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9,740,464 | 1 | 2 | 1. A non-transitory machine-readable medium, on which are stored instructions, comprising instructions that when executed cause a machine to: receive a pre-compiled library, wherein the pre-compiled library has been compiled from source code into an intermediate representation prior to being received, and wherein the pre-compiled library comprises parallel graphics operations and parallel non-graphics operations; compile the pre-compiled library from an intermediate representation file into a binary file comprising one or more kernels and one or more shaders, wherein both the one or more kernels and the one or more shaders are directly executable by a target processor; responsive to detecting a request for a kernel of the binary file, open the binary file and retrieve the kernel from the binary file; responsive to detecting a request for a shader of the binary file, open the binary file and retrieve the shader from the binary file; provide the kernel to the target processor for execution; and provide the shader to the target processor, wherein the intermediate representation file contains instructions conforming to an intermediate representation language model, wherein the intermediate representation language model is independent of the target processor and a source language of the source code, and wherein the intermediate representation language model contains functions for performing parallel graphics operations and functions for performing parallel non-graphics operations. | 1. A non-transitory machine-readable medium, on which are stored instructions, comprising instructions that when executed cause a machine to: receive a pre-compiled library, wherein the pre-compiled library has been compiled from source code into an intermediate representation prior to being received, and wherein the pre-compiled library comprises parallel graphics operations and parallel non-graphics operations; compile the pre-compiled library from an intermediate representation file into a binary file comprising one or more kernels and one or more shaders, wherein both the one or more kernels and the one or more shaders are directly executable by a target processor; responsive to detecting a request for a kernel of the binary file, open the binary file and retrieve the kernel from the binary file; responsive to detecting a request for a shader of the binary file, open the binary file and retrieve the shader from the binary file; provide the kernel to the target processor for execution; and provide the shader to the target processor, wherein the intermediate representation file contains instructions conforming to an intermediate representation language model, wherein the intermediate representation language model is independent of the target processor and a source language of the source code, and wherein the intermediate representation language model contains functions for performing parallel graphics operations and functions for performing parallel non-graphics operations. 2. The non-transitory machine-readable medium of claim 1 , wherein the target processor is one or more graphics processing units. | 0.831152 |
8,874,551 | 1 | 13 | 1. A computer-implemented method of querying distributed data sources, the method being executed using one or more processors and comprising: receiving, by one or more processors, a query; identifying, by the one or more processors and based on the query, one or more relevant elements from an overall data model stored in computer-readable memory, the overall data model specifying relationships between classes, sub-classes and attributes, each relevant element being an element of the overall data model and being determined to be relevant to the query; identifying, by the one or more processors and using an adapter mapping, one or more adapters based on the one or more relevant elements, the adapter mapping associating each relevant element with a particular adapter, each adapter providing credentials for authenticating and authorizing access to the one or more data sources, and at least one adapter comprising a generic adapter configured to be specific to a data source type of the one or more data sources based on one or more configurations to associate data provided in a respective data source to the overall data model; querying, by the one or more processors and using the one or more adapters, one or more data elements in heterogeneous data sources of the disparate data sources, each adapter being specific to a data source of the one or more data sources; in response to querying, receiving, at the one or more adapters, one or more data results; transforming, by the one or more processors, each data result of the one or more data results into a unified data format to provide respective one or more transformed data results; storing the one or more transformed data results in a temporary data store; and querying the temporary data store based on the query to generate a result. | 1. A computer-implemented method of querying distributed data sources, the method being executed using one or more processors and comprising: receiving, by one or more processors, a query; identifying, by the one or more processors and based on the query, one or more relevant elements from an overall data model stored in computer-readable memory, the overall data model specifying relationships between classes, sub-classes and attributes, each relevant element being an element of the overall data model and being determined to be relevant to the query; identifying, by the one or more processors and using an adapter mapping, one or more adapters based on the one or more relevant elements, the adapter mapping associating each relevant element with a particular adapter, each adapter providing credentials for authenticating and authorizing access to the one or more data sources, and at least one adapter comprising a generic adapter configured to be specific to a data source type of the one or more data sources based on one or more configurations to associate data provided in a respective data source to the overall data model; querying, by the one or more processors and using the one or more adapters, one or more data elements in heterogeneous data sources of the disparate data sources, each adapter being specific to a data source of the one or more data sources; in response to querying, receiving, at the one or more adapters, one or more data results; transforming, by the one or more processors, each data result of the one or more data results into a unified data format to provide respective one or more transformed data results; storing the one or more transformed data results in a temporary data store; and querying the temporary data store based on the query to generate a result. 13. The method of claim 1 , wherein the temporary data store is queried using the query. | 0.908903 |
7,519,217 | 29 | 30 | 29. A computer-readable storage medium containing instructions for controlling a computer system to generate a classifier to classify scenes of a video as commercial or not commercial using an adaptive boosting training technique, by a method comprising: providing a plurality of training scenes of a training video, each training scene represented by a feature vector and having an actual classification; assigning a current weight to each training scene; for a plurality of sub-classifiers, training the sub-classifier based on the training scenes and actual classifications of the training scenes, the trained sub-classifier to provide classifications for scenes; classifying the training scenes using the trained sub-classifier; setting the classification of the training scenes to commercial when the training scenes are in between training scenes classified as commercial and a time between the training scenes indicates that the training scenes are within a commercial; resetting the current weights of the training scenes based on similarity of the classifications to the actual classifications; and generating a weight for the sub-classifier based on similarity of the classification to the actual classification, wherein the generated classifier is a combination of the trained sub-classifiers weighted based on the generated weights of the sub-classifiers. | 29. A computer-readable storage medium containing instructions for controlling a computer system to generate a classifier to classify scenes of a video as commercial or not commercial using an adaptive boosting training technique, by a method comprising: providing a plurality of training scenes of a training video, each training scene represented by a feature vector and having an actual classification; assigning a current weight to each training scene; for a plurality of sub-classifiers, training the sub-classifier based on the training scenes and actual classifications of the training scenes, the trained sub-classifier to provide classifications for scenes; classifying the training scenes using the trained sub-classifier; setting the classification of the training scenes to commercial when the training scenes are in between training scenes classified as commercial and a time between the training scenes indicates that the training scenes are within a commercial; resetting the current weights of the training scenes based on similarity of the classifications to the actual classifications; and generating a weight for the sub-classifier based on similarity of the classification to the actual classification, wherein the generated classifier is a combination of the trained sub-classifiers weighted based on the generated weights of the sub-classifiers. 30. The computer-readable storage medium of claim 29 including classifying scenes of a video by: initially classifying each scene using each trained sub-classifier; setting the classification of scenes to commercial when the scenes are in between scenes initially classified as commercial and a time between the scenes indicates that the scenes are within a commercial; and setting a final classification of a scene to commercial or not commercial based on the classification of a majority of the scenes within a window. | 0.548611 |
9,619,534 | 16 | 17 | 16. An apparatus for extracting contact data from quotes, wherein a plurality of contacts are stored in a multi-tenant database, the apparatus comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to: obtain and store a data string having a plurality of tokens in content of a search result from a search for quoted material associated with a contact; extract a sequence of tokens corresponding to the data string; recognize a first set of tokens in the sequence of tokens as a first entity based on entity recognition probabilistic scoring derived from a machine evaluation of a training set of entities; recognize a second set of tokens in the sequence of tokens as a second entity based on identifying the first entity as a first node in a tree-like structure and identifying the second entity as by a second node in the tree-like structure, the first node connected to the second node by an arc representing a probability that the first entity is followed by the second entity in a probable entity sequence, the first node connected to another node by another arc representing another probability that the first entity is followed by another entity in another probable entity sequence, the tree-like structure created by a machine evaluation of a training set of input strings; align one or more tokens of the first set of tokens as one of a plurality of probable entities using the probabilistic scoring of the first set of tokens and grammatical rules; assign the aligned one or more tokens to one entity field of corresponding predefined entity fields of the contact based on the probabilistic scoring and the linguistic cues of the probable secondary entities; and create and store a new record for the contact if none exists, or updating an existing record for the contact, using the assigned aligned one or more tokens. | 16. An apparatus for extracting contact data from quotes, wherein a plurality of contacts are stored in a multi-tenant database, the apparatus comprising: a processor; and one or more stored sequences of instructions which, when executed by the processor, cause the processor to: obtain and store a data string having a plurality of tokens in content of a search result from a search for quoted material associated with a contact; extract a sequence of tokens corresponding to the data string; recognize a first set of tokens in the sequence of tokens as a first entity based on entity recognition probabilistic scoring derived from a machine evaluation of a training set of entities; recognize a second set of tokens in the sequence of tokens as a second entity based on identifying the first entity as a first node in a tree-like structure and identifying the second entity as by a second node in the tree-like structure, the first node connected to the second node by an arc representing a probability that the first entity is followed by the second entity in a probable entity sequence, the first node connected to another node by another arc representing another probability that the first entity is followed by another entity in another probable entity sequence, the tree-like structure created by a machine evaluation of a training set of input strings; align one or more tokens of the first set of tokens as one of a plurality of probable entities using the probabilistic scoring of the first set of tokens and grammatical rules; assign the aligned one or more tokens to one entity field of corresponding predefined entity fields of the contact based on the probabilistic scoring and the linguistic cues of the probable secondary entities; and create and store a new record for the contact if none exists, or updating an existing record for the contact, using the assigned aligned one or more tokens. 17. The apparatus of claim 16 , wherein the probabilistic scoring is learned from a plurality of training sets of input strings. | 0.889465 |
6,073,099 | 1 | 10 | 1. A method of determining the likelihood of confusing a first word for a second word, comprising the steps of: phonemically transcribing first and second orthographies of the first and second words into first and second phonemic transcriptions; calculating a Levinstein distance between the first and second phonemic transcriptions, wherein the Levinstein distance corresponds to edit operations required to transform the first phonemic transcription into the second phonemic transcription; obtaining a phonematic transformation weight for each edit operation of the Levinstein distance; and summing the obtained phonemic transformation weights to generate a value indicating the likelihood of confusion between the first and second words. | 1. A method of determining the likelihood of confusing a first word for a second word, comprising the steps of: phonemically transcribing first and second orthographies of the first and second words into first and second phonemic transcriptions; calculating a Levinstein distance between the first and second phonemic transcriptions, wherein the Levinstein distance corresponds to edit operations required to transform the first phonemic transcription into the second phonemic transcription; obtaining a phonematic transformation weight for each edit operation of the Levinstein distance; and summing the obtained phonemic transformation weights to generate a value indicating the likelihood of confusion between the first and second words. 10. The method of claim 1, further including the step of using a generated values to build test lexicons to be used in evaluating speech recognition algorithms. | 0.840319 |
8,423,547 | 1 | 9 | 1. A computer-readable medium storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a subgraph of a multi-partite graph, wherein the received subgraph encompasses search queries; receiving a global center vector table that includes cluster center entries for query clusters; filtering the received global center vector table to eliminate one or more cluster center entries that are irrelevant to the search queries in the received subgraph; and clustering the search queries in the received subgraph into the query clusters by at least comparing each of the search queries to at least some of the cluster center entries in the received global center vector table, wherein the clustering includes eliminating a comparison between a cluster center entry in the received global center vector table and a search query of the search queries by using a user-centered table that lists related cluster centers for each user enumerated in the received global center vector table and a URL-centered table that lists related cluster centers for each URL enumerated in the received global center vector table. | 1. A computer-readable medium storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: receiving a subgraph of a multi-partite graph, wherein the received subgraph encompasses search queries; receiving a global center vector table that includes cluster center entries for query clusters; filtering the received global center vector table to eliminate one or more cluster center entries that are irrelevant to the search queries in the received subgraph; and clustering the search queries in the received subgraph into the query clusters by at least comparing each of the search queries to at least some of the cluster center entries in the received global center vector table, wherein the clustering includes eliminating a comparison between a cluster center entry in the received global center vector table and a search query of the search queries by using a user-centered table that lists related cluster centers for each user enumerated in the received global center vector table and a URL-centered table that lists related cluster centers for each URL enumerated in the received global center vector table. 9. The computer-readable medium of claim 1 , wherein the clustering includes clustering the search queries using a plurality of iterations of a k-means clustering algorithm. | 0.880525 |
9,344,524 | 1 | 10 | 1. A method for providing composite web application comprising the steps of: receiving, at a webshell server, a client request from a client server in the form of an API language request, wherein the client request further comprises a plurality of command line interface (CLI) commands for querying Web services; generating, at a webshell server, an Abstract Syntax Tree (AST) from the client request, wherein the AST comprises syntax nodes and command nodes and at least one command node being associated to at least one request to the Web services; executing, at a webshell server, the Abstract Syntax Tree, wherein each command node execution further comprises: sending to a Web service, a web service request in the form of an application program interface (API) language of the corresponding requested Web service; receiving from the corresponding requested Web service the web data sent back; and storing the web data received as the response of the execution step; combining, at a webshell server, the stored web data into a composite data structure; and sending, at a webshell server, the composite data structure in the form of an API language response to a client computer. | 1. A method for providing composite web application comprising the steps of: receiving, at a webshell server, a client request from a client server in the form of an API language request, wherein the client request further comprises a plurality of command line interface (CLI) commands for querying Web services; generating, at a webshell server, an Abstract Syntax Tree (AST) from the client request, wherein the AST comprises syntax nodes and command nodes and at least one command node being associated to at least one request to the Web services; executing, at a webshell server, the Abstract Syntax Tree, wherein each command node execution further comprises: sending to a Web service, a web service request in the form of an application program interface (API) language of the corresponding requested Web service; receiving from the corresponding requested Web service the web data sent back; and storing the web data received as the response of the execution step; combining, at a webshell server, the stored web data into a composite data structure; and sending, at a webshell server, the composite data structure in the form of an API language response to a client computer. 10. The method of claim 1 , wherein the API of the client computer is a Web browser. | 0.802817 |
5,390,279 | 11 | 16 | 11. An apparatus for speech recognition system according to a current context comprising: a. association circuitry for associating with each of a plurality of speech rules, a context wherein each of said speech rules will be active; b. context determination circuitry for determining common contexts for said contexts associated with each of said plurality of speech rules; and c. partitioning circuitry for partitioning each of said plurality of speech rules into a partition of speech rule sets according to said common contexts, wherein each of said plurality of speech rules resides in only one said speech rule set of said partition, said partition of speech rule sets being used for dynamic language model generation upon the detection of speech according to said current context, each of said speech rule sets being included in said language model only upon determining that said common context for said speech rule set matches said current context; and d. model generation and recognition circuitry for using said partition of speech rule sets to dynamically generate said language model upon said detection of said speech, and recognize said speech using said language model. | 11. An apparatus for speech recognition system according to a current context comprising: a. association circuitry for associating with each of a plurality of speech rules, a context wherein each of said speech rules will be active; b. context determination circuitry for determining common contexts for said contexts associated with each of said plurality of speech rules; and c. partitioning circuitry for partitioning each of said plurality of speech rules into a partition of speech rule sets according to said common contexts, wherein each of said plurality of speech rules resides in only one said speech rule set of said partition, said partition of speech rule sets being used for dynamic language model generation upon the detection of speech according to said current context, each of said speech rule sets being included in said language model only upon determining that said common context for said speech rule set matches said current context; and d. model generation and recognition circuitry for using said partition of speech rule sets to dynamically generate said language model upon said detection of said speech, and recognize said speech using said language model. 16. The apparatus of claim 11 wherein said context associated with each of said plurality of speech rules comprises a plurality of conjoined primitive labels. | 0.769679 |
8,055,605 | 12 | 13 | 12. The system of claim 11 , wherein the data elements in the knowledge base comprise data elements associated with contract resources. | 12. The system of claim 11 , wherein the data elements in the knowledge base comprise data elements associated with contract resources. 13. The system of claim 12 , wherein the contract resources are travel-related contract resources. | 0.95656 |
8,819,541 | 11 | 14 | 11. The method of claim 8 , wherein in step (d) the output file is wrapped with the application for distribution. | 11. The method of claim 8 , wherein in step (d) the output file is wrapped with the application for distribution. 14. The method of claim 11 , wherein the application encapsulates the output file and encapsulates other secondary data content in one or more different output files. | 0.953991 |
9,946,754 | 11 | 12 | 11. A data validation computing device, comprising a processor and a memory coupled to the processor which is configured to execute one or more programmed instructions comprising and stored in the memory to: receive a data transformation specification from a user; analyze the data transformation specification to determine data transformation rules, wherein the data transformation rules are indicative of a relationship between corresponding fields of a source repository and a target repository; generate test cases and test scripts based on the data transformation rules; determine a number of records on which the test cases and the test scripts are to be executed; execute the test cases and the test scripts in an order based on the data transformation rules, on the source repository and the target repository to validate the relationship between the corresponding fields of the source repository and the target repository, wherein execution of the test cases and the test scripts is initiated serially when the determined number of records is less than a critical threshold, and wherein the execution of the test cases and the test scripts is initiated in parallel when the determined number of records is more than a critical threshold; and generate a log file indicative of the outcome of the execution of the test cases and the test scripts. | 11. A data validation computing device, comprising a processor and a memory coupled to the processor which is configured to execute one or more programmed instructions comprising and stored in the memory to: receive a data transformation specification from a user; analyze the data transformation specification to determine data transformation rules, wherein the data transformation rules are indicative of a relationship between corresponding fields of a source repository and a target repository; generate test cases and test scripts based on the data transformation rules; determine a number of records on which the test cases and the test scripts are to be executed; execute the test cases and the test scripts in an order based on the data transformation rules, on the source repository and the target repository to validate the relationship between the corresponding fields of the source repository and the target repository, wherein execution of the test cases and the test scripts is initiated serially when the determined number of records is less than a critical threshold, and wherein the execution of the test cases and the test scripts is initiated in parallel when the determined number of records is more than a critical threshold; and generate a log file indicative of the outcome of the execution of the test cases and the test scripts. 12. The device as set forth in claim 11 , wherein the processor coupled to the memory is further configured to execute at least one additional programmed instruction comprising and stored in the memory to generate a report, based on the log file, wherein the report is indicative of whether values stored in the corresponding fields of the source repository and the target repository are in accordance with the data transformation rules. | 0.866279 |
8,930,370 | 8 | 18 | 8. The system of claim 6 , wherein at least one of the one or more memories has further instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: cluster a set of products together having a threshold number of common product attribute values; generate a new category in the taxonomy corresponding to the common product attribute values; and categorize the set of products in the new category. | 8. The system of claim 6 , wherein at least one of the one or more memories has further instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: cluster a set of products together having a threshold number of common product attribute values; generate a new category in the taxonomy corresponding to the common product attribute values; and categorize the set of products in the new category. 18. The system of claim 8 , wherein at least one of the one or more memories has further instructions stored thereon that, when executed by at least one of the one or more processors, cause at least one of the one or more processors to: assign a product identifier to the cluster. | 0.915612 |
8,523,673 | 3 | 4 | 3. The vocally interactive video gaming mechanism as recited in claim 2 , further comprising: f) a second mechanism configured to pause a current game progress of said video game in order to allow said player to answer or respond to said message. | 3. The vocally interactive video gaming mechanism as recited in claim 2 , further comprising: f) a second mechanism configured to pause a current game progress of said video game in order to allow said player to answer or respond to said message. 4. The vocally interactive video gaming mechanism as recited in claim 3 , further comprising: g) a third mechanism configured to allow said player to ignore said message. | 0.931727 |
8,234,263 | 1 | 8 | 1. A computer-implemented method for building a dynamic classification dictionary, the method comprising: analyzing, with a computing device, author-generated classification information regarding a document and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization; identifying, with a computing device, a method of access through which the document has been accessed from a content provider and assigning a set of third taxonomic nouns to characterize the document based upon the method of access; evaluating, with a computing device, attributes related to the method of access and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the method of access; processing, with a computing device, the document to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; and building, with a computing device, a dynamic classification dictionary by storing the composite set of taxonomic nouns. | 1. A computer-implemented method for building a dynamic classification dictionary, the method comprising: analyzing, with a computing device, author-generated classification information regarding a document and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization; identifying, with a computing device, a method of access through which the document has been accessed from a content provider and assigning a set of third taxonomic nouns to characterize the document based upon the method of access; evaluating, with a computing device, attributes related to the method of access and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the method of access; processing, with a computing device, the document to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; and building, with a computing device, a dynamic classification dictionary by storing the composite set of taxonomic nouns. 8. The computer-implemented method for building a dynamic classification dictionary of claim 1 , further comprising: clustering related nouns; adding a topic to the dynamic classification dictionary based on the clustered related nouns; and selecting a single term to represent the cluster. | 0.580925 |
8,214,733 | 14 | 15 | 14. A system to process at least one document image comprising a plurality of text rows and a plurality of characters, each text row having at least one character, the system comprising: at least one processor; and a plurality of modules to execute on the at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; a classification system to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine one or more classes for the text rows based on the physical structures of the text rows as defined by the columns of the character blocks in each text row, each class comprising one or more particular text rows having a similar physical structure; and a pattern matching system to: determine a corresponding binary average row for each of the one or more classes, wherein each corresponding binary average row comprises binary values specifying whether a particular column position in the corresponding average row comprises a character block or a white space; determine an average row matrix for each class based on the corresponding binary average row, wherein each average row vector correspond to one particular class; interpolate the average row matrix for each class to generate corresponding interpolation matrix data; determine a correlation value between the corresponding interpolation matrix data for at least two selected classes of text rows; compare the correlation value to a threshold correlation value; and group the at least two selected classes of text rows into a first combined class when the correlation value is greater than the threshold correlation value. | 14. A system to process at least one document image comprising a plurality of text rows and a plurality of characters, each text row having at least one character, the system comprising: at least one processor; and a plurality of modules to execute on the at least one processor, the modules comprising: a character block creator to create character blocks for the characters in the text rows and to determine positions of alignments of the character blocks; a classification system to determine columns for the alignments of the character blocks at the positions of the alignments, each text row having a physical structure defined by the columns of the alignments of the character blocks in that text row, and to determine one or more classes for the text rows based on the physical structures of the text rows as defined by the columns of the character blocks in each text row, each class comprising one or more particular text rows having a similar physical structure; and a pattern matching system to: determine a corresponding binary average row for each of the one or more classes, wherein each corresponding binary average row comprises binary values specifying whether a particular column position in the corresponding average row comprises a character block or a white space; determine an average row matrix for each class based on the corresponding binary average row, wherein each average row vector correspond to one particular class; interpolate the average row matrix for each class to generate corresponding interpolation matrix data; determine a correlation value between the corresponding interpolation matrix data for at least two selected classes of text rows; compare the correlation value to a threshold correlation value; and group the at least two selected classes of text rows into a first combined class when the correlation value is greater than the threshold correlation value. 15. The system of claim 14 wherein the pattern matching system is further configured to: determine a distance between binary average rows for the at least two selected classes of text rows when the correlation value is less than the threshold correlation value; compare the distance to a threshold distance; and group the at least two selected classes of text rows into the first combined class when the distance is less than the threshold distance. | 0.828233 |
