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12. The computer storage medium of claim 11 , wherein the operation for causing the image to be rendered includes specifying a content that is to be displayed in response to detecting the selection input.

12. The computer storage medium of claim 11 , wherein the operation for causing the image to be rendered includes specifying a content that is to be displayed in response to detecting the selection input. 13. The computer storage medium of claim 12 , wherein the content includes information that is based on the metadata.

90. A system for selectable input based upon motion of a pointing device in relation to a region having a plurality of selectable characters, comprising: means for tracking the motion of the pointing device in relation to the region, wherein the tracked motion defines a device path comprising at least two selected positions; means for determining which of the selected positions along the device path correspond to at least one of the selectable characters; and logic for determining a characteristic motion of the pointing device that corresponds to at least one of the selected positions along the device path corresponding to at least one of the selectable characters.

90. A system for selectable input based upon motion of a pointing device in relation to a region having a plurality of selectable characters, comprising: means for tracking the motion of the pointing device in relation to the region, wherein the tracked motion defines a device path comprising at least two selected positions; means for determining which of the selected positions along the device path correspond to at least one of the selectable characters; and logic for determining a characteristic motion of the pointing device that corresponds to at least one of the selected positions along the device path corresponding to at least one of the selectable characters. 95. The system of claim 90 , wherein the region comprises a two-dimensional area.

55. A computer-readable memory device storing instructions executable by at least one processor, the computer-readable memory device comprising: one or more instructions to receive a search query; one or more instructions to provide a list of search results in response to the search query; one or more instructions to receive selection of one of the search results in the list of search results; one or more instructions to identify links in a document corresponding to the selected search result; one or more instructions to determine a score for one of the links based on a degree of match between the search query and a content of a linked document pointed to by the one of the links; one or more instructions to modify the document based on the determined score for the one of the links; and one or more instructions to provide the modified document.

55. A computer-readable memory device storing instructions executable by at least one processor, the computer-readable memory device comprising: one or more instructions to receive a search query; one or more instructions to provide a list of search results in response to the search query; one or more instructions to receive selection of one of the search results in the list of search results; one or more instructions to identify links in a document corresponding to the selected search result; one or more instructions to determine a score for one of the links based on a degree of match between the search query and a content of a linked document pointed to by the one of the links; one or more instructions to modify the document based on the determined score for the one of the links; and one or more instructions to provide the modified document. 58. The computer-readable memory device of claim 55 , wherein the one or more instructions to modify the document include: one or more instructions to change at least one visual characteristic of the one of the links within the document based on the determined score.

1. An information storage system which is connectable to an input interface means and an output interface means, the information storage system comprising a computer, the computer having a memory, the memory of the computer having a plurality of nodes stored therein, each node having a unique identifier within the memory, the memory of the computer including means defining pointers between pairs of said nodes, the pointers comprising only identifiers of other nodes, the pointers having been assigned by the input interface means in response to transmission of input data to the input interface means by a user, wherein each node contains no application data elements other than pointers, wherein information to be stored is stored only as a pattern of said pointers, and wherein said stored pattern is convertible by the output interface means into data recognizable by the user.

1. An information storage system which is connectable to an input interface means and an output interface means, the information storage system comprising a computer, the computer having a memory, the memory of the computer having a plurality of nodes stored therein, each node having a unique identifier within the memory, the memory of the computer including means defining pointers between pairs of said nodes, the pointers comprising only identifiers of other nodes, the pointers having been assigned by the input interface means in response to transmission of input data to the input interface means by a user, wherein each node contains no application data elements other than pointers, wherein information to be stored is stored only as a pattern of said pointers, and wherein said stored pattern is convertible by the output interface means into data recognizable by the user. 2. The system of claim 1, wherein the information being stored includes both data and procedure information, and wherein data and procedure are arranged in a structure called a Context, wherein every Context contains both data and procedure, and wherein all procedure information is stored in the same manner as any other information in the system.

12. A computer program product for communicating electronically with emotion preservation, said computer program product comprising: a computer usable storage medium having computer useable program code embodied therewith, the computer usable program code comprising: computer usable program code to receive a first language communication comprising text marked up with emotion metadata; computer usable program code to translate the emotion metadata into second language emotion metadata based on a user profile; computer usable program code to translate the text to second language text; and computer usable program code to associate the second language text with the second language emotion metadata.

12. A computer program product for communicating electronically with emotion preservation, said computer program product comprising: a computer usable storage medium having computer useable program code embodied therewith, the computer usable program code comprising: computer usable program code to receive a first language communication comprising text marked up with emotion metadata; computer usable program code to translate the emotion metadata into second language emotion metadata based on a user profile; computer usable program code to translate the text to second language text; and computer usable program code to associate the second language text with the second language emotion metadata. 13. The computer program product of claim 12 , wherein the user profile is a profile of a person originating the first language communication.

18. A method for estimating a propensity to pay an owed amount to a revenue agency, the method comprising: assigning to each score band of a plurality of score bands of a collections model a different scoring expression specially determined for the score band, wherein each said score band corresponds to a different credit score range; obtaining a first credit score for a first debtor; selecting, based on the first credit score, a first score band from the plurality of score bands; and in response to the selecting, applying the scoring expression assigned to the first score band to first raw credit data and first tax form data to determine a first collection score for the first debtor, wherein said first raw credit data and first tax form data are operable to be stored in computer memory.

18. A method for estimating a propensity to pay an owed amount to a revenue agency, the method comprising: assigning to each score band of a plurality of score bands of a collections model a different scoring expression specially determined for the score band, wherein each said score band corresponds to a different credit score range; obtaining a first credit score for a first debtor; selecting, based on the first credit score, a first score band from the plurality of score bands; and in response to the selecting, applying the scoring expression assigned to the first score band to first raw credit data and first tax form data to determine a first collection score for the first debtor, wherein said first raw credit data and first tax form data are operable to be stored in computer memory. 31. The method of claim 18 , wherein the obtaining comprises: determining the first credit score from the first raw credit data and the first tax form data.

2. A computer-implemented method of performing patent analysis on data derived from a web-based search engine pursuant to a search query specified by a user, the method comprising: causing display, in a first element of a patent analytics web page, in a client digital computing device, of search results content served by the search engine, such content including a list of patents; receiving, by the client digital computing device, a patent analytics web page, including script, from a separate server; in a first computer process on the digital computing device, analyzing data associated with the search results content according to criteria, specified by the user when specifying the search query, to produce analysis results that apply to all patents on the list, including running the script, the script being configured to perform the analysis; and in a second computer process on the digital computing device, causing display of the analysis results.

2. A computer-implemented method of performing patent analysis on data derived from a web-based search engine pursuant to a search query specified by a user, the method comprising: causing display, in a first element of a patent analytics web page, in a client digital computing device, of search results content served by the search engine, such content including a list of patents; receiving, by the client digital computing device, a patent analytics web page, including script, from a separate server; in a first computer process on the digital computing device, analyzing data associated with the search results content according to criteria, specified by the user when specifying the search query, to produce analysis results that apply to all patents on the list, including running the script, the script being configured to perform the analysis; and in a second computer process on the digital computing device, causing display of the analysis results. 6. A method according to claim 2 , wherein causing display of the analysis results includes causing display of the analysis results in a second element of the patent analytics page.

1. A computer-implemented predictive modeling method comprising: obtaining conversation metric data and conversation assessment data for respective conversations included in a plurality of conversations, wherein the metric data for a respective conversation include data indicative of one or more values of one or more metrics for evaluating conversation quality, wherein the one or more metric values are determined based, at least in part, on communications of two or more participants in the conversation, wherein the metrics include a proportionality metric and/or a matching metric, wherein a value of the proportionality metric depends on proportions of communication contributed to the conversation by the two or more participants, wherein a value of the matching metric depends on an extent to which a communication rate of a first of the participants matches a communication rate of a second of the participants, and wherein the assessment data for the conversation include data indicative of one or more assessments of the conversation; and training one or more predictive models to provide one or more assessments of an ongoing conversation based, at least in part, on conversation metric data for the ongoing conversation, wherein training a first of the one or more predictive models comprises fitting the first predictive model to training data including the conversation metric data for the plurality of conversations and at least a portion of the conversation assessment data for the plurality of conversations.

1. A computer-implemented predictive modeling method comprising: obtaining conversation metric data and conversation assessment data for respective conversations included in a plurality of conversations, wherein the metric data for a respective conversation include data indicative of one or more values of one or more metrics for evaluating conversation quality, wherein the one or more metric values are determined based, at least in part, on communications of two or more participants in the conversation, wherein the metrics include a proportionality metric and/or a matching metric, wherein a value of the proportionality metric depends on proportions of communication contributed to the conversation by the two or more participants, wherein a value of the matching metric depends on an extent to which a communication rate of a first of the participants matches a communication rate of a second of the participants, and wherein the assessment data for the conversation include data indicative of one or more assessments of the conversation; and training one or more predictive models to provide one or more assessments of an ongoing conversation based, at least in part, on conversation metric data for the ongoing conversation, wherein training a first of the one or more predictive models comprises fitting the first predictive model to training data including the conversation metric data for the plurality of conversations and at least a portion of the conversation assessment data for the plurality of conversations. 10. The method of claim 1 , wherein the one or more metrics for evaluating conversation quality comprise one or more first metrics for evaluating conversation quality, wherein the metric data for the conversation further include data indicative of one or more values of one or more second metrics for evaluating conversation quality, and wherein the one or more second metric values are determined based, at least in part, on communication of the first participant in the conversation.

9. A method of enabling input into an electronic device having a plurality of input members, a display, and a memory having a number of language objects stored therein, at least some of the language objects each comprising a number of characters, at least some of the input members each having a number of the characters assigned thereto, the method comprising: detecting an ambiguous text input; generating a number of compound language solutions by identifying a language object that corresponds with an initial portion of the ambiguous text input and identifying another language object that corresponds with another portion of the ambiguous text input; for at least a first compound language solution, generating a junction object comprising a terminal character of the language object and an initial character of the another language object, and making a determination that no language object corresponds with the junction object; and employing the determination in outputting with the display a representation of each of at least some of the compound language solutions.

9. A method of enabling input into an electronic device having a plurality of input members, a display, and a memory having a number of language objects stored therein, at least some of the language objects each comprising a number of characters, at least some of the input members each having a number of the characters assigned thereto, the method comprising: detecting an ambiguous text input; generating a number of compound language solutions by identifying a language object that corresponds with an initial portion of the ambiguous text input and identifying another language object that corresponds with another portion of the ambiguous text input; for at least a first compound language solution, generating a junction object comprising a terminal character of the language object and an initial character of the another language object, and making a determination that no language object corresponds with the junction object; and employing the determination in outputting with the display a representation of each of at least some of the compound language solutions. 12. The method of claim 9 , further comprising: determining that an intermediate portion of the ambiguous text input following the initial portion is consistent with a suffix object in the memory; employing as the another portion of the ambiguous text input the portion of the ambiguous text input following the intermediate portion; and generating as the junction object an object comprising the terminal character of the language object, the suffix object, and the initial character of the another language object.

1. A method of determining, with the use of a computer, whether a subject has an increased risk for acquiring a disease, said method comprising the steps of: selecting a plurality of diseases from a database of diseases accessible by the computer; interactively subjecting the subject to a plurality of questions relevant for the diseases using the computer; acquiring respective answers for the subject to the said plurality of questions, the computer being used to store the respective answers; and computing, using the computer, a risk factor for the subject for the diseases using said respective answers and an accessible further database comprising a plurality of respective deterministically established partial risk factors for the diseases, said partial risk factors being assigned to the respective answers by the computer.

1. A method of determining, with the use of a computer, whether a subject has an increased risk for acquiring a disease, said method comprising the steps of: selecting a plurality of diseases from a database of diseases accessible by the computer; interactively subjecting the subject to a plurality of questions relevant for the diseases using the computer; acquiring respective answers for the subject to the said plurality of questions, the computer being used to store the respective answers; and computing, using the computer, a risk factor for the subject for the diseases using said respective answers and an accessible further database comprising a plurality of respective deterministically established partial risk factors for the diseases, said partial risk factors being assigned to the respective answers by the computer. 7. The method according to claim 1 , further comprising the step of providing, by the computer, the subject with disease-related information for at least one selected disease.

5. A method, according to claim 1 , further comprising: discarding at least one of the one or more groups within the filtered set of event data based on the auto-filing rules.

5. A method, according to claim 1 , further comprising: discarding at least one of the one or more groups within the filtered set of event data based on the auto-filing rules. 7. A method, according to claim 5 , wherein discarding is performed in response to more than a predetermined amount of event data being stored in a portion of the memory of the mobile device that is used to store the filtered set of event data.

7. A computer-implemented method for facilitating a search, comprising: under control of one or more computer systems configured with executable instructions, associating the search with a category in a category hierarchy; searching the category to find items matching one or more search terms; identifying at least one further category at a level below the category in the category hierarchy based at least in part on the one or more search terms and a map for surfacing refinements, the map depicting a plurality of associations between search terms and the at least one further category; receiving a selection of at least one refinement from a set of refinements linked to said at least one further category; maintaining a log of a number of times a refinement of the set of refinements is selected during searches employing the one or more search terms in one or more time periods; determining a possibly relevant set of categories of the category hierarchy below a distinguished category based at least in part on the log; increasing an associative confidence between at least one of the one or more search terms and a subset of the set of refinements linked to the possibly relevant set of categories based at least in part on the log; determining the subset of the set of refinements linked to the possibly relevant set of categories when the associative confidence at least meets a first sufficiency threshold; providing the items and said subset of the set of refinements for presentation; and constraining subsequent search results to a particular distinguished category, based at least on the one or more search terms, when the associative confidence meets at least a second sufficiency threshold.

7. A computer-implemented method for facilitating a search, comprising: under control of one or more computer systems configured with executable instructions, associating the search with a category in a category hierarchy; searching the category to find items matching one or more search terms; identifying at least one further category at a level below the category in the category hierarchy based at least in part on the one or more search terms and a map for surfacing refinements, the map depicting a plurality of associations between search terms and the at least one further category; receiving a selection of at least one refinement from a set of refinements linked to said at least one further category; maintaining a log of a number of times a refinement of the set of refinements is selected during searches employing the one or more search terms in one or more time periods; determining a possibly relevant set of categories of the category hierarchy below a distinguished category based at least in part on the log; increasing an associative confidence between at least one of the one or more search terms and a subset of the set of refinements linked to the possibly relevant set of categories based at least in part on the log; determining the subset of the set of refinements linked to the possibly relevant set of categories when the associative confidence at least meets a first sufficiency threshold; providing the items and said subset of the set of refinements for presentation; and constraining subsequent search results to a particular distinguished category, based at least on the one or more search terms, when the associative confidence meets at least a second sufficiency threshold. 8. A computer-implemented method according to claim 7 , wherein: the category hierarchy has a root category; and the category associated with the search is the root category of the category hierarchy.

7. A method for optimizing the description of contents in a layout document, the method comprising: parsing the content of an original layout document to obtain text graphic unit data; identifying text properties of each character of the text graphic unit data, and classifying characters of the text graphic unit data according to the text properties, to save characters with the same text properties to the same text node along with the same text properties; for characters saved in each text node, saving characters on the same line or column, coordinates of an initial character on the same line or column, average character spacing of the same line or column to a text content node to obtain optimized contents in the layout document, wherein the text content node is a text content node under the text node and corresponding to the same line or column.

7. A method for optimizing the description of contents in a layout document, the method comprising: parsing the content of an original layout document to obtain text graphic unit data; identifying text properties of each character of the text graphic unit data, and classifying characters of the text graphic unit data according to the text properties, to save characters with the same text properties to the same text node along with the same text properties; for characters saved in each text node, saving characters on the same line or column, coordinates of an initial character on the same line or column, average character spacing of the same line or column to a text content node to obtain optimized contents in the layout document, wherein the text content node is a text content node under the text node and corresponding to the same line or column. 10. The method of claim 7 , characterized in that wherein the step of creating the text content node comprises: buffering characters belonging to the same line or column for characters of each text node, calculating an average character spacing and actual character spacing among characters on the same line or column; adding characters successively determined and having a difference between the actual character spacing and the average character spacing that is less than or equal to a predetermined value into the text content node, and saving the average character spacing and coordinates of the first character added to the text content node to the text content node; adding characters having a difference between the actual character spacing and the average character spacing that is larger than the predetermined value to a newly created text content node corresponding to the same line or column.

