Datasets:

patent

/

AIPD_nlp_sbert_dataset

like 0

1. A computer implemented method comprising the steps of: detecting a change to one or more conceptual paths, each path addressing a part of a structure of an ontology system, the ontology system being an application-independent representation of domain knowledge by a set of concepts and relationships between the concepts, the change being described by an ordered sequence of first operators defining semantic information on said change, the change comprising appending another structure to part of the ontology system structure, said another structure not being part of the ontology system structure before the change; defining one or more second operators that operate on a mapping from at least one application path of an intentional part of a data system to a conceptual path of the ontology system, the intentional part being prescribed by constraints on data elements and relationships between the data elements, each application path addressing a part of the structure of the data system, said one or more second operators being equivalent to said one or more first operators used to describe said change to said one or more conceptual paths addressing said part of the structure of said ontology system; and updating said mapping with said one or more equivalent second operators to reflect the change to said one or more conceptual paths addressing said part of the structure of the ontology system.

1. A computer implemented method comprising the steps of: detecting a change to one or more conceptual paths, each path addressing a part of a structure of an ontology system, the ontology system being an application-independent representation of domain knowledge by a set of concepts and relationships between the concepts, the change being described by an ordered sequence of first operators defining semantic information on said change, the change comprising appending another structure to part of the ontology system structure, said another structure not being part of the ontology system structure before the change; defining one or more second operators that operate on a mapping from at least one application path of an intentional part of a data system to a conceptual path of the ontology system, the intentional part being prescribed by constraints on data elements and relationships between the data elements, each application path addressing a part of the structure of the data system, said one or more second operators being equivalent to said one or more first operators used to describe said change to said one or more conceptual paths addressing said part of the structure of said ontology system; and updating said mapping with said one or more equivalent second operators to reflect the change to said one or more conceptual paths addressing said part of the structure of the ontology system. 6. The method as in claim 1 , wherein said change comprises inserting a further structure to a part of the ontology system structure, said further structure not being part of the ontology system structure before the change.

5. A computer-readable storage medium containing a program which, when executed, performs an operation for managing data objects in a content management system (CMS), the operation comprising: accessing a first data object managed by the CMS, wherein the first data object includes a collection of one or more data object fragments, wherein a first fragment of the one or more data object fragments is referenced by a second data object stored in the CMS, and wherein the first data object and the second data object are composed according to respective schemas; receiving a modified version of the first data object to store in the CMS wherein the modified version of the first data object includes a modified version of the first fragment; fragmenting the modified version first data object into the one or more data object fragments; validating the modified version of the first fragment against the schema associated with the second data object; and upon determining that the modified version of the first fragment fails to validate against the schema associated with the second data object, performing a corrective action specified by the CMS, wherein the corrective action comprises generating an unmodified version of the first fragment, and further comprises one of: (i) incorporating the content from the modified version of the first fragment into the first data object, associating the unmodified version of the first fragment with the second data object, and discarding the modified version of the first fragment; and (ii) incorporating the content from the unmodified version of the first fragment into the second data object, associating the modified version of the first fragment with the first data object, and discarding the unmodified version of the first fragment.

5. A computer-readable storage medium containing a program which, when executed, performs an operation for managing data objects in a content management system (CMS), the operation comprising: accessing a first data object managed by the CMS, wherein the first data object includes a collection of one or more data object fragments, wherein a first fragment of the one or more data object fragments is referenced by a second data object stored in the CMS, and wherein the first data object and the second data object are composed according to respective schemas; receiving a modified version of the first data object to store in the CMS wherein the modified version of the first data object includes a modified version of the first fragment; fragmenting the modified version first data object into the one or more data object fragments; validating the modified version of the first fragment against the schema associated with the second data object; and upon determining that the modified version of the first fragment fails to validate against the schema associated with the second data object, performing a corrective action specified by the CMS, wherein the corrective action comprises generating an unmodified version of the first fragment, and further comprises one of: (i) incorporating the content from the modified version of the first fragment into the first data object, associating the unmodified version of the first fragment with the second data object, and discarding the modified version of the first fragment; and (ii) incorporating the content from the unmodified version of the first fragment into the second data object, associating the modified version of the first fragment with the first data object, and discarding the unmodified version of the first fragment. 6. The computer-readable medium of claim 5 , wherein the schema for the first data object defines the allowable content or structure of the first data object and the schema for the second data object defines the allowable content or structure of the second data object.

6. A non-transitory computer readable storage medium comprising a computer readable program for configuring and executing card content management (CCM) operations in a declarative manner, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: composing a CCM operation declaration, wherein each CCM operation includes one or more CCM scripts, the composing the CCM operation declaration including graphically authoring the CCM operation declaration, wherein the graphically authoring includes dragging and dropping icons representing scripts into a field and connecting the icons into a sequence using constructs; storing the CCM operation declaration in memory; when provisioning is needed, fetching applicable scripts for the CCM operation declaration and creating parsed scripts by parsing the applicable scripts; preparing an execution context needed for each script in the CCM operation declaration, wherein all needed parameter values are set and the parsed scripts are stored in an iterator in a desired order of execution; and executing the scripts in an order specified in the CCM operation declaration.

6. A non-transitory computer readable storage medium comprising a computer readable program for configuring and executing card content management (CCM) operations in a declarative manner, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: composing a CCM operation declaration, wherein each CCM operation includes one or more CCM scripts, the composing the CCM operation declaration including graphically authoring the CCM operation declaration, wherein the graphically authoring includes dragging and dropping icons representing scripts into a field and connecting the icons into a sequence using constructs; storing the CCM operation declaration in memory; when provisioning is needed, fetching applicable scripts for the CCM operation declaration and creating parsed scripts by parsing the applicable scripts; preparing an execution context needed for each script in the CCM operation declaration, wherein all needed parameter values are set and the parsed scripts are stored in an iterator in a desired order of execution; and executing the scripts in an order specified in the CCM operation declaration. 8. The computer readable storage medium as recited in claim 6 , wherein graphically authoring includes representing scripts as icons and entering data associated with the script when an icon is selected.

9. A system comprising: one or more processors; and one or more computer-readable storage media embodying computer-readable instructions which, when executed by the one or more processors, implement a method comprising: receiving a webpage; building a display tree associated with the webpage; setting at least one flag on a display tree node of the display tree associated with the webpage corresponding to an element for which a default touch behavior has been specified using a declarative style; conducting an independent hit test on the display tree associated with the webpage; and calling a manipulation thread for direct manipulation of one or more elements for which a default touch behavior has been specified.

9. A system comprising: one or more processors; and one or more computer-readable storage media embodying computer-readable instructions which, when executed by the one or more processors, implement a method comprising: receiving a webpage; building a display tree associated with the webpage; setting at least one flag on a display tree node of the display tree associated with the webpage corresponding to an element for which a default touch behavior has been specified using a declarative style; conducting an independent hit test on the display tree associated with the webpage; and calling a manipulation thread for direct manipulation of one or more elements for which a default touch behavior has been specified. 12. The system of claim 9 , wherein the default touch behavior comprises enabling or disabling a double-tap-zoom manipulation.

1. A non-transitory computer readable medium having computer executable instructions for performing a method of processing expense information, the method comprising: receiving scanned information of a receipt from a scanner, the scanned information including information regarding various types of receipts having various formats and having different sizes, each of said receipts containing expense information printed thereon; processing said scanned information including numerical data in the receipt to obtain said expense information from said scanned information; categorizing said expense information for each receipt into one or more predetermined categories to obtain categorized information for each receipt, wherein said categorized information for each receipt is combined with categorized information for other said receipts to produce report information for one or more of said predetermined categories, wherein the various types of receipts include grocery receipts, purchase receipts, credit card receipts and bank statements.

1. A non-transitory computer readable medium having computer executable instructions for performing a method of processing expense information, the method comprising: receiving scanned information of a receipt from a scanner, the scanned information including information regarding various types of receipts having various formats and having different sizes, each of said receipts containing expense information printed thereon; processing said scanned information including numerical data in the receipt to obtain said expense information from said scanned information; categorizing said expense information for each receipt into one or more predetermined categories to obtain categorized information for each receipt, wherein said categorized information for each receipt is combined with categorized information for other said receipts to produce report information for one or more of said predetermined categories, wherein the various types of receipts include grocery receipts, purchase receipts, credit card receipts and bank statements. 7. A non-transitory computer readable medium as claimed in claim 1 , wherein the method further comprises: saving the expense information processed from the scanned receipts in Quicken Interchange Format, thereby allowing the expense information obtained from the scanned information to be imported by a financial management program.

9. One or more non-transitory machine-readable media storing instructions that are executable by one or more processing devices to perform operations comprising: comparing, for each entity of a plurality of entities, a number of connections associated with the entity, in one or more corresponding social graphs, to a threshold number of connections to other entities; based on the comparison, identifying one or more first entities of the plurality of entities that are associated with a number of connections greater than the threshold number of connections to other entities, and in response: identifying first content items in a search index that are authored by the one or more first entities, and associating, for each first content item, a respective author restrict with the first content item, the author restrict comprising data identifying the respective entity that authored the first content item; based on the comparison, identifying one or more second entities of the plurality of entities that are associated with a number of connections less than the threshold number of connections to other entities, and in response: identifying second content items in the search index that are authored by he one or more second items, and associating, for each second content item, one or more searcher restricts with the second content item, each searcher restrict of the one or more searcher restricts comprising data that identifies an other entity of a subset of the one or more other entities that are social connected to the second entity that authored the second content item, wherein the first content items are not associated with any searcher restricts; updating the search index to include the respective author restricts associated with each first content item and the respective one or more searcher restricts associated with each second content item; and storing the updated search index in memory.

9. One or more non-transitory machine-readable media storing instructions that are executable by one or more processing devices to perform operations comprising: comparing, for each entity of a plurality of entities, a number of connections associated with the entity, in one or more corresponding social graphs, to a threshold number of connections to other entities; based on the comparison, identifying one or more first entities of the plurality of entities that are associated with a number of connections greater than the threshold number of connections to other entities, and in response: identifying first content items in a search index that are authored by the one or more first entities, and associating, for each first content item, a respective author restrict with the first content item, the author restrict comprising data identifying the respective entity that authored the first content item; based on the comparison, identifying one or more second entities of the plurality of entities that are associated with a number of connections less than the threshold number of connections to other entities, and in response: identifying second content items in the search index that are authored by he one or more second items, and associating, for each second content item, one or more searcher restricts with the second content item, each searcher restrict of the one or more searcher restricts comprising data that identifies an other entity of a subset of the one or more other entities that are social connected to the second entity that authored the second content item, wherein the first content items are not associated with any searcher restricts; updating the search index to include the respective author restricts associated with each first content item and the respective one or more searcher restricts associated with each second content item; and storing the updated search index in memory. 11. The one or more non-transitory machine-readable media of claim 9 , wherein the operations comprise: identifying a newly-created association between two entities of the plurality of entities, a first entity of the two entities being authoring a third content item that is associated with an author restrict comprising data that identifies the first entity; and issuing, to a second entity of the two entities, the author restrict comprising data that identifies the first entity for the first of the two entities.

10. A method for extending a voice server to add text exchange capabilities, the method comprising acts of: establishing a real-time interactive dialog between a text exchange client and a speech application executing in a VoiceXML server; during the interactive dialogue, dynamically translating text entered into the text exchange client that is grammatically part of a text exchange specific language into corresponding text that is grammatically part of a conversational language using a translation table which is configurable by a user of the text exchange client; sending the corresponding text that is grammatically part of a conversational language to the speech application for automatic output generation; receiving, from the speech application, an automatic output message responsive to the text entered into the text exchange client; and sending output text related to the automatic output message to the text exchange client.

10. A method for extending a voice server to add text exchange capabilities, the method comprising acts of: establishing a real-time interactive dialog between a text exchange client and a speech application executing in a VoiceXML server; during the interactive dialogue, dynamically translating text entered into the text exchange client that is grammatically part of a text exchange specific language into corresponding text that is grammatically part of a conversational language using a translation table which is configurable by a user of the text exchange client; sending the corresponding text that is grammatically part of a conversational language to the speech application for automatic output generation; receiving, from the speech application, an automatic output message responsive to the text entered into the text exchange client; and sending output text related to the automatic output message to the text exchange client. 13. The method of claim 10 , wherein the text exchange specific language includes text exchange slang.

10. A computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to access a database having postal addresses stored therein; computer readable program code configured to, in response to accessing the database: cluster a plurality of the postal addresses based on similarity, and thereby forming at least one cluster of postal addresses; and within an identified cluster of postal addresses, identify one or more synonyms relative to one or more components of postal addresses, wherein the one or synonyms comprise variants of the one or more components; and computer readable program code configured to, with respect to one or more components of the postal addresses in the identified cluster of postal addresses, identify a standardized identifier from among the one or more synonyms and applying the standardized identifier to postal addresses within the cluster of postal addresses.

10. A computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to access a database having postal addresses stored therein; computer readable program code configured to, in response to accessing the database: cluster a plurality of the postal addresses based on similarity, and thereby forming at least one cluster of postal addresses; and within an identified cluster of postal addresses, identify one or more synonyms relative to one or more components of postal addresses, wherein the one or synonyms comprise variants of the one or more components; and computer readable program code configured to, with respect to one or more components of the postal addresses in the identified cluster of postal addresses, identify a standardized identifier from among the one or more synonyms and applying the standardized identifier to postal addresses within the cluster of postal addresses. 14. The computer program product according to claim 10 , wherein the computer readable program code further comprises: computer readable program code configured to identify one or more missing components of a postal address belonging to a cluster; and computer readable program code configured to add the one or more missing components to the postal address belonging to a cluster.

8. A computer implemented method of integrating a product data management system, the method comprising: in a processor processing machine executable instructions, the instructions causing the processor to perform the steps of: defining a requirements component that manages and traces changes in requirements data and linking the requirements component to a requirements system database; defining a software component that tracks software properties via a revision control repository database; defining a hardware component that tracks properties of at least one piece of an electronic device; defining a firmware component that tracks properties of a piece of firmware for controlling operation of the at least one piece of electronic device; defining a technical documents component configured to transmit technical documents between the technical document component and an external documents database, wherein the stored technical documents support the software, hardware and firmware components; and defining connections between said requirement components and said software component, said hardware component and said firmware component wherein a change in any one of the software, hardware or firmware components creates a change in a requirement data managed by said requirements component and wherein said requirements component updates a property in at least one other component of the product data management system.

8. A computer implemented method of integrating a product data management system, the method comprising: in a processor processing machine executable instructions, the instructions causing the processor to perform the steps of: defining a requirements component that manages and traces changes in requirements data and linking the requirements component to a requirements system database; defining a software component that tracks software properties via a revision control repository database; defining a hardware component that tracks properties of at least one piece of an electronic device; defining a firmware component that tracks properties of a piece of firmware for controlling operation of the at least one piece of electronic device; defining a technical documents component configured to transmit technical documents between the technical document component and an external documents database, wherein the stored technical documents support the software, hardware and firmware components; and defining connections between said requirement components and said software component, said hardware component and said firmware component wherein a change in any one of the software, hardware or firmware components creates a change in a requirement data managed by said requirements component and wherein said requirements component updates a property in at least one other component of the product data management system. 9. The method of claim 8 , further comprising the processor performing the steps of: defining a plurality of connector components configured to connect said firmware component to an external requirements system database, an external repository database and the revision control repository database; defining a design artifacts component that manages files, properties, analyses, design and test data for a project design; defining a model component that manages an architecture framework and software based models; defining a code component that manages a collection of files to convert software files from a human readable form to a computer executable form; defining a working files component that manages properties and files including configuration files, libraries, settings and files needed to generate executable files; and defining a burn component for managing properties and files for executable files used to embed firmware code onto a programmable device.

5. The method of claim 1 , wherein the plurality of script files comprise a script file encoded in a JSR-223 scripting language.

5. The method of claim 1 , wherein the plurality of script files comprise a script file encoded in a JSR-223 scripting language. 6. The method of claim 5 , wherein the JSR-223 scripting language comprises at least one of Jython™, JRuby™, Groovy™, JACL™, and JavaScript® scripting languages.

7. A method according to claim 6 , wherein at least one feature derived from at least one individual electronic document instance characterizes a local patch within the individual electronic document instance.

7. A method according to claim 6 , wherein at least one feature derived from at least one individual electronic document instance characterizes a local patch within the individual electronic document instance. 9. A method according to claim 7 , wherein at least one feature derived from at least one individual electronic document instance comprises a color moment feature.

1. A system for displaying spine groups, comprising the at least one processor operable to function as: a unique group placement module to place unique spine groups selected from a set of spine groups around a shape defined in a display; a selection module to select one of the spine groups remaining in the set; a comparison module to compare the selected spine group to each of the unique spine groups in the display; an identification module to identify the unique spine group that is most similar to the selected spine group; and a group placement module to place the selected spine group adjacent to the unique spine group that is most similar.

1. A system for displaying spine groups, comprising the at least one processor operable to function as: a unique group placement module to place unique spine groups selected from a set of spine groups around a shape defined in a display; a selection module to select one of the spine groups remaining in the set; a comparison module to compare the selected spine group to each of the unique spine groups in the display; an identification module to identify the unique spine group that is most similar to the selected spine group; and a group placement module to place the selected spine group adjacent to the unique spine group that is most similar. 4. A system according to claim 1 , wherein the shape defined in the display comprises at least two concentric circles and the unique spine groups are placed around an innermost circle of the concentric circles.

