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6,069,939 | 29 | 30 | 29. The method of claim 11, wherein said selecting language step includes the step of determining whether said calling party determined a language for delivery of messages to a dialed country. | 29. The method of claim 11, wherein said selecting language step includes the step of determining whether said calling party determined a language for delivery of messages to a dialed country. 30. The method of claim 29, wherein said selecting language step includes the step of selecting said language determined for said dialed country. | 0.875856 |
8,108,203 | 1 | 5 | 1. A translation system comprising: a storage device; a processor; a bilingual data storage section, a plurality of pieces of first language simple sentence data corresponding to a plurality of first language simple sentences in a first language and a plurality of pieces of second language simple sentence data corresponding to a plurality of second language simple sentences in a second language being stored in the bilingual data storage section while being associated with each other so that the first language simple sentences and the second language simple sentences respectively make pairs; and a target language simple sentence data output section which outputs target language simple sentence data corresponding to a target language simple sentence which is a translation of a given source language simple sentence based on source language simple sentence data corresponding to the source language simple sentence, the target language simple sentence data output section receiving first-language-source-language simple sentence data corresponding to a first-language-source-language simple sentence in the first language, and selecting first language simple sentence data from the plurality of pieces of the first language simple sentence data stored in the bilingual data storage section based on the received first-language-source-language simple sentence data; and the target language simple sentence data output section outputting the second language simple sentence data associated with the selected first language simple sentence data as the target language simple sentence data; wherein the first language simple sentence data is stored in the bilingual data storage section while being classified into a plurality of groups; wherein one piece of the first language simple sentence data classified into each of the groups is designated as representative data; and wherein the target language simple sentence data output section selects one piece of the first language simple sentence data designated as the representative data. | 1. A translation system comprising: a storage device; a processor; a bilingual data storage section, a plurality of pieces of first language simple sentence data corresponding to a plurality of first language simple sentences in a first language and a plurality of pieces of second language simple sentence data corresponding to a plurality of second language simple sentences in a second language being stored in the bilingual data storage section while being associated with each other so that the first language simple sentences and the second language simple sentences respectively make pairs; and a target language simple sentence data output section which outputs target language simple sentence data corresponding to a target language simple sentence which is a translation of a given source language simple sentence based on source language simple sentence data corresponding to the source language simple sentence, the target language simple sentence data output section receiving first-language-source-language simple sentence data corresponding to a first-language-source-language simple sentence in the first language, and selecting first language simple sentence data from the plurality of pieces of the first language simple sentence data stored in the bilingual data storage section based on the received first-language-source-language simple sentence data; and the target language simple sentence data output section outputting the second language simple sentence data associated with the selected first language simple sentence data as the target language simple sentence data; wherein the first language simple sentence data is stored in the bilingual data storage section while being classified into a plurality of groups; wherein one piece of the first language simple sentence data classified into each of the groups is designated as representative data; and wherein the target language simple sentence data output section selects one piece of the first language simple sentence data designated as the representative data. 5. The translation system as defined in claim 1 , wherein the target language simple sentence data output section receives second-language-source-language simple sentence data corresponding to a second-language-source-language simple sentence in the second language, and selects second language simple sentence data from the second language simple sentence data stored in the bilingual data storage section based on the received second-language-source-language simple sentence data; and wherein the target language simple sentence data output section outputs the first language simple sentence data associated with the selected second language simple sentence data as the target language simple sentence data. | 0.838717 |
9,053,497 | 11 | 12 | 11. The system of claim 10 , wherein the advertising targeting application further directs the processor to: generate an advertising campaign, where the advertising campaign comprises a portion of the advertising content and the targeting information; and transmit the advertising campaign to an online social network, where the online social network is configured to present the portion of the advertising content to the members of the online social network based on the targeting information. | 11. The system of claim 10 , wherein the advertising targeting application further directs the processor to: generate an advertising campaign, where the advertising campaign comprises a portion of the advertising content and the targeting information; and transmit the advertising campaign to an online social network, where the online social network is configured to present the portion of the advertising content to the members of the online social network based on the targeting information. 12. The system of claim 11 , wherein the advertising targeting application further directs the processor to measure the performance of the advertising campaign. | 0.971254 |
5,539,839 | 6 | 7 | 6. A method as set forth in claim 5, and further comprising the steps of: determining a covariance matrix of each of the static and dynamic spliced vector representations; determining eigenvalues and eigenvectors associated with each of the determined covariance matrices; and applying a transformation to the determined eigenvectors for providing the static feature vector representations and the dynamic feature vector representations. | 6. A method as set forth in claim 5, and further comprising the steps of: determining a covariance matrix of each of the static and dynamic spliced vector representations; determining eigenvalues and eigenvectors associated with each of the determined covariance matrices; and applying a transformation to the determined eigenvectors for providing the static feature vector representations and the dynamic feature vector representations. 7. A method as set forth in claim 6, and further comprising the steps of: performing clustering in both a static feature vector space and in a dynamic feature vector space to provide both static and dynamic prototype distributions in the feature vector spaces; performing Gaussian modelling in each of the feature vector spaces; and determining both static and dynamic mixture coefficients for evaluating relative contributions of each prototype distribution to a current sample of handwriting inputs. | 0.77165 |
9,607,621 | 7 | 8 | 7. A system for determining an identity of an individual comprising: one or more processors; and memory storing computer readable instructions that, when executed by one of the processors, cause the system to: receive, in a communication via a communication portal, audio comprising a key phrase spoken by an individual, the key phrase comprising an identifier spoken by the individual, obtain a key phrase voice print corresponding to the audio, convert the audio to text, the text comprising key phrase text corresponding to the key phrase and the key phrase text comprising identifier text corresponding to the identifier, query a voice print database with the identifier text to obtain a set of voice prints associated with the identifier, responsive to determining that a total number of voice prints in the set of voice prints exceeds a predetermined size threshold, select at least one of the voice prints in the set of voice prints to exclude from comparison to a key phrase voice print; and provide the key phrase voice print and the set of voice prints, other than the at least one voice print selected for exclusion, to a voice biometric engine for comparison. | 7. A system for determining an identity of an individual comprising: one or more processors; and memory storing computer readable instructions that, when executed by one of the processors, cause the system to: receive, in a communication via a communication portal, audio comprising a key phrase spoken by an individual, the key phrase comprising an identifier spoken by the individual, obtain a key phrase voice print corresponding to the audio, convert the audio to text, the text comprising key phrase text corresponding to the key phrase and the key phrase text comprising identifier text corresponding to the identifier, query a voice print database with the identifier text to obtain a set of voice prints associated with the identifier, responsive to determining that a total number of voice prints in the set of voice prints exceeds a predetermined size threshold, select at least one of the voice prints in the set of voice prints to exclude from comparison to a key phrase voice print; and provide the key phrase voice print and the set of voice prints, other than the at least one voice print selected for exclusion, to a voice biometric engine for comparison. 8. The system of claim 7 , wherein: the identifier comprises a first name and a last name of the individual; and each voice print of the set of voice prints is associated with a customer profile, the customer profile comprising a profile first name that matches the first name and a profile last name that matches the last name. | 0.615925 |
4,771,401 | 46 | 49 | 46. A method for electronic spelling correction in a digital data processing apparatus, said method comprising the steps of A. inputting plural linguistic expressions for storage, each said linguistic expression including alphanumeric characters, B. generating signals representing plural master lexicon entries, each said entry representing an input linguistic expression, C. forming plural master lexicon blocks, each said block being formed by the steps of (i) generating a linguistically salient word skeleton for each linguistic expression in the block, wherein said skeleton includes skeletal symbols, (ii) collating said block linguistically salient word skeletons and determining therefrom a block skeletal collation range, and (iii) storing in a storage medium one or more master lexicon entries, D. forming a master lexicon wherein said blocks are arranged in an addressable sequence determined in accord with their respective skeletal collation range thereof, E. inputting a signal representative of a suspect linguistic expression, F. locating within said master lexicon an entry representing an expression substitutable for said suspect expression, and G. generating a signal indicative of the success of said locating step. | 46. A method for electronic spelling correction in a digital data processing apparatus, said method comprising the steps of A. inputting plural linguistic expressions for storage, each said linguistic expression including alphanumeric characters, B. generating signals representing plural master lexicon entries, each said entry representing an input linguistic expression, C. forming plural master lexicon blocks, each said block being formed by the steps of (i) generating a linguistically salient word skeleton for each linguistic expression in the block, wherein said skeleton includes skeletal symbols, (ii) collating said block linguistically salient word skeletons and determining therefrom a block skeletal collation range, and (iii) storing in a storage medium one or more master lexicon entries, D. forming a master lexicon wherein said blocks are arranged in an addressable sequence determined in accord with their respective skeletal collation range thereof, E. inputting a signal representative of a suspect linguistic expression, F. locating within said master lexicon an entry representing an expression substitutable for said suspect expression, and G. generating a signal indicative of the success of said locating step. 49. A method according to claim 46 further comprising the step of generating a signal representative of a modified form of said suspect expression and for locating a linguistic expression matching said modified suspect expression. | 0.887033 |
8,713,117 | 1 | 2 | 1. In a mobile consumer messaging system (MCMS), in which the MCMS is in electronic communications with a plurality of mobile device users via one or more mobile carrier networks and is in electronic communications with one or more chat agents utilizing one or more chat platforms, a method for facilitating messages between the plurality of mobile devices users and the one or more chat agents, comprising the steps of: receiving a particular chat message at the MCMS from a specific mobile device user via a respective mobile carrier network, wherein the particular chat message includes message content and message identifying information; extracting via the MCMS the message content and message identifying information from the particular chat message and storing the message content and message identifying information in an MCMS database; generating via the MCMS a new message in a format acceptable to a respective chat platform, wherein the new message includes the message content and is based on the message identifying information; and transmitting the new message from the MCMS to a respective chat agent associated with the respective chat platform. | 1. In a mobile consumer messaging system (MCMS), in which the MCMS is in electronic communications with a plurality of mobile device users via one or more mobile carrier networks and is in electronic communications with one or more chat agents utilizing one or more chat platforms, a method for facilitating messages between the plurality of mobile devices users and the one or more chat agents, comprising the steps of: receiving a particular chat message at the MCMS from a specific mobile device user via a respective mobile carrier network, wherein the particular chat message includes message content and message identifying information; extracting via the MCMS the message content and message identifying information from the particular chat message and storing the message content and message identifying information in an MCMS database; generating via the MCMS a new message in a format acceptable to a respective chat platform, wherein the new message includes the message content and is based on the message identifying information; and transmitting the new message from the MCMS to a respective chat agent associated with the respective chat platform. 2. The method of claim 1 , further comprising the step of generating a particular chat session associated with the particular chat message, wherein the particular chat session includes session identifying information stored in the MCMS database and used to identify the particular chat session. | 0.925 |
7,630,992 | 19 | 20 | 19. A method for reducing the rank of a matrix A for information retrieval, comprising: determining via a computer a plurality of probabilistic distributions on parts; estimating via the computer a plurality of singular values corresponding to at least one of a plurality of probabilistic distributions on parts; identifying via the computer a plurality of actual singular values each having a corresponding singular vector associated with the matrix A; grouping via the computer the singular values of matrix A based on the singular values of matrix A that correspond to at least one of the estimated singular values; and computing via the computer the reduced rank approximation based on the grouping of the singular values, wherein the reduced rank approximation provides an index for use during information retrieval. | 19. A method for reducing the rank of a matrix A for information retrieval, comprising: determining via a computer a plurality of probabilistic distributions on parts; estimating via the computer a plurality of singular values corresponding to at least one of a plurality of probabilistic distributions on parts; identifying via the computer a plurality of actual singular values each having a corresponding singular vector associated with the matrix A; grouping via the computer the singular values of matrix A based on the singular values of matrix A that correspond to at least one of the estimated singular values; and computing via the computer the reduced rank approximation based on the grouping of the singular values, wherein the reduced rank approximation provides an index for use during information retrieval. 20. The method of claim 19 , wherein the grouping step comprises estimating singular values corresponding to at least one of the probabilistic distributions on parts and selecting actual singular values of matrix A that correspond to the estimated singular values. | 0.745665 |
7,913,238 | 2 | 8 | 2. An integrated development environment code completion compiler error recovery system, comprising: a processor; a language module, implemented on the processor, including a parser operable to parse the syntactic structure of a first program in a first programming language, wherein the first program can be represented by a first set of tokens; a client interface through which the language module can communicate with an extensible compiler framework, implemented on the processor; the extensible compiler framework including a namespace component wherein the namespace component is operable to store name and/or type information for one or more language modules; and wherein the parser can correct a syntax error by adding at least one token to the first set of tokens according to one of: 1) a prefix, wherein a prefix is the combination of an opening delimiter with a newly created closing delimiter; and 2) an idiom, wherein an idiom is a specific insertion sequence that can be used to overcome common errors in a given programming language; and wherein an extensible compiler framework detects the syntax error. | 2. An integrated development environment code completion compiler error recovery system, comprising: a processor; a language module, implemented on the processor, including a parser operable to parse the syntactic structure of a first program in a first programming language, wherein the first program can be represented by a first set of tokens; a client interface through which the language module can communicate with an extensible compiler framework, implemented on the processor; the extensible compiler framework including a namespace component wherein the namespace component is operable to store name and/or type information for one or more language modules; and wherein the parser can correct a syntax error by adding at least one token to the first set of tokens according to one of: 1) a prefix, wherein a prefix is the combination of an opening delimiter with a newly created closing delimiter; and 2) an idiom, wherein an idiom is a specific insertion sequence that can be used to overcome common errors in a given programming language; and wherein an extensible compiler framework detects the syntax error. 8. The system of claim 2 wherein: the idiom associates a syntax error with the at least one token. | 0.800813 |
8,244,599 | 10 | 12 | 10. A method comprising: receiving a request, over a network at a social shopping platform, from a user in a first community of users, the social shopping platform including a plurality of network-based marketplaces respectively associated with a plurality of communities, the plurality of communities including the first community of users that is associated with a first network-based marketplace; identifying the first network-based marketplace from the plurality of network-based marketplaces based on the request, the request for an activity associated with a listing for sale in the first network-based marketplace that is used by the first community of users to transact listings that describe items of a single domain that is of interest to the first community of users; updating a listing reputation score for the listing based on a user reputation score for the user and based upon the activity associated with the listing; and updating the user reputation score based on the listing reputation score. | 10. A method comprising: receiving a request, over a network at a social shopping platform, from a user in a first community of users, the social shopping platform including a plurality of network-based marketplaces respectively associated with a plurality of communities, the plurality of communities including the first community of users that is associated with a first network-based marketplace; identifying the first network-based marketplace from the plurality of network-based marketplaces based on the request, the request for an activity associated with a listing for sale in the first network-based marketplace that is used by the first community of users to transact listings that describe items of a single domain that is of interest to the first community of users; updating a listing reputation score for the listing based on a user reputation score for the user and based upon the activity associated with the listing; and updating the user reputation score based on the listing reputation score. 12. The method of claim 10 , wherein the listing for sale is selected from a group consisting of a listing for a good and a listing for a service. | 0.862524 |
9,479,524 | 1 | 5 | 1. A non-transitory machine-readable storage medium encoded with instructions executable by a hardware processor of a computing device for determining string similarity, the machine-readable storage medium comprising instructions to cause the hardware processor to: receive domain name system (DNS) query packets that were sent by a particular client computing device, each DNS query packet specifying a query domain name; generate, for each query domain name included in the received DNS query packets, a syntax string by replacing each character of the query domain name with one of a plurality of metacharacters, each of the plurality of metacharacters representing a category of characters that is different from each other category of characters represented by each other metacharacter in the plurality of metacharacters; determine, for each query domain name included in the received DNS query packets, a syntactic edit distance between the query domain name and each other query domain name included in the received DNS packets, the syntactic edit distance between query domain names being determined based on syntax strings of the corresponding domain names; cluster each query domain name included in the received DNS query packets into one of a plurality of clusters based on the syntactic edit distances; and identify the particular client computing device as a potential source of malicious software based on the plurality of clusters. | 1. A non-transitory machine-readable storage medium encoded with instructions executable by a hardware processor of a computing device for determining string similarity, the machine-readable storage medium comprising instructions to cause the hardware processor to: receive domain name system (DNS) query packets that were sent by a particular client computing device, each DNS query packet specifying a query domain name; generate, for each query domain name included in the received DNS query packets, a syntax string by replacing each character of the query domain name with one of a plurality of metacharacters, each of the plurality of metacharacters representing a category of characters that is different from each other category of characters represented by each other metacharacter in the plurality of metacharacters; determine, for each query domain name included in the received DNS query packets, a syntactic edit distance between the query domain name and each other query domain name included in the received DNS packets, the syntactic edit distance between query domain names being determined based on syntax strings of the corresponding domain names; cluster each query domain name included in the received DNS query packets into one of a plurality of clusters based on the syntactic edit distances; and identify the particular client computing device as a potential source of malicious software based on the plurality of clusters. 5. The storage medium of claim 1 , wherein at least one category of characters represented by one of the plurality of metacharacters includes at least one of: alphabetical letters; lower-case letters; upper-case letters; vowel letters; consonant letters; foreign language characters; digits; punctuation marks; dashes; periods; underscores; or unprintable characters. | 0.72734 |
8,489,538 | 1 | 2 | 1. A method for analyzing a plurality of documents, comprising: receiving the plurality of documents via a computing device; filtering the plurality of documents to produce a subset of the plurality of documents; executing instructions stored in memory, wherein execution of the instructions by a processor generates an initial control set based on random sampling of the subset of the plurality of documents; receiving user input from the computing device, the user input based on an identified subject or category; and executing instructions stored in memory, wherein execution of the instructions by a processor: reviews the initial control set to determine at least one seed set parameter associated with the identified subject or category, automatically codes a first portion of the plurality of documents, based on the initial control set and the at least one seed set parameter associated with the identified subject or category, automatically codes a second portion of the plurality of documents resulting from an application of user analysis and an adaptive identification cycle, and adds the coded second portion of the plurality of documents to the initial control set. | 1. A method for analyzing a plurality of documents, comprising: receiving the plurality of documents via a computing device; filtering the plurality of documents to produce a subset of the plurality of documents; executing instructions stored in memory, wherein execution of the instructions by a processor generates an initial control set based on random sampling of the subset of the plurality of documents; receiving user input from the computing device, the user input based on an identified subject or category; and executing instructions stored in memory, wherein execution of the instructions by a processor: reviews the initial control set to determine at least one seed set parameter associated with the identified subject or category, automatically codes a first portion of the plurality of documents, based on the initial control set and the at least one seed set parameter associated with the identified subject or category, automatically codes a second portion of the plurality of documents resulting from an application of user analysis and an adaptive identification cycle, and adds the coded second portion of the plurality of documents to the initial control set. 2. The method of claim 1 , wherein receiving user input on the initial control set includes a validation of the initial control set. | 0.86558 |