27. A non-transitory computer readable memory device, comprising instructions that are executable by a processor of a computer system, wherein as the instructions executed by the processor, the computer system: receives, from a computing device, via the network interface and the network, a first query of at least one social network media data source indicating search data and a first geographical search region, wherein the at least one social network media data source stores user-provided data from a plurality of users provided via a plurality of computing devices associated with at least the first geographical search region; determines the first geographical search region covers a first geographical area and at least a first portion of a geographic context region intersecting the first geographical search region, wherein a first location within the geographic context region is not within the first geographical search region and wherein first social media results of the at least one social network media data source in response to the first query will not include one or more second social media results associated with one or more second locations within both the first portion of the geographic context region and the first geographical search region, at least because the one or more second locations are associated with the geographic context region and the first location is not within the first geographical search region; in response to determining the first geographical search region covers the first geographical area and the at least a first portion of the geographic context region intersecting the first geographical search region, generates at least a second query of the at least one social network media data source indicating the search data and a second geographical search region covering a second geographical area including at least a second portion of the geographic context region including the first location and the one or more second locations within the geographic context region; provides, via the network interface and the network, the at least the second query to the at least one social network media data source; receives, from the at least one social network media data source via the network interface and the network, at least one result based on the at least the second query and based on the user-provided data stored via the at least one social network media data source, wherein the at least one result includes the one or more second social media results associated with the one or more second locations within the geographic context region and the first geographical search region; and provides the at least one result to the computing device.

27. A non-transitory computer readable memory device, comprising instructions that are executable by a processor of a computer system, wherein as the instructions executed by the processor, the computer system: receives, from a computing device, via the network interface and the network, a first query of at least one social network media data source indicating search data and a first geographical search region, wherein the at least one social network media data source stores user-provided data from a plurality of users provided via a plurality of computing devices associated with at least the first geographical search region; determines the first geographical search region covers a first geographical area and at least a first portion of a geographic context region intersecting the first geographical search region, wherein a first location within the geographic context region is not within the first geographical search region and wherein first social media results of the at least one social network media data source in response to the first query will not include one or more second social media results associated with one or more second locations within both the first portion of the geographic context region and the first geographical search region, at least because the one or more second locations are associated with the geographic context region and the first location is not within the first geographical search region; in response to determining the first geographical search region covers the first geographical area and the at least a first portion of the geographic context region intersecting the first geographical search region, generates at least a second query of the at least one social network media data source indicating the search data and a second geographical search region covering a second geographical area including at least a second portion of the geographic context region including the first location and the one or more second locations within the geographic context region; provides, via the network interface and the network, the at least the second query to the at least one social network media data source; receives, from the at least one social network media data source via the network interface and the network, at least one result based on the at least the second query and based on the user-provided data stored via the at least one social network media data source, wherein the at least one result includes the one or more second social media results associated with the one or more second locations within the geographic context region and the first geographical search region; and provides the at least one result to the computing device. 44. The non-transitory computer readable memory device of claim 27 , wherein the user-provided data stored via the at least one social network media data source includes user-provided data stored via at least one of FACEBOOK social network media data source, TWITTER social network media data source, YOUTUBE social network media data source, WEIBO social network media data source, a blog, a wiki, FOURSQUARE social network media data source, INSTAGRAM social network media data source, FLICKR social network media data source, VIMEO social network media data source, and YELP social network media data source.

8. The system according to claim 7 , wherein the first data are grouped according to a first criterion and wherein the changing means are adapted for changing said first criterion to said at least one second criterion for each of said first data upon activation by said triggering means.

8. The system according to claim 7 , wherein the first data are grouped according to a first criterion and wherein the changing means are adapted for changing said first criterion to said at least one second criterion for each of said first data upon activation by said triggering means. 10. The system according to claim 8 , wherein the changing means for changing the first criterion for each of said first data independently from each other.

5. The method of claim 1 , where processing the query in the first manner includes: retrieving one or more documents relating to the query, and scoring the one or more documents based on a first set of criteria, where the scoring includes assigning first weights to domain names associated with the one or more documents.

5. The method of claim 1 , where processing the query in the first manner includes: retrieving one or more documents relating to the query, and scoring the one or more documents based on a first set of criteria, where the scoring includes assigning first weights to domain names associated with the one or more documents. 6. The method of claim 5 , where processing the query in the second manner includes: retrieving the one or more documents relating to the query, and scoring the one or more documents based on a second set of criteria, where the second set of criteria is different than the first set of criteria, and where the scoring based on the second set of criteria includes assigning second weights to the domain names associated with the one or more documents.

1. A method, comprising: receiving, by a computing device, text data, said text data associated with audio/video data, wherein said audio/video data is generated during a related performance, wherein said related performance is a live performance attended by a user of said computing device, and wherein said audio/video data and said text data are discrete data; receiving, by a translation server of said computing device, a portion of video from said audio/video data during said performance; comparing, by said translation server of said computing device, said portion of video to a plurality of pre-stored reference video images on a synchronization server of said computing device; determining, by said translation server of said computing device based on results of said comparing, a match between a first reference video image of said plurality of pre-stored reference video images and a first image of said portion of video; synchronizing, said text data to correspond with said audio/video data during said performance, wherein said synchronizing comprises associating said first reference video image to a corresponding portion of said text data and aligning said corresponding portion of said text data with said first image; and displaying for said user, by a first discrete device and a second discrete device of said computing device, said synchronized text data during said performance, wherein said first discrete device consists of video glasses, wherein said second discrete device consists of a personal digital assistant, and wherein said audio/video data generated during said performance is not displayed by said computing device.

1. A method, comprising: receiving, by a computing device, text data, said text data associated with audio/video data, wherein said audio/video data is generated during a related performance, wherein said related performance is a live performance attended by a user of said computing device, and wherein said audio/video data and said text data are discrete data; receiving, by a translation server of said computing device, a portion of video from said audio/video data during said performance; comparing, by said translation server of said computing device, said portion of video to a plurality of pre-stored reference video images on a synchronization server of said computing device; determining, by said translation server of said computing device based on results of said comparing, a match between a first reference video image of said plurality of pre-stored reference video images and a first image of said portion of video; synchronizing, said text data to correspond with said audio/video data during said performance, wherein said synchronizing comprises associating said first reference video image to a corresponding portion of said text data and aligning said corresponding portion of said text data with said first image; and displaying for said user, by a first discrete device and a second discrete device of said computing device, said synchronized text data during said performance, wherein said first discrete device consists of video glasses, wherein said second discrete device consists of a personal digital assistant, and wherein said audio/video data generated during said performance is not displayed by said computing device. 8. The method of claim 1 , wherein said performance is selected from the group consisting of a television show, a movie, and a live performance.

22. The method as described in claim 16 , wherein the introducing comprises introducing one, two or three patent indices; and wherein the bounded interval for each said patent index for each patent document in the patent portfolio is the same.

22. The method as described in claim 16 , wherein the introducing comprises introducing one, two or three patent indices; and wherein the bounded interval for each said patent index for each patent document in the patent portfolio is the same. 23. The method as described in claim 22 , wherein the visualizing the results comprises displaying the quality of each patent document as a color point in a system of coordinates with axes corresponding to the patent indices, coordinates of the color point being equal to the values of patent indices characterizing said each patent document, and a color of the color point being in correspondence with the value of the respective Patent Quality index for said each patent document.

1. A mapping system implemented on a computer processor and configured to provide at least one of route guidance and reassurance from an origin to a destination, comprising: a database implemented on a one or more computer storage devices containing: landmark information including for each landmark: a text description; a location; a category of landmark; and a route guidance and reassurance ratings comprising at least one of: multiple user defined rating of at least one of: accuracy; and usefulness; single user defined rating of at least one of: accuracy; and usefulness; fee based ratings; and a road-based routing information including for a plurality of road segments: a text description of each road segment and attribution; and a location of each road segment; and the computer processor controlling a route guidance generator to accept a user input with respect to how to implement route guidance and reassurance based on one or more of the route guidance and reassurance ratings and a preference for landmark based route guidance and reassurance or road-based route guidance and reassurance.

1. A mapping system implemented on a computer processor and configured to provide at least one of route guidance and reassurance from an origin to a destination, comprising: a database implemented on a one or more computer storage devices containing: landmark information including for each landmark: a text description; a location; a category of landmark; and a route guidance and reassurance ratings comprising at least one of: multiple user defined rating of at least one of: accuracy; and usefulness; single user defined rating of at least one of: accuracy; and usefulness; fee based ratings; and a road-based routing information including for a plurality of road segments: a text description of each road segment and attribution; and a location of each road segment; and the computer processor controlling a route guidance generator to accept a user input with respect to how to implement route guidance and reassurance based on one or more of the route guidance and reassurance ratings and a preference for landmark based route guidance and reassurance or road-based route guidance and reassurance. 3. The mapping system of claim 1 wherein the route guidance and reassurance rating values associated with landmarks is in part based on the visibility of each landmark from locations along a calculated route.

20. A method of identifying content items ordered based on microgenres of desired content items, the method comprising: receiving, by a client device of a user, through the user interfacing with a video consumption application that is executed at the client device, an input identifying a desired content item of a plurality of content items, wherein each content item of the plurality of content items is associated with: a respective genre that broadly characterizes the respective content item, a respective microgenre that, with respect to the respective genre, narrowly characterizes the respective content item, and a respective base relevance value that indicates how relevant the respective content item is to the user; transmitting, to a server, the input identifying the desired content item; causing the server to: cause to be stored, at a database, an entry associated with a microgenre of the desired content item in a data structure associated with a profile of the user, identify, based on the profile of the user, a subset of the plurality of content items, wherein the respective microgenre associated with each content item of the subset comprises the microgenre of the desired content item, increase the respective relevance value associated with each content item of the subset, and rank each content item of the plurality of content items in an order reflecting the respective relevance value associated with each content item of the plurality of content items; receiving, from the server, a communication comprising an indication of the order; and generating a display, using the video consumption application, based on the order.

20. A method of identifying content items ordered based on microgenres of desired content items, the method comprising: receiving, by a client device of a user, through the user interfacing with a video consumption application that is executed at the client device, an input identifying a desired content item of a plurality of content items, wherein each content item of the plurality of content items is associated with: a respective genre that broadly characterizes the respective content item, a respective microgenre that, with respect to the respective genre, narrowly characterizes the respective content item, and a respective base relevance value that indicates how relevant the respective content item is to the user; transmitting, to a server, the input identifying the desired content item; causing the server to: cause to be stored, at a database, an entry associated with a microgenre of the desired content item in a data structure associated with a profile of the user, identify, based on the profile of the user, a subset of the plurality of content items, wherein the respective microgenre associated with each content item of the subset comprises the microgenre of the desired content item, increase the respective relevance value associated with each content item of the subset, and rank each content item of the plurality of content items in an order reflecting the respective relevance value associated with each content item of the plurality of content items; receiving, from the server, a communication comprising an indication of the order; and generating a display, using the video consumption application, based on the order. 22. The method of claim 20 , wherein the input comprises at least one of a request to access the desired content item, a request to record the desired content item, and a duration of accessing the desired content item.

16. A non-transitory computer-readable medium storing a set of instructions that, when executed by one or more processors, cause the one or more processors to perform a method of linking electronic documents, the method comprising: receiving annotations associated with source electronic documents wherein at least some of the annotations include respective selections of text from the source electronic documents and text inputs received from users; generating snippets from the received annotations; determining content of selections of text of the annotations of the respective snippets; aggregating the generated snippets into clusters based at least in part on the determined content; generating an electronic document based on the clusters; generating links between the snippets and their respective source documents; and embedding the generated links in the generated electronic document.

16. A non-transitory computer-readable medium storing a set of instructions that, when executed by one or more processors, cause the one or more processors to perform a method of linking electronic documents, the method comprising: receiving annotations associated with source electronic documents wherein at least some of the annotations include respective selections of text from the source electronic documents and text inputs received from users; generating snippets from the received annotations; determining content of selections of text of the annotations of the respective snippets; aggregating the generated snippets into clusters based at least in part on the determined content; generating an electronic document based on the clusters; generating links between the snippets and their respective source documents; and embedding the generated links in the generated electronic document. 17. The computer-readable medium of claim 16 , wherein at least some of the annotations include text input received from a user.

1. A method for invoking an audio hyperlink, the method comprising: providing a user with an option to either enter a first keyword of the user's choice or select a second keyword provided to the user, either the first keyword or the second keyword being configured for use in a speech instruction to invoke the audio hyperlink; storing a plurality of keywords to be included in a grammar, the plurality of keywords comprising either the first keyword or the second keyword; identifying, through an audio anchor element, a predetermined playback time in an audio file pre-designated as having an association with the audio hyperlink; wherein the audio anchor element is a markup language element that identifies the audio file pre-designated as having an association with the audio hyperlink, a Uniform Resource Identifier (‘URI’) identifying a target resource associated with the audio hyperlink, an audio indication of the audio hyperlink, the predetermined playback time in the audio file pre-designated as having an association with the audio hyperlink, and the grammar including the plurality of keywords for speech invocation of a respective plurality of hyperlinks including the audio hyperlink; playing the audio indication of the audio hyperlink at the predetermined playback time; receiving from the user the speech instruction to invoke the audio hyperlink; identifying, through the audio anchor element, the URI associated with the audio hyperlink; and invoking the URI.

1. A method for invoking an audio hyperlink, the method comprising: providing a user with an option to either enter a first keyword of the user's choice or select a second keyword provided to the user, either the first keyword or the second keyword being configured for use in a speech instruction to invoke the audio hyperlink; storing a plurality of keywords to be included in a grammar, the plurality of keywords comprising either the first keyword or the second keyword; identifying, through an audio anchor element, a predetermined playback time in an audio file pre-designated as having an association with the audio hyperlink; wherein the audio anchor element is a markup language element that identifies the audio file pre-designated as having an association with the audio hyperlink, a Uniform Resource Identifier (‘URI’) identifying a target resource associated with the audio hyperlink, an audio indication of the audio hyperlink, the predetermined playback time in the audio file pre-designated as having an association with the audio hyperlink, and the grammar including the plurality of keywords for speech invocation of a respective plurality of hyperlinks including the audio hyperlink; playing the audio indication of the audio hyperlink at the predetermined playback time; receiving from the user the speech instruction to invoke the audio hyperlink; identifying, through the audio anchor element, the URI associated with the audio hyperlink; and invoking the URI. 6. The method of claim 1 wherein identifying a URI associated with the audio hyperlink includes retrieving from the audio anchor element the URI in dependence upon a user speech instruction.

5. The method of claim 1 , further comprising: if it is determined that the electronic device is in the first state, displaying information on the touch-sensitive display in a first display state, wherein the first display state is a regular power mode; and if it is determined that the electronic device is in the second state, entering a second display state different from the first display state, wherein the second display state is a low-power mode.

5. The method of claim 1 , further comprising: if it is determined that the electronic device is in the first state, displaying information on the touch-sensitive display in a first display state, wherein the first display state is a regular power mode; and if it is determined that the electronic device is in the second state, entering a second display state different from the first display state, wherein the second display state is a low-power mode. 7. The method of claim 5 , wherein the electronic device includes an ambient light sensor configured to sense a level of ambient light, and the method further comprises: in response to detecting the first change in the received data and a change in the level of ambient light, changing from the second display state to the first display state.

7. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents.

7. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a search query from a user; obtaining a plurality of search results that satisfy the search query, wherein each search result identifies respective document of a plurality of documents; identifying a respective condition for each document of the plurality of documents, wherein each condition comprises one or more features of the user, the search query, and the document; obtaining a ranking model that produces a score for a particular document given a particular condition for the particular document, the score representing a likelihood that the user will select the particular document when identified by a search result provided in response to the search query, the ranking model being trained on training instances that each identify a first document selected by a particular user when the first document was identified in search results provided to the particular user in response to a particular search query; using the ranking model to compute a respective score for each document of the plurality of documents; and ranking the plurality of search results according to the respective computed score for each document of the plurality of documents. 11. The computer program product claim 7 , wherein each training instance includes data representing a previously computed score for the selected first document.

48. A system adapted to process speech, comprising: an input receiving an array of conceptual components forming words; a processor, adapted to (a) generate a set of candidate parts of speech from each word; (b) permute at least a portion of the candidate parts of speech from each array; (c) produce a plurality of potentially valid syntactic structures from the permuted candidate parts of speech; (d) for a plurality of potentially valid syntactic structures, generate a conceptual representation thereof based on a database of conceptual information comprising parts of speech and a dictionary; (e) determine at least one anomaly criterion for each conceptual representation; and (f) disambiguate between at least two potentially valid syntactic structures based on the corresponding conceptual representations, in dependence on the determined at least one anomaly criterion; and an output responsive to the disambiguation.

48. A system adapted to process speech, comprising: an input receiving an array of conceptual components forming words; a processor, adapted to (a) generate a set of candidate parts of speech from each word; (b) permute at least a portion of the candidate parts of speech from each array; (c) produce a plurality of potentially valid syntactic structures from the permuted candidate parts of speech; (d) for a plurality of potentially valid syntactic structures, generate a conceptual representation thereof based on a database of conceptual information comprising parts of speech and a dictionary; (e) determine at least one anomaly criterion for each conceptual representation; and (f) disambiguate between at least two potentially valid syntactic structures based on the corresponding conceptual representations, in dependence on the determined at least one anomaly criterion; and an output responsive to the disambiguation. 49. The system of claim 48 , wherein processing the speech comprises producing the candidate words from an N-best list of potential words produced by application of the Hidden Markov Model (HMM) technique to a speech sample from the input and also from combinations of two or more consecutive N-best list potential words.