26. The method according to claim 24 , wherein the substring generation frequency value has a constant increment amount for all substrings or has a different increment amount for each substring.

26. The method according to claim 24 , wherein the substring generation frequency value has a constant increment amount for all substrings or has a different increment amount for each substring. 27. The method according to claim 26 , wherein a corresponding increment amount is in reverse proportional to the number of substrings standardized by traffic amount appeared on a network and gives a larger weight to a frequency of a recent observation period when each of the substrings has a different increment amount.

12. A computing device configured to convert audio data to text data, comprising: an audio capture device configured to receive audio data, the received audio data representing spoken utterances; an automatic speech recognition (ASR) module configured to transform the received audio data into a sequence of speech units represented in the audio data; at least one processor; a memory device including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to determine a first duration of the sequence of speech units of the received audio data; to determine, using the first duration, an expected duration of a single speech unit of the received audio data in the sequence of speech units; to determine, by the ASR module, a second duration of the single speech unit; to determine a duration score of the single speech unit, the duration score corresponding to the second duration in relation to the expected duration; to determine a speech recognition result based at least in part on the duration score of the single speech unit, wherein the speech recognition result is the text data corresponding to the received audio data representing speech; and to cause a command to be executed using the text data.

12. A computing device configured to convert audio data to text data, comprising: an audio capture device configured to receive audio data, the received audio data representing spoken utterances; an automatic speech recognition (ASR) module configured to transform the received audio data into a sequence of speech units represented in the audio data; at least one processor; a memory device including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to determine a first duration of the sequence of speech units of the received audio data; to determine, using the first duration, an expected duration of a single speech unit of the received audio data in the sequence of speech units; to determine, by the ASR module, a second duration of the single speech unit; to determine a duration score of the single speech unit, the duration score corresponding to the second duration in relation to the expected duration; to determine a speech recognition result based at least in part on the duration score of the single speech unit, wherein the speech recognition result is the text data corresponding to the received audio data representing speech; and to cause a command to be executed using the text data. 14. The computing device of claim 12 , wherein the duration score is further based at least part on at least one of an absolute duration of the single speech unit, a duration ratio of a neighboring speech unit, or the second duration compared to a third duration of an utterance.

12. A system configured to route a facsimile, the system comprising a processor and logic in and/or executable by the processor to cause the processor to: receive text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by ascertaining a position of one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text of the facsimile for at least one of a meaning and a context of the text; route the facsimile or text thereof to one or more destinations based on the analysis; initiate a business process based on the analysis; detect a problem with the business process; generate a notification of the problem; and notify one or more entities of the problem, wherein the routing utilizes an outgoing communication device.

12. A system configured to route a facsimile, the system comprising a processor and logic in and/or executable by the processor to cause the processor to: receive text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by ascertaining a position of one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text of the facsimile for at least one of a meaning and a context of the text; route the facsimile or text thereof to one or more destinations based on the analysis; initiate a business process based on the analysis; detect a problem with the business process; generate a notification of the problem; and notify one or more entities of the problem, wherein the routing utilizes an outgoing communication device. 20. The system as recited in claim 12 , wherein at least one of the destinations corresponds to a recipient other than an intended recipient of the facsimile.

1. A computer-implemented method of reviewing and distributing digital content comprising: identifying a plurality of authors of digital content via a registration process wherein the plurality of authors agree to review digital content in exchange for review of their own digital content; receiving a submission from one of the plurality of authors including metadata for digital content to be reviewed; and effecting review of the digital content by at least one group of reviewers selected from others of the plurality of authors based on the metadata for the digital content and reviewer credentials for the others of the plurality of authors, wherein effecting review of the digital content includes selecting a group of reviewers from the others of the plurality of authors based on a default target quality level for the submission and the reviewer credentials of the others of the plurality of authors and feedback is provided to the one of the plurality of authors based on the review.

1. A computer-implemented method of reviewing and distributing digital content comprising: identifying a plurality of authors of digital content via a registration process wherein the plurality of authors agree to review digital content in exchange for review of their own digital content; receiving a submission from one of the plurality of authors including metadata for digital content to be reviewed; and effecting review of the digital content by at least one group of reviewers selected from others of the plurality of authors based on the metadata for the digital content and reviewer credentials for the others of the plurality of authors, wherein effecting review of the digital content includes selecting a group of reviewers from the others of the plurality of authors based on a default target quality level for the submission and the reviewer credentials of the others of the plurality of authors and feedback is provided to the one of the plurality of authors based on the review. 13. The computer-implemented method of claim 1 further comprising: receiving information identifying whether the one of the plurality of authors desires to distribute the digital content based on the feedback; and effecting transfer of the digital content to at least one distribution entity if the one of the plurality of authors desires to distribute the digital content.

1. A method for indexing web pages, the method comprising: crawling, by a computer, a plurality of web pages on a wide area network, each web page having text content and at least one image having an embedded spatial key; for each of the crawled web pages: extracting the spatial key from the image; storing an association between the text content and the spatial key on a computer readable medium; receiving a search request, the search request including a query and a location; determining at least one spatial key associated with the location; identifying the crawled web pages having text content relevant to the search query, the text content having an associated spatial key matching the spatial key associated with the location; and providing the identified web pages in response to the received query.

1. A method for indexing web pages, the method comprising: crawling, by a computer, a plurality of web pages on a wide area network, each web page having text content and at least one image having an embedded spatial key; for each of the crawled web pages: extracting the spatial key from the image; storing an association between the text content and the spatial key on a computer readable medium; receiving a search request, the search request including a query and a location; determining at least one spatial key associated with the location; identifying the crawled web pages having text content relevant to the search query, the text content having an associated spatial key matching the spatial key associated with the location; and providing the identified web pages in response to the received query. 4. The method of claim 1 , further comprising: for each of the crawled web pages, extracting a bounding area from the image, the bounding area defined by more than two points; and maintaining an association between the bounding area and the text content.

1. A method, comprising: analyzing handwriting data to recognize one or more objects depicted in the handwriting data, the handwriting data including a sketch of the one or more objects, analyzing the handwriting data comprising comparing the sketch of the one or more objects to images present in a database to determine if one or more of the images are similar to the sketch; determining if one or more applications of a plurality of applications are associated with the handwriting data based on the one or more objects recognized in the handwriting data, determining if one or more applications are associated with the handwriting data comprising: associating one or more keywords with each of the plurality of applications without associating any image with an application; determining one or more keywords associated with the one or more images that are determined to be similar to the sketch; and after determining the one or more keywords associated with the one or more images, determining if any applications are associated with the one or more keywords; and if one application is determined to be associated with the handwriting data, launching the one application.

1. A method, comprising: analyzing handwriting data to recognize one or more objects depicted in the handwriting data, the handwriting data including a sketch of the one or more objects, analyzing the handwriting data comprising comparing the sketch of the one or more objects to images present in a database to determine if one or more of the images are similar to the sketch; determining if one or more applications of a plurality of applications are associated with the handwriting data based on the one or more objects recognized in the handwriting data, determining if one or more applications are associated with the handwriting data comprising: associating one or more keywords with each of the plurality of applications without associating any image with an application; determining one or more keywords associated with the one or more images that are determined to be similar to the sketch; and after determining the one or more keywords associated with the one or more images, determining if any applications are associated with the one or more keywords; and if one application is determined to be associated with the handwriting data, launching the one application. 3. The method according to claim 1 , wherein the handwriting data includes text.

12. The text-to-speech method according to claim 11 , further comprising: g) determining if at least one of the substitution symbols cannot be read aloud; and h) converting the text template to the new text template by removing or replacing the substitution symbols that cannot be read aloud.

12. The text-to-speech method according to claim 11 , further comprising: g) determining if at least one of the substitution symbols cannot be read aloud; and h) converting the text template to the new text template by removing or replacing the substitution symbols that cannot be read aloud. 16. The text-to-speech method according to claim 12 , wherein if only a substitution symbol corresponding to an artist name can be read aloud, the information processing apparatus extracts the new text template having a substitution symbol corresponding to the artist name as a component.

2. The apparatus of claim 1 , wherein the first advertising content and the second advertising content are presented substantially in an order corresponding to the order in which the first location and second location are to be encountered during said journey.

2. The apparatus of claim 1 , wherein the first advertising content and the second advertising content are presented substantially in an order corresponding to the order in which the first location and second location are to be encountered during said journey. 3. The apparatus of claim 2 , wherein the first advertising content and the second advertising content are selected based at least in part on the respective available presentation times before the first location and second location are to be encountered during said journey.

1. A computer-implemented method comprising: obtaining a group of candidate content items for one or more streams of content from heterogeneous data sources; generating, with one or more processors, a model for a user comprising an interest of the user and a prior interaction of the user with the heterogeneous data sources; computing, with the one or more processors, an interestingness score for each candidate content item in the group by combining properties of each candidate content item over single-attribute properties using the model and based upon interestingness of each candidate content item to the user and an extent to which the candidate content item's popularity has changed within a geographic area associated with the user; comparing the interestingness score for each candidate content item with a threshold for a first interest type and a second interest type to determine which candidate content items have an interestingness score that exceeds the threshold for the first interest type or the second interest type; organizing a first content item and a second content item that have an interestingness score that exceeds the threshold in a first stream of content; providing the first stream of content for presentation in a first direction to the user; generating a user interface for configuring the one or more streams of content, the user interface comprising the first content item, the second content item and a marker, the marker associated with the second content item for the user to request a third content item related to the second content item; and responsive to receiving a selection of the marker associated with the second content item from the user, organizing the second and third content items in a second stream of content, providing the second stream of content for presentation in a second direction to the user, and updating the user interface to include the second stream of content.

1. A computer-implemented method comprising: obtaining a group of candidate content items for one or more streams of content from heterogeneous data sources; generating, with one or more processors, a model for a user comprising an interest of the user and a prior interaction of the user with the heterogeneous data sources; computing, with the one or more processors, an interestingness score for each candidate content item in the group by combining properties of each candidate content item over single-attribute properties using the model and based upon interestingness of each candidate content item to the user and an extent to which the candidate content item's popularity has changed within a geographic area associated with the user; comparing the interestingness score for each candidate content item with a threshold for a first interest type and a second interest type to determine which candidate content items have an interestingness score that exceeds the threshold for the first interest type or the second interest type; organizing a first content item and a second content item that have an interestingness score that exceeds the threshold in a first stream of content; providing the first stream of content for presentation in a first direction to the user; generating a user interface for configuring the one or more streams of content, the user interface comprising the first content item, the second content item and a marker, the marker associated with the second content item for the user to request a third content item related to the second content item; and responsive to receiving a selection of the marker associated with the second content item from the user, organizing the second and third content items in a second stream of content, providing the second stream of content for presentation in a second direction to the user, and updating the user interface to include the second stream of content. 6. The method of claim 1 , wherein the user interface further comprises a description of the first type of interest and a description of the second type of interest.

15. A computer system, comprising: one or more processors; a memory comprising a set of instructions which when executed causes the one or more processors to execute a method, the method comprising: receiving a plurality of comments respectively associated with a plurality of video clips from a plurality of videos stored in a video database; receiving comment metadata regarding each comment of the plurality of comments, including a category of a plurality of categories and one or more time values related to a video clip of the plurality of video clips, one or more computers receiving one or more criteria to apply to the comment metadata, wherein the one or more criteria specify at least a particular category of the plurality of categories; the one or more computers selecting two or more video clips by applying the one or more criteria to the comment metadata to identify video clips with comments that are associated with the particular category, the selecting two or more video clips further comprising: identifying two or more comments on different videos of the plurality of comments where the comment metadata specifies the two or more comments as meeting the one or more criteria; and determining, for each comment of the two or more comments, the video clip associated with the comment based on the one or more time values in the comment metadata corresponding to the comment, wherein, for each comment of the two or more comments, a duration of the video clip associated with the comment is determined based on a user-specified duration of time, a default duration of time, or a duration of time stored in the comment metadata; the one or more computers displaying the two or more video clips by merging the two or more video clips into a compilation video.

15. A computer system, comprising: one or more processors; a memory comprising a set of instructions which when executed causes the one or more processors to execute a method, the method comprising: receiving a plurality of comments respectively associated with a plurality of video clips from a plurality of videos stored in a video database; receiving comment metadata regarding each comment of the plurality of comments, including a category of a plurality of categories and one or more time values related to a video clip of the plurality of video clips, one or more computers receiving one or more criteria to apply to the comment metadata, wherein the one or more criteria specify at least a particular category of the plurality of categories; the one or more computers selecting two or more video clips by applying the one or more criteria to the comment metadata to identify video clips with comments that are associated with the particular category, the selecting two or more video clips further comprising: identifying two or more comments on different videos of the plurality of comments where the comment metadata specifies the two or more comments as meeting the one or more criteria; and determining, for each comment of the two or more comments, the video clip associated with the comment based on the one or more time values in the comment metadata corresponding to the comment, wherein, for each comment of the two or more comments, a duration of the video clip associated with the comment is determined based on a user-specified duration of time, a default duration of time, or a duration of time stored in the comment metadata; the one or more computers displaying the two or more video clips by merging the two or more video clips into a compilation video. 17. The computer system of claim 15 , the method further comprising adjusting a duration of at least one video clip of the two or more video clips.

12. A machine method of performing translations according to claim 11 wherein if all sentences have been worked upon and translated the translated sentences in the target language are collected and the source text is recomposed into sentences in the target second national language.

12. A machine method of performing translations according to claim 11 wherein if all sentences have been worked upon and translated the translated sentences in the target language are collected and the source text is recomposed into sentences in the target second national language. 13. A machine method of performing translations according to claim 12 wherein the national target language translation is displayed on-screen to permit final manual editing prior to printing.

11. The method of claim 1 further comprising: receiving a new user feedback item; automatically determining one or more proposed solutions to the new user feedback item using the items-solutions model; and providing the determined one or more proposed solutions.

11. The method of claim 1 further comprising: receiving a new user feedback item; automatically determining one or more proposed solutions to the new user feedback item using the items-solutions model; and providing the determined one or more proposed solutions. 13. The method of claim 11 where providing the determined one or more proposed solutions includes: providing, to a user, a description of the one or more proposed solutions; receiving, from the user, a selection of at least one solution from the one or more proposed solutions; and providing, in response to the received new user feedback item, the user-selected at least one solution.

1. A system comprising: a token generator associated with a third party to issue a client set of tokens to a client; a token verification list generator associated with the third party to issue a verification set of tokens to a provider; a communication module to receive a request from the provider to redeem a provider set of tokens; a redemption module to: compare the provider set of tokens with the client set of tokens, and selectively redeem the provider set of tokens, based on the results of the comparison.

1. A system comprising: a token generator associated with a third party to issue a client set of tokens to a client; a token verification list generator associated with the third party to issue a verification set of tokens to a provider; a communication module to receive a request from the provider to redeem a provider set of tokens; a redemption module to: compare the provider set of tokens with the client set of tokens, and selectively redeem the provider set of tokens, based on the results of the comparison. 4. The system of claim 1 , wherein the client set of tokens is a subset of the verification set of tokens.

16. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a configuration specification for configuring a cloud-based deployment, the configuration specification being written in specification language and requiring instantiation of respective class definitions of one or more classes, each class modeling a respective data or functional component of the cloud-based deployment using a group of, configurable class parameters, and the respective class definition of each class representing a requested state of the data or functional component modeled by the class; deriving a plurality of application programming interface (API) calls for configuring the cloud-based deployment based on the class definitions of the one or more classes; causing the plurality of API calls to be executed to configure the cloud-based deployment; storing respective class definitions of a plurality of core classes of the specification language, each core class corresponding to a modular component of a cloud-based environment, each core class being extendable with additional class parameters to configure the respective modular component; storing a mapping between each of the core classes and a respective group of API calls, the respective group of API calls for configuring the modular component associated with the core class according to the class parameters of the core class; and storing a plurality of protocols for modifying the respective groups of API calls associated with each core class to obtain a new group of API calls for a new class definition derived from the core class.

16. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a configuration specification for configuring a cloud-based deployment, the configuration specification being written in specification language and requiring instantiation of respective class definitions of one or more classes, each class modeling a respective data or functional component of the cloud-based deployment using a group of, configurable class parameters, and the respective class definition of each class representing a requested state of the data or functional component modeled by the class; deriving a plurality of application programming interface (API) calls for configuring the cloud-based deployment based on the class definitions of the one or more classes; causing the plurality of API calls to be executed to configure the cloud-based deployment; storing respective class definitions of a plurality of core classes of the specification language, each core class corresponding to a modular component of a cloud-based environment, each core class being extendable with additional class parameters to configure the respective modular component; storing a mapping between each of the core classes and a respective group of API calls, the respective group of API calls for configuring the modular component associated with the core class according to the class parameters of the core class; and storing a plurality of protocols for modifying the respective groups of API calls associated with each core class to obtain a new group of API calls for a new class definition derived from the core class. 20. The computer-readable medium of claim 16 , wherein: the specification language supports connectivity between class definitions, and a value assignment linking an instance of a second class to a class parameter of a first class represents a connectivity between respective components modeled by the first class and the second class.

12. A computer-implemented method for retrieving and generating targeted information, the method comprising: receiving an input image; performing, with one or more computers, document recognition on the input image to produce recognized text; receiving user profile information; generating, with the one or more computers, a list of relevant topics based on the recognized text and the user profile information; receiving targeted information; generating a list of relevant information based on the recognized text and the targeted information; adjusting a weight of at least one of the relevant topics in the list of relevant topics using user context information, wherein adjusting the weight of the at least one of the relevant topics includes determining word relevancy by calculating a distance from a center of the input image outward using a distance measure; and generating a final list of targeted information by comparing the list of relevant topics to the list of relevant information.

