result has been provided in response to the search query; adjusting the hover count using a hover weighting to determine an adjusted hover count, the hover weighting being based on a total click count for the search query; determining a quality measure for the image with respect to the search query, the quality measure being based at least on the click count and the adjusted hover count; ranking the image relative to a plurality of images for the search query based at least in part on the quality measure for the image; selecting one or more images from a set of images that includes the image and the plurality of images based on the ranking, wherein each particular image in the set of images is ranked based on a respective quality measure for the particular image; generating search results that reference the one or more images; and transmitting the search results for presentation. 15. The non-transitory computer storage device of claim 13 , wherein determining the quality measure for the image comprises: identifying a query hover count for the search query, the query hover count specifying a total number of hovers for image and search query pairs that include the search query as a member; adjusting the query hover count using the hover weighting to generate an adjusted query hover count; determining a total query selection count for the search query based on the adjusted query hover count and the total click count; determining a total image selection count for the image based on the click count and the adjusted hover count; and determining the quality measure for the image based on the total image selection count and the total query selection count.

1. A method comprising the steps: receiving, at a computing device over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating, via at least one processor of the computing device, a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying, via at least one processor of the computing device, at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting, via at least one processor of the computing device, one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, at the computing device over the network by the computing device, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating, via at least one processor of the computing device, a dynamic webpage having content relating to the user context query.

1. A method comprising the steps: receiving, at a computing device over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating, via at least one processor of the computing device, a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying, via at least one processor of the computing device, at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting, via at least one processor of the computing device, one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, at the computing device over the network by the computing device, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating, via at least one processor of the computing device, a dynamic webpage having content relating to the user context query. 12. The method of claim 1 , further comprising: inserting, via the network, the at least one data object of the at least one entry from the advertisement database into the dynamic webpage; transmitting, over the network, the dynamic webpage to the user; and charging the advertiser a fee associated with the selected one of the plurality of entries on the context query bid database when a user interface event relating to the dynamic webpage occurs.

1. A method for multilingual administration of enterprise data, the method comprising: retrieving, by at least one device, enterprise data comprising text and metadata; extracting, by the at least one device, the text and the metadata from the enterprise data for rendering from a digital media file, the extracted text and the extracted metadata being in a source language; selecting, by the at least one device, a target language from among a plurality of target languages based on a data type for the enterprise data; translating, by the at least one device, the extracted text and the extracted metadata in the source language to translated text and translated metadata in the target language; converting, by the at least one device, the translated text to synthesized speech in the target language; recording, by the at least one device, the synthesized speech in the target language in a digital media file; and storing the translated text as metadata associated with the digital media file.

1. A method for multilingual administration of enterprise data, the method comprising: retrieving, by at least one device, enterprise data comprising text and metadata; extracting, by the at least one device, the text and the metadata from the enterprise data for rendering from a digital media file, the extracted text and the extracted metadata being in a source language; selecting, by the at least one device, a target language from among a plurality of target languages based on a data type for the enterprise data; translating, by the at least one device, the extracted text and the extracted metadata in the source language to translated text and translated metadata in the target language; converting, by the at least one device, the translated text to synthesized speech in the target language; recording, by the at least one device, the synthesized speech in the target language in a digital media file; and storing the translated text as metadata associated with the digital media file. 6. The method of claim 1 further comprising displaying the metadata describing the digital media file thereby rendering the translated text of the enterprise data.

1. An electronic device, comprising: a display; a touch-sensitive keyboard; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a text entry area on the display; detecting a first input on the touch-sensitive keyboard, the touch-sensitive keyboard including one or more character keys; in accordance with a determination that the first input corresponds to activation of a character key on the touch-sensitive keyboard, entering a first character corresponding to the character key into the text entry area; in accordance with a determination that the first input corresponds to a first portion of a character drawn on the touch-sensitive keyboard and in accordance with detecting that the first input starts in a predefined region of the touch-sensitive keyboard that is a smaller subset of area than the entire keyboard area and that includes one or more character keys: determining one or more candidate characters for the drawn first portion of the character; and displaying a candidate character selection interface on the display, including displaying at least one of the candidate characters in the candidate character selection interface; while displaying the candidate character selection interface on the display, detecting a second input that selects a respective candidate character within the candidate character selection interface; and in response to detecting the second input, entering the selected respective candidate character into the text entry area.