8. The legal analytics platform of claim 7 , further comprising: a normalizing module configured to: identify a variant of a legal entity name in a portion of the legal data; and associate the portion with the legal entity name rather than the variant.

8. The legal analytics platform of claim 7 , further comprising: a normalizing module configured to: identify a variant of a legal entity name in a portion of the legal data; and associate the portion with the legal entity name rather than the variant. 9. The legal analytics platform of claim 8 , wherein the normalizing module is further configured to: receive an authoritative version of the legal entity name that is known to be correct, wherein the authoritative version of the legal entity name is used to identify the variant.

10. The method of claim 9 , wherein: the reference time marks a periodic event; and at least some of the time span is precedent to the reference time that marks the periodic event.

10. The method of claim 9 , wherein: the reference time marks a periodic event; and at least some of the time span is precedent to the reference time that marks the periodic event. 11. The method of claim 10 , wherein: the periodic event is at least one of an annual event, a monthly event, a calendar event, an astronomical event, a religious event, a government event, a holiday, or a season.

13. The system of the claim 12 , wherein for each action, generating a training set of command sentences from the corresponding set of command sentences includes removing each n-gram from each sentence in the corresponding set of command sentences for the action that is also not a first n-gram for the action.

13. The system of the claim 12 , wherein for each action, generating a training set of command sentences from the corresponding set of command sentences includes removing each n-gram from each sentence in the corresponding set of command sentences for the action that is also not a first n-gram for the action. 18. The system of claim 13 , wherein applying the command models to the input sentence of n-grams comprises, for each command model scoring the input sentence based, in part, on first n-grams that have been determined to be semantically relevant to the action and second n-grams that have been identified as being semantically irrelevant for all actions.

21. A computer-implemented method for processing multilingual documents in a document database using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the multi-lingual documents having an initial ranking based upon a user search query provided by a user, the method comprising; operating the processor to perform the following selecting N top ranked multi-lingual documents from the retrieved multilingual documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved multi-lingual documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved multi-lingual documents; generating a re-ranking of the N top ranked multi-lingual documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the multi-lingual documents, and for each multi-lingual document being displayed, also to display its initial ranking.

21. A computer-implemented method for processing multilingual documents in a document database using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the multi-lingual documents having an initial ranking based upon a user search query provided by a user, the method comprising; operating the processor to perform the following selecting N top ranked multi-lingual documents from the retrieved multilingual documents, with N being an integer greater than 1; displaying for the user the initial ranking of the N top ranked retrieved multi-lingual documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents; generating respective relevancies of the user-selected vocabulary words in the N top ranked retrieved multi-lingual documents; generating a re-ranking of the N top ranked multi-lingual documents based on the relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the multi-lingual documents, and for each multi-lingual document being displayed, also to display its initial ranking. 22. A computer-implemented method according to claim 21 wherein the multilingual documents comprise at least one document having multiple languages.

48. A method of fitting graphical objects within a plurality of separate graphical frames in a document, each frame being associated with at least one fitting attribute with a value for fitting one or more of the graphical objects in the frame, comprising: automatically determining an optimized value for the at least one attribute for each of the plurality of frames individually; automatically assessing the optimized values to determine a common scaling factor for the at least one attribute based on a particular one of the optimized values; and scaling the values for the at least one attribute in each of the plurality of separate graphical frames by the common scaling factor to fit one or more of the graphical objects in each of the plurality of separate graphical frames, wherein said scaling modifies at least one graphical object within each of the plurality of separate graphical frames, wherein said scaling is performed without modifying the size of the frames in the plurality of separate graphical frame, wherein at least one of the scaled values is different than another one of the scaled values.

48. A method of fitting graphical objects within a plurality of separate graphical frames in a document, each frame being associated with at least one fitting attribute with a value for fitting one or more of the graphical objects in the frame, comprising: automatically determining an optimized value for the at least one attribute for each of the plurality of frames individually; automatically assessing the optimized values to determine a common scaling factor for the at least one attribute based on a particular one of the optimized values; and scaling the values for the at least one attribute in each of the plurality of separate graphical frames by the common scaling factor to fit one or more of the graphical objects in each of the plurality of separate graphical frames, wherein said scaling modifies at least one graphical object within each of the plurality of separate graphical frames, wherein said scaling is performed without modifying the size of the frames in the plurality of separate graphical frame, wherein at least one of the scaled values is different than another one of the scaled values. 58. The method of claim 48 , wherein scaling the values results in substantially filling only one frame without overset, with other frames being underset.

1. A method for automated avatar mood effects in a virtual world, comprising: detecting occurrence of a mood changing condition relatable to a user's avatar; determining an avatar mood effect from the plurality of predefined avatar mood effects to be applied to the user's avatar in the virtual world based on the detected mood changing condition; automatically applying the avatar mood effect to the user's avatar in the virtual world in response to detecting occurrence of the mood changing condition and determining an applicable avatar mood effect based on the detected mood changing condition; and presenting the automatically applied avatar mood effect in association with the user's avatar in the virtual world, wherein presenting the automatically applied avatar mood effect comprises presenting a predefined script spoken by the user's avatar in at least one of a visual form and an audible form and presenting different colored clothing worn by the user's avatar depending on the avatar mood effect applied, bright colored clothing worn by the user's avatar expressing a happy mood and dark, black or gray colored clothing worn by the user's avatar expressing a sad mood.

1. A method for automated avatar mood effects in a virtual world, comprising: detecting occurrence of a mood changing condition relatable to a user's avatar; determining an avatar mood effect from the plurality of predefined avatar mood effects to be applied to the user's avatar in the virtual world based on the detected mood changing condition; automatically applying the avatar mood effect to the user's avatar in the virtual world in response to detecting occurrence of the mood changing condition and determining an applicable avatar mood effect based on the detected mood changing condition; and presenting the automatically applied avatar mood effect in association with the user's avatar in the virtual world, wherein presenting the automatically applied avatar mood effect comprises presenting a predefined script spoken by the user's avatar in at least one of a visual form and an audible form and presenting different colored clothing worn by the user's avatar depending on the avatar mood effect applied, bright colored clothing worn by the user's avatar expressing a happy mood and dark, black or gray colored clothing worn by the user's avatar expressing a sad mood. 10. The method of claim 1 , further comprising presenting at least one of a visual indicator and an audible indicator associated with the user's avatar to other users in the virtual world in response to the avatar mood effect being automatically applied to the user's avatar.

12. A computer-readable storage medium according to one of claim 1 and 2 , wherein the description of abstract constraints is inserted in a sub-part of the abstract part and is adapted to describe an abstract structure of messages exchanged.

12. A computer-readable storage medium according to one of claim 1 and 2 , wherein the description of abstract constraints is inserted in a sub-part of the abstract part and is adapted to describe an abstract structure of messages exchanged. 13. A computer-readable storage medium according to claim 12 , wherein the abstract part includes a sub-part adapted to declare at least one elementary message pointing to the description of the abstract constraints.

16. The method of claim 15 , wherein said model specifies regions of parameter values in accordance with said probability density of occurrence, each of said regions being associated with a respective process status.

16. The method of claim 15 , wherein said model specifies regions of parameter values in accordance with said probability density of occurrence, each of said regions being associated with a respective process status. 17. The method of claim 16 , further comprising determining said current status from a location of current parameter values within said regions.

10. The system of claim 8 , wherein at least one of the first record or the second record comprises a field, wherein the second server is programmed to assign a score to the field based on a number of matches between a content of the field and at least one of the first parameter or the second parameter.

10. The system of claim 8 , wherein at least one of the first record or the second record comprises a field, wherein the second server is programmed to assign a score to the field based on a number of matches between a content of the field and at least one of the first parameter or the second parameter. 13. The system of claim 10 , wherein the second server is programmed to sort the first record and the second record based on the score.

1. A method implemented by a digital home communication terminal (DHCT) comprising: presenting by the DHCT for display a video presentation; enabling a viewer to select an option to receive a plurality of sequential data supplements comprising on-screen comments of the video presentation, the sequential data supplements having a plurality of respective active time intervals of presentation and a screen position relative to the video presentation, wherein the active time intervals are determined based on an internal clock and a timer located on the DHCT; receiving a first input from the viewer regarding selection of the option to receive the plurality of sequential data supplements; responsive to receiving the first input corresponding to selecting the option to receive the plurality of sequential data supplements, providing the plurality of sequential data supplements for presentation at the plurality of respective active times corresponding to respective portions of the video presentation, the plurality of sequential data supplements are active only during the active time intervals at the screen position; receiving a second input from the viewer; and providing a video screen in response to the second input, wherein the video screen comprises a first reduced video area for the video presentation, a second reduced area for displaying information related to the video presentation, and a third reduced area for displaying control options for the video presentation, the control options comprising an option to stop the receipt of sequential data supplements.

1. A method implemented by a digital home communication terminal (DHCT) comprising: presenting by the DHCT for display a video presentation; enabling a viewer to select an option to receive a plurality of sequential data supplements comprising on-screen comments of the video presentation, the sequential data supplements having a plurality of respective active time intervals of presentation and a screen position relative to the video presentation, wherein the active time intervals are determined based on an internal clock and a timer located on the DHCT; receiving a first input from the viewer regarding selection of the option to receive the plurality of sequential data supplements; responsive to receiving the first input corresponding to selecting the option to receive the plurality of sequential data supplements, providing the plurality of sequential data supplements for presentation at the plurality of respective active times corresponding to respective portions of the video presentation, the plurality of sequential data supplements are active only during the active time intervals at the screen position; receiving a second input from the viewer; and providing a video screen in response to the second input, wherein the video screen comprises a first reduced video area for the video presentation, a second reduced area for displaying information related to the video presentation, and a third reduced area for displaying control options for the video presentation, the control options comprising an option to stop the receipt of sequential data supplements. 7. The method of claim 1 , further comprising: responsive to receiving the first input corresponding to selecting the option to receive the plurality of sequential data supplements, enabling the viewer to select on-screen comments from at least one other user, a director, a producer, or an actor; and receiving a second input from the viewer to select the on-screen comments from the at least one other user, director, producer, or actor.

6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, transmitting, to a client device: an audio presentation comprising a first portion and a second portion, wherein the first portion corresponds to a first item and the second portion corresponds to a second item; a first marker corresponding to the first item; and a second marker corresponding to the second item; receiving, from the client device: audio data comprising a user utterance; and marker data comprising the first marker or the second marker; and selecting an item based at least on the marker data or the audio data, wherein the selected item comprises the first item or the second item.

6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, transmitting, to a client device: an audio presentation comprising a first portion and a second portion, wherein the first portion corresponds to a first item and the second portion corresponds to a second item; a first marker corresponding to the first item; and a second marker corresponding to the second item; receiving, from the client device: audio data comprising a user utterance; and marker data comprising the first marker or the second marker; and selecting an item based at least on the marker data or the audio data, wherein the selected item comprises the first item or the second item. 7. The computer-implemented method of claim 6 , wherein the marker data comprises the second marker, the computer-implemented method further comprising: determining an amount of time between a first time that presentation of the second portion was initiated, and a second time that the user utterance was initiated.

9. A method for formatting multimedia programming information having listings elements and lineup elements to provide complete and valid programming information for an area, the method implemented on a computing device by a processor configured to execute instructions that, when executed by the processor, direct the computing device to perform acts comprising: defining a global listings format (GLF) in an extensible markup language (XML) that includes (i) an XML schema definition (XSD) for producing the listings elements and the lineup elements compliant with the XML XSD, (ii) one or more keys and keyref constraints, and (iii) a requirement that data conforming to the schema to exist for all listings elements and for all lineup elements; receiving a listings element from a data provider; receiving, from the data provider, associated listings elements and associated lineup elements; prompting the data provider for the associated listings elements and the associated lineup elements to receive a complete set of all the listings elements and the lineup elements associated with the received listings element when the associated listings elements and the associated lineup elements are missing, according to the GLF; parsing and validating the listings element, the associated listings elements, and the associated lineup elements, by the processor, against the XML XSD, wherein the XML XSD includes: a listings component including: schedule information including a channel identifier, a start time, and a duration; and program information including a program identifier and a program name; a lineups component including the area, available headends, and a channel lineup per one of the headends, the headends defining a set of channels available at a source, and the area being a region in which one of the headends exists; a common data entity including channels, the common data entity joining the listings component and the lineups component; and a fundamentals component including basic data type definitions that defines a structure of the data in the listings component and the lineups component; linking the associated listings elements and the associated lineup elements with the listings element according to the GLF by using XML XSD keys and keyref constraints, the linking including creating a logical relationship between one of the associated listings elements and one of the associated lineup elements such that presence of the one of the associated listings elements requires presence of the one of the associated lineup elements; and prompting the data provider for the associated listings elements and the associated lineup elements to enable parsing and validation showing conformance with the XML XSD when the associated listings elements and the associated lineup elements are not parsed and validated, according to the GLF; prompting the data provider for the associated listings elements and the associated lineup elements to complete the linking when the associated listings elements and the associated lineup elements are not linked, according to the GLF; wherein the listings elements include at least one of a program title, a unique program ID, an episode title, an episode number, a description, a year of creation, a cast, an acting role, a crew, a rating, a category, a length, a start time, or a frequency, and the lineup elements include at least a channel and a location information for the area.

9. A method for formatting multimedia programming information having listings elements and lineup elements to provide complete and valid programming information for an area, the method implemented on a computing device by a processor configured to execute instructions that, when executed by the processor, direct the computing device to perform acts comprising: defining a global listings format (GLF) in an extensible markup language (XML) that includes (i) an XML schema definition (XSD) for producing the listings elements and the lineup elements compliant with the XML XSD, (ii) one or more keys and keyref constraints, and (iii) a requirement that data conforming to the schema to exist for all listings elements and for all lineup elements; receiving a listings element from a data provider; receiving, from the data provider, associated listings elements and associated lineup elements; prompting the data provider for the associated listings elements and the associated lineup elements to receive a complete set of all the listings elements and the lineup elements associated with the received listings element when the associated listings elements and the associated lineup elements are missing, according to the GLF; parsing and validating the listings element, the associated listings elements, and the associated lineup elements, by the processor, against the XML XSD, wherein the XML XSD includes: a listings component including: schedule information including a channel identifier, a start time, and a duration; and program information including a program identifier and a program name; a lineups component including the area, available headends, and a channel lineup per one of the headends, the headends defining a set of channels available at a source, and the area being a region in which one of the headends exists; a common data entity including channels, the common data entity joining the listings component and the lineups component; and a fundamentals component including basic data type definitions that defines a structure of the data in the listings component and the lineups component; linking the associated listings elements and the associated lineup elements with the listings element according to the GLF by using XML XSD keys and keyref constraints, the linking including creating a logical relationship between one of the associated listings elements and one of the associated lineup elements such that presence of the one of the associated listings elements requires presence of the one of the associated lineup elements; and prompting the data provider for the associated listings elements and the associated lineup elements to enable parsing and validation showing conformance with the XML XSD when the associated listings elements and the associated lineup elements are not parsed and validated, according to the GLF; prompting the data provider for the associated listings elements and the associated lineup elements to complete the linking when the associated listings elements and the associated lineup elements are not linked, according to the GLF; wherein the listings elements include at least one of a program title, a unique program ID, an episode title, an episode number, a description, a year of creation, a cast, an acting role, a crew, a rating, a category, a length, a start time, or a frequency, and the lineup elements include at least a channel and a location information for the area. 11. The method as recited in claim 9 , wherein the area is a region characterized by specific languages spoken in the region.

15. A computer implemented method comprising: creating a plurality of explicit control functions in a software library stored on a storage device, where said software library is operable with an implicit control application development environment (ADE) executed by a central processing unit (CPU) coupled to said storage device; relating each of said plurality of explicit control functions with a progression of implicit logic, wherein said progression is selected to programmatically perform one or more operations defined by said each of said plurality of explicit control functions; and exposing said plurality of explicit control functions to a developer using said implicit control ADE.

15. A computer implemented method comprising: creating a plurality of explicit control functions in a software library stored on a storage device, where said software library is operable with an implicit control application development environment (ADE) executed by a central processing unit (CPU) coupled to said storage device; relating each of said plurality of explicit control functions with a progression of implicit logic, wherein said progression is selected to programmatically perform one or more operations defined by said each of said plurality of explicit control functions; and exposing said plurality of explicit control functions to a developer using said implicit control ADE. 16. The computer implemented method of claim 15 further comprising: defining one or more properties for ones of said plurality of explicit control functions, wherein said one or more properties are used by said progression in performing said one or more operations.

29. A method of verifying a counterfeit-resistant document, the method comprising the steps: applying a molecular code to said document; and spectrographically analyzing said molecular code to detect said molecular code.

