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56. The system of claim 44 , wherein the received search parameters have an applicability to one or more subjects, the system further comprising: means for integrating any of the specified received search parameters with a search query, wherein the integrated received search parameters are applicable to a determined subject of the received search query.
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56. The system of claim 44 , wherein the received search parameters have an applicability to one or more subjects, the system further comprising: means for integrating any of the specified received search parameters with a search query, wherein the integrated received search parameters are applicable to a determined subject of the received search query. 58. The system of claim 56 , wherein the determined subject matter is based upon the received search query.
| 0.978184 |
9. The computer program product of claim 8 , wherein the computer readable program further causes the computing device to: monitor corrections to one or more user interface automation scripts; record the corrections to the one or more user interface automation scripts in a corrections data structure; and train the machine learning model using the recorded corrections in the corrections data structure as training data.
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9. The computer program product of claim 8 , wherein the computer readable program further causes the computing device to: monitor corrections to one or more user interface automation scripts; record the corrections to the one or more user interface automation scripts in a corrections data structure; and train the machine learning model using the recorded corrections in the corrections data structure as training data. 10. The computer program product of claim 9 , wherein the corrections data structure comprises for each of correction a previous set of properties for a changed user interface control and a current set of properties for the changed user interface control.
| 0.835344 |
11. A non-transitory computer readable medium comprising a set of instructions for adaptive display of an advertisement to look-alike users using a desired user profile dataset which, when executed by a computer, cause the computer to perform actions of: obtaining a plurality of known user profiles of known users who have been recorded to interact with an advertiser, wherein each of the plurality of known user profiles includes: historical components reflecting a stream of events of the known user prior to a current time, and a temporary component reflecting a state of the known user at the current time; automatically creating a plurality of desired user profiles of desired users who are not included in the plurality of known user profiles, wherein each of the plurality of the desired user profiles includes historical components reflecting a stream of events of the desired user prior to the current time, and a temporary component reflecting a state of the desired user at the current time; scoring, with a machine-learned model, similarities between the plurality of desired user profiles with the plurality of known user profiles based on the temporal component of the plurality of known user profile and the temporal component of the plurality of desired user profile for adapting to changes of user behavior; selecting, by a computer, a plurality of predicted users from the desired users based on the score of the plurality of desired user profile and; and serving an advertisement to the predicted user.
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11. A non-transitory computer readable medium comprising a set of instructions for adaptive display of an advertisement to look-alike users using a desired user profile dataset which, when executed by a computer, cause the computer to perform actions of: obtaining a plurality of known user profiles of known users who have been recorded to interact with an advertiser, wherein each of the plurality of known user profiles includes: historical components reflecting a stream of events of the known user prior to a current time, and a temporary component reflecting a state of the known user at the current time; automatically creating a plurality of desired user profiles of desired users who are not included in the plurality of known user profiles, wherein each of the plurality of the desired user profiles includes historical components reflecting a stream of events of the desired user prior to the current time, and a temporary component reflecting a state of the desired user at the current time; scoring, with a machine-learned model, similarities between the plurality of desired user profiles with the plurality of known user profiles based on the temporal component of the plurality of known user profile and the temporal component of the plurality of desired user profile for adapting to changes of user behavior; selecting, by a computer, a plurality of predicted users from the desired users based on the score of the plurality of desired user profile and; and serving an advertisement to the predicted user. 12. The non-transitory computer readable medium of claim 11 , wherein the similarity between a desired user and a known user comprises a similarity between a current component of the desired user and a current component of the known user.
| 0.555714 |
1. A method comprising: accessing, at a computer system, a first electronic document having a first electronic document type via a first software program that is configured to provide access to the first electronic document type; accessing, at the computer system, a second electronic, document having a second electronic document type via a second software program that is configured to provide access to the second electronic document type; receiving a user selection that identifies a part of the second electronic document as an indicated portion of the second electronic document, wherein the indicated portion of the second electronic document is highlighted; integrating the indicated portion of the second electronic document having the second electronic document type into the first electronic document based on a dynamic link in the first electronic document that identifies the second electronic document by a non-address identifier that does not provide access to the second electronic document, that can be used to locate the second electronic document within a data repository, that causes the second software program to interpret the indicated portion of the second electronic document, and that causes the first software program to generate information for display in the first electronic document based on the interpreted indicated portion of the second electronic document, resulting in an integrated first electric document; receiving a user request to perform an operation in the integrated first electronic document; and performing the operation using the first software program if the request relates to the first electronic document or using the second software program if the request relates to the second electronic document.
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1. A method comprising: accessing, at a computer system, a first electronic document having a first electronic document type via a first software program that is configured to provide access to the first electronic document type; accessing, at the computer system, a second electronic, document having a second electronic document type via a second software program that is configured to provide access to the second electronic document type; receiving a user selection that identifies a part of the second electronic document as an indicated portion of the second electronic document, wherein the indicated portion of the second electronic document is highlighted; integrating the indicated portion of the second electronic document having the second electronic document type into the first electronic document based on a dynamic link in the first electronic document that identifies the second electronic document by a non-address identifier that does not provide access to the second electronic document, that can be used to locate the second electronic document within a data repository, that causes the second software program to interpret the indicated portion of the second electronic document, and that causes the first software program to generate information for display in the first electronic document based on the interpreted indicated portion of the second electronic document, resulting in an integrated first electric document; receiving a user request to perform an operation in the integrated first electronic document; and performing the operation using the first software program if the request relates to the first electronic document or using the second software program if the request relates to the second electronic document. 4. The method of claim 1 , wherein the request to perform an operation is an undo request, and performing the operation includes identifying a prior operation for reversal using a common undo stack, wherein the prior operation for reversal is associated with at least one of the first electronic document or the second electronic document.
| 0.666012 |
15. A device comprising: one or more processors; and data storage configured to store instructions executable by the one or more processors to cause the device to: receive a plurality of speech sounds that are each indicative of a different full pronunciation of a first linguistic term, wherein the first linguistic term includes a representation of one or more phonemes; determine concatenation features of the plurality of speech sounds of the first linguistic term, wherein the concatenation features are indicative of an acoustic transition between a first speech sound and a second speech sound when the first speech sound and the second speech sound are concatenated, wherein the first speech sound is included in the plurality of speech sounds of the first linguistic term and the second speech sound is indicative of a pronunciation of a second linguistic term; cluster, based on the concatenation features, the plurality of speech sounds into one or more clusters, wherein a given cluster includes one or more speech sounds of the plurality of speech sounds that have given concatenation features that are related by a clustering metric; and based on a determination that the first speech sound has the given concatenation features represented in the given cluster, provide a representative speech sound of the given cluster as the first speech sound when the first speech sound and the second speech sound are concatenated.
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15. A device comprising: one or more processors; and data storage configured to store instructions executable by the one or more processors to cause the device to: receive a plurality of speech sounds that are each indicative of a different full pronunciation of a first linguistic term, wherein the first linguistic term includes a representation of one or more phonemes; determine concatenation features of the plurality of speech sounds of the first linguistic term, wherein the concatenation features are indicative of an acoustic transition between a first speech sound and a second speech sound when the first speech sound and the second speech sound are concatenated, wherein the first speech sound is included in the plurality of speech sounds of the first linguistic term and the second speech sound is indicative of a pronunciation of a second linguistic term; cluster, based on the concatenation features, the plurality of speech sounds into one or more clusters, wherein a given cluster includes one or more speech sounds of the plurality of speech sounds that have given concatenation features that are related by a clustering metric; and based on a determination that the first speech sound has the given concatenation features represented in the given cluster, provide a representative speech sound of the given cluster as the first speech sound when the first speech sound and the second speech sound are concatenated. 18. The device of claim 15 , wherein the instructions executable by the one or more processors further cause the device to: receive configuration input indicative of a reduction for the plurality of speech sounds; and determine, based on the reduction, a quantity of the one or more clusters.
| 0.651768 |
1. A method comprising: tailoring user specific data of a user to generate tailored user specific data, the user specific data associated with an application and tailored based on one or more aesthetic preferences of the user as indicated by a template for the application; and extending a user profile of the user to comprise the tailored user specific data to generate an extended user profile, at least one of the tailoring or the extending implemented at least in part via a processing unit.
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1. A method comprising: tailoring user specific data of a user to generate tailored user specific data, the user specific data associated with an application and tailored based on one or more aesthetic preferences of the user as indicated by a template for the application; and extending a user profile of the user to comprise the tailored user specific data to generate an extended user profile, at least one of the tailoring or the extending implemented at least in part via a processing unit. 6. The method of claim 1 , comprising authenticating the user.
| 0.62884 |
14. A non-transitory computer readable storage medium configured to store program code, the program code configured to analyze contents in one or more contracts, the program code comprising instructions that when executed by a processor cause the processor to: identify a related portion of one or more contracts by: extracting primary features from the one or more contracts, and ordering and linking, by the primary features, the related portion of the one or more contracts by updating a features database to store the obtained primary features, and building a feature space matrix comprising pointers to the primary features in the features database, each pointer identifying a corresponding portion of the related portion of the one or more contracts; define an advanced policy group comprising a plurality of policy groups, the plurality of policy groups grouping a plurality of policies, the plurality of policies comprising clause examples to compare against clauses in the related portion of the one or more contracts, assign a validity state for each of the plurality of policy groups, wherein the validity state of a policy group of the plurality of policy groups corresponds to one of: a valid state indicating the policy group comprises at least one policy with a related clause from the related portion of the one or more contracts, and an invalid state indicating the policy group comprises policies without any related clause from the related portion of the one or more contracts; generate a validity of the advanced policy group based upon the validity state of each of the plurality of policy groups; updating a database using the related portion of the one or more contracts and the generated validity of the advanced policy group based upon an analysis of the contents in the related portion of the one or more contracts based on the validity of the advanced policy group.
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14. A non-transitory computer readable storage medium configured to store program code, the program code configured to analyze contents in one or more contracts, the program code comprising instructions that when executed by a processor cause the processor to: identify a related portion of one or more contracts by: extracting primary features from the one or more contracts, and ordering and linking, by the primary features, the related portion of the one or more contracts by updating a features database to store the obtained primary features, and building a feature space matrix comprising pointers to the primary features in the features database, each pointer identifying a corresponding portion of the related portion of the one or more contracts; define an advanced policy group comprising a plurality of policy groups, the plurality of policy groups grouping a plurality of policies, the plurality of policies comprising clause examples to compare against clauses in the related portion of the one or more contracts, assign a validity state for each of the plurality of policy groups, wherein the validity state of a policy group of the plurality of policy groups corresponds to one of: a valid state indicating the policy group comprises at least one policy with a related clause from the related portion of the one or more contracts, and an invalid state indicating the policy group comprises policies without any related clause from the related portion of the one or more contracts; generate a validity of the advanced policy group based upon the validity state of each of the plurality of policy groups; updating a database using the related portion of the one or more contracts and the generated validity of the advanced policy group based upon an analysis of the contents in the related portion of the one or more contracts based on the validity of the advanced policy group. 19. The non-transitory computer readable storage medium of claim 14 , further comprising instructions that when executed by the processor cause the processor to, via an input processor engine, retrieve the one or more contracts into a format that a discovery engine can process.
| 0.666144 |
54. The system as defined in claim 53 , wherein the document stored in XML form is parsed by an XML parser to create the internal representation.
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54. The system as defined in claim 53 , wherein the document stored in XML form is parsed by an XML parser to create the internal representation. 55. The system as defined in claim 54 , wherein the internal representation level of the document is transformed to a subscription-level document by applying a subscription-level transform to the internal representation.
| 0.925409 |
1. A visual editing tool for editing an on-screen image displayed on an electronic display, comprising: a processor executing tangibly embodied program instructions implementing a graphical user interface, the graphical user interface comprising a workspace for rendering an edit document, the edit document responsive to editing modules for modification according to an edit function performed by each of the editing modules; each of the editing modules rendered as an editing icon displayed in an overlay in front of the workspace; a rendering area defined by a physical visual display surface including the on-screen image, the rendering area displaying at least a portion of the edit document; a buffer region adjacent to the edit document on the workspace, the buffer region allowing unimpeded viewing of the edit document by occupying a background area behind the editing icons, the overlay such that none of the editing icons overlay the edit document on the workspace; and a dock, the dock grouping the editing icons in the buffer region when the rendering area extends beyond the edit document and wherein the dock includes a retraction slot, the retraction slot retracting at least a portion of the editing icons, the retracted portion not visible in the rendering area such that an area occupied by the editing icons is available for rendering the edit document.
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1. A visual editing tool for editing an on-screen image displayed on an electronic display, comprising: a processor executing tangibly embodied program instructions implementing a graphical user interface, the graphical user interface comprising a workspace for rendering an edit document, the edit document responsive to editing modules for modification according to an edit function performed by each of the editing modules; each of the editing modules rendered as an editing icon displayed in an overlay in front of the workspace; a rendering area defined by a physical visual display surface including the on-screen image, the rendering area displaying at least a portion of the edit document; a buffer region adjacent to the edit document on the workspace, the buffer region allowing unimpeded viewing of the edit document by occupying a background area behind the editing icons, the overlay such that none of the editing icons overlay the edit document on the workspace; and a dock, the dock grouping the editing icons in the buffer region when the rendering area extends beyond the edit document and wherein the dock includes a retraction slot, the retraction slot retracting at least a portion of the editing icons, the retracted portion not visible in the rendering area such that an area occupied by the editing icons is available for rendering the edit document. 4. The method of claim 1 wherein the editing icons have a retracted rendering and a full rendering, the retracted rendering contained within the buffer zone such that the workspace is unimpeded.
| 0.683442 |
11. Software for identifying related questions comprising computer readable instructions embodied on non-transitory computer-readable media, wherein the computer readable instructions are configured, when executed by a data processing apparatus, to: identify, using at least one hardware processor, a plurality of different previously-submitted search queries; filter, using at least one evaluation file, the plurality of different previously-submitted search queries to remove one or more specified words from the plurality of different previously-submitted search queries to generate a plurality of filtered search queries, wherein the at least one evaluation file includes at least one of instructions or parameters for generating at least one canonical search query form of the plurality of different previously-submitted search queries; modify, using the at least one evaluation file, remaining words in the plurality of filtered search queries to generate a plurality of modified search queries; determine, as search queries that map to a particular canonical search query form, a subset of the plurality of different previously-submitted search queries that are used to generate, as a result of filtering the plurality of different previously-submitted search queries and modifying the plurality of filtered search queries using the at least one evaluation file; rank the search queries that map to the particular canonical search query form based, at least in part, on a frequency of submission of each different previously-submitted search query that maps to the particular canonical search query form; and identify, based on the ranking, a particular one of the different previously-submitted search queries in the ranked search queries that map to the particular canonical search query form as a representative search query of the search queries that map to the particular canonical search query form.
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11. Software for identifying related questions comprising computer readable instructions embodied on non-transitory computer-readable media, wherein the computer readable instructions are configured, when executed by a data processing apparatus, to: identify, using at least one hardware processor, a plurality of different previously-submitted search queries; filter, using at least one evaluation file, the plurality of different previously-submitted search queries to remove one or more specified words from the plurality of different previously-submitted search queries to generate a plurality of filtered search queries, wherein the at least one evaluation file includes at least one of instructions or parameters for generating at least one canonical search query form of the plurality of different previously-submitted search queries; modify, using the at least one evaluation file, remaining words in the plurality of filtered search queries to generate a plurality of modified search queries; determine, as search queries that map to a particular canonical search query form, a subset of the plurality of different previously-submitted search queries that are used to generate, as a result of filtering the plurality of different previously-submitted search queries and modifying the plurality of filtered search queries using the at least one evaluation file; rank the search queries that map to the particular canonical search query form based, at least in part, on a frequency of submission of each different previously-submitted search query that maps to the particular canonical search query form; and identify, based on the ranking, a particular one of the different previously-submitted search queries in the ranked search queries that map to the particular canonical search query form as a representative search query of the search queries that map to the particular canonical search query form. 20. The software of claim 11 , wherein the computer readable instructions are further configured, when executed by the data processing apparatus, to: determine a most frequently submitted different previously-submitted search query based, at least in part, on the ranking of the search queries that map to the particular canonical search query form; and post the most frequently submitted different previously-submitted search query in a Question and Answer (Q&A) Webpage.
| 0.510667 |
57. The apparatus of claim 50 , wherein generating a respective input data hash value HV N comprises: applying a hash function to the N th input data symbol B N and a predetermined number of adjacent input data symbols in the sequence of input data symbols.
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57. The apparatus of claim 50 , wherein generating a respective input data hash value HV N comprises: applying a hash function to the N th input data symbol B N and a predetermined number of adjacent input data symbols in the sequence of input data symbols. 58. The apparatus of claim 57 , wherein the predetermined number of adjacent input data symbols comprises a predetermined number of symbols immediately preceding the respective N th input data symbol B N .
| 0.927786 |
16. The speech synthesizer of claim 12 wherein said vocal source is adapted to produce a voiced excitation signal having a waveform comprised of a first segment that increases in magnitude, a second segment that decreases in magnitude, and a third segment that remains at a constant magnitude.
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16. The speech synthesizer of claim 12 wherein said vocal source is adapted to produce a voiced excitation signal having a waveform comprised of a first segment that increases in magnitude, a second segment that decreases in magnitude, and a third segment that remains at a constant magnitude. 19. The speech synthesizer of claim 16 wherein said suppression means increases said predetermined bandwidths of said resonant filters during said first segment of said voiced excitation signal, decreases said bandwidths of said resonant filters from said increased levels during said second segment of said voiced excitation signal, and has no effect on said predetermined bandwidths of said resonant filters during said third segment of said voiced excitation signal.
| 0.781437 |
13. A system for proximity indexing a plurality of data comprising: storage means, connected to the grouping means, for storing a plurality of data in a database; a computer processor for manipulating the plurality of data; means for enabling the computer processor to access the plurality of data stored in the database; extractor means for creating a numerical representation of each accessed datum; patterner means for analyzing the numerical representation of the plurality of data for patterns comprising: means for a calculating a pattern representation for each datum based upon that datums relationship to every other datum; and means for weighing the significance of the pattern representation; weaver means for generating an index on the proximity of each datum to every other datum comprising: a means for determining the Euclidian distance between two pattern representations; and memory for storing the index on the proximity of each datum to every other datum.