12. A computer-implemented method for retrieving and generating targeted information, the method comprising: receiving an input image; performing, with one or more computers, document recognition on the input image to produce recognized text; receiving user profile information; generating, with the one or more computers, a list of relevant topics based on the recognized text and the user profile information; receiving targeted information; generating a list of relevant information based on the recognized text and the targeted information; adjusting a weight of at least one of the relevant topics in the list of relevant topics using user context information, wherein adjusting the weight of the at least one of the relevant topics includes determining word relevancy by calculating a distance from a center of the input image outward using a distance measure; and generating a final list of targeted information by comparing the list of relevant topics to the list of relevant information. 14. The method of claim 12 , further comprising comparing keywords in the recognized text to advertisements in the targeted information to produce a list of relevant advertisements and wherein the final list of targeted information is a final list of relevant advertisements.

1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method comprising: causing, by a computer system, an executable program associated with an ontology to be run, wherein the ontology comprises a domain metadata model ontology indicating attributes for a set of applications; obtaining, by a computer system, an instance of the ontology, wherein the ontology instance corresponds to an application of the set of applications; generating, by a computer system, based on the ontology instance, supplemental information for the executable program, wherein the supplemental information comprises metadata in a graph data structure and is related to one or more functionalities of the application to be added to the executable program, and wherein the supplemental information comprises a data model configured to use facts expressed as triples; generating, by a computer system, a programming interface based on the ontology; and providing, by a computer system, the supplemental information as input to the executable program via the programming interface, wherein the supplemental information, at least in part, causes the one or more functionalities of the application to be made available via the executable program.

1. A method of providing supplemental functionalities to an executable program via an ontology instance, the method comprising: causing, by a computer system, an executable program associated with an ontology to be run, wherein the ontology comprises a domain metadata model ontology indicating attributes for a set of applications; obtaining, by a computer system, an instance of the ontology, wherein the ontology instance corresponds to an application of the set of applications; generating, by a computer system, based on the ontology instance, supplemental information for the executable program, wherein the supplemental information comprises metadata in a graph data structure and is related to one or more functionalities of the application to be added to the executable program, and wherein the supplemental information comprises a data model configured to use facts expressed as triples; generating, by a computer system, a programming interface based on the ontology; and providing, by a computer system, the supplemental information as input to the executable program via the programming interface, wherein the supplemental information, at least in part, causes the one or more functionalities of the application to be made available via the executable program. 11. The method of claim 1 , wherein the attributes for the set of applications include at least one class, at least one property, and at least one axiom.

1. A system for facilitating the analysis of software code, the system comprising: a decompiler and analysis subsystem operating on a processor, the decompiler and analysis subsystem comprising; means for separating the executable software code into a code section and a data section; means for generating one or more signature files from an input set of libraries comprising at least one of industry standard libraries and analyst-generated libraries; and means for comparing the code section of the executable software code to the one or more signature files; and means for generating a data-flow graph from at least a portion of the code section that does not match with any of the one of more signature files, the data-flow generation comprising variablization and variable type determination.

1. A system for facilitating the analysis of software code, the system comprising: a decompiler and analysis subsystem operating on a processor, the decompiler and analysis subsystem comprising; means for separating the executable software code into a code section and a data section; means for generating one or more signature files from an input set of libraries comprising at least one of industry standard libraries and analyst-generated libraries; and means for comparing the code section of the executable software code to the one or more signature files; and means for generating a data-flow graph from at least a portion of the code section that does not match with any of the one of more signature files, the data-flow generation comprising variablization and variable type determination. 7. The system of claim 1 wherein the decompiler and analysis subsystem further comprises means for iteratively discovering variables contained in the executable software code.

1. A computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a call center question and answer system, the method comprising: ingesting, through an instant messaging application, one or more original questions from one or more call center agents; ingesting, through the instant messaging application, one or more answers from the one or more call center agents, the one or more answers associated with the one or more original questions; analyzing, through a cognitive system, each of the one or more answers associated with the one or more original questions; incorporating the analysis of the one or more answers into the analysis of the one or more answers and the one or more original questions; receiving, by one of the one or more call center agents, one or more additional questions from a customer to which the call center agent cannot answer; receiving, through the instant messaging system, the one or more additional questions; determining, in real-time, one or more proposed answers to each additional question based on analysis of the one or more original questions and answers; determining, in real-time, a confidence score for each of the one or more proposed answers; if the confidence score of the proposed answer exceeds a confidence threshold, providing, in real-time, the proposed answer to the call center agent; receiving, in real-time, through a feedback module, feedback on the proposed answer from one or more subject matter experts or call center managers; and incorporating, in real-time, the feedback on the proposed answer into the analysis of the one or more original questions and the one or more additional questions.

1. A computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a call center question and answer system, the method comprising: ingesting, through an instant messaging application, one or more original questions from one or more call center agents; ingesting, through the instant messaging application, one or more answers from the one or more call center agents, the one or more answers associated with the one or more original questions; analyzing, through a cognitive system, each of the one or more answers associated with the one or more original questions; incorporating the analysis of the one or more answers into the analysis of the one or more answers and the one or more original questions; receiving, by one of the one or more call center agents, one or more additional questions from a customer to which the call center agent cannot answer; receiving, through the instant messaging system, the one or more additional questions; determining, in real-time, one or more proposed answers to each additional question based on analysis of the one or more original questions and answers; determining, in real-time, a confidence score for each of the one or more proposed answers; if the confidence score of the proposed answer exceeds a confidence threshold, providing, in real-time, the proposed answer to the call center agent; receiving, in real-time, through a feedback module, feedback on the proposed answer from one or more subject matter experts or call center managers; and incorporating, in real-time, the feedback on the proposed answer into the analysis of the one or more original questions and the one or more additional questions. 2. The method as recited in claim 1 , further comprising: utilizing a plug-in module to moderate the interactions between the cognitive system and the instant messaging application.

2. The method of claim 1 , wherein the method further comprises embedding the created file into another file that is of a type compatible with the external application.

2. The method of claim 1 , wherein the method further comprises embedding the created file into another file that is of a type compatible with the external application. 6. The method of claim 2 , wherein the external application is an application that enables a user to create and play slide presentations, and the created file is embedded into a slide presentation file.

16. The system of claim 13 , wherein the processing component comprises at least one adapter, and wherein the at least one adapter is configured for communicating with a specific type of data source.

16. The system of claim 13 , wherein the processing component comprises at least one adapter, and wherein the at least one adapter is configured for communicating with a specific type of data source. 19. The system of claim 16 , wherein the at least one adapter comprises a query builder.

6. The method of claim 1 , wherein each of the hash values is determined by: encoding the input values as a binary decision diagram (BDD) created from a family of sets; associating positions of the BDD with bit positions of the hash values such that the input values are encoded into unique hash values dependent on the path of the BDD traversed by a particular input value.

6. The method of claim 1 , wherein each of the hash values is determined by: encoding the input values as a binary decision diagram (BDD) created from a family of sets; associating positions of the BDD with bit positions of the hash values such that the input values are encoded into unique hash values dependent on the path of the BDD traversed by a particular input value. 7. The method of claim 6 , wherein the BDD is a zero-suppressed binary decision diagram (ZDD), and wherein the positions of the ZDD associated with bit positions of the hash values include positive edges of decision nodes of the ZDD.

1. A processor-implemented method for searching a mailbox of a user device to identify and present one or more results relevant to the user's requirements, the mailbox comprising a plurality of e-mails, the method comprising: receiving at the user device, an input from the user specifying the user's requirements; identifying at least one context of a search based on the input; searching in the mailbox according to the at least one context to identify one or more results relevant to the input, the results being at least one of one or more e-mails and one or more e-mail attachments; ranking each of the results according to the extent of relevance to the received input, wherein the ranking is performed based on a plurality of pre-defined conditions; and presenting the results to the user according to the ranking.

1. A processor-implemented method for searching a mailbox of a user device to identify and present one or more results relevant to the user's requirements, the mailbox comprising a plurality of e-mails, the method comprising: receiving at the user device, an input from the user specifying the user's requirements; identifying at least one context of a search based on the input; searching in the mailbox according to the at least one context to identify one or more results relevant to the input, the results being at least one of one or more e-mails and one or more e-mail attachments; ranking each of the results according to the extent of relevance to the received input, wherein the ranking is performed based on a plurality of pre-defined conditions; and presenting the results to the user according to the ranking. 2. The processor-implemented method of claim 1 , wherein the input comprises at least one search term.

1. A method performed at a first server comprising a computing device for sharing video editing techniques by a user, comprising: receiving, at the first server, a project description file, wherein the project description file is generated during editing of multimedia content by the user, the project description file containing information relating to the edited multimedia content; receiving, at the first server, a location identifier specifying a location of the edited multimedia content; retrieving the edited multimedia content from a second server to the first server using the location identifier; providing, by the first server, a user interface comprising a timeline; displaying, by the first server, multimedia editing objects specified by the project description file along the timeline; and while displaying the edited multimedia content received from the second server on the user interface of the first server, synchronizing the displaying of the edited multimedia content with the multimedia editing objects according to timing data specifying a duration of each of the multimedia editing objects, the timing data being specified in the project description file with respect to the timeline, wherein synchronizing by the first server the displaying of the edited multimedia content received from the second server with the multimedia editing objects at the first server is performed by receiving, at the first server, a specified location of a progression bar on the timeline, wherein the multimedia editing objects comprise video editing effects previously applied to the multimedia content to generate the edited multimedia content.

1. A method performed at a first server comprising a computing device for sharing video editing techniques by a user, comprising: receiving, at the first server, a project description file, wherein the project description file is generated during editing of multimedia content by the user, the project description file containing information relating to the edited multimedia content; receiving, at the first server, a location identifier specifying a location of the edited multimedia content; retrieving the edited multimedia content from a second server to the first server using the location identifier; providing, by the first server, a user interface comprising a timeline; displaying, by the first server, multimedia editing objects specified by the project description file along the timeline; and while displaying the edited multimedia content received from the second server on the user interface of the first server, synchronizing the displaying of the edited multimedia content with the multimedia editing objects according to timing data specifying a duration of each of the multimedia editing objects, the timing data being specified in the project description file with respect to the timeline, wherein synchronizing by the first server the displaying of the edited multimedia content received from the second server with the multimedia editing objects at the first server is performed by receiving, at the first server, a specified location of a progression bar on the timeline, wherein the multimedia editing objects comprise video editing effects previously applied to the multimedia content to generate the edited multimedia content. 13. The method of claim 1 , wherein providing a user interface comprising a timeline further comprises generating the timeline on a web page.

2. The storage manufacture of claim 1 , wherein: each of the interface result entities defines zero or more result actions; each of the result actions consists of setting a value of a selected output variable based on applying a single selected action mechanism to one or more inputs; the graphical editor implements a graphical user interface that enables selection of the input from a limited set of choices consisting of a selected variable, a constant, and an input value acquired by a widget; and the selected variable is selected from a predefined set of variables that is under exclusive local control of the expert system.

2. The storage manufacture of claim 1 , wherein: each of the interface result entities defines zero or more result actions; each of the result actions consists of setting a value of a selected output variable based on applying a single selected action mechanism to one or more inputs; the graphical editor implements a graphical user interface that enables selection of the input from a limited set of choices consisting of a selected variable, a constant, and an input value acquired by a widget; and the selected variable is selected from a predefined set of variables that is under exclusive local control of the expert system. 3. The storage manufacture of claim 2 wherein the result action is configured, when invoked during execution of the expert system, to execute a predetermined action including one or more of setting a variable, opening an external document, uploading data to other servers, and integrating with a container through a container integration subsystem coupled to the graphical editor.

1. A video based instructional and entertainment system, comprising: a picture and sound presentation provided by a video and audio signal source containing digital control data embedded in said video signal, where said video signal displays at least one animated figure on the screen of a television receiver; at least one animated figure having at least one articulated component capable of motion where said motion is related to said control data; a first loudspeaker located internal to said animated figure where said loudspeaker reroduces at least a portion of said sound presentation and where said portion is selected by one of said digital control signals; a second loudspeaker internal to said system where said loudspeaker reproduces that portion of said sound presentation not delivered by said first loudspeaker; whereby said system allows real-time interaction between said animated screen figure and associated sound presentation as delivered by said television set, and said animated figure, where said interaction effectively extends said screen presentation into the physical space occupied by said animated figure.

1. A video based instructional and entertainment system, comprising: a picture and sound presentation provided by a video and audio signal source containing digital control data embedded in said video signal, where said video signal displays at least one animated figure on the screen of a television receiver; at least one animated figure having at least one articulated component capable of motion where said motion is related to said control data; a first loudspeaker located internal to said animated figure where said loudspeaker reroduces at least a portion of said sound presentation and where said portion is selected by one of said digital control signals; a second loudspeaker internal to said system where said loudspeaker reproduces that portion of said sound presentation not delivered by said first loudspeaker; whereby said system allows real-time interaction between said animated screen figure and associated sound presentation as delivered by said television set, and said animated figure, where said interaction effectively extends said screen presentation into the physical space occupied by said animated figure. 3. The system of claim 1, wherein said video and sound signal source is videodisc player.

1. A method, comprising: hosting an application for utilization by a remote computing platform; identifying a plurality of UI elements of a graphical user interface (UI) generated by the hosted application; generating a plurality of proxy UI elements, each of the plurality of proxy UI elements corresponding to one or more of the plurality of UI elements; transmitting, to the remote computing platform, the graphical UI generated by the hosted application and the plurality of proxy UI elements; processing a transcript of an audio sample, the audio sample comprising an utterance of a user of the remote computing platform, and the transcript of the audio sample comprising at least one word corresponding to one or more of the plurality of proxy UI elements; invoking a functionality of the hosted application, said functionality corresponding to one or more of the plurality of UI elements that correspond to the one or more of the plurality of proxy UI elements; identifying a plurality of properties of the plurality of UI elements and generating the plurality of proxy UI elements based on the identified plurality of properties, wherein each respective proxy UI element of the plurality of proxy UI elements is associated with one or more words corresponding to one or more of the plurality of properties, the one or more of the plurality of properties corresponding to one or more of the UI elements that correspond to the respective proxy UI element; and wherein the plurality of properties comprise one or more UI element labels of a labeled UI element of the plurality of UI elements, wherein the at least one word corresponding to one or more of the plurality of proxy UI elements comprises a word corresponding to at least one of the one or more UI element labels of the labeled UI element, and wherein invoking the functionality of the hosted application comprises changing a currently selected UI element of the hosted application from the currently selected UI element of the hosted application to the labeled UI element.

1. A method, comprising: hosting an application for utilization by a remote computing platform; identifying a plurality of UI elements of a graphical user interface (UI) generated by the hosted application; generating a plurality of proxy UI elements, each of the plurality of proxy UI elements corresponding to one or more of the plurality of UI elements; transmitting, to the remote computing platform, the graphical UI generated by the hosted application and the plurality of proxy UI elements; processing a transcript of an audio sample, the audio sample comprising an utterance of a user of the remote computing platform, and the transcript of the audio sample comprising at least one word corresponding to one or more of the plurality of proxy UI elements; invoking a functionality of the hosted application, said functionality corresponding to one or more of the plurality of UI elements that correspond to the one or more of the plurality of proxy UI elements; identifying a plurality of properties of the plurality of UI elements and generating the plurality of proxy UI elements based on the identified plurality of properties, wherein each respective proxy UI element of the plurality of proxy UI elements is associated with one or more words corresponding to one or more of the plurality of properties, the one or more of the plurality of properties corresponding to one or more of the UI elements that correspond to the respective proxy UI element; and wherein the plurality of properties comprise one or more UI element labels of a labeled UI element of the plurality of UI elements, wherein the at least one word corresponding to one or more of the plurality of proxy UI elements comprises a word corresponding to at least one of the one or more UI element labels of the labeled UI element, and wherein invoking the functionality of the hosted application comprises changing a currently selected UI element of the hosted application from the currently selected UI element of the hosted application to the labeled UI element. 11. The method of claim 1 , wherein at least a portion of the plurality of proxy UI elements are configured to be hidden from view of the user of the remote computing platform, wherein one or more of the at least a portion of the plurality of proxy UI elements that are configured to be hidden from view of the user of the remote computing platform comprises a navigation menu option, the navigation menu option being configured to show one or more navigation options available from a UI state of the hosted application currently being displayed by the remote computing platform, wherein the at least one word corresponding to the one or more of the plurality of proxy UI elements comprises at least one word corresponding to the navigation menu option, and wherein invoking the functionality of the hosted application comprises navigating the hosted application to one of the one or more navigation options.

18. The method of claim 1 , further comprising determining a tone associated with the received string and wherein determining the context for the received string based on the contact associated with the one of the one or more parties of the conversation further comprises determining the context based on the determined tone.

18. The method of claim 1 , further comprising determining a tone associated with the received string and wherein determining the context for the received string based on the contact associated with the one of the one or more parties of the conversation further comprises determining the context based on the determined tone. 19. The method of claim 18 , wherein the determined tone comprises one or more of a formal tone or an informal tone.

24. The computer readable storage device of claim 23 , wherein said dialog structure implements a halt in execution of said one or more declarative lattice structures.