9,438,876 | 1 | 7 | 1. A method for controlling replay for video content in a trick mode of operation, the method comprising: receiving a trick mode command; determining a trick mode frame rate as a function of a time interval between consecutive semantics in the video content, a time duration of the video content, a number of occurrences for the semantics in the video content and a frame rate in a normal play mode of the video content; and wherein the video content related to the time interval in the trick mode defined by the received trick mode command is displayed at the trick mode frame rate, said trick mode frame rate, V i , is determined as V i =[T i /T]×(N×L×M), where T i is a time interval between an i th and an (i+1) th consecutive semantics in the video content, T is a time duration of the video content, N is a number of occurrences for the semantics in the video content, and M is a frame rate in a normal play mode. | 1. A method for controlling replay for video content in a trick mode of operation, the method comprising: receiving a trick mode command; determining a trick mode frame rate as a function of a time interval between consecutive semantics in the video content, a time duration of the video content, a number of occurrences for the semantics in the video content and a frame rate in a normal play mode of the video content; and wherein the video content related to the time interval in the trick mode defined by the received trick mode command is displayed at the trick mode frame rate, said trick mode frame rate, V i , is determined as V i =[T i /T]×(N×L×M), where T i is a time interval between an i th and an (i+1) th consecutive semantics in the video content, T is a time duration of the video content, N is a number of occurrences for the semantics in the video content, and M is a frame rate in a normal play mode. 7. The method as defined in claim 1 , wherein the number of occurrences for the semantics in the video content, is represented as a statistical average number of occurrences for said semantics over the video content, wherein the statistical average is based upon one or more associated characteristics of the video content. | 0.692381 |
8,832,140 | 1 | 17 | 1. A computer implemented method for optimizing results returned from interaction with a collection of information, the method comprising: establishing criteria associated with at least one operation on a collection of information, wherein the criteria is based, at least in part, on a comparison of a measurement of the distinctiveness of a set of results and a distinctiveness score threshold; establishing a rule that comprises the criteria and the at least one operation; determining the set of results from interaction with a collection of information, wherein the set of results comprises a plurality of documents retrieved from the collection of information, and wherein each of the plurality of documents further comprise a unit of storage of digital data; determining, by a computer system, a measurement of distinctiveness for the set of results based on a statistical distribution of at least one identifying characteristic, wherein the distinctiveness of the set of results is measured in relation to the collection of information, and wherein the determining the measurement of distinctiveness comprises: identifying the at least one identifying characteristic within an evaluated set, and determining a measure of distinctiveness of the evaluated set within the collection of information; modifying, by the computer system, the set of results according to the at least one operation by applying the rule to the set of results in response to determining that the set of results matches the criteria based, at least in part, on the comparison of the measurement of distinctiveness for the set of results and the distinctiveness score threshold; and outputting a modified result. | 1. A computer implemented method for optimizing results returned from interaction with a collection of information, the method comprising: establishing criteria associated with at least one operation on a collection of information, wherein the criteria is based, at least in part, on a comparison of a measurement of the distinctiveness of a set of results and a distinctiveness score threshold; establishing a rule that comprises the criteria and the at least one operation; determining the set of results from interaction with a collection of information, wherein the set of results comprises a plurality of documents retrieved from the collection of information, and wherein each of the plurality of documents further comprise a unit of storage of digital data; determining, by a computer system, a measurement of distinctiveness for the set of results based on a statistical distribution of at least one identifying characteristic, wherein the distinctiveness of the set of results is measured in relation to the collection of information, and wherein the determining the measurement of distinctiveness comprises: identifying the at least one identifying characteristic within an evaluated set, and determining a measure of distinctiveness of the evaluated set within the collection of information; modifying, by the computer system, the set of results according to the at least one operation by applying the rule to the set of results in response to determining that the set of results matches the criteria based, at least in part, on the comparison of the measurement of distinctiveness for the set of results and the distinctiveness score threshold; and outputting a modified result. 17. The method according to claim 1 , further comprising: modifying a size of at least one set; and determining a measurement of distinctiveness from the at least one modified set. | 0.9 |
9,449,028 | 8 | 15 | 8. A computer-implemented method to access a definitive image, the method comprising: storing, in an image data store, one or more images or references to images stored in other data stores; receiving a request during a query for the definitive image that is representative of a topic of the query; maintaining an inverted index of images that maps one or more query terms to one or more images that are related to the one or more query terms; ranking one or more images identified in the inverted index that potentially match the query terms to sort the identified one or more images by a relative likelihood of being the definitive image for the topic of the query; selecting the definitive image based on one or more images returned from the inverted index, any overridden editor-chosen definitive image, and the ranking, wherein the editor-chosen definitive image is identified by manually overriding a system selected definitive image from a human editor; retrieving an image binary associated with the selected definitive image based on an image identifier associated with the selected definitive image; and sending the retrieved image binary associated with the selected definitive image in response to the received request; wherein the preceding steps are performed by at least one processor. | 8. A computer-implemented method to access a definitive image, the method comprising: storing, in an image data store, one or more images or references to images stored in other data stores; receiving a request during a query for the definitive image that is representative of a topic of the query; maintaining an inverted index of images that maps one or more query terms to one or more images that are related to the one or more query terms; ranking one or more images identified in the inverted index that potentially match the query terms to sort the identified one or more images by a relative likelihood of being the definitive image for the topic of the query; selecting the definitive image based on one or more images returned from the inverted index, any overridden editor-chosen definitive image, and the ranking, wherein the editor-chosen definitive image is identified by manually overriding a system selected definitive image from a human editor; retrieving an image binary associated with the selected definitive image based on an image identifier associated with the selected definitive image; and sending the retrieved image binary associated with the selected definitive image in response to the received request; wherein the preceding steps are performed by at least one processor. 15. The method of claim 8 wherein selecting the definitive image comprises identifying the image identifier that corresponds to the selected definitive image. | 0.902349 |
9,769,314 | 19 | 24 | 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. | 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. 24. The system of claim 19 , wherein the speech command includes a phrase provided by the particular user, the phrase associated with an identified website and information available at the website. | 0.784934 |
5,481,703 | 17 | 22 | 17. A method for restructuring a relational database comprising the steps of: a) extracting an attribute set of candidate keys and non-key attributes except for the candidate keys from a relation to be restructured; b) forming a plurality of combinations between a proper subset of the candidate keys extracted in said step a) and a subset of said non-key attributes; c) checking, with reference to values of tuples which are present in said relation, whether said subset of non-key attributes is functionally dependent on said proper subset of candidate keys in each of the combinations formed in said step b), and storing a determination result as dependency information, and storing attribute information representing the determination result; and d) dividing said relation into a relation generated by a projection to an attribute set having a functional dependency and a relation generated by a projection to an attribute set of attributes except for non-key attributes having a functional dependency in accordance with said dependency information; e) checking whether said relation generated by said division in said step d) has at least two non-key attributes., and executing said formation step b), said determination step c) and said division step d) automatically on said relation when said relation has at least two non-key attributes. | 17. A method for restructuring a relational database comprising the steps of: a) extracting an attribute set of candidate keys and non-key attributes except for the candidate keys from a relation to be restructured; b) forming a plurality of combinations between a proper subset of the candidate keys extracted in said step a) and a subset of said non-key attributes; c) checking, with reference to values of tuples which are present in said relation, whether said subset of non-key attributes is functionally dependent on said proper subset of candidate keys in each of the combinations formed in said step b), and storing a determination result as dependency information, and storing attribute information representing the determination result; and d) dividing said relation into a relation generated by a projection to an attribute set having a functional dependency and a relation generated by a projection to an attribute set of attributes except for non-key attributes having a functional dependency in accordance with said dependency information; e) checking whether said relation generated by said division in said step d) has at least two non-key attributes., and executing said formation step b), said determination step c) and said division step d) automatically on said relation when said relation has at least two non-key attributes. 22. A method according to claim 17, further comprising the step of converting each of at least one third normal form relations divided in step d) into a relation having a form at a level higher than that of third normal form. | 0.901316 |
9,460,074 | 13 | 18 | 13. An apparatus comprising: a processing device, wherein the processing device executes instructions that cause the apparatus to: parse training data using a plurality of pattern matching rules; assign a pattern matching rule as a parent rule of one or more child rules upon determining that failure of the parent rule to match the training data is a predictor of the one or more child rules failure to match the training data; receive data as input to be parsed; and parse the data using the plurality of pattern matching rules, the plurality of pattern matching rules organized according to a hierarchy including the parent rule and the one or more child rules of the parent rule, and wherein the parsing comprises: applying the parent rule to the data, determining the parent rule is unable to find a pattern match in the data, and bypassing application of each child rule to the data in response to the determination that the parent rule is unable to find a pattern match. | 13. An apparatus comprising: a processing device, wherein the processing device executes instructions that cause the apparatus to: parse training data using a plurality of pattern matching rules; assign a pattern matching rule as a parent rule of one or more child rules upon determining that failure of the parent rule to match the training data is a predictor of the one or more child rules failure to match the training data; receive data as input to be parsed; and parse the data using the plurality of pattern matching rules, the plurality of pattern matching rules organized according to a hierarchy including the parent rule and the one or more child rules of the parent rule, and wherein the parsing comprises: applying the parent rule to the data, determining the parent rule is unable to find a pattern match in the data, and bypassing application of each child rule to the data in response to the determination that the parent rule is unable to find a pattern match. 18. The apparatus of claim 13 , wherein the data is unstructured data combined from a plurality of different data sources. | 0.876268 |
9,483,461 | 9 | 12 | 9. A non-transitory computer-readable storage medium storing a plurality of instructions for controlling a processor, the plurality of instructions comprising: instructions that cause the processor to display, on a display, a portion of displayed text that includes a plurality of words; instructions that cause the processor to receive a request to convert the plurality of words in the portion of the displayed text to speech; instructions that cause the processor to determine whether a language ambiguity exists based on an analysis of the plurality of words of the portion of the displayed text, wherein the language ambiguity indicates that a plurality of candidate languages are applicable for converting the plurality of words in the portion of the displayed text to speech; instructions that cause the processor to, in accordance with the determination that the language ambiguity exists, concurrently display, on the display, the plurality of candidate languages for converting the plurality of words in the portion of the displayed text to speech, wherein the plurality of candidate languages was selected based on the analysis of the plurality of words in the portion of the displayed text; while concurrently displaying the plurality of candidate languages, receive, with one or more input devices, input indicative of selection of a first candidate language from the concurrently displayed plurality of candidate languages, and in response to receiving the input indicative of selection of the first candidate language, output, with one or more audio output devices, audio corresponding to the plurality of words in the portion of the displayed text, wherein the audio comprises a conversion of the plurality of words in the portion of the displayed text to speech in the first candidate language. | 9. A non-transitory computer-readable storage medium storing a plurality of instructions for controlling a processor, the plurality of instructions comprising: instructions that cause the processor to display, on a display, a portion of displayed text that includes a plurality of words; instructions that cause the processor to receive a request to convert the plurality of words in the portion of the displayed text to speech; instructions that cause the processor to determine whether a language ambiguity exists based on an analysis of the plurality of words of the portion of the displayed text, wherein the language ambiguity indicates that a plurality of candidate languages are applicable for converting the plurality of words in the portion of the displayed text to speech; instructions that cause the processor to, in accordance with the determination that the language ambiguity exists, concurrently display, on the display, the plurality of candidate languages for converting the plurality of words in the portion of the displayed text to speech, wherein the plurality of candidate languages was selected based on the analysis of the plurality of words in the portion of the displayed text; while concurrently displaying the plurality of candidate languages, receive, with one or more input devices, input indicative of selection of a first candidate language from the concurrently displayed plurality of candidate languages, and in response to receiving the input indicative of selection of the first candidate language, output, with one or more audio output devices, audio corresponding to the plurality of words in the portion of the displayed text, wherein the audio comprises a conversion of the plurality of words in the portion of the displayed text to speech in the first candidate language. 12. The non-transitory computer-readable storage medium of claim 9 further comprising: instructions that cause the processor to read a first character in the plurality of words in the portion of the displayed text; instructions that cause the processor to determine a first language to be used for converting the first character to speech; instructions that cause the processor to associate the first language with the first character; instructions that cause the processor to read a second character in the plurality of words in the portion of the displayed text, the second character following the first character; instructions that cause the processor to determine a second language to be used for converting the second character to speech, wherein the second language is different from the first language; instructions that cause the processor to associate the second language with the second character; instructions that cause the processor to convert the first character to speech using a language synthesizer corresponding to the first language associated with the first character; and instructions that cause the processor to convert the second character to speech using a language synthesizer corresponding to the second language associated with the second character. | 0.617735 |
9,769,195 | 13 | 14 | 13. A system for efficiently allocating resources for behavioral analysis, the system comprising: a determination module, stored in memory, that determines a file type of a first file subject to behavioral analysis; a loading module, stored in memory, that loads the first file within an environment for behavioral analysis to observe at least one behavior within the environment attributable to the first file; an observation module, stored in memory, that observes a malicious behavior within the environment and attribute the malicious behavior to the first file; a timing module, stored in memory, that determines a timing of the malicious behavior after loading the first file within the environment; a limitation module, stored in memory, that limits an amount of time dedicated to analyzing a second file within the environment based at least in part on the timing of the malicious behavior after loading the first file within the environment and due to the second file being of the same file type as the first file; at least one physical processor configured to execute the determination module, the loading module, the observation module, the timing module, and the limitation module. | 13. A system for efficiently allocating resources for behavioral analysis, the system comprising: a determination module, stored in memory, that determines a file type of a first file subject to behavioral analysis; a loading module, stored in memory, that loads the first file within an environment for behavioral analysis to observe at least one behavior within the environment attributable to the first file; an observation module, stored in memory, that observes a malicious behavior within the environment and attribute the malicious behavior to the first file; a timing module, stored in memory, that determines a timing of the malicious behavior after loading the first file within the environment; a limitation module, stored in memory, that limits an amount of time dedicated to analyzing a second file within the environment based at least in part on the timing of the malicious behavior after loading the first file within the environment and due to the second file being of the same file type as the first file; at least one physical processor configured to execute the determination module, the loading module, the observation module, the timing module, and the limitation module. 14. The system of claim 13 , wherein the loading module loads the first file within the environment by loading the first file within a virtual machine designated for behavioral analysis. | 0.79148 |
9,330,667 | 2 | 3 | 2. The method according to claim 1 , wherein the determining an acoustic model for a text endpoint comprises: generating a decoding network corresponding to the text according to the audio record text, and determining a last acoustic model of the decoding network as the acoustic model for the text endpoint. | 2. The method according to claim 1 , wherein the determining an acoustic model for a text endpoint comprises: generating a decoding network corresponding to the text according to the audio record text, and determining a last acoustic model of the decoding network as the acoustic model for the text endpoint. 3. The method according to claim 2 , wherein the determining a characteristics acoustic model of a decoding optimal path for a current frame of the audio record data comprises: extracting an MFCC characteristic corresponding to a preset acoustic model from the current frame of the audio record data to obtain the decoding optimal path for the current frame of the audio record data; and determining a last acoustic model of the decoding optimal path for the current frame of the audio record data as the characteristics acoustic model of the decoding optimal path. | 0.746864 |
9,146,961 | 14 | 15 | 14. The computer-readable storage medium of claim 6 , wherein the query execution plan is associated with a query cursor; wherein storing the first mapping in association with the query execution plan comprises associating the first mapping with the query cursor of the query execution plan; and wherein storing the second mapping in association with the query execution plan comprises associating the second mapping with the query cursor of the query execution plan. | 14. The computer-readable storage medium of claim 6 , wherein the query execution plan is associated with a query cursor; wherein storing the first mapping in association with the query execution plan comprises associating the first mapping with the query cursor of the query execution plan; and wherein storing the second mapping in association with the query execution plan comprises associating the second mapping with the query cursor of the query execution plan. 15. The computer-readable storage medium of claim 14 , wherein the one or more sequences of instructions include instructions which, when executed by the one or more processors, cause: in response to detecting the change in the resource path, marking the query cursor as invalid, wherein the query execution plan associated with the query cursor cannot be executed while the query cursor is marked as invalid; and after performing the subsequent resolving and recompiling the query execution plan, marking the query cursor as valid. | 0.78754 |
8,850,534 | 5 | 6 | 5. A system for enhancing the accuracy of authentication transaction results comprising: a communications device configured to capture authentication data in accordance with an authentication data requirement and biometric data for new verification phrases from users; and an authentication system comprising an authentication database, said authentication system being configured to communicate with said communications device over a network, conduct authentication transactions, store enrollment data records and an enrollment phrase registry, determine at least one enrollment phrase from an enrollment phrase registry and at least one new verification phrase for a desired transaction, the at least one enrollment phrase being an authentication data requirement for a desired transaction; and after successfully authenticating the user with authentication data captured from the user with said communications device, add the determined at least one new verification phrase to the enrollment phrase registry. | 5. A system for enhancing the accuracy of authentication transaction results comprising: a communications device configured to capture authentication data in accordance with an authentication data requirement and biometric data for new verification phrases from users; and an authentication system comprising an authentication database, said authentication system being configured to communicate with said communications device over a network, conduct authentication transactions, store enrollment data records and an enrollment phrase registry, determine at least one enrollment phrase from an enrollment phrase registry and at least one new verification phrase for a desired transaction, the at least one enrollment phrase being an authentication data requirement for a desired transaction; and after successfully authenticating the user with authentication data captured from the user with said communications device, add the determined at least one new verification phrase to the enrollment phrase registry. 6. A system for improving the accuracy of authentication transaction results in accordance with claim 5 , said authentication system being further configured to determine that biometric data captured for the at least one new verification phrase corresponds to the determined at least one new verification phrase. | 0.66879 |
10,072,941 | 7 | 13 | 7. A system comprising: a processor; a memory coupled with the processor; first logic stored in the memory and executable by the processor to cause the processor to receive at least a portion of a conversational narrative comprising at least one non-verbal physical movement of a portion of a human body of a provider and descriptive of a route to a destination expressed by the provider to a receiver not connected to the processor, the expressed conversational narrative comprising a plurality of conversational elements, wherein the plurality of conversational elements includes a plurality of navigation oriented conversational elements and at least one descriptive element characterizing at least one other of the plurality of conversational elements; second logic stored in the memory and executable by the processor to cause the processor to identify the plurality of navigation oriented conversational elements of the plurality of conversational elements as well as any of the at least one descriptive elements characterizing thereof; third logic stored in the memory and executable by the processor to cause the processor to convert each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive and relational elements; fourth logic stored in the memory and executable by the processor to cause the processor to compile the navigation data elements into a navigation route; and fifth logic stored in the memory and executable by the processor to cause the processor to present at least a portion of the navigation route. | 7. A system comprising: a processor; a memory coupled with the processor; first logic stored in the memory and executable by the processor to cause the processor to receive at least a portion of a conversational narrative comprising at least one non-verbal physical movement of a portion of a human body of a provider and descriptive of a route to a destination expressed by the provider to a receiver not connected to the processor, the expressed conversational narrative comprising a plurality of conversational elements, wherein the plurality of conversational elements includes a plurality of navigation oriented conversational elements and at least one descriptive element characterizing at least one other of the plurality of conversational elements; second logic stored in the memory and executable by the processor to cause the processor to identify the plurality of navigation oriented conversational elements of the plurality of conversational elements as well as any of the at least one descriptive elements characterizing thereof; third logic stored in the memory and executable by the processor to cause the processor to convert each of the plurality of navigation oriented conversational elements into an associated navigation data element representative thereof based on the identified descriptive and relational elements; fourth logic stored in the memory and executable by the processor to cause the processor to compile the navigation data elements into a navigation route; and fifth logic stored in the memory and executable by the processor to cause the processor to present at least a portion of the navigation route. 13. The system of claim 7 wherein the first logic is further executable by the processor to cause the processor to receive the at least one non-verbal physical movement of a portion of a human body of the conversational narrative via an optical sensor, a motion sensor, a touch sensor, a proximity sensor, or a combination thereof, and convert the received conversational narrative to data representative thereof. | 0.501208 |