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13. A system for proximity indexing a plurality of data comprising: storage means, connected to the grouping means, for storing a plurality of data in a database; a computer processor for manipulating the plurality of data; means for enabling the computer processor to access the plurality of data stored in the database; extractor means for creating a numerical representation of each accessed datum; patterner means for analyzing the numerical representation of the plurality of data for patterns comprising: means for a calculating a pattern representation for each datum based upon that datums relationship to every other datum; and means for weighing the significance of the pattern representation; weaver means for generating an index on the proximity of each datum to every other datum comprising: a means for determining the Euclidian distance between two pattern representations; and memory for storing the index on the proximity of each datum to every other datum. 18. The system of claim 13 wherein the plurality of data are received in a digital signal, the system further comprising: means for receiving the digital signals; means, connected to the receiving means, for interpreting the digital signals into data; means, connected to the interpreting means and storage means, for grouping the plurality of data into a database format; means, connected to the memory, for converting the index into a transmission signal; and means, connected to the converting means, for transmitting the transmission signal representing the index.
| 0.580374 |
18. The computer system of claim 15 , wherein program instructions to calculate the recipient interest rating for the one or more keywords, further comprise: program instructions to assign the one or more keywords a weight based on at least one of: program instructions to determine one or more actions taken on the one or more electronic messages; program instructions to determine a time spent on the one or more electronic messages by the recipient; program instructions to determine how quickly the one or more electronic messages was accessed by the recipient; and program instructions to determine a relationship between the recipient and a sender.
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18. The computer system of claim 15 , wherein program instructions to calculate the recipient interest rating for the one or more keywords, further comprise: program instructions to assign the one or more keywords a weight based on at least one of: program instructions to determine one or more actions taken on the one or more electronic messages; program instructions to determine a time spent on the one or more electronic messages by the recipient; program instructions to determine how quickly the one or more electronic messages was accessed by the recipient; and program instructions to determine a relationship between the recipient and a sender. 19. The computer system of claim 18 , wherein program instructions to assign the one or more keywords a weight based on determining one or more indicators, further comprise: program instructions to assign a positive point value for indicators suggesting high user interest, and a negative point value for indicators suggesting low user interest.
| 0.914356 |
7. A computer system adapted to translate the meanings of a source sentence from an input language into an output language, comprising: a source sentence analyzer adapted to analyze meanings of the source sentence using linguistic descriptions of the source language and to construct a language-independent semantic structure to represent the meanings of the source sentence; and an output sentence synthesizer adapted to synthesize an output sentence to represent the meanings of the source sentence in an output language from the language-independent semantic structure using information from linguistic descriptions of the output language, wherein the output sentence synthesizer comprises a linear order synthesizer adapted to determine a linear order for and restore movements on the syntactic structure of the output sentence in the output language, wherein the output sentence analyzer is adapted to apply semantic structure correction rules to the language-independent semantic structure to overcome asymmetries between the language-independent semantic structure and the syntactic structure of the output sentence in the output language, wherein a surface structure of the output sentence is built at least in part based on ratings of syntactic constructions for elements of the source sentence, and wherein applying semantic structure correction rules to the language-independent semantic structure to overcome asymmetries includes the use of semanteme calculating rules and semanteme normalization rules to remove asymmetries.
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7. A computer system adapted to translate the meanings of a source sentence from an input language into an output language, comprising: a source sentence analyzer adapted to analyze meanings of the source sentence using linguistic descriptions of the source language and to construct a language-independent semantic structure to represent the meanings of the source sentence; and an output sentence synthesizer adapted to synthesize an output sentence to represent the meanings of the source sentence in an output language from the language-independent semantic structure using information from linguistic descriptions of the output language, wherein the output sentence synthesizer comprises a linear order synthesizer adapted to determine a linear order for and restore movements on the syntactic structure of the output sentence in the output language, wherein the output sentence analyzer is adapted to apply semantic structure correction rules to the language-independent semantic structure to overcome asymmetries between the language-independent semantic structure and the syntactic structure of the output sentence in the output language, wherein a surface structure of the output sentence is built at least in part based on ratings of syntactic constructions for elements of the source sentence, and wherein applying semantic structure correction rules to the language-independent semantic structure to overcome asymmetries includes the use of semanteme calculating rules and semanteme normalization rules to remove asymmetries. 14. The computer system of claim 7 , wherein the output synthesizer further comprises a linear order synthesizer adapted to determine a linear order and restoring movements on the syntactic structure of the output sentence in the output language.
| 0.609711 |
1. A machine-implemented method, comprising: receiving a scalable encoded bitstream comprising scalable encoded media data and values of non-media-type-specific scalability attribute variables defining different adaptation points of the scalable encoded media data; obtaining receiving attributes for a destination of an outbound version of the scalable encoded bitstream, wherein ones of the receiving attributes define explicit constraints on the outbound version of the scalable encoded bitstream in terms of respective functions of ones of the scalability attribute variables; determining values of adaptation measures from respective evaluations of the functions based on the values of the ones of the scalability attribute variables; ascertaining a set of one or more candidate ones of the adaptation points of based on imposition of the constraints on the determined values of the adaptation measures; selecting an adaptation point from the set of candidate adaptation points without regard to the scalable encoded media data; and transcoding the scalable bit stream in accordance with the selected adaptation point to produce the outbound version of the scalable encoded bitstream.
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1. A machine-implemented method, comprising: receiving a scalable encoded bitstream comprising scalable encoded media data and values of non-media-type-specific scalability attribute variables defining different adaptation points of the scalable encoded media data; obtaining receiving attributes for a destination of an outbound version of the scalable encoded bitstream, wherein ones of the receiving attributes define explicit constraints on the outbound version of the scalable encoded bitstream in terms of respective functions of ones of the scalability attribute variables; determining values of adaptation measures from respective evaluations of the functions based on the values of the ones of the scalability attribute variables; ascertaining a set of one or more candidate ones of the adaptation points of based on imposition of the constraints on the determined values of the adaptation measures; selecting an adaptation point from the set of candidate adaptation points without regard to the scalable encoded media data; and transcoding the scalable bit stream in accordance with the selected adaptation point to produce the outbound version of the scalable encoded bitstream. 2. The method of claim 1 , wherein the determining comprises determining the value of at least one of the adaptation measures based at least in part on a multivariate function defined by a respective one of the receiving attributes and comprising a linear combination of products of univariate functions of ones of the scalability attribute variables.
| 0.5094 |
1. A method comprising: receiving, over a network by a networked system, a communication that is a part of a conversation involving one or more users, the networked system being a participant in the conversation; analyzing, by one or more hardware processors of the networked system, the communication, the analyzing including parsing key terms from the communication; identifying, by the networked system, a sentiment of a user among the one or more users based on the parsed key terms, the identified sentiment of the user identifying a level of commitment readiness among at least two sequentially increasing levels of commitment readiness, the at least two sequentially increasing levels including a penultimate level that indicates readiness to consider multiple options and including an ultimate level that indicates readiness to commit to one option among the multiple options; based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness, determining whether the networked system is to respond to the communication; and in response to a determination to respond, generating, by the networked system, a customized response based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness and transmitting the customized response, over the network, to a device of the user.
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1. A method comprising: receiving, over a network by a networked system, a communication that is a part of a conversation involving one or more users, the networked system being a participant in the conversation; analyzing, by one or more hardware processors of the networked system, the communication, the analyzing including parsing key terms from the communication; identifying, by the networked system, a sentiment of a user among the one or more users based on the parsed key terms, the identified sentiment of the user identifying a level of commitment readiness among at least two sequentially increasing levels of commitment readiness, the at least two sequentially increasing levels including a penultimate level that indicates readiness to consider multiple options and including an ultimate level that indicates readiness to commit to one option among the multiple options; based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness, determining whether the networked system is to respond to the communication; and in response to a determination to respond, generating, by the networked system, a customized response based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness and transmitting the customized response, over the network, to a device of the user. 5. The method of claim 1 , further comprising: inferring a goal using the parsed key terms from the communication; and modifying a set of options to best meet the goal, the set of options being provided in the customized response.
| 0.542876 |
11. A computer system comprising: a processor set; and a computer readable storage medium; wherein: the processor set is structured, located, connected, and/or programmed to run program instructions stored on the computer readable storage medium; and the program instructions which, when executed by the processor set, cause the processor set to determine a significance ranking for discovered relationships by: ingesting a first body of information for a domain of knowledge; receiving a natural language question corresponding to the domain of knowledge, the natural language question being in the form of a complete human language question; parsing the natural language question to identify a focus within the text of the natural language question; mining the body of information for found entities disclosed within the body of information; determining relationships among found entities based on the focus identified within the text of the natural language question; generating a targeting document for the domain of knowledge containing a first relationship and a second relationship, the first and second relationships being relationships among found entities determined from the first body of information; recording mining data for relationships in the targeting document in support of an importance criteria; ranking the first relationship with respect to the second relationship based on the recorded mining data and according to the importance criteria as a set of ranking data; and storing the targeting document including the set of ranking data and mining data in the first body of information for on-demand access during a question-answer session corresponding to the domain of knowledge; wherein: the importance criteria is a first degree to which first relationship is known and a second degree to which the second relationship is known according to a dictionary of commonly known relationships for the domain of knowledge; the first relationship being ranked as more important than the second relationship because the first degree is smaller than the second degree.
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11. A computer system comprising: a processor set; and a computer readable storage medium; wherein: the processor set is structured, located, connected, and/or programmed to run program instructions stored on the computer readable storage medium; and the program instructions which, when executed by the processor set, cause the processor set to determine a significance ranking for discovered relationships by: ingesting a first body of information for a domain of knowledge; receiving a natural language question corresponding to the domain of knowledge, the natural language question being in the form of a complete human language question; parsing the natural language question to identify a focus within the text of the natural language question; mining the body of information for found entities disclosed within the body of information; determining relationships among found entities based on the focus identified within the text of the natural language question; generating a targeting document for the domain of knowledge containing a first relationship and a second relationship, the first and second relationships being relationships among found entities determined from the first body of information; recording mining data for relationships in the targeting document in support of an importance criteria; ranking the first relationship with respect to the second relationship based on the recorded mining data and according to the importance criteria as a set of ranking data; and storing the targeting document including the set of ranking data and mining data in the first body of information for on-demand access during a question-answer session corresponding to the domain of knowledge; wherein: the importance criteria is a first degree to which first relationship is known and a second degree to which the second relationship is known according to a dictionary of commonly known relationships for the domain of knowledge; the first relationship being ranked as more important than the second relationship because the first degree is smaller than the second degree. 16. The computer system of claim 11 , further comprising: reporting to a user a set of top-ranked relationships in the targeting document.
| 0.543576 |
24. A memory device to store programming instructions to control at least one processor, the programming instructions comprising: instructions for calculating a first value representing a coherence of terms in a sequence of terms, where the instructions for calculating the first value include: instructions for calculating the coherence of the terms in the sequence relative to a first collection of documents; instructions for calculating a second value representing variation of context of the sequence, where the instructions for calculating the second value include: instructions for calculating entropy of the context of the sequence relative to a second collection of documents that differs from the first collection of documents, and instructions for determining the second value based on the entropy; instructions for applying one or more predefined rules to the sequence; and instructions for identifying that the sequence is a semantic unit based on the first value and the second value and based on applying the one or more predefined rules.
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24. A memory device to store programming instructions to control at least one processor, the programming instructions comprising: instructions for calculating a first value representing a coherence of terms in a sequence of terms, where the instructions for calculating the first value include: instructions for calculating the coherence of the terms in the sequence relative to a first collection of documents; instructions for calculating a second value representing variation of context of the sequence, where the instructions for calculating the second value include: instructions for calculating entropy of the context of the sequence relative to a second collection of documents that differs from the first collection of documents, and instructions for determining the second value based on the entropy; instructions for applying one or more predefined rules to the sequence; and instructions for identifying that the sequence is a semantic unit based on the first value and the second value and based on applying the one or more predefined rules. 25. The memory device of claim 24 , where the coherence of the terms in the sequence is calculated as a likelihood ratio that defines a probability of the sequence occurring in the first collection of documents relative to parts of the sequence occurring individually in the first collection of documents.
| 0.683763 |
10. The apparatus of claim 7 wherein the ordered list comprises, for each of the one or more new events, a first classification indicator specifying the riskiness of the new event utilizing the learning set and a second classification indicator specifying the riskiness of the new event without utilizing the learning set.
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10. The apparatus of claim 7 wherein the ordered list comprises, for each of the one or more new events, a first classification indicator specifying the riskiness of the new event utilizing the learning set and a second classification indicator specifying the riskiness of the new event without utilizing the learning set. 13. The apparatus of claim 10 wherein the first classification indicator comprises the risk score for the new event.
| 0.954962 |
1. An eye tracking system comprising: a video capture component configured to provide a video of an environment and a set of gaze tracking coordinates representing, for each of a plurality of frames comprising the video, a position within the environment at which a user is looking; a library, configured to store a plurality of feature sets representing respective areas of interest, with each area of interest including an object label representing an object of interest within the environment; an image annotation component configured to extract a plurality of features from a region of interest, defined around the gaze coordinates for a given frame, and match the extracted features to an area of interest in the library to produce a selected area of interest and a confidence value; and a verification component configured to accept the selected area of interest if the confidence value meets a threshold value and send the region of interest to a human expert at a user interface to assign an object label to the region of interest if the confidence value does not meet the threshold value; wherein the library is dynamically updated in response to input from the human expert to add new areas of interest and new object labels to the library.
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1. An eye tracking system comprising: a video capture component configured to provide a video of an environment and a set of gaze tracking coordinates representing, for each of a plurality of frames comprising the video, a position within the environment at which a user is looking; a library, configured to store a plurality of feature sets representing respective areas of interest, with each area of interest including an object label representing an object of interest within the environment; an image annotation component configured to extract a plurality of features from a region of interest, defined around the gaze coordinates for a given frame, and match the extracted features to an area of interest in the library to produce a selected area of interest and a confidence value; and a verification component configured to accept the selected area of interest if the confidence value meets a threshold value and send the region of interest to a human expert at a user interface to assign an object label to the region of interest if the confidence value does not meet the threshold value; wherein the library is dynamically updated in response to input from the human expert to add new areas of interest and new object labels to the library. 4. The eye tracking system of claim 1 , wherein the image annotation component is configured to match the set of features extracted from the region of interest to an area of interest in the library by calculating a distance metric between the set of features extracted from the region of interest and each of the plurality of feature sets stored in the library.
| 0.5 |
1. A computer-implemented method of generating pronounceable domain names, comprising: providing a list of character strings; determining a first probability that a character string in the list of character strings is pronounceable based on a phonetic model; determining a second probability that a character string in the list of character strings is pronounceable based on a character order model; filtering the list of character strings through a first filter based on the first probability to produce a first filtered list of character strings; filtering the list of character strings through a second filter based on the second probability to produce a second filtered list of character strings; and generating, by a processor, a list of pronounceable domain names based on the first filtered list of character strings and the second filtered list of character strings.
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1. A computer-implemented method of generating pronounceable domain names, comprising: providing a list of character strings; determining a first probability that a character string in the list of character strings is pronounceable based on a phonetic model; determining a second probability that a character string in the list of character strings is pronounceable based on a character order model; filtering the list of character strings through a first filter based on the first probability to produce a first filtered list of character strings; filtering the list of character strings through a second filter based on the second probability to produce a second filtered list of character strings; and generating, by a processor, a list of pronounceable domain names based on the first filtered list of character strings and the second filtered list of character strings. 13. The computer-implemented method of claim 1 , wherein the first filtered list of character strings is provided to the second filter to produce a second filtered list of character strings.
| 0.608864 |
1. A computer-implemented method for binary translation from a source instruction set architecture (ISA) to a target ISA distinct from the source ISA, the method comprising: a) selecting a set of peephole translation rules stored on a computer readable medium, wherein each rule in the set maps a source binary instruction sequence executable on the source ISA to corresponding equivalent binary instruction sequence executable on the target ISA; and b) using the set of peephole translation rules to directly translate a source binary executable on the first ISA to a target binary executable on the second ISA; further comprising: using superoptimization to automatically generate the set of peephole translation rules, and storing the set of peephole translation rules in the computer readable medium.
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1. A computer-implemented method for binary translation from a source instruction set architecture (ISA) to a target ISA distinct from the source ISA, the method comprising: a) selecting a set of peephole translation rules stored on a computer readable medium, wherein each rule in the set maps a source binary instruction sequence executable on the source ISA to corresponding equivalent binary instruction sequence executable on the target ISA; and b) using the set of peephole translation rules to directly translate a source binary executable on the first ISA to a target binary executable on the second ISA; further comprising: using superoptimization to automatically generate the set of peephole translation rules, and storing the set of peephole translation rules in the computer readable medium. 5. The method of claim 1 wherein (b) comprises choosing a register map for each application of the peephole translation rules.
| 0.648778 |
43. An associative memory computer program product according to claim 42 wherein the computer-readable program code that is configured to provide a processing system comprises: computer-readable program code that is configured to provide an observer system that is configured to observe into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents, to observe into the network of document associative memory networks, the associations among observed entities in a respective observer input document, to observe into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user, and to observe into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and computer-readable program code that is configured to provide a query system that is configured to imagine associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries.
