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1. A method implemented by a data processing apparatus, comprising: receiving an original query from a user device, the query including original query terms; receiving data identifying a set of web page resources that are determined to be responsive to the original query, each web page resource being a web page and identified by a corresponding URL address; determining, for the original query, a resource quality measure that is a measure of quality of the set of web page resources determined to be responsive to the original query; in response to determining that the resource quality measure does not meeting a resource quality measure threshold: determining, for each original query term of the query, a respective quality measure for the original query term, wherein each respective quality measure determined for an original query term is a quality measure that is different from the resource quality measure determined for the query; determining that an original query term of the original query term is a potentially inaccurate term based on the respective quality measure not meeting a respective quality measure threshold, and in response to determining that the original query term of the original query is a potentially inaccurate term: generating derivative queries from the original query, each derivative query not including the potentially inaccurate term; for each of the derivative queries, submitting the derivative query for a search of a resource corpus index of resources and receiving data identifying a respective set of resources that are determined to be responsive to the derivative query, wherein each resource is a web page resource hosted by a server and having a corresponding resource address; determining a corrected term that is different from the potentially inaccurate term based on the identified resources responsive to each of the one or more derivative queries, wherein the corrected term is determined independent of a set of resources identified as being responsive to the original query; generating a corrected query that that includes and the corrected term substituted for the potentially inaccurate term; performing a search operation that uses the corrected query as input; and providing results of the search operation to the user device in response to the original query.

1. A method implemented by a data processing apparatus, comprising: receiving an original query from a user device, the query including original query terms; receiving data identifying a set of web page resources that are determined to be responsive to the original query, each web page resource being a web page and identified by a corresponding URL address; determining, for the original query, a resource quality measure that is a measure of quality of the set of web page resources determined to be responsive to the original query; in response to determining that the resource quality measure does not meeting a resource quality measure threshold: determining, for each original query term of the query, a respective quality measure for the original query term, wherein each respective quality measure determined for an original query term is a quality measure that is different from the resource quality measure determined for the query; determining that an original query term of the original query term is a potentially inaccurate term based on the respective quality measure not meeting a respective quality measure threshold, and in response to determining that the original query term of the original query is a potentially inaccurate term: generating derivative queries from the original query, each derivative query not including the potentially inaccurate term; for each of the derivative queries, submitting the derivative query for a search of a resource corpus index of resources and receiving data identifying a respective set of resources that are determined to be responsive to the derivative query, wherein each resource is a web page resource hosted by a server and having a corresponding resource address; determining a corrected term that is different from the potentially inaccurate term based on the identified resources responsive to each of the one or more derivative queries, wherein the corrected term is determined independent of a set of resources identified as being responsive to the original query; generating a corrected query that that includes and the corrected term substituted for the potentially inaccurate term; performing a search operation that uses the corrected query as input; and providing results of the search operation to the user device in response to the original query. 9. The method of claim 1 , wherein determining that a term of the original query meets an inaccuracy criterion comprises determining that the term is an instance of a class of related terms, wherein the class of related terms are terms that are determined to be commonly confused terms; further comprising selecting each of the other terms that belong to the class as a candidate correction term; and generating one or more derivative queries from the original query comprises generating, for each of the candidate correction term, a derivative query that includes only the terms of the original query that are not the potentially inaccurate term and the candidate correction term.

3. The computer-implemented method of claim 2 further comprising adding a weighted value of the video parent-topic rank to a respective topic.

3. The computer-implemented method of claim 2 further comprising adding a weighted value of the video parent-topic rank to a respective topic. 4. The computer-implemented method of claim 3 , wherein: said plurality of keywords are collected from a plurality of dynamic data sources including a website providing reference information and a personalized data source associated with use of a personal computing device, wherein keywords collected from the personalized data source include video metadata information associated with a viewing history of video content accessed by the personal computing device, and wherein keywords collected from the website include keywords extracted from content available on the website related to first video topic; and a keyword appearing in only one dynamic data source is assigned to a first set to be removed during filtering.

3. A voice recognition apparatus to claim 2, wherein said second means includes at least one word net, each of said word nets being connected to a corresponding event net and for outputting said value, corresponding to said similarity in said specific word with respect to said input utterance.

3. A voice recognition apparatus to claim 2, wherein said second means includes at least one word net, each of said word nets being connected to a corresponding event net and for outputting said value, corresponding to said similarity in said specific word with respect to said input utterance. 4. A voice recognition apparatus according to claim 3, wherein said third means is a super net connected to said word net or said plurality of word nets for receiving all said values output from said word net or said plurality of word nets and for outputting said value corresponding to said classification of voice recognition in which said input utterance belongs.

17. A system comprising: a processor; and a memory coupled to the processor, the memory storing instructions which when executed by the processor causes the system to perform a method, the method comprising: obtaining an image of a document; detecting image objects on the image; matching by a processor the image objects to a predetermined document type, wherein image objects distinguish the document type from other document types, and wherein image objects include anchor elements; generating by the processor a flexible structure description corresponding to the predetermined document type based on the detected image objects, wherein the flexible structure description includes a set of search elements for each data field in the image of the document, each search element having an associated search criterion; searching, via a search algorithm, additional document images to determine a respective document type of the additional document images, wherein each of the additional document images are of a document type corresponding to the predetermined document type; modifying the flexible structure description based on said searching of additional document images, wherein the search algorithm is configured to detect data fields based on the flexible structure description, said data fields corresponding to the predetermined document type; and repeating said searching and modifying of the flexible structure description until a defined level of precision is achieved or exceeded.

17. A system comprising: a processor; and a memory coupled to the processor, the memory storing instructions which when executed by the processor causes the system to perform a method, the method comprising: obtaining an image of a document; detecting image objects on the image; matching by a processor the image objects to a predetermined document type, wherein image objects distinguish the document type from other document types, and wherein image objects include anchor elements; generating by the processor a flexible structure description corresponding to the predetermined document type based on the detected image objects, wherein the flexible structure description includes a set of search elements for each data field in the image of the document, each search element having an associated search criterion; searching, via a search algorithm, additional document images to determine a respective document type of the additional document images, wherein each of the additional document images are of a document type corresponding to the predetermined document type; modifying the flexible structure description based on said searching of additional document images, wherein the search algorithm is configured to detect data fields based on the flexible structure description, said data fields corresponding to the predetermined document type; and repeating said searching and modifying of the flexible structure description until a defined level of precision is achieved or exceeded. 19. The system of claim 17 , wherein detecting image objects on the image comprises: detecting an anchor element on the image for a data field.

10. A database driven application hosting data processing system configured for adaptive query expression handling, the system comprising: a database driven application executing in a host computing platform and coupled to a database subsystem and business context engine; and, an adaptive query processor coupled to the database driven application, business context engine and database system, and further coupled to a plurality of adaptive query expressions, the adaptive query processor comprising program code enabled to parse an initial query in the database driven application to identify a query expression key, to match the query expression key to an adaptive query expression among the adaptive query expressions, the adaptive query expression specifying a data query in addition to annotations indicating points of variability in the adaptive query expression, each annotation being replaced with a static sub-expression consistent with a configured query language for a final query expression, to transform the matched adaptive query expression to the final query expression through a replacement of the annotations in the matched adaptive query expression with static expressions conforming to the query language for the final query expression, and to apply the final query expression to the database subsystem.

10. A database driven application hosting data processing system configured for adaptive query expression handling, the system comprising: a database driven application executing in a host computing platform and coupled to a database subsystem and business context engine; and, an adaptive query processor coupled to the database driven application, business context engine and database system, and further coupled to a plurality of adaptive query expressions, the adaptive query processor comprising program code enabled to parse an initial query in the database driven application to identify a query expression key, to match the query expression key to an adaptive query expression among the adaptive query expressions, the adaptive query expression specifying a data query in addition to annotations indicating points of variability in the adaptive query expression, each annotation being replaced with a static sub-expression consistent with a configured query language for a final query expression, to transform the matched adaptive query expression to the final query expression through a replacement of the annotations in the matched adaptive query expression with static expressions conforming to the query language for the final query expression, and to apply the final query expression to the database subsystem. 11. The system of claim 10 , wherein the program code of the adaptive query process is further enabled to match the query expression key to the adaptive query expression utilizing context provided by the business context engine.

8. 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, at a server and from a mobile device, a request including a speech data representation of an utterance or feature data extracted from the speech data representation of the utterance; obtaining, by the server, a transcription of the utterance by applying a speech recognition model to the speech data representation of the utterance or the feature data extracted from the speech data representation of the utterance; identifying, by the server, a keyword based on the transcription of the utterance; and initiating a communication between the mobile device and another device based on the identified keyword.

8. 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, at a server and from a mobile device, a request including a speech data representation of an utterance or feature data extracted from the speech data representation of the utterance; obtaining, by the server, a transcription of the utterance by applying a speech recognition model to the speech data representation of the utterance or the feature data extracted from the speech data representation of the utterance; identifying, by the server, a keyword based on the transcription of the utterance; and initiating a communication between the mobile device and another device based on the identified keyword. 13. The system of claim 8 , wherein identifying, by the server, a keyword based on the transcription of the utterance comprises: determining that the keyword matches a word in the transcription of the utterance.

1. A computer-implemented method comprising: storing construction project specification documents in a data storage system, wherein the construction project specification documents have a uniform organizational structure that characterizes at least some common aspects of an organizational structure of the construction project specification documents, the uniform organizational structure defining the different parts of the construction project specification documents; receiving a search query comprising search criteria from a user electronically via a graphical user interface; analyzing information relating to the construction project specification documents to determine identified documents that satisfy the search criteria; and responsive to the search query, generating one or more displays reflecting data regarding the identified documents that satisfy the search criteria, the one or more displays including a plurality of charts, each of the plurality of charts being interactive such that each of the plurality of charts is configured to receive a user selection of a portion of an individual one of the plurality of charts to provide a modified search criteria that causes the remaining of the plurality of charts to change in response to the modified search criteria, the plurality of charts including: a geography chart including a plurality of geographic regions reflecting the data regarding the identified documents that satisfy the search criteria associated with each of the plurality of geographic regions, wherein the geography chart is configured to receive a user selection of at least one of the plurality of geographic regions via the geography chart to provide the modified search criteria, a timeline reflecting the data regarding the identified documents that satisfy the search criteria as a function of time, wherein the timeline is configured to receive a user adjustment of the timeline to focus on a specific time range to provide the modified search criteria, a project ownership chart that reflects the data regarding the identified documents that satisfy the search criteria as a function of a plurality of types of ownership entities, wherein the project ownership chart is configured to receive a user selection of a type of ownership entity via the project ownership chart to provide the modified search criteria, and a document format chart that reflects the data regarding the identified documents that satisfy the search criteria as a function of different parts of the construction project specification documents, wherein the document format chart is configured to receive a user selection of a specific part of the construction project specification documents via the document format chart to provide the modified search criteria.

1. A computer-implemented method comprising: storing construction project specification documents in a data storage system, wherein the construction project specification documents have a uniform organizational structure that characterizes at least some common aspects of an organizational structure of the construction project specification documents, the uniform organizational structure defining the different parts of the construction project specification documents; receiving a search query comprising search criteria from a user electronically via a graphical user interface; analyzing information relating to the construction project specification documents to determine identified documents that satisfy the search criteria; and responsive to the search query, generating one or more displays reflecting data regarding the identified documents that satisfy the search criteria, the one or more displays including a plurality of charts, each of the plurality of charts being interactive such that each of the plurality of charts is configured to receive a user selection of a portion of an individual one of the plurality of charts to provide a modified search criteria that causes the remaining of the plurality of charts to change in response to the modified search criteria, the plurality of charts including: a geography chart including a plurality of geographic regions reflecting the data regarding the identified documents that satisfy the search criteria associated with each of the plurality of geographic regions, wherein the geography chart is configured to receive a user selection of at least one of the plurality of geographic regions via the geography chart to provide the modified search criteria, a timeline reflecting the data regarding the identified documents that satisfy the search criteria as a function of time, wherein the timeline is configured to receive a user adjustment of the timeline to focus on a specific time range to provide the modified search criteria, a project ownership chart that reflects the data regarding the identified documents that satisfy the search criteria as a function of a plurality of types of ownership entities, wherein the project ownership chart is configured to receive a user selection of a type of ownership entity via the project ownership chart to provide the modified search criteria, and a document format chart that reflects the data regarding the identified documents that satisfy the search criteria as a function of different parts of the construction project specification documents, wherein the document format chart is configured to receive a user selection of a specific part of the construction project specification documents via the document format chart to provide the modified search criteria. 15. A method as defined in claim 1 , wherein the search query is received from the user via a globally accessible public communication network.

1. A method for generating a reduced script comprising: automatically processing, by a speech recognizer, a pre-recorded audio to derive pre-recorded speech assets for a concatenative text-to-speech (TTS) voice; determining, by a reduced script construction engine, unfulfilled speech assets needed for full phonetic coverage of the concatenative TTS voice, the unfulfilled speech assets determined from the pre-recorded speech assets and reference speech assets that are supposed to provide full phonetic coverage of the concatenative TTS voice; and constructing, by the reduced script construction engine, from the unfulfilled speech assets a reduced script that includes a set of phrases, for reading by a voice talent to provide a reduced recording, which when processed results in speech assets that include each of the unfulfilled speech assets.

1. A method for generating a reduced script comprising: automatically processing, by a speech recognizer, a pre-recorded audio to derive pre-recorded speech assets for a concatenative text-to-speech (TTS) voice; determining, by a reduced script construction engine, unfulfilled speech assets needed for full phonetic coverage of the concatenative TTS voice, the unfulfilled speech assets determined from the pre-recorded speech assets and reference speech assets that are supposed to provide full phonetic coverage of the concatenative TTS voice; and constructing, by the reduced script construction engine, from the unfulfilled speech assets a reduced script that includes a set of phrases, for reading by a voice talent to provide a reduced recording, which when processed results in speech assets that include each of the unfulfilled speech assets. 8. The method of claim 1 , wherein the pre-recorded speech assets include values for a plurality of phonetic context trees, said phonetic context trees including a pitch context tree, a duration context tree, and a power context tree.

1. A script performance monitoring and measurement system comprising: a script engine programmed to execute a provided script; a script processor configured to provide a script to said script engine for execution; and, a performance monitor disposed between said script processor and said script engine and configured to intercept scripts provided by said script processor and intended for execution in said script engine, and to monitor and measure script performance when executed by said script engine.

1. A script performance monitoring and measurement system comprising: a script engine programmed to execute a provided script; a script processor configured to provide a script to said script engine for execution; and, a performance monitor disposed between said script processor and said script engine and configured to intercept scripts provided by said script processor and intended for execution in said script engine, and to monitor and measure script performance when executed by said script engine. 2. The system of claim 1 , wherein said performance monitor implements an interface for said script engine.

2. The computer-readable storage media of claim 1 , wherein the one or more instructions further comprise instructions for: modifying the one of the first or second representations based on a first subset of the first set of modifications upon a user action indicating approval of the first subset of the first set of modifications; and automatically modifying the second set of modifications to be made in the unmodified one of the first or second representation based on the first subset of the first set of modifications.

2. The computer-readable storage media of claim 1 , wherein the one or more instructions further comprise instructions for: modifying the one of the first or second representations based on a first subset of the first set of modifications upon a user action indicating approval of the first subset of the first set of modifications; and automatically modifying the second set of modifications to be made in the unmodified one of the first or second representation based on the first subset of the first set of modifications. 3. The computer-readable storage media of claim 2 , wherein the one or more instructions further comprise instructions for: modifying the unmodified one of the first or second representation based on a second subset of the second set of modifications.

13. An article of manufacture, comprising: a machine readable medium having instructions for causing the machine to execute a method comprising: assigning a status flag to a field of an object; evaluating the status flag corresponding to the field of the object based on a subscription rule; and providing information of the status flag from a mobile middleware to a mobile device corresponding to the subscription rule.

13. An article of manufacture, comprising: a machine readable medium having instructions for causing the machine to execute a method comprising: assigning a status flag to a field of an object; evaluating the status flag corresponding to the field of the object based on a subscription rule; and providing information of the status flag from a mobile middleware to a mobile device corresponding to the subscription rule. 15. The article of manufacture of claim 13 , wherein the field comprises a rule.

21. A system comprising: a machine-readable storage device having instructions stored thereon; and data processing apparatus programmed to execute the instructions to perform operations comprising: generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams, each n-gram having a corresponding probability of occurring as a respective name in the annotated corpus; applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data, the annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names; applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names; and generating a name detection model including: deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names, deriving a not-name model using the semi-structured data not identifying names, and deriving a language model using the large annotated corpus.

21. A system comprising: a machine-readable storage device having instructions stored thereon; and data processing apparatus programmed to execute the instructions to perform operations comprising: generating a raw name detection model using a collection of family names and an annotated corpus including a collection of n-grams, each n-gram having a corresponding probability of occurring as a respective name in the annotated corpus; applying the raw name detection model to a collection of semi-structured data to form annotated semi-structured data, the annotated semi-structured data identifying n-grams identifying names and n-grams not identifying names; applying the raw name detection model to a large unannotated corpus to form a large annotated corpus data identifying n-grams of the large unannotated corpus identifying names and n-grams not identifying names; and generating a name detection model including: deriving a name model using the annotated semi-structured data identifying names and the large annotated corpus data identifying names, deriving a not-name model using the semi-structured data not identifying names, and deriving a language model using the large annotated corpus. 30. The system of claim 21 , wherein the operations further comprise: applying the raw name detection model to input data to form annotated input data, the annotated input data identifying n-grams identifying names and n-grams not identifying names; wherein generating the name detection model further comprises: deriving the name model using the annotated user input data identifying names, deriving the not-name model using the annotated user input data not identifying names, and deriving the language model using the annotated user input data.