8,874,614 | 1 | 2 | 1. A method comprising: receiving pattern language code that includes definitions of a business class and field classes, wherein the field classes include ontological context rules; and generating high-level object-oriented code that includes the business classes and the field classes with ontological contexts. | 1. A method comprising: receiving pattern language code that includes definitions of a business class and field classes, wherein the field classes include ontological context rules; and generating high-level object-oriented code that includes the business classes and the field classes with ontological contexts. 2. The method of claim 1 , wherein the ontological context rules indicate which of the field classes must be within the reachable ontological context of certain of the field classes. | 0.893318 |
8,794,972 | 1 | 12 | 1. A method of enhancing the readability of legal text placed upon a document wherein the legal text includes one or more sentences comprising the steps of: parsing the legal text by a processor to identify one or more portions of legal text for visual enhancement; selecting one or more visual markings from a set of visual markings that visually enhance individual portions of the legal text that was parsed using a processor when the one or more visual markings are applied to the legal text prior to placement of the legal text in the document and where the legal text contains English language grammar; applying one of the visual markings to the legal text such that at least one of the portions of the legal text are visually enhanced; wherein the one or more portions of legal text include at least one of (a) a primary if-then clause, (b) a secondary if-then clause, (c) a primary conjunction, (d) a secondary conjunction, (e) a primary exception, (f) a secondary exception, (g) a skeletal sentence portion, and (h) a cohesive phrase; and wherein the set of visual markings includes at least one of (i) a sentence termination marking, (ii) a primary if-then marking, (iii) an explicit if-then marking, (iv) a secondary if-then marking, (v) a primary conjunction marking, (vi) a secondary conjunction marking, (vii) a primary exception marking, (viii) a secondary exception marking, (ix) a skeletal sentence marking, and (x) a cohesive phrase marking in addition to text characters being added within the document without modification of the paragraphing employed in the document. | 1. A method of enhancing the readability of legal text placed upon a document wherein the legal text includes one or more sentences comprising the steps of: parsing the legal text by a processor to identify one or more portions of legal text for visual enhancement; selecting one or more visual markings from a set of visual markings that visually enhance individual portions of the legal text that was parsed using a processor when the one or more visual markings are applied to the legal text prior to placement of the legal text in the document and where the legal text contains English language grammar; applying one of the visual markings to the legal text such that at least one of the portions of the legal text are visually enhanced; wherein the one or more portions of legal text include at least one of (a) a primary if-then clause, (b) a secondary if-then clause, (c) a primary conjunction, (d) a secondary conjunction, (e) a primary exception, (f) a secondary exception, (g) a skeletal sentence portion, and (h) a cohesive phrase; and wherein the set of visual markings includes at least one of (i) a sentence termination marking, (ii) a primary if-then marking, (iii) an explicit if-then marking, (iv) a secondary if-then marking, (v) a primary conjunction marking, (vi) a secondary conjunction marking, (vii) a primary exception marking, (viii) a secondary exception marking, (ix) a skeletal sentence marking, and (x) a cohesive phrase marking in addition to text characters being added within the document without modification of the paragraphing employed in the document. 12. The method of claim 1 further comprising the steps of: identifying a location in the legal text where one of the sentences ends; and applying the sentence termination marking at the location in the legal text where the sentence ends such that the location is visually enhanced. | 0.735405 |
7,546,382 | 44 | 47 | 44. The method of claim 43 , wherein the speech-based representation is based on Voice Extensible Markup Language (VoiceXML). | 44. The method of claim 43 , wherein the speech-based representation is based on Voice Extensible Markup Language (VoiceXML). 47. The method of claim 44 , wherein VoiceXML is extended to specify natural language (NL) parsing via introduction of a NL grammar as a speech data file. | 0.970844 |
7,974,912 | 48 | 51 | 48. A computer system that manages pay-per-click advertising, by determining an amount to be charged in response to a click of a hyperlink associated with a target keyword, comprising a memory, and processing hardware configured to: access from memory a particular amount a first advertiser is willing to be charged in response to a click of a hyperlink associated with said first advertiser, access from memory first and second different statistics related to one or more of a rate of use by users, number of times a hyperlink was viewed, data that relates to an increase or decrease in the use of a keyword by users, demographics of users associated with a keyword or demographics of advertisers associated with a keyword, and without human intervention, determine an amount, to be charged to a second advertiser in response to a click of a hyperlink associated with said target keyword and said second advertiser, wherein said amount to be charged to said second advertiser is determined using said particular amount, and is also determined using said first and second statistics. | 48. A computer system that manages pay-per-click advertising, by determining an amount to be charged in response to a click of a hyperlink associated with a target keyword, comprising a memory, and processing hardware configured to: access from memory a particular amount a first advertiser is willing to be charged in response to a click of a hyperlink associated with said first advertiser, access from memory first and second different statistics related to one or more of a rate of use by users, number of times a hyperlink was viewed, data that relates to an increase or decrease in the use of a keyword by users, demographics of users associated with a keyword or demographics of advertisers associated with a keyword, and without human intervention, determine an amount, to be charged to a second advertiser in response to a click of a hyperlink associated with said target keyword and said second advertiser, wherein said amount to be charged to said second advertiser is determined using said particular amount, and is also determined using said first and second statistics. 51. The computer system of claim 48 wherein said amount meets pre-identified requirements of said second advertiser. | 0.876858 |
7,854,009 | 3 | 12 | 3. The system of claim 2 , wherein the LAN security system assigns the port sites with fixed security ratings. | 3. The system of claim 2 , wherein the LAN security system assigns the port sites with fixed security ratings. 12. The system of claim 3 , wherein the security system directs the any user using a port site exceeding the any user's assigned security level to a port site appropriate for the any user's security level. | 0.964459 |
9,405,797 | 4 | 5 | 4. The method of claim 1 , wherein the improved query includes a reference to a denormalized table, wherein the denormalized table comprises data accessible by the group. | 4. The method of claim 1 , wherein the improved query includes a reference to a denormalized table, wherein the denormalized table comprises data accessible by the group. 5. The method of claim 4 , wherein the denormalized table comprises a search name lookup table. | 0.976071 |
8,868,587 | 2 | 6 | 2. The system of claim 1 , wherein: determining that a term of the original query meets an inaccuracy criterion comprises determining that the term is typographically incorrect; generating one or more derivative queries from the original query comprises generating a derivative query that includes only the terms of the original query that are not the potentially inaccurate term. | 2. The system of claim 1 , wherein: determining that a term of the original query meets an inaccuracy criterion comprises determining that the term is typographically incorrect; generating one or more derivative queries from the original query comprises generating a derivative query that includes only the terms of the original query that are not the potentially inaccurate term. 6. The system of claim 2 , wherein determining a corrected term based on the identified resources comprises: generating candidate correction terms from terms that are included in the identified resources for a derivative query; determining, for each of the candidate correction terms, a similarity measure that measures the similarity of the candidate correction term to the potentially inaccurate term; and selecting as the corrected term the candidate correction term with a similarity measure that indicates a highest similarity relative to the other candidate correction terms. | 0.890087 |
8,244,755 | 12 | 16 | 12. A computer program product comprising a computer readable storage medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: receive, at a searching/indexing device, a web content search request comprising a search term; perform a web search based upon the search term; parse a markup language (ML) document returned via the web search that comprises the search term; identify a location of the search term within the ML document; determine whether an indexed hypertext link comprising an appended page anchor that references the location of the search term within the ML document exists within a search index; determine that the indexed hypertext link comprising the appended page anchor that references the location of the search term within the ML document does not exist within the search index; determine whether the ML document comprises an existing page anchor associated with the search term; determine that the ML document does not comprise the existing page anchor associated with the search term; determine whether the ML document comprises an existing page anchor proximate to a location associated with the search term within the ML document; determine that the ML document comprises the existing page anchor proximate to the location associated with the search term; determine a direction indicator and a distance offset from the existing page anchor to the location associated with the search term; and configure a hypertext link to the identified location of the search term within the ML document based upon the determination of whether the indexed hypertext link comprising the appended page anchor that references the location of the search term within the ML document exists within the search index comprising causing the computer to: form the hypertext link as a uniform resource locator (URL) to the ML document; append the existing page anchor, the distance offset, and the direction indicator to the URL; and index the formed hypertext link with the appended existing page anchor, the distance offset, and the direction indicator within the search index. | 12. A computer program product comprising a computer readable storage medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: receive, at a searching/indexing device, a web content search request comprising a search term; perform a web search based upon the search term; parse a markup language (ML) document returned via the web search that comprises the search term; identify a location of the search term within the ML document; determine whether an indexed hypertext link comprising an appended page anchor that references the location of the search term within the ML document exists within a search index; determine that the indexed hypertext link comprising the appended page anchor that references the location of the search term within the ML document does not exist within the search index; determine whether the ML document comprises an existing page anchor associated with the search term; determine that the ML document does not comprise the existing page anchor associated with the search term; determine whether the ML document comprises an existing page anchor proximate to a location associated with the search term within the ML document; determine that the ML document comprises the existing page anchor proximate to the location associated with the search term; determine a direction indicator and a distance offset from the existing page anchor to the location associated with the search term; and configure a hypertext link to the identified location of the search term within the ML document based upon the determination of whether the indexed hypertext link comprising the appended page anchor that references the location of the search term within the ML document exists within the search index comprising causing the computer to: form the hypertext link as a uniform resource locator (URL) to the ML document; append the existing page anchor, the distance offset, and the direction indicator to the URL; and index the formed hypertext link with the appended existing page anchor, the distance offset, and the direction indicator within the search index. 16. The computer program product of claim 12 , where the searching/indexing device is distributed across a plurality of devices. | 0.927928 |
8,781,827 | 30 | 31 | 30. The system of claim 27 , wherein: the duration of silence is at least about 0.50 milliseconds; and the sentence punctuation character comprises a period. | 30. The system of claim 27 , wherein: the duration of silence is at least about 0.50 milliseconds; and the sentence punctuation character comprises a period. 31. The system of claim 30 , wherein the server is further configured to capitalize a first letter of a word immediately following the duration of silence. | 0.92116 |
9,143,541 | 1 | 11 | 1. A method to provide internet-based services targeted to a geographic location, the method comprising: receiving a request from a user to provide internet-based services based on a target geographic location; obtaining a plurality of candidate geographic locations associated with the user, each candidate geographic location being associated with a respective candidate confidence level; calculating, with a computer, for one of the candidate geographic locations, a respective aggregate probabilistic utility score, the aggregate probabilistic utility score being based, at least in part, on distances from the respective candidate geographic location to the other candidate geographic locations and the confidence level scores of the other candidate geographic locations; selecting a geographic location based, at least in part, on the aggregate probabilistic utility score from among the candidate geographic locations; and providing internet-based services to the user targeting the selected geographic location. | 1. A method to provide internet-based services targeted to a geographic location, the method comprising: receiving a request from a user to provide internet-based services based on a target geographic location; obtaining a plurality of candidate geographic locations associated with the user, each candidate geographic location being associated with a respective candidate confidence level; calculating, with a computer, for one of the candidate geographic locations, a respective aggregate probabilistic utility score, the aggregate probabilistic utility score being based, at least in part, on distances from the respective candidate geographic location to the other candidate geographic locations and the confidence level scores of the other candidate geographic locations; selecting a geographic location based, at least in part, on the aggregate probabilistic utility score from among the candidate geographic locations; and providing internet-based services to the user targeting the selected geographic location. 11. The method of claim 1 , further comprising: calculating an aggregate probabilistic utility score for each of the candidate geographic locations, and wherein providing internet-based services to the user further comprises ranking web resources in accordance with the aggregate probabilistic utility score by: selecting as targeted geographic locations candidate geographic locations with aggregate probabilistic utility scores exceeding a threshold; and responsive to the selection, ranking web resources associated with the targeted geographic locations higher than the associated web resources would ranked absent the selection. | 0.655978 |
8,699,677 | 9 | 12 | 9. One or more non-transitory computer-readable media storing executable instructions configured to, when executed by at least one processor, cause an apparatus to: receive a plurality of packets, each of the plurality of packets including voice data for a voicemail message; determine that a threshold amount of voice data has been received; responsive to determining that the threshold amount of voice data has been received, create a first segment that comprises the threshold amount of voice data; transcribe the first segment to first text; transmit a first message that comprises the first text to an intended recipient of the voicemail message; determine that a second threshold amount of voice data has been received; responsive to determining that the second threshold amount of voice data has been received, create a second segment that comprises the second threshold amount of voice data; transcribe the second segment to second text; and after transmission of the first message, transmit, to the intended recipient of the voicemail message, a second message that comprises the second text. | 9. One or more non-transitory computer-readable media storing executable instructions configured to, when executed by at least one processor, cause an apparatus to: receive a plurality of packets, each of the plurality of packets including voice data for a voicemail message; determine that a threshold amount of voice data has been received; responsive to determining that the threshold amount of voice data has been received, create a first segment that comprises the threshold amount of voice data; transcribe the first segment to first text; transmit a first message that comprises the first text to an intended recipient of the voicemail message; determine that a second threshold amount of voice data has been received; responsive to determining that the second threshold amount of voice data has been received, create a second segment that comprises the second threshold amount of voice data; transcribe the second segment to second text; and after transmission of the first message, transmit, to the intended recipient of the voicemail message, a second message that comprises the second text. 12. The one or more non-transitory computer-readable media of claim 9 , wherein the voice data is uncompressed voice data from a voice data server; and wherein the first message is an e-mail, a short messaging service (SMS) message or an instant message. | 0.501961 |
7,801,358 | 23 | 28 | 23. A media material analyzer for analyzing data representative of media material having a layout, comprising: a segmenter that identifies block segments associated with columnar body text in the media material; and an article composer that determines which of the identified block segments belong to one or more articles in the media material based on language statistics information and layout transition information, wherein the article composer includes a language statistics analyzer that calculates language statistics for candidate block segments output by the segmenter, and determines probabilities that candidate block segments belong to a same article based on an overlap in language statistics information. | 23. A media material analyzer for analyzing data representative of media material having a layout, comprising: a segmenter that identifies block segments associated with columnar body text in the media material; and an article composer that determines which of the identified block segments belong to one or more articles in the media material based on language statistics information and layout transition information, wherein the article composer includes a language statistics analyzer that calculates language statistics for candidate block segments output by the segmenter, and determines probabilities that candidate block segments belong to a same article based on an overlap in language statistics information. 28. The media material analyzer of claim 23 , wherein the article composer further includes a combiner that identifies whether the candidate block segments belong to a same article in the media material based on the probabilities determined by the language statistics analyzer. | 0.841352 |
8,615,070 | 11 | 17 | 11. A computer system, said computer system comprising a computer, said computer configured to perform a method for improving satisfaction of a user at a user machine, said method comprising: said computer prompting a user at the user machine to select a language usage pattern preference from a plurality of language usage pattern preference choices respectively comprising a plurality of text passages, each text passage expressing different text; after said prompting, said computer receiving from the user machine a language usage pattern preference selected by the user from the plurality of language usage pattern preference choices; and said computer storing, in a user profile of the user located in a database accessible to the computer, a flag indicative of the selected language usage pattern preference. | 11. A computer system, said computer system comprising a computer, said computer configured to perform a method for improving satisfaction of a user at a user machine, said method comprising: said computer prompting a user at the user machine to select a language usage pattern preference from a plurality of language usage pattern preference choices respectively comprising a plurality of text passages, each text passage expressing different text; after said prompting, said computer receiving from the user machine a language usage pattern preference selected by the user from the plurality of language usage pattern preference choices; and said computer storing, in a user profile of the user located in a database accessible to the computer, a flag indicative of the selected language usage pattern preference. 17. The computer system of claim 11 , wherein the user machine is a telephone, and wherein the method further comprises: said computer querying the user at the telephone to determine preferred voice qualities while the computer is engaged in telephone communication with the user via the telephone; said computer receiving, from the user at the telephone, responses to said querying; said computer determining from the responses received from the user, using voice recognition functions of the telephonic response system, the preferred voice qualities; and said computer storing, in the user profile, the preferred voice qualities determined from the responses received from the user. | 0.50073 |
9,020,932 | 16 | 20 | 16. The computer program product of claim 15 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the computer readable program code instructions, when executed by the computer processing unit, further cause the computer processing unit to classify the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories. | 16. The computer program product of claim 15 , wherein the retrieved search history data comprises unique user search history data that is associated with identity indicia that is unique to the user, and generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having common same occupational identity indicia; and wherein the computer readable program code instructions, when executed by the computer processing unit, further cause the computer processing unit to classify the text string search query into the constituent primary search terms by weighting classifications determined as a function of the unique user search history data more highly than classifications determined as a function of the generic occupational identity search data, and weighting classifications determined as a function of the generic occupational identity search data more highly than any classifications generated by application of universal search history popularities common to all user histories. 20. The computer program product of claim 16 , wherein the computer readable program code instructions, when executed by the computer processing unit, further cause the computer processing unit to display the primary set of search results, the secondary set of search results and the set of peripheral knowledge articles to the user in the different, respective tabbed sheets that are nested on top of one another in a web-based interface dashboard, by: displaying a list of the primary set of results to the user in a primary tabbed sheet of the nested tabbed sheets; listing the secondary set of search results in a secondary tabbed sheet of the nested tabbed sheets, wherein the list of the secondary set of search results is nested behind the primary tabbed sheet and not visible to the user unless selected by the user; and listing the set of peripheral search results in a peripheral tabbed sheet of the nested tabbed sheets, wherein the list of the set of peripheral search results is nested behind the primary and secondary tabbed sheets and not visible to the user unless selected by the user; and wherein selection of one of the secondary tabbed sheet and the peripheral tabbed sheet by the user via a graphical user interface cursor routine causes the processing unit to display the list of results of the selected one of the secondary tabbed sheet and the peripheral tabbed sheet in a tabbed sheet display above each of other unselected ones of the primary tabbed sheet, the secondary tabbed sheet and the peripheral tabbed sheet. | 0.716544 |
9,940,397 | 8 | 12 | 8. A non-transitory computer-readable storage medium storing instructions that, when executed by a mobile client device executing a social media messaging program, cause the mobile client device to perform the operations of: receiving, in the social media messaging program, a search request including one or more search terms; in accordance with a predefined search type hierarchy, searching content of a first set of content types of a plurality of content types to produce first search results, wherein: the search is based on the search request; and the predefined search type hierarchy specifies an order with which content types in the plurality of content types are to be searched; determining a count of the first search results; when the count of first search results is greater than or equal to a predefined number, displaying the first search results and affordances for searching content of one or more other content types in the plurality of content types; when the count of first search results is less than the predefined number: in accordance with the predefined search type hierarchy, searching content of a second set of content types of the plurality of content types to produce second search results; and displaying the second search results. | 8. A non-transitory computer-readable storage medium storing instructions that, when executed by a mobile client device executing a social media messaging program, cause the mobile client device to perform the operations of: receiving, in the social media messaging program, a search request including one or more search terms; in accordance with a predefined search type hierarchy, searching content of a first set of content types of a plurality of content types to produce first search results, wherein: the search is based on the search request; and the predefined search type hierarchy specifies an order with which content types in the plurality of content types are to be searched; determining a count of the first search results; when the count of first search results is greater than or equal to a predefined number, displaying the first search results and affordances for searching content of one or more other content types in the plurality of content types; when the count of first search results is less than the predefined number: in accordance with the predefined search type hierarchy, searching content of a second set of content types of the plurality of content types to produce second search results; and displaying the second search results. 12. The non-transitory computer-readable storage medium of claim 8 , wherein the predefined number is one. | 0.892713 |