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43. An associative memory computer program product according to claim 42 wherein the computer-readable program code that is configured to provide a processing system comprises: computer-readable program code that is configured to provide an observer system that is configured to observe into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents, to observe into the network of document associative memory networks, the associations among observed entities in a respective observer input document, to observe into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user, and to observe into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and computer-readable program code that is configured to provide a query system that is configured to imagine associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries. 44. An associative memory computer program product according to claim 43 wherein the computer-readable program code that is configured to provide a observer system comprises: computer-readable program code that is configured to provide an entity observer that is configured to observe into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; and computer-readable program code that is configured to provide a document observer that is configured to observe into the network of document associative memory networks, the associations among observed entities in a respective observer input document.
| 0.56518 |
2. The operating system of claim 1, wherein said dialog box control system logically associates the plurality of dialog boxes in a hierarchical relationship based on a location of a representative dialog launch display element used to launch each dialog box, and further wherein said dialog launch modalities comprise: a modal dialog launch modality for which said dialog box control system provides a first degree of display clarity and a first extent of system interactivity beyond said active dialog box; and a semi-modeless dialog launch modality for which said dialog box control system provides a second degree of display clarity approximately the same as said first degree of display clarity and a second extent of system interactivity beyond said active dialog box that is greater than said first extent of system interactivity.
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2. The operating system of claim 1, wherein said dialog box control system logically associates the plurality of dialog boxes in a hierarchical relationship based on a location of a representative dialog launch display element used to launch each dialog box, and further wherein said dialog launch modalities comprise: a modal dialog launch modality for which said dialog box control system provides a first degree of display clarity and a first extent of system interactivity beyond said active dialog box; and a semi-modeless dialog launch modality for which said dialog box control system provides a second degree of display clarity approximately the same as said first degree of display clarity and a second extent of system interactivity beyond said active dialog box that is greater than said first extent of system interactivity. 3. The operating system of claim 2, wherein said dialog launch modalities further comprise: a modeless dialog launch modality for which said dialog box control system provides a third degree of display clarity substantially less than said first degree of display clarity and said second degree of display clarity, and a third extent of system interactivity beyond said active dialog box that is greater than said first extent of system interactivity and said second extent of system interactivity.
| 0.743502 |
12. A method, comprising: obtaining, by a processor, a plurality of artifacts in plaintext form; generating, by the processor, fingerprints for each of the plurality of artifacts by generating shingles from text within each of the plurality of artifacts so that there at least one character overlap between adjacent shingles; and cryptographically hashing the shingles to generate a plurality of artifact fingerprints; storing the artifact fingerprints in a database; receiving, by the processor, a plurality of query fingerprints, each of which is generated by cryptographically hashing shingles of a plaintext query, wherein a character overlap between shingles generated from the plaintext query is less than the at least one character overlap of the shingles generated from the artifacts; determining, by the processor, whether any of the plurality of query fingerprints matches any of the artifact fingerprints stored in the database by performing a cosine distance calculation; and outputting an indication of an artifact containing a matched fingerprint.
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12. A method, comprising: obtaining, by a processor, a plurality of artifacts in plaintext form; generating, by the processor, fingerprints for each of the plurality of artifacts by generating shingles from text within each of the plurality of artifacts so that there at least one character overlap between adjacent shingles; and cryptographically hashing the shingles to generate a plurality of artifact fingerprints; storing the artifact fingerprints in a database; receiving, by the processor, a plurality of query fingerprints, each of which is generated by cryptographically hashing shingles of a plaintext query, wherein a character overlap between shingles generated from the plaintext query is less than the at least one character overlap of the shingles generated from the artifacts; determining, by the processor, whether any of the plurality of query fingerprints matches any of the artifact fingerprints stored in the database by performing a cosine distance calculation; and outputting an indication of an artifact containing a matched fingerprint. 13. The method of claim 12 , wherein the cosine distance calculation is performed between each of the artifact fingerprints stored in the database to produce a median artifact similarity score, the cosine distance calculation is performed between each of the plurality of query fingerprints and each of the artifact fingerprints to produce individual query fingerprint scores, and a match between the any of the query fingerprints and any of the artifact fingerprints is determined based on both the median artifact similarity score and the individual query fingerprint similarity scores.
| 0.541799 |
1. In a system comprising one or more computing devices, a method for automatically generating an audiovisual work, the method comprising: inferentially selecting one or more design animation modules from among a plurality of design animation modules to use to generate an audiovisual work based at least upon all of: (a) one or more first metadata values reflecting one or more detected visual characteristics of at least one of one or more digital visual media items, (b) one or more second metadata values reflecting one or more detected audio characteristics of at least one of one or more digital audio media items and comprising beat timing information pertaining to the at least one digital audio media item, and (c) one or more third metadata values associated with at least one of the plurality of design animation modules and comprising beat timing information pertaining to the at least one design animation module; wherein each design animation module of the plurality of design animation modules is an independent interchangeable unit that can be combined with other design animation modules of the plurality of design animation modules to form different audiovisual works; wherein the one or more selected design animation modules comprises the at least one design animation module; wherein inferentially selecting the at least one design animation module comprises comparing the beat timing information of the one or more second metadata values pertaining to the at least one digital audio media item to the beat timing information of the one or more third metadata values pertaining to the at least one design animation module; wherein the at least one design animation modules comprises a specification of an animation scene; assigning the at least one digital visual media item to the at least one design animation module including incorporating the at least one digital visual media item into the specification of the animation scene; and generating the audiovisual work using the one or more selected design animation modules, the one or more digital visual media items, and the one or more digital audio media items; wherein the method is performed by the one or more computing devices.
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1. In a system comprising one or more computing devices, a method for automatically generating an audiovisual work, the method comprising: inferentially selecting one or more design animation modules from among a plurality of design animation modules to use to generate an audiovisual work based at least upon all of: (a) one or more first metadata values reflecting one or more detected visual characteristics of at least one of one or more digital visual media items, (b) one or more second metadata values reflecting one or more detected audio characteristics of at least one of one or more digital audio media items and comprising beat timing information pertaining to the at least one digital audio media item, and (c) one or more third metadata values associated with at least one of the plurality of design animation modules and comprising beat timing information pertaining to the at least one design animation module; wherein each design animation module of the plurality of design animation modules is an independent interchangeable unit that can be combined with other design animation modules of the plurality of design animation modules to form different audiovisual works; wherein the one or more selected design animation modules comprises the at least one design animation module; wherein inferentially selecting the at least one design animation module comprises comparing the beat timing information of the one or more second metadata values pertaining to the at least one digital audio media item to the beat timing information of the one or more third metadata values pertaining to the at least one design animation module; wherein the at least one design animation modules comprises a specification of an animation scene; assigning the at least one digital visual media item to the at least one design animation module including incorporating the at least one digital visual media item into the specification of the animation scene; and generating the audiovisual work using the one or more selected design animation modules, the one or more digital visual media items, and the one or more digital audio media items; wherein the method is performed by the one or more computing devices. 8. The method of claim 1 , further comprising: prior to inferentially selecting the one or more design animation modules, receiving a specification of an online service from which the one or more digital audio media items can be downloaded; and downloading the one or more digital audio media items from the online service responsive to receiving the specification.
| 0.589012 |
1. A method for converting a text sentence into an image sentence, the method comprising: receiving a text sentence comprising a plurality of words, wherein the text sentence includes a verb phrase, and wherein the text sentence is associated with a plurality of semantic roles; querying an image database, the image database having stored therein a plurality of candidate images, at least a portion of which are tagged with image content descriptors; making a determination that none of the candidate images in the image database captures each of the plurality of semantic roles associated with the text sentence; in response to making the determination, generating first and second sentence fragments from the text sentence, wherein each of the first and second sentence fragments is associated with a respective first and second fragmented semantic role; identifying a first subset of the candidate images that are stored in the image database, each of which captures the first fragmented semantic role; generating a first feature vector characterizing the first subset of candidate images stored in the image database; and identifying a first particular one of the candidate images in the first subset that is characterized by features closest to a first mean value derived from the first feature vector.
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1. A method for converting a text sentence into an image sentence, the method comprising: receiving a text sentence comprising a plurality of words, wherein the text sentence includes a verb phrase, and wherein the text sentence is associated with a plurality of semantic roles; querying an image database, the image database having stored therein a plurality of candidate images, at least a portion of which are tagged with image content descriptors; making a determination that none of the candidate images in the image database captures each of the plurality of semantic roles associated with the text sentence; in response to making the determination, generating first and second sentence fragments from the text sentence, wherein each of the first and second sentence fragments is associated with a respective first and second fragmented semantic role; identifying a first subset of the candidate images that are stored in the image database, each of which captures the first fragmented semantic role; generating a first feature vector characterizing the first subset of candidate images stored in the image database; and identifying a first particular one of the candidate images in the first subset that is characterized by features closest to a first mean value derived from the first feature vector. 5. The method of claim 1 , wherein a Quadratic-Chi histogram distance is used to quantify a distance between features characterizing the first particular one of the candidate images and the first mean value.
| 0.692053 |
16. A computing system for processing a request for a document search comprising: a memory storing a document summaries index file comprising an index portion and a records portion, the index portion comprising a plurality of document identifiers each identifying a document and the records portion comprising at least one record for each document identifier, each record having a structure comprising a name field, a type field, and a value field; and a processor configured to receive a query from an application programming interface for the document search wherein the query comprises a search term identifier and a search term value, compare each record in the records portion to ascertain whether the search term identifier matches the name field and if so whether the search term value matches the value field, and provide to the application programming interface that generated the query each document identifier where the search term identifier matches the name field and the search term value matches the value field.
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16. A computing system for processing a request for a document search comprising: a memory storing a document summaries index file comprising an index portion and a records portion, the index portion comprising a plurality of document identifiers each identifying a document and the records portion comprising at least one record for each document identifier, each record having a structure comprising a name field, a type field, and a value field; and a processor configured to receive a query from an application programming interface for the document search wherein the query comprises a search term identifier and a search term value, compare each record in the records portion to ascertain whether the search term identifier matches the name field and if so whether the search term value matches the value field, and provide to the application programming interface that generated the query each document identifier where the search term identifier matches the name field and the search term value matches the value field. 17. The computing system of claim 16 , wherein the name field indicates the value field stores an author name and the value field indicates the author name.
| 0.590666 |
17. A system for increasing the accuracy of optical character recognition (OCR) for at least one item, comprising: at least one processor, wherein the at least one processor is configured to perform: obtaining OCR results of OCR scanning from at least one OCR module; creating at least one OCR seed using at least a portion of the OCR results, the at least one OCR seed comprising a plurality of imagelets corresponding to each character identified in the at least a portion of the OCR results, wherein the at least one OCR seed is cleaned by selecting imagelets similar to one another for each character identified in the at least a portion of the OCR results; creating at least one OCR learn set using at least a portion of the OCR seed; comparing the at least one OCR learn set to each imagelet to create at least one mismatch distribution of the at least one OCR learn set compared to each imagelet, the at least one mismatch distribution comprising at least one confidence rating including a confidence score for the imagelet compared to at least one possible character; and applying the OCR learn set and the at least one mismatch distribution to the at least one item to obtain additional OCR results such that only possible characters having a confidence score higher than a threshold are considered when applying the at least one mismatch distribution to obtain the additional OCR results.
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17. A system for increasing the accuracy of optical character recognition (OCR) for at least one item, comprising: at least one processor, wherein the at least one processor is configured to perform: obtaining OCR results of OCR scanning from at least one OCR module; creating at least one OCR seed using at least a portion of the OCR results, the at least one OCR seed comprising a plurality of imagelets corresponding to each character identified in the at least a portion of the OCR results, wherein the at least one OCR seed is cleaned by selecting imagelets similar to one another for each character identified in the at least a portion of the OCR results; creating at least one OCR learn set using at least a portion of the OCR seed; comparing the at least one OCR learn set to each imagelet to create at least one mismatch distribution of the at least one OCR learn set compared to each imagelet, the at least one mismatch distribution comprising at least one confidence rating including a confidence score for the imagelet compared to at least one possible character; and applying the OCR learn set and the at least one mismatch distribution to the at least one item to obtain additional OCR results such that only possible characters having a confidence score higher than a threshold are considered when applying the at least one mismatch distribution to obtain the additional OCR results. 28. The system of claim 17 , wherein the OCR learn set is created by obtaining information related to the image representation for each character and the variability of the similar imagelets from the image representation for each character in the at least one OCR cleaned seed.
| 0.504332 |
1. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions executable by the processor to: group users into a plurality of distinct communities according to one or more grouping criteria, such that for each particular one of the communities, members of the particular community share at least one grouping criterion in common, and wherein membership of at least some of the communities does not completely overlap; store indications of membership of each of the communities; receive a query from a member of one or more of the communities, and in response to the query: obtain results of the query; determine one or more of the plurality of communities to associate with the query, wherein the determining comprises comparing the query to queries entered by other members of the one or more of the plurality of communities such that the member from which the query is received is a member of the determined one or more communities, and the determined one or more communities are distinct from others of the plurality of communities; identify other results from only the determined one or more communities, wherein the other results are for at least one other query from at least one other member of the determined one or more communities, and wherein the other results reflect user feedback from the at least one other member of the determined one or more communities; compare the results to the other results from the determined one or more communities to determine a measure of similarity between the results and the other results; and modify the results according to the other results in response to determining that the measure of similarity is above a predetermined threshold, wherein the results are not modified according to the other results if the measure of similarity is not above the predetermined threshold.
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1. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions executable by the processor to: group users into a plurality of distinct communities according to one or more grouping criteria, such that for each particular one of the communities, members of the particular community share at least one grouping criterion in common, and wherein membership of at least some of the communities does not completely overlap; store indications of membership of each of the communities; receive a query from a member of one or more of the communities, and in response to the query: obtain results of the query; determine one or more of the plurality of communities to associate with the query, wherein the determining comprises comparing the query to queries entered by other members of the one or more of the plurality of communities such that the member from which the query is received is a member of the determined one or more communities, and the determined one or more communities are distinct from others of the plurality of communities; identify other results from only the determined one or more communities, wherein the other results are for at least one other query from at least one other member of the determined one or more communities, and wherein the other results reflect user feedback from the at least one other member of the determined one or more communities; compare the results to the other results from the determined one or more communities to determine a measure of similarity between the results and the other results; and modify the results according to the other results in response to determining that the measure of similarity is above a predetermined threshold, wherein the results are not modified according to the other results if the measure of similarity is not above the predetermined threshold. 6. The system of claim 1 , wherein to modify the results the program instructions are further executable to aggregate the results and the other results to produce aggregated results, wherein the aggregated results include at least one result from the other results that was not in the results obtained for the query.
| 0.544961 |
11. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device to perform operations comprising: receiving a voice request from a user at a device; generating, on the device, a user identifier using the voice request and time-based rules associated with the device; comparing stored user identities to the user identifier, to yield a comparison; estimating, via successive comparisons, a background noise parameter and a transducer noise parameter, wherein a delay between the successive comparisons is increased when successive changes do not exceed a threshold value; and when, based on the comparison, the user is associated with the device: retrieving a parameterizable speaker independent speech recognition model associated with the user identifier; and adapting the parameterizable speaker independent speech recognition model based on the background noise parameter and the transducer noise parameter.
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11. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device to perform operations comprising: receiving a voice request from a user at a device; generating, on the device, a user identifier using the voice request and time-based rules associated with the device; comparing stored user identities to the user identifier, to yield a comparison; estimating, via successive comparisons, a background noise parameter and a transducer noise parameter, wherein a delay between the successive comparisons is increased when successive changes do not exceed a threshold value; and when, based on the comparison, the user is associated with the device: retrieving a parameterizable speaker independent speech recognition model associated with the user identifier; and adapting the parameterizable speaker independent speech recognition model based on the background noise parameter and the transducer noise parameter. 12. The computer-readable storage device of claim 11 , wherein generating the user identifier occurs after receiving a unique user code at a beginning of a usage session.
| 0.672098 |
15. The computing device of claim 14 , wherein the second region contains at least one second object, and wherein the second region is processed using the visual recognition technique without the at least one image quality enhancement being performed on the second region.
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15. The computing device of claim 14 , wherein the second region contains at least one second object, and wherein the second region is processed using the visual recognition technique without the at least one image quality enhancement being performed on the second region. 18. The computing device of claim 15 , wherein a user selects the first region by at least one of tapping, touching, or hovering a finger above the first region of the display screen.
| 0.879571 |
7. The method of claim 1 , further including: determining whether the clock process includes a sensitivity list; identifying an IF statement in the clock process that includes the sensitivity list; identifying conditions associated with the IF statement, if any; and determining a clock clause from the IF statement and associated conditions.
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7. The method of claim 1 , further including: determining whether the clock process includes a sensitivity list; identifying an IF statement in the clock process that includes the sensitivity list; identifying conditions associated with the IF statement, if any; and determining a clock clause from the IF statement and associated conditions. 8. The method of claim 7 , wherein the determining the clock clause further comprises: checking a form of the clock clause; checking for an assignment to a state variable by the clock clause; and checking for a case statement test of the state variable.
| 0.752309 |
3. The cross-language system of claim 2 , wherein the machine translation system or a second machine translation system is configured for translating user queries into at least one of the first and second languages; and the cross-language system further comprising a search engine configured for querying the first and second archives based on the user queries and user queries translated by the machine translation system.
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3. The cross-language system of claim 2 , wherein the machine translation system or a second machine translation system is configured for translating user queries into at least one of the first and second languages; and the cross-language system further comprising a search engine configured for querying the first and second archives based on the user queries and user queries translated by the machine translation system. 4. The cross-language system of claim 3 , wherein the user interface is configured for allowing a user to enter a query in the user's language, and for displaying a representation of responses to the queries retrieved from the archives by the search engine.
| 0.821913 |
3. The method as in claim 1 , further comprising displaying a first document tab identifying an active view of the single switchable view.