1. An electronic device, comprising: a display; a touch-sensitive keyboard; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a text entry area on the display; detecting a first input on the touch-sensitive keyboard, the touch-sensitive keyboard including one or more character keys; in accordance with a determination that the first input corresponds to activation of a character key on the touch-sensitive keyboard, entering a first character corresponding to the character key into the text entry area; in accordance with a determination that the first input corresponds to a first portion of a character drawn on the touch-sensitive keyboard and in accordance with detecting that the first input starts in a predefined region of the touch-sensitive keyboard that is a smaller subset of area than the entire keyboard area and that includes one or more character keys: determining one or more candidate characters for the drawn first portion of the character; and displaying a candidate character selection interface on the display, including displaying at least one of the candidate characters in the candidate character selection interface; while displaying the candidate character selection interface on the display, detecting a second input that selects a respective candidate character within the candidate character selection interface; and in response to detecting the second input, entering the selected respective candidate character into the text entry area. 6. The device of claim 1 , including instructions for: after entering the first character, detecting activation of one or more character keys on the touch-sensitive keyboard; in response to detecting activation of one or more character keys on the touch-sensitive keyboard, entering characters corresponding to the one or more activated character keys into the text entry area; detecting a fourth input; in response to detecting the fourth input, displaying one or more characters that correspond to a romanization corresponding to the sequence of the first character and the characters corresponding to the one or more activated character keys; while displaying the one or more characters that correspond to the romanization, detecting a fifth input that selects a respective character of the displayed characters that correspond to the romanization; and in response to detecting the fifth input, entering the selected respective character into the text entry area.

1. A computer program product for performing application search, the computer program product comprising a non-transitory computer-readable storage medium storing instructions that, when executed, cause at least one central processing unit (CPU) of a computing device to: display an application search interface on a display of the computing device; receive an application search query via the application search interface, wherein the application search query includes an entity having an entity type; transmit the application search query via a network interface of the computing device; receive application search results in response to transmitting the application search query, wherein the application search results indicate a list of ranked applications operable to present information related to the entity, the application search results include metadata for the list of ranked applications, and the metadata includes respective application images, application titles, and application descriptions; and display a first application from the application search results, wherein displaying the first application includes: displaying an application icon based on the respective application image for the first application; displaying text based on the respective application title and the respective application description for the first application; displaying a first indication that is associated with a first user-selectable link for a first edition of the first application, wherein the first indication describes that the first edition of the first application is compatible with a first device; and displaying a second indication that is associated with a second user-selectable link for a second edition of the first application, wherein the second indication describes that the second edition of the first application is compatible with a second device.

1. A computer program product for performing application search, the computer program product comprising a non-transitory computer-readable storage medium storing instructions that, when executed, cause at least one central processing unit (CPU) of a computing device to: display an application search interface on a display of the computing device; receive an application search query via the application search interface, wherein the application search query includes an entity having an entity type; transmit the application search query via a network interface of the computing device; receive application search results in response to transmitting the application search query, wherein the application search results indicate a list of ranked applications operable to present information related to the entity, the application search results include metadata for the list of ranked applications, and the metadata includes respective application images, application titles, and application descriptions; and display a first application from the application search results, wherein displaying the first application includes: displaying an application icon based on the respective application image for the first application; displaying text based on the respective application title and the respective application description for the first application; displaying a first indication that is associated with a first user-selectable link for a first edition of the first application, wherein the first indication describes that the first edition of the first application is compatible with a first device; and displaying a second indication that is associated with a second user-selectable link for a second edition of the first application, wherein the second indication describes that the second edition of the first application is compatible with a second device. 6. The computer program product of claim 1 , wherein, in response to the entity type being a song entity: the application search results indicate that the entity corresponds with a song object; and the first application enables playback of the song object and/or displays a review of the song object; and displaying the text includes indicating that the first application enables the playback of the song object and/or displays the review of the song object.

