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8,272,009 | 38 | 40 | 38. A system that delivers content to users of a broadcast network, said broadcast network primarily involving synchronized distribution of content to multiple users, said system comprising: a first network interface for receiving a content stream and assets from a broadcast network, each of the assets having associated targeting criteria, the first network interface having a processor for: monitoring textual information associated with programming received via the network interface; determining a subset of the assets by comparing said textual information with textual constraints associated with the assets to determine a goodness of fit value for each of the assets, such that the subset of assets has the highest respective goodness of fit values; and a second network interface disposed downstream in the broadcast network from the first network interface and configured for: receiving the subset of assets for presentation in conjunction with said programming from said first network interface; selecting one of the subset of assets for a predetermined asset delivery spot as a function of its respective targeting criteria; and inserting the selected one of the identified assets into the content stream of the broadcast network for distribution to a user of the broadcast network. | 38. A system that delivers content to users of a broadcast network, said broadcast network primarily involving synchronized distribution of content to multiple users, said system comprising: a first network interface for receiving a content stream and assets from a broadcast network, each of the assets having associated targeting criteria, the first network interface having a processor for: monitoring textual information associated with programming received via the network interface; determining a subset of the assets by comparing said textual information with textual constraints associated with the assets to determine a goodness of fit value for each of the assets, such that the subset of assets has the highest respective goodness of fit values; and a second network interface disposed downstream in the broadcast network from the first network interface and configured for: receiving the subset of assets for presentation in conjunction with said programming from said first network interface; selecting one of the subset of assets for a predetermined asset delivery spot as a function of its respective targeting criteria; and inserting the selected one of the identified assets into the content stream of the broadcast network for distribution to a user of the broadcast network. 40. The system of claim 38 , wherein the processor further comprises: a storage medium for storing logic instructions for use in comparing said textual information with said textual constraints. | 0.780543 |
9,805,292 | 15 | 20 | 15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a mobile device that includes a camera and a display, data identifying a selected image acquisition template associated with a particular type of object, from among multiple image acquisition templates that are stored on the multiple device and that are each associated with a different type of object; providing a pattern associated with the selected image acquisition template for output on the display; generating, by the camera included on the mobile device, a query image while the pattern associated with the selected image acquisition template is provided for output on the display; providing, to a search engine, an image search query that includes (i) the query image, and (ii) an indication of the selected image acquisition template; and receiving, from the search engine, one or more image search results in response to the image search query. | 15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving, by a mobile device that includes a camera and a display, data identifying a selected image acquisition template associated with a particular type of object, from among multiple image acquisition templates that are stored on the multiple device and that are each associated with a different type of object; providing a pattern associated with the selected image acquisition template for output on the display; generating, by the camera included on the mobile device, a query image while the pattern associated with the selected image acquisition template is provided for output on the display; providing, to a search engine, an image search query that includes (i) the query image, and (ii) an indication of the selected image acquisition template; and receiving, from the search engine, one or more image search results in response to the image search query. 20. The computer-readable medium of claim 15 , wherein the operations further comprise: detecting, at the mobile device, an inappropriate alignment between a general shape of the particular type of the object and the pattern associated with the selected image acquisition template. | 0.667849 |
9,560,150 | 7 | 9 | 7. The computer-implemented method of claim 1 , wherein each candidate social endorsement comprises text associated with a user of the social networking system. | 7. The computer-implemented method of claim 1 , wherein each candidate social endorsement comprises text associated with a user of the social networking system. 9. The computer-implemented method of claim 7 , wherein the text associated with a user comprises a nickname or partial name of the user. | 0.549342 |
9,703,769 | 7 | 10 | 7. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: inserting, via a discriminative classification approach, boundary tags into speech utterance text, the boundary tags identifying boundaries selected from a group comprising phrase boundaries, sentence boundaries, and paragraph boundaries, wherein the discriminative classification approach utilizes syntactic features before and after each word being tagged, to yield boundary marked speech utterance text and unedited text; identifying a coordinating conjunction within the unedited text based on a conjunction tag, wherein the conjunction tag comprises conjunction span information indicating how many words to the left of the conjunction tag a corresponding conjunction includes; and identifying clauses in the speech utterance text based on the boundary marked speech utterance text and the coordinating conjunction. | 7. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: inserting, via a discriminative classification approach, boundary tags into speech utterance text, the boundary tags identifying boundaries selected from a group comprising phrase boundaries, sentence boundaries, and paragraph boundaries, wherein the discriminative classification approach utilizes syntactic features before and after each word being tagged, to yield boundary marked speech utterance text and unedited text; identifying a coordinating conjunction within the unedited text based on a conjunction tag, wherein the conjunction tag comprises conjunction span information indicating how many words to the left of the conjunction tag a corresponding conjunction includes; and identifying clauses in the speech utterance text based on the boundary marked speech utterance text and the coordinating conjunction. 10. The system of claim 7 , wherein a different classifier performs each step of the operations. | 0.853659 |
8,762,318 | 25 | 26 | 25. The non-transitory computer-readable medium of claim 21 , the trained model comprising a long-term cluster membership vector, the instructions to generate a short-term cluster membership vector further comprising instructions to: combine the long-term cluster membership vector with the short-term cluster membership vector to form the short-term cluster membership vector. | 25. The non-transitory computer-readable medium of claim 21 , the trained model comprising a long-term cluster membership vector, the instructions to generate a short-term cluster membership vector further comprising instructions to: combine the long-term cluster membership vector with the short-term cluster membership vector to form the short-term cluster membership vector. 26. The non-transitory computer-readable medium of claim 25 , the instructions to combine the long-term cluster membership vector with the short-term cluster membership vector further comprising instructions to: generate a weighted long-term cluster membership vector by applying a first weight to the long-term cluster membership vector; generate a weighted short-term cluster membership vector by applying a second weight to the short-term cluster membership vector; and combine the weighted long-term cluster membership vector with the weighted short-term cluster membership vector to form the short-term cluster membership vector. | 0.5 |
9,232,059 | 19 | 20 | 19. The non-transitory computer readable storage medium of claim 15 , wherein the processor is further configured to perform: receiving a subsequent spoken call response from the user after the spoken call greeting including the at least one additional utterance; and determining whether the spoken call response is indicative of a language preference based on content of the at least one additional utterance. | 19. The non-transitory computer readable storage medium of claim 15 , wherein the processor is further configured to perform: receiving a subsequent spoken call response from the user after the spoken call greeting including the at least one additional utterance; and determining whether the spoken call response is indicative of a language preference based on content of the at least one additional utterance. 20. The non-transitory computer readable storage medium of claim 19 , wherein the processor is further configured to perform if the determining whether the spoken call response is indicative of a language preference yields that the spoken call response is indicative of a language preference, then assigning a language preference to the user based on the indicative language preference. | 0.5 |
9,824,689 | 12 | 17 | 12. A method, comprising: receiving an audio input from a user; processing the audio input to recognize at least one voice command from the audio input; determining whether the at least one voice command is valid; processing the at least one voice command when the at least one voice command is determined to be valid, further comprising: determining whether the at least one voice command includes a safety-critical command; presenting a preview of the at least one voice command when the at least one voice command includes a safety-critical command; and executing the at least one voice command only after receiving an explicit confirmation from the user when the at least one voice command includes a safety-critical command. | 12. A method, comprising: receiving an audio input from a user; processing the audio input to recognize at least one voice command from the audio input; determining whether the at least one voice command is valid; processing the at least one voice command when the at least one voice command is determined to be valid, further comprising: determining whether the at least one voice command includes a safety-critical command; presenting a preview of the at least one voice command when the at least one voice command includes a safety-critical command; and executing the at least one voice command only after receiving an explicit confirmation from the user when the at least one voice command includes a safety-critical command. 17. The method of claim 12 , further comprising: providing an audible feedback to the user regarding processing status of the at least one voice command. | 0.712406 |
7,733,347 | 12 | 16 | 12. A tangible computer-readable medium storing computer-executable instructions for causing a computer to perform a method, the method comprising: receiving at least one first parallel processing request at a parallel programming interface, the at least one first parallel processing request comprising at least one evaluation request of one or more parallel operations on one or more input arrays; building an expression graph in response to receiving the at least one first parallel processing request at the parallel programming interface, the expression graph comprising nodes representing the one or more parallel operations; and evaluating the one or more parallel operations in response to determining that a second parallel processing request received at the parallel programming interface subsequent to receiving the at least one first parallel processing request at the parallel programming interface requires evaluation of at least one of the one or more parallel operations, the determining occurring in response to receiving the second parallel processing request at the parallel programming interface, the evaluation comprising: constructing one or more shader programs formed according to resource constraints of a graphics environment; the constructing comprising at least one of: responsive to determining that a path of nodes of parallel operations through the expression graph comprises multiple texture coordinate operations, inserting a first shader break annotation in the determined path; responsive to determining that appending shader code of a first child node to a parent node of the first child node will exceed a resource constraint of the graphics environment, inserting a second shader break annotation in the expression graph; and breaking a second child node into a separate shader program, responsive to identifying an output texture from the second child node with a size constraint inconsistent with an input texture of a parent node of the second child node; invoking the one or more shader programs on a graphics processor; and returning an output of the one or more shader programs invoked on the graphics processor; and wherein the at least one first parallel processing request and the second parallel processing request are received from an application program executing on a computer system. | 12. A tangible computer-readable medium storing computer-executable instructions for causing a computer to perform a method, the method comprising: receiving at least one first parallel processing request at a parallel programming interface, the at least one first parallel processing request comprising at least one evaluation request of one or more parallel operations on one or more input arrays; building an expression graph in response to receiving the at least one first parallel processing request at the parallel programming interface, the expression graph comprising nodes representing the one or more parallel operations; and evaluating the one or more parallel operations in response to determining that a second parallel processing request received at the parallel programming interface subsequent to receiving the at least one first parallel processing request at the parallel programming interface requires evaluation of at least one of the one or more parallel operations, the determining occurring in response to receiving the second parallel processing request at the parallel programming interface, the evaluation comprising: constructing one or more shader programs formed according to resource constraints of a graphics environment; the constructing comprising at least one of: responsive to determining that a path of nodes of parallel operations through the expression graph comprises multiple texture coordinate operations, inserting a first shader break annotation in the determined path; responsive to determining that appending shader code of a first child node to a parent node of the first child node will exceed a resource constraint of the graphics environment, inserting a second shader break annotation in the expression graph; and breaking a second child node into a separate shader program, responsive to identifying an output texture from the second child node with a size constraint inconsistent with an input texture of a parent node of the second child node; invoking the one or more shader programs on a graphics processor; and returning an output of the one or more shader programs invoked on the graphics processor; and wherein the at least one first parallel processing request and the second parallel processing request are received from an application program executing on a computer system. 16. The tangible computer-readable medium of claim 12 , wherein the resource constraints of the graphics environment comprise a constraint on the number of temporary registers in a shader program. | 0.521951 |
8,943,481 | 24 | 31 | 24. An apparatus for simplifying user interface binding specifications provided to a computer program comprising: means for obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; means for performing a first transformation of the schema to generate the first set of rules for interpretation of the binding specifications in the first grammar level; means for performing a second transformation of the framework to generate a first presentation style for the first grammar level; means for obtaining binding specifications in the first grammar level, the binding specification conforming to the first set of rules; means for applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application. | 24. An apparatus for simplifying user interface binding specifications provided to a computer program comprising: means for obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; means for performing a first transformation of the schema to generate the first set of rules for interpretation of the binding specifications in the first grammar level; means for performing a second transformation of the framework to generate a first presentation style for the first grammar level; means for obtaining binding specifications in the first grammar level, the binding specification conforming to the first set of rules; means for applying the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application. 31. The apparatus of claim 24 , further comprising: means for passing the output binding specifications as input to the user interface application. | 0.789398 |
7,870,113 | 1 | 11 | 1. A method for retrieving data from a database corresponding to a search term comprising: organizing the data, based on relationships among the data, into a network including at least one predecessor group and a plurality of descendant groups; locating an occurrence of the search term in one of said plurality of descendant groups; traversing said network from said occurrence in said one of said plurality of descendant groups to related data in said at least one predecessor group using said relationships among the data; building a context including said occurrence and said related data; and retrieving the context from the database thereby retrieving data from the database corresponding to the search term. | 1. A method for retrieving data from a database corresponding to a search term comprising: organizing the data, based on relationships among the data, into a network including at least one predecessor group and a plurality of descendant groups; locating an occurrence of the search term in one of said plurality of descendant groups; traversing said network from said occurrence in said one of said plurality of descendant groups to related data in said at least one predecessor group using said relationships among the data; building a context including said occurrence and said related data; and retrieving the context from the database thereby retrieving data from the database corresponding to the search term. 11. The method of claim 1 , further comprises storing said context as a subset of the database. | 0.850158 |
10,002,182 | 17 | 19 | 17. The system according to claim 12 wherein the subset of keywords includes at most a predetermined maximum number of keywords. | 17. The system according to claim 12 wherein the subset of keywords includes at most a predetermined maximum number of keywords. 19. The system according to claim 17 wherein the subset of keywords includes less than the predetermined maximum number of keywords based at least in part on a predetermined computational criterion establishing theme name quality sufficiency being satisfied. | 0.5 |
7,478,048 | 7 | 8 | 7. A system for creating voice XML file automatically, comprising: a graphic user interface (GUI) for defining a plurality of first and second icons based on network user input, wherein each of said first icons corresponds to one or more attributes of voice XML, and wherein at least one second icon corresponds to a hyperlink to a linkable voice XML file and for receiving user input to edit a content stream displayed in said GUI to customize audio output of said content stream and to add one or more hyperlinks to one or more linkable voice XML files; a voice XML tag generator for interpreting said action stream based on a library of voice XML tags and generating the corresponding voice XML tags for said content; and a voice XML file generator for creating the voice XML file by combining the content stream to be played with the tags generated by the voice XML tag generator according to voice XML syntax including at least one hyperlink to a linkable voice XML file, wherein, upon listener hyperlink input to the generated voice XML file, audio accessed through said hyperlink is automatically delivered to said listener. | 7. A system for creating voice XML file automatically, comprising: a graphic user interface (GUI) for defining a plurality of first and second icons based on network user input, wherein each of said first icons corresponds to one or more attributes of voice XML, and wherein at least one second icon corresponds to a hyperlink to a linkable voice XML file and for receiving user input to edit a content stream displayed in said GUI to customize audio output of said content stream and to add one or more hyperlinks to one or more linkable voice XML files; a voice XML tag generator for interpreting said action stream based on a library of voice XML tags and generating the corresponding voice XML tags for said content; and a voice XML file generator for creating the voice XML file by combining the content stream to be played with the tags generated by the voice XML tag generator according to voice XML syntax including at least one hyperlink to a linkable voice XML file, wherein, upon listener hyperlink input to the generated voice XML file, audio accessed through said hyperlink is automatically delivered to said listener. 8. A system according to claim 7 , wherein said receiving user selection input to add one or more hyperlinks comprises adding the hyperlinks to a content stream comprising a TTS voice XML stream by the steps of the user editing the TTS voice XML file in the edit area of said graphic user interface, marking or typing the parts to be added the hyperlinks, invoking the corresponding icons and typing the corresponding hyperlink addresses. | 0.70604 |
8,996,568 | 1 | 10 | 1. A method of searching in an overlay network, comprising: receiving a query at a first node in a distributed network from a querying node, wherein the query includes a first keyword and a second keyword; finding a first set of a first number of documents that contain the first keyword; computing an optimal first Bloom filter length and a corresponding first number of hash functions as a function of the first number of documents in the first set; determining a second node responsible for finding a set of documents that contain the second keyword based on a hashed second keyword; generating a Bloom filter of the first set comprising an array having the first Bloom filter length and the first number of hash functions; sending the first Bloom filter of the first set to the second node in the distributed network to generate a result for the searching; returning, by the first node, documents consisting of the first set of documents to the querying node; finding, at the second node, a second set of a second number of documents that contain the second keyword; checking, at the second node, a membership of each of the documents in the second set over the first Bloom filter to determine a third set of documents that contain the second keyword and are not already present in the first Bloom filter; and returning, by second node, documents consisting of the third set of documents to the querying node. | 1. A method of searching in an overlay network, comprising: receiving a query at a first node in a distributed network from a querying node, wherein the query includes a first keyword and a second keyword; finding a first set of a first number of documents that contain the first keyword; computing an optimal first Bloom filter length and a corresponding first number of hash functions as a function of the first number of documents in the first set; determining a second node responsible for finding a set of documents that contain the second keyword based on a hashed second keyword; generating a Bloom filter of the first set comprising an array having the first Bloom filter length and the first number of hash functions; sending the first Bloom filter of the first set to the second node in the distributed network to generate a result for the searching; returning, by the first node, documents consisting of the first set of documents to the querying node; finding, at the second node, a second set of a second number of documents that contain the second keyword; checking, at the second node, a membership of each of the documents in the second set over the first Bloom filter to determine a third set of documents that contain the second keyword and are not already present in the first Bloom filter; and returning, by second node, documents consisting of the third set of documents to the querying node. 10. The method of claim 1 , further comprising determining a condition for using or not using first the Bloom filter for processing queries, wherein the condition comprises when a size of each set, |Dj|, are known apriori, where 1≦j≦q, and where q represents all keywords in the query. | 0.7 |
8,856,114 | 11 | 17 | 11. A method, implemented at least in part via a processing unit, for providing a ranking of results to a search-based query, comprising: determining a first user profile for a first user type for the search-based query and a second user profile for a second user type for the search-based query; identifying a first set of results for the first user type for the search-based query based on a number of results utilized by the first user type; identifying a second set of results for the second user type for the search-based query based on a number of results utilized by the second user type; determining a vector representing a probability distribution for a user type, the probability distribution based on a proportion of one or more users of the user type in a population of users associated with the search-based query; and determining a ranking of results based on the vector, comprising: selecting a result from at least one of the first or second sets of results to be associated with a first rank of results for the search-based query; and selecting a result from at least one of the first or second sets of results to be associated with a second rank of results for the search-based query. | 11. A method, implemented at least in part via a processing unit, for providing a ranking of results to a search-based query, comprising: determining a first user profile for a first user type for the search-based query and a second user profile for a second user type for the search-based query; identifying a first set of results for the first user type for the search-based query based on a number of results utilized by the first user type; identifying a second set of results for the second user type for the search-based query based on a number of results utilized by the second user type; determining a vector representing a probability distribution for a user type, the probability distribution based on a proportion of one or more users of the user type in a population of users associated with the search-based query; and determining a ranking of results based on the vector, comprising: selecting a result from at least one of the first or second sets of results to be associated with a first rank of results for the search-based query; and selecting a result from at least one of the first or second sets of results to be associated with a second rank of results for the search-based query. 17. The method of claim 11 , at least one of the first vector or the second vector comprising two or more values. | 0.808475 |
9,171,265 | 4 | 16 | 4. A method comprising: under control of one or more computing systems configured with executable instructions, training a classifier to categorize individual ones of multiple resumes into one of multiple classes, the training of the classifier producing a trained classifier; publishing a request to a pool of human workers via a crowdsourcing electronic marketplace to request the pool of human workers to locate resumes for categorization using the trained classifier and to provide contact information of candidates associated with the resumes, wherein the candidates are not included in the pool of human workers; receiving, based at least in part on the request, a resume of a candidate from a human worker of the pool of human workers; and categorizing, using the trained classier, the resume into one of the multiple classes based at least in part on the contact information of the candidate being received from the human worker, and wherein the trained classifier applies predetermined criteria to classify the resume. | 4. A method comprising: under control of one or more computing systems configured with executable instructions, training a classifier to categorize individual ones of multiple resumes into one of multiple classes, the training of the classifier producing a trained classifier; publishing a request to a pool of human workers via a crowdsourcing electronic marketplace to request the pool of human workers to locate resumes for categorization using the trained classifier and to provide contact information of candidates associated with the resumes, wherein the candidates are not included in the pool of human workers; receiving, based at least in part on the request, a resume of a candidate from a human worker of the pool of human workers; and categorizing, using the trained classier, the resume into one of the multiple classes based at least in part on the contact information of the candidate being received from the human worker, and wherein the trained classifier applies predetermined criteria to classify the resume. 16. A method as recited in claim 4 , wherein the classifier comprises a naïve Bayes classifier. | 0.930147 |