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3. The method as in claim 1 , further comprising displaying a first document tab identifying an active view of the single switchable view. 4. The method as in claim 3 , further comprising displaying a second document tab identifying an inactive view of the single switchable view.
| 0.968584 |
9. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, cause the one or more processors to perform operations, the operations comprising: obtaining aligned voice data that comprises untransformed voice data in a target language that has been aligned with phonemes in a corresponding textual transcript using a source acoustic model for a source language, wherein the source acoustic model includes information that maps acoustic features of the source language to phonemes in a transformed feature space, and the untransformed voice data is in an untransformed feature space; transforming the aligned voice data according to a particular transform operation, using the source acoustic model, to obtain transformed voice data; adapting the source acoustic model to the target language using the untransformed voice data in the target language to obtain an adapted acoustic model; and training a target acoustic model for the target language using the transformed voice data and the adapted acoustic model; and providing the target acoustic model in association with the target language.
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9. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, cause the one or more processors to perform operations, the operations comprising: obtaining aligned voice data that comprises untransformed voice data in a target language that has been aligned with phonemes in a corresponding textual transcript using a source acoustic model for a source language, wherein the source acoustic model includes information that maps acoustic features of the source language to phonemes in a transformed feature space, and the untransformed voice data is in an untransformed feature space; transforming the aligned voice data according to a particular transform operation, using the source acoustic model, to obtain transformed voice data; adapting the source acoustic model to the target language using the untransformed voice data in the target language to obtain an adapted acoustic model; and training a target acoustic model for the target language using the transformed voice data and the adapted acoustic model; and providing the target acoustic model in association with the target language. 16. The system of claim 9 , wherein the target language and the source language comprise languages that are different from each other.
| 0.888797 |
19. The computing device of claim 17 , wherein: the processor is further configured with processor-executable instructions to generate the lean classifier model based on the full classifier model.
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19. The computing device of claim 17 , wherein: the processor is further configured with processor-executable instructions to generate the lean classifier model based on the full classifier model. 20. The computing device of claim 19 , wherein the processor is further configured with processor-executable instructions such that generating the lean classifier model based on the full classifier model is performed by: generating a list of boosted decision stumps by converting a finite state machine included in the full classifier model into a plurality of boosted decision stumps; determining a number of different test conditions that should be evaluated to classify the device behavior of the computing device without consuming an excessive amount of processing, memory, or energy resources of the computing device; generating a list of test conditions by sequentially traversing the list of boosted decision stumps and inserting a test condition associated with each sequentially traversed boosted decision stump into the list of test conditions until the list of test conditions includes the number of different test conditions; and generating the lean classifier model to include only those boosted decision stumps that test one of a plurality of test conditions included in the list of test conditions.
| 0.609692 |
5. The method of claim 4 , further comprising in response to an update event from an indexing engine associated with the full-text search engine that an index associated with an underlying database has been changed, recaching the filter object in the cache memory of the ORM system to reflect the changed index.
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5. The method of claim 4 , further comprising in response to an update event from an indexing engine associated with the full-text search engine that an index associated with an underlying database has been changed, recaching the filter object in the cache memory of the ORM system to reflect the changed index. 6. The method of claim 5 , further comprising in response to a request to set a parameter of the filter identified by the filter name, invoking the filter factory associated with the filter name to configure the parameter of the filter.
| 0.938596 |
1. A computing system hosting an in-memory database, the system comprising: a partitioner node comprising a processor configured to, in response to receiving a collection of one or more records of the in-memory database, determine whether to compress the collection based on a machine-readable schema file associated with the collection, logically partition the collection into one or more partitions according to the schema file, and distribute the one or more partitions to one or more storage nodes according to the schema file; a storage node comprising a non-transitory machine-readable main memory storing a partition of the in-memory database received from one or more partitioner nodes associated with the storage node according to the schema file; a search manager node comprising a processor configured to receive a search query from a client device of the system, and transmit the search queries as search conductor queries to one or more search conductors upon receiving the search query from the client device, wherein the search query is a machine-readable computer file containing parameters associated with one or more records satisfying the search query, and wherein the search manager node transmits the search queries to the one or more search conductors in accordance with the schema file; a search conductor node associated with one or more partitioners according to the schema file and comprising a processor configured to, in response to receiving a search conductor query from the search manager node: query a set of one or more partitions of the in-memory database as indicated by the search conductor query, identify one or more candidate records of the in-memory database stored in the set of partitions queried by the search conductor, calculate a first score for each respective candidate record using a scoring algorithm, and transmit to the search manager node a set of one or more query results containing one or more candidate records satisfying a threshold value; and an analytics agent node comprising a processor configured to automatically generate a machine-readable computer file containing a set of one or more results derived from the set of query results, responsive to identifying in the set of query results received from the search manager node, wherein each of the storage node, the search conductor node, and the analytics agent node is a distinct node.
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1. A computing system hosting an in-memory database, the system comprising: a partitioner node comprising a processor configured to, in response to receiving a collection of one or more records of the in-memory database, determine whether to compress the collection based on a machine-readable schema file associated with the collection, logically partition the collection into one or more partitions according to the schema file, and distribute the one or more partitions to one or more storage nodes according to the schema file; a storage node comprising a non-transitory machine-readable main memory storing a partition of the in-memory database received from one or more partitioner nodes associated with the storage node according to the schema file; a search manager node comprising a processor configured to receive a search query from a client device of the system, and transmit the search queries as search conductor queries to one or more search conductors upon receiving the search query from the client device, wherein the search query is a machine-readable computer file containing parameters associated with one or more records satisfying the search query, and wherein the search manager node transmits the search queries to the one or more search conductors in accordance with the schema file; a search conductor node associated with one or more partitioners according to the schema file and comprising a processor configured to, in response to receiving a search conductor query from the search manager node: query a set of one or more partitions of the in-memory database as indicated by the search conductor query, identify one or more candidate records of the in-memory database stored in the set of partitions queried by the search conductor, calculate a first score for each respective candidate record using a scoring algorithm, and transmit to the search manager node a set of one or more query results containing one or more candidate records satisfying a threshold value; and an analytics agent node comprising a processor configured to automatically generate a machine-readable computer file containing a set of one or more results derived from the set of query results, responsive to identifying in the set of query results received from the search manager node, wherein each of the storage node, the search conductor node, and the analytics agent node is a distinct node. 20. The system according to claim 1 , wherein the search conductor limits the size of the search result records based on the search query received from the search manager.
| 0.572663 |
4. A graphical user interface produced by a computing device and presented on a display associated with the computing device, comprising: a media window presented on the display, said media window having a search text box and a search assistant, wherein said search assistant depicts a plurality of categories and a plurality of fields, wherein said search assistant horizontally and simultaneously depicts the categories and the fields in a horizontal row, wherein a user can interact with said search assistant to select one of the categories and one of the fields, wherein the fields depicted in said search assistant are dynamically determined based on a user selection of one of the categories, wherein the different categories horizontally depicted in the search assistant pertain to at least a music category and a video category, when the music category is selected, the one or more fields being dynamically determined and horizontally depicted include at least one of artist, album, composer and song, and when the video category is selected, the one or more fields being dynamically determined and horizontally depicted include at least one of artist, album and title.
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4. A graphical user interface produced by a computing device and presented on a display associated with the computing device, comprising: a media window presented on the display, said media window having a search text box and a search assistant, wherein said search assistant depicts a plurality of categories and a plurality of fields, wherein said search assistant horizontally and simultaneously depicts the categories and the fields in a horizontal row, wherein a user can interact with said search assistant to select one of the categories and one of the fields, wherein the fields depicted in said search assistant are dynamically determined based on a user selection of one of the categories, wherein the different categories horizontally depicted in the search assistant pertain to at least a music category and a video category, when the music category is selected, the one or more fields being dynamically determined and horizontally depicted include at least one of artist, album, composer and song, and when the video category is selected, the one or more fields being dynamically determined and horizontally depicted include at least one of artist, album and title. 15. A graphical user interface as recited in claim 4 , wherein the different categories horizontally depicted in the search assistant further includes a podcast category, and when the podcasts category is selected, the fields being dynamically determined and horizontally depicted include at least one of author and title.
| 0.608027 |
7. The RDF network construction device according to claim 1 , wherein the RDF triple includes a single RDF triple composed of two classes and one property and a multi-RDF triple composed of two or more classes and two or more properties.
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7. The RDF network construction device according to claim 1 , wherein the RDF triple includes a single RDF triple composed of two classes and one property and a multi-RDF triple composed of two or more classes and two or more properties. 8. The RDF network construction device according to claim 7 , wherein the multi-RDF triple is implemented by connecting two or more of the single RDF triples.
| 0.979457 |
1. A translation method adapted to a domain of interest comprising: receiving a source text string comprising a sequence of source words in a source language; generating a set of candidate translations of the source text string, each candidate translation comprising a sequence of target words in a target language; and with a processor, identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: bilingual probabilities, each bilingual probability being for a source text fragment and a target text fragment of the source text string and candidate translation respectively, the bilingual probabilities being estimated on an out-of-domain parallel corpus comprising source and target strings; and monolingual probabilities for text fragments of one of the source text string and candidate translation, the monolingual probabilities being estimated on an in-domain monolingual corpus, wherein the domain-adapted feature comprises at least one of: a) a forward domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( s i ❘ t j ) where w in (s i |t j ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (s i ); b) a reverse domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( t j ❘ s i ) where w in (t j |s i ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (t j ); c) a forward domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( s _ i ❘ t _ j ) , where phr in ( s i | t j ) is an adapted phrase probability and is a function of a product of phr out ( t j | s i ) and p in ( s i ); d) a reverse domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( t _ j ❘ s _ i ) , where phr in ( t j | s i ) is an adapted phrase probability and is a function of a product of phr out ( s i | t j ) and p in ( t j ); where s i and t j represent words of the source string and candidate translation respectively which are aligned in an alignment α of the source string and candidate translation, w out (t j |s i ) represents the bilingual probability, which is a word probability for target word t j in the presence of source word s i , derived from the parallel corpus, and w in (s i ) represents the monolingual probability, which is the word probability for source word s i derived from the in-domain monolingual corpus; s i and t j represent phrases of the source string and candidate translation respectively which are aligned in the alignment α of the source string and candidate translation, phr out ( t j | s i )represents the bilingual probability, which is a phrasal probability for target phrase t j in the presence of source phrase s i , derived from the parallel corpus, p in ( s i ) represents the monolingual probability, which is the phrasal probability for source phrase s i derived from the in-domain monolingual corpus, and p in ( t j ) represents the monolingual probability, which is the phrasal probability for target phrase t j derived from the in-domain monolingual corpus.
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1. A translation method adapted to a domain of interest comprising: receiving a source text string comprising a sequence of source words in a source language; generating a set of candidate translations of the source text string, each candidate translation comprising a sequence of target words in a target language; and with a processor, identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: bilingual probabilities, each bilingual probability being for a source text fragment and a target text fragment of the source text string and candidate translation respectively, the bilingual probabilities being estimated on an out-of-domain parallel corpus comprising source and target strings; and monolingual probabilities for text fragments of one of the source text string and candidate translation, the monolingual probabilities being estimated on an in-domain monolingual corpus, wherein the domain-adapted feature comprises at least one of: a) a forward domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( s i ❘ t j ) where w in (s i |t j ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (s i ); b) a reverse domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a w in ( t j ❘ s i ) where w in (t j |s i ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (t j ); c) a forward domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( s _ i ❘ t _ j ) , where phr in ( s i | t j ) is an adapted phrase probability and is a function of a product of phr out ( t j | s i ) and p in ( s i ); d) a reverse domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a phr in ( t _ j ❘ s _ i ) , where phr in ( t j | s i ) is an adapted phrase probability and is a function of a product of phr out ( s i | t j ) and p in ( t j ); where s i and t j represent words of the source string and candidate translation respectively which are aligned in an alignment α of the source string and candidate translation, w out (t j |s i ) represents the bilingual probability, which is a word probability for target word t j in the presence of source word s i , derived from the parallel corpus, and w in (s i ) represents the monolingual probability, which is the word probability for source word s i derived from the in-domain monolingual corpus; s i and t j represent phrases of the source string and candidate translation respectively which are aligned in the alignment α of the source string and candidate translation, phr out ( t j | s i )represents the bilingual probability, which is a phrasal probability for target phrase t j in the presence of source phrase s i , derived from the parallel corpus, p in ( s i ) represents the monolingual probability, which is the phrasal probability for source phrase s i derived from the in-domain monolingual corpus, and p in ( t j ) represents the monolingual probability, which is the phrasal probability for target phrase t j derived from the in-domain monolingual corpus. 15. The method of claim 1 , wherein the parallel corpus comprises translations pairs, each translation pair comprising a source text string comprising words in the source language and a target text string comprising words in the target language, one of the source and target text strings having been determined to be a translation of the other.
| 0.515091 |
1. A computer-implemented method of incremental relation extraction, comprising: performed by one or more processors executing computer-readable instructions: receiving a relationship seed comprising relationship data and an initial model describing an entity relationship from an input device coupled to the one or more processors; learning a new model describing an additional entity relationship; extracting a relation tuple comprising additional relationship data from a data corpus by applying the newly learned model; generating one or more patterns based on the extracted relation tuple; and selecting at least one of the one or more patterns for learning an additional new model.
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1. A computer-implemented method of incremental relation extraction, comprising: performed by one or more processors executing computer-readable instructions: receiving a relationship seed comprising relationship data and an initial model describing an entity relationship from an input device coupled to the one or more processors; learning a new model describing an additional entity relationship; extracting a relation tuple comprising additional relationship data from a data corpus by applying the newly learned model; generating one or more patterns based on the extracted relation tuple; and selecting at least one of the one or more patterns for learning an additional new model. 13. The computer-implemented method of claim 1 , further comprising: clustering the extracted relation tuples to connect same-type relation tuples; and outputting the clustered, connected relation tuples to an output device coupled to the one or more processors.
| 0.776869 |
4. The method of claim 3 further comprising re-defining one or more parameters by revising fields and subfields of the associated database, and generating a new expression including the one or more parameters.
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4. The method of claim 3 further comprising re-defining one or more parameters by revising fields and subfields of the associated database, and generating a new expression including the one or more parameters. 5. The method of claim 4 wherein re-defining one or more parameters comprises adding additional fields and subfields to the associated database.
| 0.88743 |
1. A system comprising: a computer-readable memory storing executable instructions; and one or more physical computer processors in communication with the computer-readable memory, wherein the one or more physical computer processors are programmed by the executable instructions to at least: obtain audio data regarding a user utterance, the audio data comprising a sequence of frames; identify, for a current frame of the sequence of frames, (1) one or more speech recognition decoding graph states corresponding to the current frame, and (2) a window of frames preceding the current frame in the sequence of frames; generate, for a first state of the one or more speech recognition decoding graph states, a parameter of a probability density function, wherein the parameter is generated using an artificial neural network, and wherein input into the artificial neural network comprises data regarding the first state and a plurality of feature vectors corresponding to the window of frames; generate, for the first state of the one or more speech recognition decoding graph states, a first score using a feature vector corresponding to the current frame and the parameter of the probability density function generated using the first state; and select at least one state to add to the speech recognition decoding graph based at least partly on the first score and the first state.
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1. A system comprising: a computer-readable memory storing executable instructions; and one or more physical computer processors in communication with the computer-readable memory, wherein the one or more physical computer processors are programmed by the executable instructions to at least: obtain audio data regarding a user utterance, the audio data comprising a sequence of frames; identify, for a current frame of the sequence of frames, (1) one or more speech recognition decoding graph states corresponding to the current frame, and (2) a window of frames preceding the current frame in the sequence of frames; generate, for a first state of the one or more speech recognition decoding graph states, a parameter of a probability density function, wherein the parameter is generated using an artificial neural network, and wherein input into the artificial neural network comprises data regarding the first state and a plurality of feature vectors corresponding to the window of frames; generate, for the first state of the one or more speech recognition decoding graph states, a first score using a feature vector corresponding to the current frame and the parameter of the probability density function generated using the first state; and select at least one state to add to the speech recognition decoding graph based at least partly on the first score and the first state. 2. The system of claim 1 , wherein the probability density function models a distribution of feature vectors that correspond to a given state and a given set of preceding frames.
| 0.58079 |
15. The system of claim 13 , wherein the controller processor device further generates task suggestion based on task descriptions, wherein a task description comprises task external description, task properties, task functionalities and task actions.
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15. The system of claim 13 , wherein the controller processor device further generates task suggestion based on task descriptions, wherein a task description comprises task external description, task properties, task functionalities and task actions. 19. The system of claim 15 , wherein the task action describe the sequencing and combinations of the devices that fulfill the required functionalities.
| 0.888282 |
27. A system for dynamic adjustment of audio prompts in response to a users interaction modality with a communications device having a multimodal interface comprising a speech interface for accessing a speech recognizer and another interface, comprising: means for determining the mode of user input modality and selecting a corresponding one of a foreground state and a background state of the speech interface.