13. A method for generating metadata relating to a media object, the method comprising: determining input data relating to the media object, the input data based on the content of the media object and existing metadata associated with the media object; applying a machine learning algorithm to the input data using a processor, the machine learning algorithm generating new metadata; and recording a correspondence between the new metadata and the media object.

13. A method for generating metadata relating to a media object, the method comprising: determining input data relating to the media object, the input data based on the content of the media object and existing metadata associated with the media object; applying a machine learning algorithm to the input data using a processor, the machine learning algorithm generating new metadata; and recording a correspondence between the new metadata and the media object. 18. The method of claim 13 , wherein the existing metadata comprises at least one of: user behavior data and market data.

11. A method, comprising: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign; identifying a change made to the paid portion of the search advertising campaign; determining, with a computing device and based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating, with the computing device, a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in a storage medium in association with an indication of the change.

11. A method, comprising: receiving data indicative of search traffic directed to a website, the search traffic resulting from an unpaid portion of a search advertising campaign and a paid portion of the search advertising campaign; identifying a change made to the paid portion of the search advertising campaign; determining, with a computing device and based on the received data: a first volume of search traffic resulting from the unpaid portion before the change, a second volume of search traffic resulting from the unpaid portion after the change, a third volume of search traffic resulting from the paid portion before the change, and a fourth volume of search traffic resulting from the paid portion after the change; generating, with the computing device, a synergy score based upon the first volume, the second volume, the third volume and the fourth volume, wherein the synergy score quantifies an impact of the change on the search traffic resulting from the unpaid portion; and storing the synergy score in a storage medium in association with an indication of the change. 14. The method of claim 11 wherein the change comprises beginning advertising for at least a first keyword.

1. A method for automatically processing electronic information messages, comprising: receiving an original electronic information message on an application on a server network device with one or more processors via a communications network for a target network device with one or more processors; quantifying the original electronic information with one or more information theory methods by measuring an entropy of the original electronic information; parsing on the application on the server network device using the quantified original electronic information message with the one or more information theory methods to identify portions of one or more keywords in the original electronic information message; generating automatically via the application one or more whole keywords from the identified portions of the one or more keywords using the one or more information theory methods, wherein generating a whole keyword only from a portion of a keyword creates whole keywords quicker and with less processing power than would be required from parsing whole keywords; generating automatically via the application one or more search engine queries including the generated one or more whole keywords; submitting automatically via the application the generated one or more search engine queries from the server network device to one or more search engines via the communications network; receiving query results from the one or more search engines on the application via the communications network; selecting on the application one or more electronic links from the one or more query results; collecting automatically on the application additional electronic information via the communications network by sending a selection input to the selected one or more electronic links; adding on the application dynamic hierarchical electronic links in a pre-determined hierarchy linking the automatically collected additional electronic information to the generated one or more whole keywords in the original electronic message, thereby creating a modified electronic information message; including the dynamic hierarchical links in the pre-determined hierarchy in a pre-determined order including from a first order position to a last order position including: emergency information, time-specific information, paid advertising information, general advertising information, general information, public interest information and public service information for the generated one or more whole keywords, wherein an individual dynamic hierarchical link is added or not added to an order position based on availability of electronic information for the order position, wherein the dynamic hierarchical electronic links are linked through the application on the server network device and are dynamically and automatically adjusted by removing original electronic links to original automatically collected additional electronic information and adding to new electronic links to different automatically collected additional electronic information for the modified electronic message based on a change in one or more pre-determined situations; providing access of the dynamic hierarchical electronic links with the additional collected electronic information from the modified electronic information message via the pre-determined hierarchy based on information content of the original electronic information message, wherein the dynamic hierarchical electronic links include the plurality of electronic links in the pre-determined order and wherein an individual dynamic hierarchical electronic link includes another plurality of electronic links in another pre-determined order; sending the modified electronic message from the application on the server network device to the target network device via the communications network; dynamically and automatically adjusting the dynamic hierarchical electronic links in the modified electronic message on the target network device from the application on the server network device via the communications network whenever one or more of the pre-determined situations affecting the dynamic hierarchical links change, the adjusting including adding new different electronic links for new different automatically collected additional electronic information to the dynamic hierarchical electronic links and modifying one or more of a plurality of font characteristics of a font used to display to the generated one or more whole keywords in the modified electronic message on the target network device.