29. A method of verifying a counterfeit-resistant document, the method comprising the steps: applying a molecular code to said document; and spectrographically analyzing said molecular code to detect said molecular code. 35. The method of claim 29, wherein said molecular code is specific to an identifying aspect of said document.

1. A method, in a data processing system, for evaluating the performance of a text analysis engine, the method comprising: receiving a plurality of pre-annotated reference documents; receiving a set of annotation types associated with the pre-annotated reference documents; analyzing annotation contexts of reference annotations in the plurality of pre-annotated reference documents using the set of annotation types; identifying similar annotation contexts between the reference annotations and the set of annotation types; responsive to identifying the similar annotation contexts, clustering the similar annotation contexts thereby forming a plurality of reference annotation clusters; computing a set of reference content heterogeneity scores based on the number of reference annotation clusters for each annotation type in the set of annotation types; computing an integral reference content rate for the set of annotation types; outputting the integral reference content rate to a user; receiving standard performance rates for the text analysis engine; applying the integral reference content rate to the standard performance rates; and generating reliable performance rates for the text analysis engine.

1. A method, in a data processing system, for evaluating the performance of a text analysis engine, the method comprising: receiving a plurality of pre-annotated reference documents; receiving a set of annotation types associated with the pre-annotated reference documents; analyzing annotation contexts of reference annotations in the plurality of pre-annotated reference documents using the set of annotation types; identifying similar annotation contexts between the reference annotations and the set of annotation types; responsive to identifying the similar annotation contexts, clustering the similar annotation contexts thereby forming a plurality of reference annotation clusters; computing a set of reference content heterogeneity scores based on the number of reference annotation clusters for each annotation type in the set of annotation types; computing an integral reference content rate for the set of annotation types; outputting the integral reference content rate to a user; receiving standard performance rates for the text analysis engine; applying the integral reference content rate to the standard performance rates; and generating reliable performance rates for the text analysis engine. 5. The method of claim 1 , wherein the integral reference content rate for the set of annotation types is computed using the following equation: ContentRate = ∑ n = 1 N_types ⁢ ⁢ 1 N_types ⁢ CH ⁡ ( T n ) , wherein N_types is the number of annotations types and wherein T n (n=1, N_types) are the plurality of annotations types.

1. A computer-implemented method, comprising: receiving a search request including one or more search terms; capturing each of the one or more search terms; providing a list of topics to a user as search results; receiving user selection of a topic in the list of topics, wherein the user adds one or more folksonomy tags to the topic after reviewing the topic; capturing the one or more folksonomy tags added by the user to the topic; mapping each of the one or more search terms and each of the one or more folksonomy tags to the topic; for each of the search terms: counting a first number of times the search term has been used for both searching and adding folksonomy tags to the topic; and based on the first number of times, adding the search term to retrievability aids by adding the search term to metadata for the topic, to an index, to a controlled vocabulary, and to a taxonomy, and wherein the adding is based on a search term threshold; and for each of the one or more folksonomy tags: counting a second number of times the folksonomy tag has been added to the topic; and based on the second number of times, adding the folksonomy tag to retrievability aids by adding the folksonomy tag to the metadata for the topic, to the index, to the controlled vocabulary, and to the taxonomy, and wherein the adding is based on a folksonomy tag threshold.

1. A computer-implemented method, comprising: receiving a search request including one or more search terms; capturing each of the one or more search terms; providing a list of topics to a user as search results; receiving user selection of a topic in the list of topics, wherein the user adds one or more folksonomy tags to the topic after reviewing the topic; capturing the one or more folksonomy tags added by the user to the topic; mapping each of the one or more search terms and each of the one or more folksonomy tags to the topic; for each of the search terms: counting a first number of times the search term has been used for both searching and adding folksonomy tags to the topic; and based on the first number of times, adding the search term to retrievability aids by adding the search term to metadata for the topic, to an index, to a controlled vocabulary, and to a taxonomy, and wherein the adding is based on a search term threshold; and for each of the one or more folksonomy tags: counting a second number of times the folksonomy tag has been added to the topic; and based on the second number of times, adding the folksonomy tag to retrievability aids by adding the folksonomy tag to the metadata for the topic, to the index, to the controlled vocabulary, and to the taxonomy, and wherein the adding is based on a folksonomy tag threshold. 4. The method of claim 1 , further comprising: determining whether the second number of times meets the folksonomy tag threshold; and in response to determining that the second number of times meets the folksonomy tag threshold, adding the folksonomy tag to the retrievability aids.

2. A translating apparatus, comprising: input means for inputting a range to be translated in an original text; display means for displaying the original text; context process range setting means for setting a context process range in the original text; context processing means for performing a context process for the original text; and translation processing means for translating an original text in the range to be translated into translated text, based on a context in the context process range.

2. A translating apparatus, comprising: input means for inputting a range to be translated in an original text; display means for displaying the original text; context process range setting means for setting a context process range in the original text; context processing means for performing a context process for the original text; and translation processing means for translating an original text in the range to be translated into translated text, based on a context in the context process range. 6. The translating apparatus according to claim 2, wherein said context processing means estimates a reference destination.

11. A server comprising: a memory to store instructions; and a processor to execute the instructions to: receive a document; select terms from the document to form a plurality of term pairs, where the selection of terms is weighted such that terms that appear closer to each other in the document have a higher probability of being included in the plurality of term pairs than terms that appear farther from each other in the document; create a cluster that includes the plurality of term pairs, where the cluster is created by sampling at least one of the plurality of term pairs, and a quantity of the plurality of term pairs that is sampled is determined based on a length of the document; and determine whether an input document is similar to the document by comparing pairs of terms from the input document with the plurality of term pairs in the cluster for the document.

11. A server comprising: a memory to store instructions; and a processor to execute the instructions to: receive a document; select terms from the document to form a plurality of term pairs, where the selection of terms is weighted such that terms that appear closer to each other in the document have a higher probability of being included in the plurality of term pairs than terms that appear farther from each other in the document; create a cluster that includes the plurality of term pairs, where the cluster is created by sampling at least one of the plurality of term pairs, and a quantity of the plurality of term pairs that is sampled is determined based on a length of the document; and determine whether an input document is similar to the document by comparing pairs of terms from the input document with the plurality of term pairs in the cluster for the document. 14. The server of claim 11 , where the processor executes instructions to: store a plurality of clusters, where each cluster includes a plurality of term pairs and each cluster is associated with a different document.

1. A method for evaluating content descriptors for online publications, comprising the operations of: receiving a list of websites having online publications; gathering counts of user signals for each online publication on each website; determining content descriptors for each online publication; counting the online publications at each website associated with each content descriptor; and counting the user signals at each website associated with each content descriptor, wherein each operation of the method is executed by one or more processors.

1. A method for evaluating content descriptors for online publications, comprising the operations of: receiving a list of websites having online publications; gathering counts of user signals for each online publication on each website; determining content descriptors for each online publication; counting the online publications at each website associated with each content descriptor; and counting the user signals at each website associated with each content descriptor, wherein each operation of the method is executed by one or more processors. 8. The method of claim 1 , wherein the gathering of counts of user signals involves accessing an application programming interface.

37. A computer implemented data object registry method, comprising the steps of: providing a data object registry for registering data objects; providing a database for receiving, storing, and allowing access to data objects concerning a plurality of topics, meta data created at a time of entry of said data, meta data comprising at least one annotation concerning said data, and meta data comprising access statistics concerning said data; providing a viewing tool for allowing user access to data in said database; representing a plurality of registered data objects in said data registry as a hash table entry; wherein each hash table entry identifies a corresponding data object's location, representation, and any associated meta data; and wherein each hash table entry comprises an index hash, a cryptographically strong signature for verification and security, a data identifier, and a meta data identifier; and using said viewing tool to access data objects in said database via said data object reentry.

37. A computer implemented data object registry method, comprising the steps of: providing a data object registry for registering data objects; providing a database for receiving, storing, and allowing access to data objects concerning a plurality of topics, meta data created at a time of entry of said data, meta data comprising at least one annotation concerning said data, and meta data comprising access statistics concerning said data; providing a viewing tool for allowing user access to data in said database; representing a plurality of registered data objects in said data registry as a hash table entry; wherein each hash table entry identifies a corresponding data object's location, representation, and any associated meta data; and wherein each hash table entry comprises an index hash, a cryptographically strong signature for verification and security, a data identifier, and a meta data identifier; and using said viewing tool to access data objects in said database via said data object reentry. 45. The method of claim 37 , further comprising the step of: providing a meta data identifier that contains at least one component that indicates type and location of at least one link annotating said data object; wherein each meta data component specifies multiple alternative locations where meta data are found; and wherein each location has a type specifying a format of meta data stored in that location.

5. A system comprising: one or more data sources storing contact data; and one or more processors configured to interact with the one or more data sources, the one or more processors being further configured to perform operations comprising: receiving a search query from a searching user; identifying, by the one or more processors and using a resource index, a plurality of search results that are responsive to the search query, each of the search results in the plurality of search results being representative of a web resource; determining, by the one or more processors, whether there are users responsive to the search query using an interaction system that retrieves, from one or more data sources that are distinct from the resource index, contact information that is included in a user profile of the searching user, wherein determining whether there are users responsive to the search query includes cross-referencing the search query to the contact information that is included in the user profile of the searching user; in response to determining that there are no users responsive to the search query, providing one or more search results of the plurality of search results to a computing device associated with the searching user; in response to determining that there are users responsive to the search query: providing, by the one or more processors, a sub-set of the users, each user in the sub-set being connected to the searching user through one or more computer-implemented services, the sub-set comprising at least one user; determining that contact data of the at least one user is available, wherein the contact data comprises publically available contact data, and wherein determining that contact data is available comprises determining that a portion of the contact data is accessible to the searching user based on privacy settings provided by the user, the portion of the contact data being included in the contact data in response to determining that a portion of the contact data is accessible to the searching user, and in response to determining that contact data of the at least one user is available: providing an electronic document comprising instructions that, when executed by the computing device, cause the computing device to display a search results page, wherein the search results page comprises a first portion including a group of search results each representative of a web resource responsive to the search query and a second portion including a profile card associated with the at least one user, the profile card comprising one or more graphical representations associated with an interaction channel, each interaction channel being associated with respective contact data of the contact data, and each graphical representation receiving user input and initiating execution of a respective interaction between the searching user and the at least one user from the search results page, an interaction interface that executes the respective interaction being displayed concurrently with the plurality of search results in the search results page, wherein the interaction interface is provided by an interaction hovercard displayed with the search results page in response to initiating execution of an interaction from the search results page; and transmitting the electronic document to the computing device associated with the searching user.

5. A system comprising: one or more data sources storing contact data; and one or more processors configured to interact with the one or more data sources, the one or more processors being further configured to perform operations comprising: receiving a search query from a searching user; identifying, by the one or more processors and using a resource index, a plurality of search results that are responsive to the search query, each of the search results in the plurality of search results being representative of a web resource; determining, by the one or more processors, whether there are users responsive to the search query using an interaction system that retrieves, from one or more data sources that are distinct from the resource index, contact information that is included in a user profile of the searching user, wherein determining whether there are users responsive to the search query includes cross-referencing the search query to the contact information that is included in the user profile of the searching user; in response to determining that there are no users responsive to the search query, providing one or more search results of the plurality of search results to a computing device associated with the searching user; in response to determining that there are users responsive to the search query: providing, by the one or more processors, a sub-set of the users, each user in the sub-set being connected to the searching user through one or more computer-implemented services, the sub-set comprising at least one user; determining that contact data of the at least one user is available, wherein the contact data comprises publically available contact data, and wherein determining that contact data is available comprises determining that a portion of the contact data is accessible to the searching user based on privacy settings provided by the user, the portion of the contact data being included in the contact data in response to determining that a portion of the contact data is accessible to the searching user, and in response to determining that contact data of the at least one user is available: providing an electronic document comprising instructions that, when executed by the computing device, cause the computing device to display a search results page, wherein the search results page comprises a first portion including a group of search results each representative of a web resource responsive to the search query and a second portion including a profile card associated with the at least one user, the profile card comprising one or more graphical representations associated with an interaction channel, each interaction channel being associated with respective contact data of the contact data, and each graphical representation receiving user input and initiating execution of a respective interaction between the searching user and the at least one user from the search results page, an interaction interface that executes the respective interaction being displayed concurrently with the plurality of search results in the search results page, wherein the interaction interface is provided by an interaction hovercard displayed with the search results page in response to initiating execution of an interaction from the search results page; and transmitting the electronic document to the computing device associated with the searching user. 7. The system of claim 5 , wherein the one or more data sources comprise at least one of a contact data repository associated with a computer-implemented contact management service, a social data repository associated with a computer-implemented social networking service, an electronic mail address repository associated with a computer-implemented electronic mail service, and a public data repository.

2. The mobile terminal of claim 1 , wherein the controller is further configured to: recognize the handwritten character in real-time; cause the touchscreen to display one or more candidate text characters that correspond to the recognized handwritten character; cause the memory to store one of the one or more candidate text characters as the confirmed text character; and link the confirmed text character to the handwritten character.

2. The mobile terminal of claim 1 , wherein the controller is further configured to: recognize the handwritten character in real-time; cause the touchscreen to display one or more candidate text characters that correspond to the recognized handwritten character; cause the memory to store one of the one or more candidate text characters as the confirmed text character; and link the confirmed text character to the handwritten character. 14. The mobile terminal of claim 2 , wherein the controller is further configured to: convert the handwritten character to the confirmed text character; and output the confirmed text character as text.

1. A method of opening a communications channel between a first and a second person, comprising the steps of: receiving a date of birth from said first and said second person; polling said first and said second person, and receiving answers for said first and said second person; determining a Myers-Briggs Type Indicator (MBTI) for said first and said second person based on said answers; determining a Chinese zodiac sign corresponding to said first and said second person, based on said received date of birth; determining a Western astrological sign corresponding to said first and said second person, based on said received date of birth; receiving at least one attribute characteristic of said first and said second person, and receiving at least one limiting attribute required of a person from said first and said second person; exhibiting to said first person, information about said second person if a weighted ranking of said MBTI, said Chinese zodiac, and said Western astrological sign are determined to be above a compatibility threshold, and said second person comprises said at least one limiting attributes required of said first person; and providing a communication channel between said first and said second person, based on an expressed desire to communicate from said first person to said second person.

1. A method of opening a communications channel between a first and a second person, comprising the steps of: receiving a date of birth from said first and said second person; polling said first and said second person, and receiving answers for said first and said second person; determining a Myers-Briggs Type Indicator (MBTI) for said first and said second person based on said answers; determining a Chinese zodiac sign corresponding to said first and said second person, based on said received date of birth; determining a Western astrological sign corresponding to said first and said second person, based on said received date of birth; receiving at least one attribute characteristic of said first and said second person, and receiving at least one limiting attribute required of a person from said first and said second person; exhibiting to said first person, information about said second person if a weighted ranking of said MBTI, said Chinese zodiac, and said Western astrological sign are determined to be above a compatibility threshold, and said second person comprises said at least one limiting attributes required of said first person; and providing a communication channel between said first and said second person, based on an expressed desire to communicate from said first person to said second person. 11. The method of claim 1 , wherein a said zodiac matching zodiac, including said Chinese zodiac or said Western astrological sign, is discarded only when said Myers-Briggs and other zodiac type match perfectly or near-perfectly, wherein near-perfectly is having, at most, one element or data point fail to match.

1. A computer implemented method for indexing and retrieving documents stored in a database, comprising the steps of: extracting a document feature vector from each of a plurality of documents; indexing each of the plurality of documents according the associated document feature vector; converting, using a processor, a spoken query to an intermediate representation representing possible sequential combinations of terms in the spoken query, the intermediate representation is selected from a group consisting of a lattice of terms, an n-best list, or combination thereof; generating a query certainty vector from the intermediate representation; and comparing the query certainty vector to each of the document feature vectors to retrieve a ranked result set of documents.

1. A computer implemented method for indexing and retrieving documents stored in a database, comprising the steps of: extracting a document feature vector from each of a plurality of documents; indexing each of the plurality of documents according the associated document feature vector; converting, using a processor, a spoken query to an intermediate representation representing possible sequential combinations of terms in the spoken query, the intermediate representation is selected from a group consisting of a lattice of terms, an n-best list, or combination thereof; generating a query certainty vector from the intermediate representation; and comparing the query certainty vector to each of the document feature vectors to retrieve a ranked result set of documents. 2. The method of claim 1 , further comprising: projecting each document feature vector and the query certainty vector to a low dimension.