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27. A system for dynamic adjustment of audio prompts in response to a users interaction modality with a communications device having a multimodal interface comprising a speech interface for accessing a speech recognizer and another interface, comprising: means for determining the mode of user input modality and selecting a corresponding one of a foreground state and a background state of the speech interface. 32. A system according to claim 27 comprising means for selecting an appropriate foreground state or background state of the speech interface according to a selection system when input is captured for multiple input modalities.
| 0.637143 |
1. A treatment system for modulating, approximating, or optimizing desired facial expressions by measuring personal degrees of expression of facial features in terms of Specific features, Relative distances, Elevations, Depression, Interacting features, and Coactivated distances (SREDIC) scores specifying expression intensity of individual Facial Expression Activated Markers (FEAMs) that are functionally classified and analyzed as personal relative distances between features, facial deformations and co-activated features before and after applying an agent or procedure to the face, head, or neck of a patient, the system comprising: a processor; a plurality of non-volatile program-memory locations coupled to the processor; a plurality of non-volatile data-memory locations coupled to the processor; a display device configured to be controlled by the processor; and, a camera configured to be controlled by the processor, wherein the plurality of non-volatile program-memory locations contains instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving an image file of a full human face of a patient, the image file captured by the camera, the image file corresponding to a facial expression desired to be changed by the patient; sending for display on the display device the received image file; receiving, from the patient, information representative of a desired degree of change in the expression intensity of one or more selected Facial-Expression Activation Markers (FEAMs) of the facial expression desired to be changed; retrieving from the non-volatile data memory locations a SREDIC score that is associated with the selected one or more FEAMs, wherein the SREDIC score is based on personal relative distances between features, facial deformations and co-activated features of the patient associated with the selected one or more FEAMs, and corresponding facial muscles or facial muscle groups, wherein each of the corresponding facial muscles or facial muscle groups have an activation intensity level specified in terms of the degree and gradation level of FEAMs expressions; retrieving from the non-volatile data memory locations psycho-physiological states for which the SREDIC score is shared with, or functionally related to, the corresponding facial muscles or facial muscle groups of the retrieved SREDIC score; receiving image files of facial expressions corresponding with the retrieved psycho-physiological states; and generating, in response to the SREDIC score, the retrieved expressions of psycho-physiological states, and the received desired degree of change in the expression intensity, a treatment program comprising one or more treatments at one or more treatment locations for approximating the desired facial expression while producing optimized corresponding changes in the expression of each of two or more psychophysiological states, each of the one or more treatment locations targeting one of the one or more selected FEAMs and corresponding facial muscles or facial muscle groups, each of the one or more treatment locations having an associated treatment and dosage information for each FEAM.
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1. A treatment system for modulating, approximating, or optimizing desired facial expressions by measuring personal degrees of expression of facial features in terms of Specific features, Relative distances, Elevations, Depression, Interacting features, and Coactivated distances (SREDIC) scores specifying expression intensity of individual Facial Expression Activated Markers (FEAMs) that are functionally classified and analyzed as personal relative distances between features, facial deformations and co-activated features before and after applying an agent or procedure to the face, head, or neck of a patient, the system comprising: a processor; a plurality of non-volatile program-memory locations coupled to the processor; a plurality of non-volatile data-memory locations coupled to the processor; a display device configured to be controlled by the processor; and, a camera configured to be controlled by the processor, wherein the plurality of non-volatile program-memory locations contains instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving an image file of a full human face of a patient, the image file captured by the camera, the image file corresponding to a facial expression desired to be changed by the patient; sending for display on the display device the received image file; receiving, from the patient, information representative of a desired degree of change in the expression intensity of one or more selected Facial-Expression Activation Markers (FEAMs) of the facial expression desired to be changed; retrieving from the non-volatile data memory locations a SREDIC score that is associated with the selected one or more FEAMs, wherein the SREDIC score is based on personal relative distances between features, facial deformations and co-activated features of the patient associated with the selected one or more FEAMs, and corresponding facial muscles or facial muscle groups, wherein each of the corresponding facial muscles or facial muscle groups have an activation intensity level specified in terms of the degree and gradation level of FEAMs expressions; retrieving from the non-volatile data memory locations psycho-physiological states for which the SREDIC score is shared with, or functionally related to, the corresponding facial muscles or facial muscle groups of the retrieved SREDIC score; receiving image files of facial expressions corresponding with the retrieved psycho-physiological states; and generating, in response to the SREDIC score, the retrieved expressions of psycho-physiological states, and the received desired degree of change in the expression intensity, a treatment program comprising one or more treatments at one or more treatment locations for approximating the desired facial expression while producing optimized corresponding changes in the expression of each of two or more psychophysiological states, each of the one or more treatment locations targeting one of the one or more selected FEAMs and corresponding facial muscles or facial muscle groups, each of the one or more treatment locations having an associated treatment and dosage information for each FEAM. 2. The treatment system of claim 1 , further comprising a dosing station configured to be controlled by the processor according to the generated treatment program.
| 0.544378 |
16. A system to process log data, comprising: a communication interface; and a processor coupled to the communication interface and configured to: determine a parser definition associated with a set of log data; compile the parser definition to create an instance of a parser to parse the set of log data, wherein the parser has a hierarchical structure comprising a plurality of hierarchically related nodes, each of at least a subset of said nodes having associated therewith one or more actors each configured to parse data associated with that node; and send at least a portion of the set of log data to the parser instance prior to compilation of said parser instance being completed; wherein a first node of said parser instance is configured to receive and parse log data associated with the first node even if compilation of the parser definition has not been completed with respect to a second node of said parser instance.
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16. A system to process log data, comprising: a communication interface; and a processor coupled to the communication interface and configured to: determine a parser definition associated with a set of log data; compile the parser definition to create an instance of a parser to parse the set of log data, wherein the parser has a hierarchical structure comprising a plurality of hierarchically related nodes, each of at least a subset of said nodes having associated therewith one or more actors each configured to parse data associated with that node; and send at least a portion of the set of log data to the parser instance prior to compilation of said parser instance being completed; wherein a first node of said parser instance is configured to receive and parse log data associated with the first node even if compilation of the parser definition has not been completed with respect to a second node of said parser instance. 19. The system of claim 16 , wherein the hierarchical structure of the parser corresponds to a hierarchical organization of said set of log data; wherein each node in the hierarchical structure of the parser is associated with a corresponding section comprising the set of log data; and wherein each of the respective actors at each of said at least a subset of said nodes comprising the parser is configured to parse the corresponding section of the set of log data that is associated with that node in parallel with the parsing by actors at the other of said at least a subset of said nodes of the respective sections of the set of log data associated with said other nodes.
| 0.5 |
1. A computer-implemented method, comprising: receiving, by a computing system, a first search query that was typed by a first user input at a computing device into a search input box of a mapping application program at the computing device; parsing, by the computing system, the first search query in order to determine that one or more words in the first search query name a particular geographical location; conducting, by the computing system, a search for first search results that: (i) are responsive to the first search query, and (ii) identify respective first businesses that are geographically located around the particular geographical location that is named by the one or more words in the first search query; sending, by the computing system and for receipt by the computing device, information that identifies the first search results, so as to cause the computing device to present a display of a first geographical area of a map with first graphical interface elements that identify the first search results overlaying the map at locations that correspond to locations on the map of the first businesses; receiving, by the computing system, a second search query that was typed by a second user input at the computing device into the search input box of the mapping application program into which the first search query was typed, wherein the second search query does not include one or more words that name any geographical location; parsing, by the computing system, the second search query in order to identify whether the second search query includes one or more words that name any geographical location; receiving, by the computing system, an indication of a geographical location that is indicated by a presently-displayed geographical area of the map that is being presented by the computing device; conducting, by the computing system, a search for second search results that: (i) are responsive to the second search query, and (ii) identify respective second businesses that are geographically located around the geographical location that is indicated by the presently-displayed geographical area of the map that is being presented by the computing device; and sending, by the computing system and for receipt by the computing device, information that identifies the second search results, so as to cause the computing device to present a display of a second geographical area of the map with second graphical interface elements that identify the second search results overlaying the map at locations that correspond to locations on the map of the second businesses.
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1. A computer-implemented method, comprising: receiving, by a computing system, a first search query that was typed by a first user input at a computing device into a search input box of a mapping application program at the computing device; parsing, by the computing system, the first search query in order to determine that one or more words in the first search query name a particular geographical location; conducting, by the computing system, a search for first search results that: (i) are responsive to the first search query, and (ii) identify respective first businesses that are geographically located around the particular geographical location that is named by the one or more words in the first search query; sending, by the computing system and for receipt by the computing device, information that identifies the first search results, so as to cause the computing device to present a display of a first geographical area of a map with first graphical interface elements that identify the first search results overlaying the map at locations that correspond to locations on the map of the first businesses; receiving, by the computing system, a second search query that was typed by a second user input at the computing device into the search input box of the mapping application program into which the first search query was typed, wherein the second search query does not include one or more words that name any geographical location; parsing, by the computing system, the second search query in order to identify whether the second search query includes one or more words that name any geographical location; receiving, by the computing system, an indication of a geographical location that is indicated by a presently-displayed geographical area of the map that is being presented by the computing device; conducting, by the computing system, a search for second search results that: (i) are responsive to the second search query, and (ii) identify respective second businesses that are geographically located around the geographical location that is indicated by the presently-displayed geographical area of the map that is being presented by the computing device; and sending, by the computing system and for receipt by the computing device, information that identifies the second search results, so as to cause the computing device to present a display of a second geographical area of the map with second graphical interface elements that identify the second search results overlaying the map at locations that correspond to locations on the map of the second businesses. 5. The computer-implemented method of claim 1 , wherein the indication of the geographical location that is indicated by the presently-displayed geographical area of the map is an indication of a centerpoint of the presently-displayed geographical area of the map.
| 0.790679 |
1. An application component distribution system comprising: a repository of semantic models for interdependent ones of application components; a mapping of individual listings in said semantic models to target platform specific installation instructions; and, a script generation engine configured to produce a target specific set of instructions for a specified application component based upon a mapping of at least one of said semantic models in said repository.
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1. An application component distribution system comprising: a repository of semantic models for interdependent ones of application components; a mapping of individual listings in said semantic models to target platform specific installation instructions; and, a script generation engine configured to produce a target specific set of instructions for a specified application component based upon a mapping of at least one of said semantic models in said repository. 2. The application component distribution system of claim 1 , wherein each of said semantic models comprises a listing of component relationships, target platform requirements and platform neutral installation instructions.
| 0.570285 |
1. A computer-implemented method of translating text from a source language to a target language comprising the steps of: (a) detecting a source language on a first communication device; (b) detecting a location of the first communication device; (c) determining the target language based upon the detected location of the first communication device; (d) receiving an input for translation from the first communication device; (e) displaying a list of popular source phrases that are similar to the received input on the first communication device; (f) translating a user selected similar popular source phrase if the user selects the similar popular source phrase, else translating the input by means of a machine translation engine; and (g) displaying the translation output of the user selected similar popular source phrase if the user selected the similar popular source phrase, else determining if the translation output from the machine translation engine has been approved by a human translator, submitting the translation output from the machine translation engine to a human translator and displaying the translation output from the machine translation engine together with a measure of the accuracy of the translation output from the machine translation engine.
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1. A computer-implemented method of translating text from a source language to a target language comprising the steps of: (a) detecting a source language on a first communication device; (b) detecting a location of the first communication device; (c) determining the target language based upon the detected location of the first communication device; (d) receiving an input for translation from the first communication device; (e) displaying a list of popular source phrases that are similar to the received input on the first communication device; (f) translating a user selected similar popular source phrase if the user selects the similar popular source phrase, else translating the input by means of a machine translation engine; and (g) displaying the translation output of the user selected similar popular source phrase if the user selected the similar popular source phrase, else determining if the translation output from the machine translation engine has been approved by a human translator, submitting the translation output from the machine translation engine to a human translator and displaying the translation output from the machine translation engine together with a measure of the accuracy of the translation output from the machine translation engine. 5. The method of claim 1 , wherein receiving the input for translation from the first communication device comprises receiving a text input.
| 0.563455 |
11. The system of claim 10 , wherein the probabilistic matching module is further configured to sum a joint probability of a conditional probability of the first person name given the intended person name, a conditional probability of a person name from the second set of possible intended person names given the intended person name, and the unconditional probability of the intended person name.
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11. The system of claim 10 , wherein the probabilistic matching module is further configured to sum a joint probability of a conditional probability of the first person name given the intended person name, a conditional probability of a person name from the second set of possible intended person names given the intended person name, and the unconditional probability of the intended person name. 12. The system of claim 11 , further comprising a string similarity module configured to filter the person names phonetically similar to the first name to remove person names not sufficiently similar to the first person name.
| 0.848151 |
19. An information-retrieval system for retrieving information from an information source, the information source being periodically updated with current information, comprising: (a) a speech-recognition engine coupled to a processor and a media server and adapted to receive a speech command from a particular user of a plurality of users via an electronic-communication device to access desired information, wherein each of the plurality of users has a respective electronic-communication device, the media server configured to identify and access an information source from a plurality of information sources via the network, the speech-recognition engine adapted to select speech-recognition grammar established to correspond to the speech commands received, the speech-recognition grammar associated with the desired information; (b) the media server, adapted to select at least one information-source-retrieval instruction corresponding to the speech-recognition grammar established for a particular speech command, the at least one information-source-retrieval instruction stored in a database associated with the media server and adapted to retrieve information from a particular one of the information sources that has the desired information; (c) a web-browsing server, adapted to provide access, by the speech command, to a portion of the information source to retrieve the desired information, by using a processor of the web-browsing server, which process (i) performs an instruction that requests information from an identified webpage, and (ii) utilizes a content extractor within the web-browsing server to separate a portion of the information from other information, the information derived from only a portion of the webpage containing information of interest to the particular user, wherein the content extractor uses a content-descriptor file containing a description of the portion of information and wherein the content-descriptor file indicates a location of the portion of the information within the information source and selecting, by the web-browsing server, the desired information from the information source and retrieving only the portion of the information desired by the particular user according to the at least one information-source-retrieval instruction; (d) a speech-synthesis engine coupled to the media server, and adapted to convert the portion of the information from the information source into an audio message for the particular user of the plurality of users and conveying the audio message through the electronic-communication device to the particular user of the plurality of users; and (e) a graphical display interface coupled to the media server and adapted to provide for display the desired information retrieved from the information source to certain others of the plurality of users.
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19. An information-retrieval system for retrieving information from an information source, the information source being periodically updated with current information, comprising: (a) a speech-recognition engine coupled to a processor and a media server and adapted to receive a speech command from a particular user of a plurality of users via an electronic-communication device to access desired information, wherein each of the plurality of users has a respective electronic-communication device, the media server configured to identify and access an information source from a plurality of information sources via the network, the speech-recognition engine adapted to select speech-recognition grammar established to correspond to the speech commands received, the speech-recognition grammar associated with the desired information; (b) the media server, adapted to select at least one information-source-retrieval instruction corresponding to the speech-recognition grammar established for a particular speech command, the at least one information-source-retrieval instruction stored in a database associated with the media server and adapted to retrieve information from a particular one of the information sources that has the desired information; (c) a web-browsing server, adapted to provide access, by the speech command, to a portion of the information source to retrieve the desired information, by using a processor of the web-browsing server, which process (i) performs an instruction that requests information from an identified webpage, and (ii) utilizes a content extractor within the web-browsing server to separate a portion of the information from other information, the information derived from only a portion of the webpage containing information of interest to the particular user, wherein the content extractor uses a content-descriptor file containing a description of the portion of information and wherein the content-descriptor file indicates a location of the portion of the information within the information source and selecting, by the web-browsing server, the desired information from the information source and retrieving only the portion of the information desired by the particular user according to the at least one information-source-retrieval instruction; (d) a speech-synthesis engine coupled to the media server, and adapted to convert the portion of the information from the information source into an audio message for the particular user of the plurality of users and conveying the audio message through the electronic-communication device to the particular user of the plurality of users; and (e) a graphical display interface coupled to the media server and adapted to provide for display the desired information retrieved from the information source to certain others of the plurality of users. 26. The system of claim 19 , further comprising: a database wherein a personal-recognition grammar is stored in the database and relates to web information.
| 0.548191 |
14. The method of claim 1 , wherein the identifying the speaker includes: performing speech recognition to convert the received data into text data; and identifying the speaker based on the text data.
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14. The method of claim 1 , wherein the identifying the speaker includes: performing speech recognition to convert the received data into text data; and identifying the speaker based on the text data. 18. The method of claim 14 , wherein the performing speech recognition includes: performing speech recognition based at least in part on a language model associated with the speaker.
| 0.911656 |
8. An apparatus comprising at least one computer-readable memory device storing instructions configured to cause one or more processing devices to perform operations comprising: identifying a property instantiated in a verification statement; synthesizing an auxiliary verification statement corresponding to the property and a plurality of power domains of a device design, wherein synthesizing the auxiliary verification statement comprising: determining one or more driving power domains of a device design that correspond to the property; determining a condition wherein the driving power domains are active; generating an auxiliary property based on the condition and the property; and generating the auxiliary verification statement based on the auxiliary property.
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8. An apparatus comprising at least one computer-readable memory device storing instructions configured to cause one or more processing devices to perform operations comprising: identifying a property instantiated in a verification statement; synthesizing an auxiliary verification statement corresponding to the property and a plurality of power domains of a device design, wherein synthesizing the auxiliary verification statement comprising: determining one or more driving power domains of a device design that correspond to the property; determining a condition wherein the driving power domains are active; generating an auxiliary property based on the condition and the property; and generating the auxiliary verification statement based on the auxiliary property. 9. The apparatus of claim 8 , wherein the property has a linear temporal logic form pv 1 U pv 2 , where pv represents a proportional variable.
| 0.708647 |
1. A content filtering system for filtering electronic content, the system comprising: a database configured to store user behavior data received from a plurality of client computers and related to a plurality of modalities, wherein at least one of the plurality of modalities comprises one or more web pages of a content publisher; and at least one server in communication with the database and configured to: identify one or more client-side events generated by one or more user interactions with the one or more web pages of the content publisher; store user behavior data in the database, the user behavior data being generated based on the one or more identified client-side events and associated with the one or more web pages; identify, using one or more machine learning processes, key passages of electronic content from at least the one or more web pages based on the user behavior data received from the plurality of client computers, the electronic content comprising electronic text and at least one of the machine learning processes being trained to reject invalid electronic content; rank the identified key passages, wherein to rank the identified key passages the server is further configured to determine a ratio of user interactions with a key passage within the electronic text to total views of the electronic text; and publish the highest ranked identified key passages from the one or more web pages to the application associated with the content publisher.