8,166,032 | 18 | 19 | 18. The method of claim 15 , wherein defining the region of sentimental significance in the document sentiment vector space further comprises: creating an action document vector for each document vector from the documents-by-concepts matrix representing a sentimentally significant document. | 18. The method of claim 15 , wherein defining the region of sentimental significance in the document sentiment vector space further comprises: creating an action document vector for each document vector from the documents-by-concepts matrix representing a sentimentally significant document. 19. The method of claim 18 , wherein assessing the sentimentality of the query string, by the computer, by comparing the representation of the query string for semantic similarity to the region of sentimental significance in the document sentiment vector space further comprises: selecting an action document vector most semantically similar to the query string for assessing the sentimentality of the query string. | 0.940578 |
8,701,008 | 18 | 22 | 18. A system for sharing multimedia editing techniques, comprising: a first server having a computer processor device; and a project sharing application executable in the first server that responds to requests for reviewing edited multimedia content, the project sharing application comprising: a user interface configured to receive the edited multimedia content from a second server; an object collecting module configured to receive a project description file associated with timing data of the edited multimedia content and determine arrangement of multimedia editing objects specified in the project description file, the timing data specifying a duration of each of the multimedia editing objects; and a playback module configured to playback the edited multimedia content from the second server while the multimedia editing objects specified in the project description file are synchronized according to the timing data, wherein the edited multimedia content received from the second server is synchronized with the multimedia editing objects at the first server according to a specified location of a progression bar on a timeline received by the first server, wherein the multimedia editing objects comprise video editing effects previously applied to the multimedia content to generate the edited multimedia content. | 18. A system for sharing multimedia editing techniques, comprising: a first server having a computer processor device; and a project sharing application executable in the first server that responds to requests for reviewing edited multimedia content, the project sharing application comprising: a user interface configured to receive the edited multimedia content from a second server; an object collecting module configured to receive a project description file associated with timing data of the edited multimedia content and determine arrangement of multimedia editing objects specified in the project description file, the timing data specifying a duration of each of the multimedia editing objects; and a playback module configured to playback the edited multimedia content from the second server while the multimedia editing objects specified in the project description file are synchronized according to the timing data, wherein the edited multimedia content received from the second server is synchronized with the multimedia editing objects at the first server according to a specified location of a progression bar on a timeline received by the first server, wherein the multimedia editing objects comprise video editing effects previously applied to the multimedia content to generate the edited multimedia content. 22. The system of claim 18 , wherein the project description file comprises an extensible markup language (XML) file. | 0.913462 |
8,600,733 | 2 | 4 | 2. A computer-implemented method comprising: receiving a plurality of language indicators, wherein each of the plurality of language indicators is either user defined or system defined; determining languages available for a first application; comparing the plurality of language indicators to the languages available for the first application; determining, by a processor, a most preferred language based upon the comparing of the plurality of language indicators to the languages available for the first application; and providing information from the first application to the user in the most preferred language. | 2. A computer-implemented method comprising: receiving a plurality of language indicators, wherein each of the plurality of language indicators is either user defined or system defined; determining languages available for a first application; comparing the plurality of language indicators to the languages available for the first application; determining, by a processor, a most preferred language based upon the comparing of the plurality of language indicators to the languages available for the first application; and providing information from the first application to the user in the most preferred language. 4. The method of claim 2 , wherein the plurality of language indicators includes an application-specific language override of the user. | 0.854212 |
7,653,545 | 3 | 4 | 3. A method as claimed in claim 2 wherein said grammar includes predefined grammar. | 3. A method as claimed in claim 2 wherein said grammar includes predefined grammar. 4. A method as claimed in claim 3 , wherein said slots include value data representing the meaning of phrase or term of a slot. | 0.959111 |
8,554,796 | 1 | 2 | 1. A method for analyzing the semantic content of network configuration files of a communication network, comprising: electronically accessing configuration files in a configuration language associated with corresponding network components of said network, said files containing commands that define the configuration of those components in said network; transforming, by using a processor, said commands into a structural database without the need for a grammar to understand the complete configuration language without losing any information in the configuration file; and constructing a semantic database of said configuration files by querying said structural database where the semantic database captures global relationships between commands in different parts of configuration files. | 1. A method for analyzing the semantic content of network configuration files of a communication network, comprising: electronically accessing configuration files in a configuration language associated with corresponding network components of said network, said files containing commands that define the configuration of those components in said network; transforming, by using a processor, said commands into a structural database without the need for a grammar to understand the complete configuration language without losing any information in the configuration file; and constructing a semantic database of said configuration files by querying said structural database where the semantic database captures global relationships between commands in different parts of configuration files. 2. The method of claim 1 including using said semantic database to detect communication network policy violations in said communication network. | 0.823096 |
9,769,314 | 6 | 8 | 6. A system for retrieving information from an information source, the information source being periodically updated with current information, over a network, by speech commands received from a particular user of a plurality of users provided by the particular user via an electronic-communication device, and wherein each of the plurality of users has a respective electronic-communication device, said system comprising: (a) a speech-recognition engine including a processor and coupled to a media server, the speech-recognition engine adapted to receive a speech command from each of the plurality of users provided via the respective electronic-communication device, the media server configured to identify and access the information source via the network, the speech-recognition engine adapted to select speech-recognition grammar established to correspond to the speech commands received from the plurality of users and assigned to a desired search; (b) the media server further configured 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 appropriate information-source-retrieval instruction stored in a database associated with the media server and adapted to retrieve information; (c) a web-browsing server coupled to the media server and adapted to access a portion of the information source to retrieve information of interest requested by the particular user, by using a processor of the web-browsing server, which processor (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 a webpage containing information of interest to a 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 information of interest from the information source and retrieving only the portion of the information of interest requested by the particular user according to the at least one information-source-retrieval instruction; and (d) a speech-synthesis engine including a processor and coupled to the media server, the speech-synthesis engine adapted to convert the information retrieved from the information source into an audio message and transmit the audio message by the electronic-communication device of the particular user requesting information of interest to the particular user. | 6. A system for retrieving information from an information source, the information source being periodically updated with current information, over a network, by speech commands received from a particular user of a plurality of users provided by the particular user via an electronic-communication device, and wherein each of the plurality of users has a respective electronic-communication device, said system comprising: (a) a speech-recognition engine including a processor and coupled to a media server, the speech-recognition engine adapted to receive a speech command from each of the plurality of users provided via the respective electronic-communication device, the media server configured to identify and access the information source via the network, the speech-recognition engine adapted to select speech-recognition grammar established to correspond to the speech commands received from the plurality of users and assigned to a desired search; (b) the media server further configured 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 appropriate information-source-retrieval instruction stored in a database associated with the media server and adapted to retrieve information; (c) a web-browsing server coupled to the media server and adapted to access a portion of the information source to retrieve information of interest requested by the particular user, by using a processor of the web-browsing server, which processor (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 a webpage containing information of interest to a 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 information of interest from the information source and retrieving only the portion of the information of interest requested by the particular user according to the at least one information-source-retrieval instruction; and (d) a speech-synthesis engine including a processor and coupled to the media server, the speech-synthesis engine adapted to convert the information retrieved from the information source into an audio message and transmit the audio message by the electronic-communication device of the particular user requesting information of interest to the particular user. 8. The system of claim 6 , wherein the respective electronic-communication device is at least one of a landline telephone, a wireless telephone, and an internet protocol telephone and wherein the media server is operatively connected to the network, which is at least one of a local-area network, a wide-area network, and the internet. | 0.685741 |
4,610,025 | 37 | 38 | 37. The method of claim 36, wherein the step of assigning unique identifiers to each set of substantially identical glyphs is achieved by identifying various physical characteristics of each of said glyphs and then determining which of said glyphs are substantially identical to other of said glyphs. | 37. The method of claim 36, wherein the step of assigning unique identifiers to each set of substantially identical glyphs is achieved by identifying various physical characteristics of each of said glyphs and then determining which of said glyphs are substantially identical to other of said glyphs. 38. The method of claim 37, wherein said pattern grouping means further comprises the step of arranging said identifiers into a plurality of individual sequences, wherein each of said individual sequences corresponds to a particular word in said language. | 0.896003 |
6,108,675 | 7 | 8 | 7. The communications network of claim 6 wherein said receiving display station further includes: means for calculating a distance by which the width of a screen page exceeds the width of the window within which the page is to be displayed, and means for setting said sequence of horizontal sampling positions at increments of said distance. | 7. The communications network of claim 6 wherein said receiving display station further includes: means for calculating a distance by which the width of a screen page exceeds the width of the window within which the page is to be displayed, and means for setting said sequence of horizontal sampling positions at increments of said distance. 8. The communications network of claim 7 wherein: said means for sampling said information density sequentially samples the information along a plurality of horizontal lines, and said means for comparing compares each sequential sample on each of said plurality of lines to said selected density level, and further including means for calculating a mean horizontal position at which said selected density level is attained in said plurality of lines, said mean horizontal position being said reference margin. | 0.727516 |
9,545,579 | 11 | 12 | 11. The computer-readable non-transitory medium storing the program according to claim 1 , wherein the specific character is specified on the basis of a positional relationship of the plurality of characters in the virtual world. | 11. The computer-readable non-transitory medium storing the program according to claim 1 , wherein the specific character is specified on the basis of a positional relationship of the plurality of characters in the virtual world. 12. The computer-readable non-transitory medium storing the program according to claim 11 , wherein specific character is specified on the basis of a positional relationship of the plurality of characters in a progress route of the game. | 0.936834 |
10,001,760 | 9 | 10 | 9. The system as set forth in claim 6 , wherein a majority of the set of competing adaptable predictive models are compared over a first time interval of current sensory data having a length, and only the matches within that majority are compared over a second time interval of current sensory data within the first time interval having a length that is shorter than the length of the first time interval. | 9. The system as set forth in claim 6 , wherein a majority of the set of competing adaptable predictive models are compared over a first time interval of current sensory data having a length, and only the matches within that majority are compared over a second time interval of current sensory data within the first time interval having a length that is shorter than the length of the first time interval. 10. The system as set forth in claim 9 , wherein the set of competing adaptable predictive models is compared over a cascade of time intervals of current sensory data having progressively shorter time intervals, wherein a number of the set of competing adaptable predictive models compared is progressively reduced. | 0.890397 |
9,142,137 | 16 | 18 | 16. Apparatus of claim 15 , wherein analyzing content of textual information comprises: mapping a plurality of words in the content to a plurality of ontology categories; mapping the plurality of ontology categories to a plurality of question headings; identifying any subjects and direct objects in the content; identifying verb phrases including at least one main verb, and identifying participial and prepositional phrases corresponding to the verb phrases identified; and mapping the participial and prepositional phrases to a corresponding ontology category of the plurality of ontology categories. | 16. Apparatus of claim 15 , wherein analyzing content of textual information comprises: mapping a plurality of words in the content to a plurality of ontology categories; mapping the plurality of ontology categories to a plurality of question headings; identifying any subjects and direct objects in the content; identifying verb phrases including at least one main verb, and identifying participial and prepositional phrases corresponding to the verb phrases identified; and mapping the participial and prepositional phrases to a corresponding ontology category of the plurality of ontology categories. 18. Apparatus of claim 16 , wherein mapping the plurality of ontology categories to the plurality of question headings comprises: determining patterns between the words of the content, and identifying the plurality of question headings to be mapped based upon the determined patterns. | 0.89497 |
9,772,871 | 1 | 4 | 1. In a host device, a method comprising: receiving, by the host device, a set of data elements from at least one computer environment resource of a computer infrastructure, each data element of the set of data elements relating to an attribute of the at least one computer environment resource; applying, by the host device, a system analysis function to the set of data elements to characterize at least one dataset specification associated with the set of data elements; receiving, by the host device, a user-selected policy threshold criterion identifying a dataset specification of the at least one dataset specification for analysis; and in response to the receiving the user-selected policy threshold criterion, adjusting, by the host device, a boundary of the identified dataset specification based on the received user-selected policy threshold criterion and a behavioral change of the computer infrastructure, thereby managing attributes of the computer infrastructure. | 1. In a host device, a method comprising: receiving, by the host device, a set of data elements from at least one computer environment resource of a computer infrastructure, each data element of the set of data elements relating to an attribute of the at least one computer environment resource; applying, by the host device, a system analysis function to the set of data elements to characterize at least one dataset specification associated with the set of data elements; receiving, by the host device, a user-selected policy threshold criterion identifying a dataset specification of the at least one dataset specification for analysis; and in response to the receiving the user-selected policy threshold criterion, adjusting, by the host device, a boundary of the identified dataset specification based on the received user-selected policy threshold criterion and a behavioral change of the computer infrastructure, thereby managing attributes of the computer infrastructure. 4. The method of claim 1 , further comprising: receiving, by the host device, a policy criterion; and wherein the receiving the set of data elements from the at least one computer environment resource of the computer infrastructure comprises receiving, by the host device, the set of data elements from the at least one computer environment resource of the computer infrastructure, each data element of the set of data elements relating to the attribute of the at least one computer environment resource associated with the policy criterion. | 0.603372 |
9,103,741 | 1 | 6 | 1. A method comprising: receiving, at a processing system, at least one vibration response parameter associated with an airfoil, wherein the at least one vibration response parameter comprises at least one of an airfoil excitation frequency, an airfoil vibration amplitude, and an airfoil structural damping; using the processing system for: computing a modal stress intensity factor (SIF) of at least one cracked airfoil finite element model using fracture mechanics based finite element analysis; and computing a vibratory SIF based, at least in part, on the modal SIF and a scaling factor comprising a variable number based on the at least one vibration response parameter; and computing a residual life indicator of the airfoil based, at least in part, on the vibratory SIF. | 1. A method comprising: receiving, at a processing system, at least one vibration response parameter associated with an airfoil, wherein the at least one vibration response parameter comprises at least one of an airfoil excitation frequency, an airfoil vibration amplitude, and an airfoil structural damping; using the processing system for: computing a modal stress intensity factor (SIF) of at least one cracked airfoil finite element model using fracture mechanics based finite element analysis; and computing a vibratory SIF based, at least in part, on the modal SIF and a scaling factor comprising a variable number based on the at least one vibration response parameter; and computing a residual life indicator of the airfoil based, at least in part, on the vibratory SIF. 6. The method of claim 1 , wherein the residual life indicator includes at least one of a crack growth rate, a cycle count assessment, and a crack size versus cycle count assessment. | 0.904911 |
8,408,913 | 1 | 3 | 1. A system for facilitating language learning wherein said system is used upon samples of a target language, wherein each of said samples is called in this invention ORIGINAL EXTRACT, said target language is a foreign language or is the native language of the learner, wherein said system comprises: a) a display apparatus, b) a memory containing information related to said original extracts, c) control logic means to show one or more BLIND EXTRACTS for at least one of said original extracts, wherein a blind extract is a graphical entity whose fragments have certain correspondence with fragments of an original extract, said original extract being associated to said blind extract, a blind extract is made up of one or more fragments, the fragments of a blind extract are created by replacing the sounds of said fragments of said original extract by graphical objects that are different from the letters associated to said sounds in said target language, d) means to prevent the user from watching text that represents said language sample while the user is watching said blind extract, e) control logic means to choose at least a fragment of a blind extract wherein said fragment is associated to a fragment of an original extract, f) means to generate information about said fragment of an original extract which is associated to said fragment of a blind extract, and wherein at least two of the linguistic entities which are included in said sample of target language and which have different pronunciation from each other are represented by graphical objects which display the same information, wherein a linguistic entity is an entity of any of the following plurality of types: sentences, phrases, words, syllables, or phonemes, and wherein said system is used in isolation or as a complement to other language orientated system, for facilitating foreign language learning or for correcting a problem in the utilization of the native language. | 1. A system for facilitating language learning wherein said system is used upon samples of a target language, wherein each of said samples is called in this invention ORIGINAL EXTRACT, said target language is a foreign language or is the native language of the learner, wherein said system comprises: a) a display apparatus, b) a memory containing information related to said original extracts, c) control logic means to show one or more BLIND EXTRACTS for at least one of said original extracts, wherein a blind extract is a graphical entity whose fragments have certain correspondence with fragments of an original extract, said original extract being associated to said blind extract, a blind extract is made up of one or more fragments, the fragments of a blind extract are created by replacing the sounds of said fragments of said original extract by graphical objects that are different from the letters associated to said sounds in said target language, d) means to prevent the user from watching text that represents said language sample while the user is watching said blind extract, e) control logic means to choose at least a fragment of a blind extract wherein said fragment is associated to a fragment of an original extract, f) means to generate information about said fragment of an original extract which is associated to said fragment of a blind extract, and wherein at least two of the linguistic entities which are included in said sample of target language and which have different pronunciation from each other are represented by graphical objects which display the same information, wherein a linguistic entity is an entity of any of the following plurality of types: sentences, phrases, words, syllables, or phonemes, and wherein said system is used in isolation or as a complement to other language orientated system, for facilitating foreign language learning or for correcting a problem in the utilization of the native language. 3. A system as claimed in claim 1 , further comprising means to graphically emphasize certain parts of at least one blind extract among said blind extracts. | 0.894452 |
7,996,367 | 1 | 6 | 1. A method using a document system comprising a computer with a processor for executing software instructions for document exchange directed to execution of a document by a plurality of parties, wherein the document is inputted with an input subsystem of the document system from an input source and stored for document exchange, the method comprising: receiving routing information and identifying metadata through the input subsystem; automatically storing the document with the input subsystem from the input source as specified in the routing information along with data automatically generated and structured based on the routing information and metadata; routing the document for execution to the plurality of parties based on the routing information; archiving the executed document in a document archive after automatically verifying that it has been executed by the plurality of parties; and providing search capability with respect to documents that are executed in the document archive and documents that are pending execution, for identifying data regarding the document and/or for text within the document, to the plurality of parties identified in the routing information. | 1. A method using a document system comprising a computer with a processor for executing software instructions for document exchange directed to execution of a document by a plurality of parties, wherein the document is inputted with an input subsystem of the document system from an input source and stored for document exchange, the method comprising: receiving routing information and identifying metadata through the input subsystem; automatically storing the document with the input subsystem from the input source as specified in the routing information along with data automatically generated and structured based on the routing information and metadata; routing the document for execution to the plurality of parties based on the routing information; archiving the executed document in a document archive after automatically verifying that it has been executed by the plurality of parties; and providing search capability with respect to documents that are executed in the document archive and documents that are pending execution, for identifying data regarding the document and/or for text within the document, to the plurality of parties identified in the routing information. 6. The method of claim 1 wherein the document is stored in a database and is accessible to individuals in the routing information through a web site or web service to provide the searching capability. | 0.622642 |