1. A computer implemented method comprising: receiving a query prefix from a user; obtaining a reference parameter for the user; identifying one or more likely queries that are likely to co-occur with the reference parameter in user activity sessions obtaining initial ranking scores for the one or more likely queries; computing, for each likely query of the one or more likely queries, a respective new ranking score including multiplying the initial ranking score for the likely query by a ranking factor associated with the likely query, wherein the ranking factor R is given by: R = P ⁡ ( x | q ) P ⁡ ( x ) , wherein P(x|q) is a measure of a likelihood of the likely query x occurring in a user activity session given that the reference parameter q also occurred in a same user activity session, and wherein P(x) is a measure of the likelihood of the likely query x appearing in a user activity session; determining a ranking of the one or more likely queries according to the new ranking scores; and providing the ranking of the one or more likely queries in response to receiving the query prefix.

1. A computer implemented method comprising: receiving a query prefix from a user; obtaining a reference parameter for the user; identifying one or more likely queries that are likely to co-occur with the reference parameter in user activity sessions obtaining initial ranking scores for the one or more likely queries; computing, for each likely query of the one or more likely queries, a respective new ranking score including multiplying the initial ranking score for the likely query by a ranking factor associated with the likely query, wherein the ranking factor R is given by: R = P ⁡ ( x | q ) P ⁡ ( x ) , wherein P(x|q) is a measure of a likelihood of the likely query x occurring in a user activity session given that the reference parameter q also occurred in a same user activity session, and wherein P(x) is a measure of the likelihood of the likely query x appearing in a user activity session; determining a ranking of the one or more likely queries according to the new ranking scores; and providing the ranking of the one or more likely queries in response to receiving the query prefix. 5. The method of claim 1 , wherein the reference parameter is a geographic location, a language preference, or an interest associated with a user profile for the user.

16. A computer readable medium comprising computer-executable instructions for performing a process comprising: receiving a registration request from each search provider, wherein the registration request invokes at least one registration function via an API (“Application Programming Interface”), wherein a respective registration request includes a plurality of query properties of an associated search provider, the plurality of query properties including a list of at least one data property name, query comparison operators, a number of operands for each of the query comparison operators, syntactic data value types for each operand and localization information about display strings; receiving an initial request to perform a search from a user; configuring a user interface based on the query properties of each respective search provider; displaying the user interface for the search providers to the user based upon the query properties of each respective search provider; receiving a query from the user; forming a parse tree representation of the query; marshaling the parse tree representation to a selected number of search providers using a call by value protocol, wherein each search provider is associated with a specific type of content and respective search functionality for that content, the associated content for each of the search providers being mutually exclusive.

16. A computer readable medium comprising computer-executable instructions for performing a process comprising: receiving a registration request from each search provider, wherein the registration request invokes at least one registration function via an API (“Application Programming Interface”), wherein a respective registration request includes a plurality of query properties of an associated search provider, the plurality of query properties including a list of at least one data property name, query comparison operators, a number of operands for each of the query comparison operators, syntactic data value types for each operand and localization information about display strings; receiving an initial request to perform a search from a user; configuring a user interface based on the query properties of each respective search provider; displaying the user interface for the search providers to the user based upon the query properties of each respective search provider; receiving a query from the user; forming a parse tree representation of the query; marshaling the parse tree representation to a selected number of search providers using a call by value protocol, wherein each search provider is associated with a specific type of content and respective search functionality for that content, the associated content for each of the search providers being mutually exclusive. 19. The computer readable medium of claim 16 , wherein one or more of the search providers is implemented in an object-oriented programming language.

1. A method of determining lengths of one or more substrings within an input string of characters that matches a regular expression embodied by a non-deterministic finite state automaton (NFA) stored in a search system including a forward search engine, a reverse search engine, and an inversion circuit, the method comprising: comparing the input string with the regular expression using the NFA in a forward search operation performed in the forward search engine; detecting a match state in the NFA in the forward search engine; selecting a portion of the input string as a match string in response to the match state; inverting the NFA to create a reverse NFA that embodies an inverted regular expression; reversing the match string using the inversion circuit to create a reverse match string; comparing the reverse match string with the inverted regular expression using the reverse NFA in a reverse search operation performed in the reverse search engine; and incrementing a count value in response to each character processed in the reverse search operation performed in the reverse search engine.

1. A method of determining lengths of one or more substrings within an input string of characters that matches a regular expression embodied by a non-deterministic finite state automaton (NFA) stored in a search system including a forward search engine, a reverse search engine, and an inversion circuit, the method comprising: comparing the input string with the regular expression using the NFA in a forward search operation performed in the forward search engine; detecting a match state in the NFA in the forward search engine; selecting a portion of the input string as a match string in response to the match state; inverting the NFA to create a reverse NFA that embodies an inverted regular expression; reversing the match string using the inversion circuit to create a reverse match string; comparing the reverse match string with the inverted regular expression using the reverse NFA in a reverse search operation performed in the reverse search engine; and incrementing a count value in response to each character processed in the reverse search operation performed in the reverse search engine. 2. The method of claim 1 , wherein the NFA comprises an initial state and a number of intermediate states between the initial state and the match state, and wherein the match state of the NFA corresponds to an initial state of the reverse NFA.

14. The computer program product according to claim 13 wherein said documents, statements, and resources are PDF documents, PDF statements and PDF shared resources, respectively.

14. The computer program product according to claim 13 wherein said documents, statements, and resources are PDF documents, PDF statements and PDF shared resources, respectively. 15. The computer program product according to claim 14 wherein said PDF document is a PDF report and said set of PDF statements are included in said PDF report.

16. An apparatus for identifying terms suitable for search engine optimization (SEO) for a site, the apparatus comprising: means for determining a volume of search queries for each term in a set of terms, wherein the set of terms comprises at least a plurality of terms used in search engine queries to access the site; means for counting referrals to the site for each term in the set of terms; means for computing a rate of referral for each term in the set of terms as a ratio of the counted referrals to the volume of search queries; means for computing an expectation volume for each term in the set of terms based on the highest rate of referral of the terms in the set of terms and the volume of search queries for each term in the set of terms; and means for identifying one or more terms in the set of terms that are underrepresented relative to one or more other terms in the set of terms based on the expectation volume for each term in the set of terms, wherein the one or more underrepresented terms are identified as being suitable for SEO; wherein the determining, the counting, and the computing are performed, at least in part, by one or more computing devices.

16. An apparatus for identifying terms suitable for search engine optimization (SEO) for a site, the apparatus comprising: means for determining a volume of search queries for each term in a set of terms, wherein the set of terms comprises at least a plurality of terms used in search engine queries to access the site; means for counting referrals to the site for each term in the set of terms; means for computing a rate of referral for each term in the set of terms as a ratio of the counted referrals to the volume of search queries; means for computing an expectation volume for each term in the set of terms based on the highest rate of referral of the terms in the set of terms and the volume of search queries for each term in the set of terms; and means for identifying one or more terms in the set of terms that are underrepresented relative to one or more other terms in the set of terms based on the expectation volume for each term in the set of terms, wherein the one or more underrepresented terms are identified as being suitable for SEO; wherein the determining, the counting, and the computing are performed, at least in part, by one or more computing devices. 20. The apparatus of claim 16 , further comprising: means for generating an estimate of additional referrals to the site due to additional referrals that would be generated if the SEO activities were performed for the one or more underrepresented terms; and means for generating at least one of a revenue estimate or a profit estimate based on the additional referrals.

14. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, the instructions when executed by a processor performing actions comprising: identifying, by a computer, a visual object displayed within a digital video; providing to a user a web-based user interface for annotating the digital video; receiving a request from the user to add an annotation to the visual object; determining, by the computer, a plurality of spatial and temporal positions of the visual object across a corresponding plurality of frames of the digital video; and adding the annotation to an annotation database in association with the digital video such that the annotation is displayed during playback of the digital video and moves along with the determined plurality of spatial and temporal positions of the visual object; and responsive to receiving a request for the digital video from a client device: detecting that the client device is in a locale with a language different from a language of text of the annotation; and responsive to the detecting, altering the annotation to be displayed, wherein altering the annotation comprises translating the text of the annotation according to the language of the locale.

14. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, the instructions when executed by a processor performing actions comprising: identifying, by a computer, a visual object displayed within a digital video; providing to a user a web-based user interface for annotating the digital video; receiving a request from the user to add an annotation to the visual object; determining, by the computer, a plurality of spatial and temporal positions of the visual object across a corresponding plurality of frames of the digital video; and adding the annotation to an annotation database in association with the digital video such that the annotation is displayed during playback of the digital video and moves along with the determined plurality of spatial and temporal positions of the visual object; and responsive to receiving a request for the digital video from a client device: detecting that the client device is in a locale with a language different from a language of text of the annotation; and responsive to the detecting, altering the annotation to be displayed, wherein altering the annotation comprises translating the text of the annotation according to the language of the locale. 15. The non-transitory computer-readable storage medium of claim 14 , wherein the request to add the annotation comprises a designation of a link for the annotation, wherein the target of the link is a target video, the link separately encoding both an identifier of the target video and a time stamp of a moment within the target video, and wherein selection of the annotation causes playback of the target video at the moment in the target video specified by the time stamp.

8. A method of testing compliance of a computing system, the method comprising: receiving a collection of rules in a first set of markup-language statements, the collection of rules representing a configuration benchmark against which a computing system is to be tested for compliance, the computing system having interconnected components including different types of hardware components; parsing the collection of rules to obtain test references to tests and comparison values used therein, the tests being defined in a second set of markup-language statements, with references to at least some of the interconnected components and their attributes as represented in a database organized as an object model of the computing system, the object model expressing physical and functional relationships among the interconnected components including the different types of hardware components; and invoking an interpreter with the test references and comparison values to perform the tests defined in the second set of markup-language statements using the comparison values, performance of the tests including: accessing the database using the references to the at least some of the interconnected components and their attributes to obtain actual values of their attributes; and performing the tests to generate results based on comparisons of the actual values and corresponding ones of the comparison values, the results indicating whether the computing system is compliant with the configuration benchmark.

8. A method of testing compliance of a computing system, the method comprising: receiving a collection of rules in a first set of markup-language statements, the collection of rules representing a configuration benchmark against which a computing system is to be tested for compliance, the computing system having interconnected components including different types of hardware components; parsing the collection of rules to obtain test references to tests and comparison values used therein, the tests being defined in a second set of markup-language statements, with references to at least some of the interconnected components and their attributes as represented in a database organized as an object model of the computing system, the object model expressing physical and functional relationships among the interconnected components including the different types of hardware components; and invoking an interpreter with the test references and comparison values to perform the tests defined in the second set of markup-language statements using the comparison values, performance of the tests including: accessing the database using the references to the at least some of the interconnected components and their attributes to obtain actual values of their attributes; and performing the tests to generate results based on comparisons of the actual values and corresponding ones of the comparison values, the results indicating whether the computing system is compliant with the configuration benchmark. 14. The method of claim 8 , wherein the interconnected components further include different types of software components, and the object model expresses physical and functional relationships among the interconnected components including the different types of hardware components and the different types of software components, wherein the different types of software components include a virtualizing software component, and an operating system or application component, and wherein a rule of the collection of rules specifies a relationship between the virtualizing software component, and the operating system or application component, and a test of the tests is for compliance with the rule.

1. A method of scoring items resulting from a query containing specified terms, wherein the items being scored are annotated to a set of terms in one or more ontologies comprising the steps of: determining whether the set of terms in the one or more ontologies to which the items being scored are annotated are semantically related to the terms in the specified query, assigning an observed semantic similarity score to each of the items being scored; for each item being scored, determining the probability of obtaining the observed semantic similarity score in the event a random set of query terms is used instead of the specified query terms, assigning an individual P-value to the item being scored based on the determined probability, and scoring each of the items, using a computer, according to the assigned P-values.

1. A method of scoring items resulting from a query containing specified terms, wherein the items being scored are annotated to a set of terms in one or more ontologies comprising the steps of: determining whether the set of terms in the one or more ontologies to which the items being scored are annotated are semantically related to the terms in the specified query, assigning an observed semantic similarity score to each of the items being scored; for each item being scored, determining the probability of obtaining the observed semantic similarity score in the event a random set of query terms is used instead of the specified query terms, assigning an individual P-value to the item being scored based on the determined probability, and scoring each of the items, using a computer, according to the assigned P-values. 12. The method of claim 1 , wherein said one or more ontologies are used to describe attributes of jobs and individuals, and wherein a search for matches between jobs and individuals is carried out in a database based on said one or more ontologies.

1. A tangible computer-readable storage medium including computer program code to be executed by a processor, the computer program code, when executed, implementing a content-based healthcare location management system comprising: a correlation services manager to receive a location correlation identifier for a clinical application, and correlate the location correlation identifier with a location instance identifier based on an ontology, wherein the ontology is represented in a directed acyclic graph navigable to identify the ontology for a location, wherein the directed acyclic graph includes a plurality of available ontologies for selection of a location relationship, wherein the plurality of available ontologies includes an “is a” ontology and an “is part of” ontology, wherein the location instance identifier identifies an internal instance of the location correlation identifier to provide location information according to a location schema; a location services manager to update a location map using the location instance identifier, the location services manager to store the location instance identifier in a location relationship object based on at least one location relationship associated with the location instance identifier; and a frame manager to utilize the location relationship object to configure one or more content items forming the clinical application based on the location and the at least one location relationship identified in the location relationship object.

1. A tangible computer-readable storage medium including computer program code to be executed by a processor, the computer program code, when executed, implementing a content-based healthcare location management system comprising: a correlation services manager to receive a location correlation identifier for a clinical application, and correlate the location correlation identifier with a location instance identifier based on an ontology, wherein the ontology is represented in a directed acyclic graph navigable to identify the ontology for a location, wherein the directed acyclic graph includes a plurality of available ontologies for selection of a location relationship, wherein the plurality of available ontologies includes an “is a” ontology and an “is part of” ontology, wherein the location instance identifier identifies an internal instance of the location correlation identifier to provide location information according to a location schema; a location services manager to update a location map using the location instance identifier, the location services manager to store the location instance identifier in a location relationship object based on at least one location relationship associated with the location instance identifier; and a frame manager to utilize the location relationship object to configure one or more content items forming the clinical application based on the location and the at least one location relationship identified in the location relationship object. 4. The computer-readable storage medium of claim 1 , wherein the frame manager is to use the location relationship object to select one or more context variants for the one or more content items to form the clinical application for the location.

17. A system, comprising: one or more processing units; and memory comprising instructions that when executed by at least some of the one or more processing units perform a method, comprising: receiving an itinerary query comprising a starting location, an ending location and a duration; identifying a set of trip candidates, from a location-interest graph, comprising: performing a first comparison of the starting location of the itinerary query with at least one of a first starting location of a first trip candidate, a second starting location of a second trip candidate, a third starting location of a third trip candidate or a fourth starting location of a fourth trip candidate; performing a second comparison of the ending location of the itinerary query with at least one of a first ending location of the first trip candidate, a second ending location of the second trip candidate, a third ending location of the third trip candidate or a fourth ending location of the fourth trip candidate; performing a third comparison of the duration of the itinerary query with at least one of: a combination of at least a first travel time associated with the first trip candidate and a first stay time associated with one or more locations associated with the first trip candidate; a combination of at least a second travel time associated with the second trip candidate and a second stay time associated with one or more locations associated with the second trip candidate; a combination of at least a third travel time associated with the third trip candidate and a third stay time associated with one or more locations associated with the third trip candidate; or a combination of at least a fourth travel time associated with the fourth trip candidate and a fourth stay time associated with one or more locations associated with the fourth trip candidate; and including the first trip candidate, the second trip candidate and the third trip candidate, but not the fourth trip candidate, within the set of trip candidates based on the first comparison, the second comparison and the third comparison; identifying: a first threshold difference for the first trip candidate, the first threshold difference comprising a first difference between a desired threshold value and a first value for the first trip candidate; a second threshold difference for the second trip candidate, the second threshold difference comprising a second difference between the desired threshold value and a second value for the second trip candidate; and a third threshold difference for the third trip candidate, the third threshold difference comprising a third difference between the desired threshold value and a third value for the third trip candidate, at least one of the desired threshold value, the first value, the second value or the third threshold value based on one or more trip factors; selecting the first trip candidate and the second trip candidate, but not the third trip candidate, from the set of trip candidates based on the first threshold difference and the second threshold difference corresponding to a desired range of identified threshold differences, and the third threshold difference not corresponding to the desired range of identified threshold differences; ranking the first trip candidate and the second trip candidate based on one or more ranking factors; re-ranking the first trip candidate and the second trip candidate based on one or more historical travel sequences; and providing the re-ranked trip candidates in response to receiving the itinerary query.