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1. A content filtering system for filtering electronic content, the system comprising: a database configured to store user behavior data received from a plurality of client computers and related to a plurality of modalities, wherein at least one of the plurality of modalities comprises one or more web pages of a content publisher; and at least one server in communication with the database and configured to: identify one or more client-side events generated by one or more user interactions with the one or more web pages of the content publisher; store user behavior data in the database, the user behavior data being generated based on the one or more identified client-side events and associated with the one or more web pages; identify, using one or more machine learning processes, key passages of electronic content from at least the one or more web pages based on the user behavior data received from the plurality of client computers, the electronic content comprising electronic text and at least one of the machine learning processes being trained to reject invalid electronic content; rank the identified key passages, wherein to rank the identified key passages the server is further configured to determine a ratio of user interactions with a key passage within the electronic text to total views of the electronic text; and publish the highest ranked identified key passages from the one or more web pages to the application associated with the content publisher. 7. The content filtering system of claim 1 , wherein the at least one server is further configured to: filter at least one of the identified key passages based on at least one of the number of words in the key passage, the number of sentences in the key passage, the capitalization of the key passage, the presence of quotation marks in the key passage, and the presence of ending punctuation in the key passage.
| 0.5 |
3. The method of claim 1 , further comprising providing a semi-private list selection mechanism for selection of the at least one target user, the semiprivate list selection mechanism allowing selection of a pre-determined group of individuals determined by the advertising user.
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3. The method of claim 1 , further comprising providing a semi-private list selection mechanism for selection of the at least one target user, the semiprivate list selection mechanism allowing selection of a pre-determined group of individuals determined by the advertising user. 4. The method of claim 3 , wherein the predetermined group is an online group within an online community provided by the online service.
| 0.931487 |
1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference.
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1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. 14. The computer implemented method of claim 1 wherein the set of rules includes rules for adjusting the probability of the inference based on background data.
| 0.575751 |
1. A non-transitory, computer-readable storage medium storing program instructions computer-executable to implement: a shared object in an object-oriented language, wherein the shared object is accessible by a plurality of concurrently executing atomic transactions; and a particular atomic transaction of the plurality of concurrently executing atomic transactions, wherein the particular atomic transaction comprises an access directed to the shared object and one or more accesses directed to one or more other objects; wherein the shared object comprises at least one header word storing information indicating whether one or more of the concurrently executing atomic transactions is attempting to access the shared object; and wherein the particular atomic transaction is configured to: determine, based on the at least one header word of the shared object, if the shared object is being accessed; and in response to determining that the shared object is not being accessed: modify a working copy of the shared object, access the one or more other objects, and commit the particular atomic transaction, wherein the working copy becomes the current shared object.
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1. A non-transitory, computer-readable storage medium storing program instructions computer-executable to implement: a shared object in an object-oriented language, wherein the shared object is accessible by a plurality of concurrently executing atomic transactions; and a particular atomic transaction of the plurality of concurrently executing atomic transactions, wherein the particular atomic transaction comprises an access directed to the shared object and one or more accesses directed to one or more other objects; wherein the shared object comprises at least one header word storing information indicating whether one or more of the concurrently executing atomic transactions is attempting to access the shared object; and wherein the particular atomic transaction is configured to: determine, based on the at least one header word of the shared object, if the shared object is being accessed; and in response to determining that the shared object is not being accessed: modify a working copy of the shared object, access the one or more other objects, and commit the particular atomic transaction, wherein the working copy becomes the current shared object. 2. The storage medium of claim 1 , wherein the at least one header word in the shared object indicates a lock state.
| 0.722404 |
11. The system of claim 8 wherein the specification comprises an XML Document Type Definition that describes element names and XML syntax rules for creating a description of the document.
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11. The system of claim 8 wherein the specification comprises an XML Document Type Definition that describes element names and XML syntax rules for creating a description of the document. 12. The system of claim 11 wherein the description comprises a well-formed XML document file generated responsive to the XML Document Type Definition.
| 0.940457 |
8. The computer-implemented method of claim 7 , wherein the metadata tag knowledgebase is configured to incorporate a weighted history of a plurality of previously submitted tags for a corresponding plurality of previously submitted content objects, and wherein the weighted history is used in deriving the plurality of suggested metadata tags.
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8. The computer-implemented method of claim 7 , wherein the metadata tag knowledgebase is configured to incorporate a weighted history of a plurality of previously submitted tags for a corresponding plurality of previously submitted content objects, and wherein the weighted history is used in deriving the plurality of suggested metadata tags. 9. The computer-implemented method of claim 8 , wherein the plurality of suggested metadata tags are depicted in a tree branch hierarchy, where each branch can visually indicate a different weight with respect to the hierarchy.
| 0.929412 |
7. The method as recited in claim 1 wherein said reliability value of said template rejected by context analysis means is decremented.
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7. The method as recited in claim 1 wherein said reliability value of said template rejected by context analysis means is decremented. 8. The method as recited in claim 7 wherein when the reliability value of said template decreases lower than the predefined minimal level, the said template is deleted from the template cache.
| 0.953201 |
14. A computer-implemented method comprising: receiving, by a client device, a web resource from a server; determining, by the client device, that the web resource includes a particular trigger term, from among a predefined set of trigger terms that are associated with answer box search queries, wherein an answer box search query is a search query for which a search engine responds with an answer to a search query instead of with links to web resources; generating, by the client device, a modified version of the web resource, wherein the modified version of the web resource includes an answer box gadget in association with the particular trigger term; providing, by the client device, the modified version of the web resources, including the answer box gadget, for display to a user of the client device; determining, by the client device, that the user has selected the answer box gadget; in response to determining that the user has selected the answer box gadget, transmitting, by the client device, an answer box search query to the search engine, wherein the answer box search query indicates the particular trigger term; receiving, by the client device, an answer to the answer box search query from the search engine; and providing, by the client device, a representation of the answer to the answer box search query for display.
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14. A computer-implemented method comprising: receiving, by a client device, a web resource from a server; determining, by the client device, that the web resource includes a particular trigger term, from among a predefined set of trigger terms that are associated with answer box search queries, wherein an answer box search query is a search query for which a search engine responds with an answer to a search query instead of with links to web resources; generating, by the client device, a modified version of the web resource, wherein the modified version of the web resource includes an answer box gadget in association with the particular trigger term; providing, by the client device, the modified version of the web resources, including the answer box gadget, for display to a user of the client device; determining, by the client device, that the user has selected the answer box gadget; in response to determining that the user has selected the answer box gadget, transmitting, by the client device, an answer box search query to the search engine, wherein the answer box search query indicates the particular trigger term; receiving, by the client device, an answer to the answer box search query from the search engine; and providing, by the client device, a representation of the answer to the answer box search query for display. 15. The method of claim 14 , wherein providing the representation of the answer to the answer box search query for display further comprises launching a media player application that plays a source that is identified by the answer to the answer box search query.
| 0.613132 |
1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions.
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1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions. 29. The method according to claim 1 , which comprises, subsequent to the producing step, editing the at least one application description.
| 0.634817 |
1. An apparatus for verifying a property of a design for a system, the apparatus comprising: instructions that when executed by a processor provide, a design description interface to receive a design description of the system, including a description of properties to be verified, either as part of the design description or separate from the design description, an extractor in communication with the design description interface, the extractor to extract a plurality of formulas or constraints in response to the design description of the system, a satisfiability solver in communication with the extractor, the satisfiability solver to determine a satisfiability of the plurality of formulas or constraints using a general numeric backtracking algorithm, wherein the satisfiability solver searches in a space of non-Boolean structures for the satisfiability of the plurality of formulas or constraints, an output interface in communication with the satisfiability solver, the output interface to determine whether or not one or more of the given properties are violated, and to put the result of the satisfiability solver in a form of a counterexample suitable to aid in the diagnosis of failures.
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1. An apparatus for verifying a property of a design for a system, the apparatus comprising: instructions that when executed by a processor provide, a design description interface to receive a design description of the system, including a description of properties to be verified, either as part of the design description or separate from the design description, an extractor in communication with the design description interface, the extractor to extract a plurality of formulas or constraints in response to the design description of the system, a satisfiability solver in communication with the extractor, the satisfiability solver to determine a satisfiability of the plurality of formulas or constraints using a general numeric backtracking algorithm, wherein the satisfiability solver searches in a space of non-Boolean structures for the satisfiability of the plurality of formulas or constraints, an output interface in communication with the satisfiability solver, the output interface to determine whether or not one or more of the given properties are violated, and to put the result of the satisfiability solver in a form of a counterexample suitable to aid in the diagnosis of failures. 5. The apparatus of claim 1 , wherein the search for the satisfiability by the satisfiability solver comprises generating a sequence of mutations to a structure according to a prescribed rule.
| 0.537989 |
12. One or more non-transitory computer-readable storage media storing instructions which, when executed by one or more computing devices, cause: transforming a first query to a transformed query; wherein the first query includes: a first outer join of a first database object and a second database object, and a first join predicate that specifies a first condition of the first database object for the first outer join, wherein the first join predicate does not reference the second database object; wherein the transformed query does not include the first join predicate but does include: a second predicate that specifies a second condition of the first database object, wherein the second predicate references the second database object; wherein the transformed query is semantically equivalent to the first query; causing execution of the transformed query instead of the first query.
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12. One or more non-transitory computer-readable storage media storing instructions which, when executed by one or more computing devices, cause: transforming a first query to a transformed query; wherein the first query includes: a first outer join of a first database object and a second database object, and a first join predicate that specifies a first condition of the first database object for the first outer join, wherein the first join predicate does not reference the second database object; wherein the transformed query does not include the first join predicate but does include: a second predicate that specifies a second condition of the first database object, wherein the second predicate references the second database object; wherein the transformed query is semantically equivalent to the first query; causing execution of the transformed query instead of the first query. 19. The one or more non-transitory computer-readable storage media of claim 12 , wherein two or more predicates in the first query, including the first join predicate, reference the first database object but not the second database object, and wherein two or more corresponding predicates in the transformed query reference the first database object and the second database object.
| 0.703654 |
18. A system, the system comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to carry out: receiving input indicating a selection of a first database object to be used in creating a document template in a multi-tenant database system; retrieving a list of database fields related to the first database object; generating a graphical representation for each database field in the list of database fields retrieved from the first database object, the graphical representation for each of the database fields forming at least a part of the document template; displaying, in a user interface, the graphical representation for each database field related to the first database object; storing layout information of one or more selected graphical representations of one or more database fields in the document template in the multi-tenant database system; and rendering a document in a target format using the layout information in the document template.
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18. A system, the system comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to carry out: receiving input indicating a selection of a first database object to be used in creating a document template in a multi-tenant database system; retrieving a list of database fields related to the first database object; generating a graphical representation for each database field in the list of database fields retrieved from the first database object, the graphical representation for each of the database fields forming at least a part of the document template; displaying, in a user interface, the graphical representation for each database field related to the first database object; storing layout information of one or more selected graphical representations of one or more database fields in the document template in the multi-tenant database system; and rendering a document in a target format using the layout information in the document template. 20. The system of claim 18 , wherein the one or more stored sequences of instructions which, when executed by the processor, cause the processor to further carry out: providing an identifier for a particular database object and an identifier for the layout information of the document template; generating rendering information for at least a portion of the document in an intermediate format using the layout information in the document template; and providing at least the portion of the document in the intermediate format to a conversion module to generate at least a portion of the document in the target format.
| 0.5 |
9. The method of claim 8 , further comprising obtaining, from the metadata, a list of fields returned as query results.
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9. The method of claim 8 , further comprising obtaining, from the metadata, a list of fields returned as query results. 10. The method of claim 9 , wherein generating the abstract representations comprises generating an abstract representation for at least one of the fields returned as query results.
| 0.914557 |
15. A system for providing dynamic and category-specific search suggestions to a user, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: in response to receiving one or more characters associated with a partial search query to be executed against a set of data, determine a plurality of search queries relevant to the one or more characters; associate at least one search category with each of the plurality of relevant search query suggestions; select a subset of the at least one associated search category based at least in part a relevance value for each category meeting a threshold relevance value, the relevance value indicating a strength of an association of each category in the subset of the at least one associated search category with the plurality of relevant search query suggestions; provide for display at least the subset of the at least one associated search category and the plurality of relevant search query suggestions, the plurality of relevant search query suggestions including the one or more characters of the partial search query; determine an ordered set of some of the plurality of relevant search query suggestions and the subset of the at least one associated search category based at least in part on the relevance value of each category; and provide for display, within an allowable deviation from being simultaneous to receiving the one or more characters, a search suggestion window including the ordered set, wherein the some of the plurality of relevant search query suggestions and the subset of the at least one associated search category in the ordered set are displayed concurrently in the search suggestion window, the some of the plurality of relevant search query suggestions selectable to be executed against the set of data in the at least one associated search category.
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15. A system for providing dynamic and category-specific search suggestions to a user, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: in response to receiving one or more characters associated with a partial search query to be executed against a set of data, determine a plurality of search queries relevant to the one or more characters; associate at least one search category with each of the plurality of relevant search query suggestions; select a subset of the at least one associated search category based at least in part a relevance value for each category meeting a threshold relevance value, the relevance value indicating a strength of an association of each category in the subset of the at least one associated search category with the plurality of relevant search query suggestions; provide for display at least the subset of the at least one associated search category and the plurality of relevant search query suggestions, the plurality of relevant search query suggestions including the one or more characters of the partial search query; determine an ordered set of some of the plurality of relevant search query suggestions and the subset of the at least one associated search category based at least in part on the relevance value of each category; and provide for display, within an allowable deviation from being simultaneous to receiving the one or more characters, a search suggestion window including the ordered set, wherein the some of the plurality of relevant search query suggestions and the subset of the at least one associated search category in the ordered set are displayed concurrently in the search suggestion window, the some of the plurality of relevant search query suggestions selectable to be executed against the set of data in the at least one associated search category. 22. The system of claim 15 , wherein the memory device further includes instructions that, when executed by the processor, cause the processor to: display the search suggestion window as a plurality of search suggestion segments such that at least one suggestion segment displays the ordered set of search queries, and at least one suggestion segment displays an ordered set of category-specific search query suggestions.
| 0.578605 |
1. A method performed by a computer means for changing a grammatically incorrect sentence that has been pre-translated from a source language into a grammatically correct sentence in a target language, comprising the steps of: storing a plurality of unique grammar markers in a first database and associating each unique grammar marker with a unique grammar rule; storing a plurality of unique grammar marker patterns in a second database and associating each unique grammar marker pattern with a unique self-correction rule; inputting a pre-translated sentence that may have grammatical errors therein into a raw translation buffer; pre-identifying grammar markers in said pre-translated sentence, each grammar marker being associated with a word which may have grammatical variations in said target language but not in said source language; scanning said pre-translated sentence to identify a grammar marker or a plurality of grammar markers, if any, and a grammar marker pattern or a plurality of grammar maker patterns, if any, in said pre-translated sentence; providing a key match buffer for temporary storage of data; inputting any identified grammar marker into said key match buffer; providing a pattern match buffer for temporary storage of data; inputting any identified grammar marker pattern into said pattern match buffer, providing a correction scheme means in said computer means for retrieving appropriate grammar rules and self-correction rules from said first and second databases, respectively, and for making appropriate corrections to generate a substantially grammatically correct sentence; interconnecting a first plurality of logic gates between said correction scheme means and said first database and between said correction scheme means and said key match buffer; comparing the grammar markers in the key match buffer with the grammar markers in the first database and opening said first plurality of logic gates when a match of grammar rules is made; inputting grammar rules fetched from said first database into said correction scheme means when said first plurality of logic gates is enabled; interconnecting a second plurality of logic gates between said correction scheme means and said second database and between said correction scheme means and said pattern match buffer; comparing the grammar marker patterns in the pattern match buffer with the grammar marker patterns in the second database and opening said second plurality of logic gates when a match of self-correction rules is made; inputting self-correction rules fetched from said second database into said correction scheme means when said second plurality of logic gates is enabled; and correcting said pre-translated sentence having grammatical errors therein by applying in said correction scheme means said fetched grammar rules and said fetched self-correction rules to said pre-translated sentence to produce a sentence substantially free of grammatical errors; said fetched grammar rules and said fetched self-correction rules being appropriate rules to correct the pre-translated sentence because each grammar rule in said first database is associated with a unique grammar marker stored with it in said first database and because each self-correction rule in said second database is associated with a unique grammar marker pattern stored with it in said second database so that any grammar marker in said key match buffer will match only a counterpart grammar marker in said first database and therefore cause delivery of the grammar rule associated with said counterpart grammar marker in said first database to the correction scheme means, and so that any grammar marker in said pattern match buffer will match only a counterpart grammar marker pattern in said second database and therefore cause delivery of the self-correction rule associated with said counterpart grammar marker pattern in said second database to the correction scheme means; whereby ungrammatical expressions in the pre-translated sentence are corrected in the absence of human intervention.