8,060,366 | 7 | 8 | 7. A computer-readable medium having computer-executable instructions for execution by a processing system, the computer-executable instructions for providing verbal control of a conference call in a conferencing system, the computer-readable medium comprising instructions for: bridging a plurality of conference call legs to form a bridged conference stream; evaluating the bridged conference stream with a speech recognition algorithm; determining if a hot word is identified in the bridged conference stream, wherein at least a caller name is used to populate a voice template for identifying the first hot word; responsive to determining the hot word is in the bridged conference stream, identifying a speaker of the hot word; and suppressing the hot word in the bridged stream prior to transmission of the bridged stream to conference participants. | 7. A computer-readable medium having computer-executable instructions for execution by a processing system, the computer-executable instructions for providing verbal control of a conference call in a conferencing system, the computer-readable medium comprising instructions for: bridging a plurality of conference call legs to form a bridged conference stream; evaluating the bridged conference stream with a speech recognition algorithm; determining if a hot word is identified in the bridged conference stream, wherein at least a caller name is used to populate a voice template for identifying the first hot word; responsive to determining the hot word is in the bridged conference stream, identifying a speaker of the hot word; and suppressing the hot word in the bridged stream prior to transmission of the bridged stream to conference participants. 8. The computer-readable medium of claim 7 , further comprising instructions for determining whether the speaker is authorized to invoke a conference feature associated with the hot word. | 0.692434 |
9,117,455 | 5 | 6 | 5. The system of claim 4 , further comprising a mapping module configured to map the coefficients to line spectral pairs. | 5. The system of claim 4 , further comprising a mapping module configured to map the coefficients to line spectral pairs. 6. The system of claim 5 , further comprising modifying the line spectral pairs using a modulation factor to increase gain in the spectral representation corresponding to the formant frequencies. | 0.5 |
8,510,321 | 1 | 7 | 1. An apparatus for accessing and managing a relational database, said apparatus comprising: a processor; an arrangement for querying a relational database; and an arrangement for accessing semantically relevant query results from the relational database, said accessing arrangement configured to: access at least one ontology; extract domain knowledge from at least one ontology; and employ the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein said accessing arrangement acts to: apply a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and rank results obtained through the query generalization strategy based on a number generalizations performed. | 1. An apparatus for accessing and managing a relational database, said apparatus comprising: a processor; an arrangement for querying a relational database; and an arrangement for accessing semantically relevant query results from the relational database, said accessing arrangement configured to: access at least one ontology; extract domain knowledge from at least one ontology; and employ the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein said accessing arrangement acts to: apply a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and rank results obtained through the query generalization strategy based on a number generalizations performed. 7. The apparatus according to claim 1 , wherein said accessing arrangement comprises a description logic reasoner configured to obtain the inferred results based on domain knowledge in the at least one ontology and data listed in the relational database, the description logic reasoner allowing for inferring query results not explicitly stated in the relational database. | 0.5 |
7,742,048 | 15 | 16 | 15. The computer-readable storage medium of claim 14 , wherein the list of actions comprises a dropdown menu having at least one menu item corresponding to the list of actions that may be performed on the number to convert the number to a number expressed as text in one of a plurality of languages. | 15. The computer-readable storage medium of claim 14 , wherein the list of actions comprises a dropdown menu having at least one menu item corresponding to the list of actions that may be performed on the number to convert the number to a number expressed as text in one of a plurality of languages. 16. The computer-readable storage medium of claim 15 , wherein the set of instructions further comprising: determining a current user interface language setting for the application program; and generating the menu items of the dropdown menu in a language specified by the current user interface language setting. | 0.5 |
7,970,826 | 1 | 2 | 1. At least one non-transitory computer-readable medium storing a computer language, said computer language comprising: (a) a plurality of defined document type descriptions, each document type description specifying a type of document within a common document structure that can be used; (b) a set of defined interactions describing respective document exchanges, each interaction specifying any expected inbound document types and any resulting outbound document types; (c) a set of transformations for use in connection with the defined interactions, each transformation specifying how to convert one document type in the common document structure to another document type, also in the common document structure, together with instructions for applying said transformations to compensate for mismatches between documents actually received and expected inbound document types, wherein each of at least some of the interactions has a transformation sub-element to describe a corresponding one of the transformations; and (d) a transition structure that maps all permissible flows for a given conversation by identifying interactions from the set of defined interactions and specifying transitions between the identified interactions, wherein each of (a)-(d) is a separately defined component of said computer language. | 1. At least one non-transitory computer-readable medium storing a computer language, said computer language comprising: (a) a plurality of defined document type descriptions, each document type description specifying a type of document within a common document structure that can be used; (b) a set of defined interactions describing respective document exchanges, each interaction specifying any expected inbound document types and any resulting outbound document types; (c) a set of transformations for use in connection with the defined interactions, each transformation specifying how to convert one document type in the common document structure to another document type, also in the common document structure, together with instructions for applying said transformations to compensate for mismatches between documents actually received and expected inbound document types, wherein each of at least some of the interactions has a transformation sub-element to describe a corresponding one of the transformations; and (d) a transition structure that maps all permissible flows for a given conversation by identifying interactions from the set of defined interactions and specifying transitions between the identified interactions, wherein each of (a)-(d) is a separately defined component of said computer language. 2. At least one computer-readable medium according to claim 1 , wherein at least one of the defined interactions allows for any of a plurality of inbound document types, and wherein the transition structure specifies different transitions depending upon which document type is actually received. | 0.554381 |
8,831,365 | 12 | 15 | 12. A system comprising: an input receiver operable to receive text captured from a rendered document during a text capture operation, and supplemental information relating to circumstances of performing the text capture operation, the supplemental information comprising information indicating a geographical location at which the text capture operation occurs, the information indicating a geographical location at which the text capture operation occurs comprising information indicating a location as being indoors or outdoors; a processing unit; and a computer memory configured to store the captured text, the supplemental information, and computer-readable programs executable by the processing unit; wherein the computer-readable program instructions are executable by the processing unit to determine, based on the captured text and the supplemental information, an action to be performed; and wherein a determination of the location as being indoors or outdoors is based on light entering a sensor of an optical capture device. | 12. A system comprising: an input receiver operable to receive text captured from a rendered document during a text capture operation, and supplemental information relating to circumstances of performing the text capture operation, the supplemental information comprising information indicating a geographical location at which the text capture operation occurs, the information indicating a geographical location at which the text capture operation occurs comprising information indicating a location as being indoors or outdoors; a processing unit; and a computer memory configured to store the captured text, the supplemental information, and computer-readable programs executable by the processing unit; wherein the computer-readable program instructions are executable by the processing unit to determine, based on the captured text and the supplemental information, an action to be performed; and wherein a determination of the location as being indoors or outdoors is based on light entering a sensor of an optical capture device. 15. The system of claim 12 , wherein the computer-readable program instructions are executable by the processing unit to predict context with respect to a user of a capture device that performs the text capture operation, and wherein at least a portion of the supplemental information is based on the predicted context. | 0.5 |
9,818,404 | 15 | 21 | 15. A system comprising: a microphone to receive an audible speech signal and audible background noise; a signal processor to determine a noise level of the audible background noise; an automatic speech recognition system implemented at least partially in hardware to convert the audible speech signal to a text format; and a dialog system implemented at least partially in hardware to: attempt to interpret the text format of the audible speech signal; determine that the noise level of the audible background noise causes the text format of the audible speech to be uninterpretable; and provide a message that indicates that the audible speech cannot be interpreted because the audible background noise too high; wherein the dialog system is configured to: store noise signals received over time; correlate noise signals received over time and failed attempts to interpret received speech signals; and determine a threshold noise level based on the correlation between noise signals received over time and the failed attempts to interpret received speech signals; and use the threhsold noise level to determine that the speech signal is uninterpretable. | 15. A system comprising: a microphone to receive an audible speech signal and audible background noise; a signal processor to determine a noise level of the audible background noise; an automatic speech recognition system implemented at least partially in hardware to convert the audible speech signal to a text format; and a dialog system implemented at least partially in hardware to: attempt to interpret the text format of the audible speech signal; determine that the noise level of the audible background noise causes the text format of the audible speech to be uninterpretable; and provide a message that indicates that the audible speech cannot be interpreted because the audible background noise too high; wherein the dialog system is configured to: store noise signals received over time; correlate noise signals received over time and failed attempts to interpret received speech signals; and determine a threshold noise level based on the correlation between noise signals received over time and the failed attempts to interpret received speech signals; and use the threhsold noise level to determine that the speech signal is uninterpretable. 21. The system of claim 15 , wherein the dialog system is configured to: determine that the audible speech signal is not understandable; determine that the noise level causes the audible speech signal to be not understandable; and output a message to the user indicating that the background noise level is too high to understand the audible speech signal. | 0.562808 |
10,157,203 | 6 | 7 | 6. A computer program product comprising: one or more computer readable storage media and program instructions stored on said one or more computer readable storage media, said program instructions comprising instructions to: receive a question, said question being directed to a domain-specific question answering system, wherein said question is requesting at least two distinct pieces of information; extract two or more distinct queries from said question, based on a query decomposing rule library by comparing said question to said query decomposing rule library to identify a matching decomposition rule, wherein said comparing includes using an index scan, using a keyword scan, parsing said query decomposing rule library, and using a segment scan, wherein said query decomposing rule library includes combinations of semantic, syntactic, grammatical, structural, and other predetermined rules for identifying distinct queries within said question; generate two or more question sets, each of said two or more question sets addressing all of said two or more queries, wherein said generated two or more questions sets are expressed in a language and format that said question answering system can interpret and process, wherein both said first question set and said second question set include at least one question for each of said two or more queries extracted from said question, and wherein said second question set includes at least one question different from said first question set; select one of said two or more question sets to yield a selected question set, based on analyzing each of said two or more question sets according to a pre-trained model, wherein said pre-trained model is a term vector model, wherein said term vector model is an algebraic model for representing elements within a text document as vectors and generates a number of dimensions based on keywords, terms, and elements within said extracted queries, wherein said two or more question sets are selected based on a first optimal score, wherein said first optimal score is based a number of specific terms and irrelevant terms in questions in each of said two or more question sets, and wherein said irrelevant terms lower said first optimal score; present said selected question set to said question answering system and a user; determine at least one answer set for said selected question set by accessing a structured repository of information using said pre-trained model; and present said answer set to said question answering system. | 6. A computer program product comprising: one or more computer readable storage media and program instructions stored on said one or more computer readable storage media, said program instructions comprising instructions to: receive a question, said question being directed to a domain-specific question answering system, wherein said question is requesting at least two distinct pieces of information; extract two or more distinct queries from said question, based on a query decomposing rule library by comparing said question to said query decomposing rule library to identify a matching decomposition rule, wherein said comparing includes using an index scan, using a keyword scan, parsing said query decomposing rule library, and using a segment scan, wherein said query decomposing rule library includes combinations of semantic, syntactic, grammatical, structural, and other predetermined rules for identifying distinct queries within said question; generate two or more question sets, each of said two or more question sets addressing all of said two or more queries, wherein said generated two or more questions sets are expressed in a language and format that said question answering system can interpret and process, wherein both said first question set and said second question set include at least one question for each of said two or more queries extracted from said question, and wherein said second question set includes at least one question different from said first question set; select one of said two or more question sets to yield a selected question set, based on analyzing each of said two or more question sets according to a pre-trained model, wherein said pre-trained model is a term vector model, wherein said term vector model is an algebraic model for representing elements within a text document as vectors and generates a number of dimensions based on keywords, terms, and elements within said extracted queries, wherein said two or more question sets are selected based on a first optimal score, wherein said first optimal score is based a number of specific terms and irrelevant terms in questions in each of said two or more question sets, and wherein said irrelevant terms lower said first optimal score; present said selected question set to said question answering system and a user; determine at least one answer set for said selected question set by accessing a structured repository of information using said pre-trained model; and present said answer set to said question answering system. 7. The computer program product of claim 6 , wherein instructions to extract two or more queries from said question is based on one or more semantic rules. | 0.806733 |
8,443,295 | 1 | 7 | 1. A method of generating a statistical definition defining statistics to be calculated about the behavior of an automated system, said method comprising the steps of: (i) accessing a state/event model of the automated system, the state/event model comprising a plurality of states; (ii) displaying a graphical representation of the state/event model at a user interface, the graphical representation comprising graphical elements representing the plurality of states of the state/event model; (iii) receiving user inputs comprising information to select states from the state/event model to generate a new statistical definition; (iv) displaying at the user interface said newly generated statistical definition using the graphical representation of the state/event model and an additional graphical element, said additional graphical element being arranged such that only a single graphical element is required to represent a selected one of: (a) a virtual transition between two or more states of the state/event model; and (b) a transition between two or more states of the state/event model which are of different objects, wherein said additional graphical element is added to the graphical representation in addition to the graphical elements representing the plurality of states of the state/event model. | 1. A method of generating a statistical definition defining statistics to be calculated about the behavior of an automated system, said method comprising the steps of: (i) accessing a state/event model of the automated system, the state/event model comprising a plurality of states; (ii) displaying a graphical representation of the state/event model at a user interface, the graphical representation comprising graphical elements representing the plurality of states of the state/event model; (iii) receiving user inputs comprising information to select states from the state/event model to generate a new statistical definition; (iv) displaying at the user interface said newly generated statistical definition using the graphical representation of the state/event model and an additional graphical element, said additional graphical element being arranged such that only a single graphical element is required to represent a selected one of: (a) a virtual transition between two or more states of the state/event model; and (b) a transition between two or more states of the state/event model which are of different objects, wherein said additional graphical element is added to the graphical representation in addition to the graphical elements representing the plurality of states of the state/event model. 7. A method as claimed in claim 1 wherein said user interface is formed using scalar vector graphics extensible markup language (SVG XML). | 0.860887 |
9,786,281 | 1 | 36 | 1. A device comprising: a profile building component in communication with an electronic data store; a speech recognition component; and a sensor configured to detect movement of a user independent of a direction of the user's gaze and without detecting physical contact between the user and the device; wherein the profile building component is configured to: receive, from the sensor, an indication that presence of the user was detected; begin listening for utterances from the user in response to receiving the indication; detect a first voice signal corresponding to a first utterance of the user; determine an identity of the user using the first voice signal; process the first voice signal to determine acoustic information about the user, wherein the acoustic information comprises at least one of an age, a gender, an accent type, a native language, or a type of speech pattern of the user; perform speech recognition on the first voice signal to obtain a transcript; process the transcript to determine language information relating to the user, wherein the language information comprises at least one of a name, hobbies, habits, or preferences of the user; store, in a user profile associated with the identity of the user, the acoustic information and the language information; determine acoustic model information using at least one of the first voice signal, the acoustic information, or the language information; and determine language model information using at least one of the transcript, the acoustic information, or the language information; and wherein the speech recognition component is configured to: receive a second voice signal corresponding to a second utterance of the user; determine the identity of the user using the second voice signal; perform speech recognition on the second voice signal using at least one of the acoustic model information or the language model information to obtain a word sequence that indicates that a third utterance corresponding to a language characteristic will be uttered by a second user different than the user at a time after a current time; and select a second user acoustic model corresponding to the language characteristic for performing speech recognition at the time after the current time. | 1. A device comprising: a profile building component in communication with an electronic data store; a speech recognition component; and a sensor configured to detect movement of a user independent of a direction of the user's gaze and without detecting physical contact between the user and the device; wherein the profile building component is configured to: receive, from the sensor, an indication that presence of the user was detected; begin listening for utterances from the user in response to receiving the indication; detect a first voice signal corresponding to a first utterance of the user; determine an identity of the user using the first voice signal; process the first voice signal to determine acoustic information about the user, wherein the acoustic information comprises at least one of an age, a gender, an accent type, a native language, or a type of speech pattern of the user; perform speech recognition on the first voice signal to obtain a transcript; process the transcript to determine language information relating to the user, wherein the language information comprises at least one of a name, hobbies, habits, or preferences of the user; store, in a user profile associated with the identity of the user, the acoustic information and the language information; determine acoustic model information using at least one of the first voice signal, the acoustic information, or the language information; and determine language model information using at least one of the transcript, the acoustic information, or the language information; and wherein the speech recognition component is configured to: receive a second voice signal corresponding to a second utterance of the user; determine the identity of the user using the second voice signal; perform speech recognition on the second voice signal using at least one of the acoustic model information or the language model information to obtain a word sequence that indicates that a third utterance corresponding to a language characteristic will be uttered by a second user different than the user at a time after a current time; and select a second user acoustic model corresponding to the language characteristic for performing speech recognition at the time after the current time. 36. The device of claim 1 , wherein the second user acoustic model is different than an acoustic model corresponding to the acoustic model information. | 0.873109 |
9,507,840 | 1 | 5 | 1. An information processing apparatus comprising: circuitry configured to extract first experience information of a user, the first experience information indicating a previous, current, or future experience of the user and includes information related to non-geographical experience scene, extract second experience information of other users, the second experience information indicating previous, current, or future experiences of other users and includes information related to non-geographical experience scene, and extract, from among the other users, those users who have a commonality with the user based on the information related to the non-geographical experience scene of the first experience information and the information related to the non-geographical experience scene of the second experience information. | 1. An information processing apparatus comprising: circuitry configured to extract first experience information of a user, the first experience information indicating a previous, current, or future experience of the user and includes information related to non-geographical experience scene, extract second experience information of other users, the second experience information indicating previous, current, or future experiences of other users and includes information related to non-geographical experience scene, and extract, from among the other users, those users who have a commonality with the user based on the information related to the non-geographical experience scene of the first experience information and the information related to the non-geographical experience scene of the second experience information. 5. The information processing apparatus according to claim 1 , wherein the circuitry is further configured to recommend a time or a place for avoiding experience sharing with another user to at least a part of the other users included in the extracted users. | 0.779487 |
8,954,358 | 12 | 15 | 12. A system for training a classifier for a video category, the system comprising: a non-transitory computer-readable storage medium having executable computer program instructions embodied therein; and a computer processor, the computer processor configured to execute the computer program instructions to: access a training set of items for a category, the training set comprising a first set of videos labeled with the category; access a second set of unlabeled videos not labeled with the category; form a cluster for the category, the cluster comprising labeled videos from the training set; generate a supplemental training set for the category, the supplemental training set comprising the first set of videos labeled with the category and a subset of the second set of unlabeled videos not labeled with the category, generating the supplemental training set comprising: adding to the cluster unlabeled videos from the second set that have been co-watched with one or more labeled videos in the cluster by adding the unlabeled videos to nodes of a graph representing the cluster for the category, the nodes having edges connecting with nodes of videos that are co-watched with the added unlabeled videos and the edges having weights based on the co-watch relationships; determining cluster scores for the unlabeled videos added to the cluster responsive to the weights of the edges, the cluster scores representing likelihoods that the unlabeled videos belong to the category and propagated from the labeled videos to the unlabeled videos; and pruning by removing an unlabeled video from the cluster if the cluster score of the unlabeled video is outside a threshold; train a classifier for the category using the supplemental training set for the category; and store the classifier. | 12. A system for training a classifier for a video category, the system comprising: a non-transitory computer-readable storage medium having executable computer program instructions embodied therein; and a computer processor, the computer processor configured to execute the computer program instructions to: access a training set of items for a category, the training set comprising a first set of videos labeled with the category; access a second set of unlabeled videos not labeled with the category; form a cluster for the category, the cluster comprising labeled videos from the training set; generate a supplemental training set for the category, the supplemental training set comprising the first set of videos labeled with the category and a subset of the second set of unlabeled videos not labeled with the category, generating the supplemental training set comprising: adding to the cluster unlabeled videos from the second set that have been co-watched with one or more labeled videos in the cluster by adding the unlabeled videos to nodes of a graph representing the cluster for the category, the nodes having edges connecting with nodes of videos that are co-watched with the added unlabeled videos and the edges having weights based on the co-watch relationships; determining cluster scores for the unlabeled videos added to the cluster responsive to the weights of the edges, the cluster scores representing likelihoods that the unlabeled videos belong to the category and propagated from the labeled videos to the unlabeled videos; and pruning by removing an unlabeled video from the cluster if the cluster score of the unlabeled video is outside a threshold; train a classifier for the category using the supplemental training set for the category; and store the classifier. 15. The system of claim 12 , wherein training the classifier comprises applying an initial classifier for the category to a video in the supplemental training set to generate a score that measures how strongly the video represents the category. | 0.700246 |