17. A system, comprising: one or more processing units; and memory comprising instructions that when executed by at least some of the one or more processing units perform a method, comprising: receiving an itinerary query comprising a starting location, an ending location and a duration; identifying a set of trip candidates, from a location-interest graph, comprising: performing a first comparison of the starting location of the itinerary query with at least one of a first starting location of a first trip candidate, a second starting location of a second trip candidate, a third starting location of a third trip candidate or a fourth starting location of a fourth trip candidate; performing a second comparison of the ending location of the itinerary query with at least one of a first ending location of the first trip candidate, a second ending location of the second trip candidate, a third ending location of the third trip candidate or a fourth ending location of the fourth trip candidate; performing a third comparison of the duration of the itinerary query with at least one of: a combination of at least a first travel time associated with the first trip candidate and a first stay time associated with one or more locations associated with the first trip candidate; a combination of at least a second travel time associated with the second trip candidate and a second stay time associated with one or more locations associated with the second trip candidate; a combination of at least a third travel time associated with the third trip candidate and a third stay time associated with one or more locations associated with the third trip candidate; or a combination of at least a fourth travel time associated with the fourth trip candidate and a fourth stay time associated with one or more locations associated with the fourth trip candidate; and including the first trip candidate, the second trip candidate and the third trip candidate, but not the fourth trip candidate, within the set of trip candidates based on the first comparison, the second comparison and the third comparison; identifying: a first threshold difference for the first trip candidate, the first threshold difference comprising a first difference between a desired threshold value and a first value for the first trip candidate; a second threshold difference for the second trip candidate, the second threshold difference comprising a second difference between the desired threshold value and a second value for the second trip candidate; and a third threshold difference for the third trip candidate, the third threshold difference comprising a third difference between the desired threshold value and a third value for the third trip candidate, at least one of the desired threshold value, the first value, the second value or the third threshold value based on one or more trip factors; selecting the first trip candidate and the second trip candidate, but not the third trip candidate, from the set of trip candidates based on the first threshold difference and the second threshold difference corresponding to a desired range of identified threshold differences, and the third threshold difference not corresponding to the desired range of identified threshold differences; ranking the first trip candidate and the second trip candidate based on one or more ranking factors; re-ranking the first trip candidate and the second trip candidate based on one or more historical travel sequences; and providing the re-ranked trip candidates in response to receiving the itinerary query. 18. The system of claim 17 , the one or more trip factors comprising at least one of: a stay time ratio; an interest density ratio; or an elapsed time ratio.

21. The one or more non-transitory computer-readable media of claim 15 , wherein one or more assertions are associated with the first or second process, and wherein the one or more assertions describe one or more preconditions or one or more postconditions at one or more points in the first or second process.

21. The one or more non-transitory computer-readable media of claim 15 , wherein one or more assertions are associated with the first or second process, and wherein the one or more assertions describe one or more preconditions or one or more postconditions at one or more points in the first or second process. 23. The one or more non-transitory computer-readable media of claim 21 , wherein the one or more assertions which describe the one or more preconditions are used to check the correctness of the first or second business logic prior to the executing of the first or second business logic.

11. 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, from a client device over a computer network, audio data that describes an utterance of a user; accessing stored data of an acoustic model that was generated by: accessing speech data that represents utterances of a particular phonetic unit occurring in a particular phonetic context, the speech data comprising values for multiple dimensions; determining boundaries for a set of quantiles for each of the multiple dimensions; generating, for each of the quantiles, a model that models the distribution of values within the quantile; generating a multidimensional probability function that indicates, for input speech data representing speech occurring in the particular phonetic context, a probability that the input speech data will have values that correspond to a given set of the quantiles for the multiple dimensions, wherein generating the multidimensional probability function comprises generating an n-gram model wherein the n-grams are sequences of quantile identifiers and the sequences include quantile identifiers for quantiles in at least two dimensions; storing data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function; using the stored data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function to determine a transcription for the utterance; and providing, to the client device and over the computer network, the transcription for the utterance.

11. 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, from a client device over a computer network, audio data that describes an utterance of a user; accessing stored data of an acoustic model that was generated by: accessing speech data that represents utterances of a particular phonetic unit occurring in a particular phonetic context, the speech data comprising values for multiple dimensions; determining boundaries for a set of quantiles for each of the multiple dimensions; generating, for each of the quantiles, a model that models the distribution of values within the quantile; generating a multidimensional probability function that indicates, for input speech data representing speech occurring in the particular phonetic context, a probability that the input speech data will have values that correspond to a given set of the quantiles for the multiple dimensions, wherein generating the multidimensional probability function comprises generating an n-gram model wherein the n-grams are sequences of quantile identifiers and the sequences include quantile identifiers for quantiles in at least two dimensions; storing data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function; using the stored data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function to determine a transcription for the utterance; and providing, to the client device and over the computer network, the transcription for the utterance. 17. The system of claim 11 , wherein accessing the speech data comprises accessing speech data that represents multiple utterances of a particular phonetic unit that each occur in a same, particular phonetic context that comprises one or more additional phonetic units, the speech data comprising values for multiple dimensions for each of the multiple utterances; wherein determining the boundaries for a set of quantiles comprises determining boundaries for a set of quantiles for each of the multiple dimensions based on the speech data that represents multiple utterances of the particular phonetic unit occurring in the particular phonetic context that includes the one or more additional phonetic units; wherein generating the multidimensional probability function comprises generating a multidimensional probability function that indicates, for input speech data representing speech occurring in the particular phonetic context that includes the one or more additional phonetic units, a probability that the input speech data will have values that correspond to a given set of the quantiles for the multiple dimensions; and wherein storing the data comprises storing data indicating the boundaries of the quantiles, the models for the distribution of values in the quantiles, and the multidimensional probability function as a portion of an acoustic model corresponding to the particular phonetic unit occurring in the particular phonetic context that include the one or more additional phonetic units.

1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generating sentiment tuning data from the user feedback; generating a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; applying the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identifying designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determining assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and presenting the new social posts in association with the sentiments assigned to the new social posts.

1. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving user feedback for each of one or more social posts presented to a user, each social post presented in association with a sentiment assigned to the social post, the user feedback for each social post regarding the sentiment assigned to the social post; generating sentiment tuning data from the user feedback; generating a new set of sentiment indicators from user provided sentiment indicators of the sentiment tuning data; applying the new set of sentiment indicators, generated from the sentiment tuning data, to new social posts to determine sentiments for the new social posts, wherein the applying comprises: identifying designated expressive symbols of the new set of sentiment indicators in the new social posts, the new set of sentiment indicators comprising assignments between the designated expressive symbols and designated sentiments; and determining assignments of the sentiments to the new social posts based on the assignments between the designated expressive symbols and the designated sentiments; and presenting the new social posts in association with the sentiments assigned to the new social posts. 2. The one or more computer storage media of claim 1 , wherein the applying further comprises: determining a similarity between a new social post of the new social posts and a reference social post of the sentiment tuning data, the reference social post being assigned a reference sentiment in the sentiment tuning data; assigning a sentiment to the new social post based on the similarity.

1. A system comprising: a processor; a first module controlling the processor to perform a prosodic analysis and a syntactic analysis of speech data to be spoken by a virtual agent to a user, the prosodic analysis comprising analyzing speech intonations comprising loudness and accent, identifying prosodic phrase boundaries in the speech data, and identifying a type for each of the prosodic phrase boundaries; a second module controlling the processor to determine a culture of the user based on an analysis of prosody associated with received speech from the user, the analysis being independent of an identity of the user; and a third module controlling the processor to control movement of the virtual agent according to the prosodic analysis, the syntactic analysis, and the culture of the user and not based on a previously-stored template for controlling the movement, wherein the movement of the virtual agent at each of the prosodic phrase boundaries is selected based on the type identified for each of the prosodic phrase boundaries.

1. A system comprising: a processor; a first module controlling the processor to perform a prosodic analysis and a syntactic analysis of speech data to be spoken by a virtual agent to a user, the prosodic analysis comprising analyzing speech intonations comprising loudness and accent, identifying prosodic phrase boundaries in the speech data, and identifying a type for each of the prosodic phrase boundaries; a second module controlling the processor to determine a culture of the user based on an analysis of prosody associated with received speech from the user, the analysis being independent of an identity of the user; and a third module controlling the processor to control movement of the virtual agent according to the prosodic analysis, the syntactic analysis, and the culture of the user and not based on a previously-stored template for controlling the movement, wherein the movement of the virtual agent at each of the prosodic phrase boundaries is selected based on the type identified for each of the prosodic phrase boundaries. 2. The system of claim 1 , wherein the movement of the virtual agent is controlled to be approximately simultaneous with the received speech that triggers the movement.

2. The computer program product of claim 1 , wherein identifying the noun phrase and the verb phrase includes generating a hierarchical tree for the definition.

2. The computer program product of claim 1 , wherein identifying the noun phrase and the verb phrase includes generating a hierarchical tree for the definition. 3. The computer program product of claim 2 , wherein generating the hierarchical tree comprises parsing the definition at a word class level.

10. The image-reading method as claimed in claim 9 , further comprising handling a reading error by performing prescribed action when it is determined that the page reading error has occurred in the reading error determining step.

10. The image-reading method as claimed in claim 9 , further comprising handling a reading error by performing prescribed action when it is determined that the page reading error has occurred in the reading error determining step. 11. The image-reading method as claimed in claim 10 , further comprising storing the image data read in the reading step, and skipping the image data storing step when it is determined that the page reading error has occurred in the reading error determining step.

11. A computer-implemented method for populating clusters of documents, comprising: placing a set of clusters in a display in relation to a common origin; selecting one of a plurality of unclustered documents in the display and determining an angle θ of the document from the common origin; computing for each cluster, an angle σ of the cluster relative to the common origin; determining a difference between the document angle θ and one such cluster angle σ; applying a predetermined variance to the difference; and placing the document into the cluster when the difference is less than the variance.

11. A computer-implemented method for populating clusters of documents, comprising: placing a set of clusters in a display in relation to a common origin; selecting one of a plurality of unclustered documents in the display and determining an angle θ of the document from the common origin; computing for each cluster, an angle σ of the cluster relative to the common origin; determining a difference between the document angle θ and one such cluster angle σ; applying a predetermined variance to the difference; and placing the document into the cluster when the difference is less than the variance. 13. A method according to claim 11 , further comprising: generating the themes, comprising: determining a frequency of each term within each unclustered document; mapping the frequencies of the terms across all the unclustered documents; applying a predetermined range of frequencies to the mapped frequencies; and designating those terms that fall within the threshold as the themes for the unclustered documents.

13. A computer-readable storage medium for storing computer-executable instructions that, when executed, cause a computer to perform a process comprising: receiving via a microphone at a user's computer, audio input corresponding to a voice of a selected speaker, wherein a personalized speech audio data is created by speaking a plurality of predetermined utterances into the microphone of the user's computer; encoding the audio input into a waveform; generating a personalized voice font based on the waveform; accessing a text-to-speech application through a browser on the user's computer, wherein the browser is in communication with a network; transmitting the waveform to a voice font generator of a text-to-speech (TTS) engine residing on a remote computer that is in communication with the browser of the user's computer via the network to generate the personalized voice font, wherein generating the personalized voice font after transmitting the waveform to the voice font generator comprises: associating the personalized speech audio data transmitted to the voice font generator with corresponding basic phonetic units, wherein the plurality of predetermined utterances is parsed into one or more basic phonetic units comprising at least one of phonemes, diphones, semi-syllables, or syllables, identifying the one or more basic phonetic units based on corresponding characteristics of a basic phonetic unit, and associating the one or more basic phonetic units with corresponding segments of the waveform in a data structure, wherein the data structure comprises a table having one column correspond to one or more identifiers of the one or more basic phonetic units, and having another column correspond to the segments of the waveform, wherein each identifier corresponds to one or more segments of the waveform in the table; transmitting a text from the user's computer to the TTS engine via the network; selecting the personalized voice font using a voice font selector, wherein the voice font selector is in communication with the browser of the user's computer via the network; instructing the TTS engine to generate synthesized speech based on the text transmitted to the TTS engine; concatenating the personalized voice font into a chain according to an order of the basic phonetic units in the text, the basic phonetic units are parsed into phonemes, diphones, semi-syllables, or syllables and identified by an associated diphone, a triphone, a semi-syllable, or a syllable that is associated with a corresponding segment in a waveform; downloading concatenated speech segments to the user's computer; and receiving to the user's computer via the network synthesized speech from the TTS engine, the synthesized speech corresponding to the text and being synthesized with the personalized voice font representative of the selected speaker's voice.

13. A computer-readable storage medium for storing computer-executable instructions that, when executed, cause a computer to perform a process comprising: receiving via a microphone at a user's computer, audio input corresponding to a voice of a selected speaker, wherein a personalized speech audio data is created by speaking a plurality of predetermined utterances into the microphone of the user's computer; encoding the audio input into a waveform; generating a personalized voice font based on the waveform; accessing a text-to-speech application through a browser on the user's computer, wherein the browser is in communication with a network; transmitting the waveform to a voice font generator of a text-to-speech (TTS) engine residing on a remote computer that is in communication with the browser of the user's computer via the network to generate the personalized voice font, wherein generating the personalized voice font after transmitting the waveform to the voice font generator comprises: associating the personalized speech audio data transmitted to the voice font generator with corresponding basic phonetic units, wherein the plurality of predetermined utterances is parsed into one or more basic phonetic units comprising at least one of phonemes, diphones, semi-syllables, or syllables, identifying the one or more basic phonetic units based on corresponding characteristics of a basic phonetic unit, and associating the one or more basic phonetic units with corresponding segments of the waveform in a data structure, wherein the data structure comprises a table having one column correspond to one or more identifiers of the one or more basic phonetic units, and having another column correspond to the segments of the waveform, wherein each identifier corresponds to one or more segments of the waveform in the table; transmitting a text from the user's computer to the TTS engine via the network; selecting the personalized voice font using a voice font selector, wherein the voice font selector is in communication with the browser of the user's computer via the network; instructing the TTS engine to generate synthesized speech based on the text transmitted to the TTS engine; concatenating the personalized voice font into a chain according to an order of the basic phonetic units in the text, the basic phonetic units are parsed into phonemes, diphones, semi-syllables, or syllables and identified by an associated diphone, a triphone, a semi-syllable, or a syllable that is associated with a corresponding segment in a waveform; downloading concatenated speech segments to the user's computer; and receiving to the user's computer via the network synthesized speech from the TTS engine, the synthesized speech corresponding to the text and being synthesized with the personalized voice font representative of the selected speaker's voice. 22. A computer-readable storage medium as recited in claim 13 , the process further comprising outputting audio based on the synthesized speech at the user's computer.

1. A method of carrying out a search of television data carried out in a television receiver device using a search engine, comprising: at a television receiver device, receiving a command from a television remote controller device that retrieves a video frame of metadata text associated with a television program; extracting selected portions of the metadata text from the video frame containing metadata text by optical character recognition (OCR) processing of the selected text from the video frame, the selected portions of the metadata text being selected based upon the receipt of navigation and selection commands from the television remote controller; loading the text extracted from the OCR processing as a search string into a browser connection to an Internet search engine; executing the search using the search engine operating on the search string; receiving search results from the search engine; and displaying the search results for viewing on a display associated with said television receiver device.

1. A method of carrying out a search of television data carried out in a television receiver device using a search engine, comprising: at a television receiver device, receiving a command from a television remote controller device that retrieves a video frame of metadata text associated with a television program; extracting selected portions of the metadata text from the video frame containing metadata text by optical character recognition (OCR) processing of the selected text from the video frame, the selected portions of the metadata text being selected based upon the receipt of navigation and selection commands from the television remote controller; loading the text extracted from the OCR processing as a search string into a browser connection to an Internet search engine; executing the search using the search engine operating on the search string; receiving search results from the search engine; and displaying the search results for viewing on a display associated with said television receiver device. 9. The method according to claim 1 , wherein the text is selected by a selection command that is preceded by a sequence of navigation commands.

3. The method of claim 1 , wherein computing the least common ancestor of the related terms comprises storing all non-leaf terms on at least one server.

3. The method of claim 1 , wherein computing the least common ancestor of the related terms comprises storing all non-leaf terms on at least one server. 4. The method of claim 3 , wherein the at least one server is a master server.

1. A computer-implemented method for generating a visual feature to semantic space transformation map using a set of text images, each text image including one or more annotated character bounding boxes, the method comprising: a) extracting a plurality of image patch descriptors representative of a plurality of respective image patches representative of the text images, the plurality of image patches including a background and a foreground area associated with the text images; b) computing a plurality of aggregated representations of the image patch descriptors, each aggregated representation associated with an image block including two or more image patches; c) computing character annotations associated with each image block by measuring a proximate relationship of an image block with an annotated character bounding box; and d) generating the visual feature to semantic space transformation map by constructing an intermediate subspace which maps the aggregated representations associated with the image blocks computed in step b) to the character annotations associated with each image block computer in step c).

1. A computer-implemented method for generating a visual feature to semantic space transformation map using a set of text images, each text image including one or more annotated character bounding boxes, the method comprising: a) extracting a plurality of image patch descriptors representative of a plurality of respective image patches representative of the text images, the plurality of image patches including a background and a foreground area associated with the text images; b) computing a plurality of aggregated representations of the image patch descriptors, each aggregated representation associated with an image block including two or more image patches; c) computing character annotations associated with each image block by measuring a proximate relationship of an image block with an annotated character bounding box; and d) generating the visual feature to semantic space transformation map by constructing an intermediate subspace which maps the aggregated representations associated with the image blocks computed in step b) to the character annotations associated with each image block computer in step c). 5. The computer-implemented method for generating a visual feature to semantic space transformation map according to claim 1 , wherein the proximate relationship is associated with an overlap of an image block with an annotated character bounding box.