1. A method for automatically processing electronic information messages, comprising: receiving an original electronic information message on an application on a server network device with one or more processors via a communications network for a target network device with one or more processors; quantifying the original electronic information with one or more information theory methods by measuring an entropy of the original electronic information; parsing on the application on the server network device using the quantified original electronic information message with the one or more information theory methods to identify portions of one or more keywords in the original electronic information message; generating automatically via the application one or more whole keywords from the identified portions of the one or more keywords using the one or more information theory methods, wherein generating a whole keyword only from a portion of a keyword creates whole keywords quicker and with less processing power than would be required from parsing whole keywords; generating automatically via the application one or more search engine queries including the generated one or more whole keywords; submitting automatically via the application the generated one or more search engine queries from the server network device to one or more search engines via the communications network; receiving query results from the one or more search engines on the application via the communications network; selecting on the application one or more electronic links from the one or more query results; collecting automatically on the application additional electronic information via the communications network by sending a selection input to the selected one or more electronic links; adding on the application dynamic hierarchical electronic links in a pre-determined hierarchy linking the automatically collected additional electronic information to the generated one or more whole keywords in the original electronic message, thereby creating a modified electronic information message; including the dynamic hierarchical links in the pre-determined hierarchy in a pre-determined order including from a first order position to a last order position including: emergency information, time-specific information, paid advertising information, general advertising information, general information, public interest information and public service information for the generated one or more whole keywords, wherein an individual dynamic hierarchical link is added or not added to an order position based on availability of electronic information for the order position, wherein the dynamic hierarchical electronic links are linked through the application on the server network device and are dynamically and automatically adjusted by removing original electronic links to original automatically collected additional electronic information and adding to new electronic links to different automatically collected additional electronic information for the modified electronic message based on a change in one or more pre-determined situations; providing access of the dynamic hierarchical electronic links with the additional collected electronic information from the modified electronic information message via the pre-determined hierarchy based on information content of the original electronic information message, wherein the dynamic hierarchical electronic links include the plurality of electronic links in the pre-determined order and wherein an individual dynamic hierarchical electronic link includes another plurality of electronic links in another pre-determined order; sending the modified electronic message from the application on the server network device to the target network device via the communications network; dynamically and automatically adjusting the dynamic hierarchical electronic links in the modified electronic message on the target network device from the application on the server network device via the communications network whenever one or more of the pre-determined situations affecting the dynamic hierarchical links change, the adjusting including adding new different electronic links for new different automatically collected additional electronic information to the dynamic hierarchical electronic links and modifying one or more of a plurality of font characteristics of a font used to display to the generated one or more whole keywords in the modified electronic message on the target network device. 3. The method of claim 1 wherein the electronic message is an electronic mail (e-mail) message, an instant message (IM), a Short Message Service (SMS) message, a Multimedia Messaging Service (MMS) message, a social networking message or a tweet message.

1. A method for presenting a series of exercise books and story books through a literacy software program to collectively teach all four of the language skills of phonology, semantics, syntax, and text, the method being implemented on a computer system including a computer-readable storage medium comprising executable instructions stored thereon that, when executed, cause the following operations to be performed: presenting on a display device, through a computer processor coupled with the display device, a first exercise book of the series of exercise books, each exercise book comprising a set of language skills exercises introducing a targeted set of content words and non-content words; determining, at the computer processor, an associated story book to present based on a shared content property of the associated story book and one or more exercise books including the first exercise book after user completion of the one or more exercise books from the series of exercise books, the shared content property being a story of the associated story book consisting only of those content words and non-content words that were introduced by the one or more previously completed exercise books from the series of exercise books such that the user viewing the associated story book on the display device is exposed only to those content words and non-contents words that were previously introduced with the language skills exercises of the one or more previously completed exercise books; and presenting on the display device, by the computer processor, the associated story book.