24. The computer readable storage device of claim 23 , wherein said dialog structure implements a halt in execution of said one or more declarative lattice structures. 26. The computer readable storage device of claim 24 , wherein said dialog structure is associated with computer code for tracking a data state related to said one or more declarative lattice structures during said halt in said execution.

20. The method of claim 14 wherein said script may be associated with a plurality of application programs.

20. The method of claim 14 wherein said script may be associated with a plurality of application programs. 23. The method of claim 20 wherein said plurality of application programs comprise an image editor program and a wireless messaging program.

7. An apparatus comprising: a processor; and a memory to store computer program instructions, the computer program instructions when executed on the processor cause the processor to perform operations comprising: receiving a message from a first user to a second user via one of a plurality of accounts associated with the second user, the message in a first language; and translating the message to a preferred language of the second user for the one of the plurality of accounts associated with the second user when the first language is not the same as the preferred language of the second user for the one of the plurality of accounts associated with the second user, wherein each of the plurality of accounts associated with the second user identifies a different preferred language.

7. An apparatus comprising: a processor; and a memory to store computer program instructions, the computer program instructions when executed on the processor cause the processor to perform operations comprising: receiving a message from a first user to a second user via one of a plurality of accounts associated with the second user, the message in a first language; and translating the message to a preferred language of the second user for the one of the plurality of accounts associated with the second user when the first language is not the same as the preferred language of the second user for the one of the plurality of accounts associated with the second user, wherein each of the plurality of accounts associated with the second user identifies a different preferred language. 12. The apparatus of claim 7 , the operations further comprising: broadcasting the message in the preferred language of the second user for the one of the plurality of accounts associated with the second user to a plurality of users in a chat session.

14. The system of claim 13 , wherein providing the query result causes the computing device of a user to present the query result in a plurality of page views at a user interface, wherein the additional information is presented in a page view of the plurality of page views based at least in part on one or more parameters, wherein the one or more parameters comprise an average number of presented page views before abandonment or reformulation of queries.

14. The system of claim 13 , wherein providing the query result causes the computing device of a user to present the query result in a plurality of page views at a user interface, wherein the additional information is presented in a page view of the plurality of page views based at least in part on one or more parameters, wherein the one or more parameters comprise an average number of presented page views before abandonment or reformulation of queries. 15. The system of claim 14 , wherein the page view is further determined based at least in part on the specificity of the query or an indication of an expected behavior of the user associated with viewing the query result.

7. A computer-implemented method of displaying information about a document that includes a spatial identifier that identifies a corresponding location within a metric space and wherein that spatial identifier is characterized by a semantic type that is determined by the use of the spatial identifier within the document, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; visually identifying the spatial identifier within a displayed visual representation of the content from the document; visually indicating the semantic type of the spatial identifier wherein the semantic type is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, two or more corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations.

7. A computer-implemented method of displaying information about a document that includes a spatial identifier that identifies a corresponding location within a metric space and wherein that spatial identifier is characterized by a semantic type that is determined by the use of the spatial identifier within the document, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; visually identifying the spatial identifier within a displayed visual representation of the content from the document; visually indicating the semantic type of the spatial identifier wherein the semantic type is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, two or more corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations. 9. The computer-implemented method of claim 7 , wherein the semantic type is a context-dependent property of the spatial indicator.

7. The method of claim 3 , wherein annotating of the captured portion of the reference document further comprises: displaying the captured portion of the reference document to be annotated; receiving a first input from a user designating a first point in the captured portion of the reference document defining a corner of an annotation rectangle; receiving a second input from the user designating a second point in the captured portion of the reference document defining an opposite corner of the annotation rectangle; and annotating the captured portion of the reference document from the first point to the second point of the annotation rectangle when the second input is released.

7. The method of claim 3 , wherein annotating of the captured portion of the reference document further comprises: displaying the captured portion of the reference document to be annotated; receiving a first input from a user designating a first point in the captured portion of the reference document defining a corner of an annotation rectangle; receiving a second input from the user designating a second point in the captured portion of the reference document defining an opposite corner of the annotation rectangle; and annotating the captured portion of the reference document from the first point to the second point of the annotation rectangle when the second input is released. 9. The method as recited in claim 7 , wherein if the user does not immediately release the second input, allowing the user to drag the second point to visually show a shape and a size of the annotation rectangle.

5. A method in a computer system for marshaling of a parameter for inter-language invocation of functions between a first language and a second language, the parameter to be marshaled having a first type in the first language and a second type in the second language, the method comprising: when a computer program implemented in the first language invokes a function implemented in the second language, determining that a parameter being passed to the function requires custom marshaling; creating for the invoked function an in stub that invokes custom marshaling code for converting the passed parameter of the first type to a parameter of the second type and an out stub that invokes custom marshaling code for converting a returned parameter of the second type to a parameter of the first type; executing the in stub, thereby converting the passed parameter of the first type to a parameter of the second type; invoking the function implemented in the second language and passing the parameter converted to the second type; and after invocation of the function, executing the out stub, thereby converting the parameter of the second type to a parameter of the first type.

5. A method in a computer system for marshaling of a parameter for inter-language invocation of functions between a first language and a second language, the parameter to be marshaled having a first type in the first language and a second type in the second language, the method comprising: when a computer program implemented in the first language invokes a function implemented in the second language, determining that a parameter being passed to the function requires custom marshaling; creating for the invoked function an in stub that invokes custom marshaling code for converting the passed parameter of the first type to a parameter of the second type and an out stub that invokes custom marshaling code for converting a returned parameter of the second type to a parameter of the first type; executing the in stub, thereby converting the passed parameter of the first type to a parameter of the second type; invoking the function implemented in the second language and passing the parameter converted to the second type; and after invocation of the function, executing the out stub, thereby converting the parameter of the second type to a parameter of the first type. 8. The method of claim 5 wherein the custom marshaling code is implemented as member functions of a class.

1. A computer-implemented method for identifying information assets, the method comprising: monitoring users navigating query search results, each search result presenting a list of information assets responsive to a corresponding search query, wherein each information asset in the list corresponds to a computing resource available within an enterprise computing network; generating, by operation of one or more computer processors, a semantic graph representing relationships between the information assets, wherein nodes of the semantic graph each correspond to one of the information assets, wherein relationships between nodes are identified by monitoring users navigating from one of the information assets presented in the search results to another one of the information assets presented in the search results, and wherein the semantic graph includes metadata specifying an operational state of each information asset as being either a formally managed information asset within the enterprise computing network or an informally managed information asset within the enterprise computing network; periodically evaluating the semantic graph using predefined criteria; upon determining at least a first one of the plurality of nodes in the semantic graph corresponds to a first information asset which satisfies the predefined criteria and is one of the informally managed information assets within the enterprise computing network, providing an indication of the first node as corresponding to an information asset which is a target for being a formally managed information asset within the enterprise computing network; classifying a second one of the plurality of nodes in the semantic graph corresponding to a second information asset as a first hub, based on determining that the second one of the plurality of nodes has a number of edges to other nodes that exceeds a predefined value and upon further determining that the second information asset is a formally managed information asset; responsive to classifying the second information asset as the first hub: determining to divide the second information asset into a plurality of specialized information assets, wherein each of the plurality of specialized information assets has functionality that is more specialized than functionality of the second information asset; dividing the second information asset into the plurality of specialized information assets, wherein each of the plurality of specialized information assets is a formally managed information asset; and updating the semantic graph by adding nodes corresponding to the plurality of specialized information assets; and classifying a third one of the plurality of nodes in the semantic graph corresponding to a third information asset as a second hub, based on determining that the third one of the plurality of nodes has a number of edges to other nodes that exceeds the predefined value and upon further determining that the second information asset is a formally managed information asset; responsive to classifying the third information asset as the third hub: assigning a first priority to the third information asset, wherein the first information asset is assigned a relatively lower priority; and allocating additional computing resources to the third information asset.

1. A computer-implemented method for identifying information assets, the method comprising: monitoring users navigating query search results, each search result presenting a list of information assets responsive to a corresponding search query, wherein each information asset in the list corresponds to a computing resource available within an enterprise computing network; generating, by operation of one or more computer processors, a semantic graph representing relationships between the information assets, wherein nodes of the semantic graph each correspond to one of the information assets, wherein relationships between nodes are identified by monitoring users navigating from one of the information assets presented in the search results to another one of the information assets presented in the search results, and wherein the semantic graph includes metadata specifying an operational state of each information asset as being either a formally managed information asset within the enterprise computing network or an informally managed information asset within the enterprise computing network; periodically evaluating the semantic graph using predefined criteria; upon determining at least a first one of the plurality of nodes in the semantic graph corresponds to a first information asset which satisfies the predefined criteria and is one of the informally managed information assets within the enterprise computing network, providing an indication of the first node as corresponding to an information asset which is a target for being a formally managed information asset within the enterprise computing network; classifying a second one of the plurality of nodes in the semantic graph corresponding to a second information asset as a first hub, based on determining that the second one of the plurality of nodes has a number of edges to other nodes that exceeds a predefined value and upon further determining that the second information asset is a formally managed information asset; responsive to classifying the second information asset as the first hub: determining to divide the second information asset into a plurality of specialized information assets, wherein each of the plurality of specialized information assets has functionality that is more specialized than functionality of the second information asset; dividing the second information asset into the plurality of specialized information assets, wherein each of the plurality of specialized information assets is a formally managed information asset; and updating the semantic graph by adding nodes corresponding to the plurality of specialized information assets; and classifying a third one of the plurality of nodes in the semantic graph corresponding to a third information asset as a second hub, based on determining that the third one of the plurality of nodes has a number of edges to other nodes that exceeds the predefined value and upon further determining that the second information asset is a formally managed information asset; responsive to classifying the third information asset as the third hub: assigning a first priority to the third information asset, wherein the first information asset is assigned a relatively lower priority; and allocating additional computing resources to the third information asset. 6. The method of claim 1 , further comprising: periodically evaluating the semantic graph using second predefined criteria; and upon determining at least a second one of the information assets in the semantic graph satisfies the second predefined criteria and is one of the formally managed information assets within the enterprise computing network, providing an indication of the second information asset as being an underutilized information asset within the enterprise computing network.

1. A computational method for transforming an input audio encoding of speech into an output that is rhythmically consistent with a target song, the method comprising: segmenting the input audio encoding of the speech into plural segments, the segments corresponding to successive sequences of samples of the audio encoding and delimited by onsets identified therein; mapping individual ones of the plural segments to respective sub-phrase portions of a phrase template for the target song, the mapping establishing one or more phrase candidates; temporally aligning at least one of the phrase candidates with a rhythmic skeleton for the target song; and preparing a resultant audio encoding of the speech in correspondence with the temporally aligned phrase candidate-mapped from onset-delimited segments of the input audio encoding.

1. A computational method for transforming an input audio encoding of speech into an output that is rhythmically consistent with a target song, the method comprising: segmenting the input audio encoding of the speech into plural segments, the segments corresponding to successive sequences of samples of the audio encoding and delimited by onsets identified therein; mapping individual ones of the plural segments to respective sub-phrase portions of a phrase template for the target song, the mapping establishing one or more phrase candidates; temporally aligning at least one of the phrase candidates with a rhythmic skeleton for the target song; and preparing a resultant audio encoding of the speech in correspondence with the temporally aligned phrase candidate-mapped from onset-delimited segments of the input audio encoding. 2. The computational method of claim 1 , further comprising: mixing the resultant audio encoding with an audio encoding of a backing track for the target song; and audibly rendering the mixed audio.

1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: 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; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; 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.

1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: 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; provisionally applying the semantic command to the first local version of the database before sending the semantic command to the master node; 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. 10. A method as recited in claim 1 , wherein each of the plurality of nodes includes a semantic translation processor configured to translate the semantic command so that it can be processed by a local semantic processor.

14. The apparatus of claim 13 , the application operative to determine the percentage of nodes removed from the collection after traversing the collection, increase a first specified number when the percentage is smaller than a first specified percentage, and decrease the first specified number when the percentage is larger than a second specified percentage, wherein the first specified percentage is larger than the second specified percentage.

14. The apparatus of claim 13 , the application operative to determine the percentage of nodes removed from the collection after traversing the collection, increase a first specified number when the percentage is smaller than a first specified percentage, and decrease the first specified number when the percentage is larger than a second specified percentage, wherein the first specified percentage is larger than the second specified percentage. 16. The apparatus of claim 14 , the application further operative to decrease the first specified number by one of subtracting a constant from the first specified number, decreasing the first specified number by a percentage of the current value of the first specified number, or setting the first specified number to be the minimum of a constant and a fraction of the number of nodes remaining in the collection.

1. A system for identifying keywords in search results comprising: a processor; a memory coupled to the processor; computer code loaded into the memory for executing on the processor, for implementing the following functionality: a plurality of neurons connected as a bidirectional neural network, the neurons being associated with words and documents, the neurons associated with words forming a first layer, and the neurons associated with documents forming a second layer, each neuron having multiple inputs from other neurons, a single output connecting the neuron to other neurons, and a threshold function at the single output, wherein at least some of the neurons of the first layer have connections between them and represent keywords in the documents; an activity regulator that regulates a fraction of a number of neurons of the neural network that are excited at any given time; and means for displaying to a user, on a display device, words of the search query and additional keywords from the documents and for identifying the neurons that correspond to keywords associated with at least one of the documents.

1. A system for identifying keywords in search results comprising: a processor; a memory coupled to the processor; computer code loaded into the memory for executing on the processor, for implementing the following functionality: a plurality of neurons connected as a bidirectional neural network, the neurons being associated with words and documents, the neurons associated with words forming a first layer, and the neurons associated with documents forming a second layer, each neuron having multiple inputs from other neurons, a single output connecting the neuron to other neurons, and a threshold function at the single output, wherein at least some of the neurons of the first layer have connections between them and represent keywords in the documents; an activity regulator that regulates a fraction of a number of neurons of the neural network that are excited at any given time; and means for displaying to a user, on a display device, words of the search query and additional keywords from the documents and for identifying the neurons that correspond to keywords associated with at least one of the documents. 11. The system of claim 1 , wherein the neural network is excited by a query that identifies a document considered relevant by a user.

23. A system comprising: at least one processor; and a computer-readable medium containing program code that when executed cause the at least one processor to perform operations comprising: receiving, at a server device and from a client device, a search query entered on the client device by a user; determining, using the server device, that the user belongs to at least a first population group; determining, using the server device, that at least a first article is responsive to the search query; determining, using the server device, an interest value reflecting an interest of the first population group in the first article, the interest value based on at least one selection of the first article made when the first article was previously presented to at least one member of the first population group in response to an earlier search query identical to the search query; determining, using the server device, a first ranking score for the first article, the first ranking score based at least in part on the interest value; and outputting a search result from the server device to the client device in response to the search query, the first article ranked in the search result according to the first ranking score.

23. A system comprising: at least one processor; and a computer-readable medium containing program code that when executed cause the at least one processor to perform operations comprising: receiving, at a server device and from a client device, a search query entered on the client device by a user; determining, using the server device, that the user belongs to at least a first population group; determining, using the server device, that at least a first article is responsive to the search query; determining, using the server device, an interest value reflecting an interest of the first population group in the first article, the interest value based on at least one selection of the first article made when the first article was previously presented to at least one member of the first population group in response to an earlier search query identical to the search query; determining, using the server device, a first ranking score for the first article, the first ranking score based at least in part on the interest value; and outputting a search result from the server device to the client device in response to the search query, the first article ranked in the search result according to the first ranking score. 42. The system of claim 23 , further comprising determining, using the server device, that also at least a second article is responsive to the search query; determining, using the server device, another interest value reflecting an interest of the firs population group in the second article; and determining, using the server device, a second ranking score for the second article, the second ranking score based at least in part on the other interest value, wherein the second article is ranked in the search result according to the second ranking score.

5. A method for conducting a weighted keyword search, the method comprising steps of: a computer displaying a graphical presentation showing respective keywords, in response to receiving a request for a weighted keyword search, the graphical presentation comprising respective nodes representing the respective keywords and lines connecting the respective nodes; the computer receiving a user interaction position on an area surrounded by the lines connecting the respective nodes; the computer determining respective weights of the respective keywords, based on proximity of the user interaction position to the respective keywords; the computer conducting the weighted keyword search of documents based on the keywords and the respective weights of the keywords; wherein the user interaction position is within a polygon formed by three or more lines connecting three or more nodes representing three or more keywords; and wherein a weight of a specific one of the three or more keywords is determined based on a ratio of a distance between the user interaction position and a specific one of the three or more nodes to a sum of distances between the user interaction position and each of the three or more nodes, wherein the specific one of the three or more nodes represents the specific one of the three or more keywords.

5. A method for conducting a weighted keyword search, the method comprising steps of: a computer displaying a graphical presentation showing respective keywords, in response to receiving a request for a weighted keyword search, the graphical presentation comprising respective nodes representing the respective keywords and lines connecting the respective nodes; the computer receiving a user interaction position on an area surrounded by the lines connecting the respective nodes; the computer determining respective weights of the respective keywords, based on proximity of the user interaction position to the respective keywords; the computer conducting the weighted keyword search of documents based on the keywords and the respective weights of the keywords; wherein the user interaction position is within a polygon formed by three or more lines connecting three or more nodes representing three or more keywords; and wherein a weight of a specific one of the three or more keywords is determined based on a ratio of a distance between the user interaction position and a specific one of the three or more nodes to a sum of distances between the user interaction position and each of the three or more nodes, wherein the specific one of the three or more nodes represents the specific one of the three or more keywords. 6. The method of claim 5 , wherein, for the weighted keyword search related to two keywords, the user interaction position is on a line connecting two nodes representing the two keywords.