18. The medium of claim 17 , wherein determining that a quantity of one or more of the feature point descriptors from the first image that are (i) indicated as similar to one or more feature point descriptors associated within a predefined sub-region of the second image, and (ii) associated within a corresponding predefined sub-region of the first image, satisfies a quantity threshold, comprises: determining a quantity of the one or more of the feature point descriptors associated within a predefined sub-region of the first image that are similar to the one or more feature point descriptors associated within a predefined sub-region of the second image; and determining that the determined quantity satisfies the quantity threshold.

18. The medium of claim 17 , wherein determining that a quantity of one or more of the feature point descriptors from the first image that are (i) indicated as similar to one or more feature point descriptors associated within a predefined sub-region of the second image, and (ii) associated within a corresponding predefined sub-region of the first image, satisfies a quantity threshold, comprises: determining a quantity of the one or more of the feature point descriptors associated within a predefined sub-region of the first image that are similar to the one or more feature point descriptors associated within a predefined sub-region of the second image; and determining that the determined quantity satisfies the quantity threshold. 19. The medium of claim 18 , wherein determining a quantity of the one or more of the feature point descriptors associated within a predefined sub-region of the first image that are similar to the one or more feature point descriptors associated within a predefined sub-region of the second image, comprises: for each of the one or more of the feature point descriptors associated within the predefined sub-region of the first image, generating a similarity measure representing one or more similarities to the one or more feature point descriptors associated within the predefined sub-region of the second image; and determining that one or more of the feature point descriptors from the first image associated within the predefined sub-region of the first image are similar to one or more feature point descriptors associated within the predefined sub-region of the second image based on the similarity measures.

1. For a website optimization system comprising at least one server with at least one processor and non-transitory computer-readable memory, a computer-implemented method for automatically assessing whether visual elements of a website increase or decrease the website's credibility, the computer-implemented method comprising: classifying by operation of the processor, each website of a plurality of websites based on subject matter of the website; identifying by operation of the processor, a group of credible websites from a set of the plurality of websites that are similarly classified, wherein each website of the group of credible websites is composed of a different set of visual elements defining a presentation for the website in a browser; determining by operation of the processor, a common set of visual elements presented in each credible website of the group of credible websites; scanning by operation of the processor, visual elements present on a new website that is not in the group of credible websites and that is similarly classified as the group of credible websites; computing by operation of the processor, a credibility score for the new website based on comparison of a particular visual element that is present on the new website and that is also present in the common set of visual elements; and presenting from the website optimization system, the credibility score in conjunction with presentation of the particular visual element of the new website.

1. For a website optimization system comprising at least one server with at least one processor and non-transitory computer-readable memory, a computer-implemented method for automatically assessing whether visual elements of a website increase or decrease the website's credibility, the computer-implemented method comprising: classifying by operation of the processor, each website of a plurality of websites based on subject matter of the website; identifying by operation of the processor, a group of credible websites from a set of the plurality of websites that are similarly classified, wherein each website of the group of credible websites is composed of a different set of visual elements defining a presentation for the website in a browser; determining by operation of the processor, a common set of visual elements presented in each credible website of the group of credible websites; scanning by operation of the processor, visual elements present on a new website that is not in the group of credible websites and that is similarly classified as the group of credible websites; computing by operation of the processor, a credibility score for the new website based on comparison of a particular visual element that is present on the new website and that is also present in the common set of visual elements; and presenting from the website optimization system, the credibility score in conjunction with presentation of the particular visual element of the new website. 5. The computer-implemented method of claim 1 further comprising increasing the credibility score based on each additional credible website of the group of credible websites presenting the particular visual element.

19. A method implemented on a computing device having a processor, comprising: using the computing device having the processor to perform the following: selecting a natural interaction forum; attaching a rubric to the selected natural interaction forum, wherein the rubric is a template used for assessing the learner's knowledge of the topic; assigning to the learner a natural interaction assignment in the selected natural interaction forum to assess the learner's knowledge of the topic; assessing the learner's knowledge of the topic with the natural interaction assignment to generate assessment results based at least in part on the attached rubric, wherein assessing the learner's knowledge includes using at least one of a participation metric, or a tagging metric, or a natural language metric to assess the learner and generate the assessment results; and computing a final score of the learner on the natural interaction assignment from the assessment results, wherein computing the final score includes computing a single score from the assessment results and normalizing the single score to obtain the final score of the learner on the natural interaction assignment.

19. A method implemented on a computing device having a processor, comprising: using the computing device having the processor to perform the following: selecting a natural interaction forum; attaching a rubric to the selected natural interaction forum, wherein the rubric is a template used for assessing the learner's knowledge of the topic; assigning to the learner a natural interaction assignment in the selected natural interaction forum to assess the learner's knowledge of the topic; assessing the learner's knowledge of the topic with the natural interaction assignment to generate assessment results based at least in part on the attached rubric, wherein assessing the learner's knowledge includes using at least one of a participation metric, or a tagging metric, or a natural language metric to assess the learner and generate the assessment results; and computing a final score of the learner on the natural interaction assignment from the assessment results, wherein computing the final score includes computing a single score from the assessment results and normalizing the single score to obtain the final score of the learner on the natural interaction assignment. 23. The method of claim 19 , further comprising creating tags for the learner's posts in the natural interaction forum that matches information in the learner's posts to topics in the rubric.

39. A system comprising: a computer memory for storing instructions; and a processor for executing the instructions, the instructions for: receiving activity history associated with a user from a network data source, the activity history comprising a description of a user action initiated by the user; generating a first metadata item based upon the activity history; storing the first metadata item as user profile information associated with the user in a user profile database in response to a number of times the first metadata item is generated in a defined time period being greater than a threshold value; providing a link to a widget plugin for inclusion with content objects of a content server that is disparate from the computing device and the network data source, the widget plugin enables communication between the computing device and a client computer associated with the user, the widget plugin enables via the communication, scanning of content objects received by the client computer and automatic retrieval of a subset of the content objects relevant to the first metadata item; receiving a request for user-related metadata relevant to the content objects of provided by the content server to the client computer in response to navigation of the user to a website of the content server; determining that the first metadata item is relevant to the content objects; transmitting the first metadata item to an entity that made the request; enabling via the provision of the widget plugin link, automatic retrieval of a subset of the content objects that are relevant to the first metadata item for display to the user; and removing the first metadata item from the user profile database in response to a number of times the first metadata item is generated in a defined time period being less than the threshold value.

39. A system comprising: a computer memory for storing instructions; and a processor for executing the instructions, the instructions for: receiving activity history associated with a user from a network data source, the activity history comprising a description of a user action initiated by the user; generating a first metadata item based upon the activity history; storing the first metadata item as user profile information associated with the user in a user profile database in response to a number of times the first metadata item is generated in a defined time period being greater than a threshold value; providing a link to a widget plugin for inclusion with content objects of a content server that is disparate from the computing device and the network data source, the widget plugin enables communication between the computing device and a client computer associated with the user, the widget plugin enables via the communication, scanning of content objects received by the client computer and automatic retrieval of a subset of the content objects relevant to the first metadata item; receiving a request for user-related metadata relevant to the content objects of provided by the content server to the client computer in response to navigation of the user to a website of the content server; determining that the first metadata item is relevant to the content objects; transmitting the first metadata item to an entity that made the request; enabling via the provision of the widget plugin link, automatic retrieval of a subset of the content objects that are relevant to the first metadata item for display to the user; and removing the first metadata item from the user profile database in response to a number of times the first metadata item is generated in a defined time period being less than the threshold value. 45. The system of claim 39 , wherein the first metadata item comprises a tag.

17. An article of manufacture comprising: media comprising programming configured to cause processing circuitry to perform processing comprising: accessing a plurality of rules for a reasoning module; accessing a plurality of abstractions which include a plurality of individuals; processing the abstractions according to the rules; and classifying the individual of at least one of the abstractions as a result of the processing of the at least one of the abstractions satisfying the rules.

17. An article of manufacture comprising: media comprising programming configured to cause processing circuitry to perform processing comprising: accessing a plurality of rules for a reasoning module; accessing a plurality of abstractions which include a plurality of individuals; processing the abstractions according to the rules; and classifying the individual of at least one of the abstractions as a result of the processing of the at least one of the abstractions satisfying the rules. 19. The article of claim 17 wherein the at least one abstraction has a first classification type, and the classifying comprises creating a new individual of a second classification type and associating the individual of the first classification type with the new individual of the second classification type.

6. A machine process for identifying a human language used in a computer coded document from text in the document as defined in claim 5, further comprising the steps of setting the threshold for a minimum number of words which must be read from a document before a language identification can be made, counting the words read from the document, and making a language identification only if the count exceeds the threshold.

6. A machine process for identifying a human language used in a computer coded document from text in the document as defined in claim 5, further comprising the steps of setting the threshold for a minimum number of words which must be read from a document before a language identification can be made, counting the words read from the document, and making a language identification only if the count exceeds the threshold. 7. A machine process for identifying a human language used in a computer coded document from text in the document as defined in claim 6, further comprising the steps of setting the threshold for a largest WFA value which can identify a language, and identifying the language of the document when the largest WFA value exceeds the next-largest WFA value by more than an established threshold and the word count exceeds the threshold.

19. The system of claim 16 , further comprising a means for selecting and mixing allows a user to designate a selected dialog channel during playback of the first plurality of surround audio channels.

19. The system of claim 16 , further comprising a means for selecting and mixing allows a user to designate a selected dialog channel during playback of the first plurality of surround audio channels. 20. The system of claim 19 , wherein the means for selecting and mixing comprises a matrix decoder adapted to combine the selected dialog channel with decoded first plurality of surround audio channels such that the decoded first plurality of surround audio channels comprises the selected dialog channel as a center channel.

26. An article comprising a storage medium having stored thereon instructions that, when executed by a computing platform, result the reviewing of content by: receiving a review file for content to be reviewed; playing the content with respect to a signature comprising a set of signature values of the content, wherein each of the set of signature values is related to a time based flow of the content stored in the review file and each signature value comprises a time value based on a timeline; annotating the content with an annotation; associating the annotation with respect to a corresponding signature value, wherein the corresponding signature value is one of the set of signature values that corresponds to the occurrence of the annotation with respect to the time based flow of the content; storing the annotation in an annotation file along with the corresponding signature value; and sending the annotation file to a user without requiring a server to manage the reviewing of the content.

26. An article comprising a storage medium having stored thereon instructions that, when executed by a computing platform, result the reviewing of content by: receiving a review file for content to be reviewed; playing the content with respect to a signature comprising a set of signature values of the content, wherein each of the set of signature values is related to a time based flow of the content stored in the review file and each signature value comprises a time value based on a timeline; annotating the content with an annotation; associating the annotation with respect to a corresponding signature value, wherein the corresponding signature value is one of the set of signature values that corresponds to the occurrence of the annotation with respect to the time based flow of the content; storing the annotation in an annotation file along with the corresponding signature value; and sending the annotation file to a user without requiring a server to manage the reviewing of the content. 27. An article as claimed in claim 26 , wherein the annotation is stored as a metadata tag at a time location in a timeline that corresponds to the time of the annotation with respect to the content.

8. A transmitter-side terminal for supporting a translation-based communication service, the transmitter-side terminal comprising: at least one of an input unit configured to receive input of a text in a first language with voice-related characteristic information and a display unit having an input function, wherein the voice related characteristic information is used to generate a translation voice signal in a second language with a pitch and a tone similar to a voice signal in the first language; a storage unit configured to store a translation database for translation of the text in the first language; a controller configured to translate the text in the first language to a translation text in the second language by using the translation database; and a communication unit configured to transmit the translation text in the second language with the voice-related characteristic information.

8. A transmitter-side terminal for supporting a translation-based communication service, the transmitter-side terminal comprising: at least one of an input unit configured to receive input of a text in a first language with voice-related characteristic information and a display unit having an input function, wherein the voice related characteristic information is used to generate a translation voice signal in a second language with a pitch and a tone similar to a voice signal in the first language; a storage unit configured to store a translation database for translation of the text in the first language; a controller configured to translate the text in the first language to a translation text in the second language by using the translation database; and a communication unit configured to transmit the translation text in the second language with the voice-related characteristic information. 12. The transmitter-side terminal of claim 8 , wherein a display unit is configured to provide at least one of an icon or a menu item for selection of a translation mode, and the controller is configured to select language configuration information of a receiver-side terminal that is communication-connected with the communication unit when the translation mode is selected.

14. A spinal implant system that is adapted to be mounted to a spine comprising: first and second anchors that are adapted to be secured to a spine; a first horizontal rod that is secured to the first and second anchors; a deflection rod system; a mount to mount the deflection rod system to said first horizontal rod; said deflection rod system including an inner rod and an outer shell; wherein said inner rod is elongated and said outer shell is elongated along the elongated inner rod; said deflection rod system including a shield that is elongated and is provided along and about the outer shell which shielded limits the deflection of said inner rod and said outer shell; said deflection rod system includes at least one first section that is moveable relative to a second section in order to accommodate movement of a spine; at least one joint connection located at an end of the deflection rod system; a first vertical rod that is secured by said joint connection to said first horizontal rod.

14. A spinal implant system that is adapted to be mounted to a spine comprising: first and second anchors that are adapted to be secured to a spine; a first horizontal rod that is secured to the first and second anchors; a deflection rod system; a mount to mount the deflection rod system to said first horizontal rod; said deflection rod system including an inner rod and an outer shell; wherein said inner rod is elongated and said outer shell is elongated along the elongated inner rod; said deflection rod system including a shield that is elongated and is provided along and about the outer shell which shielded limits the deflection of said inner rod and said outer shell; said deflection rod system includes at least one first section that is moveable relative to a second section in order to accommodate movement of a spine; at least one joint connection located at an end of the deflection rod system; a first vertical rod that is secured by said joint connection to said first horizontal rod. 16. The spinal implant system of claim 14 wherein the joint connection includes a ball joint.

1. A method, comprising: receiving, by at least one of one or more server devices and from a client, a search query; obtaining, by at least one of the one or more server devices, search results based on the search query, the search results identifying documents relevant to the search query; identifying, by at least one of the one or more server devices, image attributes associated with one or more of the documents, the image attributes identifying information, within the one or more of the documents, associated with images; obtaining, by at least one of the one or more server devices, classification metrics that include information for determining a measure of image intent associated with the search query, the measure of image intent representing a likelihood that image results are intended by the search query, the image results identifying images or video relevant to the search query, and the classification metrics identifying a plurality of keywords; determining, by at least one of the one or more server devices, the measure of image intent, associated with the search query, based on the image attributes and the classification metrics, the image attributes, for a particular document of the one or more of the documents, corresponding to at least one of: a particular quantity of keywords, within the particular document, that match the plurality of keywords identified by the classification metrics, or a particular keyword density based on the particular quantity of keywords and a quantity of text within the particular document; determining, by the at least one of the one or more server devices, whether the measure of image intent satisfies a threshold, the threshold being identified by the classification metrics; generating, by at least one of the one or more server devices, a search results document that selectively includes the image results or the search results based on whether the measure of image intent satisfies the threshold; and providing, to the client, the search results document.

1. A method, comprising: receiving, by at least one of one or more server devices and from a client, a search query; obtaining, by at least one of the one or more server devices, search results based on the search query, the search results identifying documents relevant to the search query; identifying, by at least one of the one or more server devices, image attributes associated with one or more of the documents, the image attributes identifying information, within the one or more of the documents, associated with images; obtaining, by at least one of the one or more server devices, classification metrics that include information for determining a measure of image intent associated with the search query, the measure of image intent representing a likelihood that image results are intended by the search query, the image results identifying images or video relevant to the search query, and the classification metrics identifying a plurality of keywords; determining, by at least one of the one or more server devices, the measure of image intent, associated with the search query, based on the image attributes and the classification metrics, the image attributes, for a particular document of the one or more of the documents, corresponding to at least one of: a particular quantity of keywords, within the particular document, that match the plurality of keywords identified by the classification metrics, or a particular keyword density based on the particular quantity of keywords and a quantity of text within the particular document; determining, by the at least one of the one or more server devices, whether the measure of image intent satisfies a threshold, the threshold being identified by the classification metrics; generating, by at least one of the one or more server devices, a search results document that selectively includes the image results or the search results based on whether the measure of image intent satisfies the threshold; and providing, to the client, the search results document. 3. The method of claim 1 , where the search results include links via which the documents can be accessed, where the documents correspond to web pages associated with the links, and where the image results are associated with at least one of: images that are relevant to the search query, or video content that is relevant to the search query.

3. The method of claim 2 , further comprising: installing, by one or more processors, the revised policy in a database server that manages the particular database.

3. The method of claim 2 , further comprising: installing, by one or more processors, the revised policy in a database server that manages the particular database. 4. The method of claim 3 , further comprising: identifying, by one or more processors, a syntax that is supported by the database server; and performing, by one or more processors, said parsing of the sample database query statement using the syntax that is supported by the database server.