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1. A method performed by a computer means for changing a grammatically incorrect sentence that has been pre-translated from a source language into a grammatically correct sentence in a target language, comprising the steps of: storing a plurality of unique grammar markers in a first database and associating each unique grammar marker with a unique grammar rule; storing a plurality of unique grammar marker patterns in a second database and associating each unique grammar marker pattern with a unique self-correction rule; inputting a pre-translated sentence that may have grammatical errors therein into a raw translation buffer; pre-identifying grammar markers in said pre-translated sentence, each grammar marker being associated with a word which may have grammatical variations in said target language but not in said source language; scanning said pre-translated sentence to identify a grammar marker or a plurality of grammar markers, if any, and a grammar marker pattern or a plurality of grammar maker patterns, if any, in said pre-translated sentence; providing a key match buffer for temporary storage of data; inputting any identified grammar marker into said key match buffer; providing a pattern match buffer for temporary storage of data; inputting any identified grammar marker pattern into said pattern match buffer, providing a correction scheme means in said computer means for retrieving appropriate grammar rules and self-correction rules from said first and second databases, respectively, and for making appropriate corrections to generate a substantially grammatically correct sentence; interconnecting a first plurality of logic gates between said correction scheme means and said first database and between said correction scheme means and said key match buffer; comparing the grammar markers in the key match buffer with the grammar markers in the first database and opening said first plurality of logic gates when a match of grammar rules is made; inputting grammar rules fetched from said first database into said correction scheme means when said first plurality of logic gates is enabled; interconnecting a second plurality of logic gates between said correction scheme means and said second database and between said correction scheme means and said pattern match buffer; comparing the grammar marker patterns in the pattern match buffer with the grammar marker patterns in the second database and opening said second plurality of logic gates when a match of self-correction rules is made; inputting self-correction rules fetched from said second database into said correction scheme means when said second plurality of logic gates is enabled; and correcting said pre-translated sentence having grammatical errors therein by applying in said correction scheme means said fetched grammar rules and said fetched self-correction rules to said pre-translated sentence to produce a sentence substantially free of grammatical errors; said fetched grammar rules and said fetched self-correction rules being appropriate rules to correct the pre-translated sentence because each grammar rule in said first database is associated with a unique grammar marker stored with it in said first database and because each self-correction rule in said second database is associated with a unique grammar marker pattern stored with it in said second database so that any grammar marker in said key match buffer will match only a counterpart grammar marker in said first database and therefore cause delivery of the grammar rule associated with said counterpart grammar marker in said first database to the correction scheme means, and so that any grammar marker in said pattern match buffer will match only a counterpart grammar marker pattern in said second database and therefore cause delivery of the self-correction rule associated with said counterpart grammar marker pattern in said second database to the correction scheme means; whereby ungrammatical expressions in the pre-translated sentence are corrected in the absence of human intervention. 31. The method of claim 1, further comprising the step of selecting pronoun person rules and tense conversion rules from said rule base and retrieving an appropriate verb-to-be and an appropriate past participle to replace the "be" and the verb, respectively, in said grammatically incorrect sentence, if the grammar markers and the grammar marker patterns in said grammatically incorrect sentence include a pronoun plus "be" plus a perfect tense verb.
| 0.52105 |
1. A system for providing a discussion topic reviewing tool, the system comprising: a video conferencing apparatus including a processor, a memory, a first display in communication with the processor, a video camera in communication with the processor, a speaker in communication with the processor, and a microphone in communication with the processor; and a video conferencing module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: initiate presentation on the first display a review bucket configured to receive from a customer a plurality of discussion topics for use in a video conference communication session between the customer and a business agent that represents a particular entity; receive from the customer, within the review bucket, an identifier associated with a first discussion topic that the customer is interested in discussing during the video conference communication session; initiate transmission of the first discussion topic to the business agent via an agent-implemented apparatus, the agent-implemented apparatus comprising a second display; initiate a video conference communication session between the customer and the business agent to discuss the first discussion topic transmitted to the business agent; present the review bucket on the first display, wherein the review bucket is configured to be dynamically positioned about the first display in one or more non-fixed orientations by the customer, wherein the review bucket is configured to allow both the customer and the business agent to view, edit, reorder and remove discussion topics within the review bucket in real time; present a replication of the review bucket on the second display; receive from the customer during the video conference communication session, within the review bucket, one or more identifiers associated with one or more second discussion topics from the plurality of discussion topics; and place the one or more identifiers associated with the one or more second discussion topics in a video conference communication queue based on at least an order in which the one or more second discussion topics are received, wherein the order is determined by the customer.
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1. A system for providing a discussion topic reviewing tool, the system comprising: a video conferencing apparatus including a processor, a memory, a first display in communication with the processor, a video camera in communication with the processor, a speaker in communication with the processor, and a microphone in communication with the processor; and a video conferencing module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: initiate presentation on the first display a review bucket configured to receive from a customer a plurality of discussion topics for use in a video conference communication session between the customer and a business agent that represents a particular entity; receive from the customer, within the review bucket, an identifier associated with a first discussion topic that the customer is interested in discussing during the video conference communication session; initiate transmission of the first discussion topic to the business agent via an agent-implemented apparatus, the agent-implemented apparatus comprising a second display; initiate a video conference communication session between the customer and the business agent to discuss the first discussion topic transmitted to the business agent; present the review bucket on the first display, wherein the review bucket is configured to be dynamically positioned about the first display in one or more non-fixed orientations by the customer, wherein the review bucket is configured to allow both the customer and the business agent to view, edit, reorder and remove discussion topics within the review bucket in real time; present a replication of the review bucket on the second display; receive from the customer during the video conference communication session, within the review bucket, one or more identifiers associated with one or more second discussion topics from the plurality of discussion topics; and place the one or more identifiers associated with the one or more second discussion topics in a video conference communication queue based on at least an order in which the one or more second discussion topics are received, wherein the order is determined by the customer. 3. The system of claim 1 , wherein the executable instructions when executed further cause the processor to initiate presentation of the review bucket prior to transmitting an indication that the customer requires communication with the business agent.
| 0.840076 |
15. A computer system for recommending leisure activities to a user, the computer system comprising: a memory; a processor; a location trace receiving mechanism that receives a cluster of locations that indicates a location trace of the user during a period of time and corresponding context; a location trace smoothing mechanism that smoothes the location trace, which involves statistically removing a first subset of locations from the location cluster, and interpolating a second subset of locations into the location cluster; a location trace preprocessing module coupled to the processor that: derives a set of venues based on the location cluster from a venue database, wherein a visit to a respective venue is identified as a hypothetical visit; responsive to the venue being located within a location range which includes the received location cluster and being associated with the corresponding context; derives a set of activity types associated with the venues from a venue-to-activity mapping; and associates attributes of the venues to the activity types based on the context; and an inferring mechanism coupled to the processor that: identifies a subset of the activity types of which the associated attributes are similar to a query context; assigns a weight to each identified activity type based on similarity between its attributes and the query context; and produces a probability distribution of various activity types based on the subset of the activity types and their weights, wherein the probability distribution predicts likelihoods that the user engages in each identified activity type associated with the query context and the location.
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15. A computer system for recommending leisure activities to a user, the computer system comprising: a memory; a processor; a location trace receiving mechanism that receives a cluster of locations that indicates a location trace of the user during a period of time and corresponding context; a location trace smoothing mechanism that smoothes the location trace, which involves statistically removing a first subset of locations from the location cluster, and interpolating a second subset of locations into the location cluster; a location trace preprocessing module coupled to the processor that: derives a set of venues based on the location cluster from a venue database, wherein a visit to a respective venue is identified as a hypothetical visit; responsive to the venue being located within a location range which includes the received location cluster and being associated with the corresponding context; derives a set of activity types associated with the venues from a venue-to-activity mapping; and associates attributes of the venues to the activity types based on the context; and an inferring mechanism coupled to the processor that: identifies a subset of the activity types of which the associated attributes are similar to a query context; assigns a weight to each identified activity type based on similarity between its attributes and the query context; and produces a probability distribution of various activity types based on the subset of the activity types and their weights, wherein the probability distribution predicts likelihoods that the user engages in each identified activity type associated with the query context and the location. 17. The computer system of claim 15 , wherein the query context comprises: a location; a time; a day of a week; and a weather condition.
| 0.685374 |
23. The method according to claim 22 , further comprising: assigning a prioritization identifier to the printer-readable format; and storing in the at least one of the at least two caches, for the document, at least one of the document key identifier associated with the document, the prioritization identifier assigned to the printer-readable format, and the printer-readable format corresponding to the document and the document key identifier.
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23. The method according to claim 22 , further comprising: assigning a prioritization identifier to the printer-readable format; and storing in the at least one of the at least two caches, for the document, at least one of the document key identifier associated with the document, the prioritization identifier assigned to the printer-readable format, and the printer-readable format corresponding to the document and the document key identifier. 28. The method according to claim 23 , further comprising: retrieving the printer-readable format corresponding to the document associated with the document key identifier from the at least one cache; and producing a print job output from the printer-readable format.
| 0.927665 |
10. A method for facilitating intellectual property rights compliance by an application comprising: receiving a structured document from a first domain, the structured document having: at least one content object, a reference to at least one digital rights compliance (DRC) object located on a second domain and associated with the at least one content object, and application-specific instructions being executable by the application, the at least one DRC object being defined in a non-executable format and containing information indicative of intellectual property rights associated with the at least one content; executing the application-specific instructions to cause the application to send at least one request to the second domain for the at least one DRC object; receiving the at least one DRC object from the second domain; executing the application-specific instructions to cause the application to modify the structured document by incorporating the at least one DRC object into the structured document; and executing the application-specific instructions to cause the application to present the at least one content object in accordance with the at least one DRC object; wherein the application is configured to limit application instructions that the application is permitted to execute such that the application is compliant with a same-origin security policy that prohibits the application from executing application-specific instructions from Hall any domain that is different from the first domain.
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10. A method for facilitating intellectual property rights compliance by an application comprising: receiving a structured document from a first domain, the structured document having: at least one content object, a reference to at least one digital rights compliance (DRC) object located on a second domain and associated with the at least one content object, and application-specific instructions being executable by the application, the at least one DRC object being defined in a non-executable format and containing information indicative of intellectual property rights associated with the at least one content; executing the application-specific instructions to cause the application to send at least one request to the second domain for the at least one DRC object; receiving the at least one DRC object from the second domain; executing the application-specific instructions to cause the application to modify the structured document by incorporating the at least one DRC object into the structured document; and executing the application-specific instructions to cause the application to present the at least one content object in accordance with the at least one DRC object; wherein the application is configured to limit application instructions that the application is permitted to execute such that the application is compliant with a same-origin security policy that prohibits the application from executing application-specific instructions from Hall any domain that is different from the first domain. 16. The method according to claim 10 , wherein the application is further operable to display at least some of the information contained in the at least one DRC object.
| 0.536716 |
4. The method of claim 3, wherein said step of graphically displaying each parameter further comprises displaying each icon for said plurality of parameters in a tree structure, wherein each icon in said tree structure has a graphic connection to said icon representing said object.
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4. The method of claim 3, wherein said step of graphically displaying each parameter further comprises displaying each icon for said plurality of parameters in a tree structure, wherein each icon in said tree structure has a graphic connection to said icon representing said object. 7. The method of claim 4, wherein said step of displaying a list of selections for a parameter comprises displaying variable as a selection for said parameter within said list of selections.
| 0.840932 |
8. The system as claimed in claim 7 further comprising means to record the text of the conversation for future analyses and incorporation into datasets of the memory.
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8. The system as claimed in claim 7 further comprising means to record the text of the conversation for future analyses and incorporation into datasets of the memory. 9. The system as claimed in claim 8 further comprising means to parse user input to remove characters used to obscure the handle or name of the possible data thief as well as for linguistic analysis including removing all punctuation from inputs and checking for duplicate inputs.
| 0.877574 |
5. A voice recognition dictionary generation apparatus according to claim 3 , wherein the external device is a digital audio device or a mobile phone, and the medium is a CD or a digital versatile disc (DVD).
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5. A voice recognition dictionary generation apparatus according to claim 3 , wherein the external device is a digital audio device or a mobile phone, and the medium is a CD or a digital versatile disc (DVD). 7. A voice recognition dictionary generation apparatus according to claim 5 , wherein, in the case where the medium is a CD, the control unit determines that information is updated when there is no album title that is matched with the music information stored in a item of the album name in the storage unit, or when TOC information is different from that of a matching album title.
| 0.884202 |
1. A system for voice control of applications, comprising: a voice navigation processor configured to analyze an application and determines application type and enabled features; a command registration processor configured to register commands based on the determined application type and enabled features, and to implement directional events and voice equivalents for the directional events for emulation of remote control button presses with speech command mapping, wherein the commands control the application when matched with associated speech; and a speech command interpretation processor configured to receive text words representing a converted speech signal of a user, to detect a speech mode for matching commands with interpreted speech, and to execute matched commands for navigation through and control of the application.
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1. A system for voice control of applications, comprising: a voice navigation processor configured to analyze an application and determines application type and enabled features; a command registration processor configured to register commands based on the determined application type and enabled features, and to implement directional events and voice equivalents for the directional events for emulation of remote control button presses with speech command mapping, wherein the commands control the application when matched with associated speech; and a speech command interpretation processor configured to receive text words representing a converted speech signal of a user, to detect a speech mode for matching commands with interpreted speech, and to execute matched commands for navigation through and control of the application. 13. The system of claim 1 , wherein the system comprises a television device.
| 0.593525 |
14. The method of claim 1 , wherein generating the audible output comprises using an audio recording.
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14. The method of claim 1 , wherein generating the audible output comprises using an audio recording. 15. The method of claim 14 , wherein the audio recording is an audio recording of a person speaking the selected words.
| 0.943606 |
11. The system of claim 9 , wherein the instructions further configure the system to determine a number of available near-duplicate images associated with individual ones of the web based images.
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11. The system of claim 9 , wherein the instructions further configure the system to determine a number of available near-duplicate images associated with individual ones of the web based images. 12. The system of claim 11 , wherein the instructions further configure the system to rank the web based images based at least in part on the number of the available near-duplicate images associated with individual ones of the web images.
| 0.938228 |
2. A method for generating metadata comprising: providing (i) a configurable metamodel for modeling metadata that describes assets of an enterprise IT system, the metamodel including meta-classes and meta-properties, wherein the meta-classes and the meta-properties are modeled by imposing binary relations and inverse binary relations on the meta-classes and the meta-properties corresponding to a transitive closure of the binary relations and the inverse binary relations, and (ii) business rules on said metamodel for indicating that certain meta-properties have impact consequences, wherein the business rules are selected from the group consisting of arithmetic conversion rules, type restrictions on inherited properties, type restrictions on indirect properties, specifying metadata values as being required, specifying valid ranges for metadata values, specifying metadata values as being unique, lookup tables, naming conventions, and assignments of stewardship responsibilities, and combinations thereof; and determining which assets of the enterprise IT system are impacted by one or more specified assets, wherein the impact determination of selected from the group consisting of determining which applications and systems will be impacted if a specific server shuts down, determining who needs to be notified if a computer is replaced with a newer model, determining which applications and systems will be impacted if a specific employee is promoted, determining which data sources are fed by data from a specific database, either directly or indirectly, determining which data transformations are impacted if the data type of a specific database column is changed, and combinations thereof.
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2. A method for generating metadata comprising: providing (i) a configurable metamodel for modeling metadata that describes assets of an enterprise IT system, the metamodel including meta-classes and meta-properties, wherein the meta-classes and the meta-properties are modeled by imposing binary relations and inverse binary relations on the meta-classes and the meta-properties corresponding to a transitive closure of the binary relations and the inverse binary relations, and (ii) business rules on said metamodel for indicating that certain meta-properties have impact consequences, wherein the business rules are selected from the group consisting of arithmetic conversion rules, type restrictions on inherited properties, type restrictions on indirect properties, specifying metadata values as being required, specifying valid ranges for metadata values, specifying metadata values as being unique, lookup tables, naming conventions, and assignments of stewardship responsibilities, and combinations thereof; and determining which assets of the enterprise IT system are impacted by one or more specified assets, wherein the impact determination of selected from the group consisting of determining which applications and systems will be impacted if a specific server shuts down, determining who needs to be notified if a computer is replaced with a newer model, determining which applications and systems will be impacted if a specific employee is promoted, determining which data sources are fed by data from a specific database, either directly or indirectly, determining which data transformations are impacted if the data type of a specific database column is changed, and combinations thereof. 3. The method of claim 2 whereby assets of the enterprise IT system include server computers.
| 0.641221 |
14. An apparatus for generating one or more context-sensitive content recommendations, the apparatus comprising: a memory; and at least one processor, coupled to the memory, operative to: detect information needs of a user; retrieve one or more content-recommendation templates that substantially match the detected information needs; and instantiate the retrieved templates with one or more parameter values to generate one or more recommended contents.
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14. An apparatus for generating one or more context-sensitive content recommendations, the apparatus comprising: a memory; and at least one processor, coupled to the memory, operative to: detect information needs of a user; retrieve one or more content-recommendation templates that substantially match the detected information needs; and instantiate the retrieved templates with one or more parameter values to generate one or more recommended contents. 15. The apparatus of claim 14 , wherein said processor is further configured to detect said information needs by analyzing user input; determining potential information needs; and generating template queries required by template retrieval.
| 0.770671 |
25. A system comprising: a database that stores abilities of users associated with one or more documents; and an analysis engine comprising a processor, the analysis engine configured to: based on information in the documents, automatically infer the abilities of the users associated with the documents, to perform language translations, the abilities including language capabilities and non-language capabilities, maintain the abilities of the respective users in the database, receive an indication of a language translation to be performed for a user, and in response to the indication of the language translation to be performed for the user, query the database to identify one or more candidate users to perform the language translation, wherein the database is configured to determine the one or more candidate users to perform the language translation using the language capabilities and non-language capabilities of the one or more candidate users.