8,006,268 | 14 | 23 | 14. A local client set-top box comprising: a processor; a plurality of tuners to receive a respective plurality of channels carrying video signals; a closed caption decoder to extract, from the channels, at least one closed captioning stream of textual data; a user interface to present to a viewer to develop first search terms for creating an active list, the active list including one or more predefined first character strings as the first search terms; an application, executed on the processor, to create a passive list of second search terms, the second search terms comprising one or more character strings that have been extracted one or more times from previously received closed captioning streams of textual data of received video signals that the viewer has viewed or recorded, the one or more second character strings being extracted based on a frequency of occurrence in the previously received textual data; the application further executed on the processor to search, for each said channel, the closed captioning stream of textual data for occurrences of textual data matching one or more search terms by comparing the at least one closed captioning stream of textual data to the active list and the passive list, the comparing including determining whether a number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds a threshold number, wherein when the number of matches of the first search terms of the active list and the second search terms of the passive list does not exceed the threshold number after a predetermined period of time, ceasing to search a first closed captioning stream of textual data from a first channel before an end of the first closed captioning stream is reached, deleting the corresponding content programming from the buffer, and searching instead a second closed captioning stream of textual data from a second channel; and a signal output device to output a notification when the number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds the threshold number. | 14. A local client set-top box comprising: a processor; a plurality of tuners to receive a respective plurality of channels carrying video signals; a closed caption decoder to extract, from the channels, at least one closed captioning stream of textual data; a user interface to present to a viewer to develop first search terms for creating an active list, the active list including one or more predefined first character strings as the first search terms; an application, executed on the processor, to create a passive list of second search terms, the second search terms comprising one or more character strings that have been extracted one or more times from previously received closed captioning streams of textual data of received video signals that the viewer has viewed or recorded, the one or more second character strings being extracted based on a frequency of occurrence in the previously received textual data; the application further executed on the processor to search, for each said channel, the closed captioning stream of textual data for occurrences of textual data matching one or more search terms by comparing the at least one closed captioning stream of textual data to the active list and the passive list, the comparing including determining whether a number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds a threshold number, wherein when the number of matches of the first search terms of the active list and the second search terms of the passive list does not exceed the threshold number after a predetermined period of time, ceasing to search a first closed captioning stream of textual data from a first channel before an end of the first closed captioning stream is reached, deleting the corresponding content programming from the buffer, and searching instead a second closed captioning stream of textual data from a second channel; and a signal output device to output a notification when the number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds the threshold number. 23. The local client set-top box as defined in claim 14 , wherein the signal output device notifies the viewer that content programming corresponding to viewer interests has been located by sending a notification message to a telephone number of the viewer, wherein the sending the notification message to the telephone number of the viewer includes placing a telephone call to the viewer. | 0.793962 |
9,703,891 | 1 | 4 | 1. A method for providing recommendations to improve a query, comprising: receiving, from a user via a user interface, a query with query keywords and selected categories; calculating a query relevance indicator for each of the selected categories, wherein the query relevance indicator for a category of the selected categories is calculated based on a keyword relevance indicator of each keyword specified in the query, a total number of keywords in the query, a keyword relevance indicator of each keyword in the category that is not specified in the query, and a total number of different keywords in the category and the query; and in response to determining that the selected categories are ranked high with reference to the query relevance indicator for each of the selected categories, calculating a query relevance indicator for each subcategory, wherein the query relevance indicator for a subcategory is calculated based on the keyword relevance indicator of each keyword specified in the query, the total number of keywords in the query, a keyword relevance indicator of each keyword in the subcategory that is not specified in the query, and a total number of different keywords in the subcategory and the query; ranking each subcategory based on the query relevance indicator of the query with each subcategory; and in response to determining that high-ranked subcategories are not in the selected categories, providing recommendations of one or more new query keywords and the ranked subcategories for use in selecting new categories to be submitted with the query; and in response to receiving a new query using at least one of the one or more new query keywords, executing the new query to identify services. | 1. A method for providing recommendations to improve a query, comprising: receiving, from a user via a user interface, a query with query keywords and selected categories; calculating a query relevance indicator for each of the selected categories, wherein the query relevance indicator for a category of the selected categories is calculated based on a keyword relevance indicator of each keyword specified in the query, a total number of keywords in the query, a keyword relevance indicator of each keyword in the category that is not specified in the query, and a total number of different keywords in the category and the query; and in response to determining that the selected categories are ranked high with reference to the query relevance indicator for each of the selected categories, calculating a query relevance indicator for each subcategory, wherein the query relevance indicator for a subcategory is calculated based on the keyword relevance indicator of each keyword specified in the query, the total number of keywords in the query, a keyword relevance indicator of each keyword in the subcategory that is not specified in the query, and a total number of different keywords in the subcategory and the query; ranking each subcategory based on the query relevance indicator of the query with each subcategory; and in response to determining that high-ranked subcategories are not in the selected categories, providing recommendations of one or more new query keywords and the ranked subcategories for use in selecting new categories to be submitted with the query; and in response to receiving a new query using at least one of the one or more new query keywords, executing the new query to identify services. 4. The method of claim 1 , further comprising: for category keywords in non-top-ranked selected categories with high keyword relevance indicators, identifying the category keywords that are not in the query and for which synonyms are not identified; and providing a recommendation that the identified category keywords be added to the query. | 0.652041 |
4,672,679 | 7 | 8 | 7. The method of claim 6, wherein each said context comprises: a group of text characters associated with said text character. | 7. The method of claim 6, wherein each said context comprises: a group of text characters associated with said text character. 8. The method of claim 7, wherein each said context contains a fixed number of said text characters. | 0.5 |
9,471,567 | 1 | 4 | 1. A processor-implemented method programmed in memory and/or a non-transitory processor-readable medium and to execute on one or more processors of a device configured to execute the method, comprising: detecting, on the device, audio in proximity to a microphone, wherein detecting further includes detecting the audio as speech from one of: a single person conversing on a phone in proximity to the microphone and multiple people conversing with one another in proximity to the microphone; filtering, on the device, the audio to detect speech; and translating, on the device, information originally being presented on a digital display in an original written language into a target written language identified for a spoken language and resolved for the detected speech, wherein the information is presented on the digital display in the target written language replacing the information presented on the digital display in the original written language, and modifying an original image presented on the digital display with a new image that is appropriate for a cultural of the spoken language. | 1. A processor-implemented method programmed in memory and/or a non-transitory processor-readable medium and to execute on one or more processors of a device configured to execute the method, comprising: detecting, on the device, audio in proximity to a microphone, wherein detecting further includes detecting the audio as speech from one of: a single person conversing on a phone in proximity to the microphone and multiple people conversing with one another in proximity to the microphone; filtering, on the device, the audio to detect speech; and translating, on the device, information originally being presented on a digital display in an original written language into a target written language identified for a spoken language and resolved for the detected speech, wherein the information is presented on the digital display in the target written language replacing the information presented on the digital display in the original written language, and modifying an original image presented on the digital display with a new image that is appropriate for a cultural of the spoken language. 4. The method of claim 1 further comprising, updating, via the device, the digital display to be consistent with cultural norms associated with the resolved spoken language. | 0.628755 |
8,375,303 | 1 | 10 | 1. A method implemented by a hand-held device adapted to process content data files to form digital data representing a work of communication, the work of communication pertaining to a narrative, and the method comprising: accessing a set of content data files stored in a memory device accessible to the hand-held device; determining context indicators from at least some of the accessed content data files based at least upon a set of rules for identifying the context indicators; providing the narrative to a voice recognition system that converts the narrative into a form that usable by a processor associated with the hand-held device; the processor determining the relative significances of at least some of the accessed content data files; determining inference queries based at least upon the context indicators and the relative significances of the accessed content data files; using at least the inference queries to determine a reduced set of the most relevant accessed content data files to include in the work of communication; and displaying, printing, storing, or transmitting the digital data representing the work of communication. | 1. A method implemented by a hand-held device adapted to process content data files to form digital data representing a work of communication, the work of communication pertaining to a narrative, and the method comprising: accessing a set of content data files stored in a memory device accessible to the hand-held device; determining context indicators from at least some of the accessed content data files based at least upon a set of rules for identifying the context indicators; providing the narrative to a voice recognition system that converts the narrative into a form that usable by a processor associated with the hand-held device; the processor determining the relative significances of at least some of the accessed content data files; determining inference queries based at least upon the context indicators and the relative significances of the accessed content data files; using at least the inference queries to determine a reduced set of the most relevant accessed content data files to include in the work of communication; and displaying, printing, storing, or transmitting the digital data representing the work of communication. 10. The method of claim 1 , further comprising selecting the first set of rules from plural sets of rules based at least upon a relationship between the first set of rules and an author of the work of communication, a subject of the work of communication, a type of the work of communication, a manner in which the work of communication is used, or a manner of use of the work of communication. | 0.5 |
8,775,328 | 7 | 9 | 7. A computer server including one or more processors having non-transitory instructions stored thereon that when executed cause the computer server: to verify that a user lives at a residence associated with a geographic location claimed by the user of an online neighborhood social network using a processor and a memory, to create a social network page of the user once verified in the online neighborhood social network, to enable the user to constrain communications to neighboring users in a geospatial vicinity of the residence of the user based on a neighborhood boundary of the online neighborhood social network, to automatically determine a set of access privileges in the online neighborhood social network associated with the neighborhood boundary of the online neighborhood social network by constraining access in a private website in the online neighborhood social network to the user and to neighboring users of the user based on each residence associated with each geographic location claimed by each user of the online neighborhood social network verified to live within the neighborhood boundary, wherein the user is provided an additional privilege as a lead user in the online neighborhood social network based on at least one of a participation level of the user in the online neighborhood social network and an activity level of the user associated with encouraging neighbors to participate in the online neighborhood social network, and wherein the computer server to permit the user to set a privacy setting associated with a profile data such that a certain information is marked as private in the online neighborhood social network and is therefore masked from being visible to neighboring users of the online neighborhood social network. | 7. A computer server including one or more processors having non-transitory instructions stored thereon that when executed cause the computer server: to verify that a user lives at a residence associated with a geographic location claimed by the user of an online neighborhood social network using a processor and a memory, to create a social network page of the user once verified in the online neighborhood social network, to enable the user to constrain communications to neighboring users in a geospatial vicinity of the residence of the user based on a neighborhood boundary of the online neighborhood social network, to automatically determine a set of access privileges in the online neighborhood social network associated with the neighborhood boundary of the online neighborhood social network by constraining access in a private website in the online neighborhood social network to the user and to neighboring users of the user based on each residence associated with each geographic location claimed by each user of the online neighborhood social network verified to live within the neighborhood boundary, wherein the user is provided an additional privilege as a lead user in the online neighborhood social network based on at least one of a participation level of the user in the online neighborhood social network and an activity level of the user associated with encouraging neighbors to participate in the online neighborhood social network, and wherein the computer server to permit the user to set a privacy setting associated with a profile data such that a certain information is marked as private in the online neighborhood social network and is therefore masked from being visible to neighboring users of the online neighborhood social network. 9. The computer server of claim 7 : wherein the computer server to permit the user to provide a recommendation to neighboring users based on the residence associated with the geographic location claimed by the user of the online neighborhood social network. | 0.688862 |
7,603,647 | 15 | 16 | 15. The computer-readable storage medium of claim 14 , further including: if ELSE or ELSEIF statements are found, searching for a THEN statement associated with the IF statement; and searching for a reset clause between the IF statement and the THEN statements. | 15. The computer-readable storage medium of claim 14 , further including: if ELSE or ELSEIF statements are found, searching for a THEN statement associated with the IF statement; and searching for a reset clause between the IF statement and the THEN statements. 16. The computer-readable storage medium of claim 15 , further including: searching for a clock statement between the ELSE or ELSEIF statement and the THEN statement. | 0.5 |
9,280,973 | 9 | 12 | 9. A method, comprising: receiving, by one or more computing devices, a request designating content, wherein the content has a user-selectable element; determining, by at least one computing device of the one or more computing devices, an audio command corresponding to the user-selectable element, the audio command being determined based at least in part on an acoustic differentiation between the audio command and a different audio command meeting or exceeding a threshold; associating, by at least one computing device of the one or more computing devices, the audio command with the user-selectable element; and causing information associated with audio command to be visually output by a projector associated with the second device. | 9. A method, comprising: receiving, by one or more computing devices, a request designating content, wherein the content has a user-selectable element; determining, by at least one computing device of the one or more computing devices, an audio command corresponding to the user-selectable element, the audio command being determined based at least in part on an acoustic differentiation between the audio command and a different audio command meeting or exceeding a threshold; associating, by at least one computing device of the one or more computing devices, the audio command with the user-selectable element; and causing information associated with audio command to be visually output by a projector associated with the second device. 12. The method of claim 9 , wherein determining the audio command comprises selecting text from the content. | 0.770213 |
8,132,152 | 12 | 13 | 12. A system configured to generate programmatically a pointer to a super implementation of a method in a programming language that is not a class-based object-oriented programming (OOP) language, comprising: a memory configured to store computer code defining one or more functions; and a processor coupled to the memory and configured to: receive a call to a function associated with a current function and wherein the function is configured to cause a pointer to a super implementation of an inherited method to be inserted into the current function, wherein the super implementation comprises the method as defined (a) at a nearest node to the current function, traversing up the hierarchy, at which the method was last overwritten, if the method was overwritten previously or (b) in the event the method has not been overwritten since being first defined the node at which it was first defined; traverse up, in response to the call, a hierarchy of the one or more functions, the hierarchy including one or more parent nodes each representing a parent function and each having one or more child nodes, each child node representing a function that inherits the methods of the corresponding parent node of which it is a child, until the super implementation of the inherited method is found; and insert programmatically into a corresponding location in the current function a programmatically created pointer to the super implementation. | 12. A system configured to generate programmatically a pointer to a super implementation of a method in a programming language that is not a class-based object-oriented programming (OOP) language, comprising: a memory configured to store computer code defining one or more functions; and a processor coupled to the memory and configured to: receive a call to a function associated with a current function and wherein the function is configured to cause a pointer to a super implementation of an inherited method to be inserted into the current function, wherein the super implementation comprises the method as defined (a) at a nearest node to the current function, traversing up the hierarchy, at which the method was last overwritten, if the method was overwritten previously or (b) in the event the method has not been overwritten since being first defined the node at which it was first defined; traverse up, in response to the call, a hierarchy of the one or more functions, the hierarchy including one or more parent nodes each representing a parent function and each having one or more child nodes, each child node representing a function that inherits the methods of the corresponding parent node of which it is a child, until the super implementation of the inherited method is found; and insert programmatically into a corresponding location in the current function a programmatically created pointer to the super implementation. 13. A system as recited in claim 12 , wherein the pointer conforms to a syntax of the programming language for invoking in the context of executing a first function a method as implemented in another function. | 0.568182 |
9,311,392 | 1 | 2 | 1. A document analysis apparatus comprising a computer with a central processing unit (CPU): the CPU being configured to function as a document collection acquisition unit which accepts an analysis object document to be an analysis object as a first document collection, and furthermore, accepts as an input a feature expression appearing during an attention period specified in advance in said first document collection, and for every said feature expression, acquires a collection of documents which have been issued, generated or updated during said attention period and in which said acquired feature expression has appeared, as a second document collection from among document collections including said first document collection; the CPU being configured to function as a context determination unit which, for every said feature expression, specifies a document corresponding to said analysis object document as a first feature expression containing document, among documents of said second document collection in which the feature expression has appeared, and furthermore, specifies a context which is common in two or more said first feature expression containing documents as the context of the feature expression, among contexts in which the feature expression has appeared in said first feature expression containing document; the CPU being configured to function as a context comparison determination unit which, for every said feature expression, specifies a document which does not correspond to said analysis object document as a second feature expression containing document, among documents of said second document collection in which the feature expression has appeared, and furthermore, performs comparison between a context in which the feature expression has appeared in said second feature expression containing document and a context which said CPU functioning as the context determination unit has specified; and the CPU being configured to function as a feature degree setting unit which, based on a result of comparison by said CPU functioning as the context comparison determination unit, gives a feature degree to said feature expression, or corrects a feature degree in the case where a feature degree has been given to said feature expression in advance, wherein said CPU functioning as the context determination unit, after specifying said first feature expression containing document, determines, for every said feature expression, whether a relation between the number of said first feature expression containing documents and the number of documents in which the feature expression has appeared within said second document collection fulfills a setting condition, and specifies said context in the case where said setting condition is not fulfilled, and wherein said CPU functioning as the context comparison determination unit performs a comparison between a context in which the feature expression has appeared in said second feature expression containing document and a context which said CPU functioning as the context determination unit has specified, with respect to each said feature expression for which said context has been specified. | 1. A document analysis apparatus comprising a computer with a central processing unit (CPU): the CPU being configured to function as a document collection acquisition unit which accepts an analysis object document to be an analysis object as a first document collection, and furthermore, accepts as an input a feature expression appearing during an attention period specified in advance in said first document collection, and for every said feature expression, acquires a collection of documents which have been issued, generated or updated during said attention period and in which said acquired feature expression has appeared, as a second document collection from among document collections including said first document collection; the CPU being configured to function as a context determination unit which, for every said feature expression, specifies a document corresponding to said analysis object document as a first feature expression containing document, among documents of said second document collection in which the feature expression has appeared, and furthermore, specifies a context which is common in two or more said first feature expression containing documents as the context of the feature expression, among contexts in which the feature expression has appeared in said first feature expression containing document; the CPU being configured to function as a context comparison determination unit which, for every said feature expression, specifies a document which does not correspond to said analysis object document as a second feature expression containing document, among documents of said second document collection in which the feature expression has appeared, and furthermore, performs comparison between a context in which the feature expression has appeared in said second feature expression containing document and a context which said CPU functioning as the context determination unit has specified; and the CPU being configured to function as a feature degree setting unit which, based on a result of comparison by said CPU functioning as the context comparison determination unit, gives a feature degree to said feature expression, or corrects a feature degree in the case where a feature degree has been given to said feature expression in advance, wherein said CPU functioning as the context determination unit, after specifying said first feature expression containing document, determines, for every said feature expression, whether a relation between the number of said first feature expression containing documents and the number of documents in which the feature expression has appeared within said second document collection fulfills a setting condition, and specifies said context in the case where said setting condition is not fulfilled, and wherein said CPU functioning as the context comparison determination unit performs a comparison between a context in which the feature expression has appeared in said second feature expression containing document and a context which said CPU functioning as the context determination unit has specified, with respect to each said feature expression for which said context has been specified. 2. The document analysis apparatus according to claim 1 , wherein said CPU functioning as the context determination unit selects a text part associated with the feature expression, for every said feature expression, with respect to each said first feature expression containing document, and extracts a linguistic expression expressing a context of the feature expression from each said selected text part, and furthermore, determines whether each said linguistic expression extracted from said first feature expression containing document has appeared in common in two or more said first feature expression containing documents, and then, specifies said linguistic expression determined to have appeared in common in two or more said first feature expression containing documents as the context of the feature expression. | 0.5 |
8,688,673 | 17 | 18 | 17. The method according to claim 15 , further comprising: associating an advertisement with a determined category context; and delivering the advertisement to at least one of the relevant users. | 17. The method according to claim 15 , further comprising: associating an advertisement with a determined category context; and delivering the advertisement to at least one of the relevant users. 18. The method according to claim 17 , wherein the advertisement is selected from at least one from a group consisting of text, audio and video, and classified advertisement. | 0.5 |
8,849,659 | 1 | 9 | 1. A method to communicate with a mobile device, comprising: receiving at a game engine, mobile device input from the mobile device over a wireless channel, wherein the mobile device input includes a multimedia data stream; receiving at the game engine, location information indicating a location of the mobile device, wherein the location information corresponds to the location of a user providing verbal instruction input to the mobile device; analyzing an audio clip or video in the multimedia data stream; analyzing the location information; and sending audio content or video content to the mobile device based at least in part on analysis of the multimedia data stream and the location information in accordance with a game engine instruction. | 1. A method to communicate with a mobile device, comprising: receiving at a game engine, mobile device input from the mobile device over a wireless channel, wherein the mobile device input includes a multimedia data stream; receiving at the game engine, location information indicating a location of the mobile device, wherein the location information corresponds to the location of a user providing verbal instruction input to the mobile device; analyzing an audio clip or video in the multimedia data stream; analyzing the location information; and sending audio content or video content to the mobile device based at least in part on analysis of the multimedia data stream and the location information in accordance with a game engine instruction. 9. The method of claim 1 , further comprising: preparing a summary of the audio clip or video including relevant image, music, or video information. | 0.708661 |