3. A method according to claim 1 , wherein the first multi-part MIME electronic mail message comprises a Content-ID identifying a sender of the first multi-part MIME electronic mail message, a filename of the business document and a first timestamp.

3. A method according to claim 1 , wherein the first multi-part MIME electronic mail message comprises a Content-ID identifying a sender of the first multi-part MIME electronic mail message, a filename of the business document and a first timestamp. 4. A method according to claim 3 , wherein transmitting the first electronic mail message comprises: transmitting the first electronic mail message to a first recipient associated with a To: header field of the first electronic mail message, wherein the business application platform is associated with a Cc: header field of the first electronic mail message, and wherein transmitting the second electronic mail message comprises: transmitting the second electronic mail message to a second recipient associated with a To: header field of the second electronic mail message, wherein the business application platform is associated with a Cc: header field of the second electronic mail message.

6. The method of claim 1 , wherein generating the first active document comprises converting a passive document to an active document.

6. The method of claim 1 , wherein generating the first active document comprises converting a passive document to an active document. 7. The method of claim 6 , wherein the passive document is a web based document.

12. A system for delivering related video content for augmented keywords on a web page, the system comprising: a server comprising a processor, the server receiving from an agent executing within a browser, responsive to the agent detecting a mouse over a keyword currently displayed on a web page of a client, the keyword identified for augmentation via a user interface overlay and identifying a plurality of videos related to the keyword, the server configured to dynamically select, responsive to receiving the keyword at a time of the mouse over, one or more videos for the user interface overlay for the keyword; a content relevancy engine determining an order of relevance of the plurality of videos to the keyword; and wherein the server selects one or more videos of the plurality of videos with a higher order of relevance and transmits to the agent of the client, within a predetermined time period from receipt of the keyword from the agent responsive to the agent detecting the mouse over, the user interface overlay, to be displayed by the agent responsive to the mouse over, to include the selected one or more videos of the plurality of videos with a higher order of relevance for at least one of user selection or display in the user interface overlay, the predetermined time period comprising a time threshold within which the server is to complete the selection of the one or more videos and to complete delivery of the selected one or more videos to the client.

12. A system for delivering related video content for augmented keywords on a web page, the system comprising: a server comprising a processor, the server receiving from an agent executing within a browser, responsive to the agent detecting a mouse over a keyword currently displayed on a web page of a client, the keyword identified for augmentation via a user interface overlay and identifying a plurality of videos related to the keyword, the server configured to dynamically select, responsive to receiving the keyword at a time of the mouse over, one or more videos for the user interface overlay for the keyword; a content relevancy engine determining an order of relevance of the plurality of videos to the keyword; and wherein the server selects one or more videos of the plurality of videos with a higher order of relevance and transmits to the agent of the client, within a predetermined time period from receipt of the keyword from the agent responsive to the agent detecting the mouse over, the user interface overlay, to be displayed by the agent responsive to the mouse over, to include the selected one or more videos of the plurality of videos with a higher order of relevance for at least one of user selection or display in the user interface overlay, the predetermined time period comprising a time threshold within which the server is to complete the selection of the one or more videos and to complete delivery of the selected one or more videos to the client. 13. The system of claim 12 , wherein the agent responsive to the detection of the mouse over displays the user interface overlay with the selected one or more videos as an overlay on the web page currently displaying the keyword.

22. A service providing device comprising: a processor; a memory device which stores a plurality of instructions, which when executed by the processor, performs: a storing step of storing a database including at least one of electronic documents and tagged electronic documents tagged according to a markup language; a receiving step of receiving, via a receiver and from a terminal device, specification information specifying at least one of an electronic document without a tag and a tagged electronic document and receiving request information indicating a request for said tagged electronic document including a tag indicating the structure of the electronic document without a tag; a transmitting step of transmitting via a transmitter; a determining step of determining, when said receiver receives said request information, whether (i) said tagged electronic document corresponding to the received specification information is stored in said database, (ii) said electronic document corresponding to the received specification information is stored in said database, or (iii) no document corresponding to the received specification information is stored in said database; and a control step of reading said tagged electronic document from said database and transmitting it to said terminal device via the transmitter when said determining step has determined that said database includes said tagged electronic document of the electronic document specified by said specification information, and when said determining step has determined that said database includes no document corresponding to the received specification information, transmitting data to said user terminal to request transmission of the electronic document indicated by said specification information.

22. A service providing device comprising: a processor; a memory device which stores a plurality of instructions, which when executed by the processor, performs: a storing step of storing a database including at least one of electronic documents and tagged electronic documents tagged according to a markup language; a receiving step of receiving, via a receiver and from a terminal device, specification information specifying at least one of an electronic document without a tag and a tagged electronic document and receiving request information indicating a request for said tagged electronic document including a tag indicating the structure of the electronic document without a tag; a transmitting step of transmitting via a transmitter; a determining step of determining, when said receiver receives said request information, whether (i) said tagged electronic document corresponding to the received specification information is stored in said database, (ii) said electronic document corresponding to the received specification information is stored in said database, or (iii) no document corresponding to the received specification information is stored in said database; and a control step of reading said tagged electronic document from said database and transmitting it to said terminal device via the transmitter when said determining step has determined that said database includes said tagged electronic document of the electronic document specified by said specification information, and when said determining step has determined that said database includes no document corresponding to the received specification information, transmitting data to said user terminal to request transmission of the electronic document indicated by said specification information. 30. A service providing device according to claim 22 , wherein said database includes, together with said electronic documents, authoring permission/prohibition information indicating whether authoring of the respective electronic documents is permitted or prohibited.

1. A sentiment analyzer for an electronic learning system comprising: one or more client devices of the electronic learning system, each client device comprising: a processing unit comprising one or more processors; an I/O subsystem configured to provide electronic learning content, and to receive user input data relating to the provided electronic learning content via one or more input devices connected to the client device; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the client device to: provide electronic learning content to one or more users via the I/O subsystem; receive user feedback data relating to the provided electronic learning content via the I/O subsystem; and transmit the user feedback data relating to the provided electronic learning content to a feedback analytics server of the electronic learning system; and a feedback analytics server of the electronic learning system, comprising: a processing unit comprising one or more processors; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the feedback analytics server of the electronic learning system to: receive a plurality of feedback data from the one or more client devices, the received feedback data corresponding to user feedback of one or more users relating to electronic learning content; determine an associated user and a sentiment score for each of the received plurality of feedback data; group the plurality of feedback data into one or more feedback aggregations associated with the one or more users; calculate a sentiment score for each of the one or more feedback aggregations associated with the one or more users using a language processing engine to determine a sentiment score for text feedback data relating to the electronic learning content; receive user records associated with each of the one or more users, the received user records relating to interactions of the one or more users with the electronic learning system occurring after the receipt of the feedback data; store the user records and associated sentiment scores for each of the one or more users within a data store of the electronic learning system; training a machine learning algorithm based on the stored user records and associated sentiment scores, for each of the one or more users within the data store of the electronic learning system; receive additional feedback data from the one or more client devices, the additional feedback data including user feedback from a first user relating to electronic learning content; calculate a sentiment score for the first user, based on the received additional feedback data; using the stored user records and associated sentiment scores in the data store of the electronic learning system, determine a user record prediction for the first user using the trained machine learning algorithm, based on the calculated sentiment score for the first user; determine a sentiment analyzer output for the electronic learning system and one or more output devices, based on the determined user record prediction for the first user; and provide the determined sentiment analyzer system-output for the electronic learning system to the determined one or more output devices.

1. A sentiment analyzer for an electronic learning system comprising: one or more client devices of the electronic learning system, each client device comprising: a processing unit comprising one or more processors; an I/O subsystem configured to provide electronic learning content, and to receive user input data relating to the provided electronic learning content via one or more input devices connected to the client device; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the client device to: provide electronic learning content to one or more users via the I/O subsystem; receive user feedback data relating to the provided electronic learning content via the I/O subsystem; and transmit the user feedback data relating to the provided electronic learning content to a feedback analytics server of the electronic learning system; and a feedback analytics server of the electronic learning system, comprising: a processing unit comprising one or more processors; and memory coupled with and readable by the processing unit and storing therein a set of instructions which, when executed by the processing unit, causes the feedback analytics server of the electronic learning system to: receive a plurality of feedback data from the one or more client devices, the received feedback data corresponding to user feedback of one or more users relating to electronic learning content; determine an associated user and a sentiment score for each of the received plurality of feedback data; group the plurality of feedback data into one or more feedback aggregations associated with the one or more users; calculate a sentiment score for each of the one or more feedback aggregations associated with the one or more users using a language processing engine to determine a sentiment score for text feedback data relating to the electronic learning content; receive user records associated with each of the one or more users, the received user records relating to interactions of the one or more users with the electronic learning system occurring after the receipt of the feedback data; store the user records and associated sentiment scores for each of the one or more users within a data store of the electronic learning system; training a machine learning algorithm based on the stored user records and associated sentiment scores, for each of the one or more users within the data store of the electronic learning system; receive additional feedback data from the one or more client devices, the additional feedback data including user feedback from a first user relating to electronic learning content; calculate a sentiment score for the first user, based on the received additional feedback data; using the stored user records and associated sentiment scores in the data store of the electronic learning system, determine a user record prediction for the first user using the trained machine learning algorithm, based on the calculated sentiment score for the first user; determine a sentiment analyzer output for the electronic learning system and one or more output devices, based on the determined user record prediction for the first user; and provide the determined sentiment analyzer system-output for the electronic learning system to the determined one or more output devices. 4. The sentiment analyzer system of claim 1 , wherein grouping the plurality of feedback data comprises: determining a first subset of the plurality of feedback data corresponding to feedback provided by the first user via the one or more client devices; and grouping the first subset of the plurality of feedback data into a first feedback aggregation.

1. A method of extracting an extensible motif from a sequence, said method comprising: assigning on a computer a significance to an extensible motif within said sequence based upon a syntactic and statistical analysis; identifying an extensible motif having a significance that exceeds a predetermined threshold; and iterating said assigning said significance and said identifying said extensible motif, wherein said assigning said significance comprises assigning said significance based on a combination of saturation conditions at each iteration and monotonicity of probabilistic scores derived from the saturation conditions of said extensible motif.

1. A method of extracting an extensible motif from a sequence, said method comprising: assigning on a computer a significance to an extensible motif within said sequence based upon a syntactic and statistical analysis; identifying an extensible motif having a significance that exceeds a predetermined threshold; and iterating said assigning said significance and said identifying said extensible motif, wherein said assigning said significance comprises assigning said significance based on a combination of saturation conditions at each iteration and monotonicity of probabilistic scores derived from the saturation conditions of said extensible motif. 3. The method of claim 1 , further comprising displaying a list of identified extensible motifs.

1. A computer-implemented method for providing a query suggestion, the method comprising: detecting access at a data source; collecting non-query data based on the detected access, the non-query data comprising metadata describing identity data, profile data, or contextual information; determining an initial query suggestion for a query of the data source based on the non-query data, the determining comprising: comparing the non-query data to prior query information; determining that at least a portion of the non-query data is associated with a portion of the prior query information; and generating the initial query suggestion based, at least in part, on the portion of the prior query information; returning the initial query suggestion; receiving an indication of action on the initial query suggestion; determining an additional query suggestion for the query for the data source, the query comprises data indicative of at least a portion of a query statement; and returning the additional query suggestion.

1. A computer-implemented method for providing a query suggestion, the method comprising: detecting access at a data source; collecting non-query data based on the detected access, the non-query data comprising metadata describing identity data, profile data, or contextual information; determining an initial query suggestion for a query of the data source based on the non-query data, the determining comprising: comparing the non-query data to prior query information; determining that at least a portion of the non-query data is associated with a portion of the prior query information; and generating the initial query suggestion based, at least in part, on the portion of the prior query information; returning the initial query suggestion; receiving an indication of action on the initial query suggestion; determining an additional query suggestion for the query for the data source, the query comprises data indicative of at least a portion of a query statement; and returning the additional query suggestion. 5. The computer-implemented method of claim 1 , wherein the returning the initial query suggestion comprises returning the initial query suggestion through a user interface (UI) element.

2. The computer-implemented method of claim 1 wherein dynamically generating parser classes and methods further comprises: for each property, reading associative values representing the attributes of the property to generate a class variable; and associating each class variable with accessor and mutator methods.

2. The computer-implemented method of claim 1 wherein dynamically generating parser classes and methods further comprises: for each property, reading associative values representing the attributes of the property to generate a class variable; and associating each class variable with accessor and mutator methods. 4. The computer-implemented method of claim 2 further comprising: responsive to a presence of a validation attribute, adding validation information to the accessor or the mutator of the class variable to which the validation attribute corresponds.

1. A method that assesses character-rendering quality, the method comprising: transmitting a test-character set of test characters to a character-rendering device for rendering; intercepting digital pixel-based character maps for the test characters of the test-character set, used by the character-rendering device for rendering the test characters, to serve as an input-character set of input characters; capturing, with a computing system, the test characters rendered by the character-rendering device to serve as an output-character set of output characters; for each input character, generating with the computing system, from the intercepted input characters, one or more first metrics that reflect differences between the input character and at least two of the input characters; for each output character, generating with the computing system, from the intercepted input characters and the captured output characters, one or more second metrics that reflect differences between the output character and at least two of the input characters; and outputting one or more indications of character-rendering quality based on the first and second metrics.

1. A method that assesses character-rendering quality, the method comprising: transmitting a test-character set of test characters to a character-rendering device for rendering; intercepting digital pixel-based character maps for the test characters of the test-character set, used by the character-rendering device for rendering the test characters, to serve as an input-character set of input characters; capturing, with a computing system, the test characters rendered by the character-rendering device to serve as an output-character set of output characters; for each input character, generating with the computing system, from the intercepted input characters, one or more first metrics that reflect differences between the input character and at least two of the input characters; for each output character, generating with the computing system, from the intercepted input characters and the captured output characters, one or more second metrics that reflect differences between the output character and at least two of the input characters; and outputting one or more indications of character-rendering quality based on the first and second metrics. 4. The method of claim 1 wherein test characters include: graphical symbols; English-language text characters; punctuation symbols; foreign-language text characters; and pixel patterns.

4. The humanoid robot of claim 1 , wherein an input in said at least one recognition module applies to text or voice inputs and activates a grammar in said dialog module.

4. The humanoid robot of claim 1 , wherein an input in said at least one recognition module applies to text or voice inputs and activates a grammar in said dialog module. 6. The humanoid robot of claim 4 , wherein said at least one recognition module includes a first and a second submodules, the first submodule operating on a closed list of words linked to at least one concept and the second submodule operating on an open list of words.

1. A method comprising: executing, by a computing device, software that (a) is written in a first programming language, (b) calls one or more native interpretive functions that interpret one or more non-native functions written in a second programming language different from the first programming language to enable the computing device to execute the one or more non-native functions, and (c) calls one or more native functions written in the first programming language for execution by the computing device, wherein each of the one or more native interpretive functions is written in the first programming language; and profiling execution of the software by: identifying, based on execution of the one or more native interpretive functions, which of the one or more non-native functions is interpreted by the one or more native interpretive functions, resulting in an identified non-native function, obtaining profile information that describes one or more characteristics of how the identified non-native function executed on the computing device, identifying which of the one or more native functions is being executed, resulting in an identified native function, and obtaining additional profile information that describes one or more characteristics of how the identified native function executed on the computing device.

1. A method comprising: executing, by a computing device, software that (a) is written in a first programming language, (b) calls one or more native interpretive functions that interpret one or more non-native functions written in a second programming language different from the first programming language to enable the computing device to execute the one or more non-native functions, and (c) calls one or more native functions written in the first programming language for execution by the computing device, wherein each of the one or more native interpretive functions is written in the first programming language; and profiling execution of the software by: identifying, based on execution of the one or more native interpretive functions, which of the one or more non-native functions is interpreted by the one or more native interpretive functions, resulting in an identified non-native function, obtaining profile information that describes one or more characteristics of how the identified non-native function executed on the computing device, identifying which of the one or more native functions is being executed, resulting in an identified native function, and obtaining additional profile information that describes one or more characteristics of how the identified native function executed on the computing device. 11. The method recited in claim 1 , further comprising: profiling the execution of the software by identifying the execution of the one or more native interpretive functions based on an examination of program stack logs periodically during execution of the software.

5. The computer-implemented method of claim 4 , wherein said human searchers are divided into the groups based on search skills of the human searchers subsequent to determining whether the searcher is available for training, and conducting said training based on the groups.

5. The computer-implemented method of claim 4 , wherein said human searchers are divided into the groups based on search skills of the human searchers subsequent to determining whether the searcher is available for training, and conducting said training based on the groups. 7. The computer-implemented method of claim 5 , wherein said dividing includes dividing the human searchers into apprentices, pros, and masters, and conducting said training based on the dividing.

9. A computer-readable storage device containing computer-executable instructions for controlling a computing device to generate a compact representation of an image, by a method comprising: for each of a plurality of blocks of pixels of the image, calculating for the block a representative intensity level derived from intensities of the pixels of the block; performing a discrete transform on the representative intensity levels for the blocks to generate transformed coefficients; applying a principal component analysis to the transformed coefficients to generate PCA coefficients of a reduced dimensionality; and setting each bit of a vector with an element corresponding to a PCA coefficient based on the value of the PCA coefficient wherein the bits represent the compact representation of the image.