9,442,946 | 9 | 10 | 9. The system of claim 1 , wherein the first mission plan corresponds to a combat plan. | 9. The system of claim 1 , wherein the first mission plan corresponds to a combat plan. 10. The system of claim 9 , wherein the second mission plan corresponds to a logistics plan, and wherein the constraint indicates a location where supplies are needed due to the change of the first mission plan. | 0.958152 |
8,370,143 | 1 | 14 | 1. A computer-implemented method, comprising: receiving, by a computing system, text of a message entered by a user into a communication application program, wherein the text represents typed or audibly spoken content input by the user; determining, by a computing system, a level of randomness of characters in a portion of the text; identifying a threshold level of randomness from a plurality of different threshold levels of randomness based at least in part on a particular label of a text entry field into which the portion of the text was input; determining, by a computing system, whether the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness; and responsive to determining that the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness, precluding, by a computing system, a text processing system from performing a spell checking procedure on the portion of the text or from performing a word auto complete procedure on the portion of the text. | 1. A computer-implemented method, comprising: receiving, by a computing system, text of a message entered by a user into a communication application program, wherein the text represents typed or audibly spoken content input by the user; determining, by a computing system, a level of randomness of characters in a portion of the text; identifying a threshold level of randomness from a plurality of different threshold levels of randomness based at least in part on a particular label of a text entry field into which the portion of the text was input; determining, by a computing system, whether the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness; and responsive to determining that the level of randomness of the characters in the portion of the text satisfies the threshold level of randomness, precluding, by a computing system, a text processing system from performing a spell checking procedure on the portion of the text or from performing a word auto complete procedure on the portion of the text. 14. The computer-implemented method of claim 1 , further comprising: responsive to determining that the level of randomness of the characters in the portion of the text does not satisfy the threshold level of randomness, permitting, by a computing system, the text processing system to perform a spell checking procedure on the portion of the text or to perform a word auto complete procedure on the portion of the text. | 0.784836 |
7,567,922 | 1 | 4 | 1. A method for generating a normalized configuration model, the method comprising: utilizing at least portions of a normalized model generation system to perform: generating product configuration instances from one or more product configuration models that include non-normalized feature references; identifying non-normalized feature references included in one or more of the product configuration instances; accessing a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locating normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replacing non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generating a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references. | 1. A method for generating a normalized configuration model, the method comprising: utilizing at least portions of a normalized model generation system to perform: generating product configuration instances from one or more product configuration models that include non-normalized feature references; identifying non-normalized feature references included in one or more of the product configuration instances; accessing a mapping file, wherein the mapping file includes a map of specific product feature references to normalized feature references; locating normalized feature references that correlate with non-normalized feature references included in the generated product configuration instances; replacing non-normalized feature references with correlating normalized feature references in accordance with the mapping file; and generating a normalized configuration model corresponding to the generated product configuration instances using the normalized feature references replacements, wherein the normalized configuration model is configured for use with a configuration system which presents the normalized feature references to a user of the configuration system to allow the user to configure a product using the normalized feature references. 4. The method of claim 1 further comprising: providing access to the normalized configuration model to a contextual configuration engine. | 0.742481 |
7,953,694 | 18 | 19 | 18. The system of claim 14 , wherein the at least one program further comprises: generating a new statement for retrieving multidimensional information, wherein the new statement is a structured query language statement and wherein the structured query language statement is generated based on the one or more aggregations in each of the measures. | 18. The system of claim 14 , wherein the at least one program further comprises: generating a new statement for retrieving multidimensional information, wherein the new statement is a structured query language statement and wherein the structured query language statement is generated based on the one or more aggregations in each of the measures. 19. The system of claim 18 , wherein the one or more aggregations is a list of aggregations and wherein the list of aggregations comprises a list of aggregation functions and corresponding dimensions sets. | 0.951605 |
10,110,385 | 14 | 16 | 14. A non-transitory computer-readable storage medium having stored thereon executable instructions that, as a result of execution by one or more processors of a computer system, cause the computer system to at least: receive a signature of a signatory, wherein the signatory is associated with a plurality of sets of credential data, wherein each set of credential data is associated with a corresponding duress level of a plurality of duress levels; receive a document identifier for identifying a document, the document identifier derived based at least in part from document contents; obtain a token identifier for identifying a token, wherein the token is authorized by a service provider to generate signatures and comprises a set of private keys of a public-private key scheme; generate a first signature, using the token, wherein the signature is based at least in part on encrypting the document identifier using a first private key of the set of private keys; determine, based at least in part on the signature, the document identifier, the token identifier, and a public key from a set of public keys corresponding to the set of private keys of the public-private key scheme; determine that the generated first signature is not a match to the received signature of the signatory; generate a second signature based at least in part on the document identifier, the second set of credential data, and the identity verification identifier, wherein the second signature is based at least in part on encrypting the document identifier using the second private key; determine that the generated second signature is a match to the received signature of the signatory and that the signature received is associated with a duress level of the plurality of duress levels, wherein the duress level indicates an occurrence of an event that is: a duress event, or a signing event that exceeded a signing authority of the signatory; and perform an action as a result of the event determined to have occurred. | 14. A non-transitory computer-readable storage medium having stored thereon executable instructions that, as a result of execution by one or more processors of a computer system, cause the computer system to at least: receive a signature of a signatory, wherein the signatory is associated with a plurality of sets of credential data, wherein each set of credential data is associated with a corresponding duress level of a plurality of duress levels; receive a document identifier for identifying a document, the document identifier derived based at least in part from document contents; obtain a token identifier for identifying a token, wherein the token is authorized by a service provider to generate signatures and comprises a set of private keys of a public-private key scheme; generate a first signature, using the token, wherein the signature is based at least in part on encrypting the document identifier using a first private key of the set of private keys; determine, based at least in part on the signature, the document identifier, the token identifier, and a public key from a set of public keys corresponding to the set of private keys of the public-private key scheme; determine that the generated first signature is not a match to the received signature of the signatory; generate a second signature based at least in part on the document identifier, the second set of credential data, and the identity verification identifier, wherein the second signature is based at least in part on encrypting the document identifier using the second private key; determine that the generated second signature is a match to the received signature of the signatory and that the signature received is associated with a duress level of the plurality of duress levels, wherein the duress level indicates an occurrence of an event that is: a duress event, or a signing event that exceeded a signing authority of the signatory; and perform an action as a result of the event determined to have occurred. 16. The non-transitory computer-readable storage medium of claim 14 , wherein the instructions that cause the computer system to at least receive the signature include instructions that cause the system to receive the signature of the signatory by scanning an optically scannable code. | 0.789513 |
8,332,350 | 1 | 2 | 1. A computerized method for automatically creating a security access policy to an electronic document in a document management system, the method comprising: employing at least one hardware processor for performing one or more of the following: (a1) associating metadata with the document, the metadata comprising one or more attributes of the document; (b1) configuring security access policies to be applied to documents in the document management system, comprising specifying one or more metadata rules governing application of security access policies to the documents, comprising specifying a dynamic metadata, which is dynamically retrieved based on external content analysis of the document performed outside the document management system, comprising the metadata not inferred from contents of the document; and (c1) determining the security access policy to be applied to the document to be added to the document management system based on said one or more metadata rules and the metadata associated with the document. | 1. A computerized method for automatically creating a security access policy to an electronic document in a document management system, the method comprising: employing at least one hardware processor for performing one or more of the following: (a1) associating metadata with the document, the metadata comprising one or more attributes of the document; (b1) configuring security access policies to be applied to documents in the document management system, comprising specifying one or more metadata rules governing application of security access policies to the documents, comprising specifying a dynamic metadata, which is dynamically retrieved based on external content analysis of the document performed outside the document management system, comprising the metadata not inferred from contents of the document; and (c1) determining the security access policy to be applied to the document to be added to the document management system based on said one or more metadata rules and the metadata associated with the document. 2. The method of claim 1 , wherein the step (b1) comprises: (a2) creating said one or more metadata rules, comprising configuring a permission configuration web page; (b2) storing said one or more metadata rules in a permissions setting configuration file; and (c2) communicating the permissions setting configuration file to the document management system. | 0.713023 |
8,078,961 | 1 | 3 | 1. An SGML validation system comprising: an XML validation engine; a translator configured to convert an SGML document to a translated XML document using a p-isomorphic translation; an XML schema against which the XML validation engine validates the translated XML document, the XML schema configured such that errors detected by the validation of the translated XML document correspond to SGML errors in the SGML document; and a report generator configured to generate an error report identifying SGML errors corresponding with errors detected by the validation and linking the identified SGML errors with corresponding locations in the SGML document; wherein the XML validation engine, the translator, and the report generator are embodied as a digital processing device. | 1. An SGML validation system comprising: an XML validation engine; a translator configured to convert an SGML document to a translated XML document using a p-isomorphic translation; an XML schema against which the XML validation engine validates the translated XML document, the XML schema configured such that errors detected by the validation of the translated XML document correspond to SGML errors in the SGML document; and a report generator configured to generate an error report identifying SGML errors corresponding with errors detected by the validation and linking the identified SGML errors with corresponding locations in the SGML document; wherein the XML validation engine, the translator, and the report generator are embodied as a digital processing device. 3. The SGML validation system as set forth in claim 1 , wherein the XML schema comprises: a first XML schema component, errors detected by validation against the first XML schema component corresponding to violations of constraints defined in an SGML DTD associated with the SGML document; and a second XML schema component, errors detected by validation against the second XML schema component corresponding to violations of a set of business rules. | 0.501109 |
8,775,158 | 10 | 11 | 10. The data processing device, as claimed in claim 2 , comprising: a semantic association level calculation unit for calculating a semantic association level which indicates strength of semantic association between words included in the association nodes; wherein the association node joint unit categorizes the association nodes into the strong association nodes and the weak association nodes based on the semantic association level. | 10. The data processing device, as claimed in claim 2 , comprising: a semantic association level calculation unit for calculating a semantic association level which indicates strength of semantic association between words included in the association nodes; wherein the association node joint unit categorizes the association nodes into the strong association nodes and the weak association nodes based on the semantic association level. 11. The data processing device, as claimed in claim 10 , wherein the association node joint unit categorizes the association nodes, of which the semantic association level is less than a first threshold, as the weak association nodes, and categorizes the association nodes, of which the semantic association level is equal to the first threshold or more, into the strong association node. | 0.889143 |
8,341,108 | 4 | 5 | 4. The nonvolatile computer-readable medium of claim 1 , comprising: creating a user feature vector for a user based upon one or more Kind feature vectors of Kinds associated with the user. | 4. The nonvolatile computer-readable medium of claim 1 , comprising: creating a user feature vector for a user based upon one or more Kind feature vectors of Kinds associated with the user. 5. The nonvolatile computer-readable medium of claim 4 , the creating a user feature vector comprising: creating one or more dimensions within the user feature vector; and for respective dimensions within the user feature vector, assigning a probabilistic value to a dimension within the user feature vector based upon the probability the user relates to a characteristic of the dimension. | 0.744079 |
8,407,041 | 15 | 20 | 15. A computer-implemented training method, comprising acts of: deriving probabilistic decision variables based on decision rules as an integrated scoring framework to evaluate translated output of a machine translation process; training the probabilistic decision variables based on an objective function that integrates a speech recognition process and the machine translation process; updating the decision variables based on gradient-based training; and utilizing a processor to execute the objective function. | 15. A computer-implemented training method, comprising acts of: deriving probabilistic decision variables based on decision rules as an integrated scoring framework to evaluate translated output of a machine translation process; training the probabilistic decision variables based on an objective function that integrates a speech recognition process and the machine translation process; updating the decision variables based on gradient-based training; and utilizing a processor to execute the objective function. 20. The method of claim 15 , further comprising evaluating the translated output utilizing at least one of a translation score, acoustic score, or a language model score as the decision variables. | 0.86119 |
10,031,907 | 9 | 11 | 9. A method comprising: collecting from a plurality of software applications, via configurable data collection components of a computer processor, text data and text metadata representing an initial state of each of the software applications and supplying the text data and text metadata to a central text matching component, the central text matching component maintaining a database of the text data and text metadata, wherein the text data and the text metadata collected by the configurable data collection components is selected by the configurable data collection components based on data collection settings of the configurable data collection components, wherein the data collection settings of the configurable data collection components establish what type and amount of the text data and text metadata are to be collected by the data collection components from each of the software applications; collecting by the configurable data collection components text data and text metadata representing changes to the state of at least one of the plurality of software applications and supplying the change text data and metadata to the central text matching component; updating by the central text matching component the database of text data and text metadata based on the changes; entering text by a user into a text entry field of a software application and supplying the entered text and any metadata associated with the text entry to the central text matching component; comparing the entered text and associated text metadata to text data and text metadata in the database by the central text matching component and locating text strings matching the entered text data and metadata; ranking the matching text strings by the weighted ordering component using the text metadata of the text strings and weighted ordering component configuration settings; selecting one of the matching text strings and completing the entered text based on the text string selection; updating text metadata of the matching text string in the database to reflect the selection; and updating the configuration settings of the weighted ordering component based on said updated text metadata. | 9. A method comprising: collecting from a plurality of software applications, via configurable data collection components of a computer processor, text data and text metadata representing an initial state of each of the software applications and supplying the text data and text metadata to a central text matching component, the central text matching component maintaining a database of the text data and text metadata, wherein the text data and the text metadata collected by the configurable data collection components is selected by the configurable data collection components based on data collection settings of the configurable data collection components, wherein the data collection settings of the configurable data collection components establish what type and amount of the text data and text metadata are to be collected by the data collection components from each of the software applications; collecting by the configurable data collection components text data and text metadata representing changes to the state of at least one of the plurality of software applications and supplying the change text data and metadata to the central text matching component; updating by the central text matching component the database of text data and text metadata based on the changes; entering text by a user into a text entry field of a software application and supplying the entered text and any metadata associated with the text entry to the central text matching component; comparing the entered text and associated text metadata to text data and text metadata in the database by the central text matching component and locating text strings matching the entered text data and metadata; ranking the matching text strings by the weighted ordering component using the text metadata of the text strings and weighted ordering component configuration settings; selecting one of the matching text strings and completing the entered text based on the text string selection; updating text metadata of the matching text string in the database to reflect the selection; and updating the configuration settings of the weighted ordering component based on said updated text metadata. 11. The method of claim 9 wherein the selecting one of the matching text strings comprises: selecting by the central text matching component the top ranked one of the text strings matching the text data and text metadata based on ranking applied by the weighted ordering component; and completing the entered text based on the text string selection. | 0.723892 |
8,831,571 | 9 | 11 | 9. A system comprising: a memory comprising instructions; a processor, wherein the processor, when executing the instructions, performs operations comprising: receiving, via a transceiver, an electronic communication comprising a user-composed body comprising text in a first form; detecting, by the processor, a keyword in the user-composed body of the electronic communication; determining, by the processor based on the keyword, that a reply electronic communication is to be automatically generated; determining, by the processor, a subset of received electronic communications in the first form that each comprise a user-composed body comprising the keyword; determining, by the processor, an average response time for the subset of received electronic communications; determining, by the processor, that a criteria is met based on the data the average response time meets a threshold; responsive to determining that the average response time meets the threshold, generating, by the processor, the reply electronic communication comprising the average response time; and transmitting, via the transceiver, the reply electronic communication in the first form. | 9. A system comprising: a memory comprising instructions; a processor, wherein the processor, when executing the instructions, performs operations comprising: receiving, via a transceiver, an electronic communication comprising a user-composed body comprising text in a first form; detecting, by the processor, a keyword in the user-composed body of the electronic communication; determining, by the processor based on the keyword, that a reply electronic communication is to be automatically generated; determining, by the processor, a subset of received electronic communications in the first form that each comprise a user-composed body comprising the keyword; determining, by the processor, an average response time for the subset of received electronic communications; determining, by the processor, that a criteria is met based on the data the average response time meets a threshold; responsive to determining that the average response time meets the threshold, generating, by the processor, the reply electronic communication comprising the average response time; and transmitting, via the transceiver, the reply electronic communication in the first form. 11. The system of claim 9 , wherein the operations further comprise transmitting, via the transceiver, the electronic communication to a recipient of the electronic communication in a second form that is different from the first form. | 0.502128 |
10,102,185 | 7 | 12 | 7. A device comprising: a display; a processor; and a memory communicatively coupled to the processor, the memory storing instructions causing the processor, after execution of the instructions by the processor, to: retrieve a digital document including embedded reference page numbers that correspond to page numbers of a reference document corresponding to the digital document; assign a fractional page number to each page to be rendered of the digital document based on characteristics of the display; and render the digital document on the display including a reference page number and a fractional page number for each rendered page of the digital document such that the reference page number and the fractional page number indicate a portion of a page of the reference document, wherein to render the digital document is based on the characteristics of the display that change the amount of content that can fit on the display, and wherein the fractional page number is updated in response to the characteristics of the display being changed, and wherein the characteristics include at least one from the group of screen size, window size, font size, line spacing, form factor, and resolution. | 7. A device comprising: a display; a processor; and a memory communicatively coupled to the processor, the memory storing instructions causing the processor, after execution of the instructions by the processor, to: retrieve a digital document including embedded reference page numbers that correspond to page numbers of a reference document corresponding to the digital document; assign a fractional page number to each page to be rendered of the digital document based on characteristics of the display; and render the digital document on the display including a reference page number and a fractional page number for each rendered page of the digital document such that the reference page number and the fractional page number indicate a portion of a page of the reference document, wherein to render the digital document is based on the characteristics of the display that change the amount of content that can fit on the display, and wherein the fractional page number is updated in response to the characteristics of the display being changed, and wherein the characteristics include at least one from the group of screen size, window size, font size, line spacing, form factor, and resolution. 12. The device of claim 7 , wherein the memory stores instructions causing the processor, after execution of the instructions by the processor, to: based on the reference page numbers and fractional page numbers, determine print charges for the digital document, estimate bandwidth for transmitting the digital document, or determine the type of content of the digital document. | 0.501319 |
7,580,937 | 13 | 17 | 13. A system for generating and transmitting a calendar of different legal events capable of occurring in the course of a legal proceeding, the system comprising: a database storing at least one rule set including a plurality of date calculation instructions for calculating a plurality of different legal events; a server coupled to the database, the server being configured to: receive an initial trigger date for an initial trigger legal event; select one or more date calculation instructions from the database based on the initial trigger legal event; calculate one or more event dates based on the initial trigger date and the retrieved date calculation instructions; transmit the one or more calculated event dates to a user client; and maintain a transaction record of the one or more date calculation instructions used for generating the one or more event dates for the user client; a database update module coupled to the server, the database update module being configured to monitor a changes table for changes in the plurality of date calculation instructions, the changes table identifying the changed date calculation instructions; and a date maintenance module configured to automatically determine whether the one or more date calculation instructions identified in the record are identified in the changes table, and, for each one of the one or more date calculation instructions identified in the changes table, the date maintenance module being further configured to recalculate the associated event date based on the change to the corresponding date calculation instruction, and transmit the recalculated one or more event dates to the user client. | 13. A system for generating and transmitting a calendar of different legal events capable of occurring in the course of a legal proceeding, the system comprising: a database storing at least one rule set including a plurality of date calculation instructions for calculating a plurality of different legal events; a server coupled to the database, the server being configured to: receive an initial trigger date for an initial trigger legal event; select one or more date calculation instructions from the database based on the initial trigger legal event; calculate one or more event dates based on the initial trigger date and the retrieved date calculation instructions; transmit the one or more calculated event dates to a user client; and maintain a transaction record of the one or more date calculation instructions used for generating the one or more event dates for the user client; a database update module coupled to the server, the database update module being configured to monitor a changes table for changes in the plurality of date calculation instructions, the changes table identifying the changed date calculation instructions; and a date maintenance module configured to automatically determine whether the one or more date calculation instructions identified in the record are identified in the changes table, and, for each one of the one or more date calculation instructions identified in the changes table, the date maintenance module being further configured to recalculate the associated event date based on the change to the corresponding date calculation instruction, and transmit the recalculated one or more event dates to the user client. 17. The system of claim 13 , wherein the database update module is further configured to receive update information for updating the date calculation instructions identified in the changes table, the update information identifying a rule set affected by the update, the database update module being further configured to identify the update as an event maintenance update or a non-event maintenance update, the event maintenance update triggering the recalculation of the one or more event dates identified in the changes table. | 0.500945 |
7,962,925 | 5 | 6 | 5. A system according to claim 1 , wherein said schema compiler is adapted to accept a pre-defined schema. | 5. A system according to claim 1 , wherein said schema compiler is adapted to accept a pre-defined schema. 6. A system according to claim 5 , wherein said API is further capable of validating the XML document against the pre-defined schema and reporting any discrepancies. | 0.951241 |