7,814,404 | 22 | 26 | 22. The system of claim 21 , wherein the events are selected from the group comprising user events and system events. | 22. The system of claim 21 , wherein the events are selected from the group comprising user events and system events. 26. The system of claim 22 further comprising a dependency link in addition to the plurality of dependency links associated with the events corresponding to the embedded elements, the additional dependency link accounting for interaction of sub-pages of the component based application, the sub-pages representing the splitting of a page of the page-based application according to presentation capabilities of the device. | 0.5 |
8,412,517 | 1 | 7 | 1. A method performed by a system comprising one or more computers, the method comprising: identifying, in a search query, one or more candidate terms, wherein each candidate term corresponds to one or more sequences of consecutive characters in the search query, and wherein a delimiter separates each sequence of consecutive characters when more than one sequence is identified in the search query; for each candidate term, determining a first count that is a number of times that the candidate term is an entire search query in a collection of search queries, and determining a second count that is a number of times that the candidate term is in, but less than, an entire search query in the collection of search queries; identifying, using one or more computing devices, one or more of the candidate terms as being candidate entries based on the first and second counts; and adding the candidate entries to an input method editor dictionary. | 1. A method performed by a system comprising one or more computers, the method comprising: identifying, in a search query, one or more candidate terms, wherein each candidate term corresponds to one or more sequences of consecutive characters in the search query, and wherein a delimiter separates each sequence of consecutive characters when more than one sequence is identified in the search query; for each candidate term, determining a first count that is a number of times that the candidate term is an entire search query in a collection of search queries, and determining a second count that is a number of times that the candidate term is in, but less than, an entire search query in the collection of search queries; identifying, using one or more computing devices, one or more of the candidate terms as being candidate entries based on the first and second counts; and adding the candidate entries to an input method editor dictionary. 7. The method of claim 1 wherein the candidate words comprise Hanzi characters. | 0.864726 |
8,855,926 | 26 | 27 | 26. The method of claim 1 where the map is displayed on a touchscreen device. | 26. The method of claim 1 where the map is displayed on a touchscreen device. 27. The method of claim 26 where the touchscreen device is a tablet device. | 0.5 |
8,996,554 | 1 | 2 | 1. A method, comprising: receiving a first set of search queries during a first search session; identifying, from the first set of search queries, a first set of search tokens; identifying, from a query log storing search queries for a plurality of different search sessions, a second search session during which at least a threshold portion of the first set of search tokens were included in a second set of search queries received during the second search session; selecting, by one or more computers and as related tokens for the first search session, a second set of search tokens from the second set of search queries; receiving a current search query during the first search session; determining, by one or more computers and based on the query log, that the current search query has historically been revised by users to replace a particular search token from the first set of search tokens with one of the related tokens; and creating, by one or more computers, a suggested search query in which the particular search token is replaced by the one of the related tokens. | 1. A method, comprising: receiving a first set of search queries during a first search session; identifying, from the first set of search queries, a first set of search tokens; identifying, from a query log storing search queries for a plurality of different search sessions, a second search session during which at least a threshold portion of the first set of search tokens were included in a second set of search queries received during the second search session; selecting, by one or more computers and as related tokens for the first search session, a second set of search tokens from the second set of search queries; receiving a current search query during the first search session; determining, by one or more computers and based on the query log, that the current search query has historically been revised by users to replace a particular search token from the first set of search tokens with one of the related tokens; and creating, by one or more computers, a suggested search query in which the particular search token is replaced by the one of the related tokens. 2. The method of claim 1 , comprising providing the suggested search query to a user device in response to receipt of the current search query. | 0.800279 |
7,707,635 | 9 | 11 | 9. A system for scanning computer network traffic for viruses, the system comprising: a buffer configured to store portions of a data stream; a plurality of script patterns, each script pattern in the plurality of script patterns comprising a set of instructions for identifying a particular network virus, each script pattern in the plurality of script patterns being created using a scripting language that allows for conditional flow control to allow conditional branching to a line of a script pattern; and a script engine configured to execute the script patterns to check the data stream for network viruses. | 9. A system for scanning computer network traffic for viruses, the system comprising: a buffer configured to store portions of a data stream; a plurality of script patterns, each script pattern in the plurality of script patterns comprising a set of instructions for identifying a particular network virus, each script pattern in the plurality of script patterns being created using a scripting language that allows for conditional flow control to allow conditional branching to a line of a script pattern; and a script engine configured to execute the script patterns to check the data stream for network viruses. 11. The system of claim 9 wherein the portions of the data stream stored in the buffer include a portion available for scanning and a portion that has already been scanned. | 0.524862 |
9,158,655 | 17 | 18 | 17. A method for evaluating standards compliance during software development, comprising: receiving, by an interface, a first selection from a user, the first selection comprising a design assessment ruleset to be used for evaluating a computer change, the design assessment ruleset comprising one or more design assessment rules, each design assessment rule associated with a condition that determines whether the design assessment rule is evaluated, the condition indicating whether the assessment rule is associated with one or more of a pilot project and a completed project; storing, by a memory, the design assessment ruleset; determining whether the computer change is associated with a pilot project; communicating to the user, by the processor, a design evaluation question relating to each design assessment rule whose associated condition indicates that the assessment rule is associated with a pilot project, an answer to the design evaluation question indicating an extent to which the computer change complies with the design assessment rule, the answer indicating one of compliance, noncompliance, or partial compliance; and determining, by the processor, one or more design scores based on the answer to each design evaluation question. | 17. A method for evaluating standards compliance during software development, comprising: receiving, by an interface, a first selection from a user, the first selection comprising a design assessment ruleset to be used for evaluating a computer change, the design assessment ruleset comprising one or more design assessment rules, each design assessment rule associated with a condition that determines whether the design assessment rule is evaluated, the condition indicating whether the assessment rule is associated with one or more of a pilot project and a completed project; storing, by a memory, the design assessment ruleset; determining whether the computer change is associated with a pilot project; communicating to the user, by the processor, a design evaluation question relating to each design assessment rule whose associated condition indicates that the assessment rule is associated with a pilot project, an answer to the design evaluation question indicating an extent to which the computer change complies with the design assessment rule, the answer indicating one of compliance, noncompliance, or partial compliance; and determining, by the processor, one or more design scores based on the answer to each design evaluation question. 18. The method of claim 17 , further comprising determining, by the processor, whether to permit building of the computer change based at least on the one or more design scores. | 0.694828 |
9,411,899 | 12 | 13 | 12. The method of claim 11 , wherein: the user action comprises a user action on one of the functional options of the first different page. | 12. The method of claim 11 , wherein: the user action comprises a user action on one of the functional options of the first different page. 13. The method of claim 12 , wherein the visual representation of the plurality of functional options of the first different page comprise respective actionable interface elements. | 0.778325 |
9,489,373 | 10 | 11 | 10. A system for segment extraction by a user for a machine learning environment, the method comprising: one or more processing devices configured to: store a set of data items, wherein each data item includes a plurality of tokens; operate as a segment extractor that is trainable to identify a segment within a data item as an example of a concept, wherein the segment includes a group of tokens; present on a user interface a concept hierarchy that represents the concept, wherein the concept hierarchy depicts a root node that corresponds to the concept and one or more child nodes that correspond to hierarchical sub-concepts that are constituent parts of the concept, wherein the child nodes depict respective labels that identify sub-concepts that correspond to the child nodes, wherein one or more of the child nodes are user-selectable for labeling tokens within the data item, wherein selection of a child node within the concept hierarchy identifies the respective label that is utilized for labeling a token within the data item; receive a user selection of a child node that corresponds to a selected sub-concept in the concept hierarchy; utilize the segment extractor to select from the plurality of data items a first data item that is predicted to include an example of the concept associated with the concept hierarchy, wherein the example is represented by one or more of the tokens in the first data item; display the first data item, wherein displaying the first data item includes presenting a first set of one or more pre-labels that identify a first set of one or more tokens as predicted positive examples of the selected sub-concept; receive a user selection of a first token in the displayed second data item that labels the first token as a positive or negative example of the selected sub-concept; replacing the first set of one or more pre-labels with a second set of one or more pre-labels that identify a second set of one or more tokens as predicted positive examples of the selected sub-concept; and based at least on the labeling of the first token as an example of the selected sub-concept, train the segment extractor. | 10. A system for segment extraction by a user for a machine learning environment, the method comprising: one or more processing devices configured to: store a set of data items, wherein each data item includes a plurality of tokens; operate as a segment extractor that is trainable to identify a segment within a data item as an example of a concept, wherein the segment includes a group of tokens; present on a user interface a concept hierarchy that represents the concept, wherein the concept hierarchy depicts a root node that corresponds to the concept and one or more child nodes that correspond to hierarchical sub-concepts that are constituent parts of the concept, wherein the child nodes depict respective labels that identify sub-concepts that correspond to the child nodes, wherein one or more of the child nodes are user-selectable for labeling tokens within the data item, wherein selection of a child node within the concept hierarchy identifies the respective label that is utilized for labeling a token within the data item; receive a user selection of a child node that corresponds to a selected sub-concept in the concept hierarchy; utilize the segment extractor to select from the plurality of data items a first data item that is predicted to include an example of the concept associated with the concept hierarchy, wherein the example is represented by one or more of the tokens in the first data item; display the first data item, wherein displaying the first data item includes presenting a first set of one or more pre-labels that identify a first set of one or more tokens as predicted positive examples of the selected sub-concept; receive a user selection of a first token in the displayed second data item that labels the first token as a positive or negative example of the selected sub-concept; replacing the first set of one or more pre-labels with a second set of one or more pre-labels that identify a second set of one or more tokens as predicted positive examples of the selected sub-concept; and based at least on the labeling of the first token as an example of the selected sub-concept, train the segment extractor. 11. The system of claim 10 , wherein the one or more processing devices are further configured to: display a second data item from the plurality of data items, wherein the second data item is selected by means of a user-provided search query; receive a user selection of a second token in the displayed second data item that labels the second token as an example of the selected sub-concept; and based at least on the labeling of the second token as an example of the selected sub-concept, training the segment extractor. | 0.5 |
7,756,987 | 6 | 7 | 6. The method of claim 1 further comprising determining if the primary URL corresponds to a composite domain name that comprises a trademark. | 6. The method of claim 1 further comprising determining if the primary URL corresponds to a composite domain name that comprises a trademark. 7. The method of claim 6 further comprising determining if the owner of the composite domain name owns the trademark. | 0.5 |
8,090,736 | 1 | 3 | 1. A method performed by a computer system, the method comprising: selecting, using one or more processors associated with the computer system, a first document; representing, using one or more processors associated with the computer system, a first relationship between the first document and a second document as a first link between the first document and the second document, where the first relationship includes at least one of: the first document and the second document sharing a same hierarchical user-defined label, the first document and the second document being associated with a same sub-directory, or the first document and the second document being associated with a same bookmark folder; representing, using one or more processors associated with the computer system, a second relationship between the first document and a third document as a second link between the first document and a third document, where the second relationship includes at least one of: a hierarchical user-defined label associated with the first document and a hierarchical user-defined label associated with the third document being sibling labels, a sub-directory associated with the first document and a sub-directory associated with the third document being sibling sub-directories, or a bookmark folder associated with the first document and a bookmark folder associated with the third document being sibling bookmark folders; and assigning, using one or more processors associated with the computer system, a rank score to the first document based on the first link and based on the second link, where the first link contributes more to the rank score than the second link. | 1. A method performed by a computer system, the method comprising: selecting, using one or more processors associated with the computer system, a first document; representing, using one or more processors associated with the computer system, a first relationship between the first document and a second document as a first link between the first document and the second document, where the first relationship includes at least one of: the first document and the second document sharing a same hierarchical user-defined label, the first document and the second document being associated with a same sub-directory, or the first document and the second document being associated with a same bookmark folder; representing, using one or more processors associated with the computer system, a second relationship between the first document and a third document as a second link between the first document and a third document, where the second relationship includes at least one of: a hierarchical user-defined label associated with the first document and a hierarchical user-defined label associated with the third document being sibling labels, a sub-directory associated with the first document and a sub-directory associated with the third document being sibling sub-directories, or a bookmark folder associated with the first document and a bookmark folder associated with the third document being sibling bookmark folders; and assigning, using one or more processors associated with the computer system, a rank score to the first document based on the first link and based on the second link, where the first link contributes more to the rank score than the second link. 3. The method of claim 1 , comprising: representing a third relationship between the second document and a fourth document as a third link between the second document and the fourth document, where the third relationship includes the second document and the fourth document sharing a same hierarchical user-defined label that is not shared by the first document; and modifying the rank score of the first document based on the third link and based on a rank score associated with the fourth document. | 0.541284 |
7,962,853 | 1 | 15 | 1. A method for collaborative editing of a document by an author of the document and a plurality of reviewers, said method being performed by program code executing on a computer, said method comprising: receiving, by the program code from the author, an identification of a plurality of selected portions of the document; receiving, by the program code from the author, a plurality of comments created by the author and an identification of at least one reviewer of the plurality of reviewers to which each received comment is directed, wherein the selected portions and the comments are associated with each other on a one-to-one basis, and wherein each comment pertains to content of the selected portion that each comment is associated with; parsing the received comments, and utilizing the received identification of the at least one reviewer to which each comment is directed, to generate a list of comments comprising the plurality of comments, wherein the list of comments specifies for each comment the at least one reviewer to which each comment is directed, and wherein said parsing and said utilizing are performed by the program code; and making available, by the program code to each reviewer, the comments on the list of comments directed to each reviewer, wherein the method further comprises for each selected portion of the document: providing, by the program code to the author, a corresponding displayed form; wherein each displayed form includes the selected portion and space for the author to specify both the comment associated with the selected portion and the identification of at the least one reviewer to which the associated comment is directed; and wherein said receiving the plurality of comments comprises receiving the comments in the displayed forms corresponding to the selected portions of the document. | 1. A method for collaborative editing of a document by an author of the document and a plurality of reviewers, said method being performed by program code executing on a computer, said method comprising: receiving, by the program code from the author, an identification of a plurality of selected portions of the document; receiving, by the program code from the author, a plurality of comments created by the author and an identification of at least one reviewer of the plurality of reviewers to which each received comment is directed, wherein the selected portions and the comments are associated with each other on a one-to-one basis, and wherein each comment pertains to content of the selected portion that each comment is associated with; parsing the received comments, and utilizing the received identification of the at least one reviewer to which each comment is directed, to generate a list of comments comprising the plurality of comments, wherein the list of comments specifies for each comment the at least one reviewer to which each comment is directed, and wherein said parsing and said utilizing are performed by the program code; and making available, by the program code to each reviewer, the comments on the list of comments directed to each reviewer, wherein the method further comprises for each selected portion of the document: providing, by the program code to the author, a corresponding displayed form; wherein each displayed form includes the selected portion and space for the author to specify both the comment associated with the selected portion and the identification of at the least one reviewer to which the associated comment is directed; and wherein said receiving the plurality of comments comprises receiving the comments in the displayed forms corresponding to the selected portions of the document. 15. The method of claim 1 , wherein a first comment of the plurality of comments is directed to at least two reviewers of the plurality of reviewers. | 0.792479 |
10,056,083 | 1 | 2 | 1. A method for dynamically generating a text transcript, comprising: segmenting, by an application server comprising a processor, each identified set of text frames to determine one or more spatial regions, wherein the one or more spatial regions comprise at least one or more portions of text content; extracting, by an application server comprising a processor, one or more keywords from the one or more spatial regions, wherein the one or more keywords are extracted from one or more available portions of the text content in the one or more spatial regions; determining, by an application server comprising a processor, a first set of keywords from the one or more extracted keywords by filtering one or more off-topic keywords from the one or more extracted keywords; extracting, by an application server comprising a processor, a second set of keywords similar to or related with the one or more second set of keywords, wherein the second set of keywords being retrieved from one or more knowledge databases; generating, by an application server comprising a processor, a graph from a semantic relationship between the first set of keywords and the second set of keywords, wherein the graph comprises one or more first nodes and one or more second nodes with each node in the one or more first nodes corresponding with a keyword in the first set of keywords and each node in the one or more second nodes corresponding with a keyword in the second set of keywords; and generating, by an application server comprising a processor, the text transcript of the audio content in the multimedia content using the generated graph, wherein the generating of the text transcript comprises utilizing at least one of an updated language module and an updated dictionary module to generate the text transcript of the audio content in the multimedia content. | 1. A method for dynamically generating a text transcript, comprising: segmenting, by an application server comprising a processor, each identified set of text frames to determine one or more spatial regions, wherein the one or more spatial regions comprise at least one or more portions of text content; extracting, by an application server comprising a processor, one or more keywords from the one or more spatial regions, wherein the one or more keywords are extracted from one or more available portions of the text content in the one or more spatial regions; determining, by an application server comprising a processor, a first set of keywords from the one or more extracted keywords by filtering one or more off-topic keywords from the one or more extracted keywords; extracting, by an application server comprising a processor, a second set of keywords similar to or related with the one or more second set of keywords, wherein the second set of keywords being retrieved from one or more knowledge databases; generating, by an application server comprising a processor, a graph from a semantic relationship between the first set of keywords and the second set of keywords, wherein the graph comprises one or more first nodes and one or more second nodes with each node in the one or more first nodes corresponding with a keyword in the first set of keywords and each node in the one or more second nodes corresponding with a keyword in the second set of keywords; and generating, by an application server comprising a processor, the text transcript of the audio content in the multimedia content using the generated graph, wherein the generating of the text transcript comprises utilizing at least one of an updated language module and an updated dictionary module to generate the text transcript of the audio content in the multimedia content. 2. The method of claim 1 , further comprising: determining one or more frames of the multimedia content; and identifying the set of text frames from the one or more frames, wherein the set of text frames are identified from one or more available portions of the text content within the one or more frames. | 0.658072 |
9,390,165 | 1 | 7 | 1. A system comprising: a memory to store a plurality of comments, the plurality of comments respectively comprising an overall rating of an entity and at least one phrase, the at least one phrase comprising a head term and a modifier associated with the head term; and one or more processors to implement: an aspect module to map respective head terms of a portion of the plurality of comments to an aspect cluster corresponding to an attribute of the entity, and a rating module to determine an aspect rating corresponding to the attribute of the entity based on the respective overall rating of the portion of the plurality of comments, and a module to cause presentation, on a client machine, of a graphical representation of the determined aspect rating corresponding to the attribute of the entity. | 1. A system comprising: a memory to store a plurality of comments, the plurality of comments respectively comprising an overall rating of an entity and at least one phrase, the at least one phrase comprising a head term and a modifier associated with the head term; and one or more processors to implement: an aspect module to map respective head terms of a portion of the plurality of comments to an aspect cluster corresponding to an attribute of the entity, and a rating module to determine an aspect rating corresponding to the attribute of the entity based on the respective overall rating of the portion of the plurality of comments, and a module to cause presentation, on a client machine, of a graphical representation of the determined aspect rating corresponding to the attribute of the entity. 7. The system of claim 1 , wherein the aspect module further comprises an aspect estimator to incorporate a topic model corresponding to the aspect cluster. | 0.715328 |
7,546,316 | 30 | 31 | 30. A system comprising: at least one processor configured to execute: heuristics program code for modifying a query string of characters using a set of heuristics; a comparator for performing a character-by-character comparison of the modified query string with at least one known string of characters in a corpus in order to locate an exact match for the modified query string; sub-string formation program code and information retrieval program code for locating an equivalent for the modified query string, responsive to the comparator not finding an exact match for the modified query string in the corpus, said formation program code for forming a plurality of sub-strings of characters from the modified query string, the sub-strings having varying lengths such that at least two of the formed substrings differ in length, each sub-string comprising a composition of characters selected based on a frequency of occurrence of the composition in the modified query string; and said information retrieval program code operating on the sub-strings formed from the modified query string for identifying a known string of characters equivalent to the query string. | 30. A system comprising: at least one processor configured to execute: heuristics program code for modifying a query string of characters using a set of heuristics; a comparator for performing a character-by-character comparison of the modified query string with at least one known string of characters in a corpus in order to locate an exact match for the modified query string; sub-string formation program code and information retrieval program code for locating an equivalent for the modified query string, responsive to the comparator not finding an exact match for the modified query string in the corpus, said formation program code for forming a plurality of sub-strings of characters from the modified query string, the sub-strings having varying lengths such that at least two of the formed substrings differ in length, each sub-string comprising a composition of characters selected based on a frequency of occurrence of the composition in the modified query string; and said information retrieval program code operating on the sub-strings formed from the modified query string for identifying a known string of characters equivalent to the query string. 31. The system of claim 30 , wherein the information retrieval program code further comprises: code for weighting the sub-strings; code for scoring known strings of characters; and code for retrieving information associated with the known string having the highest score. | 0.5 |