1. A method for presenting a series of exercise books and story books through a literacy software program to collectively teach all four of the language skills of phonology, semantics, syntax, and text, the method being implemented on a computer system including a computer-readable storage medium comprising executable instructions stored thereon that, when executed, cause the following operations to be performed: presenting on a display device, through a computer processor coupled with the display device, a first exercise book of the series of exercise books, each exercise book comprising a set of language skills exercises introducing a targeted set of content words and non-content words; determining, at the computer processor, an associated story book to present based on a shared content property of the associated story book and one or more exercise books including the first exercise book after user completion of the one or more exercise books from the series of exercise books, the shared content property being a story of the associated story book consisting only of those content words and non-content words that were introduced by the one or more previously completed exercise books from the series of exercise books such that the user viewing the associated story book on the display device is exposed only to those content words and non-contents words that were previously introduced with the language skills exercises of the one or more previously completed exercise books; and presenting on the display device, by the computer processor, the associated story book. 3. The method of claim 1 , wherein the user interface device interacts with at least one of a speech recognition software program and a pattern recognition software program stored on the computer memory storage device so that the user can interact with the literacy software program according to any of spoken words or written text, respectively.

8. A system for multimedia summary generation, wherein the system comprises: a processor containing a plurality of modules, including: a transmitter/receiver module for transmitting/receiving data; a multimedia source capturing module for capturing multimedia information from the multimedia source, wherein the multimedia information comprises at least a video clip or a picture; a multimedia source processing module coupled to the multimedia source capturing module for receiving the multimedia information captured by the multimedia source capturing module and for processing the video clip and the picture of the multimedia information according to a predetermined condition to generate a multimedia summary candidate, wherein the predetermined condition comprises at least a system setting value, an overlapping time, a maximum video clip length, a minimum video clip length, a people capturing ratio or a combination thereof, for determining a start point and an end point of the video clip, wherein the predetermined condition further comprises screening video clips and pictures similar to the video clip and the picture from the multimedia information by using a clustering algorithm to form a multimedia summary candidate group; a multimedia source summary generation module coupled to the multimedia source processing module for receiving the multimedia summary candidate to generate a multimedia summary list, wherein the multimedia source summary generation module checks whether the multimedia summary list contains a predetermined threshold, the multimedia source summary generation module outputs the multimedia summary candidate to join the multimedia summary list when no threshold is predetermined, the multimedia source summary generation module checks whether the multimedia summary candidate meets the predetermined threshold when the threshold is predetermined, the multimedia source summary generation module joins the multimedia summary candidate to the multimedia summary list when the multimedia summary candidate meets the predetermined threshold, the multimedia source summary generation module ignores the multimedia summary candidate when the multimedia summary candidate does not meet the predetermined threshold, and the multimedia source summary generation module combines the multimedia summary candidate in the multimedia summary candidate list to generate a multimedia summary; the multimedia source summary generation module sends message of the video clips and pictures similar to the video clip and the picture from the multimedia information to generate an Internet spread website via the Internet after forming the multimedia summary candidate group; wherein the modules are operated under the control of the processor; wherein the predetermined threshold of the multimedia source summary generation module comprises at least a number of users selecting the multimedia summary candidate, a ratio of the number of users selecting the multimedia summary candidate, or a combination therefore.