9. A computer-readable storage device containing computer-executable instructions for controlling a computing device to generate a compact representation of an image, by a method comprising: for each of a plurality of blocks of pixels of the image, calculating for the block a representative intensity level derived from intensities of the pixels of the block; performing a discrete transform on the representative intensity levels for the blocks to generate transformed coefficients; applying a principal component analysis to the transformed coefficients to generate PCA coefficients of a reduced dimensionality; and setting each bit of a vector with an element corresponding to a PCA coefficient based on the value of the PCA coefficient wherein the bits represent the compact representation of the image. 13. The computer-readable storage device of claim 9 wherein the transform is a discrete cosine transform and the transformed coefficients do not include a DC coefficient.

9. A method comprising: retrieving data about a health care domain; encoding said data into a data modeling technique; performing a data quality rules discovery process using a data set of said health care domain and said data modeling technique encoded with said data to said data set to produce a plurality of data quality rules for said data set associated with said health care domain, said data quality rules discovery process comprising: applying each of a set of candidate conditional functional dependencies to a data segment having a predetermined length of data points of said data set; and after said applying, if a candidate conditional functional dependency has a result signature that does not meet a predetermined expectation, refining that candidate conditional functional dependency by eliminating an attribute in that candidate conditional functional dependency that took on the most values throughout the data set; and performing an analysis on said plurality of data quality rules to generate a derivative data quality rule for said data set.

9. A method comprising: retrieving data about a health care domain; encoding said data into a data modeling technique; performing a data quality rules discovery process using a data set of said health care domain and said data modeling technique encoded with said data to said data set to produce a plurality of data quality rules for said data set associated with said health care domain, said data quality rules discovery process comprising: applying each of a set of candidate conditional functional dependencies to a data segment having a predetermined length of data points of said data set; and after said applying, if a candidate conditional functional dependency has a result signature that does not meet a predetermined expectation, refining that candidate conditional functional dependency by eliminating an attribute in that candidate conditional functional dependency that took on the most values throughout the data set; and performing an analysis on said plurality of data quality rules to generate a derivative data quality rule for said data set. 16. The method of claim 9 , wherein said predetermined expectation comprises an error estimate of how may different data points would fail a candidate conditional functional dependency.

29. A machine-readable non-transitory medium having information recorded thereon for information search and retrieval, when read by the machine, causes the machine to perform the following: obtaining a query via a communication platform; processing the query to generate a feature-based vector characterizing the query; generating a semantic-based representation of the query based on the feature-based vector, wherein the semantic-based representation has a reduced dimension; constructing a reconstructed feature-based vector based on the semantic-based representation of the query, by mapping the semantic-based representation to a feature space of the feature-based vector; comparing the feature-based vector with the reconstructed feature-based vector to identify a difference between the feature-based vector and the reconstructed feature-based vector; forming a residual feature-based representation of the query based on the difference between the feature-based vector and the reconstructed feature-based vector; generating a unified representation of the query based on the semantic-based representation and the residual feature-based representation, wherein the unified representation integrates semantic and residual feature based characterizations of the query; retrieving information relevant to the query from an information archive based on the unified representation of the query; generating a query response based on the information relevant to the query retrieved from the information archive; and transmitting the query response to respond to the query.

29. A machine-readable non-transitory medium having information recorded thereon for information search and retrieval, when read by the machine, causes the machine to perform the following: obtaining a query via a communication platform; processing the query to generate a feature-based vector characterizing the query; generating a semantic-based representation of the query based on the feature-based vector, wherein the semantic-based representation has a reduced dimension; constructing a reconstructed feature-based vector based on the semantic-based representation of the query, by mapping the semantic-based representation to a feature space of the feature-based vector; comparing the feature-based vector with the reconstructed feature-based vector to identify a difference between the feature-based vector and the reconstructed feature-based vector; forming a residual feature-based representation of the query based on the difference between the feature-based vector and the reconstructed feature-based vector; generating a unified representation of the query based on the semantic-based representation and the residual feature-based representation, wherein the unified representation integrates semantic and residual feature based characterizations of the query; retrieving information relevant to the query from an information archive based on the unified representation of the query; generating a query response based on the information relevant to the query retrieved from the information archive; and transmitting the query response to respond to the query. 31. The medium of claim 29 , wherein the step of retrieving comprises: generating a first index value based on the unified representation of the query; identifying a second index value stored in an indexing system of the information archive; obtaining a group of information items in the information archive that have similar index values; and selecting the information relevant to the query from the obtained group of information items.

12. A computer program product, encoded on a computer-readable storage device, operable to cause data processing apparatus to perform operations comprising: generating a language model, including: identifying a collection of n-grams from a corpus of training data; determining, for each n-gram of the collection, a corresponding relative frequency of occurring in the corpus, each n-gram being a sequence of tokens of length k, wherein k is an integer between 1 and a maximum length N; and identifying a set of backoff factors α k , one backoff factor for each value of k from 2 to N, inclusive, where the backoff factors can be used to identify a backoff score S k for any n-gram of length k that is not present in the language model, wherein each n-gram of length k that is not present in the language model has a particular longest backoff n-gram that is present in the collection of n-grams and that has a particular relative frequency f and a particular length m, wherein the backoff score S k is determined as a function of the collection of backoff factors, the particular length m and the particular relative frequency f of the particular longest backoff n-gram.

12. A computer program product, encoded on a computer-readable storage device, operable to cause data processing apparatus to perform operations comprising: generating a language model, including: identifying a collection of n-grams from a corpus of training data; determining, for each n-gram of the collection, a corresponding relative frequency of occurring in the corpus, each n-gram being a sequence of tokens of length k, wherein k is an integer between 1 and a maximum length N; and identifying a set of backoff factors α k , one backoff factor for each value of k from 2 to N, inclusive, where the backoff factors can be used to identify a backoff score S k for any n-gram of length k that is not present in the language model, wherein each n-gram of length k that is not present in the language model has a particular longest backoff n-gram that is present in the collection of n-grams and that has a particular relative frequency f and a particular length m, wherein the backoff score S k is determined as a function of the collection of backoff factors, the particular length m and the particular relative frequency f of the particular longest backoff n-gram. 13. The computer program product of claim 12 , where identifying the set of backoff factors comprises: performing discriminative training on a set of sample data, the discriminative training identifying values for the set of backoff factors that maximize a measure of translation quality.

12. The method of claim 8 , wherein for each retrieved advertisement, the estimated probability that the retrieved advertisement is of interest to the user is determined according to information regarding the user.

12. The method of claim 8 , wherein for each retrieved advertisement, the estimated probability that the retrieved advertisement is of interest to the user is determined according to information regarding the user. 13. The method of claim 12 , wherein the information regarding the user is maintained remotely from the computer running the browser program.

4. The method of claim 1 wherein creating the presentation grammar for the structured document comprises: identifying a content type of the original document; selecting, in dependence upon the content type, a full presentation grammar from among a multiplicity of full presentation grammars; and filtering the full presentation grammar into the presentation grammar for the structured document in dependence upon the structural elements of the structured document.

4. The method of claim 1 wherein creating the presentation grammar for the structured document comprises: identifying a content type of the original document; selecting, in dependence upon the content type, a full presentation grammar from among a multiplicity of full presentation grammars; and filtering the full presentation grammar into the presentation grammar for the structured document in dependence upon the structural elements of the structured document. 5. The method of claim 4 wherein identifying the content type comprises identifying the content type in dependence upon a filename extension.

1. A method comprising: under control of one or more processors configured with executable instructions: acquiring time sequential ink data for a character; conditioning the time sequential ink data to separate ink trajectories of real strokes and imaginary strokes into a plurality of ink frames, the conditioning comprising generating a plurality of contiguous time sequential frames for each imaginary stroke; extracting features from each ink frame of the conditioned ink data; and recognizing the character based on the extracted features using a character recognition model.

1. A method comprising: under control of one or more processors configured with executable instructions: acquiring time sequential ink data for a character; conditioning the time sequential ink data to separate ink trajectories of real strokes and imaginary strokes into a plurality of ink frames, the conditioning comprising generating a plurality of contiguous time sequential frames for each imaginary stroke; extracting features from each ink frame of the conditioned ink data; and recognizing the character based on the extracted features using a character recognition model. 4. The method as recited in claim 1 , wherein the conditioning further comprises re-sampling the time sequential ink data to convert the time sequential ink data into uniform sampled data, the sampled data enabling the character recognition model to perform character recognition independent of a speed of writing the character.

1. A method for massive-model visualization, comprising: storing a hierarchical product data structure by a product data management (PDM) system, the hierarchical product data structure including a plurality of occurrence nodes and component nodes, the component nodes including a cell index value for a corresponding product component that identifies the product component's spatial location according to defined cells of a three-dimensional model of the product assembly; receiving a query that references an occurrence node and at least one cell index value; determining a query result corresponding to the query, by the PDM system, the query result identifying at least one occurrence node that corresponds to the cell index value; forming a query result chain corresponding to the query result, the query result chain filtered by a structural criterion; applying a configuration rule to the filtered query result chain, by the PDM system, to identify child nodes of the filtered query result chain that conform to the configuration rule, and thereby producing a configured spatial retrieval result, wherein the configuration rule is only applied to occurrence nodes and occurrence chains that have already satisfied spatial constraints; and storing the configured spatial retrieval result.

1. A method for massive-model visualization, comprising: storing a hierarchical product data structure by a product data management (PDM) system, the hierarchical product data structure including a plurality of occurrence nodes and component nodes, the component nodes including a cell index value for a corresponding product component that identifies the product component's spatial location according to defined cells of a three-dimensional model of the product assembly; receiving a query that references an occurrence node and at least one cell index value; determining a query result corresponding to the query, by the PDM system, the query result identifying at least one occurrence node that corresponds to the cell index value; forming a query result chain corresponding to the query result, the query result chain filtered by a structural criterion; applying a configuration rule to the filtered query result chain, by the PDM system, to identify child nodes of the filtered query result chain that conform to the configuration rule, and thereby producing a configured spatial retrieval result, wherein the configuration rule is only applied to occurrence nodes and occurrence chains that have already satisfied spatial constraints; and storing the configured spatial retrieval result. 2. The method of claim 1 , wherein the PDM system receives performs a lookup process on an occurrence equivalency table and anchor occurrence table, and determines the query result that identifies occurrence chains corresponding to the query.

2. The tangible machine-readable medium of claim 1 , wherein the behavior model includes time-stamped vectors.

2. The tangible machine-readable medium of claim 1 , wherein the behavior model includes time-stamped vectors. 3. The tangible machine-readable medium of claim 2 , wherein the instructions, when executed, cause the machine to correlate the time-stamped vectors to predict the usage of an application on the wireless device.

1. A method, comprising: maintaining an online grammar model used by an online voice-based query processor to parse online voice-based queries, the online grammar model mapping a plurality of queries to actions, wherein the actions include non-search actions performable by a computer system, wherein each of the actions is mapped in the grammar model to one or more corresponding queries of the plurality of queries, and wherein each of a plurality of the actions includes one or more corresponding parameters for constraining performance of the action; analyzing query usage data for at least a subset of the plurality of queries to identify a subset of popular queries from among the plurality of queries mapped by the online grammar model, wherein the query usage data includes query usage data collected for queries issued by a plurality of users; and building an offline grammar model that maps the subset of popular queries to actions among the actions for use by a resource-constrained offline device, wherein the offline grammar model has reduced resource requirements relative to the online grammar model and omits mappings for one or more queries among the plurality of queries.

1. A method, comprising: maintaining an online grammar model used by an online voice-based query processor to parse online voice-based queries, the online grammar model mapping a plurality of queries to actions, wherein the actions include non-search actions performable by a computer system, wherein each of the actions is mapped in the grammar model to one or more corresponding queries of the plurality of queries, and wherein each of a plurality of the actions includes one or more corresponding parameters for constraining performance of the action; analyzing query usage data for at least a subset of the plurality of queries to identify a subset of popular queries from among the plurality of queries mapped by the online grammar model, wherein the query usage data includes query usage data collected for queries issued by a plurality of users; and building an offline grammar model that maps the subset of popular queries to actions among the actions for use by a resource-constrained offline device, wherein the offline grammar model has reduced resource requirements relative to the online grammar model and omits mappings for one or more queries among the plurality of queries. 11. The method of claim 1 , wherein analyzing the query usage data includes, for a first action among the actions: determining a distribution of queries from among a plurality of queries mapped to the first action by the online grammar model using the collected query usage data; and including a top N queries from among the plurality of queries mapped to the first action in the identified subset of popular queries.

22. A non-transitory computer-readable storage medium storing executable computer program instructions for automatically deconstructing an educational course into discrete learning units, the computer program instructions comprising instructions for: analyzing content related to an educational course stored by an education platform; extracting distinct concepts from the content; identifying passive, active, and recall user activities associated with respective distinct concepts, including instructions for: extracting a time duration for each passive, active, and recall activity from users activity logs, normalizing the extracted time durations across users, and reporting the normalized extracted time durations; generating a plurality of learning units, each learning unit comprising a distinct concept and the passive, active, and recall user activities associated with the distinct concept; and delivering at least one discrete learning unit to a registered user through the education platform.

22. A non-transitory computer-readable storage medium storing executable computer program instructions for automatically deconstructing an educational course into discrete learning units, the computer program instructions comprising instructions for: analyzing content related to an educational course stored by an education platform; extracting distinct concepts from the content; identifying passive, active, and recall user activities associated with respective distinct concepts, including instructions for: extracting a time duration for each passive, active, and recall activity from users activity logs, normalizing the extracted time durations across users, and reporting the normalized extracted time durations; generating a plurality of learning units, each learning unit comprising a distinct concept and the passive, active, and recall user activities associated with the distinct concept; and delivering at least one discrete learning unit to a registered user through the education platform. 25. The non-transitory computer-readable storage medium of claim 22 , wherein a time allotted in a schedule for the learning unit is predicted based on reported activities of a plurality of users.

1. A computer-implemented method, comprising: receiving, by a computing system, a query that was defined by user input at a computing device; identifying, by the computing system, documents that are responsive to the received query, wherein the documents that are responsive to the received query include a particular document; identifying, by the computing system, that the particular document matches another document; identifying, by the computing system, information that reflects a ranking of the another document as a result for one or more queries; determining, by the computing system and in response to having identified the information that reflects the ranking of the another document as the result for the one or more queries, a score to assign to the particular document using the information that reflects the ranking of the another document as the result for the one or more queries, wherein the computing system has determined a score to assign to each of the documents that are responsive to the received query; ranking, by the computing system and in response to having received the query, each of the documents that are responsive to the received query using the scores that have been assigned to the documents that are responsive to the received query, including the determined score that was assigned to the particular document, to generate a ranking of the documents that are responsive to the received query; and providing, by the computing system and in response to having received the query, information for receipt by the computing device so as to cause the computing device to present a display of search results that identify the documents that are responsive to the received query and that are presented in an order that is defined by the generated ranking.

1. A computer-implemented method, comprising: receiving, by a computing system, a query that was defined by user input at a computing device; identifying, by the computing system, documents that are responsive to the received query, wherein the documents that are responsive to the received query include a particular document; identifying, by the computing system, that the particular document matches another document; identifying, by the computing system, information that reflects a ranking of the another document as a result for one or more queries; determining, by the computing system and in response to having identified the information that reflects the ranking of the another document as the result for the one or more queries, a score to assign to the particular document using the information that reflects the ranking of the another document as the result for the one or more queries, wherein the computing system has determined a score to assign to each of the documents that are responsive to the received query; ranking, by the computing system and in response to having received the query, each of the documents that are responsive to the received query using the scores that have been assigned to the documents that are responsive to the received query, including the determined score that was assigned to the particular document, to generate a ranking of the documents that are responsive to the received query; and providing, by the computing system and in response to having received the query, information for receipt by the computing device so as to cause the computing device to present a display of search results that identify the documents that are responsive to the received query and that are presented in an order that is defined by the generated ranking. 2. The computer-implemented method of claim 1 , further comprising: determining, by the computing system, that the particular document matches the another document by determining that content of the particular document matches content of the another document.

20. The method recited in claim 19 , further comprising: representing the text of the local web page information of the plurality of first web pages, the plurality of second web pages, and the third web page using at least one dimensional vector of words; and representing the hyperlink relationships of the global web graph information about the plurality of first web pages, the plurality of second web pages, and the third web page using a graph that comprises a plurality of nodes and a plurality of edges, wherein each node of the graph represents one of the web pages, and each edge of the graph connects two of the nodes where the corresponding two web pages are linked.

20. The method recited in claim 19 , further comprising: representing the text of the local web page information of the plurality of first web pages, the plurality of second web pages, and the third web page using at least one dimensional vector of words; and representing the hyperlink relationships of the global web graph information about the plurality of first web pages, the plurality of second web pages, and the third web page using a graph that comprises a plurality of nodes and a plurality of edges, wherein each node of the graph represents one of the web pages, and each edge of the graph connects two of the nodes where the corresponding two web pages are linked. 21. The method recited in claim 20 , wherein determining the quality of the third web page using collective inference comprises applying a dual algorithm for binary classification of the third web page based on the local web page information of and the global web graph information about the plurality of first web pages, the local web page information of and the global web graph information about the plurality of second web pages, and the local web page information of and the global web graph information about the third web page.