1. An interactive robot capable of speech recognition, comprising: a sound-source-direction estimating unit that estimates a direction of a sound source for target voices which are required to undergo speech recognition; a moving unit that moves the interactive robot in the sound-source direction; a target-voice acquiring unit that acquires the target voices at a position after moving; a target-voice holding unit that holds voice patterns of the target voices, the target voices including misrecognition-notification voices signifying that speech recognition by the speech recognizing unit is erroneous; a speech recognizing unit that performs speech recognition of the target voices by pattern matching of the voice patterns of the target voices, which are held in the target-voice holding unit, with the target voices acquired by the target-voice acquiring unit; a recognition-accuracy evaluating unit that calculates, as an accuracy of recognition results, an agreement accuracy between the acquired target voices and the voice patterns of the target voices held in the target-voice holding unit; wherein the moving unit moves the interactive robot itself in the direction of the sound source when the recognition accuracy for results of speech recognition of the target voices is smaller than a predetermined recognition-accuracy threshold and when the misrecognition-notification voices held in the target-voice holding unit are recognized.

1. An interactive robot capable of speech recognition, comprising: a sound-source-direction estimating unit that estimates a direction of a sound source for target voices which are required to undergo speech recognition; a moving unit that moves the interactive robot in the sound-source direction; a target-voice acquiring unit that acquires the target voices at a position after moving; a target-voice holding unit that holds voice patterns of the target voices, the target voices including misrecognition-notification voices signifying that speech recognition by the speech recognizing unit is erroneous; a speech recognizing unit that performs speech recognition of the target voices by pattern matching of the voice patterns of the target voices, which are held in the target-voice holding unit, with the target voices acquired by the target-voice acquiring unit; a recognition-accuracy evaluating unit that calculates, as an accuracy of recognition results, an agreement accuracy between the acquired target voices and the voice patterns of the target voices held in the target-voice holding unit; wherein the moving unit moves the interactive robot itself in the direction of the sound source when the recognition accuracy for results of speech recognition of the target voices is smaller than a predetermined recognition-accuracy threshold and when the misrecognition-notification voices held in the target-voice holding unit are recognized. 9. The interactive robot according to claim 1 , wherein the target voices are voices produced by an interlocutor communicating with the interactive robot, and the interactive robot further comprises an image acquiring unit that acquires images including the interlocutor as the sound source of the target voices; and a mouth-movement detecting unit that detects, from the images, mouth movement of the interlocutor, wherein the moving unit moves the interactive robot in the direction of the sound source when the mouth movement is not detected and the target voices are not acquired.

11. The system of claim 10 , the method comprising identifying one or more mislabeled pairs in a pre-existing relevance ranking.

11. The system of claim 10 , the method comprising identifying one or more mislabeled pairs in a pre-existing relevance ranking. 15. The system of claim 11 , the method comprising at least one of: determining a longest common subsequence (LCS) of one or more pairs that is decreasing in both the pre-existing relevance ranking and the click relevance ranking; or removing labels from one or more pairs which are not in the LCS.

21. The method of claim 16 , further comprising the step of creating one or more reports comprising the qualitative or quantitative assessments of the respective social media page.

21. The method of claim 16 , further comprising the step of creating one or more reports comprising the qualitative or quantitative assessments of the respective social media page. 22. The method of claim 21 , wherein the one or more reports comprise analytics representative of user interaction on the respective social media page.

11. A computing device for recognizing a received phoneme, the computing device comprising: a module configured to generate an expanded stored-phoneme vector from each of a plurality of class phonemes; a module configured to transform the expanded stored-phoneme vector into an orthogonal form associated with a hypersphere having a center and a radius; and a module configured to recognize a received phoneme by generating an expanded received-signal vector associated with the received phoneme into an orthogonal form for analysis in the hypersphere.

11. A computing device for recognizing a received phoneme, the computing device comprising: a module configured to generate an expanded stored-phoneme vector from each of a plurality of class phonemes; a module configured to transform the expanded stored-phoneme vector into an orthogonal form associated with a hypersphere having a center and a radius; and a module configured to recognize a received phoneme by generating an expanded received-signal vector associated with the received phoneme into an orthogonal form for analysis in the hypersphere. 12. The computing device of claim 11 , wherein the module configured to generate the expanded stored phoneme vector from the class phoneme further: determines the phoneme vector as a time-frequency representation of the class phoneme; divides the phoneme vector into phoneme segments; assigns each phoneme segment into a plurality of phoneme parameters; and expands each phoneme segment and plurality of phoneme parameters into an expanded stored phoneme vector with expanded vector parameters.

2. The method of claim 1 , wherein obtaining the displayed text string comprises: extracting the text string from the user interface element annotation by executing the internationalize method, and the method further comprising: defining a name for a resource bundle to which the text string of the user interface element annotation may be extracted, wherein the defining is provided, at least in part, by a resource bundle annotation in the target computer program; and creating the resource bundle by a computer system executing an annotation processor program, wherein the executing annotation processor program processes source code of the target computer program, including processing the user interface element annotation and resource bundle annotation.

2. The method of claim 1 , wherein obtaining the displayed text string comprises: extracting the text string from the user interface element annotation by executing the internationalize method, and the method further comprising: defining a name for a resource bundle to which the text string of the user interface element annotation may be extracted, wherein the defining is provided, at least in part, by a resource bundle annotation in the target computer program; and creating the resource bundle by a computer system executing an annotation processor program, wherein the executing annotation processor program processes source code of the target computer program, including processing the user interface element annotation and resource bundle annotation. 4. The method of claim 2 , wherein obtaining the displayed text string directly from the text string of the user interface element annotation is in response to determining that the resource bundle does not exist.

5. The method of claim 4 , wherein the state machine definition provide the respective scripting functions having one or more tokens with script expressions included therein, the one or more tokens used in the state machine definition to indicate information that is unspecified at least in part in the state machine definition, and is determined during execution of the game engine module.

5. The method of claim 4 , wherein the state machine definition provide the respective scripting functions having one or more tokens with script expressions included therein, the one or more tokens used in the state machine definition to indicate information that is unspecified at least in part in the state machine definition, and is determined during execution of the game engine module. 6. The method of claim 5 , wherein parsing the respective scripting functions provided within the state machine definition includes parsing the respective scripting functions to obtain one or more expressions including one or more of a function to be performed on the particular graphical object, a literal expression, a geographically-specified text expression, or a property of the particular graphical object; and wherein the method includes: evaluating an expression obtained from the respective scripting functions; and in response, substituting the evaluated expression for the one or more tokens included in the state machine definition.

33. A method for detecting a violation of an email security policy of a computer system by transmission of selected email through said computer system, said computer system comprising a server and one more clients having an email account, the method comprising: (a) defining a model relating to transmission behavior of prior email transmitted by said email account derived from statistics relating to transmission behavior of prior emails transmitted by said email account, wherein defining the model comprises grouping email addresses in said prior emails into one or more cliques based on the occurrence of said email addresses in common prior emails; (b) gathering statistics relating to transmission behavior of said selected emails transmitted by said email account; (c) defining a model of said new email transmission behavior derived from said statistics; and (d) comparing said model of said new email transmission behavior and said model relating to prior email transmission behavior by said email account based on whether email addresses in said new email are members of more than one said clique.

33. A method for detecting a violation of an email security policy of a computer system by transmission of selected email through said computer system, said computer system comprising a server and one more clients having an email account, the method comprising: (a) defining a model relating to transmission behavior of prior email transmitted by said email account derived from statistics relating to transmission behavior of prior emails transmitted by said email account, wherein defining the model comprises grouping email addresses in said prior emails into one or more cliques based on the occurrence of said email addresses in common prior emails; (b) gathering statistics relating to transmission behavior of said selected emails transmitted by said email account; (c) defining a model of said new email transmission behavior derived from said statistics; and (d) comparing said model of said new email transmission behavior and said model relating to prior email transmission behavior by said email account based on whether email addresses in said new email are members of more than one said clique. 34. The method as recited in claim 33 , wherein defining a model relating to prior email comprises defining a model relating to statistics accumulated over a predetermined time period.

22. The computer of claim 21 , wherein the software causes the processor to control the in-degree and out-degree by trading off in-transitions for out-transitions in the automaton.

22. The computer of claim 21 , wherein the software causes the processor to control the in-degree and out-degree by trading off in-transitions for out-transitions in the automaton. 23. The computer of claim 22 , wherein the in-transitions for each state are limited to below a threshold number when unrolling.

6. A method for managing a graphical user interface in a computer-based system having an operating system, in response to a receipt of an activation request to open a selected dialog box, wherein all dialog boxes are logically related in a hierarchical manner based upon launch dependencies, the method comprising the steps of: (a) recursively closing all open child dialog boxes having a predetermined logical relationship with the selected dialog box; and (b) opening the selected dialog box.

6. A method for managing a graphical user interface in a computer-based system having an operating system, in response to a receipt of an activation request to open a selected dialog box, wherein all dialog boxes are logically related in a hierarchical manner based upon launch dependencies, the method comprising the steps of: (a) recursively closing all open child dialog boxes having a predetermined logical relationship with the selected dialog box; and (b) opening the selected dialog box. 15. The method of claim 6, further comprising the step of: (c) closing displayed parent dialog boxes of the selected dialog box.

3. The data analysis method of claim 2 , said method further comprising the step of establishing mappings between said reference range and a real value range of the data in the data warehouse if they are inconsistent with each other.

3. The data analysis method of claim 2 , said method further comprising the step of establishing mappings between said reference range and a real value range of the data in the data warehouse if they are inconsistent with each other. 4. The data analysis method of claim 3 , said method further comprising the step of generating a graphical representation of at least one of the selected entities, properties, values thereof, the defined measures, and the calculating results.

11. A method for analyzing documents, the method comprising: receiving a search criteria; identifying one or more documents responsive to the search criteria; determining a text match score for each document based on degree of match between the responsive document and the search criteria; determining a document-categories score for each of a plurality of categories based on a degree of match between each document and each of the categories; determining a search criteria-categories score for each of the one or more categories based on a degree of match between the search criteria and each of the one or more categories, wherein the search criteria-categories score for a particular category indicates the degree of match between the search criteria and the category; determining a category match score for each document by combining the document-categories score of each of the one or more categories and the respective search criteria-categories score; determining an overall score for each document based on the text match score of each document and the respective category match score; and determining, based on the overall score for each document, a ranked order for the one or more documents.

11. A method for analyzing documents, the method comprising: receiving a search criteria; identifying one or more documents responsive to the search criteria; determining a text match score for each document based on degree of match between the responsive document and the search criteria; determining a document-categories score for each of a plurality of categories based on a degree of match between each document and each of the categories; determining a search criteria-categories score for each of the one or more categories based on a degree of match between the search criteria and each of the one or more categories, wherein the search criteria-categories score for a particular category indicates the degree of match between the search criteria and the category; determining a category match score for each document by combining the document-categories score of each of the one or more categories and the respective search criteria-categories score; determining an overall score for each document based on the text match score of each document and the respective category match score; and determining, based on the overall score for each document, a ranked order for the one or more documents. 12. The method of claim 11 , wherein the search criteria is a search query comprising one or more query terms, and wherein the text match score indicates a quality of match between the query terms and each document, and wherein the search criteria-categories score indicates a quality of match between the query terms and each of the plurality of categories.

11. A method as claimed in claim 1 which comprises receiving user input adding an extension to the first community that extension being code which is available to all members of the first community.

11. A method as claimed in claim 1 which comprises receiving user input adding an extension to the first community that extension being code which is available to all members of the first community. 12. A method as claimed in claim 11 which comprises monitoring use of the extension and assigning reputation points to the extension on the basis of the monitored use.

1. A method for evaluation of data relevance, comprising: (a) generating a query; (b) receiving a topic-evaluation vector the topic-evaluation vector including a plurality of relevance determinations for a collection of data, each relevance determination in the plurality of relevance determinations pertaining to a topic; (c) comparing the topic-evaluation vector to the generated query; and (d) performing a resulting action based on the results of the comparison performed in step (c).

1. A method for evaluation of data relevance, comprising: (a) generating a query; (b) receiving a topic-evaluation vector the topic-evaluation vector including a plurality of relevance determinations for a collection of data, each relevance determination in the plurality of relevance determinations pertaining to a topic; (c) comparing the topic-evaluation vector to the generated query; and (d) performing a resulting action based on the results of the comparison performed in step (c). 2. The method of claim 1, further comprising: (e) receiving a topic dictionary, wherein the topic dictionary comprises information regarding where in the topic-evaluation vector certain topics are located.

2. A method, comprising: in a processor, defining one or more measurable science inquiry skills; in a computer, measuring the one or more science inquiry skills of a subject person, the measuring being in real-time and using at least one of an assessment model and a tracking model programmed to infer science inquiry skill demonstration from interactive engagement by the subject person with an environment comprised of at least one of a simulation and a microworld; providing to the subject person real-time feedback through the environment, the real-time feedback being based on the at least one of the assessment model and the tracking model; providing to the subject person guidance on how to better conduct scientific inquiry; and at least one of: evaluating and estimating proficiency at science inquiry of the subject person, by the assessment model or the tracking model, using at least one of a data-mining based algorithm and a knowledge-engineering based algorithm; providing a performance assessment of at least one or more aggregate science inquiry skills by measuring of the one or more science inquiry skills; and further providing to the subject person the real-time feedback through the environment, the real-time feedback being further based on at least one of: a knowledge-engineering based assessment model, a data-mining based assessment model, a knowledge-engineering based tracking model, and a data-mining based tracking model.

2. A method, comprising: in a processor, defining one or more measurable science inquiry skills; in a computer, measuring the one or more science inquiry skills of a subject person, the measuring being in real-time and using at least one of an assessment model and a tracking model programmed to infer science inquiry skill demonstration from interactive engagement by the subject person with an environment comprised of at least one of a simulation and a microworld; providing to the subject person real-time feedback through the environment, the real-time feedback being based on the at least one of the assessment model and the tracking model; providing to the subject person guidance on how to better conduct scientific inquiry; and at least one of: evaluating and estimating proficiency at science inquiry of the subject person, by the assessment model or the tracking model, using at least one of a data-mining based algorithm and a knowledge-engineering based algorithm; providing a performance assessment of at least one or more aggregate science inquiry skills by measuring of the one or more science inquiry skills; and further providing to the subject person the real-time feedback through the environment, the real-time feedback being further based on at least one of: a knowledge-engineering based assessment model, a data-mining based assessment model, a knowledge-engineering based tracking model, and a data-mining based tracking model. 12. The method of claim 2 , wherein the general science inquiry skills are engineering skills.

1. A method for prefetching at a proxy server based on root node identification for a requested HTTP object at the proxy server, the method comprising: receiving a request for an HTTP object; determining, using a computing system, a plurality of candidate root nodes for the requested HTTP object, each candidate root node comprising an object that may have caused the request for the HTTP object; for each candidate root node: determining a likelihood that the respective candidate root node is the root node that caused the request for the HTTP object, and associating, at the computing system proxy server, the determined likelihood with the candidate root node; selecting one of the candidate root nodes from the plurality of candidate root nodes based on the determined likelihoods for each of the candidate root nodes; and establishing the selected candidate root node as the root node for the requested HTTP object.

1. A method for prefetching at a proxy server based on root node identification for a requested HTTP object at the proxy server, the method comprising: receiving a request for an HTTP object; determining, using a computing system, a plurality of candidate root nodes for the requested HTTP object, each candidate root node comprising an object that may have caused the request for the HTTP object; for each candidate root node: determining a likelihood that the respective candidate root node is the root node that caused the request for the HTTP object, and associating, at the computing system proxy server, the determined likelihood with the candidate root node; selecting one of the candidate root nodes from the plurality of candidate root nodes based on the determined likelihoods for each of the candidate root nodes; and establishing the selected candidate root node as the root node for the requested HTTP object. 2. The method of claim 1 wherein identifying a plurality of candidate root nodes comprises identifying a first node of the plurality of candidate root nodes from a referrer tag as a first potential candidate root node.

1. A method for expansion of search queries on large vocabulary continuous speech recognition transcripts comprising: obtaining a textual transcript of audio interaction generated by the large vocabulary continuous speech recognition; generating a topic model from the textual transcripts; said topic model comprises a plurality of topics wherein each topic of the plurality of topics comprises a list of keywords; obtaining a search term; associating a topic from the topic model with the search term; and generating a list of candidate term expansion words by selecting keywords from the list of keywords of the associated topic; said candidate term expansion words are of high probability to be substitution errors of the search term that are generated by the large vocabulary continuous speech recognition.

1. A method for expansion of search queries on large vocabulary continuous speech recognition transcripts comprising: obtaining a textual transcript of audio interaction generated by the large vocabulary continuous speech recognition; generating a topic model from the textual transcripts; said topic model comprises a plurality of topics wherein each topic of the plurality of topics comprises a list of keywords; obtaining a search term; associating a topic from the topic model with the search term; and generating a list of candidate term expansion words by selecting keywords from the list of keywords of the associated topic; said candidate term expansion words are of high probability to be substitution errors of the search term that are generated by the large vocabulary continuous speech recognition. 5. The method according to claim 1 further comprises extracting the stem form of the keywords on the list of keywords.