8. A system for multimedia summary generation, wherein the system comprises: a processor containing a plurality of modules, including: a transmitter/receiver module for transmitting/receiving data; a multimedia source capturing module for capturing multimedia information from the multimedia source, wherein the multimedia information comprises at least a video clip or a picture; a multimedia source processing module coupled to the multimedia source capturing module for receiving the multimedia information captured by the multimedia source capturing module and for processing the video clip and the picture of the multimedia information according to a predetermined condition to generate a multimedia summary candidate, wherein the predetermined condition comprises at least a system setting value, an overlapping time, a maximum video clip length, a minimum video clip length, a people capturing ratio or a combination thereof, for determining a start point and an end point of the video clip, wherein the predetermined condition further comprises screening video clips and pictures similar to the video clip and the picture from the multimedia information by using a clustering algorithm to form a multimedia summary candidate group; a multimedia source summary generation module coupled to the multimedia source processing module for receiving the multimedia summary candidate to generate a multimedia summary list, wherein the multimedia source summary generation module checks whether the multimedia summary list contains a predetermined threshold, the multimedia source summary generation module outputs the multimedia summary candidate to join the multimedia summary list when no threshold is predetermined, the multimedia source summary generation module checks whether the multimedia summary candidate meets the predetermined threshold when the threshold is predetermined, the multimedia source summary generation module joins the multimedia summary candidate to the multimedia summary list when the multimedia summary candidate meets the predetermined threshold, the multimedia source summary generation module ignores the multimedia summary candidate when the multimedia summary candidate does not meet the predetermined threshold, and the multimedia source summary generation module combines the multimedia summary candidate in the multimedia summary candidate list to generate a multimedia summary; the multimedia source summary generation module sends message of the video clips and pictures similar to the video clip and the picture from the multimedia information to generate an Internet spread website via the Internet after forming the multimedia summary candidate group; wherein the modules are operated under the control of the processor; wherein the predetermined threshold of the multimedia source summary generation module comprises at least a number of users selecting the multimedia summary candidate, a ratio of the number of users selecting the multimedia summary candidate, or a combination therefore. 11. The system according to claim 8 , wherein the multimedia information captured by the multimedia source capturing module further comprises a user-input information or a relevant content captured from the Internet.

1. A method of designing an essentially digital system, the method comprising: generating a description of the functionality and timing of the digital system, the description comprising a plurality of tasks; determining trade-off task optimization information; and designing the essentially digital system based at least upon an optimized description, wherein the optimized description further includes a description of a real-time operating system that uses the trade-off task optimization information,. wherein the method is executed on a processor-based system.

1. A method of designing an essentially digital system, the method comprising: generating a description of the functionality and timing of the digital system, the description comprising a plurality of tasks; determining trade-off task optimization information; and designing the essentially digital system based at least upon an optimized description, wherein the optimized description further includes a description of a real-time operating system that uses the trade-off task optimization information,. wherein the method is executed on a processor-based system. 2. The method of claim 1 , wherein the trade-off task optimization information comprises Pareto task optimization information.

23. A system for processing a text input within a man-machine interface (MMI) application framework, the system comprising: a memory configured to store a plurality of applications; a processor configured to: enable activation of an application from among the plurality of applications as an active application, enable said active application to create a new text editor, said new text editor being configured to perform under a constraint specified by said active application, enable said new text editor to generate a text edit view, said text edit view being configured to receive a text input in accordance with said constraint specified by said active application, enable said new text editor to receive said text input in accordance with said constraint specified by said active application, and enable encoding of said received text input, said encoding being capable of being changed based on said received text input.

23. A system for processing a text input within a man-machine interface (MMI) application framework, the system comprising: a memory configured to store a plurality of applications; a processor configured to: enable activation of an application from among the plurality of applications as an active application, enable said active application to create a new text editor, said new text editor being configured to perform under a constraint specified by said active application, enable said new text editor to generate a text edit view, said text edit view being configured to receive a text input in accordance with said constraint specified by said active application, enable said new text editor to receive said text input in accordance with said constraint specified by said active application, and enable encoding of said received text input, said encoding being capable of being changed based on said received text input. 24. The system of claim 23 , wherein said received text input comprises a predictive input, a multi-tap input or a numeric input.