29. The computer system of claim 25 , wherein the indexing is performed at times based upon times selected by the user.

29. The computer system of claim 25 , wherein the indexing is performed at times based upon times selected by the user. 30. The computer system of claim 29 , wherein the indexing is performed every two days in accordance with the times selected by the user.

1. A method of operation in an automated Web portal generation system to generate sets of customizations of Web portal templates, the method comprising: parsing, by at least one component of the automated Web portal generation system, a number of Webpages of a first Website, represented by a domain or Universal Resource Locator (URL), from which a Web portal template to be customized is to be accessed; producing an entity feature set for the first Website based on a result of the parsing; processing the entity feature set for the first Website via a classifier executed by at least one component of the automated Web portal generation system to produce a set of data that represents, for each of a plurality of entities, a respective probability of the entity belonging to a respective one of a plurality of classes; performing color matching on the set of data produced via the classifier to generate a number of proposed color combinations for a proposed customization of the Web portal template, wherein performing color matching to generate a number of proposed color combinations includes identifying candidate background colors by evaluating contrast between colors of each pair of a plurality of pairs of colors in a device-independent color space; ranking pairs of color combinations based at least in part on the probabilities from the processing via the classifier; returning the ranking as a collection of results for user evaluation; and identifying one of the proposed color combinations for a proposed customization of the Web portal template.

1. A method of operation in an automated Web portal generation system to generate sets of customizations of Web portal templates, the method comprising: parsing, by at least one component of the automated Web portal generation system, a number of Webpages of a first Website, represented by a domain or Universal Resource Locator (URL), from which a Web portal template to be customized is to be accessed; producing an entity feature set for the first Website based on a result of the parsing; processing the entity feature set for the first Website via a classifier executed by at least one component of the automated Web portal generation system to produce a set of data that represents, for each of a plurality of entities, a respective probability of the entity belonging to a respective one of a plurality of classes; performing color matching on the set of data produced via the classifier to generate a number of proposed color combinations for a proposed customization of the Web portal template, wherein performing color matching to generate a number of proposed color combinations includes identifying candidate background colors by evaluating contrast between colors of each pair of a plurality of pairs of colors in a device-independent color space; ranking pairs of color combinations based at least in part on the probabilities from the processing via the classifier; returning the ranking as a collection of results for user evaluation; and identifying one of the proposed color combinations for a proposed customization of the Web portal template. 14. The method of claim 1 wherein identifying candidate background colors includes accounting for visually active or passive positions of the corresponding entities.

11. An apparatus, comprising: a storage device; and a processor coupled to the storage device, wherein the storage device stores a program for controlling the processor, and wherein the processor, being operative with the program, is configured to: identify first mapping data for mapping values of a source attribute into at least one value of a conceptual attribute, the source attribute being associated with a source model, the conceptual attribute being associated with a conceptual model; generate, based on the first mapping data, suggested mapping formulas for transforming the source attribute values into the at least one conceptual attribute value, the suggested mapping formulas being associated with probability values indicative of a probability that the transformed source attribute values match the at least one conceptual attribute value; establish a corresponding one of the suggested mapping formulas as a first mapping formula, the first mapping formula being associated with a probability value that exceeds a predetermined value; generate second mapping data for mapping the conceptual attribute to a target attribute of a target model; and based on the second mapping data and the first mapping formula, generate a second mapping formula for transforming the conceptual attribute value into at least one value associated with the target attribute.

11. An apparatus, comprising: a storage device; and a processor coupled to the storage device, wherein the storage device stores a program for controlling the processor, and wherein the processor, being operative with the program, is configured to: identify first mapping data for mapping values of a source attribute into at least one value of a conceptual attribute, the source attribute being associated with a source model, the conceptual attribute being associated with a conceptual model; generate, based on the first mapping data, suggested mapping formulas for transforming the source attribute values into the at least one conceptual attribute value, the suggested mapping formulas being associated with probability values indicative of a probability that the transformed source attribute values match the at least one conceptual attribute value; establish a corresponding one of the suggested mapping formulas as a first mapping formula, the first mapping formula being associated with a probability value that exceeds a predetermined value; generate second mapping data for mapping the conceptual attribute to a target attribute of a target model; and based on the second mapping data and the first mapping formula, generate a second mapping formula for transforming the conceptual attribute value into at least one value associated with the target attribute. 17. The apparatus of claim 11 , wherein the processor further configured to: determine a conceptual layout for the conceptual model, a source layout for the source model, and a target layout for the target model; and generate (i) a first instruction to display the source model to a user in accordance to the source layout, (ii) a second instruction to display the conceptual model to the user in accordance with the conceptual layout, and (iii) a third instruction to display the target model to the user in accordance with the target layout.

6. The system as recited in claim 1 , wherein said expression whose type is context-dependent comprises a lambda expression, wherein said one or more invocable operation declarations comprise (a) a first method declaration with a first function type as a parameter and (b) a second method declaration with a second function type as a parameter, wherein to determine whether a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria, the one or more computing devices are configured to: determine whether parameter types of the first method declaration are subtypes of corresponding parameter types of the second method declaration; and in response to determining that parameter types of the first method declaration are subtypes of the corresponding parameter types of the second method declaration, determine that the first method declaration is more specific than the second method declaration.

6. The system as recited in claim 1 , wherein said expression whose type is context-dependent comprises a lambda expression, wherein said one or more invocable operation declarations comprise (a) a first method declaration with a first function type as a parameter and (b) a second method declaration with a second function type as a parameter, wherein to determine whether a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria, the one or more computing devices are configured to: determine whether parameter types of the first method declaration are subtypes of corresponding parameter types of the second method declaration; and in response to determining that parameter types of the first method declaration are subtypes of the corresponding parameter types of the second method declaration, determine that the first method declaration is more specific than the second method declaration. 7. The system as recited in claim 6 , wherein the one or more computing devices are further configured to: in response to determining that parameter types of the first method declaration are not subtypes of corresponding parameter types of the second method declaration, determine whether the first and second function types have the same function descriptor parameter types; and in response to determining that the first and second function types have the same function descriptor parameter types, determine that the first method declaration is more specific than the second method declaration based at least in part on an analysis of at least the function descriptor return types of the first and second methods.

3. The computer-implemented method of claim 2 , further comprising: receiving feedback from the user during display of the first or second portions of the first document through the GUI for the determined amount of time; based on the received feedback, adjusting the respective determined amount of time; and displaying a third portion of the first document to the user through the GUI for the adjusted amount of time.

3. The computer-implemented method of claim 2 , further comprising: receiving feedback from the user during display of the first or second portions of the first document through the GUI for the determined amount of time; based on the received feedback, adjusting the respective determined amount of time; and displaying a third portion of the first document to the user through the GUI for the adjusted amount of time. 4. The computer-implemented method of claim 3 , wherein the received feedback comprises at least one of a command to change the GUI from displaying the second portion of the first document to the first portion of the first document subsequent to expiration of the respective determined amount of time, or a command to change the GUI from displaying the first portion of the first document to the second portion of the first document prior to expiration of the respective determined amount of time.

1. A search system comprising: a database for storing information including a plurality of documents to be searched for; and a computer system with at least one processor, and further including: a communication processing unit to receive a search request including a search word, send the search request to search the database, and send a search result; and a search engine to receive the search request through the communication processing unit and search for the information, said search engine comprising: a token assignment unit to extract a character string from each of the documents of the information and assign a plurality of different kinds of tokens to each document with each kind of token obtained by applying a corresponding character string analysis to the character string extracted from that document, wherein a combination of at least two different types of character string analyses are applied to assign the plurality of different kinds of tokens to each document; an index generating unit to generate an index list that registers the tokens, a token type identifying a corresponding type of the character string analysis used, an information identification value for identifying the registered information, and a score for each of the plurality of kinds of tokens; a search processing unit to: receive the search word used for inquiring for the information; extract a plurality of kinds of search tokens from the search word by applying the different types of character string analyses to the search word; link the plurality of kinds of search tokens extracted from the search word in parallel to issue a search command to inquire the information in parallel for searching through the index list based on the search command; and determine a total score for each of one or more documents of the information by identifying one or more of the plurality of kinds of tokens assigned to that document matching the search tokens of the search word and combining the scores of each of the identified plurality of kinds of tokens; a search result generating unit to generate a file used for displaying the information obtained by searching in association with the search word upon performing the parallel inquiry, as a search result and ordering within the file the information obtained by searching based on the total scores for the one or more documents.

1. A search system comprising: a database for storing information including a plurality of documents to be searched for; and a computer system with at least one processor, and further including: a communication processing unit to receive a search request including a search word, send the search request to search the database, and send a search result; and a search engine to receive the search request through the communication processing unit and search for the information, said search engine comprising: a token assignment unit to extract a character string from each of the documents of the information and assign a plurality of different kinds of tokens to each document with each kind of token obtained by applying a corresponding character string analysis to the character string extracted from that document, wherein a combination of at least two different types of character string analyses are applied to assign the plurality of different kinds of tokens to each document; an index generating unit to generate an index list that registers the tokens, a token type identifying a corresponding type of the character string analysis used, an information identification value for identifying the registered information, and a score for each of the plurality of kinds of tokens; a search processing unit to: receive the search word used for inquiring for the information; extract a plurality of kinds of search tokens from the search word by applying the different types of character string analyses to the search word; link the plurality of kinds of search tokens extracted from the search word in parallel to issue a search command to inquire the information in parallel for searching through the index list based on the search command; and determine a total score for each of one or more documents of the information by identifying one or more of the plurality of kinds of tokens assigned to that document matching the search tokens of the search word and combining the scores of each of the identified plurality of kinds of tokens; a search result generating unit to generate a file used for displaying the information obtained by searching in association with the search word upon performing the parallel inquiry, as a search result and ordering within the file the information obtained by searching based on the total scores for the one or more documents. 6. The search system according to claim 1 , wherein the database is managed with a remote server connected through the communication processing unit.

7. A computer-implemented method performed by a client device, the method comprising: (A) receiving a request from a requester to apply automatic speech recognition to an audio signal; (B) providing the audio signal to a first automatic speech recognition engine in the client device; (C) providing the audio signal to a second automatic speech recognition engine in a server device; (D) receiving first speech recognition results from the first automatic speech recognition engine; (E) determining whether a confidence measure associated with the first speech recognition results exceeds a predetermined threshold; and (F) if the confidence measure exceeds the predetermined threshold, then providing the first speech recognition results to the requester in response to the request.

7. A computer-implemented method performed by a client device, the method comprising: (A) receiving a request from a requester to apply automatic speech recognition to an audio signal; (B) providing the audio signal to a first automatic speech recognition engine in the client device; (C) providing the audio signal to a second automatic speech recognition engine in a server device; (D) receiving first speech recognition results from the first automatic speech recognition engine; (E) determining whether a confidence measure associated with the first speech recognition results exceeds a predetermined threshold; and (F) if the confidence measure exceeds the predetermined threshold, then providing the first speech recognition results to the requester in response to the request. 8. The method of claim 7 , further comprising: (G) before (F), receiving second speech recognition results from the second automatic speech recognition engine; and wherein (F) comprises providing the first speech recognition results but not the second speech recognition results to the requester.

7. A system for image-based retrieval and rendering, the system comprising: a first physical device comprising hardware, the first device extracting a plurality of distinctive local descriptors from the content of a digital image; a second physical device comprising hardware, the second device indexing a set of digitally-stored documents by extracting a plurality of distinctive local descriptors from the content of each document in the set; a third physical device comprising hardware, the third device matching the digital image against the set of digitally-stored documents by using near-duplicate image detection to compare corresponding distinctive local descriptors of the digital image and each document in the indexed set, wherein near-duplicate image detection comprises using locality-sensitive hashing; a fourth physical device comprising hardware, the fourth device retrieving a digitally-stored document from the set of digitally-stored documents that matches the digital image, the retrieved digitally stored document comprising a composite of images of a plurality of articles in a defined layout, wherein each of the plurality of articles has a corresponding article layout; a fifth physical device comprising hardware, the fifth device retrieving, after the digital image is matched and the digitally-stored document is retrieved, from the composite of images, one article from the plurality of articles that corresponds to the digital image based on overlapping areas associated with the plurality of articles, wherein for each article of the plurality of articles, the overlapping area is between the boundary of the corresponding article layout of the article and the boundary of the complete digital image, the retrieved article having the greatest overlapping area among the overlapping areas; and a sixth physical device comprising hardware, the sixth device rendering the retrieved article for output to a user device, wherein rendering includes at least one of: converting the retrieved article to text and converting the text to speech, and converting the retrieved article for Braille output.

7. A system for image-based retrieval and rendering, the system comprising: a first physical device comprising hardware, the first device extracting a plurality of distinctive local descriptors from the content of a digital image; a second physical device comprising hardware, the second device indexing a set of digitally-stored documents by extracting a plurality of distinctive local descriptors from the content of each document in the set; a third physical device comprising hardware, the third device matching the digital image against the set of digitally-stored documents by using near-duplicate image detection to compare corresponding distinctive local descriptors of the digital image and each document in the indexed set, wherein near-duplicate image detection comprises using locality-sensitive hashing; a fourth physical device comprising hardware, the fourth device retrieving a digitally-stored document from the set of digitally-stored documents that matches the digital image, the retrieved digitally stored document comprising a composite of images of a plurality of articles in a defined layout, wherein each of the plurality of articles has a corresponding article layout; a fifth physical device comprising hardware, the fifth device retrieving, after the digital image is matched and the digitally-stored document is retrieved, from the composite of images, one article from the plurality of articles that corresponds to the digital image based on overlapping areas associated with the plurality of articles, wherein for each article of the plurality of articles, the overlapping area is between the boundary of the corresponding article layout of the article and the boundary of the complete digital image, the retrieved article having the greatest overlapping area among the overlapping areas; and a sixth physical device comprising hardware, the sixth device rendering the retrieved article for output to a user device, wherein rendering includes at least one of: converting the retrieved article to text and converting the text to speech, and converting the retrieved article for Braille output. 13. The system of claim 7 , wherein converting the retrieved article for Braille output includes converting the retrieved article to text.

1. A computer-implemented method of displaying information about a document that includes a plurality of spatial identifiers each of which identifies a corresponding location within a metric space and at least two of the locations of the spatial identifiers have a geometric relationship to each other, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; displaying a map image of a portion of the metric space; displaying a visual indicator at a position on the map image representing the location that corresponds to one of said plurality of spatial identifiers; visually indicating that the location corresponding to the visual indicator has associated data that characterizes the geometric relationship between that location and the location of another spatial identifier in the document, wherein the geometric relationship is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, the at least two corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations.

1. A computer-implemented method of displaying information about a document that includes a plurality of spatial identifiers each of which identifies a corresponding location within a metric space and at least two of the locations of the spatial identifiers have a geometric relationship to each other, said method comprising: displaying at least a portion of content from the document, wherein the at least one portion of content is a natural language; displaying a map image of a portion of the metric space; displaying a visual indicator at a position on the map image representing the location that corresponds to one of said plurality of spatial identifiers; visually indicating that the location corresponding to the visual indicator has associated data that characterizes the geometric relationship between that location and the location of another spatial identifier in the document, wherein the geometric relationship is determined by a path hierarchy for each location; and visually differentiating, by visually promoting and highlighting differently, the at least two corresponding locations based on attributes that are defined with reference to the document, wherein the locations that are metonymic are given less prominent visual emphasis than other locations. 3. The computer-implemented method of claim 1 , wherein the geometric relationship is one of being contained in another location.

11. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with one or more processors and memory, cause the electronic device to: generate a decoding network for decoding speech input, the decoding network comprising a primary sub-network and one or more classification sub-networks, wherein: the primary sub-network includes a plurality of classification nodes, each classification node corresponding to a respective classification sub-network of the one or more classification sub-networks, wherein each respective classification sub-network is distinct from the primary sub-network; and each classification sub-network of the one or more classification sub-networks corresponds to a group of uncommon words; receive a speech input; and decode the speech input by: instantiating a token corresponding to the speech input in the primary sub-network; passing the token through the primary sub-network; when the token reaches a respective classification node of the plurality of classification nodes, transferring the token to the corresponding classification sub-network; passing the token through the corresponding classification sub-network; when the token reaches an accept node of the classification sub-network, returning a result of the token passing through the classification sub-network to the primary sub-network, wherein the result includes one or more words in the group of uncommon words corresponding to the classification sub-network; output a string corresponding to the speech input that includes the one or more words.

11. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with one or more processors and memory, cause the electronic device to: generate a decoding network for decoding speech input, the decoding network comprising a primary sub-network and one or more classification sub-networks, wherein: the primary sub-network includes a plurality of classification nodes, each classification node corresponding to a respective classification sub-network of the one or more classification sub-networks, wherein each respective classification sub-network is distinct from the primary sub-network; and each classification sub-network of the one or more classification sub-networks corresponds to a group of uncommon words; receive a speech input; and decode the speech input by: instantiating a token corresponding to the speech input in the primary sub-network; passing the token through the primary sub-network; when the token reaches a respective classification node of the plurality of classification nodes, transferring the token to the corresponding classification sub-network; passing the token through the corresponding classification sub-network; when the token reaches an accept node of the classification sub-network, returning a result of the token passing through the classification sub-network to the primary sub-network, wherein the result includes one or more words in the group of uncommon words corresponding to the classification sub-network; output a string corresponding to the speech input that includes the one or more words. 13. The non-transitory computer readable storage medium of claim 11 , wherein: transferring the token to the corresponding classification sub-network further includes preserving one or more phones obtained prior to the token reaching the classification node as a starting index for the classification sub-network; and returning the result of the token passing through the classification sub-network to the primary sub-network includes preserving one or more phones obtained prior to the token reaching the accept node of the classification sub-network as a returning index for the primary decoding sub-network.