9,607,032 | 9 | 14 | 9. A system comprising: one or more data processing apparatus; and a data storage device storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: serving, to a user device, a document that includes value text that specifies a first value that is not tagged as a time sensitive attribute value; automatically identifying an entity based on entity text included in document text of the document after serving the document to the user device; automatically, after the document is served to the user device, identifying a time-sensitive attribute for the entity specified by attribute text included in the document text, wherein attributes identified by the document text have not previously been identified for the document as time-sensitive before serving the document; identifying the first value for the time-sensitive attribute based on the value text included in the document text; providing data to the user device that causes a prompt to be displayed in the document, the prompt identifying the first value for the time-sensitive attribute and including a user-selectable interface element that, upon selection, will cause the first value for the time-sensitive attribute to be tagged as a time-sensitive attribute value; and generating, responsive to a selection of the user-selectable interface element, a tag for the first value for the time-sensitive attribute in response to receiving user input indicating a selection of the user-selectable interface element, the tag indicating that the first value is time-sensitive, and wherein the tag causes the value text specifying the first value to be updated in response to one or more predetermined actions; responsive to generating the tag, generating a query specifying the entity; providing the query to a search system that provides a result value for the time-sensitive attribute of the entity included in the query; providing, to a user device that is currently accessing the document, result data that causes presentation of the result value as a replacement for the first value as indicated by the tag. | 9. A system comprising: one or more data processing apparatus; and a data storage device storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: serving, to a user device, a document that includes value text that specifies a first value that is not tagged as a time sensitive attribute value; automatically identifying an entity based on entity text included in document text of the document after serving the document to the user device; automatically, after the document is served to the user device, identifying a time-sensitive attribute for the entity specified by attribute text included in the document text, wherein attributes identified by the document text have not previously been identified for the document as time-sensitive before serving the document; identifying the first value for the time-sensitive attribute based on the value text included in the document text; providing data to the user device that causes a prompt to be displayed in the document, the prompt identifying the first value for the time-sensitive attribute and including a user-selectable interface element that, upon selection, will cause the first value for the time-sensitive attribute to be tagged as a time-sensitive attribute value; and generating, responsive to a selection of the user-selectable interface element, a tag for the first value for the time-sensitive attribute in response to receiving user input indicating a selection of the user-selectable interface element, the tag indicating that the first value is time-sensitive, and wherein the tag causes the value text specifying the first value to be updated in response to one or more predetermined actions; responsive to generating the tag, generating a query specifying the entity; providing the query to a search system that provides a result value for the time-sensitive attribute of the entity included in the query; providing, to a user device that is currently accessing the document, result data that causes presentation of the result value as a replacement for the first value as indicated by the tag. 14. The system of claim 9 , wherein the query specifies the time-sensitive attribute for the entity. | 0.90099 |
8,347,147 | 1 | 5 | 1. A method for lifecycle management of automated testing, comprising: processing a plurality of manual test cases for an application under test; associating a set of reusable test scripts to the plurality of manual test cases, wherein the set of reusable test scripts is selected from a library of reusable test scripts, wherein the library of reusable test scripts is accessed for an automated testing tool when the automated testing tool is selected from a number of licensed automated testing tools; executing the set of reusable test scripts for the application under test using the automated testing tool associated with the set of reusable test scripts; displaying automated testing projects which include the automated testing of the application under test; and displaying a return on investment (ROI) for each of the automated testing projects. | 1. A method for lifecycle management of automated testing, comprising: processing a plurality of manual test cases for an application under test; associating a set of reusable test scripts to the plurality of manual test cases, wherein the set of reusable test scripts is selected from a library of reusable test scripts, wherein the library of reusable test scripts is accessed for an automated testing tool when the automated testing tool is selected from a number of licensed automated testing tools; executing the set of reusable test scripts for the application under test using the automated testing tool associated with the set of reusable test scripts; displaying automated testing projects which include the automated testing of the application under test; and displaying a return on investment (ROI) for each of the automated testing projects. 5. The method of claim 1 , wherein the associating the set of reusable test scripts further comprises setting respective parameters for the set of reusable test scripts. | 0.517143 |
8,447,751 | 29 | 30 | 29. The apparatus of claim 27 , wherein the computer readable instructions, when executed, further cause the apparatus to: determine an improvement for raising the search engine score of the network document by analyzing at least one of: a missing meta title, a missing meta description, a missing meta keyword, a duplicate meta title, a duplicate meta description, a duplicate meta keyword, and a broken link; and display the improvement. | 29. The apparatus of claim 27 , wherein the computer readable instructions, when executed, further cause the apparatus to: determine an improvement for raising the search engine score of the network document by analyzing at least one of: a missing meta title, a missing meta description, a missing meta keyword, a duplicate meta title, a duplicate meta description, a duplicate meta keyword, and a broken link; and display the improvement. 30. The apparatus of claim 29 , wherein the computer readable instructions, when executed, further cause the apparatus to: receive a request to re-analyze the network document upon the improvement being made to the network document; and re-analyze the network document including the improvement. | 0.931235 |
8,589,373 | 1 | 4 | 1. A method for an improved News Meta-Search over a large number of Online news sources on the Internet or similar networks, comprising providing a meta-search system which includes at least one server, and displaying news items to a user through a browser on a computer, wherein the server performs, under software instruction from the meta-search system, at least one of the steps of: i. Switching between news items from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention; and ii. Switching between news images from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention, and wherein said images are at least one of still images and streaming data; wherein at least one of the following features exists: a. Recursive sub-clustering is performed and the recursive sub-clustering continues until there are sufficiently few items in the final sub-category or until the items are too different to group further; b. If the user searches for keywords in the News Meta Search, the results are displayed recursively in clusters and sub-cluster in a way similar to the automatically generated newspaper page; c. If the user searches for keywords in the News Meta Search, the results can have all the features that exist in the automatically generated newspaper page; d. The system enables the user to switch between a mode that displays also images and a mode without images; e. The same news item or same sub-cluster can belong to more than one cluster or sub-cluster, and thus it is shown and/or can be reached from all the sufficiently relevant clusters or sub-clusters to which it is related; f. The system enables the user to request to sort a list of related items by relevance and/or by time and date to create order between and/or within the sub-clusters, so that the system performs the sorting without interfering with the cluster structure itself; g. The system enables the user to request to sort the items by at least one of: 1. The country of the source, so that the system orders or clusters the news items in addition or instead also according to the country of the news source, 2. The level of reliability of the source, so that the system orders or clusters the news items in addition or instead also according to the reliability of the news source; h. The system enables the user to view a graphical or textual hierarchical representation which shows simultaneously the multi-level structure of clusters and sub-clusters, showing more than two levels of the hierarchy at the same time, or showing the structure down to the end-nodes; i. The Meta News system automatically chooses only images that are within a certain reasonable range of sizes; j. As additional new related news items come in, the headlines and/or the images can be automatically updated even if the user does not click on any refresh button; k. The user gets a different indication when the items or images themselves have changed or new items or images are brought in (compared to the normal swapping between items), and said indication is at least one of sound indication and visual indication of the item that has changed or the new item that has been inserted; l. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is either truncated automatically to fit in the allowed window, or is automatically downscaled in order to fit completely into the allowed space; m. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is truncated automatically to fit in the allowed window and for said truncation the improved html protocol allows the web programmer to specify for each image the x-y coordinates of its central point of interest, and/or various heuristics are used by the browser or by the server in order to find the central point of interest automatically; n. When switching images contain also streaming data, at least one of the following is done: 1. Automatic switching of images is disabled so that the user has to click on something in order to view related streaming data from a different source or other still images, and 2. Each streaming source remains in the position for a longer time than still images until switching to the next streaming source or to the next still image; o. The system determines which item to use as the main item of the general cluster by at least one of: 1. First picking the sub-cluster that has the largest number of items and/or the most recent cluster that is big enough relative to other sub-clusters, 2. Picking the item within the chosen first sub-cluster which has the highest average similarity to other items in that sub-cluster and/or belongs to the largest sub-cluster of that sub-cluster and/or is most relevant within the cluster or within the sub-cluster and/or is most recent within the cluster or within the sub-cluster; p. When requesting News alerts, instead of being able to request only by specific keywords, the system enables the user to also at least one of: 1. Mark a cluster or a specific sub-cluster, so that he/she is notified automatically on any new items that belong to that cluster or after sufficient changes have accumulated in the cluster, 2. Use semantic qualifiers, 3. Mark words in a way that indicates that synonyms should also be checked for these words, so that he/she will be notified also about items that contain synonyms of these marked words; and wherein at least one of the following features exists: q. In order to improve the clustering ability, the time the items were published is taken into account, with the assumption that the closer the time of publication between them, the higher the chance that two items are dealing with the same event; r. Temporal words or phrases used in the news item are used to decide when the event occurred, and this time is used to separate between news items that occurred before this time and items that occurred after this time and/or to help decide the similarity between items that might be referring to the same event; s. Temporal words or phrases used in the news item are used to decide when the event occurred, and in order to analyze the temporal phrases used in the item, the system is able to perform also at least some minimal type of semantic analysis and/or has at least knowledge of the relevant temporal nouns and relevant verbs; and t. When sorting automatically generated news clusters the number of items in each cluster is normalized by the time factor, since clusters that have exited for a longer time would normally have more items than a newer cluster even if the new cluster is more important. | 1. A method for an improved News Meta-Search over a large number of Online news sources on the Internet or similar networks, comprising providing a meta-search system which includes at least one server, and displaying news items to a user through a browser on a computer, wherein the server performs, under software instruction from the meta-search system, at least one of the steps of: i. Switching between news items from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention; and ii. Switching between news images from the same cluster or sub-cluster which are displayed in a given position in an automatically generated newspaper page, wherein said switching is done automatically or with user intervention, and wherein said images are at least one of still images and streaming data; wherein at least one of the following features exists: a. Recursive sub-clustering is performed and the recursive sub-clustering continues until there are sufficiently few items in the final sub-category or until the items are too different to group further; b. If the user searches for keywords in the News Meta Search, the results are displayed recursively in clusters and sub-cluster in a way similar to the automatically generated newspaper page; c. If the user searches for keywords in the News Meta Search, the results can have all the features that exist in the automatically generated newspaper page; d. The system enables the user to switch between a mode that displays also images and a mode without images; e. The same news item or same sub-cluster can belong to more than one cluster or sub-cluster, and thus it is shown and/or can be reached from all the sufficiently relevant clusters or sub-clusters to which it is related; f. The system enables the user to request to sort a list of related items by relevance and/or by time and date to create order between and/or within the sub-clusters, so that the system performs the sorting without interfering with the cluster structure itself; g. The system enables the user to request to sort the items by at least one of: 1. The country of the source, so that the system orders or clusters the news items in addition or instead also according to the country of the news source, 2. The level of reliability of the source, so that the system orders or clusters the news items in addition or instead also according to the reliability of the news source; h. The system enables the user to view a graphical or textual hierarchical representation which shows simultaneously the multi-level structure of clusters and sub-clusters, showing more than two levels of the hierarchy at the same time, or showing the structure down to the end-nodes; i. The Meta News system automatically chooses only images that are within a certain reasonable range of sizes; j. As additional new related news items come in, the headlines and/or the images can be automatically updated even if the user does not click on any refresh button; k. The user gets a different indication when the items or images themselves have changed or new items or images are brought in (compared to the normal swapping between items), and said indication is at least one of sound indication and visual indication of the item that has changed or the new item that has been inserted; l. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is either truncated automatically to fit in the allowed window, or is automatically downscaled in order to fit completely into the allowed space; m. The html protocol and/or the html command set is expanded to allow an image to be requested with a given size limit, so that if the original image is bigger it is truncated automatically to fit in the allowed window and for said truncation the improved html protocol allows the web programmer to specify for each image the x-y coordinates of its central point of interest, and/or various heuristics are used by the browser or by the server in order to find the central point of interest automatically; n. When switching images contain also streaming data, at least one of the following is done: 1. Automatic switching of images is disabled so that the user has to click on something in order to view related streaming data from a different source or other still images, and 2. Each streaming source remains in the position for a longer time than still images until switching to the next streaming source or to the next still image; o. The system determines which item to use as the main item of the general cluster by at least one of: 1. First picking the sub-cluster that has the largest number of items and/or the most recent cluster that is big enough relative to other sub-clusters, 2. Picking the item within the chosen first sub-cluster which has the highest average similarity to other items in that sub-cluster and/or belongs to the largest sub-cluster of that sub-cluster and/or is most relevant within the cluster or within the sub-cluster and/or is most recent within the cluster or within the sub-cluster; p. When requesting News alerts, instead of being able to request only by specific keywords, the system enables the user to also at least one of: 1. Mark a cluster or a specific sub-cluster, so that he/she is notified automatically on any new items that belong to that cluster or after sufficient changes have accumulated in the cluster, 2. Use semantic qualifiers, 3. Mark words in a way that indicates that synonyms should also be checked for these words, so that he/she will be notified also about items that contain synonyms of these marked words; and wherein at least one of the following features exists: q. In order to improve the clustering ability, the time the items were published is taken into account, with the assumption that the closer the time of publication between them, the higher the chance that two items are dealing with the same event; r. Temporal words or phrases used in the news item are used to decide when the event occurred, and this time is used to separate between news items that occurred before this time and items that occurred after this time and/or to help decide the similarity between items that might be referring to the same event; s. Temporal words or phrases used in the news item are used to decide when the event occurred, and in order to analyze the temporal phrases used in the item, the system is able to perform also at least some minimal type of semantic analysis and/or has at least knowledge of the relevant temporal nouns and relevant verbs; and t. When sorting automatically generated news clusters the number of items in each cluster is normalized by the time factor, since clusters that have exited for a longer time would normally have more items than a newer cluster even if the new cluster is more important. 4. The method of claim 1 wherein at least one of the following features exists: a. In order to enable the multi-level sub-clustering the same or similar principles are applied similarly at all levels, except that in each step they are applied now to the items of the previous cluster or sub-cluster in order to further divide them into additional sub-clusters; b. For clustering the system analyses the similarity in the occurrence of combinations of two or more words in the headline and/or in the first 1 or 2 sentences and/or in the entire item. | 0.871723 |
9,275,121 | 10 | 11 | 10. A computer program product encoded on a tangible, non-transitory storage medium, the product comprising computer readable instructions for causing one or more processors to perform operations comprising: receiving, by a computer system, a request to execute a shared query, wherein the shared query comprises one of a plurality of pre-defined shared queries, and the shared query comprises a pre-defined query specification associated with the shared query, the query specification comprising pre-defined connections to a first and a second data sources associated with the shared query, the query specification specifying the shared query on a semantic layer and including search terms, parameters, filters, and aspects of the shared query to be used at runtime upon execution of the shared query, where each pre-defined shared query of the plurality of pre-defined shared queries is associated with a corresponding set of access rights, and wherein the request to execute the shared query represents a specific request to execute a particular shared query from the plurality of pre-defined shared queries from a particular application or user; in response to receiving the request, determining whether the particular application or user is allowed to access the shared query based on the set of access rights associated with the shared query; allowing execution of the shared query upon a determination that the particular application or user is allowed to access the shared query, wherein allowing execution of the share query includes: identifying the pre-defined query specification associated with the shared query; in response to the identifying the pre-defined query specification, identifying the first data source and the second data source based on the identified query specification; generating a native query for each respective data source of the identified first and second data sources based on the identified query specification; executing the generated native queries at the respective data sources to collect a set of query results from the respective data sources; and formatting the set of query results from the respective data sources into a unified set of query results; and rejecting the execution request upon a determination that the particular application or user is not allowed to access the shared query. | 10. A computer program product encoded on a tangible, non-transitory storage medium, the product comprising computer readable instructions for causing one or more processors to perform operations comprising: receiving, by a computer system, a request to execute a shared query, wherein the shared query comprises one of a plurality of pre-defined shared queries, and the shared query comprises a pre-defined query specification associated with the shared query, the query specification comprising pre-defined connections to a first and a second data sources associated with the shared query, the query specification specifying the shared query on a semantic layer and including search terms, parameters, filters, and aspects of the shared query to be used at runtime upon execution of the shared query, where each pre-defined shared query of the plurality of pre-defined shared queries is associated with a corresponding set of access rights, and wherein the request to execute the shared query represents a specific request to execute a particular shared query from the plurality of pre-defined shared queries from a particular application or user; in response to receiving the request, determining whether the particular application or user is allowed to access the shared query based on the set of access rights associated with the shared query; allowing execution of the shared query upon a determination that the particular application or user is allowed to access the shared query, wherein allowing execution of the share query includes: identifying the pre-defined query specification associated with the shared query; in response to the identifying the pre-defined query specification, identifying the first data source and the second data source based on the identified query specification; generating a native query for each respective data source of the identified first and second data sources based on the identified query specification; executing the generated native queries at the respective data sources to collect a set of query results from the respective data sources; and formatting the set of query results from the respective data sources into a unified set of query results; and rejecting the execution request upon a determination that the particular application or user is not allowed to access the shared query. 11. The computer program product of claim 10 , wherein the at least one of the first data source and the second data source includes at least one business object universe and at least one of a text file, a web service, an extensible markup language (XML) file, and a spreadsheet file. | 0.785174 |
10,065,104 | 6 | 8 | 6. A device having a display configured to display a game board having a plurality of selectable game objects comprising tiles displayed in a configuration on said game board, a user interface configured to receive user input, and at least one processor in connection or communication with at least one memory and the user interface and configured to: responsive to user input received via the user interface of said user device, determine a game level of a plurality of game levels which is to be provided, each game level having an associated difficulty; use at least one dictionary stored in a memory to select one or more words stored in the at least one dictionary to seed an initial game board which is to be displayed on the display for the determined game level, the at least one dictionary comprising a plurality of words of a first type and a plurality of words of a second type, said words of the first type and the second type being in a common language, the plurality of words of the second type categorised as more common than the plurality of words of the first type, wherein at least one of a type of said selected at least one word and orientation in which said at least one word is displayed is dependent on the associated difficulty of the determined game level; cause to be displayed on the display a plurality of selectable game objects comprising tiles arranged on the initial game board, each tile having a letter, said tiles in said game board being arranged to enable a user to select one or more of the tiles in a manner that spells a word, the initial game board including said selected at least one word; receive user input, via the user interface, selecting a plurality of said tiles of said initial game board to spell a word; determine if the spelled word comprises a valid input, said spelled word being a valid input if the spelled word is in said at least one dictionary, wherein words of said first type and words of said second type both comprise valid inputs; in response to determining that said spelled word is a valid input, cause said selected tiles to be removed from said game board; and cause said game board to be replenished after said selected tiles have been removed. | 6. A device having a display configured to display a game board having a plurality of selectable game objects comprising tiles displayed in a configuration on said game board, a user interface configured to receive user input, and at least one processor in connection or communication with at least one memory and the user interface and configured to: responsive to user input received via the user interface of said user device, determine a game level of a plurality of game levels which is to be provided, each game level having an associated difficulty; use at least one dictionary stored in a memory to select one or more words stored in the at least one dictionary to seed an initial game board which is to be displayed on the display for the determined game level, the at least one dictionary comprising a plurality of words of a first type and a plurality of words of a second type, said words of the first type and the second type being in a common language, the plurality of words of the second type categorised as more common than the plurality of words of the first type, wherein at least one of a type of said selected at least one word and orientation in which said at least one word is displayed is dependent on the associated difficulty of the determined game level; cause to be displayed on the display a plurality of selectable game objects comprising tiles arranged on the initial game board, each tile having a letter, said tiles in said game board being arranged to enable a user to select one or more of the tiles in a manner that spells a word, the initial game board including said selected at least one word; receive user input, via the user interface, selecting a plurality of said tiles of said initial game board to spell a word; determine if the spelled word comprises a valid input, said spelled word being a valid input if the spelled word is in said at least one dictionary, wherein words of said first type and words of said second type both comprise valid inputs; in response to determining that said spelled word is a valid input, cause said selected tiles to be removed from said game board; and cause said game board to be replenished after said selected tiles have been removed. 8. A device as set forth in claim 6 , wherein the plurality of words of the first type are stored in a first dictionary, and the plurality of words of the second type are stored in a second dictionary. | 0.551339 |
8,688,366 | 1 | 4 | 1. A computer implemented method of operating a navigation system to provide geographic location information, the method comprising: receiving a text string query for only a child geographic location; providing a plurality of candidate geographic locations for the child geographic location from a geographic database; receiving a selection of one of the candidate geographic locations from a user; recording the candidate geographic location that was selected in a use history database; increasing, using a processor, a usage pattern weight for the candidate geographic location that was selected; and increasing, using the processor, a usage pattern weight for a parent geographic feature that includes the child geographic location from the text string query, wherein the parent geographic feature is a composite geographic feature that includes other geographic features. | 1. A computer implemented method of operating a navigation system to provide geographic location information, the method comprising: receiving a text string query for only a child geographic location; providing a plurality of candidate geographic locations for the child geographic location from a geographic database; receiving a selection of one of the candidate geographic locations from a user; recording the candidate geographic location that was selected in a use history database; increasing, using a processor, a usage pattern weight for the candidate geographic location that was selected; and increasing, using the processor, a usage pattern weight for a parent geographic feature that includes the child geographic location from the text string query, wherein the parent geographic feature is a composite geographic feature that includes other geographic features. 4. The method of claim 1 further comprising: recording the query in the use history database. | 0.881679 |
8,516,458 | 2 | 44 | 2. A computer-programming tool as claimed in claim 1 , wherein said first data structure is at least partly a heterogeneous tree structure. | 2. A computer-programming tool as claimed in claim 1 , wherein said first data structure is at least partly a heterogeneous tree structure. 44. A computer programming tool as claimed in claim 2 , wherein the heterogeneous tree structure is an abstract syntax tree. | 0.978352 |