8,321,197 | 4 | 5 | 4. The automated computer based method as recited in claim 2 wherein a pre-determined sequence of color-codes are incorporated into the method of displaying the resultant category-based error analysis and evaluation whereby error relationships and frequency are easily discernible by the writer who is then able to make appropriate decisions allocating available practice time to the most critical areas for his or her personal performance characteristics. | 4. The automated computer based method as recited in claim 2 wherein a pre-determined sequence of color-codes are incorporated into the method of displaying the resultant category-based error analysis and evaluation whereby error relationships and frequency are easily discernible by the writer who is then able to make appropriate decisions allocating available practice time to the most critical areas for his or her personal performance characteristics. 5. The automated computer based method as recited in claim 4 wherein a tabular display compares each word or character element of the writing sample submitted to each corresponding word or character element of the master file with resultant non-matches noted and highlighted in the color-codes corresponding to the category based analysis. | 0.887897 |
8,832,104 | 1 | 2 | 1. A method for an advertiser to associate an advertisement published on a plurality of Internet websites on the world wide web comprising: a) obtaining from the advertiser at least one of the advertisement and a keyword string corresponding to the advertisement; b) deriving a contextual information regarding the advertisement from the at least one of the advertisement and the keyword string corresponding to the advertisement; c) comparing the contextual information regarding the advertisement with a set of pre-defined categories; d) determining one or more pre-defined categories from the set of pre-defined categories based on at least one of an amount of content in each of the pre-defined categories and a demographic data corresponding to a plurality of users viewing a plurality of contents in the pre-defined categories; and e) conveying the one or more pre-defined categories to the advertiser, wherein the advertiser associates the advertisement published on the plurality of Internet websites on the world wide web belonging to the one or more pre-defined categories. | 1. A method for an advertiser to associate an advertisement published on a plurality of Internet websites on the world wide web comprising: a) obtaining from the advertiser at least one of the advertisement and a keyword string corresponding to the advertisement; b) deriving a contextual information regarding the advertisement from the at least one of the advertisement and the keyword string corresponding to the advertisement; c) comparing the contextual information regarding the advertisement with a set of pre-defined categories; d) determining one or more pre-defined categories from the set of pre-defined categories based on at least one of an amount of content in each of the pre-defined categories and a demographic data corresponding to a plurality of users viewing a plurality of contents in the pre-defined categories; and e) conveying the one or more pre-defined categories to the advertiser, wherein the advertiser associates the advertisement published on the plurality of Internet websites on the world wide web belonging to the one or more pre-defined categories. 2. A method for an advertiser to associate an advertisement published on a plurality of Internet websites on the world wide web as recited in claim 1 further comprising: gathering one or more feeds associated with at least one content from a plurality of content; categorizing the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, wherein the at least one content is categorized based on the one or more feeds associated with the at least one content; and translating the set of general web-based categories into the set of pre-defined categories. | 0.500756 |
7,685,155 | 1 | 8 | 1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema. | 1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema. 8. The method of claim 1 , wherein the plurality of attributes describing the relationships between the one or more classes further comprises one or more of parent class, child class, parent member, child member, composition, parent cardinality, child cardinality, and default span. | 0.501767 |
7,809,760 | 1 | 4 | 1. A method for utilizing description records from multimedia content, the method causing a computing device to perform steps comprising: receiving multimedia content having description records generated by steps comprising: generating multimedia object descriptions for at least one identified multimedia type based on multimedia objects extracted from the multimedia content; generating, from the multimedia object descriptions, non-hierarchical entity relation graph descriptions for the at least one identified multimedia type, wherein the non-hierarchical entity relation graph descriptions are associated with communication between multimedia objects; and integrating the multimedia object descriptions and the entity relation graph descriptions to generate at least one description record to represent content embedded within the multimedia content; extracting a description record from the multimedia content; displaying the multimedia content; and displaying the extracted description record in connection with the displayed multimedia content. | 1. A method for utilizing description records from multimedia content, the method causing a computing device to perform steps comprising: receiving multimedia content having description records generated by steps comprising: generating multimedia object descriptions for at least one identified multimedia type based on multimedia objects extracted from the multimedia content; generating, from the multimedia object descriptions, non-hierarchical entity relation graph descriptions for the at least one identified multimedia type, wherein the non-hierarchical entity relation graph descriptions are associated with communication between multimedia objects; and integrating the multimedia object descriptions and the entity relation graph descriptions to generate at least one description record to represent content embedded within the multimedia content; extracting a description record from the multimedia content; displaying the multimedia content; and displaying the extracted description record in connection with the displayed multimedia content. 4. The method of claim 1 , wherein multimedia types include image, audio, video, synthetic and text. | 0.899598 |
4,156,868 | 11 | 12 | 11. A speech analyzer for recognizing a series of spoken words as one of a set of predetermined sequences of prescribed words according to claim 10 wherein said cumulative correspondence signal forming means comprises first register means addressed by said first signal initial states for storing the third signals of said sequences at the beginning of each word position time interval; second register means addressed by the first signal terminal states for storing the third signals of said sequences at the end of each word position interval, said starting state position of said first register means being initially set to a first code, all other state positions of said first and second register means being initially set to a selected largest number code, means operative in each word position interval responsive to each first signal for selecting the word position second signal associated with said first signal prescribed word; means for adding said selected word position second signal to the signal in the position of said first register means addressed by said first signal initial state; means for comparing the signal from said adding means to the signal in said second register means addressed by said first signal terminal state; means responsive to said signal from said adding means being less than the signal from said second register means for inserting said adding means signal into the position of said second register means addressed by the first signal terminal state as the word position third signal of the sequence ending in said first signal terminal state, means addressed by said first signal terminal state for storing the first signal initial state and prescribed word, and means for transferring the word position third signals in said second register means at the end of said word position time interval to said first register means and for setting each second register means position to said selected largest number code upon termination of said transfer. | 11. A speech analyzer for recognizing a series of spoken words as one of a set of predetermined sequences of prescribed words according to claim 10 wherein said cumulative correspondence signal forming means comprises first register means addressed by said first signal initial states for storing the third signals of said sequences at the beginning of each word position time interval; second register means addressed by the first signal terminal states for storing the third signals of said sequences at the end of each word position interval, said starting state position of said first register means being initially set to a first code, all other state positions of said first and second register means being initially set to a selected largest number code, means operative in each word position interval responsive to each first signal for selecting the word position second signal associated with said first signal prescribed word; means for adding said selected word position second signal to the signal in the position of said first register means addressed by said first signal initial state; means for comparing the signal from said adding means to the signal in said second register means addressed by said first signal terminal state; means responsive to said signal from said adding means being less than the signal from said second register means for inserting said adding means signal into the position of said second register means addressed by the first signal terminal state as the word position third signal of the sequence ending in said first signal terminal state, means addressed by said first signal terminal state for storing the first signal initial state and prescribed word, and means for transferring the word position third signals in said second register means at the end of said word position time interval to said first register means and for setting each second register means position to said selected largest number code upon termination of said transfer. 12. A speech analyzer for recognizing a series of spoken words as one of a set of predetermined sequences of prescribed words according to claim 11 wherein said predetermined sequence identifying means further comprises means operative upon the termination of said last word position time interval responsive to the last word position third signals for identifying the final state of the selected sequence having the minimum third signal, and means responsive to the identified final state and the stored initial states for forming a signal representative of the predetermined sequence corresponding to said identified final state from said stored prescribed words. | 0.803835 |
10,089,985 | 1 | 9 | 1. A method of providing content upon request, the method comprising: receiving, from a first user, a configuration for a guide application, the guide application being configured for use by a second user, the second user being different than the first user; receiving, from the first user, authorization for the guide application to return search results for specific content; storing, in a database, searches and content selections of the specific content; receiving, from the second user, a request to open the guide application on a user device; and via the guide application: receiving a search request for items of content, the second user selecting a first selectable graphical icon among a plurality of first selectable graphical icons, and the second user selecting, based on a selection of the first selectable graphical icon, a second selectable graphical icon among a plurality of second selectable graphical icons, the search request for the items of content being received based on a selection of the second selectable graphical icon; recognizing, by a processor of the user device, a pattern of the content selections stored in the database; modifying, by the processor and based on recognition of the pattern, the search request before a search algorithm searches for the items of content to return in response to the search request; determining, based on the search request modified by the processor and from the specific content authorized by the first user, a plurality of listings for content; and converting text describing the plurality of listings to corresponding speech describing the plurality of listings. | 1. A method of providing content upon request, the method comprising: receiving, from a first user, a configuration for a guide application, the guide application being configured for use by a second user, the second user being different than the first user; receiving, from the first user, authorization for the guide application to return search results for specific content; storing, in a database, searches and content selections of the specific content; receiving, from the second user, a request to open the guide application on a user device; and via the guide application: receiving a search request for items of content, the second user selecting a first selectable graphical icon among a plurality of first selectable graphical icons, and the second user selecting, based on a selection of the first selectable graphical icon, a second selectable graphical icon among a plurality of second selectable graphical icons, the search request for the items of content being received based on a selection of the second selectable graphical icon; recognizing, by a processor of the user device, a pattern of the content selections stored in the database; modifying, by the processor and based on recognition of the pattern, the search request before a search algorithm searches for the items of content to return in response to the search request; determining, based on the search request modified by the processor and from the specific content authorized by the first user, a plurality of listings for content; and converting text describing the plurality of listings to corresponding speech describing the plurality of listings. 9. The method of claim 1 , further comprising: detecting movement of the second user in proximity to a device that detects the movement; and determining, based on the movement of the second user, an arrangement of the plurality of listings; and configuring an arrangement of the plurality of listings in accordance with the determining. | 0.501484 |
10,147,438 | 14 | 15 | 14. The computer program product of claim 13 , further comprising: receiving first audio data comprising a first audio conversation between a first speaker and a second speaker; partitioning the first audio conversation in to one or more segments and associating each of the one or more segments with one or both of the first speaker and the second speaker; and determining a first role of the first speaker based at least in part on the role classification model. | 14. The computer program product of claim 13 , further comprising: receiving first audio data comprising a first audio conversation between a first speaker and a second speaker; partitioning the first audio conversation in to one or more segments and associating each of the one or more segments with one or both of the first speaker and the second speaker; and determining a first role of the first speaker based at least in part on the role classification model. 15. The computer program product of claim 14 , further comprising determining a second role of the second speaker based on the role classification model. | 0.936515 |
7,831,596 | 1 | 5 | 1. A method of accessing webpages, the method comprising: receiving, at a server, a query from a remote user comprising one or more query terms; identifying, at the server, one or more user attributes of the remote user responsive to the received query, wherein the user attributes are different from the query terms; evaluating a set of webpages based at least in part on the one or more query terms and a webpage score associated with each webpage of the set of webpages, wherein the webpage score is based at least in part on ratings from users with at least one user attribute that corresponds to at least one of the user attributes of the remote user; determining a list of results based on the evaluation of the set of webpages, the evaluation including the query terms received from the remote user and user attributes associated with ratings of the webpages from users, wherein the list of results includes at least one webpage of the set of webpages; transmitting the list of results to the remote user; and affecting the score of a relevant webpage from the list of results by storing a rating and the user attributes of the remote user for the relevant webpage. | 1. A method of accessing webpages, the method comprising: receiving, at a server, a query from a remote user comprising one or more query terms; identifying, at the server, one or more user attributes of the remote user responsive to the received query, wherein the user attributes are different from the query terms; evaluating a set of webpages based at least in part on the one or more query terms and a webpage score associated with each webpage of the set of webpages, wherein the webpage score is based at least in part on ratings from users with at least one user attribute that corresponds to at least one of the user attributes of the remote user; determining a list of results based on the evaluation of the set of webpages, the evaluation including the query terms received from the remote user and user attributes associated with ratings of the webpages from users, wherein the list of results includes at least one webpage of the set of webpages; transmitting the list of results to the remote user; and affecting the score of a relevant webpage from the list of results by storing a rating and the user attributes of the remote user for the relevant webpage. 5. The method of claim 1 wherein at least one of the user attributes identifies a role of a user. | 0.913547 |
8,392,441 | 23 | 30 | 23. A computer-implemented method, comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting a first split from the one or more splits according to the overall score for each split; and augmenting the query with a first synonym phrase, wherein the first synonym phrase is a synonym of a first subterm of the first split. | 23. A computer-implemented method, comprising: receiving a query submitted by a user to a search engine, wherein the query includes a first compound term; and in response to receiving the query, performing the following operations: generating one or more splits of the first compound term, wherein each split divides the compound term into two or more subterms, wherein at least one subterm is a term in a dictionary that associates terms with scores derived from a respective frequency of use of the subterm; assigning a score to one or more subterms of each split that are in the dictionary, wherein the score for a subterm is the score stored in the dictionary for the subterm; determining an overall score for each split from the scores for the subterms of the split; selecting a first split from the one or more splits according to the overall score for each split; and augmenting the query with a first synonym phrase, wherein the first synonym phrase is a synonym of a first subterm of the first split. 30. The method of claim 23 , further comprising augmenting the query with a second synonym phrase, wherein the second synonym phrase is a synonym of the first subterm of the first split. | 0.789593 |
7,636,700 | 10 | 11 | 10. An object recognition system incorporating swarming domain classifiers as set forth in claim 9 , wherein the multi-dimensional solution space consists of the dimensions (x, y, z), size, scale, internal classifier parameters, object rotation angle, and time. | 10. An object recognition system incorporating swarming domain classifiers as set forth in claim 9 , wherein the multi-dimensional solution space consists of the dimensions (x, y, z), size, scale, internal classifier parameters, object rotation angle, and time. 11. An object recognition system incorporating swarming domain classifiers as set forth in claim 10 , wherein the domain is a domain selected from a group consisting of an image, space, frequency, time, Doppler shift, time delay, wave length, and phase. | 0.965588 |
8,417,512 | 1 | 12 | 1. A computer implemented method for developing an ontology ( 70 ) of a text ( 10 ) in natural language, comprising the steps of: receiving text data from text ( 10 ); a grammatical analyzer extracting, by a computer, syntax and meaningful words ( 20 ) from the text via a grammatical analysis (S 100 ) of the received text data; for each of at least some of the meaningful words ( 20 ) of the text: searching (S 200 ) for a definition ( 40 ) of the meaningful word ( 20 ) by means of at least one electronic dictionary ( 30 , 35 ), the grammatical analyzer extracting syntax and meaningful words of the definition, and creating (S 300 ) an elementary lexical graph ( 50 ) of the definition based on the syntax and the meaningful words of the definition; and merging (S 400 ), by the computer, at least two of the elementary lexical graphs ( 50 ) created, as a function of the syntax of the text, so as to create at least one semantic graph ( 60 ) of the text. | 1. A computer implemented method for developing an ontology ( 70 ) of a text ( 10 ) in natural language, comprising the steps of: receiving text data from text ( 10 ); a grammatical analyzer extracting, by a computer, syntax and meaningful words ( 20 ) from the text via a grammatical analysis (S 100 ) of the received text data; for each of at least some of the meaningful words ( 20 ) of the text: searching (S 200 ) for a definition ( 40 ) of the meaningful word ( 20 ) by means of at least one electronic dictionary ( 30 , 35 ), the grammatical analyzer extracting syntax and meaningful words of the definition, and creating (S 300 ) an elementary lexical graph ( 50 ) of the definition based on the syntax and the meaningful words of the definition; and merging (S 400 ), by the computer, at least two of the elementary lexical graphs ( 50 ) created, as a function of the syntax of the text, so as to create at least one semantic graph ( 60 ) of the text. 12. The method according to claim 1 further comprising searching for a Web service as a function of the at least one semantic graph ( 60 ). | 0.838747 |
8,326,631 | 6 | 10 | 6. A system for indexing speech, comprising: a phonetic decoder that associates audio features of an audio signal with a first phonetic sequence at a first position in said audio signal; a lexical interpreter that associates said first phonetic sequence with a first linguistic element based on a first parameter; large vocabulary speech recognizer that associates a second linguistic element with a second position in said audio signal; a speech index comparator that compares said first position and said second position to determine a phrase window; and, said speech index comparator also compares said first linguistic element to said second linguistic element if said phrase window meets a first criteria; and a parameter adjuster that adjusts said first parameter based upon a result of said speech index comparator wherein said large vocabulary speech recognizer performs said association on a lesser portion of said audio signal than said phonetic decoder; wherein said lexical interpreter also associates said first linguistic element with a confidence value and said lesser portion of said audio signal is selected to correspond to said first linguistic element based upon said confidence value. | 6. A system for indexing speech, comprising: a phonetic decoder that associates audio features of an audio signal with a first phonetic sequence at a first position in said audio signal; a lexical interpreter that associates said first phonetic sequence with a first linguistic element based on a first parameter; large vocabulary speech recognizer that associates a second linguistic element with a second position in said audio signal; a speech index comparator that compares said first position and said second position to determine a phrase window; and, said speech index comparator also compares said first linguistic element to said second linguistic element if said phrase window meets a first criteria; and a parameter adjuster that adjusts said first parameter based upon a result of said speech index comparator wherein said large vocabulary speech recognizer performs said association on a lesser portion of said audio signal than said phonetic decoder; wherein said lexical interpreter also associates said first linguistic element with a confidence value and said lesser portion of said audio signal is selected to correspond to said first linguistic element based upon said confidence value. 10. The system of claim 6 , further comprising: a phonetic sequence correlator that correlates a second phonetic sequence associated with said second linguistic element with said first phonetic sequence. | 0.787657 |
8,447,139 | 8 | 10 | 8. An information processing system for detecting objects in a digital image, the information processing system comprising: a memory; a processor communicatively coupled to the memory; and an object detection system communicatively coupled to the memory and the processor, the object detection system configured to perform a method comprising: receiving at least one image representing at least one frame of a video sequence comprising zero or more objects of at least one desired object type; placing a sliding window of different window sizes at different locations in the at least one image; applying, for each window size and each location, a cascaded classifier comprising a plurality of increasingly accurate layers, each layer comprising a plurality of classifiers; evaluating, at each layer in the plurality of increasingly accurate layers, an area of the at least one image within a current sliding window using one or more weak classifiers in the plurality of classifiers based on at least one of Haar features and Histograms of Oriented Gradients (HOG) features, wherein an output of each weak classifier is a weak decision as to whether the area of the at least one image within the current sliding window comprises an instance of an object of the desired object type; identifying, based on the evaluating, a location within the image of the zero or more objects associated with the desired object type; and training each weak classifier in the plurality of classifiers based on Haar features and HOG features, wherein a selection of a subsequent weak classifier during the training is based on the subsequent weak classifier that provides a strongest separation between desired object types than other available weak classifiers independent of the subsequent weak classifier being associated with one of a Haar feature and a HOG feature. | 8. An information processing system for detecting objects in a digital image, the information processing system comprising: a memory; a processor communicatively coupled to the memory; and an object detection system communicatively coupled to the memory and the processor, the object detection system configured to perform a method comprising: receiving at least one image representing at least one frame of a video sequence comprising zero or more objects of at least one desired object type; placing a sliding window of different window sizes at different locations in the at least one image; applying, for each window size and each location, a cascaded classifier comprising a plurality of increasingly accurate layers, each layer comprising a plurality of classifiers; evaluating, at each layer in the plurality of increasingly accurate layers, an area of the at least one image within a current sliding window using one or more weak classifiers in the plurality of classifiers based on at least one of Haar features and Histograms of Oriented Gradients (HOG) features, wherein an output of each weak classifier is a weak decision as to whether the area of the at least one image within the current sliding window comprises an instance of an object of the desired object type; identifying, based on the evaluating, a location within the image of the zero or more objects associated with the desired object type; and training each weak classifier in the plurality of classifiers based on Haar features and HOG features, wherein a selection of a subsequent weak classifier during the training is based on the subsequent weak classifier that provides a strongest separation between desired object types than other available weak classifiers independent of the subsequent weak classifier being associated with one of a Haar feature and a HOG feature. 10. The information processing system of claim 8 , wherein the evaluating further comprises: combining each decision from all of the classifiers in the plurality of classifiers into a unified decision; determining that the unified decision indicates that the area of the at least one image fails to comprise an instance of the desired object type; and preventing a sliding window currently being evaluated from being evaluated any further. | 0.675296 |