1. A computer-implemented system for designing software-based components for systems of systems where the systems of systems consist of components that are themselves systems, the computer implemented system comprising: multiple software-based components saved in a relational database where the functions of each software component are defined by one or more examples of its operation using a natural language and where each software component is assigned a searchable, unique free-text field such that each of the components have multiple indexed levels in a literal restriction path; and a processor and memory, the processor and memory controlling retrieval, synthesis, substitution, reuse and modification of the components in the relational database at every level of the multiple levels, including means for defining a new software component, including functional I/O definitions where each component saved in the relational database is associated with one or more tests that serve to map a random input vector to a correct output vector; where the I/O definitions includes I/O specification vectors for testing the systems of systems; where the I/O definitions includes I/O specification rules for component construction and including I/O specification vectors which are local to each component and where each component has an input vector holding bin and an output vector holding bin and where the output bins feed the input bins to which they are connected so that a component will only produce outputs for those respective inputs which are found in its respective specification vector.

1. A computer-implemented system for designing software-based components for systems of systems where the systems of systems consist of components that are themselves systems, the computer implemented system comprising: multiple software-based components saved in a relational database where the functions of each software component are defined by one or more examples of its operation using a natural language and where each software component is assigned a searchable, unique free-text field such that each of the components have multiple indexed levels in a literal restriction path; and a processor and memory, the processor and memory controlling retrieval, synthesis, substitution, reuse and modification of the components in the relational database at every level of the multiple levels, including means for defining a new software component, including functional I/O definitions where each component saved in the relational database is associated with one or more tests that serve to map a random input vector to a correct output vector; where the I/O definitions includes I/O specification vectors for testing the systems of systems; where the I/O definitions includes I/O specification rules for component construction and including I/O specification vectors which are local to each component and where each component has an input vector holding bin and an output vector holding bin and where the output bins feed the input bins to which they are connected so that a component will only produce outputs for those respective inputs which are found in its respective specification vector. 8. The system of claim 1 including a CASE optimization tool for measuring component execution time and spatial requirements.

2. The computer-implemented method of claim 1 , wherein each of the multiple candidate transcriptions of the user utterance is associated with a speech recognition lattice that is generated by the server-based, automated speech recognizer based on the audio data.

2. The computer-implemented method of claim 1 , wherein each of the multiple candidate transcriptions of the user utterance is associated with a speech recognition lattice that is generated by the server-based, automated speech recognizer based on the audio data. 3. The computer-implemented method of claim 2 , wherein the second transcription of the user utterance is an only alternate transcription of the user utterance associated with the speech recognition lattice that includes one or more alternate words substituted for the at least one incorrect word.

1. A method comprising: receiving, on a computer system comprising a processor and memory storing instructions, a supplied phrase, the supplied phrase comprising one or more terms, the supplied phrase being associated with a category of a plurality of categories, each category being associated with a different topic and a plurality of phrases each having a meaning semantically related to the different topic, the plurality of categories being used by an analytics system to perform classifications; examining one or more terms included in the supplied phrase; based on examining the one or more terms, determining that a first term of the supplied phrase corresponds to a semantic group; identifying a second term that is included in the semantic group; generating, using the supplied phrase and the second term, a suggested phrase having a similar meaning to the supplied phrase, the suggested phrase and the supplied phrase being semantically related to the different topic associated with the category; and adding the suggested phrase to the category that includes the supplied phrase.

1. A method comprising: receiving, on a computer system comprising a processor and memory storing instructions, a supplied phrase, the supplied phrase comprising one or more terms, the supplied phrase being associated with a category of a plurality of categories, each category being associated with a different topic and a plurality of phrases each having a meaning semantically related to the different topic, the plurality of categories being used by an analytics system to perform classifications; examining one or more terms included in the supplied phrase; based on examining the one or more terms, determining that a first term of the supplied phrase corresponds to a semantic group; identifying a second term that is included in the semantic group; generating, using the supplied phrase and the second term, a suggested phrase having a similar meaning to the supplied phrase, the suggested phrase and the supplied phrase being semantically related to the different topic associated with the category; and adding the suggested phrase to the category that includes the supplied phrase. 20. The method of claim 1 , wherein adding the suggested phrase to the category that includes the supplied phrase comprises: displaying the suggested phrase to a user as an alternate option for the supplied phrase; receiving a user input accepting the suggested phrase as an alternate option; and in response to receiving the user input, adding the suggested phrase to the category that includes the supplied phrase.

17. A network based interactive speech system adapted for responding to speech-based queries concerning a set of topic entries, the system comprising: a speech recognition engine adapted to generate recognized speech utterance data from speech data associated with a speech-based query from a speaker concerning one of the set of topic entries; a first routine executing on a server system and adapted to perform natural language processing on said recognized speech utterance data to identify a selected set of phrases related to the set of topic entries; a second routine executing on the server system and adapted to convert said selected set of phrases from the first routine into a search query suitable for identifying a first group of one or more topic entries corresponding to said speech-based query; wherein words and/or phrases in said search query can be assigned different weightings determined by said first routine from said recognized speech utterance data; a third routine executing on the server system adapted to evaluate said first group of one or more topic entries and to identify a single topic entry responsive to said speech-based query; wherein third routine can consider words and/or phrases in said search query which are not in said set of topic entries; and wherein information corresponding to a single topic entry taken from said first group can be determined and presented in real-time by the interactive speech system automatically as a response best matching said speech-based query; and a second server system adapted to assist with a response to said speech-based query, such that said speech based query is recognized at the server system, and multiple databases at different server systems linked to the server system can be considered in responding to queries for said set of topic entries, wherein a database at said second server system can be considered for said response to said speech-based query when said server system cannot satisfy a desired confidence level required for said response.

17. A network based interactive speech system adapted for responding to speech-based queries concerning a set of topic entries, the system comprising: a speech recognition engine adapted to generate recognized speech utterance data from speech data associated with a speech-based query from a speaker concerning one of the set of topic entries; a first routine executing on a server system and adapted to perform natural language processing on said recognized speech utterance data to identify a selected set of phrases related to the set of topic entries; a second routine executing on the server system and adapted to convert said selected set of phrases from the first routine into a search query suitable for identifying a first group of one or more topic entries corresponding to said speech-based query; wherein words and/or phrases in said search query can be assigned different weightings determined by said first routine from said recognized speech utterance data; a third routine executing on the server system adapted to evaluate said first group of one or more topic entries and to identify a single topic entry responsive to said speech-based query; wherein third routine can consider words and/or phrases in said search query which are not in said set of topic entries; and wherein information corresponding to a single topic entry taken from said first group can be determined and presented in real-time by the interactive speech system automatically as a response best matching said speech-based query; and a second server system adapted to assist with a response to said speech-based query, such that said speech based query is recognized at the server system, and multiple databases at different server systems linked to the server system can be considered in responding to queries for said set of topic entries, wherein a database at said second server system can be considered for said response to said speech-based query when said server system cannot satisfy a desired confidence level required for said response. 23. The interactive speech system of claim 17 , wherein said speech-based query controls an interaction by said speaker with content associated with a web page.

17. The computerized method of claim 16 , wherein the result-generating function associated with the same query is also associated with the another query that is substantially similar to the same query.

17. The computerized method of claim 16 , wherein the result-generating function associated with the same query is also associated with the another query that is substantially similar to the same query. 18. The computerized method of claim 17 , further comprising: receiving the another query that is substantially similar to the same query from a user; identifying, at least in part in response to the receiving of the another query from the user, the result-generating function; and generating query results for the user that submitted the another query using the identified result-generating function.

1. A method for a computer system to represent the meaning of a source sentence from a source language, the method comprising: obtaining a language-independent semantic structure to represent the meaning of the source sentence; synthesizing a syntactic structure of an output sentence from the language independent semantic structure using information which includes semantic descriptions, lexical descriptions of an output language, syntactic descriptions of the output language, and morphological descriptions of the output language, wherein the syntactic structure is built at least in part based on ratings of syntactic constructions for each element of the source sentence; and constructing the output sentence to represent the meaning of the source sentence in the output language by performing a lexical selection on the language-independent semantic structure of the sentence using lexical descriptions of the output language and semantic descriptions, wherein performing the lexical selection further comprises applying one or more semantic structure correction rules to overcome asymmetries between the language-independent semantic structure and the syntactic structure of the output sentence in the output language, and wherein applying one or more semantic structure correction rules to overcome asymmetries includes the use of one or more semanteme calculating rules and one or more semanteme normalization rules.

1. A method for a computer system to represent the meaning of a source sentence from a source language, the method comprising: obtaining a language-independent semantic structure to represent the meaning of the source sentence; synthesizing a syntactic structure of an output sentence from the language independent semantic structure using information which includes semantic descriptions, lexical descriptions of an output language, syntactic descriptions of the output language, and morphological descriptions of the output language, wherein the syntactic structure is built at least in part based on ratings of syntactic constructions for each element of the source sentence; and constructing the output sentence to represent the meaning of the source sentence in the output language by performing a lexical selection on the language-independent semantic structure of the sentence using lexical descriptions of the output language and semantic descriptions, wherein performing the lexical selection further comprises applying one or more semantic structure correction rules to overcome asymmetries between the language-independent semantic structure and the syntactic structure of the output sentence in the output language, and wherein applying one or more semantic structure correction rules to overcome asymmetries includes the use of one or more semanteme calculating rules and one or more semanteme normalization rules. 5. The method of claim 1 , wherein the morphological synthesis is performed on lexical meanings of constituent cores of the surface structure of the output sentence in the output language.

7. The system as claimed in claim 2 wherein said reminder information includes a plurality of options to include information with said reminder message.

7. The system as claimed in claim 2 wherein said reminder information includes a plurality of options to include information with said reminder message. 8. The system as claimed in claim 7 wherein one said option includes the ability to attach a checklist to said reminder message.

13. A system for hierarchical program source management, comprising: a display; a memory for storing a main program; and a processor programmed to provide a program development interface via the display and to: retrieve the main program from the memory; initiate a layer representing a portion of the main program for editing on the display; edit program code within the layer in response to detected user programming inputs; generate a layer abstract syntax tree corresponding to the edited program code; compare the layer abstract syntax tree with a main program abstract syntax tree; and generate a layer file comprising differences between the layer abstract syntax tree and the main program abstract syntax tree.

13. A system for hierarchical program source management, comprising: a display; a memory for storing a main program; and a processor programmed to provide a program development interface via the display and to: retrieve the main program from the memory; initiate a layer representing a portion of the main program for editing on the display; edit program code within the layer in response to detected user programming inputs; generate a layer abstract syntax tree corresponding to the edited program code; compare the layer abstract syntax tree with a main program abstract syntax tree; and generate a layer file comprising differences between the layer abstract syntax tree and the main program abstract syntax tree. 18. The system of claim 13 , where the processor is further programmed to: detect a selection of at least one layer file by the user; and flatten the at least one layer file and the main program to generate a new main program using the layer abstract syntax tree corresponding to the at least one layer file.

18. A system for processing an interaction with a person, comprising a processor, two or more analyst user interface devices in communication with the processor, and a memory in communication with the processor, the memory storing programming instructions executable by the processor to: receive data representing a multi-utterance transaction with the person, the data having multiple elements, a subset of the elements including sensitive customer data; portion the multi-utterance transaction into discrete, logical utterance units; automatically present the utterance units in perceptible form through the analyst interface devices to a number of intent analysts, the utterance units being distributed so that no intent analyst is ever exposed to more than one of said subset of the elements including sensitive customer data; accept intent input from each intent analyst through the respective analyst user interface device, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance, and where the intent input is prevented from providing information to be communicated to the person; and automatically communicate a message to the person, in perceptible form and in substantially real time relative to the receiving function, the message being automatically selected from among a predetermined set of possible messages as a function of the intent input accepted from the two or more intent analysts.

18. A system for processing an interaction with a person, comprising a processor, two or more analyst user interface devices in communication with the processor, and a memory in communication with the processor, the memory storing programming instructions executable by the processor to: receive data representing a multi-utterance transaction with the person, the data having multiple elements, a subset of the elements including sensitive customer data; portion the multi-utterance transaction into discrete, logical utterance units; automatically present the utterance units in perceptible form through the analyst interface devices to a number of intent analysts, the utterance units being distributed so that no intent analyst is ever exposed to more than one of said subset of the elements including sensitive customer data; accept intent input from each intent analyst through the respective analyst user interface device, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance, and where the intent input is prevented from providing information to be communicated to the person; and automatically communicate a message to the person, in perceptible form and in substantially real time relative to the receiving function, the message being automatically selected from among a predetermined set of possible messages as a function of the intent input accepted from the two or more intent analysts. 23. The system of claim 18 , wherein the programming instructions are further executable by the processor to automatically change the number of intent analysts to whom one of the utterance units is presented depending on a load factor, the utterance units still being distributed so that no intent analyst is ever exposed to more than one of said subset of the elements including sensitive customer data.

1. An Internet infrastructure that supports searching of images, the Internet infrastructure having a web browser contained in a client device that supports displaying of the images from the plurality of web hosting servers, the Internet infrastructure including an image search server, the image search server comprising: memory; and a processor operably coupled to the memory, the processor configured to: receive from the web browser, a search string, and a search image; support delivery of one or more search result pages that include images from the plurality of web servers to the client device based upon the search string and search image; respond to the receiving of a search string by selecting a first set of selected images, the titles of which correspond to the search string; respond to the receiving of a search image by selecting a second set of selected images, one or more image characteristics of each image of the second set of selected images which correlate to that of the search image; and deliver a first search result page comprising a first portion of the first set of selected images and a second portion of the second set of selected images.

1. An Internet infrastructure that supports searching of images, the Internet infrastructure having a web browser contained in a client device that supports displaying of the images from the plurality of web hosting servers, the Internet infrastructure including an image search server, the image search server comprising: memory; and a processor operably coupled to the memory, the processor configured to: receive from the web browser, a search string, and a search image; support delivery of one or more search result pages that include images from the plurality of web servers to the client device based upon the search string and search image; respond to the receiving of a search string by selecting a first set of selected images, the titles of which correspond to the search string; respond to the receiving of a search image by selecting a second set of selected images, one or more image characteristics of each image of the second set of selected images which correlate to that of the search image; and deliver a first search result page comprising a first portion of the first set of selected images and a second portion of the second set of selected images. 3. The Internet infrastructure of claim 1 , wherein image characteristics of which correlates to that of search image comprising close correlation between the characteristic parameters of the search image and characteristic parameters of the images.

9. The method of claim 8 , further comprising refining at least one partial interpretation, wherein the at least one partial interpretation is refined by way of spatial processing.

9. The method of claim 8 , further comprising refining at least one partial interpretation, wherein the at least one partial interpretation is refined by way of spatial processing. 10. The method of claim 9 , wherein the at least one partial interpretation is refined by determining that an entity in the first dataset spatially corresponds with a region of interest pertaining to the query.

1. A device comprising: a display; a processor; and a memory communicatively coupled to the processor, the memory storing instructions causing the processor, after execution of the instructions by the processor, to: display a reference page number with each displayed page of a digital document having reference page numbers, the digital document corresponding to a reference document having page numbers that correspond to the reference page numbers; render the digital document based on the characteristics of the display that change the amount of content that can fit on the display; and display a fractional page number with each displayed page of the digital document, each fractional page number corresponding to a portion of a page of the reference document, wherein the fractional page number is updated in response to the characteristics of the display being changed, wherein the memory stores instructions causing the processor, after execution of the instructions by the processor, to: based on the reference page numbers and fractional page numbers, determine print charges for the digital document, estimate bandwidth for transmitting the digital document, or determine the type of content of the digital document.

1. A device comprising: a display; a processor; and a memory communicatively coupled to the processor, the memory storing instructions causing the processor, after execution of the instructions by the processor, to: display a reference page number with each displayed page of a digital document having reference page numbers, the digital document corresponding to a reference document having page numbers that correspond to the reference page numbers; render the digital document based on the characteristics of the display that change the amount of content that can fit on the display; and display a fractional page number with each displayed page of the digital document, each fractional page number corresponding to a portion of a page of the reference document, wherein the fractional page number is updated in response to the characteristics of the display being changed, wherein the memory stores instructions causing the processor, after execution of the instructions by the processor, to: based on the reference page numbers and fractional page numbers, determine print charges for the digital document, estimate bandwidth for transmitting the digital document, or determine the type of content of the digital document. 3. The device of claim 1 , wherein the fractional page number comprises a decimal representation.

14. A system of generating domain name suggestions based on inputs comprising: a non-transitory memory storing instructions; and a processor executing the instructions to cause the system to perform a method comprising: receiving, at a computer, an input source, wherein the input source corresponds to at least one of an image data file, an audio data file, or a metadata source; processing, via the computer, the input source to extract information from the input source; identifying a similar data file that is similar to at least a portion of the input source, wherein the similar data file is extracted from a similar data file source; determining additional information about the similar data file based on contextual data describing the similar data file in the similar data file source; building, via the computer, a submission string based on the extracted information and the additional information; submitting the submission string to a name suggestion service; receiving name suggestions based on the submission string; and providing the name suggestions.