4,866,778 | 21 | 22 | 21. A speech recognition system for recognizing a succession of words comprising: means for receiving an acoustic description of a portion of speech to be recognized; means for storing an acoustic description of each word in a system vocabulary; recognition means for making a determination of which one or more words of a sub-vocabulary comprised of one or more words of said system vocabulary most probably correspond to said portion of speech, said recognition means including comparing means for determining how closely the acoustic description of said portion of speech compares to the acoustic descriptions of words from said sub-vocabulary; means for storing a body of text comprised of one or more words and for associating the portion of speech to be recognized with a location in that text which can be preceded by one or more of said words first-pass means for causing said recognition means to make a first determination of which one or more words of a first sub-vocabulary of said system vocabulary most probably correspond to said portion of speech, said first pass-means including language model filtering means for selecting said first sub-vocabulary as a function of the sequence of one or more words preceding the location associated with the speech to be recognized in said body of text; and means for displaying said one or more words of said first sub-vocabulary selected by said first determination as most probably corresponding to said portion of speech; re-recognition means for causing said recognition means to start making a second determination of which one or more words of a second sub-vocabulary, which can be different from said first sub-vocabulary, most probably correspond to said portion of speech; control-input means for enabling an operator to input a command to control the re-recognition process; and means for aborting, in response to in input of said command by said operator, said second determination of which one or more words of said second sub-vocabulary most probably correspond to said portion of speech. | 21. A speech recognition system for recognizing a succession of words comprising: means for receiving an acoustic description of a portion of speech to be recognized; means for storing an acoustic description of each word in a system vocabulary; recognition means for making a determination of which one or more words of a sub-vocabulary comprised of one or more words of said system vocabulary most probably correspond to said portion of speech, said recognition means including comparing means for determining how closely the acoustic description of said portion of speech compares to the acoustic descriptions of words from said sub-vocabulary; means for storing a body of text comprised of one or more words and for associating the portion of speech to be recognized with a location in that text which can be preceded by one or more of said words first-pass means for causing said recognition means to make a first determination of which one or more words of a first sub-vocabulary of said system vocabulary most probably correspond to said portion of speech, said first pass-means including language model filtering means for selecting said first sub-vocabulary as a function of the sequence of one or more words preceding the location associated with the speech to be recognized in said body of text; and means for displaying said one or more words of said first sub-vocabulary selected by said first determination as most probably corresponding to said portion of speech; re-recognition means for causing said recognition means to start making a second determination of which one or more words of a second sub-vocabulary, which can be different from said first sub-vocabulary, most probably correspond to said portion of speech; control-input means for enabling an operator to input a command to control the re-recognition process; and means for aborting, in response to in input of said command by said operator, said second determination of which one or more words of said second sub-vocabulary most probably correspond to said portion of speech. 22. A speech recognition system as described in claim 21 wherein said language model filtering means selects said first sub-vocabulary so that it is comprised substantially of the words from said system vocabulary which are the most likely words to occur following said sequence of one or more words preceding the location associated with the speech to be recognized in said body of text, according to a probablistic model of what words are likely to occur after given other words in a given type of speech modeled by said probabilistic model. | 0.757156 |
9,208,450 | 15 | 16 | 15. An article of manufacture for processing electronic documents, the article of manufacture comprising: at least one non-transitory processor readable storage medium; and instructions stored on the at least one medium; wherein the instructions are configured to be readable from the at least one medium by at least one processor and thereby cause the at least one processor to operate so as to: obtain an electronic document being sent over a network toward a destination; analyze text content of the electronic documents to identify whether the electronic document matches any of a plurality of predefined document templates, wherein the electronic document conforms to a structure of at least one of the plurality of predefined document templates, and wherein the analyzing comprises executing at least one machine learning algorithm, the at least one machine learning algorithm trained using at least one sample electronic document having a predefined template; obtain a document loss prevention (DLP) policy based on the at least one predefined document template associated with the electronic document, wherein the DLP policy defines at least one rule to block sending of at least one of the electronic documents if the at least one of the electronic documents matches any of the plurality of predefined document templates; and selectively allow the electronic document to continue toward the destination based on the DLP policy. | 15. An article of manufacture for processing electronic documents, the article of manufacture comprising: at least one non-transitory processor readable storage medium; and instructions stored on the at least one medium; wherein the instructions are configured to be readable from the at least one medium by at least one processor and thereby cause the at least one processor to operate so as to: obtain an electronic document being sent over a network toward a destination; analyze text content of the electronic documents to identify whether the electronic document matches any of a plurality of predefined document templates, wherein the electronic document conforms to a structure of at least one of the plurality of predefined document templates, and wherein the analyzing comprises executing at least one machine learning algorithm, the at least one machine learning algorithm trained using at least one sample electronic document having a predefined template; obtain a document loss prevention (DLP) policy based on the at least one predefined document template associated with the electronic document, wherein the DLP policy defines at least one rule to block sending of at least one of the electronic documents if the at least one of the electronic documents matches any of the plurality of predefined document templates; and selectively allow the electronic document to continue toward the destination based on the DLP policy. 16. The article of manufacture of claim 15 , wherein the electronic document is obtained from an electronic mail message, and wherein the destination is represented by an electronic mail address. | 0.721429 |
10,127,323 | 15 | 20 | 15. A computer program product for generating a multi-document summary, the computer program product comprising: one or more computer-readable tangible storage media and program instructions stored on at least one of the one or more tangible storage media, the program instructions executable by a processor of a computer to perform a method, the method comprising: receiving a query statement, one or more documents, one or more summary constraints, and one or more goals; identifying one or more keywords within the query statement; performing a sentence selection from the one or more documents based on the one or more identified keywords; generating a plurality of candidate summaries of the one or more documents based on the performed sentence selection, the one or more goals, and a fully-polynomial randomized approximation scheme (FPRAS) cross entropy method; calculating a quality score for each of the plurality of generated candidate summaries using a plurality of quality features; and selecting a candidate summary from the plurality of generated candidate summaries with the highest calculated quality score that also satisfies a quality score threshold. | 15. A computer program product for generating a multi-document summary, the computer program product comprising: one or more computer-readable tangible storage media and program instructions stored on at least one of the one or more tangible storage media, the program instructions executable by a processor of a computer to perform a method, the method comprising: receiving a query statement, one or more documents, one or more summary constraints, and one or more goals; identifying one or more keywords within the query statement; performing a sentence selection from the one or more documents based on the one or more identified keywords; generating a plurality of candidate summaries of the one or more documents based on the performed sentence selection, the one or more goals, and a fully-polynomial randomized approximation scheme (FPRAS) cross entropy method; calculating a quality score for each of the plurality of generated candidate summaries using a plurality of quality features; and selecting a candidate summary from the plurality of generated candidate summaries with the highest calculated quality score that also satisfies a quality score threshold. 20. The computer program product of claim 15 , wherein the plurality of quality features are selected from a group consisting of measuring a Bhattacharyya similarity between a unigram language model (LM) of the received query statement and a unigram LM of a candidate summary within the plurality of candidate summaries, measuring a relative mass that the candidate summary devotes to the received query statement, measuring to what extent the candidate summary generally covers the one or more documents, measuring a sentence diversity of each candidate summary by calculating a bigram LM entropy for each candidate summary, biasing the sentence selection towards one or more sentences that appear earlier in a containing document, and biasing the sentence selection towards one or more longer summaries that still satisfy a length constraint that contain few long sentences rather than a plurality of candidate summaries that contain many short sentences. | 0.548585 |
7,945,929 | 12 | 16 | 12. The system of claim 11 , wherein the processor is configured to combine at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category by: combining the identified simple categories into groups of two or more of the identified simple categories; and determining, for each of the groups of simple categories, whether the respective group is contained within a list of supported categories; wherein the at least one combination category comprises one of the groups of simple categories contained within the list of supported categories. | 12. The system of claim 11 , wherein the processor is configured to combine at least a subset of the identified simple categories associated with the at least one program listing into the at least one combination category by: combining the identified simple categories into groups of two or more of the identified simple categories; and determining, for each of the groups of simple categories, whether the respective group is contained within a list of supported categories; wherein the at least one combination category comprises one of the groups of simple categories contained within the list of supported categories. 16. The system of claim 12 , wherein each of the plurality of program listings has associated metadata, and wherein the processor is further configured to automatically assign each of the plurality of program listings at least one of a plurality of simple categories based on the associated metadata. | 0.786325 |
7,725,322 | 4 | 6 | 4. The spoken dialogue interface apparatus as set forth in claim 1 , further comprising a system intention selection module for performing a service based on the user intention selected by the user intention selection module and transferring performance result; wherein the system response generation module generates a system response sentence corresponding to the transferred results. | 4. The spoken dialogue interface apparatus as set forth in claim 1 , further comprising a system intention selection module for performing a service based on the user intention selected by the user intention selection module and transferring performance result; wherein the system response generation module generates a system response sentence corresponding to the transferred results. 6. The spoken dialogue interface apparatus as set forth in claim 4 , further comprising a speech synthesis module for transforming the system response sentence generated by the system response generation module into speech and outputting it to the user. | 0.927257 |
8,799,773 | 1 | 10 | 1. A method of summarizing sentiment expressed by reviews of an entity, comprising: identifying sentiment phrases in the reviews expressing sentiment about the entity; identifying reviewable aspects of the entity, wherein identifying reviewable aspects of the entity includes identifying one or more static aspects of the entity based on a type of the entity and identifying one or more dynamic aspects of the entity based on text of one or more of the reviews; associating the sentiment phrases with the reviewable aspects of the entity to which the sentiment phrases pertain; summarizing the sentiment expressed by the sentiment phrases associated with the reviewable aspects of the entity; receiving a request for the summarized sentiment for the entity; selecting one or more reviewable aspects of the entity, the selected reviewable aspects a subset of the identified reviewable aspects and being selected to identify the more relevant of the identified reviewable aspects; wherein the selecting the one or more reviewable aspects of the entity includes selecting from the static aspects based on first criteria and selecting from the dynamic aspects based on second criteria, the second criteria unique from the first criteria; wherein a given reviewable aspect of the selected reviewable aspects is selected based at least in part on how many unique user opinion sources provided the sentiment phrases associated with the given reviewable aspect; and storing the selected reviewable aspects in response to the received request. | 1. A method of summarizing sentiment expressed by reviews of an entity, comprising: identifying sentiment phrases in the reviews expressing sentiment about the entity; identifying reviewable aspects of the entity, wherein identifying reviewable aspects of the entity includes identifying one or more static aspects of the entity based on a type of the entity and identifying one or more dynamic aspects of the entity based on text of one or more of the reviews; associating the sentiment phrases with the reviewable aspects of the entity to which the sentiment phrases pertain; summarizing the sentiment expressed by the sentiment phrases associated with the reviewable aspects of the entity; receiving a request for the summarized sentiment for the entity; selecting one or more reviewable aspects of the entity, the selected reviewable aspects a subset of the identified reviewable aspects and being selected to identify the more relevant of the identified reviewable aspects; wherein the selecting the one or more reviewable aspects of the entity includes selecting from the static aspects based on first criteria and selecting from the dynamic aspects based on second criteria, the second criteria unique from the first criteria; wherein a given reviewable aspect of the selected reviewable aspects is selected based at least in part on how many unique user opinion sources provided the sentiment phrases associated with the given reviewable aspect; and storing the selected reviewable aspects in response to the received request. 10. The method of claim 1 , further comprising: selecting one or more of the sentiment phrases for display in association with the selected reviewable aspects; and generating a display of the selected reviewable aspects and the selected sentiment phrases in response to the received request. | 0.845377 |
9,116,921 | 16 | 18 | 16. The computer readable medium of claim 15 , wherein the instructions cause the data processing apparatus to perform operations further comprising: determining that user interaction with one of the identified canonical images; and in response to the determination, increasing a presentation size of images that are included in a same hierarchical grouping as the one of the canonical images. | 16. The computer readable medium of claim 15 , wherein the instructions cause the data processing apparatus to perform operations further comprising: determining that user interaction with one of the identified canonical images; and in response to the determination, increasing a presentation size of images that are included in a same hierarchical grouping as the one of the canonical images. 18. The computer readable medium of claim 16 , wherein increasing in presentation size of images that are included in a same hierarchical grouping as the one of the canonical images comprises increasing a presentation size of child or grandchild images of the one of the canonical images more than an amount by which a presentation size of the one of the canonical images is increased. | 0.792565 |
9,760,559 | 1 | 9 | 1. A method for text prediction comprising: at an electronic device: receiving a text input, the text input associated with an input context; determining, using a first language model, a first frequency of occurrence of an m-gram with respect to a first subset of a corpus, wherein the first subset is associated with a first context, and wherein the m-gram includes at least one word in the text input; determining, based on a degree of similarity between the input context and the first context, a first weighting factor, wherein a weighted first frequency of occurrence of the m-gram is obtained by applying the first weighting factor to the first frequency of occurrence of the m-gram; determining, using the first language model, a second frequency of occurrence of the m-gram with respect to a second subset of the corpus, wherein the second subset is associated with a second context; determining, based on a degree of similarity between the input context and the second context, a second weighting factor, wherein a weighted second frequency of occurrence of the m-gram is obtained by applying the second weighting factor to the second frequency of occurrence of the m-gram; and determining, based on the weighted first frequency of occurrence of the m-gram and the weighted second frequency of occurrence of the m-gram, a first weighted probability of a first predicted text given the text input, wherein the m-gram includes at least one word in the first predicted text. | 1. A method for text prediction comprising: at an electronic device: receiving a text input, the text input associated with an input context; determining, using a first language model, a first frequency of occurrence of an m-gram with respect to a first subset of a corpus, wherein the first subset is associated with a first context, and wherein the m-gram includes at least one word in the text input; determining, based on a degree of similarity between the input context and the first context, a first weighting factor, wherein a weighted first frequency of occurrence of the m-gram is obtained by applying the first weighting factor to the first frequency of occurrence of the m-gram; determining, using the first language model, a second frequency of occurrence of the m-gram with respect to a second subset of the corpus, wherein the second subset is associated with a second context; determining, based on a degree of similarity between the input context and the second context, a second weighting factor, wherein a weighted second frequency of occurrence of the m-gram is obtained by applying the second weighting factor to the second frequency of occurrence of the m-gram; and determining, based on the weighted first frequency of occurrence of the m-gram and the weighted second frequency of occurrence of the m-gram, a first weighted probability of a first predicted text given the text input, wherein the m-gram includes at least one word in the first predicted text. 9. The method of claim 1 , wherein the first language model includes a plurality of sub-models arranged in a hierarchical context tree, and wherein each sub-model is associated with a specific context. | 0.850224 |
9,021,055 | 1 | 4 | 1. A method for enforcing a nonconforming web service policy document, the method comprising: receiving, by a web service computer system, from a web service client computer system, a request for a conforming web service policy document, wherein: the conforming web service policy document is required to conform to the web service description language; the conforming web service policy document specifies security requirements between the web service computer and the web service client computer system; generating, by the web service computer system, dynamically in response to the request from the web service client computer system, the conforming web service policy document using the nonconforming web service policy document, wherein: the nonconforming web service policy document expressed in the web service description language and comprising at least one element conforming to web service description language and at least one element not conforming to the web service description language including at least a generating function unsupported by the web service description language that is used to generate a conforming document based on the request and the nonconforming web service policy document, the generating function comprising at least a silent element for identifying if another element should be included in the conforming document; the nonconforming web service policy document specifies security requirements between the web service computer and the web service client computer system; the nonconforming web service policy document is stored on the web service computer system; the content of the conforming web service policy document is generated from the nonconforming web service policy document at least partially based on a context of the web service client computer system; transmitting, by the web service computer system, to the web service client computer system, the conforming web service policy document; and enforcing, by the web service computer system, with the web service client computer system, security requirements specified in the nonconforming web service policy document, wherein: the nonconforming web service policy document comprises an enforcing function unsupported by the web service description language that is used to affect how web service policies are processed by the web service, the enforcing function comprising at least one of: a sequence element for identifying an order in which assertions are to be evaluated, or a guard element for specifying which elements to enforce based on a context of the client; the enforcing function that is unsupported by the web service description language is utilized for enforcement of the conforming web service policy document by the web service computer system; and the conforming web service policy document comprises sufficient information for the web service client computer system to comply with the security requirements specified in nonconforming web service policy document. | 1. A method for enforcing a nonconforming web service policy document, the method comprising: receiving, by a web service computer system, from a web service client computer system, a request for a conforming web service policy document, wherein: the conforming web service policy document is required to conform to the web service description language; the conforming web service policy document specifies security requirements between the web service computer and the web service client computer system; generating, by the web service computer system, dynamically in response to the request from the web service client computer system, the conforming web service policy document using the nonconforming web service policy document, wherein: the nonconforming web service policy document expressed in the web service description language and comprising at least one element conforming to web service description language and at least one element not conforming to the web service description language including at least a generating function unsupported by the web service description language that is used to generate a conforming document based on the request and the nonconforming web service policy document, the generating function comprising at least a silent element for identifying if another element should be included in the conforming document; the nonconforming web service policy document specifies security requirements between the web service computer and the web service client computer system; the nonconforming web service policy document is stored on the web service computer system; the content of the conforming web service policy document is generated from the nonconforming web service policy document at least partially based on a context of the web service client computer system; transmitting, by the web service computer system, to the web service client computer system, the conforming web service policy document; and enforcing, by the web service computer system, with the web service client computer system, security requirements specified in the nonconforming web service policy document, wherein: the nonconforming web service policy document comprises an enforcing function unsupported by the web service description language that is used to affect how web service policies are processed by the web service, the enforcing function comprising at least one of: a sequence element for identifying an order in which assertions are to be evaluated, or a guard element for specifying which elements to enforce based on a context of the client; the enforcing function that is unsupported by the web service description language is utilized for enforcement of the conforming web service policy document by the web service computer system; and the conforming web service policy document comprises sufficient information for the web service client computer system to comply with the security requirements specified in nonconforming web service policy document. 4. The method for enforcing the nonconforming web service policy document of claim 1 , wherein content of the conforming web service policy document is at least partially determined based on the generating function unsupported by the web service description language. | 0.683649 |
8,706,750 | 2 | 3 | 2. The system of claim 1 , wherein: the query suggestions are ranked according to an order from a highest rank to a lowest rank, and wherein the highest ranked query suggestion is the one of the subsequent query suggestions for which search results are provided in response to determining that the prediction criterion is met; and the interface instructions cause the client device to: render the subsequent query suggestions according to the order; and in response to the client device receiving the search results, generate an indication in the interface that indicates the one of the subsequent query suggestion for which the search results are responsive. | 2. The system of claim 1 , wherein: the query suggestions are ranked according to an order from a highest rank to a lowest rank, and wherein the highest ranked query suggestion is the one of the subsequent query suggestions for which search results are provided in response to determining that the prediction criterion is met; and the interface instructions cause the client device to: render the subsequent query suggestions according to the order; and in response to the client device receiving the search results, generate an indication in the interface that indicates the one of the subsequent query suggestion for which the search results are responsive. 3. The system of claim 2 , wherein the indication is a highlight of the one of the subsequent query suggestions that visually distinguishes the one of the subsequent query suggestions from the other query suggestions. | 0.952224 |
8,200,495 | 15 | 17 | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. | 15. An apparatus for recognizing speech and implementing a speech recognition function, the apparatus comprising: circuitry for initiating a speech dialog with at least one point in the dialog where there is a grammar of possible responses and a set of at least one expected response and wherein the set is a subset of the grammar and the set includes the most likely response or responses expected to be uttered by a user at the at least one point in the speech dialog, the set of at least one expected response for the at least one point being known in the speech recognition system before receiving input speech from the user; circuitry operable for receiving input speech from the user for progressing through the speech dialog; circuitry configured for generating acoustic features of the input speech received from a user; processing circuitry including a match/search algorithm having acoustic models, the acoustic models including acoustic models that are associated with the set of at least one expected response; the processing circuitry operable for comparing the generated input speech acoustic features to acoustic models associated with words in the grammar to generate a hypothesis and further operable for comparing the hypothesis with at least one expected response in the set to determine if the hypothesis matches the at least one expected response in the set; the processing circuitry further operable, if the hypothesis matches the at least one expected response in the set to adapt at least one acoustic model corresponding to the matched expected response using the acoustic features of the input speech to use the at least one adapted model with future input speech in the speech recognition system, otherwise, not adapting the at least one acoustic model corresponding to the expected response. 17. The apparatus of claim 15 wherein the match/search algorithm processes the input speech through a plurality of models with states, and the acoustic models are adapted by modifying statistics associated with the model states. | 0.502183 |
8,627,463 | 1 | 8 | 1. A computer-implemented method for using reputation information to evaluate the trustworthiness of files obtained via torrent transactions, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, by the computing device, a torrent file that comprises metadata for facilitating a torrent transaction for obtaining a target file via a peer-to-peer file-sharing protocol; identifying, by the computing device, a plurality of computing systems involved in the torrent transaction, the plurality of computing systems comprising at least one of: an original seeder that uploaded the torrent file to a torrent hosting site; a peer capable of providing at least a portion of the target file; a peer attempting to download at least a portion of the target file; obtaining, by the computing device, reputation information for the plurality of computing systems involved in the torrent transaction, wherein the reputation information identifies a community's opinion on the trustworthiness of the plurality of computing systems involved in the torrent transaction based at least in part on results of at least one previous torrent transaction in which the plurality of computing systems were involved; calculating an average peer reputation based at least in part on the reputation information for the plurality of computing systems; determining, by the computing device, that the target file represents a potential security risk based at least in part on the calculated average peer reputation; performing, by the computing device, a security action on the target file. | 1. A computer-implemented method for using reputation information to evaluate the trustworthiness of files obtained via torrent transactions, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying, by the computing device, a torrent file that comprises metadata for facilitating a torrent transaction for obtaining a target file via a peer-to-peer file-sharing protocol; identifying, by the computing device, a plurality of computing systems involved in the torrent transaction, the plurality of computing systems comprising at least one of: an original seeder that uploaded the torrent file to a torrent hosting site; a peer capable of providing at least a portion of the target file; a peer attempting to download at least a portion of the target file; obtaining, by the computing device, reputation information for the plurality of computing systems involved in the torrent transaction, wherein the reputation information identifies a community's opinion on the trustworthiness of the plurality of computing systems involved in the torrent transaction based at least in part on results of at least one previous torrent transaction in which the plurality of computing systems were involved; calculating an average peer reputation based at least in part on the reputation information for the plurality of computing systems; determining, by the computing device, that the target file represents a potential security risk based at least in part on the calculated average peer reputation; performing, by the computing device, a security action on the target file. 8. The method of claim 1 , wherein determining that the target file represents the potential security risk further comprises: obtaining at least a portion of the target file; determining that the target file negatively impacts the health of the computing device. | 0.807353 |