10,068,129 | 16 | 17 | 16. In a digital medium environment for identifying an unknown person in an image, a system comprising: at least one processor; and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to: train a cluster classifier for each image cluster of a plurality of image clusters comprising images from an image gallery based on a plurality of known person instances; determine a probability that a first unknown person instance is each known person instance in the image cluster using the cluster classifier of an image cluster that corresponds to the image based on one or more characteristics of the image cluster; determine a context weight for each combination of the first unknown person instance and each known person instance from the plurality of known person instances using a conditional random field algorithm based on a plurality of context cues between one or more of the first unknown person instance and one or more known person instances of the plurality of known person instances or between known person instances of the plurality of known person instances; calculate a contextual probability based on the determined probabilities and the determined context weights; and identify the first unknown person instance as a known person instance from the plurality of known person instances with a highest contextual probability. | 16. In a digital medium environment for identifying an unknown person in an image, a system comprising: at least one processor; and at least one non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to: train a cluster classifier for each image cluster of a plurality of image clusters comprising images from an image gallery based on a plurality of known person instances; determine a probability that a first unknown person instance is each known person instance in the image cluster using the cluster classifier of an image cluster that corresponds to the image based on one or more characteristics of the image cluster; determine a context weight for each combination of the first unknown person instance and each known person instance from the plurality of known person instances using a conditional random field algorithm based on a plurality of context cues between one or more of the first unknown person instance and one or more known person instances of the plurality of known person instances or between known person instances of the plurality of known person instances; calculate a contextual probability based on the determined probabilities and the determined context weights; and identify the first unknown person instance as a known person instance from the plurality of known person instances with a highest contextual probability. 17. The system as recited in claim 16 , further comprising instructions that, when executed by the at least one processor, cause the system to: train a plurality of cluster classifiers for each cluster of the plurality of clusters; determine a probability that the first unknown person instance is each known person instance in the image cluster for each cluster classifier from the plurality of cluster classifiers of the image cluster; and determine a combined probability by generating a weighted average of the probabilities that the first unknown person instance is each known person instance in the image cluster for the plurality of cluster classifiers. | 0.5 |
4,760,606 | 6 | 7 | 6. The digital imaging file processing system of claim 3 further comprising: header page means associated with each group of documents to be digitized for automatically instructing the operation of the system with the use of a coded header page. | 6. The digital imaging file processing system of claim 3 further comprising: header page means associated with each group of documents to be digitized for automatically instructing the operation of the system with the use of a coded header page. 7. The digital imaging file processing system of claim 6 wherein said header page includes instructions relating to the control of the scanner means, control of the storage means and the use, non-use and nature of use of an optical character recognition device. | 0.5 |
8,321,409 | 20 | 21 | 20. The computer program product of claim 19 , wherein the document relationships graph includes nodes representing documents and edges between nodes representing relationships between documents. | 20. The computer program product of claim 19 , wherein the document relationships graph includes nodes representing documents and edges between nodes representing relationships between documents. 21. The computer program product of claim 20 , wherein a first edge representing relationships between first and second documents has a direction from the first document to the second document, wherein the first document is lower in the initial order than the second document. | 0.5 |
8,965,761 | 2 | 4 | 2. A system for differential dynamic content delivery, the system comprising: means for providing to a multiplicity of users a presentation including content from a session document; means for streaming presentation speech to the user including individual speech from at least one user participating in the presentation; means for converting the presentation speech to text; means for detecting whether the presentation speech contains simultaneous individual speech from two or more users; means for displaying the text if the presentation speech contains simultaneous individual speech from two or more users, wherein means for providing to a multiplicity of users a presentation including content from a session document further comprises: means for providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; means for selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and means for presenting the selected structural element to the user; and means for creating a session document from a presentation document, including: means for identifying a presentation document for a presentation, the presentation document including a presentation grammar and a structured document having structural elements classified with classification identifiers; means for identifying a user participant for the presentation, the user having a user profile comprising user classifications; and means for filtering the structured document in dependence upon the user classifications and the classification identifiers. | 2. A system for differential dynamic content delivery, the system comprising: means for providing to a multiplicity of users a presentation including content from a session document; means for streaming presentation speech to the user including individual speech from at least one user participating in the presentation; means for converting the presentation speech to text; means for detecting whether the presentation speech contains simultaneous individual speech from two or more users; means for displaying the text if the presentation speech contains simultaneous individual speech from two or more users, wherein means for providing to a multiplicity of users a presentation including content from a session document further comprises: means for providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; means for selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and means for presenting the selected structural element to the user; and means for creating a session document from a presentation document, including: means for identifying a presentation document for a presentation, the presentation document including a presentation grammar and a structured document having structural elements classified with classification identifiers; means for identifying a user participant for the presentation, the user having a user profile comprising user classifications; and means for filtering the structured document in dependence upon the user classifications and the classification identifiers. 4. The system of claim 2 further comprising means for creating a presentation document, including: means for creating, in dependence upon an original document, a structured document comprising one or more structural elements; means for classifying a structural element of the structured document according to a presentation attribute; and means for creating a presentation grammar for the structured document, wherein the presentation grammar for the structured document includes grammar elements each of which includes an identifier for at least one structural element of the structured document. | 0.5 |
9,160,738 | 19 | 20 | 19. A method according to claim 18 , wherein the reference monitor receives a request for access and credential statement from the first entity over a communication network. | 19. A method according to claim 18 , wherein the reference monitor receives a request for access and credential statement from the first entity over a communication network. 20. A method according to claim 19 , wherein the reference monitor is arranged to formulate the query from the request, and provide the query and the credential statement to the hardware processor. | 0.5 |
8,612,433 | 1 | 7 | 1. A system to provide a search result, the system comprising: a search term reception unit to receive a search term; a processor to extract information corresponding to at least one of a first personal network associated with the search term and a second personal network different than the first personal network; a search result providing unit to provide a document associated with at least one of the first personal network and the second personal network as a search result of the search term; and a neighbor information extraction unit to extract information corresponding to at least one neighbor having interests corresponding to interests of a user, the information corresponding to the at least one neighbor being based, at least in part, on a profile of the user, the profile being configured using keywords in a document prepared by the user, and the search term being received from the user, the keywords being time-variable and corresponding to keywords having the highest frequency of occurrence in the document. | 1. A system to provide a search result, the system comprising: a search term reception unit to receive a search term; a processor to extract information corresponding to at least one of a first personal network associated with the search term and a second personal network different than the first personal network; a search result providing unit to provide a document associated with at least one of the first personal network and the second personal network as a search result of the search term; and a neighbor information extraction unit to extract information corresponding to at least one neighbor having interests corresponding to interests of a user, the information corresponding to the at least one neighbor being based, at least in part, on a profile of the user, the profile being configured using keywords in a document prepared by the user, and the search term being received from the user, the keywords being time-variable and corresponding to keywords having the highest frequency of occurrence in the document. 7. The system of claim 1 , wherein the search result providing unit is configured to provide the document associated with the at least one of the first personal network and the second personal network as a search result of the search term by arranging the document among documents associated with the search term, based on an association between the user providing the search term and the at least one of the first personal network and the second personal network. | 0.581227 |
8,204,748 | 1 | 3 | 1. A method of providing a first communication device with a textual representation of a voice message transmitted from a second communication device, the method comprising: detecting that the first communication device is operating in a silent mode in which the first communication device is switched on but wherein calls are directly routed to a user's messaging system; in response to said detection, prompting a user of the second communication device to input a voice message; converting the input voice message to phonemes; accessing a dictionary of words and their corresponding phonemes to identify, where present, a word which corresponds to a group of the phonemes; for each phoneme not recognized as part of a word in the dictionary, representing the phoneme as a representative character; and automatically transmitting a textual representation of the converted voice message to the first communication device, the representation including characters based on the phonemes and words identified in the dictionary that correspond to a group of the phonemes. | 1. A method of providing a first communication device with a textual representation of a voice message transmitted from a second communication device, the method comprising: detecting that the first communication device is operating in a silent mode in which the first communication device is switched on but wherein calls are directly routed to a user's messaging system; in response to said detection, prompting a user of the second communication device to input a voice message; converting the input voice message to phonemes; accessing a dictionary of words and their corresponding phonemes to identify, where present, a word which corresponds to a group of the phonemes; for each phoneme not recognized as part of a word in the dictionary, representing the phoneme as a representative character; and automatically transmitting a textual representation of the converted voice message to the first communication device, the representation including characters based on the phonemes and words identified in the dictionary that correspond to a group of the phonemes. 3. The method of claim 1 , wherein the phonemes are selected from a finite set of phonemes and wherein each phoneme is associated with a representative character and wherein the representation of phonemes not recognized as part of a word includes representing the phoneme as its representative character. | 0.5 |
9,754,020 | 18 | 19 | 18. The method of claim 17 , wherein said step of normalizing includes the steps of: defining a set of reference words; calculating a word pair relevancy for each reference word relative to the keyword; and calculating the normalized word pair relevancy measure based upon said word pair relevancy for each reference word relative to the keyword. | 18. The method of claim 17 , wherein said step of normalizing includes the steps of: defining a set of reference words; calculating a word pair relevancy for each reference word relative to the keyword; and calculating the normalized word pair relevancy measure based upon said word pair relevancy for each reference word relative to the keyword. 19. The method of claim 18 , wherein said normalized word pair relevancy is defined as: s d , k ′ = s d , k - μ k ( A ) σ k ( A ) wherein , μ k ( A ) = 1 A ∑ a ∈ A s a , k , and σ k ( A ) = ( 1 A ∑ a ∈ A s a , k 2 ) - ( 1 A ∑ a ∈ A s a , k ) 2 | 0.5 |
9,152,625 | 1 | 6 | 1. A method comprising: processing, using a computing device, multiple resources to build a word dictionary configured to enable summarizing a plurality of microblogs, the word dictionary containing individual words that are nouns that are associated with a particular domain; using, using the computing device, the word dictionary to create concepts, at least some individual concepts comprising a semantic tag comprising multiple words; assigning, using the computing device, a plurality of microblogs to a plurality of the concepts effective to form potential clusters; computing, using the computing device, a membership score for each microblog/cluster pairing; using, using the computing device, the membership score to assign a microblog to a cluster; ranking, using the computing device, each cluster using an entropy measure that incorporates sentiment value computed for each microblog and probability of words computed over microblogs in a particular cluster, and summarizing the plurality of microblogs by displaying a cluster summary for each cluster on a display of the computing device. | 1. A method comprising: processing, using a computing device, multiple resources to build a word dictionary configured to enable summarizing a plurality of microblogs, the word dictionary containing individual words that are nouns that are associated with a particular domain; using, using the computing device, the word dictionary to create concepts, at least some individual concepts comprising a semantic tag comprising multiple words; assigning, using the computing device, a plurality of microblogs to a plurality of the concepts effective to form potential clusters; computing, using the computing device, a membership score for each microblog/cluster pairing; using, using the computing device, the membership score to assign a microblog to a cluster; ranking, using the computing device, each cluster using an entropy measure that incorporates sentiment value computed for each microblog and probability of words computed over microblogs in a particular cluster, and summarizing the plurality of microblogs by displaying a cluster summary for each cluster on a display of the computing device. 6. The method of claim 1 , wherein using the word dictionary to create concepts comprises utilizing, using the computing device, a hypernym path, the semantic tag comprising multiple words from the hypernym path. | 0.805861 |
9,665,615 | 1 | 7 | 1. A computer-implemented method of accessing data, comprising: identifying an entity in a relational database; identifying look-up metadata used to locate the entity in the relational database; using an indexing component to generate an index based on one or more fields of the entity in the relational database, wherein the index is separate from the relational database and stores the look-up metadata; receiving an indication of a first character input, of a multi character query, in a search user input mechanism; prior to acting on a subsequent character input of the multi character query, searching the index based on the first character input to obtain a search result corresponding to the entity; receiving an indication of user selection of the search result; and based on the indication of user selection of the search result, accessing the entity in the relational database using the look-up metadata stored in the index, wherein accessing the entity in the relational database using the look-up metadata stored in the index comprises: locating a data record in the relational database using the look-up metadata, the data record corresponding to the entity; identifying a data field in the data record; and generating a representation of a results user interface display that displays the data field. | 1. A computer-implemented method of accessing data, comprising: identifying an entity in a relational database; identifying look-up metadata used to locate the entity in the relational database; using an indexing component to generate an index based on one or more fields of the entity in the relational database, wherein the index is separate from the relational database and stores the look-up metadata; receiving an indication of a first character input, of a multi character query, in a search user input mechanism; prior to acting on a subsequent character input of the multi character query, searching the index based on the first character input to obtain a search result corresponding to the entity; receiving an indication of user selection of the search result; and based on the indication of user selection of the search result, accessing the entity in the relational database using the look-up metadata stored in the index, wherein accessing the entity in the relational database using the look-up metadata stored in the index comprises: locating a data record in the relational database using the look-up metadata, the data record corresponding to the entity; identifying a data field in the data record; and generating a representation of a results user interface display that displays the data field. 7. The computer-implemented method of claim 1 and further comprising: automatically generating an association in the relational database between a target entity and the identified entity. | 0.772506 |
8,234,561 | 50 | 51 | 50. The software product of claim 40 , the operations further comprising, before predicting a value for the current form field object, adjusting the generated likelihood assessments based on a determined characteristic of the possible values. | 50. The software product of claim 40 , the operations further comprising, before predicting a value for the current form field object, adjusting the generated likelihood assessments based on a determined characteristic of the possible values. 51. The software product of claim 50 , wherein the determined characteristic of the possible values comprises frequency of common session use for the possible values in relation to values already entered in a current form instance. | 0.5 |
7,966,172 | 1 | 5 | 1. A method for creating an expression to specify a subset of data, comprising: receiving a selection of a command; in response to receiving the selection of the command, displaying a natural language expression that includes the command and at least a first changeable field embedded in the displayed natural language expression; receiving a indication of first data for the first changeable embedded field from a direct interaction with the displayed natural language expression; modifying the natural language expression in response to the first data and displaying the modified natural language expression; displaying an add field indicator; receiving a selection of the add field indicator from a direct interaction with the displayed natural language expression; in response to the selection of the add field indicator, adding a second changeable field embedded in the natural language expression and displaying the natural language expression with the second changeable field embedded in the displayed natural language expression; receiving an indication of second data for the second changeable embedded field from a direct interaction with the displayed natural language expression; and modifying the natural language expression in response to the second data and displaying the modified natural language expression. | 1. A method for creating an expression to specify a subset of data, comprising: receiving a selection of a command; in response to receiving the selection of the command, displaying a natural language expression that includes the command and at least a first changeable field embedded in the displayed natural language expression; receiving a indication of first data for the first changeable embedded field from a direct interaction with the displayed natural language expression; modifying the natural language expression in response to the first data and displaying the modified natural language expression; displaying an add field indicator; receiving a selection of the add field indicator from a direct interaction with the displayed natural language expression; in response to the selection of the add field indicator, adding a second changeable field embedded in the natural language expression and displaying the natural language expression with the second changeable field embedded in the displayed natural language expression; receiving an indication of second data for the second changeable embedded field from a direct interaction with the displayed natural language expression; and modifying the natural language expression in response to the second data and displaying the modified natural language expression. 5. The method of claim 1 , further comprising: accessing a set of data, the natural language expression identifies a subset of the set of data; determining a condition of the set of data; and pre-populating at least a portion of the natural language expression based on the determined condition, the pre-populating includes adding the command to the natural language expression, the selection of the command includes accepting the adding of the command to the natural language expression. | 0.766953 |
10,063,582 | 15 | 19 | 15. One or more non-transitory computer-readable media comprising one or more computer-readable instructions that, when executed by one or more processors of one or more computing devices, cause the one or more computing devices to perform a method comprising: (a) identifying a Positive Unlabeled (PU) machine learning classifier; (b) selecting labeled positive samples and unlabeled positive and negative samples as a bootstrap subset of training data from a set of training data; (c) training the PU machine learning classifier with the bootstrap subset of training data; (d) repeating (a)-(c) one or more times to create a set of trained PU machine learning classifiers; (e) predicting probabilities that a network device in a network has been compromised using each of the trained PU machine learning classifiers in the set of trained PU machine learning classifiers; (f) combining the probabilities predicted at (e) to generate a combined risk score for the network device; (g) repeating (e)-(f) one or more times to create a ranked list of combined risk scores; and (h) performing a security action on one or more of the network devices in the ranked list. | 15. One or more non-transitory computer-readable media comprising one or more computer-readable instructions that, when executed by one or more processors of one or more computing devices, cause the one or more computing devices to perform a method comprising: (a) identifying a Positive Unlabeled (PU) machine learning classifier; (b) selecting labeled positive samples and unlabeled positive and negative samples as a bootstrap subset of training data from a set of training data; (c) training the PU machine learning classifier with the bootstrap subset of training data; (d) repeating (a)-(c) one or more times to create a set of trained PU machine learning classifiers; (e) predicting probabilities that a network device in a network has been compromised using each of the trained PU machine learning classifiers in the set of trained PU machine learning classifiers; (f) combining the probabilities predicted at (e) to generate a combined risk score for the network device; (g) repeating (e)-(f) one or more times to create a ranked list of combined risk scores; and (h) performing a security action on one or more of the network devices in the ranked list. 19. The one or more non-transitory computer-readable media of claim 15 , wherein the method is performed in a Security Information and Event Management (SIEM) application. | 0.80254 |
9,317,760 | 15 | 16 | 15. A system of determining an input character based upon character recognition output, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive a proposed value generated using character recognition, wherein the proposed value is associated with at least one handwritten character of an assessment, and determine whether the proposed value is correct, by: determining a posterior probability associated with each of one or more possible characters, identifying the possible character associated with the posterior probability having a highest value, and in response to identifying the proposed value as the possible character associated with the posterior probability having a highest value, determining, by the processing device, that the proposed value is correct, otherwise, determining that the proposed value is incorrect. | 15. A system of determining an input character based upon character recognition output, the system comprising: a computing device; and a non-transitory computer-readable storage medium in communication with the computing device, wherein the computer-readable storage medium comprises one or more programming instructions that, when executed, cause the computing device to: receive a proposed value generated using character recognition, wherein the proposed value is associated with at least one handwritten character of an assessment, and determine whether the proposed value is correct, by: determining a posterior probability associated with each of one or more possible characters, identifying the possible character associated with the posterior probability having a highest value, and in response to identifying the proposed value as the possible character associated with the posterior probability having a highest value, determining, by the processing device, that the proposed value is correct, otherwise, determining that the proposed value is incorrect. 16. The system of claim 15 , wherein the one or more programming instructions that, when executed, cause the computing device to determine a posterior probability associated with each of one or more possible characters comprise one or more programming instructions that, when executed, cause the computing device to: determine a probability of evidence value; determine a prior probability value; determine a prior probability of evidence value; determine a product of the probability of evidence value and prior probability value; and determine a ratio of the product and the prior probability of evidence value. | 0.5 |
9,965,469 | 9 | 16 | 9. A system for dynamically producing a document with transformed terms comprising: a computer system including at least one processor configured to: analyze a retrieved document using one or more natural language processing (NLP) translation techniques to identify one or more terms with equivalent expressions in the same natural language and provide annotations, wherein at least one equivalent expression includes an equivalent numerical expression and an annotation for corresponding identified terms of the equivalent numerical expression includes values and a mathematical operation to determine the equivalent numerical expression; transform the identified terms to the equivalent expressions identified by the one or more NLP translation techniques based on at least the annotations, wherein the mathematical operation is performed on the values to produce the equivalent numerical expression; and produce a transformed document for display by replacing the identified one or more terms in the retrieved document with the equivalent expressions. | 9. A system for dynamically producing a document with transformed terms comprising: a computer system including at least one processor configured to: analyze a retrieved document using one or more natural language processing (NLP) translation techniques to identify one or more terms with equivalent expressions in the same natural language and provide annotations, wherein at least one equivalent expression includes an equivalent numerical expression and an annotation for corresponding identified terms of the equivalent numerical expression includes values and a mathematical operation to determine the equivalent numerical expression; transform the identified terms to the equivalent expressions identified by the one or more NLP translation techniques based on at least the annotations, wherein the mathematical operation is performed on the values to produce the equivalent numerical expression; and produce a transformed document for display by replacing the identified one or more terms in the retrieved document with the equivalent expressions. 16. The system of claim 9 , wherein transforming each of the identified terms comprises: traversing a state machine to determine whether the identified one or more terms are stored in a dictionary containing transformation information. | 0.581851 |