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25. A system comprising: a database that stores abilities of users associated with one or more documents; and an analysis engine comprising a processor, the analysis engine configured to: based on information in the documents, automatically infer the abilities of the users associated with the documents, to perform language translations, the abilities including language capabilities and non-language capabilities, maintain the abilities of the respective users in the database, receive an indication of a language translation to be performed for a user, and in response to the indication of the language translation to be performed for the user, query the database to identify one or more candidate users to perform the language translation, wherein the database is configured to determine the one or more candidate users to perform the language translation using the language capabilities and non-language capabilities of the one or more candidate users. 28. The system of claim 25 , wherein automatically inferring language capabilities and non-language capabilities of users associated with the documents comprises automatically inferring, for each of the users, a proficiency in a technical skill.
| 0.750305 |
17. The system of claim 16 , wherein the instructions cause the processor to further perform: generating, via the one or more user interaction capability elements, one or more user interfaces (UIs); receiving the user input via at least one input UI of the one or more UIs; providing the user feedback via at least one output UI of the one or more UIs; and providing, via the at least one output UI subsequent to performing the one or more task actions, one or more task-related parameters in the set of task-related parameters that are modifiable to modify the one or more task actions.
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17. The system of claim 16 , wherein the instructions cause the processor to further perform: generating, via the one or more user interaction capability elements, one or more user interfaces (UIs); receiving the user input via at least one input UI of the one or more UIs; providing the user feedback via at least one output UI of the one or more UIs; and providing, via the at least one output UI subsequent to performing the one or more task actions, one or more task-related parameters in the set of task-related parameters that are modifiable to modify the one or more task actions. 19. The system of claim 17 , wherein the instructions cause the processor to further perform: unloading the robot capability element subsequent to performing the one or more task actions; loading a new robot capability element in place of the robot capability element; determining that the user input satisfies one or more parameterization requirements of the new robot capability element; indicating, via the at least one output UI, that the user input satisfies the one or more parameterization requirements of the new robot capability element; and providing, via the at least one output UI, information associated with a change in a robot state of the robot.
| 0.700215 |
12. The method of claim 11, further comprising using the language model along with at least one acoustic model to perform a hypothesis search on an acoustic sequence to provide a word sequence output.
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12. The method of claim 11, further comprising using the language model along with at least one acoustic model to perform a hypothesis search on an acoustic sequence to provide a word sequence output. 13. The method of claim 12, wherein the at least one acoustic model is based on a hidden Markov model paradigm, wherein the at least one acoustic model comprises one model for each of at least one phonemes.
| 0.875831 |
13. A system for detecting network anomalies, the system comprising: a processor that: receives a training dataset of communication protocol messages having argument strings; determines a content and a structure associated with each of the argument strings; receives a mixture size that specifies a number of Markov chains to use in a probabilistic model; trains the probabilistic model using the determined content and structure of each of the argument strings and using a mixture of Markov chains specified by the received mixture size; receives a communication protocol message having an argument string that is transmitted from a first processor to a second processor across a computer network; applies the probabilistic model to the received communication protocol message to determine whether the communication protocol message is anomalous; and performs a predetermined action in response to determining that the communication protocol message is anomalous.
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13. A system for detecting network anomalies, the system comprising: a processor that: receives a training dataset of communication protocol messages having argument strings; determines a content and a structure associated with each of the argument strings; receives a mixture size that specifies a number of Markov chains to use in a probabilistic model; trains the probabilistic model using the determined content and structure of each of the argument strings and using a mixture of Markov chains specified by the received mixture size; receives a communication protocol message having an argument string that is transmitted from a first processor to a second processor across a computer network; applies the probabilistic model to the received communication protocol message to determine whether the communication protocol message is anomalous; and performs a predetermined action in response to determining that the communication protocol message is anomalous. 14. The system of claim 13 , wherein the anomalous communication protocol message is caused by a web layer code injection attack.
| 0.868668 |
1. A method comprising: detecting an inaudible physiological reaction by a person to an instance of at least two instances of a displayed first content, the at least two instances of the first content having a common contextual attribute, the detecting being performed while the person is viewing at least one of the at least two instances of the displayed first content; determining a content attribute of the instance of the at least two instances of the displayed first content that is at least substantially absent from other instances of the at least two instances of the displayed first content; initiating a search for a second content using a search parameter corresponding to the detected inaudible physiological reaction and to the determined content attribute of the instance; selecting the second content from a result of the initiated search, the selecting being automated and performed at least in part with a processing device; and facilitating a display of the selected second content in a manner perceivable by the person.
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1. A method comprising: detecting an inaudible physiological reaction by a person to an instance of at least two instances of a displayed first content, the at least two instances of the first content having a common contextual attribute, the detecting being performed while the person is viewing at least one of the at least two instances of the displayed first content; determining a content attribute of the instance of the at least two instances of the displayed first content that is at least substantially absent from other instances of the at least two instances of the displayed first content; initiating a search for a second content using a search parameter corresponding to the detected inaudible physiological reaction and to the determined content attribute of the instance; selecting the second content from a result of the initiated search, the selecting being automated and performed at least in part with a processing device; and facilitating a display of the selected second content in a manner perceivable by the person. 30. The method of claim 1 , wherein the detecting an inaudible physiological reaction by a person to an instance of at least two instances of a displayed first content, the at least two instances of the first content having a common contextual attribute, the detecting being performed while the person is viewing at least one of the at least two instances of the displayed first content includes: detecting an inaudible physiological reaction that includes a stance.
| 0.644304 |
3. The method of claim 2 , further comprising: summarizing a collection of scanned original text using an optically recognized highlighted text within said scanned text document to generate a summarized document.
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3. The method of claim 2 , further comprising: summarizing a collection of scanned original text using an optically recognized highlighted text within said scanned text document to generate a summarized document. 8. The method of claim 3 further comprising electronically storing said summarized within an electronic repository.
| 0.903935 |
1. A computer-implemented method comprising the steps of: generating a plurality of navigation trails based on an ordered sequence of navigational activities performed by a plurality of users; grouping the plurality of navigation trails into a plurality of navigation trail groups based on original queries with which navigation trails in the plurality of navigation trails begin; for at least a particular navigation trail group of the plurality of navigation trail groups, determining one or more uniform resource locators (URLs) or revised queries that occur in at least a specified proportion of navigation trails in the particular navigation trail group; generating a search results page based at least in part on the one or more URLs or revised queries that occur in at least a specified proportion of navigation trails in the particular navigation trail group; and storing the search results page on a computer-readable storage medium; wherein at least one navigation trail in the particular navigation trail group contains at least one URL or revised query that another navigation trail in the particular navigation trail group does not contain; and wherein the steps are performed by one or more computing devices.
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1. A computer-implemented method comprising the steps of: generating a plurality of navigation trails based on an ordered sequence of navigational activities performed by a plurality of users; grouping the plurality of navigation trails into a plurality of navigation trail groups based on original queries with which navigation trails in the plurality of navigation trails begin; for at least a particular navigation trail group of the plurality of navigation trail groups, determining one or more uniform resource locators (URLs) or revised queries that occur in at least a specified proportion of navigation trails in the particular navigation trail group; generating a search results page based at least in part on the one or more URLs or revised queries that occur in at least a specified proportion of navigation trails in the particular navigation trail group; and storing the search results page on a computer-readable storage medium; wherein at least one navigation trail in the particular navigation trail group contains at least one URL or revised query that another navigation trail in the particular navigation trail group does not contain; and wherein the steps are performed by one or more computing devices. 6. The method of claim 1 , wherein grouping the plurality of navigation trails into a plurality of navigation trail groups comprises: grouping all navigation trails that begin with a first original query into a first navigation trail group of the plurality of navigation trail groups; and grouping all navigation trails that begin with a second original query into a second navigation trail group of the plurality of navigation trail groups; wherein the first original query differs from the second original query.
| 0.771691 |
1. In a computing environment, a method comprising; processing a webpage to understand one or more entities of the webpage by bidirectional integration of web structure understanding and text understanding, including understanding text of the webpage into text segmentation data, using the text segmentation data of understanding the text and visual layout features of the web page to produce webpage structure information including a labeled block, and using the webpage structure information including the labeled block to further understand the text of the webpage including the one more entities, wherein understanding the text of the webpage and understanding the structure of the webpage are performed iteratively until an iteration similarity stop criterion is met.
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1. In a computing environment, a method comprising; processing a webpage to understand one or more entities of the webpage by bidirectional integration of web structure understanding and text understanding, including understanding text of the webpage into text segmentation data, using the text segmentation data of understanding the text and visual layout features of the web page to produce webpage structure information including a labeled block, and using the webpage structure information including the labeled block to further understand the text of the webpage including the one more entities, wherein understanding the text of the webpage and understanding the structure of the webpage are performed iteratively until an iteration similarity stop criterion is met. 4. The method of claim 1 wherein using the text segmentation data comprises providing a feature to a hierarchical conditional random fields model.
| 0.675285 |
9. The method of claim 1 , comprising forming a PPAN chain from the PPAN elements.
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9. The method of claim 1 , comprising forming a PPAN chain from the PPAN elements. 10. The method of claim 9 , wherein using the PPAN elements from the structured request document to identify a subset of the stored structured service documents that contain data and structure that match the PPAN elements comprises using the PPAN chain to search for a subset of structured service documents that contains the PPAN chain.
| 0.898315 |
1. A method comprising: dividing a media instance into a first component and a second component, the first component and second component concurrently presented; correlating first physiological response data from a first subject exposed to media with the first component and the second component to form first correlated data and second correlated data; processing, using a processor, the first correlated data to identify a first transition representative of a first change; processing, using the processor, the second correlated data to identify a second transition representative of a second change; parsing the first component into a first plurality of events based on the first transition; parsing the second component into a second plurality of events based on the second transition; identifying a first event of the first plurality of events as a first candidate for modification based on the first change; and identifying a second event of the second plurality of events as a second candidate for modification based on the second change.
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1. A method comprising: dividing a media instance into a first component and a second component, the first component and second component concurrently presented; correlating first physiological response data from a first subject exposed to media with the first component and the second component to form first correlated data and second correlated data; processing, using a processor, the first correlated data to identify a first transition representative of a first change; processing, using the processor, the second correlated data to identify a second transition representative of a second change; parsing the first component into a first plurality of events based on the first transition; parsing the second component into a second plurality of events based on the second transition; identifying a first event of the first plurality of events as a first candidate for modification based on the first change; and identifying a second event of the second plurality of events as a second candidate for modification based on the second change. 2. The method of claim 1 , wherein the first component and the second component comprise at least one of voiceover, music, branding, dialogue, text, or a visual component, the first component being different from the second component.
| 0.720851 |
10. A computer implemented method for binding an image descriptor of a Graphical User Interface (GUI) widget to a text field, the computer implemented method comprising: associating an image descriptor, of the GUI widget, with a content of an active field in the text field, wherein the image descriptor of the GUI widget and the active field in the text field are substantially similar, and wherein the GUI widget and the text field are both displayed on a GUI; and in response to the content of the active field in the text field changing, a processor automatically modifying the image descriptor of the GUI widget and changing an appearance of the GUI widget to reflect the changed content of the active field in the text field.
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10. A computer implemented method for binding an image descriptor of a Graphical User Interface (GUI) widget to a text field, the computer implemented method comprising: associating an image descriptor, of the GUI widget, with a content of an active field in the text field, wherein the image descriptor of the GUI widget and the active field in the text field are substantially similar, and wherein the GUI widget and the text field are both displayed on a GUI; and in response to the content of the active field in the text field changing, a processor automatically modifying the image descriptor of the GUI widget and changing an appearance of the GUI widget to reflect the changed content of the active field in the text field. 11. The computer implemented method of claim 10 , wherein changing the content of the active field in the text field results in a change to an appearance of the GUI widget from a first shape to a second shape.
| 0.62123 |
15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event.
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15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event. 19. The method of claim 15 , further comprising: determining an event type based on the article; creating the event object of the event type, including an event description from the article; and storing the event object in an event database.
| 0.724464 |
1. A method comprising: performing by one or more computer processors: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a comparison of a word-based feature of the original text and the translation correction, wherein calculating the at least one metric comprises determining a difference in a number of words, characters, emojis, numbers, or punctuation marks between the original text and the translation correction; and determining an accuracy of the translation correction based on the at least one metric.
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1. A method comprising: performing by one or more computer processors: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a comparison of a word-based feature of the original text and the translation correction, wherein calculating the at least one metric comprises determining a difference in a number of words, characters, emojis, numbers, or punctuation marks between the original text and the translation correction; and determining an accuracy of the translation correction based on the at least one metric. 4. The method of claim 1 , further comprising: offering an incentive to the second user to provide the translation correction; and rewarding the second user with the respective incentive when the translation correction is determined to be accurate.
| 0.710709 |
16. A computer system for listing optimal machine instances in a computing environment to address one or more received tasks based on user context, the computer system comprising: at least one processing unit; at least one computer readable memory; at least one computer readable tangible, non-transitory storage medium; and program instructions stored on the at least one computer readable tangible, non-transitory storage medium for execution by the at least one processing unit via the at least one computer readable memory, wherein the program instructions comprise program instructions for: receiving a task request based on a first task to be performed within the computing environment, wherein the received task request comprises a request to resolve at least one problem associated with at least one application, wherein the first task comprises at least one project task to resolve the at least one problem and comprises metadata associated with the first task to identify the at least one problem, and wherein a description of the first task is received via the metadata and user input; based on the received task request, identifying one or more similar tasks from a plurality of other tasks comprising: comparing the metadata for the first task to a plurality of metadata for the plurality of other tasks based on a classification analysis, and selecting the identified one or more similar tasks based on the comparison, wherein similarity of the identified and selected one or more similar tasks to the first task is based on a result from the classification analysis exceeding a predetermined confidence level, and wherein the plurality of other tasks comprise previous tasks performed within the computing environment on corresponding previous machine instances that are associated with previous problems; and in response to identifying and selecting the one or more similar tasks, generating a list of one or more previous machine instances corresponding to the identified and selected one or more similar tasks, wherein the list of one or more previous machine instances is associated with instructions to commence the one or more previous machine instances, and wherein the one or more previous machine instances comprises at least one of a virtual machine (VM) instance or a physical machine instance, and wherein generating the list comprises ranking the one or more previous machine instances based on a priority ranking and information associated with the first task and the identified and selected one or more similar tasks, and listing the one or more previous machine instances based on the ranking.
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16. A computer system for listing optimal machine instances in a computing environment to address one or more received tasks based on user context, the computer system comprising: at least one processing unit; at least one computer readable memory; at least one computer readable tangible, non-transitory storage medium; and program instructions stored on the at least one computer readable tangible, non-transitory storage medium for execution by the at least one processing unit via the at least one computer readable memory, wherein the program instructions comprise program instructions for: receiving a task request based on a first task to be performed within the computing environment, wherein the received task request comprises a request to resolve at least one problem associated with at least one application, wherein the first task comprises at least one project task to resolve the at least one problem and comprises metadata associated with the first task to identify the at least one problem, and wherein a description of the first task is received via the metadata and user input; based on the received task request, identifying one or more similar tasks from a plurality of other tasks comprising: comparing the metadata for the first task to a plurality of metadata for the plurality of other tasks based on a classification analysis, and selecting the identified one or more similar tasks based on the comparison, wherein similarity of the identified and selected one or more similar tasks to the first task is based on a result from the classification analysis exceeding a predetermined confidence level, and wherein the plurality of other tasks comprise previous tasks performed within the computing environment on corresponding previous machine instances that are associated with previous problems; and in response to identifying and selecting the one or more similar tasks, generating a list of one or more previous machine instances corresponding to the identified and selected one or more similar tasks, wherein the list of one or more previous machine instances is associated with instructions to commence the one or more previous machine instances, and wherein the one or more previous machine instances comprises at least one of a virtual machine (VM) instance or a physical machine instance, and wherein generating the list comprises ranking the one or more previous machine instances based on a priority ranking and information associated with the first task and the identified and selected one or more similar tasks, and listing the one or more previous machine instances based on the ranking. 17. The computer system according to claim 16 , wherein the first task is associated with a first task category and a first customer name, and wherein ranking the one or more previous machine instances corresponding to the one or more similar tasks comprises assigning the priority ranking, wherein the priority ranking is selected from the group consisting of: a highest rank priority to a machine instance corresponding to a previous task performed by the user within the computing environment; a second highest rank priority to a machine instance corresponding to a similar task associated with the first task category and the first customer name; a third highest rank priority to a machine instance corresponding to a similar task associated with the first task category; and a fourth highest rank priority to a machine instance corresponding to a similar task associated with the first customer name.
| 0.5 |
8. A method of determining a collections treatment type, said method comprising: selecting, by a computer processor, a score band based on a credit score associated with a debtor; determining, by the computer processor, a collections score based on raw credit data and a first scoring expression of a plurality of different scoring expressions, wherein said first scoring expression is associated with said score band, wherein said first scoring expression utilizes a first variable, and wherein a second scoring expression associated with a second score band utilizes a second variable; and determining, by the computer processor, said collections treatment type based on said collections score.
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8. A method of determining a collections treatment type, said method comprising: selecting, by a computer processor, a score band based on a credit score associated with a debtor; determining, by the computer processor, a collections score based on raw credit data and a first scoring expression of a plurality of different scoring expressions, wherein said first scoring expression is associated with said score band, wherein said first scoring expression utilizes a first variable, and wherein a second scoring expression associated with a second score band utilizes a second variable; and determining, by the computer processor, said collections treatment type based on said collections score. 14. The method of claim 8 , wherein said first and second variables are the same.
| 0.896985 |
2. The method according to claim 1 , wherein the determining recurring visual patterns based on the visual words and connections between the visual words further comprises determining a salient pattern based on a number of extracted patches contained in each visual word.
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2. The method according to claim 1 , wherein the determining recurring visual patterns based on the visual words and connections between the visual words further comprises determining a salient pattern based on a number of extracted patches contained in each visual word. 3. The method according to claim 2 , wherein the determining visual patterns based on the visual words and connections between the visual words further comprises determining a concurrent pattern based on a number of connections between the visual words, wherein there is a connection between first and second visual words when the first visual word contains a first patch and the second visual word contains a second patch, and the first patch and the second patch were extracted from a same image of the plurality of second images.
| 0.745989 |
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