7,769,768 | 1 | 6 | 1. A method for managing an organization of data, the method comprising: generating a candidate reference taxonomy for representing an organization of stored data for multiple disparate application programs that are operating under different operating systems in different computer systems, wherein the candidate reference taxonomy is a proposed hierarchical organization of folders for the stored data; comparing the candidate reference taxonomy with an application taxonomy for each of the multiple disparate application programs wherein an application taxonomy is an innate hierarchy of folders that is associated with a particular application program; and in response to a user selecting the candidate reference taxonomy to be used to replace the application taxonomies for the disparate application programs, storing the candidate reference taxonomy as a replacement reference taxonomy for the application taxonomies for all of the disparate application programs, wherein each of the disparate application programs utilizes the replacement reference taxonomy instead of an application taxonomy to organize the folders of the stored data, and wherein the replacement reference taxonomy generated from an aggregation of data structures and data interrelationships used by two or more of the multiple disparate application programs repositions depictions of folders found in the innate hierarchy of folders that was associated with the particular application program. | 1. A method for managing an organization of data, the method comprising: generating a candidate reference taxonomy for representing an organization of stored data for multiple disparate application programs that are operating under different operating systems in different computer systems, wherein the candidate reference taxonomy is a proposed hierarchical organization of folders for the stored data; comparing the candidate reference taxonomy with an application taxonomy for each of the multiple disparate application programs wherein an application taxonomy is an innate hierarchy of folders that is associated with a particular application program; and in response to a user selecting the candidate reference taxonomy to be used to replace the application taxonomies for the disparate application programs, storing the candidate reference taxonomy as a replacement reference taxonomy for the application taxonomies for all of the disparate application programs, wherein each of the disparate application programs utilizes the replacement reference taxonomy instead of an application taxonomy to organize the folders of the stored data, and wherein the replacement reference taxonomy generated from an aggregation of data structures and data interrelationships used by two or more of the multiple disparate application programs repositions depictions of folders found in the innate hierarchy of folders that was associated with the particular application program. 6. The method of claim 1 , wherein the step of generating a candidate reference taxonomy further comprises: receiving user inputs via a graphical user interface; and interpreting user inputs to generate nodes representing data structures of a taxonomy and to generate information representing relationships between data structures in the candidate reference taxonomy. | 0.72281 |
6,044,385 | 10 | 11 | 10. A data processing system according to claim 9, wherein said second magnification level comprises a range of vertical magnification levels that decrease in proportion to vertical distance from said lens. | 10. A data processing system according to claim 9, wherein said second magnification level comprises a range of vertical magnification levels that decrease in proportion to vertical distance from said lens. 11. A data processing system according to claim 10, wherein, when said vertical magnification level would cause corresponding contents of said document to be displayed illegibly, said document presenter displays textual characters that are less complex than said corresponding contents in said window, in lieu of said corresponding contents. | 0.886258 |
9,954,805 | 9 | 13 | 9. A non-transitory computer readable medium, on which is stored software for detecting graymail without explicit user feedback, comprising instructions that when executed by a graymail detection system cause the graymail detection system to: receive a non-spam email for a user; extract features of the email; predict with a classifier model based on the extracted features whether the user would consider the email as graymail; modifying the email by inserting tracking information before delivering the email to the user; storing the inserted tracking information in a tracking database; track user actions on the email without explicit user feedback using the inserted tracking information; updating the tracking database upon detection of tracked user actions on the email; determine whether the user considered the email as graymail responsive to the tracked user actions without explicit user feedback; and train the classifier model responsive to the tracked user actions. | 9. A non-transitory computer readable medium, on which is stored software for detecting graymail without explicit user feedback, comprising instructions that when executed by a graymail detection system cause the graymail detection system to: receive a non-spam email for a user; extract features of the email; predict with a classifier model based on the extracted features whether the user would consider the email as graymail; modifying the email by inserting tracking information before delivering the email to the user; storing the inserted tracking information in a tracking database; track user actions on the email without explicit user feedback using the inserted tracking information; updating the tracking database upon detection of tracked user actions on the email; determine whether the user considered the email as graymail responsive to the tracked user actions without explicit user feedback; and train the classifier model responsive to the tracked user actions. 13. The computer readable medium of claim 9 , wherein the instructions that when executed cause the graymail detection system to determine whether the user considered the email as graymail comprise instructions that when executed cause the graymail detection system to: detect user actions on the email without explicit user feedback; analyze the detected user actions; and determine whether the user considered the email as graymail or non-graymail responsive to the analysis. | 0.830731 |
8,997,073 | 8 | 9 | 8. A heterogenous computing system comprising: a processor; an accelerator memory; and a compiler that identifies code regions in an application from which one or more offloadable tasks can be generated for the heterogenous computing system, wherein the identifying comprises: adding relaxed semantics to a directive based language in the heterogenous computing system for allowing a user to suggest rather than specify a parallel code region as an offloadable task candidate, wherein the offloadable task candidate is a sub-offload or a super-offload; and identifying one or more offloadable tasks in a neighborhood of code region marked by the directive based language. | 8. A heterogenous computing system comprising: a processor; an accelerator memory; and a compiler that identifies code regions in an application from which one or more offloadable tasks can be generated for the heterogenous computing system, wherein the identifying comprises: adding relaxed semantics to a directive based language in the heterogenous computing system for allowing a user to suggest rather than specify a parallel code region as an offloadable task candidate, wherein the offloadable task candidate is a sub-offload or a super-offload; and identifying one or more offloadable tasks in a neighborhood of code region marked by the directive based language. 9. The heterogenous computing system of claim 8 , wherein the sub-offload comprises only part of the neighborhood of code region marked by the directive based language is offloaded to the accelerator memory while the other part of the neighborhood of code region executes on the processor in parallel. | 0.52673 |
9,760,640 | 1 | 8 | 1. A method comprising: receiving, by a Web server over a communications network including the Internet, a request from a user client device to access content of a target domain, the request being addressed to a domain address of the target domain; identifying, by the Web server, a new content domain that is determined to be relevant to the request to access content of a target domain based on a combination of the domain address of the target domain, source context factors that characterize the user client device, and historical relevance data associated with the target domain, the historical relevance data including source context factors of multiple users who requested to access at least one given address from addresses belonging to the domain address of the target domain and interests of the multiple users, the interests of the multiple users based on pre-access behavior of the multiple users; and providing, by the Web server, the user client device with access to content of the identified new content domain over the communications network, responsive to the request. | 1. A method comprising: receiving, by a Web server over a communications network including the Internet, a request from a user client device to access content of a target domain, the request being addressed to a domain address of the target domain; identifying, by the Web server, a new content domain that is determined to be relevant to the request to access content of a target domain based on a combination of the domain address of the target domain, source context factors that characterize the user client device, and historical relevance data associated with the target domain, the historical relevance data including source context factors of multiple users who requested to access at least one given address from addresses belonging to the domain address of the target domain and interests of the multiple users, the interests of the multiple users based on pre-access behavior of the multiple users; and providing, by the Web server, the user client device with access to content of the identified new content domain over the communications network, responsive to the request. 8. The method of claim 1 wherein the domain address is an IP address. | 0.942975 |
8,903,924 | 6 | 7 | 6. The method of claim 1 , further comprising determining, by the computer system, if an additional first set of associated data that is associated with the extracted first data of interest is available, and, if available, obtaining, by the computer, the additional first set of associated data. | 6. The method of claim 1 , further comprising determining, by the computer system, if an additional first set of associated data that is associated with the extracted first data of interest is available, and, if available, obtaining, by the computer, the additional first set of associated data. 7. The method of claim 6 , wherein determining, by the computer system, if an additional first set of associated data that is associated with the extracted first data of interest is available is performed after a predetermined time period after displaying, by the computer system and independently of the text-based electronic communications and the at least one electronic resource, the extracted first data of interest with the obtained initial first set of associated data. | 0.902138 |
8,082,241 | 6 | 7 | 6. A computer-based system for processing one or more citations within a document, the system comprising: citation editor software to identify an unformatted citation within a document; and a citation application to receive the unformatted citation, identify a citation that matches the unformatted citation in a citation library storing multiple citations, and pass information based on the matching citation to the citation editor software for enabling the citation editor software to insert a formatted citation into the document. | 6. A computer-based system for processing one or more citations within a document, the system comprising: citation editor software to identify an unformatted citation within a document; and a citation application to receive the unformatted citation, identify a citation that matches the unformatted citation in a citation library storing multiple citations, and pass information based on the matching citation to the citation editor software for enabling the citation editor software to insert a formatted citation into the document. 7. The system of claim 6 wherein the citation editor software identifies the unformatted citation on a periodic basis. | 0.826471 |
9,928,829 | 14 | 16 | 14. An apparatus for identifying a possible error made by a speech recognition system comprising: a processor that is operable to: identify when a hypothesis generated by the speech recognition system does not match an expected response word-for-word, but the hypothesis mostly matches the expected response word-for-word; identify an instance where the speech recognition system rejects a first hypothesis of a first utterance received from a user, followed by the speech recognition system accepting a second hypothesis of a second utterance received from the user, wherein the first hypothesis and the second hypothesis substantially match word-for-word; incrementing a count of an occurrence of a possible error made by the speech recognition system; and adjusting an adaptation of a model used by the speech recognition system for a word associated with the possible error when the count exceeds an acceptance threshold. | 14. An apparatus for identifying a possible error made by a speech recognition system comprising: a processor that is operable to: identify when a hypothesis generated by the speech recognition system does not match an expected response word-for-word, but the hypothesis mostly matches the expected response word-for-word; identify an instance where the speech recognition system rejects a first hypothesis of a first utterance received from a user, followed by the speech recognition system accepting a second hypothesis of a second utterance received from the user, wherein the first hypothesis and the second hypothesis substantially match word-for-word; incrementing a count of an occurrence of a possible error made by the speech recognition system; and adjusting an adaptation of a model used by the speech recognition system for a word associated with the possible error when the count exceeds an acceptance threshold. 16. The apparatus of claim 14 , wherein the first and second utterances are spoken consecutively, proximately or within a predetermined amount of time. | 0.867544 |
9,463,334 | 1 | 2 | 1. A computer implemented method of automatically generating a radiation treatment plan for a patient, said method comprising: accessing patient information pertaining to planning a radiation treatment for said patient; automatically selecting one or more predictive models based on said patient information in accordance with a hierarchical model comprising a plurality of predictive models arranged in a hierarchy, wherein a respective predictive model of said plurality of predictive models is established based on training data and operable to generate a radiation treatment prediction, wherein said hierarchical model is automatically generated through a machine training process, and wherein said respective predictive model represents a correlation between a set of input variables representing patient information features and a set of output variables; processing said patient information in accordance with said one or more predictive models; and outputting one or more radiation treatment predictions. | 1. A computer implemented method of automatically generating a radiation treatment plan for a patient, said method comprising: accessing patient information pertaining to planning a radiation treatment for said patient; automatically selecting one or more predictive models based on said patient information in accordance with a hierarchical model comprising a plurality of predictive models arranged in a hierarchy, wherein a respective predictive model of said plurality of predictive models is established based on training data and operable to generate a radiation treatment prediction, wherein said hierarchical model is automatically generated through a machine training process, and wherein said respective predictive model represents a correlation between a set of input variables representing patient information features and a set of output variables; processing said patient information in accordance with said one or more predictive models; and outputting one or more radiation treatment predictions. 2. The computer implemented method of claim 1 , wherein said automatically selecting and said processing comprise: generating radiation treatment predictions based on said patient information using said plurality of predictive models; evaluating said radiation treatment predictions; and selecting said one or more predictive model based on said evaluating. | 0.787753 |
7,917,478 | 1 | 12 | 1. A computer implemented method for inferring a probability of a first inference related to identification of a cause of an outcome in a healthcare setting, the computer implemented method comprising: receiving a query at a database regarding a fact related to the healthcare setting, wherein the fact further relates to a network of interactions associated with the outcome, 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 specifying cohorts associated with the corresponding datum, data specifying hierarchies associated with the corresponding datum, data specifying a corresponding source of the datum, and data specifying probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; applying a first set of rules to the query, wherein the first set of rules are determined for the query according to a second set of rules, wherein the first set of rules determine how the plurality of 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 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; and storing the probability of the first inference. | 1. A computer implemented method for inferring a probability of a first inference related to identification of a cause of an outcome in a healthcare setting, the computer implemented method comprising: receiving a query at a database regarding a fact related to the healthcare setting, wherein the fact further relates to a network of interactions associated with the outcome, 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 specifying cohorts associated with the corresponding datum, data specifying hierarchies associated with the corresponding datum, data specifying a corresponding source of the datum, and data specifying probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; applying a first set of rules to the query, wherein the first set of rules are determined for the query according to a second set of rules, wherein the first set of rules determine how the plurality of 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 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; and storing the probability of the first inference. 12. The computer implemented method of claim 1 further comprising: cross-linking a network of outcomes to the network of interactions. | 0.946698 |
9,589,562 | 13 | 14 | 13. A speech recognition system for assisted dynamic learning of new pronunciations for user input, the speech recognition system comprising: at least one processor; a memory connected to the at least one processor; and a recognition event store encoded on the memory storing recognition event data for tasks initiated by spoken utterances, the recognition event data including audio data of the spoken utterances, recognition results obtained by decoding the spoken utterances, subsequent user inputs, and indicators of whether outcomes of tasks initiated based on the recognition results and the subsequent user inputs were accepted or rejected by users; wherein the memory contains computer executable instructions for: an event classifier configured to classify recognition results as misrecognized spoken utterances based on determining that tasks initiated by the recognition result were not completed successfully based on an indication that outcomes of the tasks were not accepted, determining that subsequent tasks initiated based on subsequent user inputs were completed successfully based on an indication that outcomes of the subsequent tasks being accepted, and determining that a subsequent user input and recognition result pair from a single source have significant similarity, and configured to identify misrecognized portions of the recognition results based on the subsequent user inputs; a pronunciation generator configured to generate hypothetical pronunciations for the identified misrecognized portions using the corresponding portions of the subsequent user inputs after the event classifier has classified recognition results as misrecognized spoken utterances based on determining that tasks initiated by the recognition result were not completed successfully based on an indication that outcomes of the tasks were not accepted, determining that subsequent tasks initiate based on subsequent user inputs were completed successfully based on an indication that outcomes of the subsequent tasks being accepted, and determining that a subsequent user input and recognition result pair from a single source have significant similarity; a speech recognizer configured to match hypothetical pronunciations with the audio data of spoken utterances that produced recognition results classified as misrecognized spoken utterances; and an aggregation adjudicator configured to select new pronunciations for the misrecognized words from the matching pronunciations. | 13. A speech recognition system for assisted dynamic learning of new pronunciations for user input, the speech recognition system comprising: at least one processor; a memory connected to the at least one processor; and a recognition event store encoded on the memory storing recognition event data for tasks initiated by spoken utterances, the recognition event data including audio data of the spoken utterances, recognition results obtained by decoding the spoken utterances, subsequent user inputs, and indicators of whether outcomes of tasks initiated based on the recognition results and the subsequent user inputs were accepted or rejected by users; wherein the memory contains computer executable instructions for: an event classifier configured to classify recognition results as misrecognized spoken utterances based on determining that tasks initiated by the recognition result were not completed successfully based on an indication that outcomes of the tasks were not accepted, determining that subsequent tasks initiated based on subsequent user inputs were completed successfully based on an indication that outcomes of the subsequent tasks being accepted, and determining that a subsequent user input and recognition result pair from a single source have significant similarity, and configured to identify misrecognized portions of the recognition results based on the subsequent user inputs; a pronunciation generator configured to generate hypothetical pronunciations for the identified misrecognized portions using the corresponding portions of the subsequent user inputs after the event classifier has classified recognition results as misrecognized spoken utterances based on determining that tasks initiated by the recognition result were not completed successfully based on an indication that outcomes of the tasks were not accepted, determining that subsequent tasks initiate based on subsequent user inputs were completed successfully based on an indication that outcomes of the subsequent tasks being accepted, and determining that a subsequent user input and recognition result pair from a single source have significant similarity; a speech recognizer configured to match hypothetical pronunciations with the audio data of spoken utterances that produced recognition results classified as misrecognized spoken utterances; and an aggregation adjudicator configured to select new pronunciations for the misrecognized words from the matching pronunciations. 14. The speech recognition system of claim 13 wherein the aggregation adjudicator is further configured to aggregate the matching pronunciations and select a new pronunciation based on the occurrence frequency of the matching pronunciations. | 0.751033 |
9,417,941 | 6 | 7 | 6. The processing device of claim 1 , where the instruction sequence comprises one or more non-selected instructions, which are not in the subsequence of selected instructions. | 6. The processing device of claim 1 , where the instruction sequence comprises one or more non-selected instructions, which are not in the subsequence of selected instructions. 7. The processing device of claim 6 , wherein the processing device is arranged, in response to execution of each of the non-selected instructions, to set the status word to a value, which is independent of input data of the instruction sequence and results of preceding instructions of the instruction sequence. | 0.875796 |
8,914,769 | 17 | 20 | 17. A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the method comprising: identifying a server data structure defined according to the first programming language; determining types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client; generating a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; and generating source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. | 17. A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the method comprising: identifying a server data structure defined according to the first programming language; determining types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client; generating a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; and generating source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. 20. The medium of claim 17 wherein: identifying the original data structure comprises reviewing compiled source code for a server implementing the original data structure. | 0.788366 |