8,538,982 | 25 | 30 | 25. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: while receiving a first text input entered in a search engine query input field by a first user, and before the first user has submitted the first text input as a search request: deriving, in a data processing system, a first dominant query from the first text input, wherein deriving the first dominant query includes: determining that the first text input is missing information needed to trigger an answer box; obtaining the needed information from user profile data for the first user, including analyzing the user profile data for the first user to determine that a particular category of answer box is relevant to the first user; and generating the first dominant query from the first text input, the needed information, and the particular category of answer box; obtaining, by the system, content for a first answer box associated with the first dominant query; and presenting the first answer box to the first user. | 25. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: while receiving a first text input entered in a search engine query input field by a first user, and before the first user has submitted the first text input as a search request: deriving, in a data processing system, a first dominant query from the first text input, wherein deriving the first dominant query includes: determining that the first text input is missing information needed to trigger an answer box; obtaining the needed information from user profile data for the first user, including analyzing the user profile data for the first user to determine that a particular category of answer box is relevant to the first user; and generating the first dominant query from the first text input, the needed information, and the particular category of answer box; obtaining, by the system, content for a first answer box associated with the first dominant query; and presenting the first answer box to the first user. 30. The computer-readable medium of claim 25 , wherein generating the first dominant query includes: identifying, from a user search history for the first user, one or more queries submitted by the first user that begin with text matching the first text input; and identifying the first dominant query from the one or more queries based on the first dominant query appearing in the user search history a number of times that satisfies a threshold. | 0.594374 |
6,061,654 | 1 | 2 | 1. A method of recognizing an identifier entered by a user, the identifier including a first plurality of predetermined characters, wherein the characters are selected from a first set of characters, the first set of characters having a first total number of characters, the method comprising the steps of: a) providing a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; b) providing a plurality of reference identifiers, each one of the plurality of reference identifiers comprising a different plurality of predetermined characters, each one of the different plurality of predetermined characters belonging to the first set of characters; c) providing a first arrangement of character recognition probabilities, the first arrangement of character recognition probabilities encompassing a second set of characters having a second total number of characters and is a superset of the characters of the first set of characters; d) producing a constrained arrangement of character recognition probabilities by constraining the first arrangement of character recognition probabilities to encompass a third set of characters constituting a subset of the second set of characters; e) obtaining, for each character position in at least one of the reference identifiers and each character position in the recognized identifier, from the constrained arrangement of character recognition probabilities, a probability that a character in the at least one reference identifier is recognized as a character found in the corresponding character position in the recognized identifier; f) determining an identifier recognition probability based on the obtained probabilities; g) repeating steps e) and f) for every reference identifier in the plurality of reference identifiers, each one of the plurality of reference identifiers being associated with a corresponding identifier recognition probability; and h) selecting the reference identifier most likely matching the entered identifier based on the plurality of obtained recognition probabilities. | 1. A method of recognizing an identifier entered by a user, the identifier including a first plurality of predetermined characters, wherein the characters are selected from a first set of characters, the first set of characters having a first total number of characters, the method comprising the steps of: a) providing a recognized identifier based on the entered identifier, the recognized identifier comprising a second plurality of predetermined characters; b) providing a plurality of reference identifiers, each one of the plurality of reference identifiers comprising a different plurality of predetermined characters, each one of the different plurality of predetermined characters belonging to the first set of characters; c) providing a first arrangement of character recognition probabilities, the first arrangement of character recognition probabilities encompassing a second set of characters having a second total number of characters and is a superset of the characters of the first set of characters; d) producing a constrained arrangement of character recognition probabilities by constraining the first arrangement of character recognition probabilities to encompass a third set of characters constituting a subset of the second set of characters; e) obtaining, for each character position in at least one of the reference identifiers and each character position in the recognized identifier, from the constrained arrangement of character recognition probabilities, a probability that a character in the at least one reference identifier is recognized as a character found in the corresponding character position in the recognized identifier; f) determining an identifier recognition probability based on the obtained probabilities; g) repeating steps e) and f) for every reference identifier in the plurality of reference identifiers, each one of the plurality of reference identifiers being associated with a corresponding identifier recognition probability; and h) selecting the reference identifier most likely matching the entered identifier based on the plurality of obtained recognition probabilities. 2. The method according to claim 1, wherein each one of the entered identifier, the recognized identifier, and the plurality of reference identifiers comprises a plurality of alphanumeric characters. | 0.910842 |
7,644,062 | 1 | 9 | 1. A computer implemented method, comprising: transforming a base query to generate a transformed query; wherein the base query includes a union between each base branch of a plurality of base branches; wherein each of two or more base branches of said plurality of base branches joins a set of tables; wherein the sets of tables of the two or more base branches of the plurality of base branches include a common table set shared by all the sets of tables, said common table set including a common table; wherein each of the two or more base branches of the plurality of base branches include a respective set of tables that does not include said common table set; wherein the step of transforming the base query includes replacing the plurality of base branches with a first group branch that joins the common table and an inline view, the inline view comprising a union between a plurality of respective branches, wherein the plurality of respective branches includes, for each base branch of said plurality of base branches, a FROM list that: references the respective set of tables, and does not reference the common table; and wherein the method is performed by one or more computing devices. | 1. A computer implemented method, comprising: transforming a base query to generate a transformed query; wherein the base query includes a union between each base branch of a plurality of base branches; wherein each of two or more base branches of said plurality of base branches joins a set of tables; wherein the sets of tables of the two or more base branches of the plurality of base branches include a common table set shared by all the sets of tables, said common table set including a common table; wherein each of the two or more base branches of the plurality of base branches include a respective set of tables that does not include said common table set; wherein the step of transforming the base query includes replacing the plurality of base branches with a first group branch that joins the common table and an inline view, the inline view comprising a union between a plurality of respective branches, wherein the plurality of respective branches includes, for each base branch of said plurality of base branches, a FROM list that: references the respective set of tables, and does not reference the common table; and wherein the method is performed by one or more computing devices. 9. The method of claim 1 , wherein the plurality of base branches are contained with a query block within the base query. | 0.888787 |
9,542,182 | 6 | 8 | 6. A computer program product for providing for standardization of variable names in an integrated development environment, the computer program product comprising: one or more computer-readable tangible storage devices and program instructions stored on the one or more computer-readable tangible storage devices, wherein the one or more computer-readable tangible storage devices are hardware, and the one or more computer-readable tangible storage devices are not a transitory signal per se, the program instructions comprising: program instructions to scan a project source code for variable names, the project source code managed by a development team in an integrated development environment, wherein a variable name is determined based, at least in part, on whether the variable name includes one or more mutations to a root word of a standard variable name, and at least one of one or more inheritance relationships for the standard variable name, and one or more general rules for variable names; program instructions to determine the project source code contains a non-standard variable name, wherein the non-standard variable name is a variable name that is not stored as a standard variable name determined by the development team; program instructions to identify a location of the non-standard variable name in the project source code, the location identified to the development team by a notification and wherein the notification includes at least a highlight of the non-standard variable name; program instructions to determine whether the non-standard variable name is added to a database, wherein adding the non-standard variable name in the database indicates approval of the non-standard variable name; program instructions to determine the project source code contains one or more standard variable names; responsive to determining the project source code contains one or more standard variable names, program instructions to store the one or more standard variable names in the database; and program instructions to use the database to standardize new source code by auto-completion of one or more variable names while the new source code is being written. | 6. A computer program product for providing for standardization of variable names in an integrated development environment, the computer program product comprising: one or more computer-readable tangible storage devices and program instructions stored on the one or more computer-readable tangible storage devices, wherein the one or more computer-readable tangible storage devices are hardware, and the one or more computer-readable tangible storage devices are not a transitory signal per se, the program instructions comprising: program instructions to scan a project source code for variable names, the project source code managed by a development team in an integrated development environment, wherein a variable name is determined based, at least in part, on whether the variable name includes one or more mutations to a root word of a standard variable name, and at least one of one or more inheritance relationships for the standard variable name, and one or more general rules for variable names; program instructions to determine the project source code contains a non-standard variable name, wherein the non-standard variable name is a variable name that is not stored as a standard variable name determined by the development team; program instructions to identify a location of the non-standard variable name in the project source code, the location identified to the development team by a notification and wherein the notification includes at least a highlight of the non-standard variable name; program instructions to determine whether the non-standard variable name is added to a database, wherein adding the non-standard variable name in the database indicates approval of the non-standard variable name; program instructions to determine the project source code contains one or more standard variable names; responsive to determining the project source code contains one or more standard variable names, program instructions to store the one or more standard variable names in the database; and program instructions to use the database to standardize new source code by auto-completion of one or more variable names while the new source code is being written. 8. The computer program product of claim 6 , further comprising program instructions to determine the adding of the non-standard variable name to the database is associated with a level of permission corresponding to permission to add, remove, or edit variable names in the database. | 0.5 |
8,869,019 | 1 | 5 | 1. A method executed by a computing device, comprising: parsing a set of one or more web pages of a website; generating a first plurality of n-grams based on at least content that is included on the set of one or more web pages, wherein n is at least two; determining a relevancy value for each of the first plurality of n-grams; generating a second plurality of n-grams based on at least removing any of the first plurality of n-grams whose corresponding relevancy value is below a relevancy value threshold; for each one of the second plurality of n-grams, determining whether that one of the second plurality of n-grams is similar to another one of the second plurality of n-grams, generating a third plurality of n-grams based on at least removing any of those second plurality of n-grams that have been determined as being similar to another one of the second plurality of n-grams; for at least one of the third plurality of n-grams, determining whether there is at least one of the set of web pages of the website that that is directed at content regarding that n-gram; and responsive to determining that there is not at least one of the set of web pages of the website that is directed at content regarding the at least one of the third plurality of n-grams, performing the following: automatically creating a web page with content directed at the at least one of the third plurality of n-grams, wherein automatically creating the web page includes, using a same template of the website for the created web page, inserting content into the created web page with existing content of the website that is related to the at least one of the third plurality of n-grams, and adding a title for the created web page based on the at least one of the third plurality of n-grams; providing the created web page in a graphical editor for a user to review the created web page; and creating a set of one or more links to the reviewed and created web page on one or more of the set of web pages of the website so that the created web page is not an orphan web page. | 1. A method executed by a computing device, comprising: parsing a set of one or more web pages of a website; generating a first plurality of n-grams based on at least content that is included on the set of one or more web pages, wherein n is at least two; determining a relevancy value for each of the first plurality of n-grams; generating a second plurality of n-grams based on at least removing any of the first plurality of n-grams whose corresponding relevancy value is below a relevancy value threshold; for each one of the second plurality of n-grams, determining whether that one of the second plurality of n-grams is similar to another one of the second plurality of n-grams, generating a third plurality of n-grams based on at least removing any of those second plurality of n-grams that have been determined as being similar to another one of the second plurality of n-grams; for at least one of the third plurality of n-grams, determining whether there is at least one of the set of web pages of the website that that is directed at content regarding that n-gram; and responsive to determining that there is not at least one of the set of web pages of the website that is directed at content regarding the at least one of the third plurality of n-grams, performing the following: automatically creating a web page with content directed at the at least one of the third plurality of n-grams, wherein automatically creating the web page includes, using a same template of the website for the created web page, inserting content into the created web page with existing content of the website that is related to the at least one of the third plurality of n-grams, and adding a title for the created web page based on the at least one of the third plurality of n-grams; providing the created web page in a graphical editor for a user to review the created web page; and creating a set of one or more links to the reviewed and created web page on one or more of the set of web pages of the website so that the created web page is not an orphan web page. 5. The method of claim 1 , wherein determining the relevancy value for each of the first plurality of n-grams includes performing a term frequency-inverse document frequency (TF-IDF) on each of those n-grams. | 0.883277 |
9,487,167 | 7 | 8 | 7. The vehicle of claim 1 , wherein the one or more processors are further configured to: identify a learn new input indication; track, based at least in part upon identifying the learn new input indication, one or more learn new user inputs; and associate the tracked one or more learn new user inputs with a learn new input function. | 7. The vehicle of claim 1 , wherein the one or more processors are further configured to: identify a learn new input indication; track, based at least in part upon identifying the learn new input indication, one or more learn new user inputs; and associate the tracked one or more learn new user inputs with a learn new input function. 8. The vehicle of claim 7 , wherein the one or more processors are further configured to: direct an output of a prompt for a user to speak one or more words associated with a first grammar element to be associated with control of the learn new input function; receive audio data collected in response to the prompt; and associate at least a portion of the received audio data with the first grammar element. | 0.5 |
7,826,672 | 30 | 31 | 30. The method of claim 23 , further comprising: preprocessing the stream of data to perform an initial compression; analyzing the preprocessed stream of data in order to identify sequences of data that occur more than once; calculating for each instance of such a repeating sequence of data, how much intervening data occurs in the preprocessed stream of data between the instance and a previous instance; carrying out a local dictionary encoding process comprising, for each repeating sequence of data for which the sum of the size of the intervening data and the size of the sequence of data does not exceed a predetermined threshold value, replacing the sequence of data with a reference to a location in an internal memory of a local dictionary decoder at which the previous instance may be found during decoding of the stream of data by the local dictionary decoder; and forwarding the output of the local dictionary encoding process to a global dictionary encoding process comprising replacing at least a portion of the remaining repeating sequences with references to a location in an external memory to be used by a global dictionary decoder at which a representation of the repeating sequence may be found during decoding of the stream of data by the global dictionary decoder. | 30. The method of claim 23 , further comprising: preprocessing the stream of data to perform an initial compression; analyzing the preprocessed stream of data in order to identify sequences of data that occur more than once; calculating for each instance of such a repeating sequence of data, how much intervening data occurs in the preprocessed stream of data between the instance and a previous instance; carrying out a local dictionary encoding process comprising, for each repeating sequence of data for which the sum of the size of the intervening data and the size of the sequence of data does not exceed a predetermined threshold value, replacing the sequence of data with a reference to a location in an internal memory of a local dictionary decoder at which the previous instance may be found during decoding of the stream of data by the local dictionary decoder; and forwarding the output of the local dictionary encoding process to a global dictionary encoding process comprising replacing at least a portion of the remaining repeating sequences with references to a location in an external memory to be used by a global dictionary decoder at which a representation of the repeating sequence may be found during decoding of the stream of data by the global dictionary decoder. 31. The method of claim 30 , wherein the predetermined threshold value is determined according to a capacity of the internal memory. | 0.676471 |
7,558,737 | 1 | 23 | 1. A computer-implemented method for validating one entity for another entity, comprising: classifying an entity type of an entity to be validated based on one or more predefined entity classifiers; selecting one or more validation rules based on the classification of the entity; producing, by a computer of a requesting entity, a validation request including an identification of the entity to be validated and the selected one or more validation rules; providing, by the computer, the validation request to one or more validation entities that perform at least a portion of the validation in accordance with the validation rules; providing to the computer of the requesting entity a validation outcome of the validation; and generating a validation request management display including an inbox icon, an outbox icon, an overview section, and a details section, wherein: responsive to selection of the inbox icon, the overview section displays a list of validation outcomes that have been received and the details section displays detailed information regarding a selected one of the listed validation outcomes; and responsive to selection of the outbox icon, the overview section displays a list of validation requests that have been provided to validation entities and the details section displays detailed information regarding a selected one of the listed validation requests. | 1. A computer-implemented method for validating one entity for another entity, comprising: classifying an entity type of an entity to be validated based on one or more predefined entity classifiers; selecting one or more validation rules based on the classification of the entity; producing, by a computer of a requesting entity, a validation request including an identification of the entity to be validated and the selected one or more validation rules; providing, by the computer, the validation request to one or more validation entities that perform at least a portion of the validation in accordance with the validation rules; providing to the computer of the requesting entity a validation outcome of the validation; and generating a validation request management display including an inbox icon, an outbox icon, an overview section, and a details section, wherein: responsive to selection of the inbox icon, the overview section displays a list of validation outcomes that have been received and the details section displays detailed information regarding a selected one of the listed validation outcomes; and responsive to selection of the outbox icon, the overview section displays a list of validation requests that have been provided to validation entities and the details section displays detailed information regarding a selected one of the listed validation requests. 23. The method of claim 1 , wherein the classification is performed by the computer. | 0.882682 |
8,615,070 | 1 | 5 | 1. A method for improving user satisfaction of a user at a user machine, said method comprising: prompting, by a computer, 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. | 1. A method for improving user satisfaction of a user at a user machine, said method comprising: prompting, by a computer, 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. 5. The method of claim 1 , wherein the computer is located at a web site, wherein the user machine is separated from the web site by a web network, and wherein the method further comprises: said computer detecting an attempt by the user machine to access the web site via the web network, wherein said prompting is in response to said detecting. | 0.743685 |
7,849,148 | 76 | 95 | 76. The computer program product of claim 75 , and further comprising computer code for displaying, in response to a first user interaction, the first additional information associated with the first message, utilizing the at least one window. | 76. The computer program product of claim 75 , and further comprising computer code for displaying, in response to a first user interaction, the first additional information associated with the first message, utilizing the at least one window. 95. The computer program product of claim 76 , wherein the computer program product is configured such that the first additional information is displayed utilizing a static object. | 0.717868 |
10,102,199 | 1 | 5 | 1. A method for completing a question comprising: receiving, from a user, a question prefix representing a portion of a natural language question; selecting, based on the question prefix, at least one index comprising a short text index or a question term index, the short text index comprising a plurality of text entries, each entry corresponding to an associated document, the question term index comprising a plurality of question entries, each entry corresponding to a partial question phrase; searching the selected at least one index using the question prefix and retrieving a plurality of retrieved entries; selecting a subset of the plurality of retrieved entries; responsive to selecting the subset, creating a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability; creating a plurality of question completion suggestions based on the language model and the question prefix; and causing presentation of the plurality of question completion suggestions to the user via a user interface. | 1. A method for completing a question comprising: receiving, from a user, a question prefix representing a portion of a natural language question; selecting, based on the question prefix, at least one index comprising a short text index or a question term index, the short text index comprising a plurality of text entries, each entry corresponding to an associated document, the question term index comprising a plurality of question entries, each entry corresponding to a partial question phrase; searching the selected at least one index using the question prefix and retrieving a plurality of retrieved entries; selecting a subset of the plurality of retrieved entries; responsive to selecting the subset, creating a language model from the subset, the language model comprising a plurality of n-grams each with an n-gram probability; creating a plurality of question completion suggestions based on the language model and the question prefix; and causing presentation of the plurality of question completion suggestions to the user via a user interface. 5. The method of claim 1 wherein creating the plurality of question completion suggestions comprises: generating a set of candidate completion suggestions based on the question prefix and the language model; removing from the set of candidate completion suggestions candidate completion suggestions that do not comply with a set of grammar rules to create a subset of candidate completion suggestions; and filtering the subset of candidate completion suggestions based on a filter criteria; and ranking the filtered subset. | 0.546007 |
9,729,525 | 11 | 14 | 11. A computer program product including a non-transitory, computer-readable storage medium which stores executable code, which when executed by a client computer, causes the client computer to perform a method of performing a query, the method comprising: receiving, by processing circuitry, bits representing concealed query logic, the concealed query logic being generated from a query function and encrypted query input, the encrypted query input being produced by an encryption operation on query input; and in response to unencrypted query data being input into the concealed query logic: performing an unconcealing operation on the concealed query logic to produce the query function and the query input; and inputting the unencrypted query data and the unencrypted query input into the second query function to produce a readable query result; and in response to encrypted query data being input into the concealed query logic, producing, by the processing circuitry, a concealed query result based on the encrypted query data and the concealed query logic, the concealed query result, when unconcealed, producing an encrypted query result. | 11. A computer program product including a non-transitory, computer-readable storage medium which stores executable code, which when executed by a client computer, causes the client computer to perform a method of performing a query, the method comprising: receiving, by processing circuitry, bits representing concealed query logic, the concealed query logic being generated from a query function and encrypted query input, the encrypted query input being produced by an encryption operation on query input; and in response to unencrypted query data being input into the concealed query logic: performing an unconcealing operation on the concealed query logic to produce the query function and the query input; and inputting the unencrypted query data and the unencrypted query input into the second query function to produce a readable query result; and in response to encrypted query data being input into the concealed query logic, producing, by the processing circuitry, a concealed query result based on the encrypted query data and the concealed query logic, the concealed query result, when unconcealed, producing an encrypted query result. 14. A computer program product as in claim 11 , wherein the query function is represented by a set of truth tables, each of the set of truth tables having entries, each entry of that truth table having a value of a server bit, a value of an input bit, and a value of an output bit, wherein the concealed query logic includes, for each of the set of truth tables representing the query function, a respective concealed truth table, the respective concealed truth table replacing the values of the server bits and the client bits of that truth table with random binary strings and replacing the values of the output bits with encrypted binary strings, each of the encrypted binary strings resulting from a respective encryption operation on one of two possible output bitstrings, and wherein performing an unconcealing operation on the concealed query logic includes, for each of the set of truth tables, producing that truth table from the respective concealed truth table. | 0.5 |