9. A method as recited in claim 7 , further comprising: before vectorizing, adjusting a dimension of the clipart image; extracting a stroke of the clipart image; extracting a region of the clipart image; and converting the extracted stroke and the extracted region into a vector-based representation.

9. A method as recited in claim 7 , further comprising: before vectorizing, adjusting a dimension of the clipart image; extracting a stroke of the clipart image; extracting a region of the clipart image; and converting the extracted stroke and the extracted region into a vector-based representation. 10. A method as recited in claim 9 , wherein extracting the stroke of the clipart image comprises: constructing a stroke mask; filling the stroke that has a region inside the extracted stroke; and removing a false stroke.

5. Apparatus for determining when a final conclusion can be made regarding the value of an output variable in a continuous-state feedforward neural network, despite some number of unknown input states, said apparatus comprising: a computer comprising a CPU, an input device coupled to the CPU, and an output device coupled to the CPU; wherein the neural network is fed into the CPU via the input device, and the CPU comprises an inference module comprising: means for making a tentative decision for the output variable by executing the neural network; coupled to said making means, means for determining high and low bounds on states of the output variable using the process of claim 5, wherein the process of claim 5 is executed on said CPU; coupled to the determining means, means for using the high and low bounds on the output states to determine if the tentative decision for the output variable can ever change; and coupled to the using means, means for declaring a final conclusion if the tentative decision cannot change and for sending a signal announcing the final conclusion to the output device.

5. Apparatus for determining when a final conclusion can be made regarding the value of an output variable in a continuous-state feedforward neural network, despite some number of unknown input states, said apparatus comprising: a computer comprising a CPU, an input device coupled to the CPU, and an output device coupled to the CPU; wherein the neural network is fed into the CPU via the input device, and the CPU comprises an inference module comprising: means for making a tentative decision for the output variable by executing the neural network; coupled to said making means, means for determining high and low bounds on states of the output variable using the process of claim 5, wherein the process of claim 5 is executed on said CPU; coupled to the determining means, means for using the high and low bounds on the output states to determine if the tentative decision for the output variable can ever change; and coupled to the using means, means for declaring a final conclusion if the tentative decision cannot change and for sending a signal announcing the final conclusion to the output device. 6. A computer-implemented process for computing a measure of certainty for a decision corresponding to the value of an output variable in a continuous-state feedforward neural network that is stored in a computer, said computer comprising a CPU and an output device coupled to the CPU, said CPU comprising an inference module, said neural network being stored with the CPU, said process comprising directing the inference module to perform the steps of: determining network output states given a set of input variables some of whose values are known and others of whose values are unknown; determining upper and lower bounds on the output states using the process of claim 5; comparing the bounds with a preselected conclusion criterion; determining a certainty of the decision by quantitatively measuring a closeness of the bounds to the conclusion criterion; and sending a signal to the output device corresponding to said certainty.

10. The method of claim 4 , wherein providing the indicator in proximity to the particular search result for presentation comprises: providing, for presentation, the indicator adjacent to a URL associated with the particular search result.

10. The method of claim 4 , wherein providing the indicator in proximity to the particular search result for presentation comprises: providing, for presentation, the indicator adjacent to a URL associated with the particular search result. 14. The method of claim 10 , wherein providing the reordered search results for presentation comprises providing the search results for presentation on a user device, and wherein the method further comprises: designating the configurable number of entries to include in the group based on a type of the user device.

1. A method, comprising: receiving a query word entered by a user and identifying source language of the query word, the source language being a natural language; translating, using a processor, the query word from the source language to query words of a plurality of target languages, the plurality of target languages being different than the source language; searching indices of web page information corresponding to the plurality of target languages based on the translated query words in the plurality of corresponding target languages to obtain web page information in the plurality of corresponding target languages, wherein the searching of the indices of web page information corresponding to the plurality of target languages comprises: acquiring domain information for characteristic domains corresponding to web page information in at least one target language, the characteristic domains including product information title, product information ID, product information keywords, product information attributes, product information categories, general description of the product information, detailed description of the product information, or any combination thereof; performing a normalization processing on the domain information based on semantic rules for the at least one target language and obtaining the smallest semantic unit in the at least one target language, the smallest semantic unit corresponds to a word or a phrase; wherein: the normalization processing includes one or more of: encoding processing, upper to lower case conversion, garbage character processing, improper character processing special character processing, division into sentences, division into words, reduction to word root, or elimination of tones; and establishing an index based on the characteristic domains and the smallest semantic unit in the corresponding characteristic domains; and searching the indices of the web page information corresponding to the plurality of target languages based on the smallest semantic unit in the plurality of target languages to obtain web page information in a corresponding target language, wherein the obtaining of the web page information in the corresponding target language comprises: calculating a first relevance weight of web page information in a first target language and a query word in the first target language; calculating a second relevance weight of web page information in a second target language and a query word in the second target language; and ranking web page information in the first and second target languages based on the first and second relevance weights to obtain the web page information in the corresponding target language; from the web page information obtained from the indices corresponding to the plurality of target languages, translating, using the processor, the obtained web page information from the plurality of target languages to the source language; and sending back at least one piece of the obtained translated web page information to the user.

1. A method, comprising: receiving a query word entered by a user and identifying source language of the query word, the source language being a natural language; translating, using a processor, the query word from the source language to query words of a plurality of target languages, the plurality of target languages being different than the source language; searching indices of web page information corresponding to the plurality of target languages based on the translated query words in the plurality of corresponding target languages to obtain web page information in the plurality of corresponding target languages, wherein the searching of the indices of web page information corresponding to the plurality of target languages comprises: acquiring domain information for characteristic domains corresponding to web page information in at least one target language, the characteristic domains including product information title, product information ID, product information keywords, product information attributes, product information categories, general description of the product information, detailed description of the product information, or any combination thereof; performing a normalization processing on the domain information based on semantic rules for the at least one target language and obtaining the smallest semantic unit in the at least one target language, the smallest semantic unit corresponds to a word or a phrase; wherein: the normalization processing includes one or more of: encoding processing, upper to lower case conversion, garbage character processing, improper character processing special character processing, division into sentences, division into words, reduction to word root, or elimination of tones; and establishing an index based on the characteristic domains and the smallest semantic unit in the corresponding characteristic domains; and searching the indices of the web page information corresponding to the plurality of target languages based on the smallest semantic unit in the plurality of target languages to obtain web page information in a corresponding target language, wherein the obtaining of the web page information in the corresponding target language comprises: calculating a first relevance weight of web page information in a first target language and a query word in the first target language; calculating a second relevance weight of web page information in a second target language and a query word in the second target language; and ranking web page information in the first and second target languages based on the first and second relevance weights to obtain the web page information in the corresponding target language; from the web page information obtained from the indices corresponding to the plurality of target languages, translating, using the processor, the obtained web page information from the plurality of target languages to the source language; and sending back at least one piece of the obtained translated web page information to the user. 3. The method as described in claim 1 , the translating of the query word from the source language to the query words of the plurality of target languages comprises: calculating a first translation weight for translation of the query word from the source language to the query words in the plurality of target languages.

26. A computer program product tangibly embodied on a computer readable storage device, the computer program product comprising instructions for causing a processor to: display a sequence of words on a user interface rendered on a display device; apply in response to a user-based selection of a first portion of words in the sequence of words, a first indicium to the user-selected first portion of words in the sequence of words; associate a first character having an associated first voice model to the first portion of words in the sequence of words; and associate a second character having an associated second, different voice model to a second, different portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words.

26. A computer program product tangibly embodied on a computer readable storage device, the computer program product comprising instructions for causing a processor to: display a sequence of words on a user interface rendered on a display device; apply in response to a user-based selection of a first portion of words in the sequence of words, a first indicium to the user-selected first portion of words in the sequence of words; associate a first character having an associated first voice model to the first portion of words in the sequence of words; and associate a second character having an associated second, different voice model to a second, different portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words. 27. The computer program product of claim 26 , wherein the computer program product further comprises instructions for causing the processor to: generate an audible output corresponding to the words in the sequence of words where the words in the first portion of words are narrated using the first voice model for the first character and the words in the second portion of words are narrated using the second voice model for the second character.

10. An apparatus for recognizing gesture, comprising: one or more gesture capturing sensors; a raw data capture block configured to generate raw data of a gesture from the gesture capturing sensors; a gesture elements categorizing block configured to categorize the raw data into a plurality of gesture elements and to recategorize the raw data into different gesture elements based on a contextual dependency between the plurality of gesture elements, wherein each gesture element corresponds to a predetermined movement identified from the raw data; a contextual dependency determining block configured to determine a contextual dependency between the plurality of gesture elements, wherein the contextual dependency comprises probabilities of the plurality of gesture elements appearing next to each other in a temporal order or sequence; and a gesture recognition block configured to recognize the gesture based on the determined gesture elements.

10. An apparatus for recognizing gesture, comprising: one or more gesture capturing sensors; a raw data capture block configured to generate raw data of a gesture from the gesture capturing sensors; a gesture elements categorizing block configured to categorize the raw data into a plurality of gesture elements and to recategorize the raw data into different gesture elements based on a contextual dependency between the plurality of gesture elements, wherein each gesture element corresponds to a predetermined movement identified from the raw data; a contextual dependency determining block configured to determine a contextual dependency between the plurality of gesture elements, wherein the contextual dependency comprises probabilities of the plurality of gesture elements appearing next to each other in a temporal order or sequence; and a gesture recognition block configured to recognize the gesture based on the determined gesture elements. 12. The apparatus of claim 10 , wherein the raw data obtained from the gesture capturing sensors, has not been subjected to processing or manipulation related to gesture recognition.

9. The method of claim 8 , wherein the section heading is a first section heading, and wherein the method further comprises: providing to the user a plurality of alternative section headings for the first text section.

9. The method of claim 8 , wherein the section heading is a first section heading, and wherein the method further comprises: providing to the user a plurality of alternative section headings for the first text section. 10. The method of claim 9 , wherein the structured text is a first structured text, and wherein the method further comprises: receiving user input indicative of the user selecting an alternative section heading from the plurality of alternative section headings to replace the first section heading; and providing to the user a second structured text in which the first section heading has been replaced by the alternative section heading selected by the user.

8. The method according to claim 1 , wherein the attributes are parameters of a product categorized by respective attribute groups.

8. The method according to claim 1 , wherein the attributes are parameters of a product categorized by respective attribute groups. 9. The method according to claim 8 , wherein the user specifies a value for a respective parameter of the product in at least some of the input fields.

23. A computer-implemented method of querying a computer database that comprises a plurality of electronic data records containing strings of terms in a natural human language format, to retrieve a final result set comprising a selection of data records that satisfy a search query, comprising the computer-implemented steps of: receiving input from a user corresponding to a creation of at least one initial inclusion rule, the initial inclusion rule comprising one or more descriptive search terms that are required to occur in each record in the final result set; receiving input from a user corresponding to a creation of at least one initial exclusion rule, the initial exclusion rule comprising one or more descriptive search terms that are required to not occur in the final result set; storing the at least one initial inclusion rule and the at least one initial exclusion rule as an initial descriptive taxonomy; a computer querying the computer database utilizing the initial descriptive taxonomy as a search query to generate an initial inclusion result set and an initial exclusion result set; displaying the initial inclusion result set and the initial exclusion result set to the user, for inspection by the user to assess whether the initial inclusion result set and the initial exclusion result set comprise records desired by the user, the display of the initial inclusion result set including an exclusion flag identifying data records that also appear in the initial exclusion result set; receiving input from the user corresponding to a provision of additional descriptive search terms for addition to the descriptive search terms in the initial inclusion rule such that further data records containing such additional descriptive search terms will be included in the final result set; storing the additional descriptive search terms for the initial inclusion rule as an updated inclusion rule; receiving input from the user removing the exclusion flag for a particular data record that the user has determined should occur in the final result set notwithstanding its occurrence in the initial exclusion result set; storing information relating to a data record for which an exclusion flag has been removed as an updated exclusion rule, such that the data record will henceforth occur in the final result set; storing the updated inclusion rule and the updated exclusion rule as an updated descriptive taxonomy; and a computer querying the computer database utilizing the updated descriptive taxonomy as a search query to generate the final result set, whereby data records that satisfy the updated inclusion rule are included in the data records in the final result set and data records for which the exclusion flag has been removed also are included in the final result set.

23. A computer-implemented method of querying a computer database that comprises a plurality of electronic data records containing strings of terms in a natural human language format, to retrieve a final result set comprising a selection of data records that satisfy a search query, comprising the computer-implemented steps of: receiving input from a user corresponding to a creation of at least one initial inclusion rule, the initial inclusion rule comprising one or more descriptive search terms that are required to occur in each record in the final result set; receiving input from a user corresponding to a creation of at least one initial exclusion rule, the initial exclusion rule comprising one or more descriptive search terms that are required to not occur in the final result set; storing the at least one initial inclusion rule and the at least one initial exclusion rule as an initial descriptive taxonomy; a computer querying the computer database utilizing the initial descriptive taxonomy as a search query to generate an initial inclusion result set and an initial exclusion result set; displaying the initial inclusion result set and the initial exclusion result set to the user, for inspection by the user to assess whether the initial inclusion result set and the initial exclusion result set comprise records desired by the user, the display of the initial inclusion result set including an exclusion flag identifying data records that also appear in the initial exclusion result set; receiving input from the user corresponding to a provision of additional descriptive search terms for addition to the descriptive search terms in the initial inclusion rule such that further data records containing such additional descriptive search terms will be included in the final result set; storing the additional descriptive search terms for the initial inclusion rule as an updated inclusion rule; receiving input from the user removing the exclusion flag for a particular data record that the user has determined should occur in the final result set notwithstanding its occurrence in the initial exclusion result set; storing information relating to a data record for which an exclusion flag has been removed as an updated exclusion rule, such that the data record will henceforth occur in the final result set; storing the updated inclusion rule and the updated exclusion rule as an updated descriptive taxonomy; and a computer querying the computer database utilizing the updated descriptive taxonomy as a search query to generate the final result set, whereby data records that satisfy the updated inclusion rule are included in the data records in the final result set and data records for which the exclusion flag has been removed also are included in the final result set. 26. The computer-implemented method of claim 23 , wherein the plurality of electronic data records comprise structured electronic medical records.

8. The method of claim 1 , wherein the first electronic message further satisfies a second set of content-based clustering rules associated with a second message cluster; and the method further comprises: assigning the first electronic message to the second message cluster; and formatting for display, in an electronic message folder of the messaging application, the electronic messages in the second message cluster as a second cluster graphic.

8. The method of claim 1 , wherein the first electronic message further satisfies a second set of content-based clustering rules associated with a second message cluster; and the method further comprises: assigning the first electronic message to the second message cluster; and formatting for display, in an electronic message folder of the messaging application, the electronic messages in the second message cluster as a second cluster graphic. 10. The method of claim 8 , wherein (i) the first set of content-based clustering rules comprises system-defined clustering rules; and (ii) the second set of content-based clustering rules comprises user-defined clustering rules.

1. A non-transitory computer-readable recording medium that, when read and executed by a computer causes the same to perform a logical structure model creation assistance method for assisting in the creation of a logical structure model, which stores, from an image in which character strings associated respectively with a plurality of logical elements constituting a logical structure are described, the logical elements, character strings associated with the logical elements, and the logical structure, the method comprising: firstly extracting character strings in an input image and the logical structure among the character strings in the input image; selecting one among the plurality of logical elements according to degrees of similarity between the extracted character strings in the input image and the character strings associated respectively with the plurality of logical elements stored in the logical structure model; secondly extracting a character string associated with the selected logical element and a character string in the input image associated with the logical element based on the logical structure among the extracted character strings in the input image; and displaying the extracted character string as an update candidate for the character string associated with the selected logical element.

1. A non-transitory computer-readable recording medium that, when read and executed by a computer causes the same to perform a logical structure model creation assistance method for assisting in the creation of a logical structure model, which stores, from an image in which character strings associated respectively with a plurality of logical elements constituting a logical structure are described, the logical elements, character strings associated with the logical elements, and the logical structure, the method comprising: firstly extracting character strings in an input image and the logical structure among the character strings in the input image; selecting one among the plurality of logical elements according to degrees of similarity between the extracted character strings in the input image and the character strings associated respectively with the plurality of logical elements stored in the logical structure model; secondly extracting a character string associated with the selected logical element and a character string in the input image associated with the logical element based on the logical structure among the extracted character strings in the input image; and displaying the extracted character string as an update candidate for the character string associated with the selected logical element. 8. The non-transitory computer-readable recording medium according to claim 1 , further comprising: displaying, when no logical element has been selected among the plurality of logical elements, based on the estimated degree of similarity between the logical structure stored in the logical structure model and the logical structure among the extracted character strings in the input image a logical element to be associated with a character string in the input image and added to the logical structure model, as an additional logical element candidate together with an addition position.

8. The method of claim 1 , wherein a third data storage is configured to store local work processes comprising a first set of business processes generated by an actor in variance from a second set of business processes defined by the business process generator.

8. The method of claim 1 , wherein a third data storage is configured to store local work processes comprising a first set of business processes generated by an actor in variance from a second set of business processes defined by the business process generator. 9. The method of claim 8 , wherein the first data storage, second data storage and third data storage are allocated areas of a common data storage device.