14. A system of generating domain name suggestions based on inputs comprising: a non-transitory memory storing instructions; and a processor executing the instructions to cause the system to perform a method comprising: receiving, at a computer, an input source, wherein the input source corresponds to at least one of an image data file, an audio data file, or a metadata source; processing, via the computer, the input source to extract information from the input source; identifying a similar data file that is similar to at least a portion of the input source, wherein the similar data file is extracted from a similar data file source; determining additional information about the similar data file based on contextual data describing the similar data file in the similar data file source; building, via the computer, a submission string based on the extracted information and the additional information; submitting the submission string to a name suggestion service; receiving name suggestions based on the submission string; and providing the name suggestions. 21. The system of claim 14 , wherein the input source corresponds to at least one metadata source and the processing comprises: extracting metadata from the metadata source; and processing the metadata to create extracted information based on the metadata source.

11. The system according to claim 1 , wherein the computing device is further configured to: receive the grammar from the selected domain agent; and evaluate the determined context and the question using the grammar received from the selected domain agent, wherein the request includes all tokens that are required to format the question in the grammar used by the selected domain agent.

11. The system according to claim 1 , wherein the computing device is further configured to: receive the grammar from the selected domain agent; and evaluate the determined context and the question using the grammar received from the selected domain agent, wherein the request includes all tokens that are required to format the question in the grammar used by the selected domain agent. 12. The system according to claim 11 , wherein the request further includes one or more tokens that are optional to format the question in the grammar used by the selected domain agent.

13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving audio data that encodes an utterance of a user; determining that the user has been classified as a novice user of a speech recognizer, comprising determining that an amount of training data that has been collected for the user does not satisfy a threshold; in response to determining that the user has been classified as a novice user of a speech recognizer, selecting a speech recognizer setting that is used by the speech recognizer in generating a transcription of the utterance, wherein the selected speech recognizer setting is different than a default speech recognizer setting that is used by the speech recognizer in generating transcriptions of utterances of users that are not classified as novice users, and wherein the selected speech recognizer setting results in increased speech recognition accuracy for the utterance in comparison with the default setting, wherein the selected speech recognizer setting results in increased speech recognition latency for the utterance in comparison with the default setting; and obtaining a transcription of the utterance that is generated by the speech recognizer using the selected speech recognizer setting.

13. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving audio data that encodes an utterance of a user; determining that the user has been classified as a novice user of a speech recognizer, comprising determining that an amount of training data that has been collected for the user does not satisfy a threshold; in response to determining that the user has been classified as a novice user of a speech recognizer, selecting a speech recognizer setting that is used by the speech recognizer in generating a transcription of the utterance, wherein the selected speech recognizer setting is different than a default speech recognizer setting that is used by the speech recognizer in generating transcriptions of utterances of users that are not classified as novice users, and wherein the selected speech recognizer setting results in increased speech recognition accuracy for the utterance in comparison with the default setting, wherein the selected speech recognizer setting results in increased speech recognition latency for the utterance in comparison with the default setting; and obtaining a transcription of the utterance that is generated by the speech recognizer using the selected speech recognizer setting. 14. The system of claim 13 , wherein determining that an amount of training data that has been collected for the user does not satisfy a threshold comprises: determining a size of the training data; and determining that the size does not satisfy the threshold.

1. A method comprising: receiving, by at least one computing device from an access device, a request for a content instance included in a plurality of stored content instances associated with a plurality of user profiles, the request associated with a user profile included in the plurality of user profiles; identifying, by the at least one computing device based on a predefined relationship heuristic, a plurality of other content instances included in the plurality of stored content instances as being related to the requested content instance, the plurality of other content instances associated with other user profiles included in the plurality of user profiles; determining, by the at least one computing device based on a predefined relevance heuristic, a relevance between the user profile and each of the other user profiles; prioritizing, by the at least one computing device based on the determined relevance between the user profile and each of the other user profiles, the other content instances relative to one another; and providing, by the at least one computing device to the access device in response to the request, data representative of the requested content instance and the prioritized other content instances; wherein the predefined relevance heuristic is custom defined by a user associated with the user profile.

1. A method comprising: receiving, by at least one computing device from an access device, a request for a content instance included in a plurality of stored content instances associated with a plurality of user profiles, the request associated with a user profile included in the plurality of user profiles; identifying, by the at least one computing device based on a predefined relationship heuristic, a plurality of other content instances included in the plurality of stored content instances as being related to the requested content instance, the plurality of other content instances associated with other user profiles included in the plurality of user profiles; determining, by the at least one computing device based on a predefined relevance heuristic, a relevance between the user profile and each of the other user profiles; prioritizing, by the at least one computing device based on the determined relevance between the user profile and each of the other user profiles, the other content instances relative to one another; and providing, by the at least one computing device to the access device in response to the request, data representative of the requested content instance and the prioritized other content instances; wherein the predefined relevance heuristic is custom defined by a user associated with the user profile. 4. The method of claim 1 , wherein the determining of the relevance between the user profile and each of the other user profiles comprises determining a relevance between the user profile and each of the other user profiles based at least in part on a measure of reliance between the user associated with the user profile and each other user associated with each of the other user profiles.

6. The device claimed in claim 5 wherein said predicate phrase area comprises: a means for accepting addresses of a series of auxiliary verb forms, and for coupling said forms with the infinitive, past participle and gerund modes of verbs to create present, past and future conjugations of said verbs.

6. The device claimed in claim 5 wherein said predicate phrase area comprises: a means for accepting addresses of a series of auxiliary verb forms, and for coupling said forms with the infinitive, past participle and gerund modes of verbs to create present, past and future conjugations of said verbs. 7. The device claimed in claim 6 wherein said dedicated keys include keys for entering auxiliary verb forms, articles, prepositions, personal pronouns, demonstrative pronouns and interrogative adverbs.

20. The computer-readable medium as recited in claim 18 , wherein the instructions for determining a relevance of each one of a plurality of lines of text of a document based upon the intent of the query, content of the query, and content of each of the plurality of lines of text comprises: instructions for determining a query-independent relevance of each of the plurality of lines of text in the document; instructions for determining a query-dependent relevance of each of the plurality of lines of text in the document; and instructions for calculating the relevance of each one of the plurality of lines of text based upon the intent of the query, the query independent relevance of the one of the plurality of lines of text in the document and the query dependent relevance of the one of the plurality of lines of text in the document.

20. The computer-readable medium as recited in claim 18 , wherein the instructions for determining a relevance of each one of a plurality of lines of text of a document based upon the intent of the query, content of the query, and content of each of the plurality of lines of text comprises: instructions for determining a query-independent relevance of each of the plurality of lines of text in the document; instructions for determining a query-dependent relevance of each of the plurality of lines of text in the document; and instructions for calculating the relevance of each one of the plurality of lines of text based upon the intent of the query, the query independent relevance of the one of the plurality of lines of text in the document and the query dependent relevance of the one of the plurality of lines of text in the document. 21. The computer-readable medium as recited in claim 20 , wherein determining a query-independent relevance of each of the plurality of lines of text in the document includes identifying a set of one or more query-independent features in each of the plurality of lines of text in the document, and wherein determining a query-dependent relevance of each of the plurality of lines of text in the document includes identifying a set of one or more query-dependent features in each of the plurality of lines of text in the document.

14. A computer-implemented method of processing messages, performed on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors to perform the method, comprising: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, each conversation in the list of conversations being represented as a single row in the set of rows, the single row including conversation identifying information for the conversation and the sender list associated with the conversation; and wherein the sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation.

14. A computer-implemented method of processing messages, performed on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors to perform the method, comprising: receiving a plurality of messages directed to a particular user, each message having a unique message identifier; associating each of the plurality of messages with a respective conversation; associating with each conversation a sender list, the sender list identifying a set of senders of messages included in the conversation; and providing presentation information for displaying a list of conversations and their associated sender lists comprising a set of rows, each conversation in the list of conversations being represented as a single row in the set of rows, the single row including conversation identifying information for the conversation and the sender list associated with the conversation; and wherein the sender list of at least one respective conversation in the list of conversations identifies two or more distinct senders of messages in the respective conversation. 24. The method of claim 14 , wherein at least one row in the set of rows includes a recipient indicator that indicates whether the user is a primary recipient or secondary recipient of any message in the conversation.

27. A non-transitory computer-readable storage medium for building a trait model for essay evaluation, the computer-readable storage medium comprising computer executable instructions which, when executed, cause the computer system to execute steps comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files; and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model.

27. A non-transitory computer-readable storage medium for building a trait model for essay evaluation, the computer-readable storage medium comprising computer executable instructions which, when executed, cause the computer system to execute steps comprising: receiving at least one evaluated essay; identifying and extracting with a processor a plurality of features pertaining to one or more traits from the received at least one evaluated essay; wherein a trait comprises one or more features or feature sets and each feature set comprises one or more features; wherein the one or more traits comprise writing errors, discourse, or vocabulary usage; creating a plurality of vector files based upon the plurality of features; building the trait model for essay evaluation based upon the plurality of vector files; and evaluating the trait model, the evaluating including: mapping features of a new essay to the trait model by navigating a multi-branched decision tree, and wherein at each branch of the decision tree, a value associated with the features of the new essay is used to determine how to proceed through the trait model. 30. The non-transitory computer-readable storage medium of claim 27 , wherein the received at least one evaluated essay has been evaluated by a judge trained by an expert.

3. The method of claim 2 , further comprising generating a taxonomy of categories based on the category type.

3. The method of claim 2 , further comprising generating a taxonomy of categories based on the category type. 4. The method of claim 3 , further comprising: selecting one or more categories from the taxonomy; extracting a plurality of features for each category; and generating the user intent model by using the first plurality of user actions with respect to the extracted features.

9. The method of claim 7 , further comprising: comparing the discovered speakers to speaker models from pre-recording videos; and suggesting names of potential speakers if a match between the discovered speakers and the speaker models is below a predetermined threshold.

9. The method of claim 7 , further comprising: comparing the discovered speakers to speaker models from pre-recording videos; and suggesting names of potential speakers if a match between the discovered speakers and the speaker models is below a predetermined threshold. 10. The method of claim 9 , further comprising: reconciling the discovered speakers with an invitee list to generate an attendee list; determining if substantially all attendees in the attendee list spoke in the meeting recording; and determining the passive participants as those attendees who did not speak.

13. The method of claim 1 , wherein receiving captured text from a printed document further comprises: receiving information identifying a region of the printed document from which the captured text was captured; and determining the action at least in part on the received information related to the region.

13. The method of claim 1 , wherein receiving captured text from a printed document further comprises: receiving information identifying a region of the printed document from which the captured text was captured; and determining the action at least in part on the received information related to the region. 16. The method of claim 13 , wherein determining the action at least in part on the received information related to the region further comprises: combining actions determined from more than one region identified as comprising the captured information.

12. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining, by a voice action system, that a software application installed on a user device is compatible with one or more other voice actions; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the new voice action; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the one or more other voice actions; ranking, by the voice action system, the new voice action and the one or more other voice actions; biasing, by the voice action system, an automatic speech recognizer to prefer the identified one or more trigger terms of the new voice action over the trigger terms of the one or more other voice actions, wherein the automatic speech recognizer is biased based at least on the ranking; obtaining, by the voice action system, a transcription of an utterance generated by the biased automatic speech recognizer; determining, by the voice action system, that the transcription of the utterance generated by the biased automatic speech recognizer includes a particular trigger term included in the identified one or more trigger terms; and triggering, by the voice action system, execution of the new voice action based at least on determining that the transcription of the utterance generated by the biased automatic speech recognizer includes the particular trigger term.

12. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining, by a voice action system, that a software application installed on a user device is compatible with one or more other voice actions; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the new voice action; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the one or more other voice actions; ranking, by the voice action system, the new voice action and the one or more other voice actions; biasing, by the voice action system, an automatic speech recognizer to prefer the identified one or more trigger terms of the new voice action over the trigger terms of the one or more other voice actions, wherein the automatic speech recognizer is biased based at least on the ranking; obtaining, by the voice action system, a transcription of an utterance generated by the biased automatic speech recognizer; determining, by the voice action system, that the transcription of the utterance generated by the biased automatic speech recognizer includes a particular trigger term included in the identified one or more trigger terms; and triggering, by the voice action system, execution of the new voice action based at least on determining that the transcription of the utterance generated by the biased automatic speech recognizer includes the particular trigger term. 19. The system of claim 12 , wherein the biased automatic speech recognizer receives audio data corresponding to the utterance from the user device, and wherein the biased automatic speech recognizer generates the transcription of the utterance based on performing speech recognition on the audio data corresponding to the utterance.

1. A method of comparing a unit of streaming text data to an existing document collection, comprising: constructing a term-by-document matrix of the existing document collection; decomposing the term-by-document matrix into a term basis matrix, a weights matrix, and a document basis matrix; determining a multidimensional term subspace of the term basis matrix; computing a vector representation of the unit of streaming text data; transforming the vector representation into a projection into the predetermined multidimensional term subspace; calculating a relationship value indicative of a relationship between the vector representation and the predetermined multidimensional term subspace in real-time, wherein the relationship value is a residual vector that quantifies the difference between the vector representation of the streaming text data document and the subspace representing the original document collection; and appending the projection of the unit of streaming text data to the existing document collection represented by the predetermined multidimensional term subspace, the existing document collection being represented by a quantity of vectors corresponding to an equivalent quantity of documents in the existing document collection, the appending of the projection of the streaming text data to the existing document collection being performed without determining a new multidimensional term subspace and without adding additional terms not originally included in the term basis matrix, the appending being performed when it is determined that a relationship exists between the streaming text data and the predetermined multidimensional term subspace, wherein the relationship exists when the residual vector is less than a threshold.

1. A method of comparing a unit of streaming text data to an existing document collection, comprising: constructing a term-by-document matrix of the existing document collection; decomposing the term-by-document matrix into a term basis matrix, a weights matrix, and a document basis matrix; determining a multidimensional term subspace of the term basis matrix; computing a vector representation of the unit of streaming text data; transforming the vector representation into a projection into the predetermined multidimensional term subspace; calculating a relationship value indicative of a relationship between the vector representation and the predetermined multidimensional term subspace in real-time, wherein the relationship value is a residual vector that quantifies the difference between the vector representation of the streaming text data document and the subspace representing the original document collection; and appending the projection of the unit of streaming text data to the existing document collection represented by the predetermined multidimensional term subspace, the existing document collection being represented by a quantity of vectors corresponding to an equivalent quantity of documents in the existing document collection, the appending of the projection of the streaming text data to the existing document collection being performed without determining a new multidimensional term subspace and without adding additional terms not originally included in the term basis matrix, the appending being performed when it is determined that a relationship exists between the streaming text data and the predetermined multidimensional term subspace, wherein the relationship exists when the residual vector is less than a threshold. 5. The method of claim 1 , wherein the relationship value is based at least in part on an angle between the projection and the vector representation.

1. A method of web search by a search engine among rich media objects, the method comprising: maintaining, by a search engine for each of a plurality of users, a reputation score quantifying each user's activity of tagging rich media objects; counting a number of tags that include a particular searchable term, the particular searchable term among a plurality of searchable terms, the tags associated with a rich media object, the tag associations created by one or more of the plurality of users, the tags comprising text describing the rich media object, the text including the particular searchable term, the rich media object lacking a searchable textual element prior to the tag associations; calculating, by the search engine, a search result score for the particular searchable term included within tags of the rich media object, the search result score based on the number of tags associated with the rich media object that include the particular searchable term and the reputation scores of the users that associated the tags having the particular searchable term with the rich media object, the search result score specific to the particular searchable term, the rich media object having a distinct search result score for each of two or more searchable terms included in tags for the rich media object; and recording, by the search engine, in a primary search index, each search result score for each of the two or more searchable terms of the rich media object.

1. A method of web search by a search engine among rich media objects, the method comprising: maintaining, by a search engine for each of a plurality of users, a reputation score quantifying each user's activity of tagging rich media objects; counting a number of tags that include a particular searchable term, the particular searchable term among a plurality of searchable terms, the tags associated with a rich media object, the tag associations created by one or more of the plurality of users, the tags comprising text describing the rich media object, the text including the particular searchable term, the rich media object lacking a searchable textual element prior to the tag associations; calculating, by the search engine, a search result score for the particular searchable term included within tags of the rich media object, the search result score based on the number of tags associated with the rich media object that include the particular searchable term and the reputation scores of the users that associated the tags having the particular searchable term with the rich media object, the search result score specific to the particular searchable term, the rich media object having a distinct search result score for each of two or more searchable terms included in tags for the rich media object; and recording, by the search engine, in a primary search index, each search result score for each of the two or more searchable terms of the rich media object. 5. The method of claim 1 wherein maintaining, by a search engine for each of a plurality of users, a reputation score further comprises: identifying a malicious tag associated with a particular rich media object, the malicious tag including an inaccurate description of the particular rich media object intended to provide inaccurate search results for search requests having, as a search term, text included in the malicious tag; and decreasing the reputation score of users subsequently associating the same malicious tag to the particular rich media object.