10,089,555 | 1 | 8 | 1. A method executed by a processor of an optical character recognition (OCR) accuracy testing apparatus for testing an OCR process on a healthcare document, the method comprising: receiving an original text file and a template for the healthcare document, the healthcare document being one of an electronic health record, a lab result, a patient visit record, a triage report, an emergency room report, or a surgery report, wherein the original text file comprises machine-readable text, wherein the template defines a font and a layout to be applied to the text in the original text file; automatically converting the original text file according to the font and the layout defined by the template to generate a plurality of images of different file formats, each image in the plurality of images having pixels indicative of the text, an associated resolution, and the font and the layout defined by the template; causing the OCR process to be executed for each image in the plurality of images to generate a converted text file for each image, the converted text file for each image comprising second machine-readable text, wherein the second machine-readable text is based upon the pixels; calculating, with the processor, an accuracy score of the OCR process for each image in the plurality of the images based on a comparison of the text in the original text file and the second text in the converted text file for each image; and flagging an image in the plurality of images when an accuracy score of the OCR process associated with the image is below a threshold score, wherein flagging the image indicates that a problem exists in the OCR process with respect to a file format of the image and the template. | 1. A method executed by a processor of an optical character recognition (OCR) accuracy testing apparatus for testing an OCR process on a healthcare document, the method comprising: receiving an original text file and a template for the healthcare document, the healthcare document being one of an electronic health record, a lab result, a patient visit record, a triage report, an emergency room report, or a surgery report, wherein the original text file comprises machine-readable text, wherein the template defines a font and a layout to be applied to the text in the original text file; automatically converting the original text file according to the font and the layout defined by the template to generate a plurality of images of different file formats, each image in the plurality of images having pixels indicative of the text, an associated resolution, and the font and the layout defined by the template; causing the OCR process to be executed for each image in the plurality of images to generate a converted text file for each image, the converted text file for each image comprising second machine-readable text, wherein the second machine-readable text is based upon the pixels; calculating, with the processor, an accuracy score of the OCR process for each image in the plurality of the images based on a comparison of the text in the original text file and the second text in the converted text file for each image; and flagging an image in the plurality of images when an accuracy score of the OCR process associated with the image is below a threshold score, wherein flagging the image indicates that a problem exists in the OCR process with respect to a file format of the image and the template. 8. The method of claim 1 , wherein the font and layout are applied to the text during the conversion of the original text file to the plurality of images of different file formats. | 0.859155 |
8,738,595 | 1 | 2 | 1. A computer-implemented method for facilitating location based full text search, the method comprising: receiving a location value; receiving a search term; interweaving characters of the location value and the search term to create an interwoven bit vector of alternating portions of characters of the the search term and the location value; querying an index using the interwoven bit vector; and receiving, based on the querying, a result set that is associated with the search term and the location value. | 1. A computer-implemented method for facilitating location based full text search, the method comprising: receiving a location value; receiving a search term; interweaving characters of the location value and the search term to create an interwoven bit vector of alternating portions of characters of the the search term and the location value; querying an index using the interwoven bit vector; and receiving, based on the querying, a result set that is associated with the search term and the location value. 2. The method of claim 1 , wherein the location value is a first character string, wherein the search term is a second character string, and wherein the interwoven bit vector comprises an interwoven character string containing alternating portions of characters of the first character string and the second character string. | 0.78628 |
8,433,998 | 13 | 14 | 13. The tool of claim 12 , wherein said annotated event map comprises plural event maps which are associated with plural events and stored in said storage device. | 13. The tool of claim 12 , wherein said annotated event map comprises plural event maps which are associated with plural events and stored in said storage device. 14. The tool of claim 13 , further comprising: a search unit for performing a search of said plural event maps based on search criteria input to said search unit by a user. | 0.5 |
7,987,443 | 1 | 5 | 1. A computer-based user interface comprising: a dialog control element that executes on a computer for usage in creating a dialog, configured to receive and act upon a data model containing recursive data structures comprising at least one object defined by at least one property and modifiable by at least one control, the dialog control element further configured to associate object properties with controls recursively whereby properties contain objects which further contain properties and responsive to a user request to modify objects by modifying user interface controls and modifying portions of the recursive data structure to reflect object modifications, wherein the dialog control element performs recursive operations by retrieving a template and repeats a dialog interaction for object properties contained in the at least one object and creates at least one control recursively corresponding to the object properties and the template. | 1. A computer-based user interface comprising: a dialog control element that executes on a computer for usage in creating a dialog, configured to receive and act upon a data model containing recursive data structures comprising at least one object defined by at least one property and modifiable by at least one control, the dialog control element further configured to associate object properties with controls recursively whereby properties contain objects which further contain properties and responsive to a user request to modify objects by modifying user interface controls and modifying portions of the recursive data structure to reflect object modifications, wherein the dialog control element performs recursive operations by retrieving a template and repeats a dialog interaction for object properties contained in the at least one object and creates at least one control recursively corresponding to the object properties and the template. 5. The computer-based user interface according to claim 1 wherein: the dialog control element is configured to be invoked by application code at runtime and responsive to a provided dialog description and reference to an application object to which the dialog applies, and the dialog control element is configured to create the dialog according to the dialog description including creating as many copies of vector property template descriptions as are directed according to the dialog. | 0.588832 |
6,152,612 | 29 | 30 | 29. A computer readable memory unit for use by a computer system and having stored thereon instructions that, when executed by said computer system, realize an application program interface for providing a C++ programming framework for simulating a circuit design, said interface comprising: a) a C++ base class inherited by a plurality of user processes that model the circuit behavior said circuit design, said C++ base class having no circuit behavior of its own and comprising: 1) a scheduler for scheduling said plurality of C++ user having processes for execution, said scheduler simulating concurrency of operation of circuits of said circuit design; and 2) a reactivity model for allowing said plurality of C++ user processes to react to events represented as signals; b) a clock interface for defining clock objects upon which said plurality of C++ user processes are synchronized; and c) a multi-valued logic interface in C++ wherein signal values of: logical high ("1"); logical low ("0"); and high impedance are represented by multi-value logic values, said multi-valued logic interface for performing AND, OR, XOR, and NOT functions on said multi-valued logic values. | 29. A computer readable memory unit for use by a computer system and having stored thereon instructions that, when executed by said computer system, realize an application program interface for providing a C++ programming framework for simulating a circuit design, said interface comprising: a) a C++ base class inherited by a plurality of user processes that model the circuit behavior said circuit design, said C++ base class having no circuit behavior of its own and comprising: 1) a scheduler for scheduling said plurality of C++ user having processes for execution, said scheduler simulating concurrency of operation of circuits of said circuit design; and 2) a reactivity model for allowing said plurality of C++ user processes to react to events represented as signals; b) a clock interface for defining clock objects upon which said plurality of C++ user processes are synchronized; and c) a multi-valued logic interface in C++ wherein signal values of: logical high ("1"); logical low ("0"); and high impedance are represented by multi-value logic values, said multi-valued logic interface for performing AND, OR, XOR, and NOT functions on said multi-valued logic values. 30. A computer readable memory unit as described in claim 29 wherein said scheduler schedules said plurality of C++ user processes by synchronizing said plurality of C++ user processes to an edge of a respective clock object by sequentially scheduling said plurality of C++ user processes for execution upon the occurrence of said edge of said respective clock object, said edge obtained from a priority queue maintained in said memory unit and wherein said scheduler is also for computing a time of a next clock edge of said edge of said respective clock object and for placing said time of said next clock edge into said priority queue in temporal order. | 0.5 |
8,463,795 | 12 | 18 | 12. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for generating an aggregated social feed, the code for: receiving a feed from each of a plurality of social networking systems, each feed comprising a plurality of content items personalized for a user based on the user's social connections in the social networking system; determining a grouping criteria based on content in the plurality of content items; forming a group including a plurality of content items satisfying the grouping criteria; scoring the content items from the plurality of feeds based on one or more relevance factors, wherein each content item is scored by: assigning one or more of the relevance factors to the content item, weighting the assigned relevance factors based on a target velocity of the aggregated social feed, the target velocity representing a predetermined number of content items received from the plurality of social networking system feeds to be included in the aggregated social feed, wherein the weighting is applied to achieve the target velocity for the aggregated social feed, and calculating a composite score based on the weighted relevance factors for the content item; selecting one or more of the scored content items having a composite score that meets a relevance threshold; and sending the selected items in the aggregated social feed for display in a content region of a page. | 12. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for generating an aggregated social feed, the code for: receiving a feed from each of a plurality of social networking systems, each feed comprising a plurality of content items personalized for a user based on the user's social connections in the social networking system; determining a grouping criteria based on content in the plurality of content items; forming a group including a plurality of content items satisfying the grouping criteria; scoring the content items from the plurality of feeds based on one or more relevance factors, wherein each content item is scored by: assigning one or more of the relevance factors to the content item, weighting the assigned relevance factors based on a target velocity of the aggregated social feed, the target velocity representing a predetermined number of content items received from the plurality of social networking system feeds to be included in the aggregated social feed, wherein the weighting is applied to achieve the target velocity for the aggregated social feed, and calculating a composite score based on the weighted relevance factors for the content item; selecting one or more of the scored content items having a composite score that meets a relevance threshold; and sending the selected items in the aggregated social feed for display in a content region of a page. 18. The computer program product of claim 12 , wherein a relevance factor is based on a social networking system from which the content item originated. | 0.764706 |
9,792,588 | 1 | 6 | 1. A method comprising: incorporating one or more modules into an online social networking service to improve a capability of the online networking service to identify a content item stored in a database of the online social networking service as a spam content item, the one or more modules configuring one or more computer processors of the online social networking service to perform operations, the operations comprising: generating a recommendation graph represented as a matrix listing vertices on both the vertical and horizontal axes and edges as entries corresponding to an intersection of the vertices, each of the vertices representing respective electronic profiles of members of the social networking service, each of the edges representing a recommendation of a recommendee member of the social networking service by a recommender member of the social networking service; training a reputation model to learn a respective importance for each respective feature of a subset of features of the electronic profiles, the training including providing the generated recommendation graph to a classifier; estimating a professional reputation of a member, the estimating including applying the trained reputation model to a feature vector of the member, the feature vector including feature values for the subset of the features, the applying including adjusting at least one of the feature values by a respective weight corresponding to the respective learned importance of the respective feature; aggregating a set of estimated professional reputations of members that have engaged with the content item stored in the database of the online social networking service; performing the identifying based on the aggregated set of estimated professional reputations; and determining a target audience for the content item based on the identifying. | 1. A method comprising: incorporating one or more modules into an online social networking service to improve a capability of the online networking service to identify a content item stored in a database of the online social networking service as a spam content item, the one or more modules configuring one or more computer processors of the online social networking service to perform operations, the operations comprising: generating a recommendation graph represented as a matrix listing vertices on both the vertical and horizontal axes and edges as entries corresponding to an intersection of the vertices, each of the vertices representing respective electronic profiles of members of the social networking service, each of the edges representing a recommendation of a recommendee member of the social networking service by a recommender member of the social networking service; training a reputation model to learn a respective importance for each respective feature of a subset of features of the electronic profiles, the training including providing the generated recommendation graph to a classifier; estimating a professional reputation of a member, the estimating including applying the trained reputation model to a feature vector of the member, the feature vector including feature values for the subset of the features, the applying including adjusting at least one of the feature values by a respective weight corresponding to the respective learned importance of the respective feature; aggregating a set of estimated professional reputations of members that have engaged with the content item stored in the database of the online social networking service; performing the identifying based on the aggregated set of estimated professional reputations; and determining a target audience for the content item based on the identifying. 6. The method of claim 1 , wherein the estimated professional reputation of the member corresponds to a level of seniority of the member. | 0.899413 |
8,959,192 | 14 | 15 | 14. A context server comprising: a context repository; a context discoverer that receives user-context information at a data center from a client device, wherein the user-context information is associated with a particular user of the client device; wherein the context discoverer is enabled to receive user-context information selected from the group consisting of spatial, social, personal, physical, system, information, and regulation user-context information; a context manager that: receives the user-context information from the context discoverer; stores the user-context information in the context repository in accordance with a particular context model; wherein the context model is selected from the group consisting of user operations, user processes, user business activities, user real-time locations models; wherein the particular context model comprises a spatial aspect, a social aspect, a personal aspect, a physical aspect, a system aspect, an information aspect, and a regulation aspect; and in accordance with a particular set of rules; and retrieves context information from the context repository in accordance with the particular set of rules; a rule engine that enforces the particular set of rules; wherein the rules determine what portion of the user-context information is to be retrieved to be provided to the resource and a query manager that: receives a context request from a resource accessed by the client device; communicates with the context manager to retrieve context information from the context repository, wherein the retrieved context information includes at least a portion of the user-context information; and sends the retrieved context information to the resource accessed by the client device; wherein the content discoverer is communicatively coupled to a second resource; wherein the content discoverer receives user-context information from the second resource; and wherein the user-context information received from the second resource is stored in the context repository; wherein the resource uses a service broker to find the context server; wherein the context model includes a person object, a location object, a platform object, an environment object, an application object, an activity object, a time object, and regulation object and wherein each of the objects of the context model are enabled to have one or more relationships with other objects. | 14. A context server comprising: a context repository; a context discoverer that receives user-context information at a data center from a client device, wherein the user-context information is associated with a particular user of the client device; wherein the context discoverer is enabled to receive user-context information selected from the group consisting of spatial, social, personal, physical, system, information, and regulation user-context information; a context manager that: receives the user-context information from the context discoverer; stores the user-context information in the context repository in accordance with a particular context model; wherein the context model is selected from the group consisting of user operations, user processes, user business activities, user real-time locations models; wherein the particular context model comprises a spatial aspect, a social aspect, a personal aspect, a physical aspect, a system aspect, an information aspect, and a regulation aspect; and in accordance with a particular set of rules; and retrieves context information from the context repository in accordance with the particular set of rules; a rule engine that enforces the particular set of rules; wherein the rules determine what portion of the user-context information is to be retrieved to be provided to the resource and a query manager that: receives a context request from a resource accessed by the client device; communicates with the context manager to retrieve context information from the context repository, wherein the retrieved context information includes at least a portion of the user-context information; and sends the retrieved context information to the resource accessed by the client device; wherein the content discoverer is communicatively coupled to a second resource; wherein the content discoverer receives user-context information from the second resource; and wherein the user-context information received from the second resource is stored in the context repository; wherein the resource uses a service broker to find the context server; wherein the context model includes a person object, a location object, a platform object, an environment object, an application object, an activity object, a time object, and regulation object and wherein each of the objects of the context model are enabled to have one or more relationships with other objects. 15. The context server of claim 14 , wherein the context server is included within a data center. | 0.925154 |
7,673,230 | 12 | 19 | 12. In a distributed system having a server and a client, wherein the client includes a display device and a keyboard device having at least one key, a method comprising: (a) providing an image map at the client from the server wherein the image map includes a plurality of hyperlinks, each hyperlink being associated with a particular portion of the image map; (b) displaying the image map on the display device; (c) in response to actuating a selected key of the keyboard device, sequentially determining a next hyperlink associated with a particular portion of the image map, wherein the determination of the next hyperlink is executed on the client; and (d) displaying a visual indication of the presence of the next hyperlink in the image map without providing any visual indication of the presence of other hyperlinks in the image map. | 12. In a distributed system having a server and a client, wherein the client includes a display device and a keyboard device having at least one key, a method comprising: (a) providing an image map at the client from the server wherein the image map includes a plurality of hyperlinks, each hyperlink being associated with a particular portion of the image map; (b) displaying the image map on the display device; (c) in response to actuating a selected key of the keyboard device, sequentially determining a next hyperlink associated with a particular portion of the image map, wherein the determination of the next hyperlink is executed on the client; and (d) displaying a visual indication of the presence of the next hyperlink in the image map without providing any visual indication of the presence of other hyperlinks in the image map. 19. The method of claim 12 , wherein the selected key is a tab key. | 0.899701 |
9,489,453 | 8 | 11 | 8. A computer system comprising: a central processing unit (CPU); a memory coupled to the CPU; and a computer readable storage device coupled to the CPU, the storage device containing instructions that are executed by the CPU via the memory to implement a method of building an ontology, the method comprising the steps of: the computer system extracting a plurality of complex triples from free-form text provided by a software application, each complex triple including a compound subject, a compound predicate and a compound object; the computer system performing a syntactic transformation of the plurality of complex triples by, based on a grammar, identifying core terms and non-core terms in the plurality of complex triples, identifying syntactic elements in the plurality of complex triples including nouns, verbs, adjectives and adverbs, and standardizing the plurality of complex triples, wherein a result of the step of performing the syntactic transformation is a plurality of syntactically transformed complex triples whose terms are aligned to the grammar; the computer system performing a semantic transformation of the plurality of syntactically transformed complex triples into respective one or more simplified triples included in a plurality of simplified triples by assigning each core term included in the plurality of simplified triples to exactly one term definition and to exactly one identification key of a reference ontology, wherein each simplified triple includes a subject term, a predicate term and an object term, and wherein each of the one or more simplified triples retains the semantics of the respective syntactically transformed complex triple; based in part on a meta-schema of the reference ontology, the computer system performing an enrichment transformation of the plurality of simplified triples into a plurality of simplified and enriched triples by adding relations derived from a correspondence each term in the plurality of simplified triples has with the reference ontology and by adding representations of semantics of definitions of terms in the plurality of simplified triples, wherein the definitions are included in the reference ontology; based on the plurality of simplified and enriched triples, the computer system generating a new ontology that is aligned with the reference ontology and that represents knowledge included within the software application that provides the free-form text, the new ontology addressing a first domain of expertise; the computer system aligning another ontology with the reference ontology, the other ontology addressing a second domain of expertise that is different from the first domain of expertise; and based on the new ontology and the other ontology being aligned with the reference ontology, the computer system merging the new ontology and the other ontology even though the first and second domains of expertise are different, wherein the step of performing the syntactic transformation of the plurality of complex triples includes: determining a first term of a complex triple included in the plurality of complex triples is a core term and is a verb; and determining a second term of the complex triple is an object, wherein the step of performing the semantic transformation of the plurality of syntactically transformed complex triples into the respective one or more simplified triples included in the plurality of simplified triples is based in part on the first term that is a core term and a verb, and includes generating a conceptualized verb from the verb, wherein the step of generating the conceptualized verb includes: sending to a user a list of verbs included in a lexical database that lexically match the verb and determining a verb in the list of verbs whose definition is selected by the user; sending to the user a list of nouns included in the lexical database that are derivationally related forms of the verb whose definition is selected by the user and determining whether the user selects one of the nouns as having a meaning that matches a meaning of the conceptualized verb; if the user selects one of the nouns, designating the selected noun as the conceptualized verb; if the user does not select one of the nouns, sending to the user a list of hypernyms and hyponyms that the lexical database associates with the nouns in the list of nouns, and determining whether the user selects one of the hypernyms or one of the hyponyms; if the user selects one of the hypernyms or one of the hyponyms, designating the selected hypernym or hyponym ad the conceptualized verb; if the user does not select one of the hypernyms or hyponyms, creating the conceptualized verb by adding a suffix_ness to an end of the verb, and wherein the step of performing the enrichment transformation of the plurality of simplified triples is based in part on the conceptualized verb and includes the step of generating a new set of complex triples that represents the semantics of the definitions of core terms in the plurality of simplified triples, and wherein the method further comprises the steps of: the computer system receiving a desired analysis depth and initializing an analysis depth parameter; based on the grammar, the computer system syntactically transforming the new set of complex triples into a new syntactically transformed set of complex triples; the computer system semantically transforming the new syntactically transformed set of complex triples into a new set of simplified triples; the computer system updating the analysis depth parameter subsequent to the steps of syntactically transforming and semantically transforming; and while the updated analysis depth parameter does not indicate the desired analysis depth, the computer system: performing an enrichment transformation on the new set of simplified triples to generate another new set of complex triples; and repeating, for the other new set of simplified triples, the steps of syntactically transforming, semantically transforming, and updating the analysis depth parameter. | 8. A computer system comprising: a central processing unit (CPU); a memory coupled to the CPU; and a computer readable storage device coupled to the CPU, the storage device containing instructions that are executed by the CPU via the memory to implement a method of building an ontology, the method comprising the steps of: the computer system extracting a plurality of complex triples from free-form text provided by a software application, each complex triple including a compound subject, a compound predicate and a compound object; the computer system