9,177,262 | 1 | 6 | 1. A method comprising: automatically extracting, by a database source computer, from a document corpus, data associated with a plurality of co-occurring topics; in response to automatically extracting the plurality of co-occurring topics, extracting, by a synchronizing framework computer, a plurality of topic identifiers from the plurality of co-occurring topics; creating, by the synchronizing framework computer, a master topic computer model for the document corpus from a first plurality of term vectors; creating, by the synchronizing framework computer, a periodic new topic computer model by comparing topic significance among the plurality of topic identifiers, the periodic new topic computer model including a second plurality of term vectors; and selecting, by the synchronizing framework computer, one or more new topics by identifying one or more term vectors from the second plurality of term vectors in the periodic new topic computer model that have no correlation with the first plurality of term vectors in the master topic computer model. | 1. A method comprising: automatically extracting, by a database source computer, from a document corpus, data associated with a plurality of co-occurring topics; in response to automatically extracting the plurality of co-occurring topics, extracting, by a synchronizing framework computer, a plurality of topic identifiers from the plurality of co-occurring topics; creating, by the synchronizing framework computer, a master topic computer model for the document corpus from a first plurality of term vectors; creating, by the synchronizing framework computer, a periodic new topic computer model by comparing topic significance among the plurality of topic identifiers, the periodic new topic computer model including a second plurality of term vectors; and selecting, by the synchronizing framework computer, one or more new topics by identifying one or more term vectors from the second plurality of term vectors in the periodic new topic computer model that have no correlation with the first plurality of term vectors in the master topic computer model. 6. The method of claim 1 wherein comparing topic significance among the plurality of topic identifiers is based on a predetermined significance threshold. | 0.866319 |
8,122,440 | 11 | 20 | 11. A computer-readable storage medium comprising instructions for performing a method for identifying an external program code dependency, the method comprising: executing compiler functionality upon a code base to generate compilation parameters indicative of external programming code dependencies between one or more entities within the code base and one or more external program code modules, the compilation parameters not predefined before execution of the compiler functionality; determining an external program code dependency indicative of a dependency between an entity within the code base and an external program code module based upon the compilation parameters, the external program code dependency comprising an indication of a source associated with the external program code module; and utilizing the external program code dependency to automatically port a computer application associated with the code base from a first computing system to a second computing system, at least one of the execution of the compiler functionality and the determination of the external program code dependency being automated. | 11. A computer-readable storage medium comprising instructions for performing a method for identifying an external program code dependency, the method comprising: executing compiler functionality upon a code base to generate compilation parameters indicative of external programming code dependencies between one or more entities within the code base and one or more external program code modules, the compilation parameters not predefined before execution of the compiler functionality; determining an external program code dependency indicative of a dependency between an entity within the code base and an external program code module based upon the compilation parameters, the external program code dependency comprising an indication of a source associated with the external program code module; and utilizing the external program code dependency to automatically port a computer application associated with the code base from a first computing system to a second computing system, at least one of the execution of the compiler functionality and the determination of the external program code dependency being automated. 20. The computer-readable storage medium of claim 11 , comprising: performing semantic analysis upon the code base to generate a symbol table listing one or more identifiers utilized in the code base and one or more external program code modules; and determining the external program code dependency based upon the symbol table. | 0.50152 |
10,018,993 | 10 | 16 | 10. A method for transforming industrial data, comprising: executing, by an industrial device comprising at least one processor, an industrial control program, wherein the executing causes the industrial device to process input signals from input devices and to control output signals directed to output devices; generating and collecting, by the industrial device, industrial data generated via control of an industrial process via the input devices and the output devices; determining, by the industrial device, a plant site identifier and a production area identifier associated with the industrial data based on a referencing of a hierarchical organizational model of an industrial enterprise that defines at least an enterprise level, a site level, and a production area level; transforming, by the industrial device, the industrial data into refined data in accordance with a requirement of a cloud-based application, wherein the transforming comprises at least adding contextual information to the industrial data, the contextual information comprising at least an actionable tag, the plant site identifier, the production area identifier, an identity of a product being produced at a time that the industrial data was generated, and a quality indicator for the product; and transferring, by the industrial device, the refined data to the cloud-based application to facilitate notifying a user in accordance with the actionable tag. | 10. A method for transforming industrial data, comprising: executing, by an industrial device comprising at least one processor, an industrial control program, wherein the executing causes the industrial device to process input signals from input devices and to control output signals directed to output devices; generating and collecting, by the industrial device, industrial data generated via control of an industrial process via the input devices and the output devices; determining, by the industrial device, a plant site identifier and a production area identifier associated with the industrial data based on a referencing of a hierarchical organizational model of an industrial enterprise that defines at least an enterprise level, a site level, and a production area level; transforming, by the industrial device, the industrial data into refined data in accordance with a requirement of a cloud-based application, wherein the transforming comprises at least adding contextual information to the industrial data, the contextual information comprising at least an actionable tag, the plant site identifier, the production area identifier, an identity of a product being produced at a time that the industrial data was generated, and a quality indicator for the product; and transferring, by the industrial device, the refined data to the cloud-based application to facilitate notifying a user in accordance with the actionable tag. 16. The method of claim 10 , wherein the transforming comprising adding the actionable tag to the industrial data in response to determining that a value contained in the industrial data is indicative of at least one of an alarm condition or an achieved production goal. | 0.85342 |
10,031,970 | 5 | 7 | 5. The method of claim 1 , wherein applying the predictive model involves obtaining model attributes from one or more of: content of the received input; data associated with the user; and data associated with a product. | 5. The method of claim 1 , wherein applying the predictive model involves obtaining model attributes from one or more of: content of the received input; data associated with the user; and data associated with a product. 7. The method of claim 5 , wherein values for the model attributes from the data associated with the user are based on one or more of: a type of the user; a type of web browser; a type of operating system; and a location of the user. | 0.946658 |
10,089,299 | 11 | 12 | 11. A system for applying a translation model, the system comprising: one or more processors; an interface configured to obtain one or more input n-grams, wherein an n-gram is a digital representation of one or more words or groups of characters; and wherein each of the one or more input n-grams is associated with one or more multi-media labels for one or more multi-media items associated with the one or more input n-grams; and a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising applying, to each particular n-gram of the one or more input n-grams, the translation model, wherein the translation model comprises a probability distribution indicating, for selected n-grams, a probability that an output n-gram is a translation of the selected n-gram, given one or more multi-media labels; and wherein the applying the translation model includes selecting one or more output n-grams that, based at least in part on the probability distribution, have a highest probability of being the translation of the particular n-gram, given the one or more multi-media labels associated with the particular n-gram. | 11. A system for applying a translation model, the system comprising: one or more processors; an interface configured to obtain one or more input n-grams, wherein an n-gram is a digital representation of one or more words or groups of characters; and wherein each of the one or more input n-grams is associated with one or more multi-media labels for one or more multi-media items associated with the one or more input n-grams; and a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations comprising applying, to each particular n-gram of the one or more input n-grams, the translation model, wherein the translation model comprises a probability distribution indicating, for selected n-grams, a probability that an output n-gram is a translation of the selected n-gram, given one or more multi-media labels; and wherein the applying the translation model includes selecting one or more output n-grams that, based at least in part on the probability distribution, have a highest probability of being the translation of the particular n-gram, given the one or more multi-media labels associated with the particular n-gram. 12. The system of claim 11 , wherein at least one multi-media label, of the one or more multi-media labels, identifies at least one of: an object, a place, a person, or any combination thereof, depicted in the one or more multi-media items that the at least one multi-media label is for. | 0.813151 |
9,875,018 | 4 | 5 | 4. The electronic device as claimed in claim 3 , wherein, in a second mode, the input rule table comprises a Chinese input rule table, and the text input interface has a Chinese default interface when the text input interface operates as a Chinese interface, wherein in the Chinese default interface a first set of Chinese characters comprising a first set of Chinese Zhuyin characters is displayed in the first display region, and a second set of Chinese characters comprising five tones of Chinese displayed in the second display region. | 4. The electronic device as claimed in claim 3 , wherein, in a second mode, the input rule table comprises a Chinese input rule table, and the text input interface has a Chinese default interface when the text input interface operates as a Chinese interface, wherein in the Chinese default interface a first set of Chinese characters comprising a first set of Chinese Zhuyin characters is displayed in the first display region, and a second set of Chinese characters comprising five tones of Chinese displayed in the second display region. 5. The electronic device as claimed in claim 4 , wherein at least five of the display blocks of the second display region are in use in the Chinese default interface, and the processor further enables the display blocks of the second display region to be transparent except for the display blocks arranged to display the five tones of Chinese, thereby changing the ratio of the interface area and the predetermined display area of the display region. | 0.886878 |
9,959,657 | 2 | 4 | 2. The method according to claim 1 , wherein each cluster includes at least one sub-cluster, and wherein the identified expression dependent weightings are retrieved for said each cluster such that there is one weight per sub-cluster. | 2. The method according to claim 1 , wherein each cluster includes at least one sub-cluster, and wherein the identified expression dependent weightings are retrieved for said each cluster such that there is one weight per sub-cluster. 4. The method according to claim 2 , further comprising selecting the speech expression from at least one of different emotions, different accents, or different speaking styles, wherein the selecting includes randomly selecting a set of the identified expression dependent weightings from a plurality of pre-stored sets of the identified expression dependent weightings, and wherein each selected set of the identified expression dependent weightings includes weightings for the at least one sub-cluster. | 0.888938 |
9,870,423 | 10 | 16 | 10. A system, comprising: one or more non-transitory computer readable media storing instructions; one or more processors operable to execute the instructions, wherein the instructions include instructions to: identify a particular entity, the particular entity being a particular person, place, or thing; identify a plurality of search queries that are each associated with the particular entity; determine a query score for each of the search queries, wherein the query score for a search query of the search queries is based on search result document quality for search result documents, for the search query, that are associated with the particular entity, wherein the search result document quality is based on a document centric signal of the search result documents that are associated with the particular entity; assign a particular search query of the search queries to the particular entity based on the determined query scores; receive input, the input being provided via a user interface input device of a client computing device; determine that the particular entity is associated with the input; provide, for presentation via a user interface output device of the client computing device, content that includes a name of the particular entity and one or more additional properties of the particular entity, wherein providing the content is in response to the input and is in response to determining that the particular entity is associated with the input; and submit, in response to selection of the content at the client computing device, the particular search query to a search engine based on the particular search query being assigned to the particular entity. | 10. A system, comprising: one or more non-transitory computer readable media storing instructions; one or more processors operable to execute the instructions, wherein the instructions include instructions to: identify a particular entity, the particular entity being a particular person, place, or thing; identify a plurality of search queries that are each associated with the particular entity; determine a query score for each of the search queries, wherein the query score for a search query of the search queries is based on search result document quality for search result documents, for the search query, that are associated with the particular entity, wherein the search result document quality is based on a document centric signal of the search result documents that are associated with the particular entity; assign a particular search query of the search queries to the particular entity based on the determined query scores; receive input, the input being provided via a user interface input device of a client computing device; determine that the particular entity is associated with the input; provide, for presentation via a user interface output device of the client computing device, content that includes a name of the particular entity and one or more additional properties of the particular entity, wherein providing the content is in response to the input and is in response to determining that the particular entity is associated with the input; and submit, in response to selection of the content at the client computing device, the particular search query to a search engine based on the particular search query being assigned to the particular entity. 16. The system of claim 10 , wherein the query score for the search query is further based on entity ambiguity of the search query and wherein the entity ambiguity is based on a comparison of a quantity of the search result documents, for the search query, that describe the particular entity to a quantity of the search result documents, for the search query, that do not describe the particular entity. | 0.501235 |
9,308,446 | 9 | 13 | 9. A training program comprising a combination of games configured to systematically drive neurological changes to overcome social cognitive deficits, the training program comprising: one or more computerized social cue perception games; one or more computerized emotion perception games, wherein one of the emotion perception games challenges the participant to match pairs of sentences with tags that identify emotional prosodies with which the sentences are aurally expressed; and one or more computerized theory of mind games; wherein each computerized game is configured to: present a plurality of target and/or distractor stimuli; prompt a game participant to respond to the target and/or distractor stimuli; receive the game participant's input through a game piece; provide an indication to the game participant of whether the game participant's input was accurate or apt; provide a signal indicative of the game participant's performance or game difficulty; and repeat the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range. | 9. A training program comprising a combination of games configured to systematically drive neurological changes to overcome social cognitive deficits, the training program comprising: one or more computerized social cue perception games; one or more computerized emotion perception games, wherein one of the emotion perception games challenges the participant to match pairs of sentences with tags that identify emotional prosodies with which the sentences are aurally expressed; and one or more computerized theory of mind games; wherein each computerized game is configured to: present a plurality of target and/or distractor stimuli; prompt a game participant to respond to the target and/or distractor stimuli; receive the game participant's input through a game piece; provide an indication to the game participant of whether the game participant's input was accurate or apt; provide a signal indicative of the game participant's performance or game difficulty; and repeat the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range. 13. The training program of claim 9 , wherein another one of the emotion perception games challenges the participant to match pairs of emotion clips and emotion labels. | 0.508772 |
9,530,409 | 1 | 6 | 1. A method operable on an electronic device, comprising: during media playback, detecting an event; initiating output of a first indication of the event, wherein the first indication is a first audio overlay on top of the media playback and indicates that speech recognition is available for a predefined period of time; determining an event type from a plurality of event types, wherein each of the plurality of event types is associated with a set of speech commands; determining a set of speech commands associated with the event type; executing a speech recognition application to process speech commands associated with the event and to provide options to the user for controlling the electronic device, wherein executing the speech recognition application includes initiating a speech recognition engine using the set of speech commands associated with the event type; initiating output of a second indication of a state of readiness to process speech commands in association with the event, wherein the second indication is an audio overlay on top of the media playback; identifying a recognized speech command from a set of expected speech commands using custom speech recognition grammar based on the event; and in response to identifying the recognized speech command: pausing the media playback; and executing the recognized speech command. | 1. A method operable on an electronic device, comprising: during media playback, detecting an event; initiating output of a first indication of the event, wherein the first indication is a first audio overlay on top of the media playback and indicates that speech recognition is available for a predefined period of time; determining an event type from a plurality of event types, wherein each of the plurality of event types is associated with a set of speech commands; determining a set of speech commands associated with the event type; executing a speech recognition application to process speech commands associated with the event and to provide options to the user for controlling the electronic device, wherein executing the speech recognition application includes initiating a speech recognition engine using the set of speech commands associated with the event type; initiating output of a second indication of a state of readiness to process speech commands in association with the event, wherein the second indication is an audio overlay on top of the media playback; identifying a recognized speech command from a set of expected speech commands using custom speech recognition grammar based on the event; and in response to identifying the recognized speech command: pausing the media playback; and executing the recognized speech command. 6. The method of claim 1 , wherein the speech commands are based on the event and a user activity when the event occurred. | 0.88403 |
7,693,823 | 18 | 19 | 18. The computing device of claim 16 wherein the model parameters are represented by the following: ω j = λ j * , T j = 2 π / ω j = 2 π / λ j * , α j = ∑ t = 1 N q t ⅇ - ⅈ λ j * t , A j = 2 α j and φ j = arg ( α j ) . | 18. The computing device of claim 16 wherein the model parameters are represented by the following: ω j = λ j * , T j = 2 π / ω j = 2 π / λ j * , α j = ∑ t = 1 N q t ⅇ - ⅈ λ j * t , A j = 2 α j and φ j = arg ( α j ) . 19. The computing device of claim 18 wherein the frequency spectral is represented by the following: S N ( λ ) = ∑ t = 1 N q t ⅇ - ⅈ λ t λ ∈ [ - π , π ] . | 0.936138 |
8,063,800 | 1 | 8 | 1. A method for encoding alphanumeric data onto a tangible computer readable medium comprising: (a) receiving an alphanumeric character string having a plurality of characters; (b) generating a character map having a string of character type symbols, wherein generating the character map includes: for each of the plurality of characters in the alphanumeric character string, assigning a character type value to a symbol in the string of character type symbols; (c) generating a character map remainder, wherein the character map remainder is a variable-length bit pattern and generating the character map remainder includes: (i) identifying one or more runs of character type symbols in sequential positions in the character map having the same character type value, and (ii) removing the one or more identified runs of character type symbols from the character map; (d) for each identified run, generating a run field, wherein generating the run field includes encoding base data and run length data; (e) encoding the characters of each character type into binary encoded substrings, wherein encoding includes: (i) assembling characters into separate substrings by character type, and (ii) encoding each character type substring into binary; (f) generating an encoded data string including one or more run fields, the character map remainder, and the binary encoded substrings; and (g) writing the encoded data string to the tangible computer readable medium. | 1. A method for encoding alphanumeric data onto a tangible computer readable medium comprising: (a) receiving an alphanumeric character string having a plurality of characters; (b) generating a character map having a string of character type symbols, wherein generating the character map includes: for each of the plurality of characters in the alphanumeric character string, assigning a character type value to a symbol in the string of character type symbols; (c) generating a character map remainder, wherein the character map remainder is a variable-length bit pattern and generating the character map remainder includes: (i) identifying one or more runs of character type symbols in sequential positions in the character map having the same character type value, and (ii) removing the one or more identified runs of character type symbols from the character map; (d) for each identified run, generating a run field, wherein generating the run field includes encoding base data and run length data; (e) encoding the characters of each character type into binary encoded substrings, wherein encoding includes: (i) assembling characters into separate substrings by character type, and (ii) encoding each character type substring into binary; (f) generating an encoded data string including one or more run fields, the character map remainder, and the binary encoded substrings; and (g) writing the encoded data string to the tangible computer readable medium. 8. The method of claim 1 , wherein step (c) further comprises, wherein if the run is an infix run, determining the center for a center infix run, comprising: removing any identified prefix and suffix runs from the character map to generate a reduced character map, determining the center of the reduced character map, and centering the center infix run about the center of the reduced character map. | 0.618547 |
8,438,007 | 9 | 10 | 9. A computer implemented method for generating a second human language user interface for a software product having a first human language user interface, the method comprising: opening a glossary database that includes a plurality of string sets at least some of which include a user interface string in a first human language and a corresponding user interface string in a second human language, wherein a string set comprises user interface strings having the same set identifier, a set identifier comprising context information about a previous use of a user interface string in a user interface of a software product including a name of the software product and an identifier specifying a type of user interface string and each user interface string comprises a string displayed in a user interface of a software product; selecting a user interface string in the first human language user interface; finding, using a processor, a string set in the glossary database having the selected user interface string and a user interface string in the second human language, wherein the user interface strings in the string set were previously used in a software product different from the software product for which the second human language user interface is being generated; and using the user interface string in the second human language in the second human language user interface, wherein finding a string set in the glossary database having the selected user interface string comprises: searching for one or more literal user interface strings in the glossary database that matches the selected user interface string, and generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string, and deciding, based on the score, whether or not to select a string set including a matching interface string. | 9. A computer implemented method for generating a second human language user interface for a software product having a first human language user interface, the method comprising: opening a glossary database that includes a plurality of string sets at least some of which include a user interface string in a first human language and a corresponding user interface string in a second human language, wherein a string set comprises user interface strings having the same set identifier, a set identifier comprising context information about a previous use of a user interface string in a user interface of a software product including a name of the software product and an identifier specifying a type of user interface string and each user interface string comprises a string displayed in a user interface of a software product; selecting a user interface string in the first human language user interface; finding, using a processor, a string set in the glossary database having the selected user interface string and a user interface string in the second human language, wherein the user interface strings in the string set were previously used in a software product different from the software product for which the second human language user interface is being generated; and using the user interface string in the second human language in the second human language user interface, wherein finding a string set in the glossary database having the selected user interface string comprises: searching for one or more literal user interface strings in the glossary database that matches the selected user interface string, and generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string, and deciding, based on the score, whether or not to select a string set including a matching interface string. 10. The method of claim 9 , wherein if multiple matches are found, selecting a string set that includes the matching user interface string having the highest score and having a score that equals or exceeds a specified minimum score value and if no string set includes such a user interface string, then not selecting a string set and delegating to a human translator the translation of the user interface string in the first human language into the second human language. | 0.715236 |
9,842,590 | 1 | 4 | 1. A system for analyzing a face-to-face customer-agent communication, comprising: a node comprising a processor and a non-transitory computer readable medium operably coupled thereto, the non-transitory computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, wherein the plurality of instructions when executed: record a mono recording of a communication between an agent and a customer using a microphone, wherein the mono recording is unseparated and includes agent voice data and customer voice data; separately record the agent voice data in an agent recording using a second microphone; align the unseparated mono recording and the agent recording so they are time-synched; subtract agent voice data from the unseparated mono recording using the agent recording to provide a separated recording including only customer voice data, wherein the agent voice data is subtracted from the unseparated mono recording based on the alignment, sound frequency analysis, or both; convert at least the customer voice data to text; and determine a personality type of the customer by applying one or more computer-implemented linguistic algorithms to the text of the customer voice data. | 1. A system for analyzing a face-to-face customer-agent communication, comprising: a node comprising a processor and a non-transitory computer readable medium operably coupled thereto, the non-transitory computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, wherein the plurality of instructions when executed: record a mono recording of a communication between an agent and a customer using a microphone, wherein the mono recording is unseparated and includes agent voice data and customer voice data; separately record the agent voice data in an agent recording using a second microphone; align the unseparated mono recording and the agent recording so they are time-synched; subtract agent voice data from the unseparated mono recording using the agent recording to provide a separated recording including only customer voice data, wherein the agent voice data is subtracted from the unseparated mono recording based on the alignment, sound frequency analysis, or both; convert at least the customer voice data to text; and determine a personality type of the customer by applying one or more computer-implemented linguistic algorithms to the text of the customer voice data. 4. The system of claim 1 , wherein the agent is associated with one or more commercial organizations, financial institutions, government agencies or public safety organizations. | 0.588372 |