7. The non-transitory computer-readable medium of claim 6 , wherein the YATL statement is selected from the group consisting of: a foreach-match statement, a match-once statement, a match statement, a foreach-element statement, a debug statement, a native statement, a print statement, a log statement, an express “on” statement, an isolated statement, a continue statement, a die statement, an “on” statement, a statement insertion statement, a layout insertion statement, an if statement, a while statement, a do while statement, a for statement, a delete statement, a transform decl statement, a transform use statement, a replace with statement, a return statement, a try catch statement, an either or statement, a fail statement, an on file statement, and a pointer declare statement.

7. The non-transitory computer-readable medium of claim 6 , wherein the YATL statement is selected from the group consisting of: a foreach-match statement, a match-once statement, a match statement, a foreach-element statement, a debug statement, a native statement, a print statement, a log statement, an express “on” statement, an isolated statement, a continue statement, a die statement, an “on” statement, a statement insertion statement, a layout insertion statement, an if statement, a while statement, a do while statement, a for statement, a delete statement, a transform decl statement, a transform use statement, a replace with statement, a return statement, a try catch statement, an either or statement, a fail statement, an on file statement, and a pointer declare statement. 18. The non-transitory computer-readable medium of claim 7 , wherein the YATL program includes a delete statement having “delete at” followed by a pointer dereference.

1. A computer-implemented method of presenting information to a user in which a computer system initiates execution of software instructions stored in memory, the computer-implemented method comprising: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers, after receiving an amount of the subsequently received numbers above a second predetermined threshold amount of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection.

1. A computer-implemented method of presenting information to a user in which a computer system initiates execution of software instructions stored in memory, the computer-implemented method comprising: receiving one or more ambiguous characters via a reduced-entry keypad of a wireless phone, the one or more ambiguous characters received as a sequence of numbers input through the reduced-entry keypad, each respective ambiguous character being a number that represents one of at least two disambiguated letters; exchanging at least one of the ambiguous characters with a host by transmitting the sequence of numbers to the host across a wireless network, exchanging the at least one of the ambiguous characters including exchanging the sequence of numbers upon receiving an amount of numbers in the sequence that meets an initial predetermined threshold amount of numbers, and exchanging subsequently received numbers, received as part of the sequence of numbers, after receiving an amount of the subsequently received numbers above a second predetermined threshold amount of numbers; receiving, from the host, results that represent disambiguated terms corresponding to the ambiguous characters exchanged with the host; rendering the results in a display of the wireless phone in a manner that enables identification of which of the disambiguated terms will be used upon a received selection of a displayed result; receiving, from the host, updated results that represent disambiguated terms corresponding to the subsequently received numbers exchanged with the host; rendering the updated results in the display of the wireless phone; and in response to receiving a selection of one of the disambiguated terms, displaying information corresponding to the selection. 5. The computer-implemented method of claim 1 , wherein exchanging the at least one of the ambiguous characters with the host includes: transmitting updates to the host upon receiving the subsequently received numbers, the transmitting occurring after detecting that user inactivity in entering the sequence of numbers exceeds a predetermined period of time.

1. A method of incorporating at least user-supplied text into an electronic product design having a first content area containing one or more content elements, the method comprising receiving a plurality of user text entries, the plurality of text entries comprising at least one text entry being of a first horizontal alignment type and at least one text entry being of a second horizontal alignment type, determining a first height, the first height being the height of all received text entries of the first horizontal alignment type positioned in a vertical arrangement, and a second height, the second height being the height of all received text entries of the second horizontal alignment type positioned in a vertical arrangement, modifying the electronic product design by sizing a second content area outside the first content area according to the larger of the first and second heights, positioning the plurality of user text entries in the product design in the second content area, and resizing the first content area to accommodate the second content area in the electronic product design, determining an available text width in the second content area, partitioning the available text width into a first maximum justified text width and a second maximum justified text width, and justifying the one or more user text entries of the first horizontal alignment type according to the first horizontal alignment type, wrapping such text entries as exceed the first maximum justified text width, and justifying the one or more user text entries of the second horizontal alignment type according to the second horizontal alignment type, wrapping such text entries as exceed the second maximum justified text width.

1. A method of incorporating at least user-supplied text into an electronic product design having a first content area containing one or more content elements, the method comprising receiving a plurality of user text entries, the plurality of text entries comprising at least one text entry being of a first horizontal alignment type and at least one text entry being of a second horizontal alignment type, determining a first height, the first height being the height of all received text entries of the first horizontal alignment type positioned in a vertical arrangement, and a second height, the second height being the height of all received text entries of the second horizontal alignment type positioned in a vertical arrangement, modifying the electronic product design by sizing a second content area outside the first content area according to the larger of the first and second heights, positioning the plurality of user text entries in the product design in the second content area, and resizing the first content area to accommodate the second content area in the electronic product design, determining an available text width in the second content area, partitioning the available text width into a first maximum justified text width and a second maximum justified text width, and justifying the one or more user text entries of the first horizontal alignment type according to the first horizontal alignment type, wrapping such text entries as exceed the first maximum justified text width, and justifying the one or more user text entries of the second horizontal alignment type according to the second horizontal alignment type, wrapping such text entries as exceed the second maximum justified text width. 7. The method of claim 1 , wherein resizing of the first content area comprises cropping at least one of the content elements in the first content area.

6. The method of claim 1 , further comprising determining whether at least one of the voice units conforms to at least one pronunciation error pattern.

6. The method of claim 1 , further comprising determining whether at least one of the voice units conforms to at least one pronunciation error pattern. 7. The method of claim 6 , further comprising determining a correction action according to the pronunciation error pattern when a specific voice unit within the voice units conforms to the pronunciation error pattern.

1. A method of operating an application service to enhance document productivity, the method comprising: identifying an attempt to add a data connection in a document; in response to identifying the attempt to add the data connection in the document, identifying at least one other document as relevant to the attempt; and communicating a suggestion that identifies at least a portion of the other document for surfacing in a user interface to the application service.

1. A method of operating an application service to enhance document productivity, the method comprising: identifying an attempt to add a data connection in a document; in response to identifying the attempt to add the data connection in the document, identifying at least one other document as relevant to the attempt; and communicating a suggestion that identifies at least a portion of the other document for surfacing in a user interface to the application service. 5. The method of claim 1 further comprising identifying an attempt to add a query in the document, responsively identifying at least one other query as relevant, and communicate another suggestion that identifies at least the one other query for surfacing in the user interface to the application service.

1. A computer-implemented method employing at least one hardware implemented computer processor for performing cepstral mean normalization (CMN) in automatic speech recognition comprising: storing a current CMN function in a computer memory as a previous CMN function; updating the current CMN function based on a current audio input to produce an updated CMN function; using the updated CMN function to process the current audio input to produce a processed audio input; attempting to perform automatic speech recognition of the processed audio input to determine representative text; if the processed audio input is not recognized as representative text, replacing the updated CMN function with the previous CMN function.

1. A computer-implemented method employing at least one hardware implemented computer processor for performing cepstral mean normalization (CMN) in automatic speech recognition comprising: storing a current CMN function in a computer memory as a previous CMN function; updating the current CMN function based on a current audio input to produce an updated CMN function; using the updated CMN function to process the current audio input to produce a processed audio input; attempting to perform automatic speech recognition of the processed audio input to determine representative text; if the processed audio input is not recognized as representative text, replacing the updated CMN function with the previous CMN function. 3. A method according to claim 1 , wherein the process is performed in real time with minimal response latency.

3. The method of claim 1 , wherein the menu structure is populated with information from documents stored on the front-end computer based on a parameter conversion, wherein the parameter conversion converts tokens to different text for data object functions.

3. The method of claim 1 , wherein the menu structure is populated with information from documents stored on the front-end computer based on a parameter conversion, wherein the parameter conversion converts tokens to different text for data object functions. 4. The method of claim 3 , wherein the menu structure is received if textual information to be displayed with the menu is not available at that time.

1. A computer-implemented method for mapping a first schema to a second schema, the method comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema.

1. A computer-implemented method for mapping a first schema to a second schema, the method comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema. 7. The method of claim 1 , wherein generating the new name for each first data element definition comprises: receiving a human-understandable description of a specific first data element definition for which a new name is to be created, the new name complying with a predefined name format that is same as a predefined name format of the second names; identifying a noun phrase and a verb phrase in the human-understandable description; and generating the new name using a first noun obtained from the noun phrase and a second noun obtained from the verb phrase.

8. The method of claim 1 , wherein the navigation key is selected from an enter key, a tab key, a space key, a right arrow key, a left arrow key and combinations thereof.

8. The method of claim 1 , wherein the navigation key is selected from an enter key, a tab key, a space key, a right arrow key, a left arrow key and combinations thereof. 10. The method of claim 8 , wherein the space key is a prompt for a multi-term entry.

6. The server according to claim 5 , wherein the approval request history storage unit is configured to further store an approval flag indicative of eligibility for approval that was received from the approver client, and a time of approval indicative of a time at which the approval was made, the display information generation unit is configured to send to a display screen of the one or more of the request-source client and the one or more other clients at least one of an approved translation word display window displaying translation word approval request information that was approved at or prior to a predetermined time period, a newly arrived approved translation word display window displaying translation word approval request information that was approved past the predetermined time period, a request-pending translation word display window displaying translation word approval request information that is yet to be approved, and a rejected translation word display window displaying translation word approval request information that has been rejected on the display screen of the one or more of the request-source client and the one or more other clients, in accordance with the approval flag and the time of approval.

6. The server according to claim 5 , wherein the approval request history storage unit is configured to further store an approval flag indicative of eligibility for approval that was received from the approver client, and a time of approval indicative of a time at which the approval was made, the display information generation unit is configured to send to a display screen of the one or more of the request-source client and the one or more other clients at least one of an approved translation word display window displaying translation word approval request information that was approved at or prior to a predetermined time period, a newly arrived approved translation word display window displaying translation word approval request information that was approved past the predetermined time period, a request-pending translation word display window displaying translation word approval request information that is yet to be approved, and a rejected translation word display window displaying translation word approval request information that has been rejected on the display screen of the one or more of the request-source client and the one or more other clients, in accordance with the approval flag and the time of approval. 7. The server according to claim 6 , further comprising an operation information reception unit configured to receive operation information from the one or more of the request-source client and the one or more other clients, the operation information including input information that is input in the one or more of the request-source client and the one or more other clients, wherein the display information generation unit is configured to send information for displaying, to the display screen of the one or more of the request-source client and the one or more other clients, an original display window displaying an original text which should be translated by an operator of the one or more of the request-source client and the one or more other clients using the original text within the assignment range and a translation display window displaying a translated text which is a result of translation of the original text in accordance with the received operation information.

8. A method for disambiguating lexemes in text-to-speech processing comprising: loading a set of disambiguation rules for use in a text disambiguation engine of a text-to-speech system, wherein the disambiguation rules include a plurality of entries that define usage senses for lexemes, wherein each usage sense for each of the entries comprises: at least one conditional statement that defines a sense of usage for a lexeme; and a significance indicator associated with the conditional statement, wherein the significance indicator defines a criteria for selecting an associated sense of usage and wherein the at least one conditional statement includes a context range specification, wherein the set of disambiguation rules includes a first conditional statement for determining a sense of usage of a lexeme as an acronym and a second conditional statement for determining a sense of usage of the lexeme as a word, wherein the first conditional statement and/or the second conditional statement distinguishes between the sense of usage of the lexeme as an acronym and the sense of usage of the lexeme as a word at least in part by requiring a specified word within a specified context range of words of the lexeme; identifying, by the text disambiguation engine of the text-to-speech system, an ambiguous lexeme in a text input string; obtaining, by the text disambiguation engine of the text-to-speech system, the entry in the disambiguation rules that pertains to the identified lexeme, wherein the entry comprises at least one usage sense; determining, by the text disambiguation engine of the text-to-speech system, an applicable one of said at least one usage sense for the identified lexeme based upon an evaluation of the disambiguation rules associated with said at least one usage sense; and in response to determining a usage sense corresponding to the lexeme used as an acronym, replacing the lexeme with a defined full text equivalent.

8. A method for disambiguating lexemes in text-to-speech processing comprising: loading a set of disambiguation rules for use in a text disambiguation engine of a text-to-speech system, wherein the disambiguation rules include a plurality of entries that define usage senses for lexemes, wherein each usage sense for each of the entries comprises: at least one conditional statement that defines a sense of usage for a lexeme; and a significance indicator associated with the conditional statement, wherein the significance indicator defines a criteria for selecting an associated sense of usage and wherein the at least one conditional statement includes a context range specification, wherein the set of disambiguation rules includes a first conditional statement for determining a sense of usage of a lexeme as an acronym and a second conditional statement for determining a sense of usage of the lexeme as a word, wherein the first conditional statement and/or the second conditional statement distinguishes between the sense of usage of the lexeme as an acronym and the sense of usage of the lexeme as a word at least in part by requiring a specified word within a specified context range of words of the lexeme; identifying, by the text disambiguation engine of the text-to-speech system, an ambiguous lexeme in a text input string; obtaining, by the text disambiguation engine of the text-to-speech system, the entry in the disambiguation rules that pertains to the identified lexeme, wherein the entry comprises at least one usage sense; determining, by the text disambiguation engine of the text-to-speech system, an applicable one of said at least one usage sense for the identified lexeme based upon an evaluation of the disambiguation rules associated with said at least one usage sense; and in response to determining a usage sense corresponding to the lexeme used as an acronym, replacing the lexeme with a defined full text equivalent. 12. The method of claim 8 , further comprising: performing an action defined by the determined usage sense.

2. The server of claim 1 wherein said server includes a web request controller structured to receive asynchronous requests over a wide area network such as the internet from a client computer running a web browser, and wherein some resource types are related to other resource types and wherein said rules of syntax require a first search on a nesting level below a next preceding nesting level to specify a resource type which is related to said resource type specified in a first search on said next preceding nesting level, and wherein said rules of syntax require said first search on a nesting level below said next preceding nesting level to only search configuration or performance metric data gathered during said relevant interval of instances of said related resource type which are related to instances of said resource type specified in said first search on said next preceding nesting level whose configuration or performance metric data met a filter or matching criteria of a last search on said next preceding nesting level.

2. The server of claim 1 wherein said server includes a web request controller structured to receive asynchronous requests over a wide area network such as the internet from a client computer running a web browser, and wherein some resource types are related to other resource types and wherein said rules of syntax require a first search on a nesting level below a next preceding nesting level to specify a resource type which is related to said resource type specified in a first search on said next preceding nesting level, and wherein said rules of syntax require said first search on a nesting level below said next preceding nesting level to only search configuration or performance metric data gathered during said relevant interval of instances of said related resource type which are related to instances of said resource type specified in said first search on said next preceding nesting level whose configuration or performance metric data met a filter or matching criteria of a last search on said next preceding nesting level. 3. The server of claim 2 wherein said memory stores said Unicode characters representing said performance metric data numerical values in a special data structure comprising a single directory for storing each day's data, said directory having a name, said name having the date of said day in said name, each said directory having a separate subdirectory for each instance of a resource type, each said subdirectory having files therein each of which store one or more of said time series of Unicode characters, each said time series of Unicode characters representing one time series of performance metric data numerical values measured or gathered over said time slots of one day from one attribute of said instance of said resource to which said subdirectory is devoted, each said file storing a group of time series of Unicode characters representing a group of time series of performance metric numerical values for a group of attributes of said resource instance to which said subdirectory is devoted, each said time series of Unicode characters stored in a separate section of said file having a number of storage locations equal to the number of timeslots in a day with one Unicode character stored per storage location, and wherein said storage location of each said Unicode character maps to said time slot during which said performance metric data numerical value which was mapped to said Unicode character stored therein was gathered or measured.

4. The method of claim 1 wherein the information indicative of dialog turns between the application and the at least one user includes recorded audio having expected audio that was received by the application when the application was expecting a response and unexpected audio that was received by the application when the application was not expecting a response.

4. The method of claim 1 wherein the information indicative of dialog turns between the application and the at least one user includes recorded audio having expected audio that was received by the application when the application was expecting a response and unexpected audio that was received by the application when the application was not expecting a response. 5. The method of claim 4 , and further comprising isolating the expected audio and unexpected audio to form an actual response provided by the user, the actual response including both the expected audio and the unexpected audio.

1. A method for searching a datastore of data objects, the method comprising; receiving a search query; identifying, by a computer from the datastore of data objects, a first data object that matches the search query; generating a first sentence that includes a subject, verb and object, the object of the first sentence representing the first data object, the subject of the first sentence representing a second data object from the datastore that is related to the first data object; generating a second sentence that includes a subject, verb and object, the object of the second sentence representing the second data object, the subject of the second sentence representing a third data object from the datastore that is related to the second data object; and outputting information corresponding to a user interface based on the first sentence and the second sentence, the first sentence and the second sentence organized in the user interface as a hierarchy of sentences that includes a plurality of levels, wherein the first sentence is in a subordinate level of the hierarchy and the second sentence is in a superior level of the hierarchy.

1. A method for searching a datastore of data objects, the method comprising; receiving a search query; identifying, by a computer from the datastore of data objects, a first data object that matches the search query; generating a first sentence that includes a subject, verb and object, the object of the first sentence representing the first data object, the subject of the first sentence representing a second data object from the datastore that is related to the first data object; generating a second sentence that includes a subject, verb and object, the object of the second sentence representing the second data object, the subject of the second sentence representing a third data object from the datastore that is related to the second data object; and outputting information corresponding to a user interface based on the first sentence and the second sentence, the first sentence and the second sentence organized in the user interface as a hierarchy of sentences that includes a plurality of levels, wherein the first sentence is in a subordinate level of the hierarchy and the second sentence is in a superior level of the hierarchy. 3. The method of claim 1 , wherein generating the second sentence comprises generating the second sentence to include a verb that indicates a relationship between the second and third data objects.