performing a syntactic transformation of the plurality of complex triples by, based on a grammar, identifying core terms and non-core terms in the plurality of complex triples, identifying syntactic elements in the plurality of complex triples including nouns, verbs, adjectives and adverbs, and standardizing the plurality of complex triples, wherein a result of the step of performing the syntactic transformation is a plurality of syntactically transformed complex triples whose terms are aligned to the grammar; the computer system performing a semantic transformation of the plurality of syntactically transformed complex triples into respective one or more simplified triples included in a plurality of simplified triples by assigning each core term included in the plurality of simplified triples to exactly one term definition and to exactly one identification key of a reference ontology, wherein each simplified triple includes a subject term, a predicate term and an object term, and wherein each of the one or more simplified triples retains the semantics of the respective syntactically transformed complex triple; based in part on a meta-schema of the reference ontology, the computer system performing an enrichment transformation of the plurality of simplified triples into a plurality of simplified and enriched triples by adding relations derived from a correspondence each term in the plurality of simplified triples has with the reference ontology and by adding representations of semantics of definitions of terms in the plurality of simplified triples, wherein the definitions are included in the reference ontology; based on the plurality of simplified and enriched triples, the computer system generating a new ontology that is aligned with the reference ontology and that represents knowledge included within the software application that provides the free-form text, the new ontology addressing a first domain of expertise; the computer system aligning another ontology with the reference ontology, the other ontology addressing a second domain of expertise that is different from the first domain of expertise; and based on the new ontology and the other ontology being aligned with the reference ontology, the computer system merging the new ontology and the other ontology even though the first and second domains of expertise are different, wherein the step of performing the syntactic transformation of the plurality of complex triples includes: determining a first term of a complex triple included in the plurality of complex triples is a core term and is a verb; and determining a second term of the complex triple is an object, wherein the step of performing the semantic transformation of the plurality of syntactically transformed complex triples into the respective one or more simplified triples included in the plurality of simplified triples is based in part on the first term that is a core term and a verb, and includes generating a conceptualized verb from the verb, wherein the step of generating the conceptualized verb includes: sending to a user a list of verbs included in a lexical database that lexically match the verb and determining a verb in the list of verbs whose definition is selected by the user; sending to the user a list of nouns included in the lexical database that are derivationally related forms of the verb whose definition is selected by the user and determining whether the user selects one of the nouns as having a meaning that matches a meaning of the conceptualized verb; if the user selects one of the nouns, designating the selected noun as the conceptualized verb; if the user does not select one of the nouns, sending to the user a list of hypernyms and hyponyms that the lexical database associates with the nouns in the list of nouns, and determining whether the user selects one of the hypernyms or one of the hyponyms; if the user selects one of the hypernyms or one of the hyponyms, designating the selected hypernym or hyponym ad the conceptualized verb; if the user does not select one of the hypernyms or hyponyms, creating the conceptualized verb by adding a suffix_ness to an end of the verb, and wherein the step of performing the enrichment transformation of the plurality of simplified triples is based in part on the conceptualized verb and includes the step of generating a new set of complex triples that represents the semantics of the definitions of core terms in the plurality of simplified triples, and wherein the method further comprises the steps of: the computer system receiving a desired analysis depth and initializing an analysis depth parameter; based on the grammar, the computer system syntactically transforming the new set of complex triples into a new syntactically transformed set of complex triples; the computer system semantically transforming the new syntactically transformed set of complex triples into a new set of simplified triples; the computer system updating the analysis depth parameter subsequent to the steps of syntactically transforming and semantically transforming; and while the updated analysis depth parameter does not indicate the desired analysis depth, the computer system: performing an enrichment transformation on the new set of simplified triples to generate another new set of complex triples; and repeating, for the other new set of simplified triples, the steps of syntactically transforming, semantically transforming, and updating the analysis depth parameter. 11. The computer system of claim 8 , wherein the step of the computer system performing the semantic transformation of the plurality of syntactically transformed complex triples into the respective one or more simplified triples included in the plurality of simplified triples includes: determining a noun is needed in a simplified triple of the respective one or more simplified triples; determining the reference ontology and meta-schema of the reference ontology do not include a definition of the noun needed in the simplified triple; generating the noun that is determined to be needed in the simplified triple; generating a definition of the noun as relationships between the noun and terms in the new ontology being built; storing the noun and the definition of the noun in the meta-schema of the reference ontology; and based in part on the stored noun and the stored definition of the noun, building a second new ontology. | 0.781353 |
8,041,694 | 26 | 32 | 26. A system comprising: one or more computers, the one or more computers implementing: a dataset tool to identify a comparison vector x having processed features and non-processed features, a first set of vectors, each vector in the first set of vectors having processed features and non-processed features corresponding to the processed features and non-processed features of the comparison vector x, and a candidate vector y from the first set of vectors; and a similarity tool to determine a similarity threshold, and a maximum similarity between the non-processed features of x and the non-processed features of y; wherein the dataset tool removes the vector y from the first set of vectors if the maximum similarity does not meet the similarity threshold. | 26. A system comprising: one or more computers, the one or more computers implementing: a dataset tool to identify a comparison vector x having processed features and non-processed features, a first set of vectors, each vector in the first set of vectors having processed features and non-processed features corresponding to the processed features and non-processed features of the comparison vector x, and a candidate vector y from the first set of vectors; and a similarity tool to determine a similarity threshold, and a maximum similarity between the non-processed features of x and the non-processed features of y; wherein the dataset tool removes the vector y from the first set of vectors if the maximum similarity does not meet the similarity threshold. 32. The system of claim 26 in which each vector in the set of vectors represents a corresponding user in a community, and each feature of each vector represents a preference of the corresponding user towards an object in a set of objects. | 0.83518 |
8,943,043 | 4 | 5 | 4. The method of claim 2 wherein locally servicing queries further comprises steps for using matching query/link pairs corresponding to the query for dynamically synthesizing and displaying a search results page on the mobile communication device, and wherein links on the search results page are ordered by aggregate volume. | 4. The method of claim 2 wherein locally servicing queries further comprises steps for using matching query/link pairs corresponding to the query for dynamically synthesizing and displaying a search results page on the mobile communication device, and wherein links on the search results page are ordered by aggregate volume. 5. The method of claim 4 wherein probabilistic search string matching is used to determine whether a query is a match to query/link in the query cache. | 0.807888 |
7,899,665 | 22 | 30 | 22. A system that is configured to determine a set of rules for ordering text of a language, said system comprising: an interface configured to receive information that indicates a target order of sets of characters in text of a language; and a processor configured by program code to determine strengths of differences between the characters based on the target order, identify strings of characters that were sorted in the target order as a shorter string of characters, identify strings of characters that were sorted in the target order as a longer string of characters, determine a set of rules for ordering text of the language based on the strengths of differences between the characters, the identified strings of characters that were sorted in the target order as a shorter string, and the identified strings of characters that were sorted in the target order as a longer string, wherein the target order is a sequential ordering among the sets of characters in the text of the language. | 22. A system that is configured to determine a set of rules for ordering text of a language, said system comprising: an interface configured to receive information that indicates a target order of sets of characters in text of a language; and a processor configured by program code to determine strengths of differences between the characters based on the target order, identify strings of characters that were sorted in the target order as a shorter string of characters, identify strings of characters that were sorted in the target order as a longer string of characters, determine a set of rules for ordering text of the language based on the strengths of differences between the characters, the identified strings of characters that were sorted in the target order as a shorter string, and the identified strings of characters that were sorted in the target order as a longer string, wherein the target order is a sequential ordering among the sets of characters in the text of the language. 30. The system of claim 22 , wherein the processor identifies the strings of characters that sort as longer strings of characters based on program code for scanning through the target order to identify a last difference between a first character and a second character, program code for determining where the first character sorts in relation the second character in combination with another character, program code for identifying the first character as a string of characters that sort as a longer string of characters based on where the first character sorted. | 0.678653 |
9,904,768 | 15 | 20 | 15. At least one non-transitory computer-readable storage medium encoded with computer-executable instructions that, when executed, perform a method comprising: accessing a text documenting a patient encounter; analyzing the text to identify a set of one or more features of at least a portion of the text; correlating the set of one or more features to a set of alternative hypotheses for an abstract semantic concept representing an intended semantic meaning of the at least a portion of the text; computing, using at least one statistical model implemented using at least one processor and for each of at least some of the alternative hypotheses of the set, one or more measures of estimated likelihood that the respective alternative hypothesis accurately represents the intended semantic meaning of the at least a portion of the text; identifying hypotheses, including some or all of the at least some of the alternative hypotheses, to be presented to a user, wherein identifying the hypotheses comprises, for each of the at least some of the alternative hypotheses of the set: in response to determining that the one or more measures of estimated likelihood for the alternative hypothesis satisfy one or more criteria, identifying that the alternative hypothesis is to be presented to the user; and presenting the identified hypotheses, to the user documenting the patient encounter, as alternative hypotheses for a medical fact that could be extracted from the text. | 15. At least one non-transitory computer-readable storage medium encoded with computer-executable instructions that, when executed, perform a method comprising: accessing a text documenting a patient encounter; analyzing the text to identify a set of one or more features of at least a portion of the text; correlating the set of one or more features to a set of alternative hypotheses for an abstract semantic concept representing an intended semantic meaning of the at least a portion of the text; computing, using at least one statistical model implemented using at least one processor and for each of at least some of the alternative hypotheses of the set, one or more measures of estimated likelihood that the respective alternative hypothesis accurately represents the intended semantic meaning of the at least a portion of the text; identifying hypotheses, including some or all of the at least some of the alternative hypotheses, to be presented to a user, wherein identifying the hypotheses comprises, for each of the at least some of the alternative hypotheses of the set: in response to determining that the one or more measures of estimated likelihood for the alternative hypothesis satisfy one or more criteria, identifying that the alternative hypothesis is to be presented to the user; and presenting the identified hypotheses, to the user documenting the patient encounter, as alternative hypotheses for a medical fact that could be extracted from the text. 20. The at least one non-transitory computer-readable storage medium of claim 15 , wherein: the identified hypotheses comprise a first hypothesis and a second hypothesis of the at least some of the alternative hypotheses, and the presenting comprises: presenting the first hypothesis to the user; and in response to a selection by the user of the presented first hypothesis, presenting the second hypothesis to the user. | 0.5 |
8,812,296 | 1 | 11 | 1. A method for a computer system to create a morphological dictionary for a natural language, the method comprising: identifying a word token in a text corpus; applying by the computer system one or more paradigm rules to the word token; generating by the computer system one or more hypotheses about a part of speech for a base form of the word token; searching by the computer system for one or more word inflected forms corresponding to the base form of the word token; verifying by the computer system a hypothesis of the one or more hypotheses for the base form of the word token; adding by the computer system at least one grammatical value and at least one inflection paradigm to the base form of the word token based at least in part on the verified hypothesis; obtaining by the computer system one or more morphological descriptions for the word token based at least in part on the verified hypothesis; and adding the base form of the word token with the one or more morphological descriptions to the morphological dictionary of the natural language. | 1. A method for a computer system to create a morphological dictionary for a natural language, the method comprising: identifying a word token in a text corpus; applying by the computer system one or more paradigm rules to the word token; generating by the computer system one or more hypotheses about a part of speech for a base form of the word token; searching by the computer system for one or more word inflected forms corresponding to the base form of the word token; verifying by the computer system a hypothesis of the one or more hypotheses for the base form of the word token; adding by the computer system at least one grammatical value and at least one inflection paradigm to the base form of the word token based at least in part on the verified hypothesis; obtaining by the computer system one or more morphological descriptions for the word token based at least in part on the verified hypothesis; and adding the base form of the word token with the one or more morphological descriptions to the morphological dictionary of the natural language. 11. The method of claim 1 , wherein the at least one grammatical value added to the base form of the word token includes information about the part of speech for the word token. | 0.765873 |
8,661,336 | 15 | 16 | 15. A system comprising: one or more programmable processors; and a computer-readable storage device storing instructions that, when executed by the one or more programmable processors, perform operations comprising: using, by a computing system, a particular object schema to generate multiple objects, wherein the particular object schema identifies constraints on a structure and content of the multiple objects, and wherein the multiple objects include a first object; storing, by the computing system, multiple configuration templates that each identify a mapping of multiple attributes defined by a respective object schema to multiple attributes or elements defined by a respective markup language document schema; displaying, by the computing system, a graphical user interface that permits a user of the computing system to select a first configuration template from a displayed set of the multiple configuration templates, wherein the first configuration template identifies a mapping of multiple attributes defined by the particular object schema to multiple attributes or elements defined by a particular markup language document schema; receiving, by the computing system, first user input that selects the first configuration template; displaying, by the computing system and concurrently in the graphical user interface: (i) a list of names of at least some attributes of the multiple attributes defined by the particular object schema, and (ii) for each of the at least some attributes, a name of the associated markup language attribute or element that is identified by the first configuration template, so as to visually indicate in the graphical user interface the mapping between each of the at least some attributes and its associated markup language attribute or element; receiving, by the computing system, second user input that interacts with the displayed graphical user interface to change either: (i) a name for a particular one of the at least some attributes, or (ii) a name for a particular one of the associated markup language attributes or elements, so as to change a mapping that is identified by the first configuration template for the particular one of the at least some attributes or the particular one of the associated markup language attributes or elements; generating, by the computing system and in response to receiving the second user input, an updated configuration template that identifies a mapping of the particular object schema to the particular markup language document schema, the updated configuration template including the changed mapping for the particular one of the at least some attributes or the particular one of the associated markup language attributes or elements, the updated configuration template configured to enable the computing system to export content associated with an object generated using the particular object schema to a document for which the particular markup language schema identifies constraints on structure and content; receiving, by the computing system, third user input that requests generation of a first markup language document representation of the first object; and generating, by the computing system and in response to receiving the third user input, the first markup language document using the updated configuration template. | 15. A system comprising: one or more programmable processors; and a computer-readable storage device storing instructions that, when executed by the one or more programmable processors, perform operations comprising: using, by a computing system, a particular object schema to generate multiple objects, wherein the particular object schema identifies constraints on a structure and content of the multiple objects, and wherein the multiple objects include a first object; storing, by the computing system, multiple configuration templates that each identify a mapping of multiple attributes defined by a respective object schema to multiple attributes or elements defined by a respective markup language document schema; displaying, by the computing system, a graphical user interface that permits a user of the computing system to select a first configuration template from a displayed set of the multiple configuration templates, wherein the first configuration template identifies a mapping of multiple attributes defined by the particular object schema to multiple attributes or elements defined by a particular markup language document schema; receiving, by the computing system, first user input that selects the first configuration template; displaying, by the computing system and concurrently in the graphical user interface: (i) a list of names of at least some attributes of the multiple attributes defined by the particular object schema, and (ii) for each of the at least some attributes, a name of the associated markup language attribute or element that is identified by the first configuration template, so as to visually indicate in the graphical user interface the mapping between each of the at least some attributes and its associated markup language attribute or element; receiving, by the computing system, second user input that interacts with the displayed graphical user interface to change either: (i) a name for a particular one of the at least some attributes, or (ii) a name for a particular one of the associated markup language attributes or elements, so as to change a mapping that is identified by the first configuration template for the particular one of the at least some attributes or the particular one of the associated markup language attributes or elements; generating, by the computing system and in response to receiving the second user input, an updated configuration template that identifies a mapping of the particular object schema to the particular markup language document schema, the updated configuration template including the changed mapping for the particular one of the at least some attributes or the particular one of the associated markup language attributes or elements, the updated configuration template configured to enable the computing system to export content associated with an object generated using the particular object schema to a document for which the particular markup language schema identifies constraints on structure and content; receiving, by the computing system, third user input that requests generation of a first markup language document representation of the first object; and generating, by the computing system and in response to receiving the third user input, the first markup language document using the updated configuration template. 16. The system of claim 15 , wherein the operations further comprise: receiving, by the computing system, fourth user input that requests creation of a second object that is of the particular object schema from a second markup language document that is of the markup language document schema; and generating, by the computing system and using the updated configuration template, the second object for storage by the computing system, the second object representing content of the markup language document. | 0.7475 |
6,026,395 | 13 | 16 | 13. A method performed by a computing system during a proceeding in which a transcript representative of spoken words is generated in real-time, the method comprising: generating a transcript in real time; storing the transcript; accepting, during generation of the transcript, a user input representative of a first search request; and displaying, during generation of the transcript and after access the user input, at least a portion of the transcript corresponding to results of the first search request. | 13. A method performed by a computing system during a proceeding in which a transcript representative of spoken words is generated in real-time, the method comprising: generating a transcript in real time; storing the transcript; accepting, during generation of the transcript, a user input representative of a first search request; and displaying, during generation of the transcript and after access the user input, at least a portion of the transcript corresponding to results of the first search request. 16. The method of claim 13 further comprising displaying the text for viewing in real time and accepting a user input selecting at least a portion of the displayed text as a second search request. | 0.5 |
7,937,394 | 1 | 10 | 1. A method of processing unresolved keystroke entries by a user from a keypad with overloaded keys in which a given key is in fixed association with a number and at least one alphabetic character, the unresolved keystroke entries being directed at identifying an item from a set of items, each of the items being associated with information describing the item comprising one or more words, the method comprising: providing access to an index of the items, the index having an association between subsets of the items and corresponding strings of one or more unresolved keystrokes for overloaded keys so that the subsets of items are directly mapped to the corresponding strings of unresolved keystrokes for various search query prefix substrings; for at least one subset of items, determining which letters and numbers present in the information associated with and describing the indexed items of the subset caused the items to be associated with the strings of one or more unresolved keystrokes that directly mapped to the subset; receiving from a user a search query for desired items composed of unresolved keystrokes, the search query comprising a prefix substring for at least one word in information associated with the desired item; in response to each unresolved keystroke, identifying and displaying the subsets of items, and information associated therewith, that are associated with the strings of one or more unresolved keystrokes received from the user based on the direct mapping of strings of unresolved keystrokes to subsets of items; and in response to each unresolved keystroke, as the identified items are displayed, highlighting the letters and numbers present in the one or more words in the information describing the identified items that were determined to have caused the displayed items to be associated with the strings of unresolved keystrokes that are directly mapped to the items so as to illustrate to the user how the unresolved keystrokes entered match the information associated with the displayed items. | 1. A method of processing unresolved keystroke entries by a user from a keypad with overloaded keys in which a given key is in fixed association with a number and at least one alphabetic character, the unresolved keystroke entries being directed at identifying an item from a set of items, each of the items being associated with information describing the item comprising one or more words, the method comprising: providing access to an index of the items, the index having an association between subsets of the items and corresponding strings of one or more unresolved keystrokes for overloaded keys so that the subsets of items are directly mapped to the corresponding strings of unresolved keystrokes for various search query prefix substrings; for at least one subset of items, determining which letters and numbers present in the information associated with and describing the indexed items of the subset caused the items to be associated with the strings of one or more unresolved keystrokes that directly mapped to the subset; receiving from a user a search query for desired items composed of unresolved keystrokes, the search query comprising a prefix substring for at least one word in information associated with the desired item; in response to each unresolved keystroke, identifying and displaying the subsets of items, and information associated therewith, that are associated with the strings of one or more unresolved keystrokes received from the user based on the direct mapping of strings of unresolved keystrokes to subsets of items; and in response to each unresolved keystroke, as the identified items are displayed, highlighting the letters and numbers present in the one or more words in the information describing the identified items that were determined to have caused the displayed items to be associated with the strings of unresolved keystrokes that are directly mapped to the items so as to illustrate to the user how the unresolved keystrokes entered match the information associated with the displayed items. 10. The method of claim 1 , wherein at least some items of the set of items are product items. | 0.879177 |
9,223,590 | 30 | 31 | 30. The method of claim 27 , wherein the contextual information relating to the text manipulation event includes a logical location and a predetermined unit of text relating to the text manipulation event. | 30. The method of claim 27 , wherein the contextual information relating to the text manipulation event includes a logical location and a predetermined unit of text relating to the text manipulation event. 31. The method of claim 30 , wherein the predetermined unit of text is selected from the group consisting of: a character, a word, a sentence, a paragraph, a line of text, a section of a document, and a document. | 0.669782 |
9,946,433 | 9 | 10 | 9. The user interface designing system as claimed in claim 8 , wherein the user selected first answer for a respective pre-defined question is from amongst the first set of pre-defined answers for the respective pre-defined question. | 9. The user interface designing system as claimed in claim 8 , wherein the user selected first answer for a respective pre-defined question is from amongst the first set of pre-defined answers for the respective pre-defined question. 10. The user interface designing system as claimed in claim 9 , wherein each of the pre-defined answers in the first set is associated with an STI score with respect to each of the pre-defined user experience parameters based on which the STI weightage is assigned to the user selected first answer, and wherein the STI score of a pre-defined answer is indicative of degree of significance of the corresponding requirement with respect to a pre-defined user experience parameter. | 0.5 |
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