7,610,281 | 1 | 2 | 1. A system, comprising: a processor; a gram logic configured to cause the processor to produce a gram from a string; a candidate logic configured to cause the processor to identify one or more candidate documents based on identifying at least one match between a query gram produced by the gram logic from a query string and a document gram associated with a document, where document grams are stored in an inverted index that relates grams to documents, where an entry in the inverted index includes a document identifier and one or more of, a gram offset, a term offset, and a gram type; a reconstruction logic configured to cause the processor to produce a partially reconstructed candidate document from one or more entries in the inverted index, the entries being associated with the candidate document, the entries corresponding to one or more query grams that match one or more document grams; an edit distance logic configured to cause the processor to compute an edit distance between a first string associated with the query string and a second string associated with the partially reconstructed candidate document, where the edit distance logic is embodied as executable instructions stored on a computer-readable medium; a signal logic configured to cause the processor to provide data corresponding to the edit distance; and where the reconstruction logic causes the processor to produce the second string, the second string having one or more of, a known substring, and an unknown substring, the location and content of the known substring being determined by information stored in one or more entries in the inverted index, the information comprising offset information, the one or more entries corresponding to matches between document grams associated with the candidate document and query grams associated with the query string. | 1. A system, comprising: a processor; a gram logic configured to cause the processor to produce a gram from a string; a candidate logic configured to cause the processor to identify one or more candidate documents based on identifying at least one match between a query gram produced by the gram logic from a query string and a document gram associated with a document, where document grams are stored in an inverted index that relates grams to documents, where an entry in the inverted index includes a document identifier and one or more of, a gram offset, a term offset, and a gram type; a reconstruction logic configured to cause the processor to produce a partially reconstructed candidate document from one or more entries in the inverted index, the entries being associated with the candidate document, the entries corresponding to one or more query grams that match one or more document grams; an edit distance logic configured to cause the processor to compute an edit distance between a first string associated with the query string and a second string associated with the partially reconstructed candidate document, where the edit distance logic is embodied as executable instructions stored on a computer-readable medium; a signal logic configured to cause the processor to provide data corresponding to the edit distance; and where the reconstruction logic causes the processor to produce the second string, the second string having one or more of, a known substring, and an unknown substring, the location and content of the known substring being determined by information stored in one or more entries in the inverted index, the information comprising offset information, the one or more entries corresponding to matches between document grams associated with the candidate document and query grams associated with the query string. 2. The system of claim 1 , comprising a query logic to receive and store the query string. | 0.932432 |
9,116,980 | 7 | 8 | 7. A system, comprising: a processor coupled to a memory, the memory storing program instructions that when executed by the processor perform the following: identifying textual input, including notes taken by a user during a conversation; determining a first plurality of categories describing a plurality of types of information found within the textual input by applying a plurality of linguistic rules to a plurality of portions of the textual input; identifying a second plurality of categories determined by the user in response to the conversation; determining whether a number of differences between the first set of categories and the second set of categories exceeds a predetermined threshold; and generating a report, when it is determined that the number of differences between the first set of categories and the second set of categories exceeds the predetermined threshold. | 7. A system, comprising: a processor coupled to a memory, the memory storing program instructions that when executed by the processor perform the following: identifying textual input, including notes taken by a user during a conversation; determining a first plurality of categories describing a plurality of types of information found within the textual input by applying a plurality of linguistic rules to a plurality of portions of the textual input; identifying a second plurality of categories determined by the user in response to the conversation; determining whether a number of differences between the first set of categories and the second set of categories exceeds a predetermined threshold; and generating a report, when it is determined that the number of differences between the first set of categories and the second set of categories exceeds the predetermined threshold. 8. The system of claim 7 , wherein the processor is coupled to the memory via a bus. | 0.761364 |
7,624,118 | 1 | 6 | 1. A system that facilitates data processing, comprising: a processor that executes the following computer executable components stored on a computer readable storage medium: a receiver component that receives a structured query language (SQL) query; a partitioning component that partitions the SQL query into multiple tasks and provides the tasks to multiple cluster nodes for processing, wherein the multiple cluster nodes include a hierarchical arrangement of sub-clusters of nodes, at least one of the cluster nodes includes a second partitioning component that partitions the received tasks into multiple sub-tasks, the at least one of the cluster nodes determine for one or more sub-tasks whether to execute the sub-task at the at least one cluster node or to provide the sub-task to a first sub-cluster for execution, and further wherein the multiple tasks that are provided to the multiple cluster nodes are assigned based on the association of the data content accessible by each of the multiple cluster nodes with the data content required by the one or more tasks; and a monitoring component that monitors the progress of a first task at a first cluster of nodes of the multiple clusters of nodes, wherein the monitoring component determines the first task is not completed within a first threshold of time, and further wherein the monitoring component reassigns the first task from the first cluster of nodes of the multiple clusters of nodes to a second cluster of nodes of the multiple clusters of nodes upon determining the first task was not completed in the first threshold of time. | 1. A system that facilitates data processing, comprising: a processor that executes the following computer executable components stored on a computer readable storage medium: a receiver component that receives a structured query language (SQL) query; a partitioning component that partitions the SQL query into multiple tasks and provides the tasks to multiple cluster nodes for processing, wherein the multiple cluster nodes include a hierarchical arrangement of sub-clusters of nodes, at least one of the cluster nodes includes a second partitioning component that partitions the received tasks into multiple sub-tasks, the at least one of the cluster nodes determine for one or more sub-tasks whether to execute the sub-task at the at least one cluster node or to provide the sub-task to a first sub-cluster for execution, and further wherein the multiple tasks that are provided to the multiple cluster nodes are assigned based on the association of the data content accessible by each of the multiple cluster nodes with the data content required by the one or more tasks; and a monitoring component that monitors the progress of a first task at a first cluster of nodes of the multiple clusters of nodes, wherein the monitoring component determines the first task is not completed within a first threshold of time, and further wherein the monitoring component reassigns the first task from the first cluster of nodes of the multiple clusters of nodes to a second cluster of nodes of the multiple clusters of nodes upon determining the first task was not completed in the first threshold of time. 6. The system of claim 1 , unreliable communications are undertaken between the partitioning component and the multiple cluster nodes. | 0.759857 |
8,868,590 | 1 | 15 | 1. A method, comprising: maintaining, in an automated fashion, a user-specific profile comprising information relating to at least one user interaction with at least one electronic content through at least one computing device, receiving a search request, the search request comprising at least one search term, determining whether the at least one search term has an association with the information in the user-specific profile, and if a search term has an association with the information in the user-specific profile: determining user-specific semantic information relating to the search term based on the association of the search term with the information in the user-profile, adding the user-specific semantic information to the search term, formulating at least one computer-executable query based on the search request and based on the association of the search term with the information in the user-specific profile, the at least one computer-executable query comprising the user-specific semantic information associated with the search term, formulating a first alternative version of the search request based on a first association of the search term with first information in the user-specific profile and formulating a second alternative version of the search request, and executing a first computer-executable query based on the first alternative version of the search request to generate a first search result, executing a second computer-executable query based on the second alternative version of the search request to generate a second search result, and selecting one of the first and second search results. | 1. A method, comprising: maintaining, in an automated fashion, a user-specific profile comprising information relating to at least one user interaction with at least one electronic content through at least one computing device, receiving a search request, the search request comprising at least one search term, determining whether the at least one search term has an association with the information in the user-specific profile, and if a search term has an association with the information in the user-specific profile: determining user-specific semantic information relating to the search term based on the association of the search term with the information in the user-profile, adding the user-specific semantic information to the search term, formulating at least one computer-executable query based on the search request and based on the association of the search term with the information in the user-specific profile, the at least one computer-executable query comprising the user-specific semantic information associated with the search term, formulating a first alternative version of the search request based on a first association of the search term with first information in the user-specific profile and formulating a second alternative version of the search request, and executing a first computer-executable query based on the first alternative version of the search request to generate a first search result, executing a second computer-executable query based on the second alternative version of the search request to generate a second search result, and selecting one of the first and second search results. 15. The method of claim 1 , wherein the at least one search term comprises an unknown word, comprising accessing the user-specific profile to, in an automated fashion, resolve the unknown word prior to formulating the computer-executable query. | 0.772388 |
9,922,133 | 4 | 5 | 4. The method of claim 1 , wherein said query graph is a first query graph, the method further comprising: creating a second live topological query result in response to a second query graph, and determining whether said change is relevant to said second query graph, said determining whether said change is relevant to said second query graph is performed with an overhead below a predefined threshold without relying on any result stored in said cache memory. | 4. The method of claim 1 , wherein said query graph is a first query graph, the method further comprising: creating a second live topological query result in response to a second query graph, and determining whether said change is relevant to said second query graph, said determining whether said change is relevant to said second query graph is performed with an overhead below a predefined threshold without relying on any result stored in said cache memory. 5. The method of claim 4 , wherein said first query graph is of a structure such that said calculation to determine whether said change is relevant to said first query graph involves a processing overhead complexity above said predefined threshold, and said processing overhead complexity is reduced by caching a subset of nodes within said query result for said first query graph. | 0.884755 |
9,852,192 | 1 | 2 | 1. A system for recommending media content, the system comprising: at least one hardware processor configured to: determine that a session including presentation of at least a first media content item and a second media content item is likely to have ended, wherein the second media content item is presented within a given span of the presentation of the first media content item; in response to determining that the session is likely to have ended, determine a first plurality of topics associated with the first media content item and the second media content item; determine a second plurality of topics associated with the media content presentation session based on distance information for pairs of topics in the first plurality of topics, wherein each of the pairs of topics includes a first topic associated with the first media content item and a second topic associated with the second media content item; and transmit an indication of a plurality of media content items that correspond to at least a portion of the second plurality of topics. | 1. A system for recommending media content, the system comprising: at least one hardware processor configured to: determine that a session including presentation of at least a first media content item and a second media content item is likely to have ended, wherein the second media content item is presented within a given span of the presentation of the first media content item; in response to determining that the session is likely to have ended, determine a first plurality of topics associated with the first media content item and the second media content item; determine a second plurality of topics associated with the media content presentation session based on distance information for pairs of topics in the first plurality of topics, wherein each of the pairs of topics includes a first topic associated with the first media content item and a second topic associated with the second media content item; and transmit an indication of a plurality of media content items that correspond to at least a portion of the second plurality of topics. 2. The system of claim 1 , wherein the at least one hardware processor is further configured to select the first media content item and the second media content item from media content search results that are responsive to search terms. | 0.677596 |
8,997,069 | 16 | 20 | 16. A method implemented by one or more computing devices, the method comprising: parsing a first collection of statically-typed machine-executable code of a web browser application to locate one or more application programming interface (API) descriptions; projecting the descriptions of the one or more application programming interfaces from the first collection of statically-typed machine-executable code of the web browser into an alternate form consumable by a dynamically-typed language; and checking compatibility of the first collection of statically-typed machine-executable code of the web browser with a second collection of dynamically-typed machine-executable code by verifying that one or more call sites of the second collection of dynamically-typed machine-executable code are mapped to at least one said application programming interface (API) referenced in the projected description from the first collection of statically-typed machine-executable code of the web browser. | 16. A method implemented by one or more computing devices, the method comprising: parsing a first collection of statically-typed machine-executable code of a web browser application to locate one or more application programming interface (API) descriptions; projecting the descriptions of the one or more application programming interfaces from the first collection of statically-typed machine-executable code of the web browser into an alternate form consumable by a dynamically-typed language; and checking compatibility of the first collection of statically-typed machine-executable code of the web browser with a second collection of dynamically-typed machine-executable code by verifying that one or more call sites of the second collection of dynamically-typed machine-executable code are mapped to at least one said application programming interface (API) referenced in the projected description from the first collection of statically-typed machine-executable code of the web browser. 20. A method as described in claim 16 , wherein the descriptions of the one or more application programming interfaces are further used to construct valid executable code by exposing a user interface. | 0.872774 |
8,250,004 | 20 | 21 | 20. The method of claim 19 wherein the importance of each potential input is quantified by calculating the relative importance of the potential inputs. | 20. The method of claim 19 wherein the importance of each potential input is quantified by calculating the relative importance of the potential inputs. 21. The method of claim 20 , and further comprising calculating a normalised value of the relative importance and wherein the normalised value of the relative importance is compared with a threshold value to determine whether to discard a potential input. | 0.906456 |
8,032,820 | 15 | 16 | 15. The method of claim 10 , where the representation of the second web page also serves as a representation of a third web page, where the third web page includes a reference to the first web page. | 15. The method of claim 10 , where the representation of the second web page also serves as a representation of a third web page, where the third web page includes a reference to the first web page. 16. The method of claim 15 , where the representation of the second web page indicates how many web pages it serves as a representation for. | 0.973067 |
8,560,937 | 1 | 20 | 1. A method for segmenting a document comprising: identifying a rectangular page frame using information from multiple pages of a document; matching the page frame to a page of the document; identifying elements within the matched page frame; for a zone of the document page having a zone width and comprising a set of the elements, the zone comprising at least a portion of the page frame width: a) for a first iteration: segmenting the zone regularly into a number of candidate columns, a width of each of the candidate columns being function of the number of the candidate columns and the zone width; for each of the candidate columns, identifying the elements in the set which are within the candidate column; where the candidate columns meet a threshold for identified elements and a gutter is found which spaces the candidate columns, assigning, to a set of segmented columns, those elements in the set which are within the segmented columns, and identifying remaining elements in the set which are not covered by the segmented columns, the segmented columns corresponding in number to the number of candidate columns and each segmented column being spaced by the computed gutter; b) where there are remaining elements after a), performing at least one of: i) at least one subsequent iteration which includes repeating a), wherein in each subsequent iteration, the set of elements is the remaining elements in the set, and wherein the segmenting of the zone regularly into a number of candidate columns segments the zone into a different number of candidate columns from the first iteration and all other subsequent iterations, and ii) considering the zone as a single segmented column only, identifying the elements in the set which are within the single segmented column; and where there are remaining elements in the set after a) and b), providing for a) and b) to be performed for at least one subsequent zone of the page, wherein for each subsequent zone, the set of elements includes remaining elements not covered by the segmented columns identified for any of the preceding zones. | 1. A method for segmenting a document comprising: identifying a rectangular page frame using information from multiple pages of a document; matching the page frame to a page of the document; identifying elements within the matched page frame; for a zone of the document page having a zone width and comprising a set of the elements, the zone comprising at least a portion of the page frame width: a) for a first iteration: segmenting the zone regularly into a number of candidate columns, a width of each of the candidate columns being function of the number of the candidate columns and the zone width; for each of the candidate columns, identifying the elements in the set which are within the candidate column; where the candidate columns meet a threshold for identified elements and a gutter is found which spaces the candidate columns, assigning, to a set of segmented columns, those elements in the set which are within the segmented columns, and identifying remaining elements in the set which are not covered by the segmented columns, the segmented columns corresponding in number to the number of candidate columns and each segmented column being spaced by the computed gutter; b) where there are remaining elements after a), performing at least one of: i) at least one subsequent iteration which includes repeating a), wherein in each subsequent iteration, the set of elements is the remaining elements in the set, and wherein the segmenting of the zone regularly into a number of candidate columns segments the zone into a different number of candidate columns from the first iteration and all other subsequent iterations, and ii) considering the zone as a single segmented column only, identifying the elements in the set which are within the single segmented column; and where there are remaining elements in the set after a) and b), providing for a) and b) to be performed for at least one subsequent zone of the page, wherein for each subsequent zone, the set of elements includes remaining elements not covered by the segmented columns identified for any of the preceding zones. 20. The method of claim 1 , wherein the assigning of elements in the set to the segmented columns comprises assigning elements to respective blocks of the segmented columns, each segmented column comprising at least one block, wherein rules are provided for determining at least one of: an end of a block of a segmented column, and a start of a subsequent block in the same segmented column. | 0.731087 |
8,280,823 | 133 | 171 | 133. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: send a request to search the resume database; send search criteria; and receive a result set in response to a database query to the resume database, the database query including the search criteria, and the result set including at least one matching resume, wherein the resume database includes at least one resume, and a parsed resume associated with each resume, wherein each resume includes at least one skill or experience-related phrase, wherein each skill or experience-related phrase has an experience range determined by examining a use of the skill or experience-related phrase in the resume, and a term of experience based on the experience range, wherein the term of experience for each skill or experience-related phrase having multiple occurrences in the resume is a summation of the term of experience, or a portion of the term of experience, for each occurrence of the skill or experience-related phrase associated with a different experience range, wherein each parsed resume includes each said at least one skill or experience-related phrase located in the resume, the term of experience for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase, and wherein each matching resume is one of said at least one resume having the parsed resume associated with the matching resume satisfying the search criteria. | 133. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: send a request to search the resume database; send search criteria; and receive a result set in response to a database query to the resume database, the database query including the search criteria, and the result set including at least one matching resume, wherein the resume database includes at least one resume, and a parsed resume associated with each resume, wherein each resume includes at least one skill or experience-related phrase, wherein each skill or experience-related phrase has an experience range determined by examining a use of the skill or experience-related phrase in the resume, and a term of experience based on the experience range, wherein the term of experience for each skill or experience-related phrase having multiple occurrences in the resume is a summation of the term of experience, or a portion of the term of experience, for each occurrence of the skill or experience-related phrase associated with a different experience range, wherein each parsed resume includes each said at least one skill or experience-related phrase located in the resume, the term of experience for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase, and wherein each matching resume is one of said at least one resume having the parsed resume associated with the matching resume satisfying the search criteria. 171. The system of claim 133 , wherein the search criteria comprises a required salary range that includes a minimum required salary and a maximum required salary. | 0.867047 |
7,590,631 | 8 | 9 | 8. A computer program product in a computer readable storage media for use in a data processing system for aiding a user in navigating documents containing hyperlinks, the computer program product comprising: first instructions for storing reader preferences relating to information contained in the headers of secondary documents; second instructions for including an audience category in the reader preferences, whereby the user may obtain a modified hyperlink indication of relevance to reader preferences by secondary document author; third instructions for including an identification of a domain in the reader preferences, whereby the user may obtain a modified hyperlink indicating a secondary document from a predetermined source that the user expects to be useful; fourth instructions for retrieving a document from a network location; fifth instructions for parsing the document for hyperlinks associated with secondary documents; sixth instructions, responsive to detecting a hyperlink, for sending a request to a server for the header of the secondary document associated with the hyperlink, wherein the header contains information corresponding to characteristics of the secondary document; seventh instructions for receiving only the secondary document header from a hypertext server responding to the request; eighth instructions for comparing the information within the header of the secondary document to the stored reader preferences; and ninth instructions for modifying the hyperlink based on results of the comparison of the information contained within the header with the stored reader preferences. | 8. A computer program product in a computer readable storage media for use in a data processing system for aiding a user in navigating documents containing hyperlinks, the computer program product comprising: first instructions for storing reader preferences relating to information contained in the headers of secondary documents; second instructions for including an audience category in the reader preferences, whereby the user may obtain a modified hyperlink indication of relevance to reader preferences by secondary document author; third instructions for including an identification of a domain in the reader preferences, whereby the user may obtain a modified hyperlink indicating a secondary document from a predetermined source that the user expects to be useful; fourth instructions for retrieving a document from a network location; fifth instructions for parsing the document for hyperlinks associated with secondary documents; sixth instructions, responsive to detecting a hyperlink, for sending a request to a server for the header of the secondary document associated with the hyperlink, wherein the header contains information corresponding to characteristics of the secondary document; seventh instructions for receiving only the secondary document header from a hypertext server responding to the request; eighth instructions for comparing the information within the header of the secondary document to the stored reader preferences; and ninth instructions for modifying the hyperlink based on results of the comparison of the information contained within the header with the stored reader preferences. 9. The computer program product as recited in claim 8 , further comprising: eighth instructions, responsive to the comparison of the information to the reader preferences, for prefetching the secondary document and storing the secondary document in a read ahead cache. | 0.501859 |
9,501,384 | 1 | 5 | 1. A method for testing of software automation scripts, the method comprising: obtaining at least one software automation script, wherein the software automation script comprises a sequence of executable tasks configured to automatically place a computing system into a target state comprising one or more state properties; analyzing the software automation script; identifying, based on the analyzing, a plurality of tasks to be performed during execution of the software automation script; determining a set of possible states of the computing system and a set of expected state transitions associated with each of the plurality of tasks; generating a state transition graph based on the set of possible states and the set of expected state transitions, wherein the state transition graph comprises: a set of nodes, wherein each of the set of nodes represents one of the set of possible states of the computing system, a set of directed edges, wherein each of the set of directed edges connects two in the set of nodes, a first subset of the set of nodes, wherein each of the first subset of the set of nodes represents an initial state of the computing system when the software automation script is executed, a second subset of the set of nodes, wherein each of the second subset of the set of nodes represents a post state of the computing system after the software automation script has been executed, and a third subset of the of the set of nodes, wherein each of the third subset of the set of nodes is situated between at least one of the first subset and the second subset of the set of nodes, wherein a path between one of the first subset and one of the second subset of the set of nodes represents an execution of the software automation script, and wherein a transition edge between any two of the set of nodes represents an execution of one of the plurality of tasks; executing a plurality of test cases for the software automation script, wherein each of the plurality of test cases is a separate executable instance of the software automation script configured to test the software automation script, wherein each of the plurality of test cases executes the software automation script based on a different configuration of the computing system; and at least one of determining, based on executing the plurality of test cases, that the software automation script is one of idempotent and non-idempotent; and determining, based on executing the plurality of test cases, that the software automation script is one of convergent and non-convergent. | 1. A method for testing of software automation scripts, the method comprising: obtaining at least one software automation script, wherein the software automation script comprises a sequence of executable tasks configured to automatically place a computing system into a target state comprising one or more state properties; analyzing the software automation script; identifying, based on the analyzing, a plurality of tasks to be performed during execution of the software automation script; determining a set of possible states of the computing system and a set of expected state transitions associated with each of the plurality of tasks; generating a state transition graph based on the set of possible states and the set of expected state transitions, wherein the state transition graph comprises: a set of nodes, wherein each of the set of nodes represents one of the set of possible states of the computing system, a set of directed edges, wherein each of the set of directed edges connects two in the set of nodes, a first subset of the set of nodes, wherein each of the first subset of the set of nodes represents an initial state of the computing system when the software automation script is executed, a second subset of the set of nodes, wherein each of the second subset of the set of nodes represents a post state of the computing system after the software automation script has been executed, and a third subset of the of the set of nodes, wherein each of the third subset of the set of nodes is situated between at least one of the first subset and the second subset of the set of nodes, wherein a path between one of the first subset and one of the second subset of the set of nodes represents an execution of the software automation script, and wherein a transition edge between any two of the set of nodes represents an execution of one of the plurality of tasks; executing a plurality of test cases for the software automation script, wherein each of the plurality of test cases is a separate executable instance of the software automation script configured to test the software automation script, wherein each of the plurality of test cases executes the software automation script based on a different configuration of the computing system; and at least one of determining, based on executing the plurality of test cases, that the software automation script is one of idempotent and non-idempotent; and determining, based on executing the plurality of test cases, that the software automation script is one of convergent and non-convergent. 5. The method of claim 1 , wherein determining that the software automation script is one of idempotent and non-idempotent comprises: determining, based on executing the plurality of test cases, if the sequence of executable tasks for each separate instance of the software automation script yielded a non-conflicting state of the computing system; determining that the software automation script is idempotent based on determining that the sequence of executable tasks for each separate instance of the software automation script yielded a non-conflicting state of the computing system; and determining that the software automation script is non-idempotent based on determining that the sequence of executable tasks for at least one of the separate instances of the software automation script yielded a conflicting state of the computing system. | 0.596759 |