1. A method of presenting computer-generated search result information, comprising: receiving a search request from a first user; obtaining a plurality of search results, wherein each search result identifies a respective search result document responsive to the search request; determining an initial ranking of the plurality of search results; determining that one or more particular web notebooks each have a respective title that matches the search request and that a particular search result document corresponding to a particular search result has document content related to respective notebook content in the one or more particular web notebooks of a plurality of web notebooks, wherein each web notebook has an author, the first user is not the author of any of the one or more particular web notebooks, and the related notebook content in each of the plurality of web notebooks includes web clippings taken by the author of the respective web notebook, wherein each of the web clippings is a snippet or a portion of a web document added to the respective web notebook by the author of the respective web notebook; modifying the ranking of the plurality of search results including modifying the ranking of the particular search result based on a web notebook based ranker and using the content from the one or more particular web notebooks; and providing a response to the search request including the plurality of search results for presentation in an order based on the modified ranking.

1. A method of presenting computer-generated search result information, comprising: receiving a search request from a first user; obtaining a plurality of search results, wherein each search result identifies a respective search result document responsive to the search request; determining an initial ranking of the plurality of search results; determining that one or more particular web notebooks each have a respective title that matches the search request and that a particular search result document corresponding to a particular search result has document content related to respective notebook content in the one or more particular web notebooks of a plurality of web notebooks, wherein each web notebook has an author, the first user is not the author of any of the one or more particular web notebooks, and the related notebook content in each of the plurality of web notebooks includes web clippings taken by the author of the respective web notebook, wherein each of the web clippings is a snippet or a portion of a web document added to the respective web notebook by the author of the respective web notebook; modifying the ranking of the plurality of search results including modifying the ranking of the particular search result based on a web notebook based ranker and using the content from the one or more particular web notebooks; and providing a response to the search request including the plurality of search results for presentation in an order based on the modified ranking. 2. The method of claim 1 , wherein determining that the particular search result document has document content related to respective notebook content in one or more particular web notebooks comprises: determining that at least one of a title, a heading, clipped content, metadata or a user-annotation in the one or more particular web notebooks relates to the particular search result document.

12. The method of claim 11 comprising comparing the at least one digital signal to at least one reference standard that includes at least one known vocabulary.

12. The method of claim 11 comprising comparing the at least one digital signal to at least one reference standard that includes at least one known vocabulary. 13. The method of claim 12 , comprising evaluating the at least one voice interaction which includes matching the at least one digital signal to at least one of words and phrases contained in the at least one reference standard.

12. The humanoid robot of claim 2 , wherein a first communication channel is a channel for receiving visual messages and a second communication channel is a channel for sending sound messages and in that said control module is able to evaluate the confidence level of the understanding by said robot of a first message received on said first channel and to generate at least one second message on said second channel whose content depends on said confidence level.

12. The humanoid robot of claim 2 , wherein a first communication channel is a channel for receiving visual messages and a second communication channel is a channel for sending sound messages and in that said control module is able to evaluate the confidence level of the understanding by said robot of a first message received on said first channel and to generate at least one second message on said second channel whose content depends on said confidence level. 13. The humanoid robot of claim 12 , wherein the first channel comprises a filter for recognizing images of the messages received by a list of expressions with each of which is associated an expected recognition rate and in that the content of said second message is chosen by a heuristic from a group of requests comprising a request for repetition of said first message on the first channel, a request for confirmation by a third message to be sent by the interlocutor on a third channel for receiving sound messages of a subset of the expressions of the filter, and a request for sending by the interlocutor of at least another message on at least a fourth channel.

2. A contextual rendering system, comprising: circuitry configured to at least: parse at least one graphics file into a plurality of graphics objects; determine whether one or more dynamic behavior attributes are present for each graphics object; extract at least one tag name for each graphics object having the one or more dynamic behavior attributes; assign an attribute weight to each dynamic behavior attribute; compute a sum of the attribute weights for each tag name-graphics object combination as Score_OT; sort the plurality of graphics objects based on their respective location and respective Score_OT for each tag name; and compute a combined score for each tag name-graphics file combination as a summation of all Score_OTs for an associated tag name; rank each of the tag name-graphics file combinations according to the respective combined score; and display a portion of a graphics view of one or more graphics objects for a first-ranked tag name-graphics file combination in context with other graphics objects.

2. A contextual rendering system, comprising: circuitry configured to at least: parse at least one graphics file into a plurality of graphics objects; determine whether one or more dynamic behavior attributes are present for each graphics object; extract at least one tag name for each graphics object having the one or more dynamic behavior attributes; assign an attribute weight to each dynamic behavior attribute; compute a sum of the attribute weights for each tag name-graphics object combination as Score_OT; sort the plurality of graphics objects based on their respective location and respective Score_OT for each tag name; and compute a combined score for each tag name-graphics file combination as a summation of all Score_OTs for an associated tag name; rank each of the tag name-graphics file combinations according to the respective combined score; and display a portion of a graphics view of one or more graphics objects for a first-ranked tag name-graphics file combination in context with other graphics objects. 3. The contextual rendering system of claim 2 , wherein the circuitry is further configured to: display the portion of the graphics view according to a display area size of a rendering device.

1. A method of recommending a short message recipient, comprising steps of: detecting an operation to add short message recipient by a user; receiving a text of a new short message currently edited by the user in response to detecting the operation to add the short message recipient; cutting words of the text of the new short message to generate a list of words; identifying a critical object in a new short message text of the user; analyzing an association between the critical object and the contacts by using a crucial object association database; recommending a short message recipient to the user according to a strength of association; parsing history short messages of the user to generate the data associated with the contacts; and constructing the critical object association data using the data, wherein the analyzing an association is based on a weight W(a i ) of the critical object with respect to a contact p j in the critical object association data base and weight W(a i )′ of the critical object with respect to the new short message text, and wherein the analyzing the association further comprises calculating a vector product of the W(a i ) and the W(a i )′ to obtain a strength of association between the critical object of the new short message text and the contact p i and wherein constructing the critical object association database by using the data comprises: extracting identification information corresponding to at least one word in the list of words of the history short message; inquiring about whether or not there exists identification information of the contact corresponding to the history short message in the critical object association database; and if the result of the inquiry is No, adding to the critical object association database the identification information of the contact and associating the identification information of the at least one word and the index information of the at least one word with the identification information of the contact.

1. A method of recommending a short message recipient, comprising steps of: detecting an operation to add short message recipient by a user; receiving a text of a new short message currently edited by the user in response to detecting the operation to add the short message recipient; cutting words of the text of the new short message to generate a list of words; identifying a critical object in a new short message text of the user; analyzing an association between the critical object and the contacts by using a crucial object association database; recommending a short message recipient to the user according to a strength of association; parsing history short messages of the user to generate the data associated with the contacts; and constructing the critical object association data using the data, wherein the analyzing an association is based on a weight W(a i ) of the critical object with respect to a contact p j in the critical object association data base and weight W(a i )′ of the critical object with respect to the new short message text, and wherein the analyzing the association further comprises calculating a vector product of the W(a i ) and the W(a i )′ to obtain a strength of association between the critical object of the new short message text and the contact p i and wherein constructing the critical object association database by using the data comprises: extracting identification information corresponding to at least one word in the list of words of the history short message; inquiring about whether or not there exists identification information of the contact corresponding to the history short message in the critical object association database; and if the result of the inquiry is No, adding to the critical object association database the identification information of the contact and associating the identification information of the at least one word and the index information of the at least one word with the identification information of the contact. 6. The method according to claim 1 , wherein the identifying a critical object in a new short message text of the user further comprises: identifying a critical object in a new short message text of the user by calculating importance of at least one word in the list of words in the new short message text and importance of at least one word in the list of words to contacts contained in the critical object association database.

10. A computer implemented method of secure generation and transmission, over a communication network, of data, the method comprising: generating, by a data security server system, a key based on a passphrase received from a user; receiving, by the data security server system, a query from the user; retrieving, by the data security server system, raw data from a data repository based on the received query; generating, by the data security server system, an obfuscated query based on the received query and the generated key; randomizing, by the data security server system, at least one of a table and a field of the raw data based on the generated key to produce a randomized schema; pre-processing, by the data security server system, the raw data based on the received query, wherein the pre-processing does not exceed a user-defined threshold of execution of the received query; inserting, by the data security server system, the preprocessed data into the randomized schema; and generating, by the data security server system, a data payload by inserting the obfuscated query and the randomized schema into a data carrier, wherein the data payload is to be transferred to at least one client device for processing and wherein the data carrier comprises one or more data packets.

10. A computer implemented method of secure generation and transmission, over a communication network, of data, the method comprising: generating, by a data security server system, a key based on a passphrase received from a user; receiving, by the data security server system, a query from the user; retrieving, by the data security server system, raw data from a data repository based on the received query; generating, by the data security server system, an obfuscated query based on the received query and the generated key; randomizing, by the data security server system, at least one of a table and a field of the raw data based on the generated key to produce a randomized schema; pre-processing, by the data security server system, the raw data based on the received query, wherein the pre-processing does not exceed a user-defined threshold of execution of the received query; inserting, by the data security server system, the preprocessed data into the randomized schema; and generating, by the data security server system, a data payload by inserting the obfuscated query and the randomized schema into a data carrier, wherein the data payload is to be transferred to at least one client device for processing and wherein the data carrier comprises one or more data packets. 14. The method as claimed in claim 10 , wherein the method further comprises: generating, by the data security server system, a master script template, wherein the master script template is indicative of the query which is to be executed by the at least one of the client user and the client device, the document protection rules to be implemented by the at least one of the client user and the client device, and the intrusion detection rules to be implemented by the at least one of the client user and the client device; and inserting, by the data security server system, the master script template to the data payload.

1. A computer system for facilitating sales of a product to a user, the computer system comprising: a user interface configured to query the user regarding product interests of the user; a selection device operatively connected to the user interface, and configured to present a customized proposal to the user based on the user's product interests; an active database operatively connected to the selection device, and configured to store the user's product interests; a report database operatively connected to the selection device, and configured to store a plurality of page layouts; a static database operatively connected to the selection device, and configured to store product information; a difference database operatively connected to the static database, wherein the difference database stores update information configured for transmittal to the static database; and a report generator operatively connected to the active database, the report database, the selection device, and the static database, and configured to link page layout identifiers with particular data that appear in the customized proposal, wherein the customized proposal includes at least one item based upon the user's product interests, and wherein the at least one item includes at least one of: a product picture, an environment picture, and a text portion.

1. A computer system for facilitating sales of a product to a user, the computer system comprising: a user interface configured to query the user regarding product interests of the user; a selection device operatively connected to the user interface, and configured to present a customized proposal to the user based on the user's product interests; an active database operatively connected to the selection device, and configured to store the user's product interests; a report database operatively connected to the selection device, and configured to store a plurality of page layouts; a static database operatively connected to the selection device, and configured to store product information; a difference database operatively connected to the static database, wherein the difference database stores update information configured for transmittal to the static database; and a report generator operatively connected to the active database, the report database, the selection device, and the static database, and configured to link page layout identifiers with particular data that appear in the customized proposal, wherein the customized proposal includes at least one item based upon the user's product interests, and wherein the at least one item includes at least one of: a product picture, an environment picture, and a text portion. 14. The computer system of claim 1 , wherein the at least one item based upon the user's product interests includes a product picture, an environment picture, and a text portion.

5. The method of claim 1 , wherein said identifying of evidence further comprises: determining boundaries for said evidence in said at least one content resource.

5. The method of claim 1 , wherein said identifying of evidence further comprises: determining boundaries for said evidence in said at least one content resource. 6. The method of claim 5 , further comprising using said at least one hardware processor for dividing said text of said at least one content resource into sentences.

1. A method for routing confirmation of receipt and/or delivery of a facsimile, the method comprising: generating text of a facsimile in a computer readable format; ascertaining one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyzing the text for at least one of a meaning and a context of the text; initiating a business process; generating a notification of a problem with the initiated business process in response to determining the problem exists; notifying one or more entities of the problem; and routing at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the routing utilizes an outgoing communication device, and wherein the business process is initiated based at least in part on the analysis.

1. A method for routing confirmation of receipt and/or delivery of a facsimile, the method comprising: generating text of a facsimile in a computer readable format; ascertaining one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyzing the text for at least one of a meaning and a context of the text; initiating a business process; generating a notification of a problem with the initiated business process in response to determining the problem exists; notifying one or more entities of the problem; and routing at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the routing utilizes an outgoing communication device, and wherein the business process is initiated based at least in part on the analysis. 2. The method as recited in claim 1 , wherein the analysis further includes matching one or more of the located keywords to data stored in memory.

9. A method for providing a natural language assessment of relative color quality between a series of reference images from video images and a series of source images from video images, the method comprising: determining, via a moving image color appearance model, a color comparison difference measurement between selected ones of the reference images and a corresponding source image of the series of source images, wherein the color comparison difference measurement is within a region of interest in space and/or time; accepting, at a processor and from the moving image color appearance model, an input of the color comparison difference measurement; converting, via the processor, the color comparison difference measurement to a two-dimensional color space difference; determining, via the processor, a color attribute change based on the two-dimensional color space difference; determining, via the processor, a magnitude of the color attribute change; mapping, via the processor, the magnitude of the color attribute change to one of a collection of natural language words; generating, via the processor, from the mapped magnitude, and from the two-dimensional color space difference, the natural language assessment; outputting, via the processor, the natural language assessment.

9. A method for providing a natural language assessment of relative color quality between a series of reference images from video images and a series of source images from video images, the method comprising: determining, via a moving image color appearance model, a color comparison difference measurement between selected ones of the reference images and a corresponding source image of the series of source images, wherein the color comparison difference measurement is within a region of interest in space and/or time; accepting, at a processor and from the moving image color appearance model, an input of the color comparison difference measurement; converting, via the processor, the color comparison difference measurement to a two-dimensional color space difference; determining, via the processor, a color attribute change based on the two-dimensional color space difference; determining, via the processor, a magnitude of the color attribute change; mapping, via the processor, the magnitude of the color attribute change to one of a collection of natural language words; generating, via the processor, from the mapped magnitude, and from the two-dimensional color space difference, the natural language assessment; outputting, via the processor, the natural language assessment. 10. The method providing a natural language assessment of relative color quality between a series of reference images and a series of source images of claim 9 , wherein the two-dimensional color space accords to CIECAM02.

2. The user interface of claim 1 , wherein the recognition display state is presented after receipt of the handwriting input and prior to receipt of a selection of the selected one of the recognition candidates and combination candidates and the prediction display state is presented after receipt of the selection.

2. The user interface of claim 1 , wherein the recognition display state is presented after receipt of the handwriting input and prior to receipt of a selection of the selected one of the recognition candidates and combination candidates and the prediction display state is presented after receipt of the selection. 3. The user interface of claim 2 , wherein when in the recognition display state the edit field displays the first recognition candidate as determined text.

1. One or more computer-readable storage media containing computer-executable instructions stored thereon, that when implemented by a computer, cause the computer to perform a method comprising: a) receiving a first image and a second image, at least a portion of the first image representing a first view of a scene and at least a portion of the second image representing a second view of the scene; b) determining a first image intensity function of the first image; c) determining a second image intensity function of the second image; d) determining a disparity map based on the first image and the second image; e) determining a cyclopean image based on the first image and the second image; f) determining an energy function including a matching likelihood, a color likelihood, and a stereo disparity likelihood based on the first image intensity function, the second image intensity function, the disparity map and the cyclopean image; g) optimizing the energy function to determine a segmentation state variable value for a plurality of pixels in a reference image, the reference image including the first image, the second image, or the cyclopean image, the segmentation state variable value indicating a segmentation layer of the pixel, the segmentation layer being a member of a group comprising a foreground layer and a background layer.

1. One or more computer-readable storage media containing computer-executable instructions stored thereon, that when implemented by a computer, cause the computer to perform a method comprising: a) receiving a first image and a second image, at least a portion of the first image representing a first view of a scene and at least a portion of the second image representing a second view of the scene; b) determining a first image intensity function of the first image; c) determining a second image intensity function of the second image; d) determining a disparity map based on the first image and the second image; e) determining a cyclopean image based on the first image and the second image; f) determining an energy function including a matching likelihood, a color likelihood, and a stereo disparity likelihood based on the first image intensity function, the second image intensity function, the disparity map and the cyclopean image; g) optimizing the energy function to determine a segmentation state variable value for a plurality of pixels in a reference image, the reference image including the first image, the second image, or the cyclopean image, the segmentation state variable value indicating a segmentation layer of the pixel, the segmentation layer being a member of a group comprising a foreground layer and a background layer. 2. The computer readable media of claim 1 , wherein determining a cyclopean image includes preventing movement of a matching path in a diagonal direction.

28. The translation device of claim 27 , wherein the translation request includes data to be translated in order for the network device to process the data to be translated for a routing or switching operation, the translation device further comprising: an identification module to identify a first data format associated with the received data and a second data format associated with the network device; and a translator to translate the received data corresponding to the first data format into translated data corresponding to the second data format, wherein the transmitter is configured to communicate the translated data to the network device.