1. A method comprising: receiving, by a processing device, a data set, wherein the data set is annotated with at least a first annotation and at least a second annotation, wherein at least the first annotation and the second annotation represent characteristics within the data set; determining, by the processing device, a first identifier from the first annotation and a second identifier from the second annotation; associating, by the processing device, the first identifier to the second identifier to generate at least one joined identifier, wherein the at least one joined identifier is placed between the first annotation and the second annotation; computing, by the processing device, a feature weight and a transition weight for the annotated data set based on the first annotation, the second annotation, and the at least one joined identifier and a transition between each of the first annotation, the second annotation and the at least one joined identifier; receiving, by the processing device, a second data set, wherein the second data set is un-annotated; and classifying, by the processing device, the second data set based on the computed feature weight and the transition weight from the first data set.

1. A method comprising: receiving, by a processing device, a data set, wherein the data set is annotated with at least a first annotation and at least a second annotation, wherein at least the first annotation and the second annotation represent characteristics within the data set; determining, by the processing device, a first identifier from the first annotation and a second identifier from the second annotation; associating, by the processing device, the first identifier to the second identifier to generate at least one joined identifier, wherein the at least one joined identifier is placed between the first annotation and the second annotation; computing, by the processing device, a feature weight and a transition weight for the annotated data set based on the first annotation, the second annotation, and the at least one joined identifier and a transition between each of the first annotation, the second annotation and the at least one joined identifier; receiving, by the processing device, a second data set, wherein the second data set is un-annotated; and classifying, by the processing device, the second data set based on the computed feature weight and the transition weight from the first data set. 3. The method of claim 1 wherein the data set and the second data set comprise a plurality of sentences having a plurality of words.

1. A method operational in a processing device, comprising: inputting data into the processing device in a formal, naturalistic, speakable, hybrid language, wherein the formal, naturalistic, speakable, hybrid language is characterized by having a completely defined set of non-ambiguous grammar rules and excludes natural languages; parsing the input data at the processing device into an internal format in such a way that a memory of an original grammar structure present in the input data is retained; comparing the parsed input data with previously stored data in a data/knowledge base according to non-statistical, logic operations to prove, disprove or determine if the meaning of the parsed input data is plausible; storing results of the evaluation in the data/knowledge base, wherein the input data is obtained from a plurality of different users and the data/knowledge base stores knowledge while recognizing, maintaining, and storing distinct realities for different users; and in reply to a question, generating one of an auditory or visual response at the processing device in the formal, naturalistic, speakable, hybrid language based on accumulated knowledge of the data/knowledge base, wherein for the same question, a first auditory or visual response for a first user is contradictory to a second auditory or visual response for a second user if the first and second users have different realities.

1. A method operational in a processing device, comprising: inputting data into the processing device in a formal, naturalistic, speakable, hybrid language, wherein the formal, naturalistic, speakable, hybrid language is characterized by having a completely defined set of non-ambiguous grammar rules and excludes natural languages; parsing the input data at the processing device into an internal format in such a way that a memory of an original grammar structure present in the input data is retained; comparing the parsed input data with previously stored data in a data/knowledge base according to non-statistical, logic operations to prove, disprove or determine if the meaning of the parsed input data is plausible; storing results of the evaluation in the data/knowledge base, wherein the input data is obtained from a plurality of different users and the data/knowledge base stores knowledge while recognizing, maintaining, and storing distinct realities for different users; and in reply to a question, generating one of an auditory or visual response at the processing device in the formal, naturalistic, speakable, hybrid language based on accumulated knowledge of the data/knowledge base, wherein for the same question, a first auditory or visual response for a first user is contradictory to a second auditory or visual response for a second user if the first and second users have different realities. 13. The method of claim 1 , wherein different veracity levels are associated with the different users, such veracity levels are utilized in generating the response from inconsistent knowledge stored in the data/knowledge base.

1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image.

1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. 12. The method of claim 1 , wherein the storing of the at least one computed feature includes a storage of a bounding box that defines the region of interest in the at least one image, whereby the region of interest represents an image area that is used to generate the at least one feature, and a reference to the at least one image, whereby the at least one image is stored on an image database.