9,497,204 | 1 | 11 | 1. A computer implemented method that detects intrusions using a computer by analysing network traffic comprising: coupling a semi-supervised learning module to a network node that uses labeled and unlabeled data to train a semi-supervised machine learning sensor; recording events that comprise a feature set that include unauthorized intrusions and benign requests; identifying at least some of the benign behavior that occurs during the recording of the events while treating the remainder of the data as unlabeled; and training the semi-supervised learning module at the network node in-situ, such that the computer implemented method including the semi-supervised learning module is configured to identify the malicious traffic without relying on specific rules, signatures, or an anomaly detection; where the semi-supervised machine learning sensor comprises an extension of a plurality of pipelines and filters and the feature set is stored in one of the plurality of pipelines that the semi-supervised learning module is trained. | 1. A computer implemented method that detects intrusions using a computer by analysing network traffic comprising: coupling a semi-supervised learning module to a network node that uses labeled and unlabeled data to train a semi-supervised machine learning sensor; recording events that comprise a feature set that include unauthorized intrusions and benign requests; identifying at least some of the benign behavior that occurs during the recording of the events while treating the remainder of the data as unlabeled; and training the semi-supervised learning module at the network node in-situ, such that the computer implemented method including the semi-supervised learning module is configured to identify the malicious traffic without relying on specific rules, signatures, or an anomaly detection; where the semi-supervised machine learning sensor comprises an extension of a plurality of pipelines and filters and the feature set is stored in one of the plurality of pipelines that the semi-supervised learning module is trained. 11. The computer method of claim 1 further comprising retraining the semi-supervised learning module by interactively modifying training set data accessed by the semi-supervised learning module. | 0.632576 |
7,882,100 | 2 | 3 | 2. The method of claim 1 , wherein said transforming step includes determining a portion of the left deep nested loop join tree requiring transformation into a bushy tree shape for generating a semantically correct query execution plan. | 2. The method of claim 1 , wherein said transforming step includes determining a portion of the left deep nested loop join tree requiring transformation into a bushy tree shape for generating a semantically correct query execution plan. 3. The method of claim 2 , wherein said transforming step includes transforming said portion of the left deep nested loop join tree into a bushy tree shape. | 0.911765 |
9,230,215 | 8 | 15 | 8. A machine-implemented method comprising: (a) the machine receiving an original ontology containing a plurality of original concepts; and (b) the machine applying a concept expansion mechanism to the original ontology to generate an expanded ontology containing the original concepts and one or more pseudo concepts, wherein step (b) comprises applying at least one non-conventional reasoning process to a logical expression for a concept to generate at least one new pseudo concept. | 8. A machine-implemented method comprising: (a) the machine receiving an original ontology containing a plurality of original concepts; and (b) the machine applying a concept expansion mechanism to the original ontology to generate an expanded ontology containing the original concepts and one or more pseudo concepts, wherein step (b) comprises applying at least one non-conventional reasoning process to a logical expression for a concept to generate at least one new pseudo concept. 15. The method of claim 8 , wherein the at least one non-conventional reasoning process applies one or more distributive rules for one or more universal restrictions in the logical expression to generate a new pseudo concept. | 0.842657 |
7,627,543 | 1 | 4 | 1. An automated method of detection of software vulnerabilities by applying a rule set to test for vulnerabilities in computer software, the rule set comprising at least one vulnerability characterisation rule, the method incorporating the steps of: a) providing a training data set of computer software incorporating positive and negative vulnerability examples and expressed as programs flagged to indicate either presence or absence of vulnerability, the programs comprising instructions each incorporating an identifier to indicate its associated program, the instruction's address, an instruction operator and a list of instruction operands, b) defining a rule generalisation, the rule generalisation being processable to transform it into the at least one vulnerability characterisation rule, and c) using computer apparatus to execute the steps of: i) receiving the training data set and the rule generalisation, ii) processing the rule generalisation to transform it into a more specific rule generalisation by employing logic of at least First-Order and adding to the rule generalisation at least one of a condition, a variable, a constant, a unification of variables and a function based on the training data set and background knowledge relating to attributes of the training data set and consisting of at least one of concepts, facts of interest and functions for calculating values of interest from items of data, iii) evaluating the more specific rule generalisation by applying it to the training data set to identify vulnerabilities, and iv) incorporating the more specific rule generalisation in the rule set if it classifies vulnerabilities in the training data set adequately in terms of covering at least some of the positive vulnerability examples, v) applying the rule set to a test program for vulnerability detection therein, and vi) providing an alert or a report to a user regarding vulnerability detection in the test program resulting from operation of the method in order to enable corrective action to be taken. | 1. An automated method of detection of software vulnerabilities by applying a rule set to test for vulnerabilities in computer software, the rule set comprising at least one vulnerability characterisation rule, the method incorporating the steps of: a) providing a training data set of computer software incorporating positive and negative vulnerability examples and expressed as programs flagged to indicate either presence or absence of vulnerability, the programs comprising instructions each incorporating an identifier to indicate its associated program, the instruction's address, an instruction operator and a list of instruction operands, b) defining a rule generalisation, the rule generalisation being processable to transform it into the at least one vulnerability characterisation rule, and c) using computer apparatus to execute the steps of: i) receiving the training data set and the rule generalisation, ii) processing the rule generalisation to transform it into a more specific rule generalisation by employing logic of at least First-Order and adding to the rule generalisation at least one of a condition, a variable, a constant, a unification of variables and a function based on the training data set and background knowledge relating to attributes of the training data set and consisting of at least one of concepts, facts of interest and functions for calculating values of interest from items of data, iii) evaluating the more specific rule generalisation by applying it to the training data set to identify vulnerabilities, and iv) incorporating the more specific rule generalisation in the rule set if it classifies vulnerabilities in the training data set adequately in terms of covering at least some of the positive vulnerability examples, v) applying the rule set to a test program for vulnerability detection therein, and vi) providing an alert or a report to a user regarding vulnerability detection in the test program resulting from operation of the method in order to enable corrective action to be taken. 4. An automated method of detection of software vulnerabilities according to claim 1 wherein the rule set incorporates a rule which classifies a program as vulnerable if there is a copying loop defined as a portion of code that copies to a register from a source pointer, changes the source pointer, copies from the register into a destination pointer, changes that destination pointer, and has a control flow path from the code portion's end back to the code portion's beginning thus forming a loop. | 0.626308 |
7,545,986 | 11 | 20 | 11. An apparatus for classifying and sorting input data in a data stream, comprising: a processor having a first input for receiving said input data, a second input, and an output, and wherein said processor includes: a classifier input control including said first input and said second input; an adaptive classifier; a ground truth data input; a ground truth resampling buffer; and a source data re-sampling buffer, wherein said processor is configured for: a) sampling the input data with the input control; b) comparing one or more classes of the sampled input data with initially preset data classifications that constitute a baseline for determining mis-classification of data patterns; c) determining a degree of mis-classification of the input data and assigning a probability proportional to the degree of misclassification as a criterion for entry into a resampling buffer thereto; d) entering data patterns causing mis-classification in a resampling buffer with a probability value proportional to the degree of mis-classification; e) comparing the data patterns to a ground truth source and aligning the data patterns with their associated data pattern labels employing the same decision outcome based on a mis-classification probability as applied to the resampling buffer to form a set of training data; and f) updating the adaptive classifier to correlate with the training data; and g) repeating steps a)-f) until a sufficient degree of data classification optimization is realized; whereby an optimized data stream is provided by said processor at said output. | 11. An apparatus for classifying and sorting input data in a data stream, comprising: a processor having a first input for receiving said input data, a second input, and an output, and wherein said processor includes: a classifier input control including said first input and said second input; an adaptive classifier; a ground truth data input; a ground truth resampling buffer; and a source data re-sampling buffer, wherein said processor is configured for: a) sampling the input data with the input control; b) comparing one or more classes of the sampled input data with initially preset data classifications that constitute a baseline for determining mis-classification of data patterns; c) determining a degree of mis-classification of the input data and assigning a probability proportional to the degree of misclassification as a criterion for entry into a resampling buffer thereto; d) entering data patterns causing mis-classification in a resampling buffer with a probability value proportional to the degree of mis-classification; e) comparing the data patterns to a ground truth source and aligning the data patterns with their associated data pattern labels employing the same decision outcome based on a mis-classification probability as applied to the resampling buffer to form a set of training data; and f) updating the adaptive classifier to correlate with the training data; and g) repeating steps a)-f) until a sufficient degree of data classification optimization is realized; whereby an optimized data stream is provided by said processor at said output. 20. An apparatus as in claim 11 , wherein the degree of mis-classification is determined by the function
d ( x ) =P ( C 1 |x ) −P ( C 0 |x ) where C0 is a first class, C1 is a second class, and P(C0|x)is a first discriminant function and P(C1|x) is a second discriminant function representing Bayesian posterior probabilities for a sample vector x. | 0.705882 |
9,519,681 | 9 | 12 | 9. A computer-implemented method, comprising: storing a knowledge base in a data store, the knowledge base comprising first knowledge represented in a structured, machine-readable format; storing a plurality of generators in the data store, each generator including a fact pattern representing one or more characteristics of facts that can be generated by that generator, and code for generating the facts; using one or more computing devices, generating second knowledge for inclusion in the knowledge base by inferring the second knowledge from the first knowledge using a first generator of the plurality of generators; using one or more computing devices, determining that the second knowledge is not semantically contradicted by other knowledge in the knowledge base; using the one or more computing devices, storing the second knowledge in the knowledge base in association with related knowledge information identifying the first knowledge from which the second knowledge was inferred; using the one or more computing devices, responding to a first query using the second knowledge, the first query having been received subsequent to storage of the second knowledge in the knowledge base; using the one or more computing devices, identifying a second generator of the plurality of generators for which the included fact pattern is compatible with a second query; using the one or more computing devices, dynamically generating third knowledge not represented in the knowledge base in response to the second query by inferring the third knowledge from the second knowledge using the second generator; storing the third knowledge in a cache; using the one or more computing devices, retrieving the third knowledge from the cache as part of recursive processing of the second query; using the one or more computing devices, responding to the second query using the third knowledge; using the one or more computing devices, determining that the first knowledge from which the second knowledge was inferred is no longer valid; and using the one or more computing devices, removing the second knowledge from the knowledge base using the related knowledge information. | 9. A computer-implemented method, comprising: storing a knowledge base in a data store, the knowledge base comprising first knowledge represented in a structured, machine-readable format; storing a plurality of generators in the data store, each generator including a fact pattern representing one or more characteristics of facts that can be generated by that generator, and code for generating the facts; using one or more computing devices, generating second knowledge for inclusion in the knowledge base by inferring the second knowledge from the first knowledge using a first generator of the plurality of generators; using one or more computing devices, determining that the second knowledge is not semantically contradicted by other knowledge in the knowledge base; using the one or more computing devices, storing the second knowledge in the knowledge base in association with related knowledge information identifying the first knowledge from which the second knowledge was inferred; using the one or more computing devices, responding to a first query using the second knowledge, the first query having been received subsequent to storage of the second knowledge in the knowledge base; using the one or more computing devices, identifying a second generator of the plurality of generators for which the included fact pattern is compatible with a second query; using the one or more computing devices, dynamically generating third knowledge not represented in the knowledge base in response to the second query by inferring the third knowledge from the second knowledge using the second generator; storing the third knowledge in a cache; using the one or more computing devices, retrieving the third knowledge from the cache as part of recursive processing of the second query; using the one or more computing devices, responding to the second query using the third knowledge; using the one or more computing devices, determining that the first knowledge from which the second knowledge was inferred is no longer valid; and using the one or more computing devices, removing the second knowledge from the knowledge base using the related knowledge information. 12. The method of claim 9 , further comprising generating the second knowledge with reference to previously generated knowledge inferred from the first knowledge. | 0.896684 |
8,001,154 | 1 | 4 | 1. A method of creating a library description file, the method comprising: receiving, at a computing device, a description of one or more locations, said description containing information describing a data source of each of the one or more locations; automatically grouping, at the computing device, a subset of the one or more locations based on predefined criteria into a library, wherein the library is a group of data sources grouped together for simultaneous searching, and wherein the data sources are at different locations; creating, at a computing device, a library description file for the library, wherein said library description file is comprised of information describing the library including a display format element for the library, at least one location element for the library, a library description format, a scope element, a properties element, and a shell link element, wherein the display format element defines formatting of a visual indicia used to represent the library in a user interface and for how search results are presented for search queries performed upon the library, wherein the location element contains methods for communicating within the group of data sources, wherein the library description format is created using a standard library description format and is a XML root element, wherein the scope element provides information related to scopes of the one or more locations associated with the library and exclusions to searchers upon the library, wherein the properties element includes information detailing a format and a syntax required of search queries that are issued to the library, and wherein the shell link element points to the visual indicia representing the library description file; and storing the library description file on a computer-readable medium. | 1. A method of creating a library description file, the method comprising: receiving, at a computing device, a description of one or more locations, said description containing information describing a data source of each of the one or more locations; automatically grouping, at the computing device, a subset of the one or more locations based on predefined criteria into a library, wherein the library is a group of data sources grouped together for simultaneous searching, and wherein the data sources are at different locations; creating, at a computing device, a library description file for the library, wherein said library description file is comprised of information describing the library including a display format element for the library, at least one location element for the library, a library description format, a scope element, a properties element, and a shell link element, wherein the display format element defines formatting of a visual indicia used to represent the library in a user interface and for how search results are presented for search queries performed upon the library, wherein the location element contains methods for communicating within the group of data sources, wherein the library description format is created using a standard library description format and is a XML root element, wherein the scope element provides information related to scopes of the one or more locations associated with the library and exclusions to searchers upon the library, wherein the properties element includes information detailing a format and a syntax required of search queries that are issued to the library, and wherein the shell link element points to the visual indicia representing the library description file; and storing the library description file on a computer-readable medium. 4. The method of claim 1 , wherein the library description file is created using a library description template. | 0.878525 |
8,027,957 | 1 | 2 | 1. A method for compressing a grammar, the method comprising: receiving a grammar by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; identifying, from the set of token classes within each rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify duplicates within the set of unimportant token classes; merging the set of unimportant token classes to generate a merged token class by removing duplicates within the set of unimportant token classes; and substituting the merged token class in the grammar for the set of unimportant token classes to generate a compressed grammar, wherein substituting the merged token class in the grammar for the set of unimportant token classes that were merged to generate the merged token class comprises substituting the merged token class for all instances within the grammar of the set of unimportant token classes that were merged to generate the merged token class. | 1. A method for compressing a grammar, the method comprising: receiving a grammar by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; identifying, from the set of token classes within each rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify duplicates within the set of unimportant token classes; merging the set of unimportant token classes to generate a merged token class by removing duplicates within the set of unimportant token classes; and substituting the merged token class in the grammar for the set of unimportant token classes to generate a compressed grammar, wherein substituting the merged token class in the grammar for the set of unimportant token classes that were merged to generate the merged token class comprises substituting the merged token class for all instances within the grammar of the set of unimportant token classes that were merged to generate the merged token class. 2. The method of claim 1 , wherein the grammar comprises at least one of: a manually-generated grammar; and an automatically-generated grammar. | 0.96753 |
8,335,381 | 9 | 10 | 9. The method of claim 1 , wherein the training a model based on the at least one computer-generated image comprises extracting features from patches of the computer-generated image. | 9. The method of claim 1 , wherein the training a model based on the at least one computer-generated image comprises extracting features from patches of the computer-generated image. 10. The method of claim 9 , wherein the extracting features from patches of the computer-generated image comprises translating the image stepwise with a window of fixed height and width and at each step, extracting a patch. | 0.927785 |
8,140,326 | 1 | 11 | 1. A method for reducing speech intelligibility while preserving environmental sounds, the method comprising: receiving an audio signal; processing the audio signal to separate a vocalic region that comprises vowels; computing a representation of at least the vocalic region, the representation including at least a vocal tract transfer function and an excitation; replacing the vocal tract transfer function of the vocalic region with a replacement sound transfer function of a replacement sound to create a modified vocal tract transfer function; and synthesizing a modified audio signal of at least the vocalic region from the modified vocal tract transfer function and the excitation. | 1. A method for reducing speech intelligibility while preserving environmental sounds, the method comprising: receiving an audio signal; processing the audio signal to separate a vocalic region that comprises vowels; computing a representation of at least the vocalic region, the representation including at least a vocal tract transfer function and an excitation; replacing the vocal tract transfer function of the vocalic region with a replacement sound transfer function of a replacement sound to create a modified vocal tract transfer function; and synthesizing a modified audio signal of at least the vocalic region from the modified vocal tract transfer function and the excitation. 11. The method of claim 1 , further comprising selecting a tone or a synthesized vowel as the replacement sound. | 0.831832 |
9,240,184 | 17 | 22 | 17. A tangible, non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by one or more processors of a system, cause the system to perform operations comprising: transforming an audio input signal into a first sequence of feature vectors and a second sequence of feature vectors, wherein both the first and second sequences of feature vectors correspond in common to a sequence of temporal frames of the audio input signal, and wherein each respective feature vector of the first sequence and a corresponding respective feature vector of the second sequence bear quantitative measures of acoustic properties of a corresponding, respective temporal frame of the sequence of temporal frames of the audio input signal; processing the first sequence of feature vectors with a neural network (NN) implemented by the system to generate a NN-based set of emission probabilities for a plurality of hidden Markov models (HMMs) implemented by the system; processing the second sequence of feature vectors with a Gaussian mixture model (GMM) implemented by the system to generate a GMM-based set of emission probabilities for the plurality of HMMs by computing, for each temporal frame, weighted sums of the NN-based emission probabilities and the GMM-based emission probabilities, merging the NN-based set of emission probabilities with the GMM-based set of emission probabilities to generate a merged set of emission probabilities for the plurality of HMMs; and applying the merged set of emission probabilities to the plurality of HMMs to determine speech content corresponding to the sequence of temporal frames of the audio input signal, wherein the weighted sums are computed according to weights computationally-determined by at least one processor during to a training process that minimizes a computationally-determined difference between computationally-predicted speech in training temporal frames and predetermined speech in the training temporal frames. | 17. A tangible, non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by one or more processors of a system, cause the system to perform operations comprising: transforming an audio input signal into a first sequence of feature vectors and a second sequence of feature vectors, wherein both the first and second sequences of feature vectors correspond in common to a sequence of temporal frames of the audio input signal, and wherein each respective feature vector of the first sequence and a corresponding respective feature vector of the second sequence bear quantitative measures of acoustic properties of a corresponding, respective temporal frame of the sequence of temporal frames of the audio input signal; processing the first sequence of feature vectors with a neural network (NN) implemented by the system to generate a NN-based set of emission probabilities for a plurality of hidden Markov models (HMMs) implemented by the system; processing the second sequence of feature vectors with a Gaussian mixture model (GMM) implemented by the system to generate a GMM-based set of emission probabilities for the plurality of HMMs by computing, for each temporal frame, weighted sums of the NN-based emission probabilities and the GMM-based emission probabilities, merging the NN-based set of emission probabilities with the GMM-based set of emission probabilities to generate a merged set of emission probabilities for the plurality of HMMs; and applying the merged set of emission probabilities to the plurality of HMMs to determine speech content corresponding to the sequence of temporal frames of the audio input signal, wherein the weighted sums are computed according to weights computationally-determined by at least one processor during to a training process that minimizes a computationally-determined difference between computationally-predicted speech in training temporal frames and predetermined speech in the training temporal frames. 22. The tangible, non-transitory computer-readable storage medium of claim 17 , wherein determining speech content is at least one of generating a text string of the speech content, or identifying a computer-executable command based on the speech content. | 0.907205 |
8,327,326 | 1 | 4 | 1. At a computer system including one or more processors and system memory, the computer system also including an editor for editing source code of a programming language, a method for providing automated assistance to resolve the placement of a closing code construct operative as an editor caret when editing a portion of source code, the method comprising: while the editor is in a non-interaction mode for positioning closing code constructs: an act of receiving user input from a user, the user input for entering an opening code construct at a specified position within the portion of source code, wherein the opening code construct in combination with a corresponding closing code construct form a grouping representing a feature of the programming language that is being used to develop the source code; in response to receiving the user input for entering the opening code construct: an act of visually indicating placement of the opening code construct at the specified position within the portion of source code; and an act of visually indicating placement of the corresponding closing code construct at another position within the portion of source code based on one or more syntactical rules or semantic rules of the programming language; and an act of detecting that the user's intent with respect to placement of the corresponding closing construct is ambiguous, the ambiguous placement being a real-time event identified as a mismatch between the predicted placement for the closing construct and the user's actual placement of the closing construct in view of the user's earlier placement of the opening construct, the mismatch based on observance of the syntactical and semantic rules of the programming language; in response to the ambiguous placement, an act of the processor transitioning the editor to an interaction mode for positioning closing code constructs, the interaction mode visually indicating that the user is permitted to reposition the closing construct between one or more visually indicated valid positions within the portion of source code, the visual indication of one or more valid positions in accordance with the one or more syntactical rules or semantic rules of the programming language, the interaction mode altering how one or more forms of user input are interpreted by the editor; an act of receiving a form of user input, selected from among the one or more of forms of user input, from the user; an act of re-positioning the closing code construct in accordance with an altered interpretation of the received form of user input due to the editor being in the interaction mode; and an act of transitioning the editor out of the interaction mode subsequent to re-positioning the closing code construct. | 1. At a computer system including one or more processors and system memory, the computer system also including an editor for editing source code of a programming language, a method for providing automated assistance to resolve the placement of a closing code construct operative as an editor caret when editing a portion of source code, the method comprising: while the editor is in a non-interaction mode for positioning closing code constructs: an act of receiving user input from a user, the user input for entering an opening code construct at a specified position within the portion of source code, wherein the opening code construct in combination with a corresponding closing code construct form a grouping representing a feature of the programming language that is being used to develop the source code; in response to receiving the user input for entering the opening code construct: an act of visually indicating placement of the opening code construct at the specified position within the portion of source code; and an act of visually indicating placement of the corresponding closing code construct at another position within the portion of source code based on one or more syntactical rules or semantic rules of the programming language; and an act of detecting that the user's intent with respect to placement of the corresponding closing construct is ambiguous, the ambiguous placement being a real-time event identified as a mismatch between the predicted placement for the closing construct and the user's actual placement of the closing construct in view of the user's earlier placement of the opening construct, the mismatch based on observance of the syntactical and semantic rules of the programming language; in response to the ambiguous placement, an act of the processor transitioning the editor to an interaction mode for positioning closing code constructs, the interaction mode visually indicating that the user is permitted to reposition the closing construct between one or more visually indicated valid positions within the portion of source code, the visual indication of one or more valid positions in accordance with the one or more syntactical rules or semantic rules of the programming language, the interaction mode altering how one or more forms of user input are interpreted by the editor; an act of receiving a form of user input, selected from among the one or more of forms of user input, from the user; an act of re-positioning the closing code construct in accordance with an altered interpretation of the received form of user input due to the editor being in the interaction mode; and an act of transitioning the editor out of the interaction mode subsequent to re-positioning the closing code construct. 4. The method as recited in claim 1 , wherein the act of the transitioning the editor to an interaction mode for positioning closing code constructs comprises an act of transitioning to an interaction mode that permits repositioning of the closing construct based on semantic rules of the programming language. | 0.766566 |