9,660,869 | 12 | 14 | 12. A non-transitory computer program product storing instructions which, when executed by at least one data processor forming part of at least one computing system, result in operations comprising: obtaining, by at least one data processor, a plurality of records from a plurality of sources, the plurality of records comprising a plurality of types of data; assembling, by at least one data processor, a plurality of typed datasets based on the obtained records, the assembling comprising: extracting, from the plurality of records, typed data that corresponds to all data of a single type found in the obtained records; assembling, by at least one data processor, at least one network comprising: a plurality of nodes representing all instances of the typed data corresponding to a common event; and a plurality of edges representing a relationship between the plurality of nodes, the relationship defining a connection between two or more of the plurality of nodes, where the edges comprise a weighting attribute representing a similarity between the nodes connected by the connection, the plurality of nodes and the plurality of edges stored as accessible memory objects in the at least one computing system; assembling, by at least one data processor, a vector by using a network analyzer the assembling comprising: determining a required input format for an analytic configured to operate on the vector; and generating, at the network analyzer, the vector comprising a subset of the typed data corresponding to the required input format; passing, by at least one data processor, the vector to the one analytic; generating, by at least one data processor and the analytic, an output from the analytic based on at least the vector passed to the analytic, the output comprising electronic data corresponding to a result of the analytic operating on the vector; and providing, by at least one data processor, data comprising the output. | 12. A non-transitory computer program product storing instructions which, when executed by at least one data processor forming part of at least one computing system, result in operations comprising: obtaining, by at least one data processor, a plurality of records from a plurality of sources, the plurality of records comprising a plurality of types of data; assembling, by at least one data processor, a plurality of typed datasets based on the obtained records, the assembling comprising: extracting, from the plurality of records, typed data that corresponds to all data of a single type found in the obtained records; assembling, by at least one data processor, at least one network comprising: a plurality of nodes representing all instances of the typed data corresponding to a common event; and a plurality of edges representing a relationship between the plurality of nodes, the relationship defining a connection between two or more of the plurality of nodes, where the edges comprise a weighting attribute representing a similarity between the nodes connected by the connection, the plurality of nodes and the plurality of edges stored as accessible memory objects in the at least one computing system; assembling, by at least one data processor, a vector by using a network analyzer the assembling comprising: determining a required input format for an analytic configured to operate on the vector; and generating, at the network analyzer, the vector comprising a subset of the typed data corresponding to the required input format; passing, by at least one data processor, the vector to the one analytic; generating, by at least one data processor and the analytic, an output from the analytic based on at least the vector passed to the analytic, the output comprising electronic data corresponding to a result of the analytic operating on the vector; and providing, by at least one data processor, data comprising the output. 14. The computer program product of claim 12 the assembling further comprising: reducing, by at least one data processor, a dimensionality of the vector relative to the network to allow the analytic to receive the vector and generate the output. | 0.652975 |
9,740,297 | 1 | 2 | 1. A computer-implemented method, comprising: receiving first image data captured using one or more imaging sensors associated with an electronic device; analyzing the first image data to determine a first relative orientation between the electronic device and at least a first portion of an object represented in the first image data; displaying a plurality of selectable elements on a display element associated with the electronic device; receiving second image data captured using the one or more imaging sensors; analyzing the second image data to determine a second relative orientation between the electronic device and at least a second portion of the object represented in the second image data; determining a first rate of a first change in orientation between the first relative orientation and the second relative orientation; displaying a first movement of a selection element to a first selectable element of the plurality of selectable elements on the display element such that a first direction of the first movement corresponds to the first change in orientation and a second rate of the first movement corresponds to the first rate of the first change in orientation; receiving third image data captured using the one or more imaging sensors; analyzing the third image data to determine a third relative orientation between the electronic device and at least a third portion of the object represented in the third image data; determining a third rate of a second change in orientation between the second relative orientation and the third relative orientation; displaying a second movement of the selection element to a second selectable element of the plurality of selectable elements on the display element such that a second direction of the second movement corresponds to the second change in orientation and a fourth rate of the second movement corresponds to the third rate of the second change in orientation; receiving a selection of the second selectable element; and performing an action on the electronic device associated with the selection of the second selectable element. | 1. A computer-implemented method, comprising: receiving first image data captured using one or more imaging sensors associated with an electronic device; analyzing the first image data to determine a first relative orientation between the electronic device and at least a first portion of an object represented in the first image data; displaying a plurality of selectable elements on a display element associated with the electronic device; receiving second image data captured using the one or more imaging sensors; analyzing the second image data to determine a second relative orientation between the electronic device and at least a second portion of the object represented in the second image data; determining a first rate of a first change in orientation between the first relative orientation and the second relative orientation; displaying a first movement of a selection element to a first selectable element of the plurality of selectable elements on the display element such that a first direction of the first movement corresponds to the first change in orientation and a second rate of the first movement corresponds to the first rate of the first change in orientation; receiving third image data captured using the one or more imaging sensors; analyzing the third image data to determine a third relative orientation between the electronic device and at least a third portion of the object represented in the third image data; determining a third rate of a second change in orientation between the second relative orientation and the third relative orientation; displaying a second movement of the selection element to a second selectable element of the plurality of selectable elements on the display element such that a second direction of the second movement corresponds to the second change in orientation and a fourth rate of the second movement corresponds to the third rate of the second change in orientation; receiving a selection of the second selectable element; and performing an action on the electronic device associated with the selection of the second selectable element. 2. The computer-implemented method of claim 1 , further comprising: determining a relative motion of the first portion of the object over a period of time between capture of the first image data and capture of the second image data. | 0.786765 |
9,244,973 | 1 | 6 | 1. A method comprising: receiving, by a computing device, a media file; parsing the media file to determine a grammatical structure of language contained in the media file; and adding the language contained in the media file to an index. | 1. A method comprising: receiving, by a computing device, a media file; parsing the media file to determine a grammatical structure of language contained in the media file; and adding the language contained in the media file to an index. 6. The method of claim 1 , comprising: determining a part of speech of the language contained in the media file. | 0.88501 |
7,529,729 | 9 | 10 | 9. A program product stored on a computer recordable medium for analyzing table access in a database system, comprising: program code configured for defining an incorrect rule set and a related correct rule set from a database model associated with the database system; program code configured for retrieving index definitions for the database system; program code configured for comparing the index definitions with the incorrect rule set to identify improper indexes independent of SQL processing; program code configured for generating a list of index definitions that match a rule in the incorrect rule set; program code configured for retrieving application programs for the database system; program code configured for comparing application programs with the index definitions that match a rule in the incorrect rule set; program code configured for generating a list of application programs which match a rule in the incorrect rule set; program code configured for merging the list of index definitions with the list of application programs; program code configured for reporting the merged list of index definitions and application programs; program code configured for identifying and outputting to memory application program statements that utilize the improper indexes; and program code configured for using the related correct rule set to propose changes to the improper indexes and any application programs that depend on the improper indexes. | 9. A program product stored on a computer recordable medium for analyzing table access in a database system, comprising: program code configured for defining an incorrect rule set and a related correct rule set from a database model associated with the database system; program code configured for retrieving index definitions for the database system; program code configured for comparing the index definitions with the incorrect rule set to identify improper indexes independent of SQL processing; program code configured for generating a list of index definitions that match a rule in the incorrect rule set; program code configured for retrieving application programs for the database system; program code configured for comparing application programs with the index definitions that match a rule in the incorrect rule set; program code configured for generating a list of application programs which match a rule in the incorrect rule set; program code configured for merging the list of index definitions with the list of application programs; program code configured for reporting the merged list of index definitions and application programs; program code configured for identifying and outputting to memory application program statements that utilize the improper indexes; and program code configured for using the related correct rule set to propose changes to the improper indexes and any application programs that depend on the improper indexes. 10. The program product of claim 9 , wherein each incorrect rule in the incorrect rule set includes a table name, a name of a column in the table containing redundantly stored data that is properly indexed in another table, and a link to a correct rule. | 0.501969 |
9,846,731 | 11 | 13 | 11. One or more non-transitory computer-readable storage media comprising stored instructions which, when executed by one or more processors, cause performing a method of matching a plurality of imported data entities to a plurality of existing data entities in a database comprising: receiving first input specifying a first matching criteria that is based at least in part on a first subset of one or more properties of the imported data entities, and specifying a first matching technique to use as part of the first matching criteria; receiving second input specifying a second matching criteria that is different from the first matching criteria and that is based at least in part on a second subset of the one or more properties of the imported data entities, wherein the second subset of the one or more properties is different than the first subset of one or more properties, and specifying a second matching technique that is different than the first matching technique and to use as part of the second matching criteria; receiving third input specifying a particular one of the imported data entities and signaling a request to resolve that particular one of the imported data entities in relation to the existing data entities; matching the particular one of the imported data entities to a first subset of the existing data entities using the first matching criteria and using the first matching technique; matching the particular one of the imported data entities to a second subset of the existing data entities using the second matching criteria and using the second matching technique; causing display of a first result of matching the particular one imported data entity to the first subset of the existing data entities and a second result of matching the particular one imported data entity to the second subset of the existing data entities; receiving, in response to the display, a selection of one or more of continuing resolving the particular one imported data entity, resolving others of the imported data entities, and consolidating the particular one imported data entity into the existing data entities, the consolidating comprising adding at least one value from the particular one imported data entity to one of the first subset of the existing data entities or one of the second subset of the existing data entities; performing further resolution or consolidation based on the selection. | 11. One or more non-transitory computer-readable storage media comprising stored instructions which, when executed by one or more processors, cause performing a method of matching a plurality of imported data entities to a plurality of existing data entities in a database comprising: receiving first input specifying a first matching criteria that is based at least in part on a first subset of one or more properties of the imported data entities, and specifying a first matching technique to use as part of the first matching criteria; receiving second input specifying a second matching criteria that is different from the first matching criteria and that is based at least in part on a second subset of the one or more properties of the imported data entities, wherein the second subset of the one or more properties is different than the first subset of one or more properties, and specifying a second matching technique that is different than the first matching technique and to use as part of the second matching criteria; receiving third input specifying a particular one of the imported data entities and signaling a request to resolve that particular one of the imported data entities in relation to the existing data entities; matching the particular one of the imported data entities to a first subset of the existing data entities using the first matching criteria and using the first matching technique; matching the particular one of the imported data entities to a second subset of the existing data entities using the second matching criteria and using the second matching technique; causing display of a first result of matching the particular one imported data entity to the first subset of the existing data entities and a second result of matching the particular one imported data entity to the second subset of the existing data entities; receiving, in response to the display, a selection of one or more of continuing resolving the particular one imported data entity, resolving others of the imported data entities, and consolidating the particular one imported data entity into the existing data entities, the consolidating comprising adding at least one value from the particular one imported data entity to one of the first subset of the existing data entities or one of the second subset of the existing data entities; performing further resolution or consolidation based on the selection. 13. The one or more non-transitory computer-readable storage media of claim 11 , comprising instructions which when executed cause using the first matching criteria to check for an exact match between the first subset of one or more properties and a first corresponding subset of one or more properties of the existing data entities, and comprising instructions which when executed cause using the second matching criteria to check for an exact match between the second subset of one or more properties and a second corresponding subset of one or more properties of the existing data entities. | 0.534537 |
7,805,390 | 1 | 15 | 1. A computer implemented method for inferring a probability of a first inference relating to an accident, the computer implemented method comprising: receiving a query at a database, on a data processing system, regarding a fact relating to the accident, 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, by a processing unit of the data processing system, wherein the frame of reference is used to determine data to be searched and rules to apply to the query, wherein the fact becomes a compound fact that includes multiple sub-facts on a subsequent iteration of the recursion process; mathematically refocusing the database such that the fact is modeled as a first center of an inverted star schema, and modeling each datum of the plurality of data in the inverted star schema around the fact; applying a first set of rules to the query, by the processing unit, wherein the first set of rules are determined for the query according to a second set of rules, wherein the first set of rules determine how the plurality of data are to be compared to the fact, wherein the first set of rules is prioritized, and wherein the first set of rules determine a first search space of the inverted star schema for the query including the associated metadata and associated key, wherein the second set of rules is a rule set used in a previous iteration of a recursive executing the query, by the processing unit, to create the probability of the first inference, wherein the probability of the first inference is determined from comparing the first search space according to the first set of rules; storing the probability of the first inference by the processing unit in a memory element of the data processing system; establishing the first inference as a second frame of reference, using the first set of rules to determine a third set of rules, wherein the third set of rules is a rule set used in a subsequent iteration of the recursive process; mathematically refocusing the database such that the first inference is modeled as a second center of the inverted star schema, and modeling each datum of the plurality of data in the inverted star schema around the first inference; and applying the third set of rules to create the probability of a second inference, wherein the third set of rules determines a second search space of the inverted star schema for the query including the associated metadata and associated key, wherein the probability of the second inference is determined from comparing the second search space according to the third set of rules; wherein the accident is selected from the group consisting of an airplane accident, a train accident, a maritime accident, a multi-vehicle accident, a single vehicle accident, a nuclear meltdown, a black-out, a building collapse, a failure of a bridge, a failure of a dam, a toxic spill, an explosion, and combinations thereof. | 1. A computer implemented method for inferring a probability of a first inference relating to an accident, the computer implemented method comprising: receiving a query at a database, on a data processing system, regarding a fact relating to the accident, 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, by a processing unit of the data processing system, wherein the frame of reference is used to determine data to be searched and rules to apply to the query, wherein the fact becomes a compound fact that includes multiple sub-facts on a subsequent iteration of the recursion process; mathematically refocusing the database such that the fact is modeled as a first center of an inverted star schema, and modeling each datum of the plurality of data in the inverted star schema around the fact; applying a first set of rules to the query, by the processing unit, wherein the first set of rules are determined for the query according to a second set of rules, wherein the first set of rules determine how the plurality of data are to be compared to the fact, wherein the first set of rules is prioritized, and wherein the first set of rules determine a first search space of the inverted star schema for the query including the associated metadata and associated key, wherein the second set of rules is a rule set used in a previous iteration of a recursive executing the query, by the processing unit, to create the probability of the first inference, wherein the probability of the first inference is determined from comparing the first search space according to the first set of rules; storing the probability of the first inference by the processing unit in a memory element of the data processing system; establishing the first inference as a second frame of reference, using the first set of rules to determine a third set of rules, wherein the third set of rules is a rule set used in a subsequent iteration of the recursive process; mathematically refocusing the database such that the first inference is modeled as a second center of the inverted star schema, and modeling each datum of the plurality of data in the inverted star schema around the first inference; and applying the third set of rules to create the probability of a second inference, wherein the third set of rules determines a second search space of the inverted star schema for the query including the associated metadata and associated key, wherein the probability of the second inference is determined from comparing the second search space according to the third set of rules; wherein the accident is selected from the group consisting of an airplane accident, a train accident, a maritime accident, a multi-vehicle accident, a single vehicle accident, a nuclear meltdown, a black-out, a building collapse, a failure of a bridge, a failure of a dam, a toxic spill, an explosion, and combinations thereof. 15. The computer implemented method of claim 1 wherein the additional data is imported according to a technique selected from a group consisting of federation and extraction, transformation, and loading. | 0.916667 |
8,205,200 | 13 | 14 | 13. The method of claim 1 , wherein the scheduling hint information further comprises: indication of a hot spot. | 13. The method of claim 1 , wherein the scheduling hint information further comprises: indication of a hot spot. 14. The method of claim 13 , wherein said utilizing further comprises: utilizing the scheduling hint information to schedule the user-level thread on a physical sequencer so as to reduce the latency of the user-level thread. | 0.907054 |
9,972,322 | 10 | 14 | 10. A system for performing speaker recognition comprising: a memory configured to store a received audio input; and a digital signal processor coupled to the memory, the digital signal processor to determine a speaker recognition score based on a received audio input, to generate a speech to noise ratio based on the received audio input, to generate a noise type label corresponding to the received audio input, to determine a selected adaptive speaker recognition threshold from a plurality of adaptive speaker recognition thresholds based on the speech to noise ratio, the noise type label, and a target false accept rate corresponding to the received audio input, wherein each of the plurality of adaptive speaker recognition thresholds is associated with a particular noise type label, a particular speech to noise ratio, and a particular target false accept rate, and wherein each of the plurality of adaptive speaker recognition thresholds provides a threshold corresponding to a lowest target false reject rate for the particular noise type label, the particular speech to noise ratio, and the particular target false accept rate, and to perform speaker recognition for the received audio input based on a comparison of the speaker recognition score to the selected adaptive speaker recognition threshold. | 10. A system for performing speaker recognition comprising: a memory configured to store a received audio input; and a digital signal processor coupled to the memory, the digital signal processor to determine a speaker recognition score based on a received audio input, to generate a speech to noise ratio based on the received audio input, to generate a noise type label corresponding to the received audio input, to determine a selected adaptive speaker recognition threshold from a plurality of adaptive speaker recognition thresholds based on the speech to noise ratio, the noise type label, and a target false accept rate corresponding to the received audio input, wherein each of the plurality of adaptive speaker recognition thresholds is associated with a particular noise type label, a particular speech to noise ratio, and a particular target false accept rate, and wherein each of the plurality of adaptive speaker recognition thresholds provides a threshold corresponding to a lowest target false reject rate for the particular noise type label, the particular speech to noise ratio, and the particular target false accept rate, and to perform speaker recognition for the received audio input based on a comparison of the speaker recognition score to the selected adaptive speaker recognition threshold. 14. The system of claim 10 , wherein the digital signal processor to perform speaker recognition comprises the digital signal processor to accept the received audio input as corresponding to a target user when the speaker recognition score exceeds the selected adaptive speaker recognition threshold or to reject the received audio input as corresponding to the target user when the speaker recognition score does not exceed the selected adaptive speaker recognition threshold. | 0.694231 |