28. The translation device of claim 27 , wherein the translation request includes data to be translated in order for the network device to process the data to be translated for a routing or switching operation, the translation device further comprising: an identification module to identify a first data format associated with the received data and a second data format associated with the network device; and a translator to translate the received data corresponding to the first data format into translated data corresponding to the second data format, wherein the transmitter is configured to communicate the translated data to the network device. 29. The device of claim 28 , wherein the receiver is configured to receive, via a network, the data formats corresponding to a plurality of data schemas from a network management device, the memory to store the data schemas to process translation requests received from the plurality of network devices.

15. The method of claim 10 , wherein the combining at least one set of candidate tags further comprises: assigning a factor weight to each set of the candidate tags from a particular factor; combining the sets of candidate tags in accordance to their factor weights; and assigning an importance score to each candidate tag in the overall recommendation list of candidate tags.

15. The method of claim 10 , wherein the combining at least one set of candidate tags further comprises: assigning a factor weight to each set of the candidate tags from a particular factor; combining the sets of candidate tags in accordance to their factor weights; and assigning an importance score to each candidate tag in the overall recommendation list of candidate tags. 16. The method of claim 15 , wherein adjusting the overall recommendation list of candidate tags further comprises: comparing the set of candidate tags from every factor with the set of tags applied by the user; and adjusting the factor weight of every factor based on the comparison.

7. The computer-implemented method of claim 6 , further comprising sorting the common candidate word and the geographic-related language candidate word based on a sorting factor of a candidate word.

7. The computer-implemented method of claim 6 , further comprising sorting the common candidate word and the geographic-related language candidate word based on a sorting factor of a candidate word. 9. The computer-implemented method of claim 7 , wherein the sorting factor further includes an association degree of application program environment information and a geographic position.

1. A computer method, comprising carrying out operations on a computer, the operations comprising: maintaining machine readable embodiments on a medium of a bipartite graph and a tripartite graph, the tripartite graph comprising a first plurality of nodes corresponding to labeled and unlabeled examples from source and target domains; a second plurality of nodes corresponding to features; and a first plurality of edges connecting the nodes corresponding to the features to the nodes corresponding to the examples according to whether the features appear in the examples or not; the bipartite graph comprising the first plurality of nodes corresponding to the examples; and a second plurality of edges connecting the examples, the edges being associated with indications that indicate whether connected examples are in a same domain or not; deriving labels for at least one target domain based on the tripartite and bipartite graphs; and presenting an embodiment of the labels as a result, wherein said deriving comprises: formulating an objective function based on said bipartite and tripartite graphs, said objective function encompassing smoothness and consistency constraints and providing label information in the target domain at least responsive to label information in the source domain; applying the objective function to the all examples, whether labeled or unlabeled, and all features in order to obtain at least one result relative to the unlabeled examples; minimizing the objective function to yield a label function; and providing output labels responsive to the label function.

1. A computer method, comprising carrying out operations on a computer, the operations comprising: maintaining machine readable embodiments on a medium of a bipartite graph and a tripartite graph, the tripartite graph comprising a first plurality of nodes corresponding to labeled and unlabeled examples from source and target domains; a second plurality of nodes corresponding to features; and a first plurality of edges connecting the nodes corresponding to the features to the nodes corresponding to the examples according to whether the features appear in the examples or not; the bipartite graph comprising the first plurality of nodes corresponding to the examples; and a second plurality of edges connecting the examples, the edges being associated with indications that indicate whether connected examples are in a same domain or not; deriving labels for at least one target domain based on the tripartite and bipartite graphs; and presenting an embodiment of the labels as a result, wherein said deriving comprises: formulating an objective function based on said bipartite and tripartite graphs, said objective function encompassing smoothness and consistency constraints and providing label information in the target domain at least responsive to label information in the source domain; applying the objective function to the all examples, whether labeled or unlabeled, and all features in order to obtain at least one result relative to the unlabeled examples; minimizing the objective function to yield a label function; and providing output labels responsive to the label function. 9. The method of claim 1 , wherein deriving comprises imposing at least one label consistency constraint on the graphs.

10. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions.

10. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions. 11. The one or more non-transitory machine-readable media of claim 10 , wherein generating the one or more temporary path expressions includes modifying the subset of the plurality of normalized path expressions to include information from the particular path expression.

14. A computer-readable storage medium storing computer program instructions for composing a collection of information, the computer program instructions when executed by a computer processor performing steps comprising: receiving a plurality of paper documents in an order, wherein receiving the plurality of paper documents includes receiving a first paper document and receiving a subsequent paper document; determining the order of the plurality of paper documents; responsive to the order of the plurality of paper documents determining whether the first paper document includes an indicium identifying a collection; responsive to determining that the first paper document includes an indicium, adding an electronic representation of the subsequent paper document to the collection identified by the indicium; and responsive to determining that the first paper document does not include an indicium, creating a new collection.

14. A computer-readable storage medium storing computer program instructions for composing a collection of information, the computer program instructions when executed by a computer processor performing steps comprising: receiving a plurality of paper documents in an order, wherein receiving the plurality of paper documents includes receiving a first paper document and receiving a subsequent paper document; determining the order of the plurality of paper documents; responsive to the order of the plurality of paper documents determining whether the first paper document includes an indicium identifying a collection; responsive to determining that the first paper document includes an indicium, adding an electronic representation of the subsequent paper document to the collection identified by the indicium; and responsive to determining that the first paper document does not include an indicium, creating a new collection. 23. The computer-readable storage medium of claim 14 , wherein adding the electronic representation of the subsequent paper document comprises: retrieving, from a storage device, the collection; modifying the retrieved collection to add the electronic representation of the subsequent paper document; and storing the modified collection.

42. A method comprising: determining, for a change to a node of a hierarchical data file subtree, whether applying a partial transformation file subtree corresponding to the hierarchical data file subtree will produce a third rendering file equivalent to a difference between a first rendering file created by applying a full transformation file on a full hierarchical data file prior to the change to the node and a second rendering file created by applying the full transformation file on the full hierarchical data file after the change to the node; and producing the third rendering file by applying a partial transformation file when it is determined that applying a partial transformation file on the changed hierarchical data file will produce a third rendering file equivalent to the difference.

42. A method comprising: determining, for a change to a node of a hierarchical data file subtree, whether applying a partial transformation file subtree corresponding to the hierarchical data file subtree will produce a third rendering file equivalent to a difference between a first rendering file created by applying a full transformation file on a full hierarchical data file prior to the change to the node and a second rendering file created by applying the full transformation file on the full hierarchical data file after the change to the node; and producing the third rendering file by applying a partial transformation file when it is determined that applying a partial transformation file on the changed hierarchical data file will produce a third rendering file equivalent to the difference. 43. The method of claim 42 , wherein the determining includes finding that there are no references in the partial transformation file subtree to parts outside of those subtrees.

1. A method comprising: automatically receiving an asset including content and metadata; automatically identifying a source metadata format of the metadata; automatically identifying a target metadata format; automatically selecting a data map to perform validation of the metadata and at least one of transforming or translating of the metadata based on the identifying of the source metadata format and the identifying of the target metadata format, wherein the transforming includes converting the metadata to the target metadata format and the translating includes converting a file type of the metadata to a target metadata file type; automatically attempting to validate the metadata based on the data map; automatically performing the at least one of the transforming or the translating of a validated metadata when the metadata is validated based on the data map, wherein the transforming includes converting the validated metadata to the target metadata format, wherein the target metadata format includes one or more extendible fields and values that correspond to one or more fields and values included in a source metadata format of the metadata and not provided by a standard of a metadata format on which the target metadata format is based and the target metadata format includes each of the fields and values provided by the standard of the metadata format on which the target metadata format is based, and wherein the transforming includes using the one or more extendible fields when one or more fields of the validated metadata do not have corresponding one or more fields afforded by the standard of the metadata format; and automatically storing a target metadata based on the performing.

1. A method comprising: automatically receiving an asset including content and metadata; automatically identifying a source metadata format of the metadata; automatically identifying a target metadata format; automatically selecting a data map to perform validation of the metadata and at least one of transforming or translating of the metadata based on the identifying of the source metadata format and the identifying of the target metadata format, wherein the transforming includes converting the metadata to the target metadata format and the translating includes converting a file type of the metadata to a target metadata file type; automatically attempting to validate the metadata based on the data map; automatically performing the at least one of the transforming or the translating of a validated metadata when the metadata is validated based on the data map, wherein the transforming includes converting the validated metadata to the target metadata format, wherein the target metadata format includes one or more extendible fields and values that correspond to one or more fields and values included in a source metadata format of the metadata and not provided by a standard of a metadata format on which the target metadata format is based and the target metadata format includes each of the fields and values provided by the standard of the metadata format on which the target metadata format is based, and wherein the transforming includes using the one or more extendible fields when one or more fields of the validated metadata do not have corresponding one or more fields afforded by the standard of the metadata format; and automatically storing a target metadata based on the performing. 8. The method of claim 1 , wherein the automatically identifying the source metadata format comprises: receiving a work unit that includes information indicating a particular asset provider from which the asset is received, and wherein the automatically selecting comprises: automatically selecting a data map identifier based on the particular asset provider, wherein the data map identifier references the data map.

8. The computer program product of claim 1 , wherein the preferences include at least one of personal information and topical information related to interactions of the user.

8. The computer program product of claim 1 , wherein the preferences include at least one of personal information and topical information related to interactions of the user. 9. The computer program product of claim 8 , wherein the interactions are through the Internet based social interactive graphical representation.

1. A computer-implemented method comprising: receiving a first normalized taxonomy, the first normalized taxonomy corresponding to a first repository that has a single-level security access that provides a secure login mechanism on a per-repository basis; receiving a second normalized taxonomy, the second normalized taxonomy corresponding to a second repository that has a multi-level security access that provides a secure login mechanism on a per-asset basis; generating a composite taxonomy from the first normalized taxonomy and the second normalized taxonomy; storing the composite taxonomy in a storage area; receiving a taxonomy request from a portal, the taxonomy request including a user identifier; retrieving the composite taxonomy from the storage area in response to receiving the taxonomy request; identifying a user security level associated with the user identifier; filtering the composite taxonomy based upon the user security level, the filtering resulting in a filtered composite taxonomy that includes one or more available nodes that correspond to a subset of assets from a combination of assets included in the first repository and the second repository; and providing the filtered composite taxonomy to the portal.

1. A computer-implemented method comprising: receiving a first normalized taxonomy, the first normalized taxonomy corresponding to a first repository that has a single-level security access that provides a secure login mechanism on a per-repository basis; receiving a second normalized taxonomy, the second normalized taxonomy corresponding to a second repository that has a multi-level security access that provides a secure login mechanism on a per-asset basis; generating a composite taxonomy from the first normalized taxonomy and the second normalized taxonomy; storing the composite taxonomy in a storage area; receiving a taxonomy request from a portal, the taxonomy request including a user identifier; retrieving the composite taxonomy from the storage area in response to receiving the taxonomy request; identifying a user security level associated with the user identifier; filtering the composite taxonomy based upon the user security level, the filtering resulting in a filtered composite taxonomy that includes one or more available nodes that correspond to a subset of assets from a combination of assets included in the first repository and the second repository; and providing the filtered composite taxonomy to the portal. 2. The method of claim 1 further comprising: receiving the filtered composite taxonomy at the portal; and generating a user interface view at the portal based upon the filtered composite taxonomy, wherein the user interface view only includes nodes corresponding to the subset of assets from the combination of assets included in the first repository and the second repository.

1. A system for transforming historical data collected in response to one or more triggering events, in order to classify textual values, the system comprising: a computer apparatus including a processor and a memory; and a software module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: access a plurality of textual values from historical transaction data; remove undesired characters from the plurality of textual values; implement a clustering algorithm to the plurality of textual values to identify one or more distinct patterns within the plurality of textual values, wherein the clustering algorithm comprises: a primary process for coding the plurality of textual values into one or more phonetic components, thereby reducing the plurality of textual values into a combination of consonant sounds, wherein identifying the one or more distinct patterns within the plurality of textual values comprises comparing pronunciations and phonetics of the plurality of textual values; and a secondary process for identifying and classifying, based on an Internet search, one or more of the plurality of textual values unable to be classified by the primary process; create one or more clusters by grouping the plurality of textual values based, respectively, on the one or more distinct patterns output by the primary process and the Internet search of the secondary process; apply a similarity gauge to the textual values of each of the clusters to determine similarity or dissimilarity among the textual values of each cluster; filter the textual values of each cluster to determine which textual values belong in each cluster and which textual values do not belong in each cluster, wherein the textual values that belong are cluster values; pass the cluster values for each cluster to a reference table; store the cluster values for each cluster in the reference table for future access; and in response to a need for classification of a future set of textual values, access the reference table and lookup the future set of textual values in the reference table to determine whether any of the future set of textual values are cluster values.

1. A system for transforming historical data collected in response to one or more triggering events, in order to classify textual values, the system comprising: a computer apparatus including a processor and a memory; and a software module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: access a plurality of textual values from historical transaction data; remove undesired characters from the plurality of textual values; implement a clustering algorithm to the plurality of textual values to identify one or more distinct patterns within the plurality of textual values, wherein the clustering algorithm comprises: a primary process for coding the plurality of textual values into one or more phonetic components, thereby reducing the plurality of textual values into a combination of consonant sounds, wherein identifying the one or more distinct patterns within the plurality of textual values comprises comparing pronunciations and phonetics of the plurality of textual values; and a secondary process for identifying and classifying, based on an Internet search, one or more of the plurality of textual values unable to be classified by the primary process; create one or more clusters by grouping the plurality of textual values based, respectively, on the one or more distinct patterns output by the primary process and the Internet search of the secondary process; apply a similarity gauge to the textual values of each of the clusters to determine similarity or dissimilarity among the textual values of each cluster; filter the textual values of each cluster to determine which textual values belong in each cluster and which textual values do not belong in each cluster, wherein the textual values that belong are cluster values; pass the cluster values for each cluster to a reference table; store the cluster values for each cluster in the reference table for future access; and in response to a need for classification of a future set of textual values, access the reference table and lookup the future set of textual values in the reference table to determine whether any of the future set of textual values are cluster values. 3. The system of claim 1 , wherein applying a similarity gauge to the textual values comprises: determining a Jaccard distance score among the textual values of each cluster.

13. The mobile body track identification method according to claim 12 further comprising: storing a probability map defining detection probabilities of identifications of mobile bodies in response to positional coordinates of mobile bodies in the tracking area in advance; specifying a position of a mobile body on tracks indicated by each track-coupling candidate at each identification detection time for each track-coupling candidate/identification pair ascribed to each of the selected hypotheses; reading a probability value of detecting the mobile body at the position from the probability map; calculating an identification likelihood based on the probability value; further integrating identification likelihoods for each track-coupling candidate/identification pair so as to calculate an identification likelihood regarding each of the selected hypotheses; and estimating the most-probable hypothesis based on identification likelihoods of hypotheses.

13. The mobile body track identification method according to claim 12 further comprising: storing a probability map defining detection probabilities of identifications of mobile bodies in response to positional coordinates of mobile bodies in the tracking area in advance; specifying a position of a mobile body on tracks indicated by each track-coupling candidate at each identification detection time for each track-coupling candidate/identification pair ascribed to each of the selected hypotheses; reading a probability value of detecting the mobile body at the position from the probability map; calculating an identification likelihood based on the probability value; further integrating identification likelihoods for each track-coupling candidate/identification pair so as to calculate an identification likelihood regarding each of the selected hypotheses; and estimating the most-probable hypothesis based on identification likelihoods of hypotheses. 14. The mobile body track identification method according to claim 13 further comprising: storing track/identification correlation likelihoods representing likelihoods of correlating identifications to tracks of mobile bodies; calculating a track/identification correlation likelihood, corresponding to a current combination of a track and an identification included in track-coupling candidates in track-coupling candidate/identification pairs ascribed to the most-probable hypothesis and all other hypotheses; and calculating an identification likelihood regarding each track-coupling candidate/identification pair based on the track/identification correlation likelihood corresponding to the current combination of the track and the identification included in track-coupling candidates for each track-coupling candidate/identification pair as well as the probability value read from the probability map at each identification detection time.

5. The method of claim 2 , wherein the multimedia objects are extracted from the multimedia content by steps comprising: segmenting multimedia content into segments including content from at least one of the multimedia types for the multimedia content; and generating at least one feature description for at least one of the segments by feature extraction and annotation, wherein the generated multimedia object descriptions comprise the at least one feature description for the at least one segment.

5. The method of claim 2 , wherein the multimedia objects are extracted from the multimedia content by steps comprising: segmenting multimedia content into segments including content from at least one of the multimedia types for the multimedia content; and generating at least one feature description for at least one of the segments by feature extraction and annotation, wherein the generated multimedia object descriptions comprise the at least one feature description for the at least one segment. 11. The method of claim 5 , wherein the multimedia objects are extracted from the multimedia content by steps further comprising: generating media object descriptions from the multimedia segment for one of the multimedia types by media object extraction processing; generating media object hierarchy descriptions from the generated media object descriptions by object hierarchy construction and extraction processing; and generating media entity relation graph descriptions from the generated media object descriptions by entity relation graph generation processing.