9,632,748 | 1 | 18 | 1. A method comprising: receiving, by a first computing device of a plurality of computing devices in physical proximity to one another, a spoken audio input that is also received by one or more additional computing devices of the plurality of computing devices; determining, by the first computing device and based at least in part on information received from the one or more additional computing devices, whether the first computing device should perform speech recognition on the spoken audio input; and responsive to determining that the first computing device should perform speech recognition on the spoken audio input: sending, by the first computing device and to at least a second computing device from the plurality of computing devices, a command to temporarily refrain from performing speech recognition; performing, by the first computing device, speech recognition on the spoken audio input; determining, by the first computing device, based on performing speech recognition on the spoken audio input, whether the spoken audio input includes a predetermined spoken audio command; and responsive to determining that the spoken audio input includes the predetermined spoken audio command, executing, by the first computing device, an action associated with the predetermined spoken audio command. | 1. A method comprising: receiving, by a first computing device of a plurality of computing devices in physical proximity to one another, a spoken audio input that is also received by one or more additional computing devices of the plurality of computing devices; determining, by the first computing device and based at least in part on information received from the one or more additional computing devices, whether the first computing device should perform speech recognition on the spoken audio input; and responsive to determining that the first computing device should perform speech recognition on the spoken audio input: sending, by the first computing device and to at least a second computing device from the plurality of computing devices, a command to temporarily refrain from performing speech recognition; performing, by the first computing device, speech recognition on the spoken audio input; determining, by the first computing device, based on performing speech recognition on the spoken audio input, whether the spoken audio input includes a predetermined spoken audio command; and responsive to determining that the spoken audio input includes the predetermined spoken audio command, executing, by the first computing device, an action associated with the predetermined spoken audio command. 18. The method of claim 1 , further comprising: determining, by the first computing device, based on a network connection of the first computing device and a respective network connection of the one or more additional computing devices, that the one or more additional computing devices are in proximity to the first computing device, wherein determining whether the first computing device should perform speech recognition on the spoken audio input is responsive to determining that the one or more additional computing devices are in proximity to the first computing device. | 0.687296 |
9,916,384 | 1 | 8 | 1. A method performed by one or more computers, the method comprising: maintaining an authoritative resources index that, for each entity of a plurality of entities, maps one or more authoritative resources to the entity, wherein each of the one or more authoritative resources is a resource whose occurrence in search results for a received search query has been determined to be an indicator that the received search query is directed to the entity; receiving a first search query from a user device; receiving search results for the first search query provided by a search engine, wherein each of the search results identifies a respective resource; determining that the first search query relates to a first entity of a first entity type based on determining that a count of search results for the first search query that identify resources that have been mapped to the first entity in the authoritative resources index exceeds a first threshold number; and in response to determining that the first search query relates to the first entity of the first entity type, transmitting information identifying one or more entities of a second entity type that have a predetermined relationship with the first entity to the user device as part of a response to the first search query. | 1. A method performed by one or more computers, the method comprising: maintaining an authoritative resources index that, for each entity of a plurality of entities, maps one or more authoritative resources to the entity, wherein each of the one or more authoritative resources is a resource whose occurrence in search results for a received search query has been determined to be an indicator that the received search query is directed to the entity; receiving a first search query from a user device; receiving search results for the first search query provided by a search engine, wherein each of the search results identifies a respective resource; determining that the first search query relates to a first entity of a first entity type based on determining that a count of search results for the first search query that identify resources that have been mapped to the first entity in the authoritative resources index exceeds a first threshold number; and in response to determining that the first search query relates to the first entity of the first entity type, transmitting information identifying one or more entities of a second entity type that have a predetermined relationship with the first entity to the user device as part of a response to the first search query. 8. The method of claim 1 , further comprising: obtaining data identifying the first entity and the first entity type; obtaining data identifying one or more resources that are associated with the first entity; and generating a respective mapping between the first entity and each of the one or more resources associated with the first entity in the second index. | 0.801752 |
7,734,619 | 1 | 5 | 1. A method of presenting to a user a lineage diagram representing a query plan, the method comprising: receiving by a computer a query plan from a query engine during a query planning mode when a logical query is processed by the query engine to generate the query plan, the query plan containing transformations used to convert the logical query into one or more native queries that are applicable to databases storing data relevant to the native queries; generating, during the query planning mode, a lineage diagram representing the query plan using one or more query subjects and one or more symbolic links representing the transformations and conceptual data streams between the query subjects connected by the symbolic links, wherein at least a first query subject in the lineage diagram references a second query subject defined by a metadata model describing a plurality of layers of abstraction of the database storing data relevant to the native queries, and wherein at least one query subject in the lineage diagram references a database table present in one of the databases storing data relevant to the native queries; receiving user selection of a query subject presented in the lineage diagram; changing, in the lineage diagram, presentation of the selected query subject to show one or more corresponding query subjects that are represented by the selected query subject such that lineage of the selected query subject is interactively shown in the diagram using the corresponding query subjects in a same or different layer of the metadata model; allowing the user to select one of the symbolic links visual in a current view; and expanding or collapsing the selected symbolic link to show or hide one or more query subjects that are represented by the selected symbolic link based on the user's selection. | 1. A method of presenting to a user a lineage diagram representing a query plan, the method comprising: receiving by a computer a query plan from a query engine during a query planning mode when a logical query is processed by the query engine to generate the query plan, the query plan containing transformations used to convert the logical query into one or more native queries that are applicable to databases storing data relevant to the native queries; generating, during the query planning mode, a lineage diagram representing the query plan using one or more query subjects and one or more symbolic links representing the transformations and conceptual data streams between the query subjects connected by the symbolic links, wherein at least a first query subject in the lineage diagram references a second query subject defined by a metadata model describing a plurality of layers of abstraction of the database storing data relevant to the native queries, and wherein at least one query subject in the lineage diagram references a database table present in one of the databases storing data relevant to the native queries; receiving user selection of a query subject presented in the lineage diagram; changing, in the lineage diagram, presentation of the selected query subject to show one or more corresponding query subjects that are represented by the selected query subject such that lineage of the selected query subject is interactively shown in the diagram using the corresponding query subjects in a same or different layer of the metadata model; allowing the user to select one of the symbolic links visual in a current view; and expanding or collapsing the selected symbolic link to show or hide one or more query subjects that are represented by the selected symbolic link based on the user's selection. 5. The method as claimed in claim 1 , further comprising: receiving a user change in the lineage diagram; and changing the metadata model in response to the user change made to the lineage diagram. | 0.502525 |
8,561,021 | 9 | 11 | 9. A method performed on a computer processor, said method comprising: receiving application code to test; receiving test code designed to test said application code, said test code comprising unit tests for said application code; performing an automated evaluation of said test code to determine a qualitative test code health metric for each of said unit tests, by: determining a block of application code covered by a first test code component; identifying each output from said block to determine a number of outputs; examining said first test code component to determine a number of assertions corresponding to said outputs; and using said number of assertions and said number of outputs to determine the qualitative test code health metric; and displaying said qualitative test code health metric for each of said unit tests. | 9. A method performed on a computer processor, said method comprising: receiving application code to test; receiving test code designed to test said application code, said test code comprising unit tests for said application code; performing an automated evaluation of said test code to determine a qualitative test code health metric for each of said unit tests, by: determining a block of application code covered by a first test code component; identifying each output from said block to determine a number of outputs; examining said first test code component to determine a number of assertions corresponding to said outputs; and using said number of assertions and said number of outputs to determine the qualitative test code health metric; and displaying said qualitative test code health metric for each of said unit tests. 11. The method of claim 9 further comprising: executing said test code against said application code to generate test results; and displaying said test results along with said qualitative test code health metrics. | 0.84407 |
8,432,367 | 11 | 16 | 11. A touch screen system comprising: a touch screen graphical display; a command interpreter configured to identify modifier interactions with the graphical display and, in response to identification of the modifier interaction, modify the interpretation of other interaction with the graphical display; and one or more persistent data storage devices, the data storage devices storing a first set of rules for interpreting user interaction with the graphical display and a second set of rules for interpreting user interaction with the graphical display, the first set of rules interpreting motion across a map or a proper subset of a collection of information as a scrolling or panning command, the second set of rules interpreting the motion as a glyph, wherein the command interpreter is configured to modify the interpretation of the other interaction by switching between interpretation under the first set of rules and interpretation under the second set of rules in response to determining that a first input over a selectable object on the touch screen graphical display does not match a type of input associated with selection of the selectable object. | 11. A touch screen system comprising: a touch screen graphical display; a command interpreter configured to identify modifier interactions with the graphical display and, in response to identification of the modifier interaction, modify the interpretation of other interaction with the graphical display; and one or more persistent data storage devices, the data storage devices storing a first set of rules for interpreting user interaction with the graphical display and a second set of rules for interpreting user interaction with the graphical display, the first set of rules interpreting motion across a map or a proper subset of a collection of information as a scrolling or panning command, the second set of rules interpreting the motion as a glyph, wherein the command interpreter is configured to modify the interpretation of the other interaction by switching between interpretation under the first set of rules and interpretation under the second set of rules in response to determining that a first input over a selectable object on the touch screen graphical display does not match a type of input associated with selection of the selectable object. 16. The touch screen system of claim 11 , wherein the second set of rules comprises rules for interpreting the motion as a custom glyph. | 0.774834 |
9,430,652 | 1 | 5 | 1. A computer-implemented method for tokenizing data comprising: receiving, by a computing device, a data value to be tokenized; identifying, by the computing device, one or more use rules associated with the received data value, wherein each use rule defines a limitation on use of the received data value; modifying, by the computing device, the received data value to include a use rule identifier representing the identified one or more use rules to produce a modified data value; identifying, by the computing device, one or more token tables based on the use rule identifier; accessing, by the computing device, the identified one or more token tables for use in tokenizing the modified data value; and tokenizing, by the computing device, the modified data value using the accessed one or more token tables by querying at least one accessed token table with a portion of the modified data value including at least a portion of the use rule identifier to identify a token value mapped to the portion of the modified data value by the at least one access token table and replacing the portion of the modified data value with the identified token value to create tokenized data. | 1. A computer-implemented method for tokenizing data comprising: receiving, by a computing device, a data value to be tokenized; identifying, by the computing device, one or more use rules associated with the received data value, wherein each use rule defines a limitation on use of the received data value; modifying, by the computing device, the received data value to include a use rule identifier representing the identified one or more use rules to produce a modified data value; identifying, by the computing device, one or more token tables based on the use rule identifier; accessing, by the computing device, the identified one or more token tables for use in tokenizing the modified data value; and tokenizing, by the computing device, the modified data value using the accessed one or more token tables by querying at least one accessed token table with a portion of the modified data value including at least a portion of the use rule identifier to identify a token value mapped to the portion of the modified data value by the at least one access token table and replacing the portion of the modified data value with the identified token value to create tokenized data. 5. The method of claim 1 , wherein the received data value comprises a credit card number. | 0.904661 |
8,781,204 | 29 | 30 | 29. The method according to claim 8 , wherein said at least one region of interest is selected to include a high density of patterns, preferably linear or curvilinear intaglio-printed patterns. | 29. The method according to claim 8 , wherein said at least one region of interest is selected to include a high density of patterns, preferably linear or curvilinear intaglio-printed patterns. 30. The method according to claim 29 , wherein said at least one region of interest is selected to include patterns of a pictorial representation, such as a portrait, provided on the candidate document. | 0.927806 |
9,405,792 | 28 | 34 | 28. A method of processing a search query with an online computing system comprising: a) receiving a search query relating to a first event and/or a first topic; determining if said search query includes temporal parameters related to said first event and/or said first topic; b) generating an initial set of search results, including an initial set of electronic documents, which are responsive to the search query with the online computing system; c) based on steps (a) and (b) processing documents, including said initial set of electronic documents, to determine temporal characteristics of such documents with respect to said first event and/or said first topic; wherein said temporal characteristics are associated with content in said documents pertaining to {object, object status} pairs but are not any of creation time alone, publication time alone, or a combination of creation time and publication time alone; further wherein said processing determines said temporal characteristics in said documents by analyzing said {object, object status} pairs and assigning an object status for each object to a distinct temporal period; and d) altering a composition and/or ordering of said initial set of search results based on said step (c) and returning such as a final set of search results responsive to said search query. | 28. A method of processing a search query with an online computing system comprising: a) receiving a search query relating to a first event and/or a first topic; determining if said search query includes temporal parameters related to said first event and/or said first topic; b) generating an initial set of search results, including an initial set of electronic documents, which are responsive to the search query with the online computing system; c) based on steps (a) and (b) processing documents, including said initial set of electronic documents, to determine temporal characteristics of such documents with respect to said first event and/or said first topic; wherein said temporal characteristics are associated with content in said documents pertaining to {object, object status} pairs but are not any of creation time alone, publication time alone, or a combination of creation time and publication time alone; further wherein said processing determines said temporal characteristics in said documents by analyzing said {object, object status} pairs and assigning an object status for each object to a distinct temporal period; and d) altering a composition and/or ordering of said initial set of search results based on said step (c) and returning such as a final set of search results responsive to said search query. 34. The method of claim 28 wherein advertising is presented to a user presenting said search query based on a current state identified for said first event or topic determined from said {object, status} pairs. | 0.924874 |
10,043,500 | 1 | 4 | 1. A method of making audio music selection and creating a mixtape, comprising: importing one or more audio digital data files from an audio music repository; sorting and filtering the audio digital data files based on one or more selection criteria; creating the mixtape from the audio digital data files sorting and filtering results, the results comprising one or more sorted and filtered audio digital data files; wherein the sorting and filtering of the audio digital data files comprise: spectral analyzing each of the audio digital data files to extract one or more low level acoustic feature parameters of the audio digital data file; from the low level acoustic feature parameter values, determining one or more high level acoustic feature parameters of the analyzed audio digital data file; determining a first similarity score of each of the analyzed audio digital data files by comparing the acoustic feature parameter values of the analyzed audio digital data file against desired acoustic feature parameter values determined from the selection criteria; and sorting the analyzed audio digital data files according to their first similarity scores; and filtering out the analyzed audio digital data files with first similarity scores lower than a filter threshold; and compiling a similarity matrix comprising a second similarity score of each of the analyzed audio digital data file comprising: determining the second similarity score of each of the analyzed audio digital data files by comparing the acoustic feature parameter values of the analyzed audio digital data file against the acoustic feature parameter values of another one of the analyzed audio digital data files; including the second similarity score in the similarity matrix with reference to the two analyzed audio digital data files compared; excluding second similarity scores that are identical from the similarity matrix; and excluding second similarity scores that are below a similarity threshold from the similarity matrix; wherein the the similarity matrix is used to identify candidate audio digital data files with similar acoustic feature to those audio digital data files in the mixtape. | 1. A method of making audio music selection and creating a mixtape, comprising: importing one or more audio digital data files from an audio music repository; sorting and filtering the audio digital data files based on one or more selection criteria; creating the mixtape from the audio digital data files sorting and filtering results, the results comprising one or more sorted and filtered audio digital data files; wherein the sorting and filtering of the audio digital data files comprise: spectral analyzing each of the audio digital data files to extract one or more low level acoustic feature parameters of the audio digital data file; from the low level acoustic feature parameter values, determining one or more high level acoustic feature parameters of the analyzed audio digital data file; determining a first similarity score of each of the analyzed audio digital data files by comparing the acoustic feature parameter values of the analyzed audio digital data file against desired acoustic feature parameter values determined from the selection criteria; and sorting the analyzed audio digital data files according to their first similarity scores; and filtering out the analyzed audio digital data files with first similarity scores lower than a filter threshold; and compiling a similarity matrix comprising a second similarity score of each of the analyzed audio digital data file comprising: determining the second similarity score of each of the analyzed audio digital data files by comparing the acoustic feature parameter values of the analyzed audio digital data file against the acoustic feature parameter values of another one of the analyzed audio digital data files; including the second similarity score in the similarity matrix with reference to the two analyzed audio digital data files compared; excluding second similarity scores that are identical from the similarity matrix; and excluding second similarity scores that are below a similarity threshold from the similarity matrix; wherein the the similarity matrix is used to identify candidate audio digital data files with similar acoustic feature to those audio digital data files in the mixtape. 4. The method of claim 1 , wherein the selection criteria include scaled values of tempo, intensity, bass level, treble level, rhythm, mood, and energy of a song. | 0.84453 |
10,108,601 | 18 | 24 | 18. A system for presenting content personalized for a user comprising: a processor; memory coupled to the processor; a learning module of a server computer for analyzing and categorizing the content using artificial intelligence and storing the categorized content on a memory of a server computer; a training module of the server computer for capturing explicit preferences of a user comprising user content interests, preferred content type, preferred presentation type, preferred language and preferred presentation format; storing the captured explicit preferences of the user on the memory of the server computer in an internal representation of the user's preferences; storing an internal representation of prior knowledge of the user; and determining a plurality of implicit preferences of the user, wherein the implicit preferences comprise geography, language, or media type; a content processing module of the server computer for mapping the categorized content to the internal representation of the user's preferences and the internal representation of prior knowledge of the user to discover the content relevant to the user, from the categorized content, and to discover the preferred presentation type and formats; and processing the content relevant to the user into the preferred presentation type and format for presenting to the user on a user device; wherein at least one conflict between a conflicting explicit preference and a conflicting implicit preference is resolved by giving precedence to the conflicting explicit preference; and a content presentation module of the server computer for rendering the relevant content in the preferred presentation type and format on the user device. | 18. A system for presenting content personalized for a user comprising: a processor; memory coupled to the processor; a learning module of a server computer for analyzing and categorizing the content using artificial intelligence and storing the categorized content on a memory of a server computer; a training module of the server computer for capturing explicit preferences of a user comprising user content interests, preferred content type, preferred presentation type, preferred language and preferred presentation format; storing the captured explicit preferences of the user on the memory of the server computer in an internal representation of the user's preferences; storing an internal representation of prior knowledge of the user; and determining a plurality of implicit preferences of the user, wherein the implicit preferences comprise geography, language, or media type; a content processing module of the server computer for mapping the categorized content to the internal representation of the user's preferences and the internal representation of prior knowledge of the user to discover the content relevant to the user, from the categorized content, and to discover the preferred presentation type and formats; and processing the content relevant to the user into the preferred presentation type and format for presenting to the user on a user device; wherein at least one conflict between a conflicting explicit preference and a conflicting implicit preference is resolved by giving precedence to the conflicting explicit preference; and a content presentation module of the server computer for rendering the relevant content in the preferred presentation type and format on the user device. 24. The system according to claim 18 , wherein the preferred presentation type comprises at least one selected from the group consisting of: Text data, Graphical representation, Images, Concept map, Flow charts, Text to speech, Bulleted list, display of trends, and patterns in the content. | 0.802721 |
9,311,057 | 15 | 20 | 15. A system comprising: one or more processors to: import, in a text-based format, a model that describes software or a system in a modeling language into a graphical modeling environment, wherein the modeling language does not define a formal, executable semantic capable of describing a dynamic behavior of the software or system, and wherein the model comprises model components; generate executable elements, in the graphical modeling environment, that represent the model components, wherein at least some of the executable elements comply with standards of a domain or a platform, and wherein the domain or platform comprises CORBA, CORBA-RT, Advanced Architecture Description Language (AADL), AUTOSAR, Software Communication Architecture (SCA) as defined by the Department of Defense, or one or more derivatives of any one of the above; generate an executable model in the graphical modeling environment, the executable model comprising executable elements and corresponding to the model that describes the software or system; and update: the model that describes the software or system based on changes made to the executable model, or the executable model based on changes made to the model that describes the software or system. | 15. A system comprising: one or more processors to: import, in a text-based format, a model that describes software or a system in a modeling language into a graphical modeling environment, wherein the modeling language does not define a formal, executable semantic capable of describing a dynamic behavior of the software or system, and wherein the model comprises model components; generate executable elements, in the graphical modeling environment, that represent the model components, wherein at least some of the executable elements comply with standards of a domain or a platform, and wherein the domain or platform comprises CORBA, CORBA-RT, Advanced Architecture Description Language (AADL), AUTOSAR, Software Communication Architecture (SCA) as defined by the Department of Defense, or one or more derivatives of any one of the above; generate an executable model in the graphical modeling environment, the executable model comprising executable elements and corresponding to the model that describes the software or system; and update: the model that describes the software or system based on changes made to the executable model, or the executable model based on changes made to the model that describes the software or system. 20. The system of claim 15 , wherein the executable model elements comprise hierarchical functional blocks. | 0.878959 |
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