5,515,490 | 19 | 23 | 19. A method of temporally formatting a plurality of media items included in a time-dependent document in an information presentation system; the information presentation system including memory for storing data, a processor connected for accessing the data stored in the memory, and a plurality of media presentation devices; the data stored in the memory including instruction data indicating instructions the processor executes; the method comprising: operating the processor to obtain, for each media item, at least one pair of temporally adjacent media item event data items, referred to as a pair of temporally adjacent events, identifying a media item segment; each event in a pair of temporally adjacent events marking a point in time in the respective media item segment such that a second event in the pair of events follows a first event in time with no intervening media item events specified between the pair of temporally adjacent events; each media item segment indicating whether occurrence of the media item segment in the time-dependent document is predictable or unpredictable; operating the processor to obtain a durational time data item, hereafter referred to as a duration, for each respective media item segment; each durational time data item indicating an elapsed time for presentation of the media item segment by a respective one of the media presentation devices; each durational time data item further indicating whether the duration is predictable or unpredictable; each predictable duration including a range of predictable elapsed presentation durations including a minimum duration, an optimum duration, and a maximum duration for presenting the respective media item segment; the optimum duration indicating a durational time value that produces a preferred presentation quality for the respective media item segment when the respective media item segment is presented by a respective one of the media presentation devices for the optimum duration; each predictable duration further indicating flexibility metric data measuring a deviation from the preferred presentation quality of the respective media item segment at each respective duration within the range of durations when the media item segment is presented by the at least one media presentation device for the respective duration; the flexibility metric data indicating a penalty value for adjusting the predictable elapsed presentation duration of a respective media item segment to an adjusted duration different from the optimum duration; operating the processor to obtain temporal constraint data indicating a time ordering relation value specified between first and second temporally related event data items, referred to hereafter as a pair of temporally related events, identified from among the temporally adjacent events; a first one of the temporally related events being an event included in a first media item segment and a second one of the temporally related events being an event included in a second media item segment; operating the processor to identify media item segments indicating a predictable occurrence and a predictable media segment duration as having predictable behavior, and to identify media item segments indicating an unpredictable occurrence or an unpredictable media segment duration as having unpredictable behavior; for each respective media item segment having predictable behavior, operating the processor to assign a document presentation time value to each event included in the respective media item segment; each document presentation time value assigned producing a computed duration within the range of durations indicated for the respective media item segment, and satisfying the temporal constraint data specified between the respective media item segment and a second media item segment; the computed duration being an adjusted duration when document presentation time values cannot be assigned that are consistent with the optimum duration for the respective media item segment and still satisfy the temporal constraint data; the adjusted duration being determined using the flexibility metric data and producing assigned document presentation time values satisfying the temporal constraint data specified between the respective media item segment and a second media item segment while producing a presentation quality that deviates by an acceptable amount from the preferred presentation quality of the respective media item segment, as measured by an acceptably small penalty value indicated by the flexibility metric data; and for each respective media item segment having unpredictable behavior, operating the processor to assign an unresolved document presentation time to a starting event in a media item segment having an unpredictable occurrence, and to assign an unresolved document presentation time assigned to an ending event in a media item segment having an unpredictable duration. | 19. A method of temporally formatting a plurality of media items included in a time-dependent document in an information presentation system; the information presentation system including memory for storing data, a processor connected for accessing the data stored in the memory, and a plurality of media presentation devices; the data stored in the memory including instruction data indicating instructions the processor executes; the method comprising: operating the processor to obtain, for each media item, at least one pair of temporally adjacent media item event data items, referred to as a pair of temporally adjacent events, identifying a media item segment; each event in a pair of temporally adjacent events marking a point in time in the respective media item segment such that a second event in the pair of events follows a first event in time with no intervening media item events specified between the pair of temporally adjacent events; each media item segment indicating whether occurrence of the media item segment in the time-dependent document is predictable or unpredictable; operating the processor to obtain a durational time data item, hereafter referred to as a duration, for each respective media item segment; each durational time data item indicating an elapsed time for presentation of the media item segment by a respective one of the media presentation devices; each durational time data item further indicating whether the duration is predictable or unpredictable; each predictable duration including a range of predictable elapsed presentation durations including a minimum duration, an optimum duration, and a maximum duration for presenting the respective media item segment; the optimum duration indicating a durational time value that produces a preferred presentation quality for the respective media item segment when the respective media item segment is presented by a respective one of the media presentation devices for the optimum duration; each predictable duration further indicating flexibility metric data measuring a deviation from the preferred presentation quality of the respective media item segment at each respective duration within the range of durations when the media item segment is presented by the at least one media presentation device for the respective duration; the flexibility metric data indicating a penalty value for adjusting the predictable elapsed presentation duration of a respective media item segment to an adjusted duration different from the optimum duration; operating the processor to obtain temporal constraint data indicating a time ordering relation value specified between first and second temporally related event data items, referred to hereafter as a pair of temporally related events, identified from among the temporally adjacent events; a first one of the temporally related events being an event included in a first media item segment and a second one of the temporally related events being an event included in a second media item segment; operating the processor to identify media item segments indicating a predictable occurrence and a predictable media segment duration as having predictable behavior, and to identify media item segments indicating an unpredictable occurrence or an unpredictable media segment duration as having unpredictable behavior; for each respective media item segment having predictable behavior, operating the processor to assign a document presentation time value to each event included in the respective media item segment; each document presentation time value assigned producing a computed duration within the range of durations indicated for the respective media item segment, and satisfying the temporal constraint data specified between the respective media item segment and a second media item segment; the computed duration being an adjusted duration when document presentation time values cannot be assigned that are consistent with the optimum duration for the respective media item segment and still satisfy the temporal constraint data; the adjusted duration being determined using the flexibility metric data and producing assigned document presentation time values satisfying the temporal constraint data specified between the respective media item segment and a second media item segment while producing a presentation quality that deviates by an acceptable amount from the preferred presentation quality of the respective media item segment, as measured by an acceptably small penalty value indicated by the flexibility metric data; and for each respective media item segment having unpredictable behavior, operating the processor to assign an unresolved document presentation time to a starting event in a media item segment having an unpredictable occurrence, and to assign an unresolved document presentation time assigned to an ending event in a media item segment having an unpredictable duration. 23. The temporal formatting method of claim 19 wherein the time ordering relation specified between temporally related events specifies a time ordering relation between media item segments included in different media items. | 0.938904 |
8,346,534 | 119 | 124 | 119. The system as recited in claim 94 , wherein the processor further: extracts sense definitions from a sense inventory; and applies at least one disambiguation algorithm to each candidate entry, whereby the most likely sense is determined for each candidate entry. | 119. The system as recited in claim 94 , wherein the processor further: extracts sense definitions from a sense inventory; and applies at least one disambiguation algorithm to each candidate entry, whereby the most likely sense is determined for each candidate entry. 124. The system as recited in claim 119 , wherein the processor further: associates each disambiguated candidate entry with a link to an article in an electronic encyclopedia; and incorporates the entries and links into the electronic document, whereby the electronic document is annotated with links to relevant articles in the electronic encyclopedia. | 0.929681 |
8,725,581 | 1 | 7 | 1. A client device capable of data communication with one or more communication networks, said client device comprising: a data capture apparatus; at least one interface configured to communicate with one or more entities of said one or more communication networks; and a digital processor, said processor having at least one computer program configured to run thereon, said at least one computer program comprising a plurality of instructions which are configured to, when executed: enable a user of said client device to generate a request for information, said request for information comprising at least one element configured to identify at least one item for auction, said at least one element obtained from information scanned or captured via an application configured to run on said client device; transmit said request to said one or more entities of said communication network via said at least one interface; and in response to said request, receive information regarding said at least one item for auction. | 1. A client device capable of data communication with one or more communication networks, said client device comprising: a data capture apparatus; at least one interface configured to communicate with one or more entities of said one or more communication networks; and a digital processor, said processor having at least one computer program configured to run thereon, said at least one computer program comprising a plurality of instructions which are configured to, when executed: enable a user of said client device to generate a request for information, said request for information comprising at least one element configured to identify at least one item for auction, said at least one element obtained from information scanned or captured via an application configured to run on said client device; transmit said request to said one or more entities of said communication network via said at least one interface; and in response to said request, receive information regarding said at least one item for auction. 7. The client device of claim 1 , wherein said information regarding said at least one item for auction comprises information relating to an estimated value of said at least one item for auction. | 0.893791 |
8,938,384 | 11 | 14 | 11. A system for identifying one or more languages in a document, the system comprising: a language model data store configured to store an n-gram based language model for each of a plurality of languages, wherein the plurality of languages belong to a plurality of disjoint subsets, wherein any two languages that are in different disjoint subsets do not overlap with each other; a document information data store configured to store information for each of a plurality of documents, the information including language identifying information indicating one or more languages associated with the document; and a processor coupled to the language model data store and the document information data store, the processor being configured to execute language identification processes, the language identification processes including: a first process that, when executed, segments a test document into one or more segments of consecutive characters, wherein each segment contains n-grams that have greater than a default probability of occurrence only for languages in a same one of the plurality of disjoint subsets, and further generates a set of segment scores for the test document, wherein the set of segment scores includes a score for each one of the segments scored against each one of the language models in the one of the plurality of disjoint subsets applicable to that segment; and a second process that, when executed, identifies one or more of the plurality of languages as being languages of the documents based on the set of segment scores. | 11. A system for identifying one or more languages in a document, the system comprising: a language model data store configured to store an n-gram based language model for each of a plurality of languages, wherein the plurality of languages belong to a plurality of disjoint subsets, wherein any two languages that are in different disjoint subsets do not overlap with each other; a document information data store configured to store information for each of a plurality of documents, the information including language identifying information indicating one or more languages associated with the document; and a processor coupled to the language model data store and the document information data store, the processor being configured to execute language identification processes, the language identification processes including: a first process that, when executed, segments a test document into one or more segments of consecutive characters, wherein each segment contains n-grams that have greater than a default probability of occurrence only for languages in a same one of the plurality of disjoint subsets, and further generates a set of segment scores for the test document, wherein the set of segment scores includes a score for each one of the segments scored against each one of the language models in the one of the plurality of disjoint subsets applicable to that segment; and a second process that, when executed, identifies one or more of the plurality of languages as being languages of the documents based on the set of segment scores. 14. The system of claim 11 wherein the processor is further configured to execute a first process that, when executed, defines the plurality of disjoint subsets based on the n-gram based language models stored in the language model data store. | 0.821324 |
9,530,097 | 8 | 9 | 8. The system of claim 1 , further comprising a preferencing module configured to modify said profile to impose a viewing preference upon any use of said profile based upon a preference user input received by said user interface module. | 8. The system of claim 1 , further comprising a preferencing module configured to modify said profile to impose a viewing preference upon any use of said profile based upon a preference user input received by said user interface module. 9. The system of claim 8 , wherein said viewing preference is selected from the group of: a ranking preference, a quantity preference, a content preference, and a filtering preference. | 0.931902 |
8,433,718 | 29 | 31 | 29. The system according to claim 23 , wherein the text string is translated so that the translated text string is compatible with a given function utilized to obtain the content in the first language. | 29. The system according to claim 23 , wherein the text string is translated so that the translated text string is compatible with a given function utilized to obtain the content in the first language. 31. The system according to claim 29 , wherein the text string is translated by at least one of human translation and machine translation. | 0.95 |
7,962,507 | 1 | 2 | 1. A method for web mining at least one couplet part, the method comprising: parsing, by a computer, a search result resulting from a query based on a search term comprising a first part of a couplet comprising the first part and a second part, wherein each of the first part and the second part include at least one character or word, and wherein the parsing results in a snippet set wherein each snippet in the set comprises at least one returned character or word that matches the query; filtering, by the computer, the resulting snippet set, wherein the filtering results in at least one candidate couplet part; and generating, by the computer, at least one output couplet part, wherein the generating comprises classifying, by a support vector machine classifier, the at least one candidate couplet part, wherein the at least one couplet part comprises the generated at least one output couplet part. | 1. A method for web mining at least one couplet part, the method comprising: parsing, by a computer, a search result resulting from a query based on a search term comprising a first part of a couplet comprising the first part and a second part, wherein each of the first part and the second part include at least one character or word, and wherein the parsing results in a snippet set wherein each snippet in the set comprises at least one returned character or word that matches the query; filtering, by the computer, the resulting snippet set, wherein the filtering results in at least one candidate couplet part; and generating, by the computer, at least one output couplet part, wherein the generating comprises classifying, by a support vector machine classifier, the at least one candidate couplet part, wherein the at least one couplet part comprises the generated at least one output couplet part. 2. The method as recited in claim 1 wherein the search result is obtained by processing the search term using a search engine. | 0.802508 |
10,031,940 | 4 | 5 | 4. The method of claim 1 , further comprising determining whether initialization of the runtime plan tree is complete. | 4. The method of claim 1 , further comprising determining whether initialization of the runtime plan tree is complete. 5. The method of claim 4 , further comprising performing runtime execution upon determining that the initialization of the runtime plan tree is complete. | 0.964286 |
10,019,515 | 1 | 9 | 1. A method, comprising: obtaining a set of content items; generating a set of clauses from the set of content items; generating a set of n-grams from the set of clauses; using the set of n-grams to automatically extract a set of topics from the set of clauses in the set of content items; for each topic in the set of topics: automatically extracting, by one or more computer systems, a set of attributes that provides a context for the topic from a subset of the content items containing the topic, wherein the set of attributes is extracted as a set of words in a vicinity of the topic contained in each clause in the set of clauses; obtaining a refined set of attributes by removing from the set of attributes one or more high-frequency words that appear in the set of n-grams; using the refined set of attributes to obtain a set of sentiments associated with the topic; and aggregating the set of sentiments into a sentiment distribution for the topic; and displaying, by the one or more computer systems, the refined set of attributes in the context of the topic and the sentiment distribution for the topic to improve understanding of the set of content items by the user without requiring the user to manually analyze the set of content items. | 1. A method, comprising: obtaining a set of content items; generating a set of clauses from the set of content items; generating a set of n-grams from the set of clauses; using the set of n-grams to automatically extract a set of topics from the set of clauses in the set of content items; for each topic in the set of topics: automatically extracting, by one or more computer systems, a set of attributes that provides a context for the topic from a subset of the content items containing the topic, wherein the set of attributes is extracted as a set of words in a vicinity of the topic contained in each clause in the set of clauses; obtaining a refined set of attributes by removing from the set of attributes one or more high-frequency words that appear in the set of n-grams; using the refined set of attributes to obtain a set of sentiments associated with the topic; and aggregating the set of sentiments into a sentiment distribution for the topic; and displaying, by the one or more computer systems, the refined set of attributes in the context of the topic and the sentiment distribution for the topic to improve understanding of the set of content items by the user without requiring the user to manually analyze the set of content items. 9. The method of claim 1 , wherein the set of content items comprises unstructured data. | 0.92 |
9,535,963 | 1 | 4 | 1. A computer-system-implemented method for requesting desired information from a graph database storing a graph, the method comprising: receiving an initial query that is compatible with a first type of database that is different from the graph database; converting the initial query into a query using primitives, wherein the primitives comprise: a rule, based on edges in the graph, that expresses a relational schema in the first type of database, and information associated with a compound key that specifies a relationship between nodes, edges and predicates in the graph corresponding to a table in the first type of database; executing the query against the graph database, wherein: the graph comprises nodes, edges between the nodes, and predicates to represent and store data with index-free adjacency; and the query identifies a first edge associated with a predicate that specifies one or more of the nodes in the graph; and receiving a result in response to the query, wherein the result includes a subset of the graph. | 1. A computer-system-implemented method for requesting desired information from a graph database storing a graph, the method comprising: receiving an initial query that is compatible with a first type of database that is different from the graph database; converting the initial query into a query using primitives, wherein the primitives comprise: a rule, based on edges in the graph, that expresses a relational schema in the first type of database, and information associated with a compound key that specifies a relationship between nodes, edges and predicates in the graph corresponding to a table in the first type of database; executing the query against the graph database, wherein: the graph comprises nodes, edges between the nodes, and predicates to represent and store data with index-free adjacency; and the query identifies a first edge associated with a predicate that specifies one or more of the nodes in the graph; and receiving a result in response to the query, wherein the result includes a subset of the graph. 4. The method of claim 1 , wherein the type of database includes one of: a relational database, and a hierarchical database. | 0.879845 |
10,095,735 | 3 | 4 | 3. The system of claim 1 , wherein the receiving of the result comprises to: determine a formatted result for the result. | 3. The system of claim 1 , wherein the receiving of the result comprises to: determine a formatted result for the result. 4. The system of claim 3 , wherein the receiving of the result comprises to: provide the formatted result. | 0.965674 |
10,108,619 | 1 | 13 | 1. A method comprising: accessing seed metadata, the seed metadata describing a seed, the seed being a basis on which a station library is to be defined; generating a station descriptor profile based on the seed metadata, the station descriptor profile defining a genre composition of the station library; generating a candidate set based on the seed metadata, the candidate set comprising a plurality of candidate media files; for each candidate media file in the candidate set: computing a similarity score associated with the candidate media file, the similarity score including a measure of similarity between the candidate media file and the station descriptor profile; computing one or more boost values associated with the candidate media file based on candidate metadata describing the candidate media file; and computing a relevancy score associated with the candidate media file based on the similarity score and the one or more boost values associated with the candidate media file, the relevancy score providing a basis for selecting the candidate media file for inclusion in the station library; and machine-generating a station set including a portion of the candidate set selected based on the relevancy scores associated with the plurality of candidate media files included in the candidate set, the machine-generated station set defining the station library by referencing each candidate media file in the portion of the candidate set, wherein the station descriptor profile includes one or more focus genre profiles and each candidate media file includes a file genre profile, the one or more focus genre profiles and the file genre profile each including respective multiple genre values and a weight assigned to each genre value, each genre value corresponding to a genre, each weight indicating a percentage of the corresponding genre value relative to the other genre values in the respective multiple genre values, and computing the similarity score associated with the candidate media file includes: computing one or more focus-level similarity scores by comparing, for each focus genre profile in the station descriptor profile: (a) the respective multiple genre values and the corresponding weights of the focus genre profile, and (b) the respective multiple genre values and the corresponding weights of the file genre profile of the candidate media file; and selecting the highest focus-level similarity score to be the similarity score associated with the candidate media file. | 1. A method comprising: accessing seed metadata, the seed metadata describing a seed, the seed being a basis on which a station library is to be defined; generating a station descriptor profile based on the seed metadata, the station descriptor profile defining a genre composition of the station library; generating a candidate set based on the seed metadata, the candidate set comprising a plurality of candidate media files; for each candidate media file in the candidate set: computing a similarity score associated with the candidate media file, the similarity score including a measure of similarity between the candidate media file and the station descriptor profile; computing one or more boost values associated with the candidate media file based on candidate metadata describing the candidate media file; and computing a relevancy score associated with the candidate media file based on the similarity score and the one or more boost values associated with the candidate media file, the relevancy score providing a basis for selecting the candidate media file for inclusion in the station library; and machine-generating a station set including a portion of the candidate set selected based on the relevancy scores associated with the plurality of candidate media files included in the candidate set, the machine-generated station set defining the station library by referencing each candidate media file in the portion of the candidate set, wherein the station descriptor profile includes one or more focus genre profiles and each candidate media file includes a file genre profile, the one or more focus genre profiles and the file genre profile each including respective multiple genre values and a weight assigned to each genre value, each genre value corresponding to a genre, each weight indicating a percentage of the corresponding genre value relative to the other genre values in the respective multiple genre values, and computing the similarity score associated with the candidate media file includes: computing one or more focus-level similarity scores by comparing, for each focus genre profile in the station descriptor profile: (a) the respective multiple genre values and the corresponding weights of the focus genre profile, and (b) the respective multiple genre values and the corresponding weights of the file genre profile of the candidate media file; and selecting the highest focus-level similarity score to be the similarity score associated with the candidate media file. 13. The method of claim 1 , further comprising: creating a seed artist set, the seed artist set including a plurality of media files corresponding to an artist associated with the seed; and incorporating the seed artist set into the station set. | 0.699017 |
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