1. A system, comprising: a processor configured to: parse a PDF file to extract script stream data embedded in the PDF file, wherein the PDF file is known to include malicious content; and determine whether to generate a signature associated with the PDF file based at least in part on at least a portion of the extracted script stream data: in the event that the signature associated with the PDF file is determined to be based at least in part on the at least portion of the extracted script stream data, automatically generate the signature associated with the PDF file based at least in part on the at least portion of the extracted script stream data, wherein the signature is configured to be matched against a potentially malicious PDF file; and in the event that the signature associated with the PDF file is determined not to be based at least in part on the at least portion of the extracted script stream data, automatically generate the signature associated with the PDF file from an identified cross-reference table from a plurality of cross-reference tables within the PDF file, wherein the identified cross-reference table is identified from the plurality of cross-reference tables based at least in part on a position of the identified cross-reference table relative to respective positions associated with one or more cross-reference tables other than the identified cross-reference table from the plurality of cross-reference tables; and a memory coupled to the processor and configured to provide the processor with instructions.

1. A system, comprising: a processor configured to: parse a PDF file to extract script stream data embedded in the PDF file, wherein the PDF file is known to include malicious content; and determine whether to generate a signature associated with the PDF file based at least in part on at least a portion of the extracted script stream data: in the event that the signature associated with the PDF file is determined to be based at least in part on the at least portion of the extracted script stream data, automatically generate the signature associated with the PDF file based at least in part on the at least portion of the extracted script stream data, wherein the signature is configured to be matched against a potentially malicious PDF file; and in the event that the signature associated with the PDF file is determined not to be based at least in part on the at least portion of the extracted script stream data, automatically generate the signature associated with the PDF file from an identified cross-reference table from a plurality of cross-reference tables within the PDF file, wherein the identified cross-reference table is identified from the plurality of cross-reference tables based at least in part on a position of the identified cross-reference table relative to respective positions associated with one or more cross-reference tables other than the identified cross-reference table from the plurality of cross-reference tables; and a memory coupled to the processor and configured to provide the processor with instructions. 6. The system of claim 1 , wherein the processor is further configured to de-obfuscate the PDF file.

1. A system comprising: a user interface for displaying a web document to a user; a processor in communication with the user interface and coupled to computer readable storage media storing instructions adapted to be executed by the processor; a scanning component implemented by the processor to receive the web document for display on the user interface and scan content of the web document to select candidate phrases comprising at least one word in the web document; an analysis component implemented by the processor to: access at least one of a search engine query log file or a search engine cache containing a plurality of search queries received from a plurality of different users of a search engine; identify, from the plurality of search queries received from the plurality of different users, query frequency information comprising a list of words frequently submitted as the search queries to the search engine by the plurality of different users of the search engine over a defined period of time; extract at least one phrase comprising at least one word from the web document based, at least in part, on a comparison of the candidate phrases with the list of words frequently submitted as the search queries to the search engine by the plurality of different users; generate at least one query based upon the at least one phrase extracted; and provide the at least one query based upon the at least one phrase to an advertising system in communication with the processor; and a display component to display at least one advertisement on the user interface in conjunction with display of the content of the web document, the at least one advertisement being received by the processor from the advertising system in response to the at least one query provided to the advertising system.

1. A system comprising: a user interface for displaying a web document to a user; a processor in communication with the user interface and coupled to computer readable storage media storing instructions adapted to be executed by the processor; a scanning component implemented by the processor to receive the web document for display on the user interface and scan content of the web document to select candidate phrases comprising at least one word in the web document; an analysis component implemented by the processor to: access at least one of a search engine query log file or a search engine cache containing a plurality of search queries received from a plurality of different users of a search engine; identify, from the plurality of search queries received from the plurality of different users, query frequency information comprising a list of words frequently submitted as the search queries to the search engine by the plurality of different users of the search engine over a defined period of time; extract at least one phrase comprising at least one word from the web document based, at least in part, on a comparison of the candidate phrases with the list of words frequently submitted as the search queries to the search engine by the plurality of different users; generate at least one query based upon the at least one phrase extracted; and provide the at least one query based upon the at least one phrase to an advertising system in communication with the processor; and a display component to display at least one advertisement on the user interface in conjunction with display of the content of the web document, the at least one advertisement being received by the processor from the advertising system in response to the at least one query provided to the advertising system. 9. The system according to claim 1 , wherein the at least one query is automatically displayed on the user interface in conjunction with display of the content of the web document, and wherein the at least one query is provided to the advertisement system and the at least one advertisement is displayed on the user interface in conjunction with the display of the content of the web document following user selection of the at least one query displayed on the user interface.

1. A method of determining a predictive model for discourse functions comprising the steps of: determining a training corpus of speech utterances; determining discourse functions associated with speech utterances in the training corpus, the discourse functions being determined automatically based on a theory of discourse analysis; determining prosodic features associated with the speech utterances in the training corpus; and determining a predictive model of discourse functions by associating the prosodic features determined from the speech utterances in the training corpus with the discourse functions determined from the speech utterances in the training corpus, wherein the predictive model of discourse functions is used to predict from prosodic features of a specific recognized speech, a likelihood that speech utterances of the specific recognized speech reflect a specific discourse function, and wherein the predictive model of discourse functions is used to predict, based, at least in part, on the prosodic features, a likelihood of a first portion of a speech utterance being associated with a command directed at an application and a second portion of the speech utterance being associated with content being provided to the application.

1. A method of determining a predictive model for discourse functions comprising the steps of: determining a training corpus of speech utterances; determining discourse functions associated with speech utterances in the training corpus, the discourse functions being determined automatically based on a theory of discourse analysis; determining prosodic features associated with the speech utterances in the training corpus; and determining a predictive model of discourse functions by associating the prosodic features determined from the speech utterances in the training corpus with the discourse functions determined from the speech utterances in the training corpus, wherein the predictive model of discourse functions is used to predict from prosodic features of a specific recognized speech, a likelihood that speech utterances of the specific recognized speech reflect a specific discourse function, and wherein the predictive model of discourse functions is used to predict, based, at least in part, on the prosodic features, a likelihood of a first portion of a speech utterance being associated with a command directed at an application and a second portion of the speech utterance being associated with content being provided to the application. 3. The method of claim 1 , in which the predictive models are determined based on at least one of: machine learning, rules.

11. A method of providing information related to a broadcast program, the method comprising: detecting at least one object from a scene by an object detector; generating a keyword including a name and information relating to a meaning of the object; setting a scene section comprising a group of the scenes that deal with a same subject between the scenes displayed on a display by using the keyword that is generated based on the at least one object from the scenes, the scene section comprising a group of the scenes that deal with a same subject between the scenes displayed on the display; requesting searching of related information associated with the object by using the keyword and receiving the searched related information; and synchronizing the received related information along with the scene section comprising the group of the scenes that deal with the same subject between the scenes displayed on the display and providing the related information synchronized with the scene section, wherein the setting of the scene section comprises setting as the scene section a group of scenes between which an amount of preserved keywords is equal to or greater than a threshold value, the preserved keywords being defined by a number of keywords that exist in common between keywords generated from a first scene and keywords generated from a second scene, and wherein the generating of the keyword comprises determining an object name which corresponds to the object and a category to which the object name belongs by using an object name dictionary in which a plurality of object names are individually mapped to categories, thereby generating the keyword including the object name and the category.

11. A method of providing information related to a broadcast program, the method comprising: detecting at least one object from a scene by an object detector; generating a keyword including a name and information relating to a meaning of the object; setting a scene section comprising a group of the scenes that deal with a same subject between the scenes displayed on a display by using the keyword that is generated based on the at least one object from the scenes, the scene section comprising a group of the scenes that deal with a same subject between the scenes displayed on the display; requesting searching of related information associated with the object by using the keyword and receiving the searched related information; and synchronizing the received related information along with the scene section comprising the group of the scenes that deal with the same subject between the scenes displayed on the display and providing the related information synchronized with the scene section, wherein the setting of the scene section comprises setting as the scene section a group of scenes between which an amount of preserved keywords is equal to or greater than a threshold value, the preserved keywords being defined by a number of keywords that exist in common between keywords generated from a first scene and keywords generated from a second scene, and wherein the generating of the keyword comprises determining an object name which corresponds to the object and a category to which the object name belongs by using an object name dictionary in which a plurality of object names are individually mapped to categories, thereby generating the keyword including the object name and the category. 12. The method of claim 11 , wherein the generating of the keyword comprises determining the category by analyzing context of a part where the keyword appears.

5. The apparatus according to claim 1 or 4 , wherein the function generation unit includes: a selecting unit configured to select one component from a set of a plurality of components of the feature vector; a dividing unit configured to divide the group into two groups using the selected component as a border; a first operation unit configured to calculate a first quantization error when quantizing one of the divided set of the components into quantization number 1; a second operation unit configured to calculate a second quantization error when quantizing the other of the divided set of the components into quantization number n based on the quantization threshold and the first quantization error calculated on quantization number n−1; a third operation unit configured to add the first quantization error and the second quantization error to calculate a quantization error of the quantization number n+1; and a fourth operation unit configured to calculate a division value of the quantization threshold corresponding to a quantization error of the quantization number n+1.

5. The apparatus according to claim 1 or 4 , wherein the function generation unit includes: a selecting unit configured to select one component from a set of a plurality of components of the feature vector; a dividing unit configured to divide the group into two groups using the selected component as a border; a first operation unit configured to calculate a first quantization error when quantizing one of the divided set of the components into quantization number 1; a second operation unit configured to calculate a second quantization error when quantizing the other of the divided set of the components into quantization number n based on the quantization threshold and the first quantization error calculated on quantization number n−1; a third operation unit configured to add the first quantization error and the second quantization error to calculate a quantization error of the quantization number n+1; and a fourth operation unit configured to calculate a division value of the quantization threshold corresponding to a quantization error of the quantization number n+1. 7. The apparatus according to claim 5 , wherein the function generation unit arranges a value of each component of the input feature vector in an ascending order based on a magnitude of each value.

1. A method for business context oriented request processing, the method comprising: establishing a stack of business context instances in a thread, each for a context type; receiving an object request for an object in an object request broker (ORB); passing the request from the ORB to an enterprise Java bean (EJB) container, the EJB container identifying a type of the object request, determining if a business context data service collaborator is registered for the object and calling the business context data service, the business context data service establishing a business context instance in the stack on the thread for the object; and, upon the EJB completing processing of the object request, calling by the EJB container a post-invocation collaborator to remove one of the context instances corresponding to the type from stack in the thread by clearing in the thread a context identifier for the business context instance and restoring the business context instance corresponding to the context identifier.

1. A method for business context oriented request processing, the method comprising: establishing a stack of business context instances in a thread, each for a context type; receiving an object request for an object in an object request broker (ORB); passing the request from the ORB to an enterprise Java bean (EJB) container, the EJB container identifying a type of the object request, determining if a business context data service collaborator is registered for the object and calling the business context data service, the business context data service establishing a business context instance in the stack on the thread for the object; and, upon the EJB completing processing of the object request, calling by the EJB container a post-invocation collaborator to remove one of the context instances corresponding to the type from stack in the thread by clearing in the thread a context identifier for the business context instance and restoring the business context instance corresponding to the context identifier. 5. The method of claim 1 , wherein the business context comprises any of a solution context, a task context, a role context and a data context.

2. A method for implementing an automated assistant on one or more computing devices having one or more processors and memory, the method comprising: at the one or more computing devices: invoking the automated assistant; causing a first output to be displayed, wherein the first output comprises a plurality of core competencies of the automated assistant and an example of a natural language input for invoking each of the plurality of core competencies; at an input device, receiving user input; interpreting the received user input to derive a representation of user intent; identifying at least one task based at least in part on the derived representation of user intent; calling at least one service for performing the identified task; and causing a second output to be displayed based on data received from the at least one called service; wherein the first output is displayed prior to receiving the user input.

2. A method for implementing an automated assistant on one or more computing devices having one or more processors and memory, the method comprising: at the one or more computing devices: invoking the automated assistant; causing a first output to be displayed, wherein the first output comprises a plurality of core competencies of the automated assistant and an example of a natural language input for invoking each of the plurality of core competencies; at an input device, receiving user input; interpreting the received user input to derive a representation of user intent; identifying at least one task based at least in part on the derived representation of user intent; calling at least one service for performing the identified task; and causing a second output to be displayed based on data received from the at least one called service; wherein the first output is displayed prior to receiving the user input. 22. The method of claim 2 , wherein one of the plurality of core competencies is searching for an entertainment event.

15. A system for indexing documents comprising: a processor; and a computer memory operatively coupled to the processor, the computer memory including: computer readable program code configured to index a document written in one or more natural languages, wherein indexing includes: applying language-specific rules of one of the one or more natural languages to content of the document; and generating a number of tokens from the content of the document that comply with the language-specific rules; computer readable program code configured to determine a success metric based on the generated number of tokens that complied with the language-specific rules; computer readable program code configured to compare the success metric to a threshold value, wherein the threshold value indicates a predetermined amount of content in the document designating a multi-lingual document; computer readable program code configured to identify the document as a multi-lingual document based upon the comparing; and computer readable program code configured to queue the document for multi-lingual indexing in response to identifying the document as a multi-lingual document.

15. A system for indexing documents comprising: a processor; and a computer memory operatively coupled to the processor, the computer memory including: computer readable program code configured to index a document written in one or more natural languages, wherein indexing includes: applying language-specific rules of one of the one or more natural languages to content of the document; and generating a number of tokens from the content of the document that comply with the language-specific rules; computer readable program code configured to determine a success metric based on the generated number of tokens that complied with the language-specific rules; computer readable program code configured to compare the success metric to a threshold value, wherein the threshold value indicates a predetermined amount of content in the document designating a multi-lingual document; computer readable program code configured to identify the document as a multi-lingual document based upon the comparing; and computer readable program code configured to queue the document for multi-lingual indexing in response to identifying the document as a multi-lingual document. 18. The system of claim 15 wherein the computer readable program code configured to queue the document for multi-lingual indexing comprises computer readable program code configured to queue the document for immediate processing.

1. A computer-implemented method, comprising: generating a generic relevance function based on training data from a plurality of first users and that is not based on a specific context associated with any of the plurality of first users; storing the generic relevance function in a machine-readable storage medium; collecting context-specific training data, wherein the context-specific training data is based on a plurality of second users and a specific context associated with the plurality of second users; adapting the generic relevance function to produce a context-specific relevance function, wherein the adapting comprises using the generic relevance function and the context-specific training data as input to a machine learning technique to generate the context-specific relevance function; after producing the context-specific relevance function, receiving a query from a particular user; processing the query to identify results of the query; identifying a particular context of the query or of the particular user; selecting, based on the particular context, a particular context-specific relevance function from among a plurality of context-specific relevance functions; using the particular context-specific relevance function to determine relevance of each of the results only in response to determining that the particular context is the same as the specific context upon which the particular context-specific relevance function is based; based on the particular context-specific relevance function, assigning a relevance value to each of the results; and sending, to the particular user, at least a subset of the results to be displayed; wherein the method is performed by one or more computing devices.

1. A computer-implemented method, comprising: generating a generic relevance function based on training data from a plurality of first users and that is not based on a specific context associated with any of the plurality of first users; storing the generic relevance function in a machine-readable storage medium; collecting context-specific training data, wherein the context-specific training data is based on a plurality of second users and a specific context associated with the plurality of second users; adapting the generic relevance function to produce a context-specific relevance function, wherein the adapting comprises using the generic relevance function and the context-specific training data as input to a machine learning technique to generate the context-specific relevance function; after producing the context-specific relevance function, receiving a query from a particular user; processing the query to identify results of the query; identifying a particular context of the query or of the particular user; selecting, based on the particular context, a particular context-specific relevance function from among a plurality of context-specific relevance functions; using the particular context-specific relevance function to determine relevance of each of the results only in response to determining that the particular context is the same as the specific context upon which the particular context-specific relevance function is based; based on the particular context-specific relevance function, assigning a relevance value to each of the results; and sending, to the particular user, at least a subset of the results to be displayed; wherein the method is performed by one or more computing devices. 25. The method of claim 1 , wherein selecting is not based on the query.

39. The system of claim 38 , wherein said subjective user state data acquisition module configured to acquire subjective user state data, the acquired subjective user state data including data indicating incidence of the at least one subjective user state associated with the user comprises: a subjective user state data reception module configured to receive the subjective user state data including the data indicating incidence of the at least one subjective user state associated with the user.

39. The system of claim 38 , wherein said subjective user state data acquisition module configured to acquire subjective user state data, the acquired subjective user state data including data indicating incidence of the at least one subjective user state associated with the user comprises: a subjective user state data reception module configured to receive the subjective user state data including the data indicating incidence of the at least one subjective user state associated with the user. 41. The system of claim 39 , wherein said subjective user state data reception module configured to receive the subjective user state data including the data indicating incidence of the at least one subjective user state associated with the user comprises: a subjective user state data reception module configured to receive, via one or more status reports, the subjective user state data.

8. A system comprising: one or more computers operable to perform operations comprising: receiving an image as a query from a user device associated with a user; deriving a textual query corresponding to the received image, wherein deriving the textual query for the image includes: using the image to determine a group of images that are similar to the received image; for each similar image of the group of similar images, identifying one or more n-grams associated with the similar image; and selecting one or more of the identified n-grams as a textual query for the received image; obtaining search results responsive to the textual query; and providing for presentation on the user device one or more of the obtained search results.

8. A system comprising: one or more computers operable to perform operations comprising: receiving an image as a query from a user device associated with a user; deriving a textual query corresponding to the received image, wherein deriving the textual query for the image includes: using the image to determine a group of images that are similar to the received image; for each similar image of the group of similar images, identifying one or more n-grams associated with the similar image; and selecting one or more of the identified n-grams as a textual query for the received image; obtaining search results responsive to the textual query; and providing for presentation on the user device one or more of the obtained search results. 13. The system of claim 8 , where the search results are image search results comprising a group of one or more images.

1. A method of decoding of syntactic elements of a data stream, wherein: before beginning of decoding of the data stream, cells of all context models are initialized with predefined values, so that each context model contains in each cell thereof data on a probability and a counter of a context occurrence number, a number of cells stored in each context model is selected to be not less than a number of all possible states of context elements associated with a respective context model, and in the process of decoding of at least a portion of bits of the data stream: a group of context models is selected, said group of context models comprising at least two context models of different size; values of at least two context elements associated with the selected group of context models are calculated; selection of the cells in the context models is carried out by means of values of the context elements associated with the respective context model; one context model is selected from the group of context models using values of individual counters of a context occurrence number stored in the selected cells; the data on the probability is extracted from the selected cell of the selected context model, said data being used for entropy decoding of a current bit in the data stream, and/or for selecting a mode of direct extraction of decoded bits from the data stream; data in the selected cell of the selected context model as well as in all the context models of the group of context models, which have a size greater than that of the selected context model, is updated; and a procedure of probability inheritance from the selected context model is carried out in respect of the selected cells of those context models of the group of context models for which predefined inheritance criteria are met.

1. A method of decoding of syntactic elements of a data stream, wherein: before beginning of decoding of the data stream, cells of all context models are initialized with predefined values, so that each context model contains in each cell thereof data on a probability and a counter of a context occurrence number, a number of cells stored in each context model is selected to be not less than a number of all possible states of context elements associated with a respective context model, and in the process of decoding of at least a portion of bits of the data stream: a group of context models is selected, said group of context models comprising at least two context models of different size; values of at least two context elements associated with the selected group of context models are calculated; selection of the cells in the context models is carried out by means of values of the context elements associated with the respective context model; one context model is selected from the group of context models using values of individual counters of a context occurrence number stored in the selected cells; the data on the probability is extracted from the selected cell of the selected context model, said data being used for entropy decoding of a current bit in the data stream, and/or for selecting a mode of direct extraction of decoded bits from the data stream; data in the selected cell of the selected context model as well as in all the context models of the group of context models, which have a size greater than that of the selected context model, is updated; and a procedure of probability inheritance from the selected context model is carried out in respect of the selected cells of those context models of the group of context models for which predefined inheritance criteria are met. 12. The method of decoding according to claim 1 , wherein in the process of decoding: at least one decoded syntactic element is debinarized, and at least one context element is calculated using values of the already decoded bits of a binarized string.

8. The system of claim 1 , further comprising a criteria component for providing criteria that is processed by the data selection component as a basis for selecting the subset of correlated data.

8. The system of claim 1 , further comprising a criteria component for providing criteria that is processed by the data selection component as a basis for selecting the subset of correlated data. 9. The system of claim 8 , wherein the criteria component detects display capabilities of a device, and the data selection component selects the subset of correlated data based on the display capabilities of the device.

1. An extended online analytical apparatus for one or more data sources wherein each data source has a data format, comprising: an aggregator that aggregates one or more pieces of data from the one or more data sources to generate aggregated pieces of data; a virtual schema generator that generates an XML-based virtual schema from the aggregated pieces of data without a data warehouse and without a data warehouse data model, wherein the virtual schema is a multidimensional data model generated based on the data format of the one or more data sources; and an analytical cube generator that generates an eXtensible on-line analytical processing (XOLAP) cube by executing commands from a declarative language against the virtual schema.

1. An extended online analytical apparatus for one or more data sources wherein each data source has a data format, comprising: an aggregator that aggregates one or more pieces of data from the one or more data sources to generate aggregated pieces of data; a virtual schema generator that generates an XML-based virtual schema from the aggregated pieces of data without a data warehouse and without a data warehouse data model, wherein the virtual schema is a multidimensional data model generated based on the data format of the one or more data sources; and an analytical cube generator that generates an eXtensible on-line analytical processing (XOLAP) cube by executing commands from a declarative language against the virtual schema. 5. The apparatus of claim 1 further comprising an indexing engine and a scheduler that update the virtual schema when new pieces of data are received by the aggregator.

2. The method of claim 1 wherein the protocol comprises a HyperText Markup Language (HTML)-compliant protocol.

2. The method of claim 1 wherein the protocol comprises a HyperText Markup Language (HTML)-compliant protocol. 4. The method of claim 2 wherein the input field comprises a form field.

10. The mechanism of claim 1 wherein the group stores a persistent record indicating a current location for each mobile agent object within such group.

10. The mechanism of claim 1 wherein the group stores a persistent record indicating a current location for each mobile agent object within such group. 11. The mechanism of claim 10 wherein the group stores a persistent record indicating a current state for each mobile agent object within such group.

9. A non-transitory computer-readable storage medium containing instructions that, when executed by one or more processors, perform an operation for creating an aggregate training data set corresponding to a document type, the operation comprising: for each document of a document type in a set of documents: receiving the document type, wherein the document type identifies a type of content that is common to a plurality of documents of the set of documents; receiving input corresponding to a text sample in the document; receiving an image of the text sample in the document; for each of a plurality of candidate presentation styles: training an OCR processing engine using a training data set corresponding to the candidate presentation style; identifying text in the image of the text sample; producing OCR processing results for the document and the candidate presentation style using the OCR processing engine as trained; comparing the OCR processing results to the input corresponding to the text sample; and calculating a score for the candidate presentation style based on the comparison; ranking the candidate presentation styles based on the score calculated for each candidate presentation style; selecting a candidate presentation style for the document based on the ranking; and storing the selected candidate presentation style for the document with respect to the document type; and combining the training data set corresponding to the selected candidate presentation style for each document of the document type in the set of documents to create an aggregate training data set for the document type.

9. A non-transitory computer-readable storage medium containing instructions that, when executed by one or more processors, perform an operation for creating an aggregate training data set corresponding to a document type, the operation comprising: for each document of a document type in a set of documents: receiving the document type, wherein the document type identifies a type of content that is common to a plurality of documents of the set of documents; receiving input corresponding to a text sample in the document; receiving an image of the text sample in the document; for each of a plurality of candidate presentation styles: training an OCR processing engine using a training data set corresponding to the candidate presentation style; identifying text in the image of the text sample; producing OCR processing results for the document and the candidate presentation style using the OCR processing engine as trained; comparing the OCR processing results to the input corresponding to the text sample; and calculating a score for the candidate presentation style based on the comparison; ranking the candidate presentation styles based on the score calculated for each candidate presentation style; selecting a candidate presentation style for the document based on the ranking; and storing the selected candidate presentation style for the document with respect to the document type; and combining the training data set corresponding to the selected candidate presentation style for each document of the document type in the set of documents to create an aggregate training data set for the document type. 13. The non-transitory computer-readable storage medium of claim 9 , wherein calculating a score for the candidate presentation style based on the comparison comprises: calculating a Levenshtein distance between the OCR processing results and the input corresponding to the text sample.

6. One or more computer-readable storage media containing executable instructions that, when executed, implement the following steps: establishing communication with a base computing device; during the communication: receiving, on a mobile electronic device, a voice command, wherein the mobile electronic device is separate from the base computing device; causing the base computing device to perform at least a portion of processing associated with the voice command, wherein to perform at least a portion of the processing comprises performing speech-to-text translation on the voice command to provide translated text that includes a keyword; manipulating in real time one or more electronic files stored on the base computing device in response to the voice command, wherein the manipulating comprises selection of an individual electronic file of the one or more electronic files stored on the base computing device based at least in part on the keyword, wherein the electronic files comprise digital photo image files; directing, from the mobile electronic device and in real time a presentation of the one or more electronic files by the base computing device, and wherein the directing is performed based at least in part on one or both of the voice command or at least one other voice command received on the mobile electronic device; and sending image resolution data from the mobile electronic device to the base computing device that is configured to cause the base computing device to adjust a resolution of at least one of the at least one digital image file or another digital image file of a plurality of locally stored digital image files.

6. One or more computer-readable storage media containing executable instructions that, when executed, implement the following steps: establishing communication with a base computing device; during the communication: receiving, on a mobile electronic device, a voice command, wherein the mobile electronic device is separate from the base computing device; causing the base computing device to perform at least a portion of processing associated with the voice command, wherein to perform at least a portion of the processing comprises performing speech-to-text translation on the voice command to provide translated text that includes a keyword; manipulating in real time one or more electronic files stored on the base computing device in response to the voice command, wherein the manipulating comprises selection of an individual electronic file of the one or more electronic files stored on the base computing device based at least in part on the keyword, wherein the electronic files comprise digital photo image files; directing, from the mobile electronic device and in real time a presentation of the one or more electronic files by the base computing device, and wherein the directing is performed based at least in part on one or both of the voice command or at least one other voice command received on the mobile electronic device; and sending image resolution data from the mobile electronic device to the base computing device that is configured to cause the base computing device to adjust a resolution of at least one of the at least one digital image file or another digital image file of a plurality of locally stored digital image files. 11. One or more computer-readable storage media as recited in claim 6 , wherein the presentation is achieved on a remote display device that is separate from the mobile electronic device.

1. A method comprising: receiving, by a server computer from a user that is customizing a custom product, a first attribute value that defines an attribute of the custom product; in response to receiving the first attribute value, generating, by the server computer based at least in part on the first attribute value and one or more other attributes of the custom product, a particular key-value expression that includes a plurality of key attributes and values; matching, by the server computer, the particular key-value expression to a set of one or more render files stored in volatile or non-volatile storage; based on the set of one or more render files, rendering an image of the custom product.

1. A method comprising: receiving, by a server computer from a user that is customizing a custom product, a first attribute value that defines an attribute of the custom product; in response to receiving the first attribute value, generating, by the server computer based at least in part on the first attribute value and one or more other attributes of the custom product, a particular key-value expression that includes a plurality of key attributes and values; matching, by the server computer, the particular key-value expression to a set of one or more render files stored in volatile or non-volatile storage; based on the set of one or more render files, rendering an image of the custom product. 8. The method of claim 1 , further comprising determining a view for displaying the custom product based on the particular key-value expression.

15. The method of claim 9 , wherein determining the one or more clusters of application state records for each application state record in the consideration set comprises: determining the function identifier of the application state record; and searching a subset of the plurality of cluster records using the function identifier of the application state record to identify the cluster records in the subset of the plurality of cluster records, the subset of the plurality of cluster records being selected based on having been clustered according to one or more sets of feature types.

15. The method of claim 9 , wherein determining the one or more clusters of application state records for each application state record in the consideration set comprises: determining the function identifier of the application state record; and searching a subset of the plurality of cluster records using the function identifier of the application state record to identify the cluster records in the subset of the plurality of cluster records, the subset of the plurality of cluster records being selected based on having been clustered according to one or more sets of feature types. 16. The method of claim 15 , wherein determining the result score for each application state record in the consideration set comprises: including the cluster identifier of the identified cluster records in a feature vector corresponding to the application state record, the feature vector defining a plurality of features of the application state record; and feeding the feature vector into a machine-learned scoring module, the machine-learned scoring model determining the result score of the application state record based on the feature vector.

19. The computer program product of claim 15 , wherein the expected answer is a hypothesis answer or a mean answer of a totality of answers received from the experts with respect to a sent question, and wherein the second and third program instructions are further to: determine that an answer received from a sixth expert has a degree of correlation to the expected answer that is outside of an acceptable variance; and label the sixth expert an outlier expert; or decrease a value metric score of the sixth expert.

19. The computer program product of claim 15 , wherein the expected answer is a hypothesis answer or a mean answer of a totality of answers received from the experts with respect to a sent question, and wherein the second and third program instructions are further to: determine that an answer received from a sixth expert has a degree of correlation to the expected answer that is outside of an acceptable variance; and label the sixth expert an outlier expert; or decrease a value metric score of the sixth expert. 20. The computer program product of claim 19 , wherein the second program instructions are further to: determine that a question has been satisfied with a satisfactory answer upon receiving a total number of responses that meets a threshold number of responses; or determine that a question has been satisfied with a satisfactory answer if an answer to a question is within a threshold variance of correlation to the expected answer.

16. A machine-readable medium comprising instructions for classifying input text to a target classification system having two or more target classes, the instructions comprising: a first set of instructions for determining first and second scores based on the input text and one of the target classes, wherein the first score is based on similarity of a set of one or more non-target classes associated with the input text and a set of one or more non-target classes associated with the one target class; and wherein the second score is based on probability of the one target class given at least a portion of the input text; a second set of instructions for determining a composite score based on a linear combination of the first and second scores; and a third set of instructions for comparing the composite score to a decision threshold.

16. A machine-readable medium comprising instructions for classifying input text to a target classification system having two or more target classes, the instructions comprising: a first set of instructions for determining first and second scores based on the input text and one of the target classes, wherein the first score is based on similarity of a set of one or more non-target classes associated with the input text and a set of one or more non-target classes associated with the one target class; and wherein the second score is based on probability of the one target class given at least a portion of the input text; a second set of instructions for determining a composite score based on a linear combination of the first and second scores; and a third set of instructions for comparing the composite score to a decision threshold. 19. The medium of claim 16 , further comprising instructions for: classifying or recommending classification of, for one or more of the target classes, the input text to the target class based on the composite score and the decision threshold; and updating the decision threshold for one of the target classes based on acceptance or rejection of recommended classifications of the input text.

4. The method of claim 1 wherein the first in-vehicle console has a dock that allows at least one external device to interoperate with the console.

4. The method of claim 1 wherein the first in-vehicle console has a dock that allows at least one external device to interoperate with the console. 5. The method of claim 4 wherein the at least one external device is selected from a group consisting of a mobile phone, a portable MP3 player, a global positioning system, a personal data assistant, a signature capture device, a computing tablet, a notebook computer, a DVD player, a video gaming unit, a digital camera, and a portable storage device.

1. A computer-implemented method of facilitating training of a computer to recognize a computer user's handwriting comprising the steps of: (a) receiving, by a computing system configured to facilitate computer recognition of user's handwriting, handwriting samples of at least one character written by the user, the samples comprising at least one sample of the character being provided as the beginning character among a plurality of other characters, at least one sample of the character being provided in the middle of a plurality of other of characters, and at least one sample of the letter being provided as the ending character among a plurality of characters; (b) extracting, by the computing system, a plurality of control points from the samples, wherein the control points represent the shape of the character; (c) determining, by the computing system, the vertical position of the character in relation to a baseline comprising the step of determining the distance from the bottom of the character to a baseline; and (d) normalizing, by the computing system, the at least one sample of at least one character.

1. A computer-implemented method of facilitating training of a computer to recognize a computer user's handwriting comprising the steps of: (a) receiving, by a computing system configured to facilitate computer recognition of user's handwriting, handwriting samples of at least one character written by the user, the samples comprising at least one sample of the character being provided as the beginning character among a plurality of other characters, at least one sample of the character being provided in the middle of a plurality of other of characters, and at least one sample of the letter being provided as the ending character among a plurality of characters; (b) extracting, by the computing system, a plurality of control points from the samples, wherein the control points represent the shape of the character; (c) determining, by the computing system, the vertical position of the character in relation to a baseline comprising the step of determining the distance from the bottom of the character to a baseline; and (d) normalizing, by the computing system, the at least one sample of at least one character. 6. The computer-implemented method of claim 1 , further comprising the step of: (e) prior to normalization, categorizing, by the computing system, at least one character into a group selected from the group consisting of: ascenders, descenders, middle zone, multi-zone, and equivalents thereof.

56. A method of indexing and searching timed media files, as recited in claim 25 , further comprising the step of calculating a centrality number for at least one occurrence of at least one information representation contained within the timed media file.

56. A method of indexing and searching timed media files, as recited in claim 25 , further comprising the step of calculating a centrality number for at least one occurrence of at least one information representation contained within the timed media file. 57. A method of indexing and searching timed media files, as recited in claim 56 , wherein said processing of language contained within the timed media file includes segmenting said language into sentences; and said calculation of a centrality number of at least one occurrence of at least one information representation is based on the position of said occurrence within the grammatical structure of the sentence that contains the occurrence.