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9,904,679 | 11 | 17 | 11. A non-transitory computer-readable medium comprising computer program instructions, the computer program instructions when executed by a processor of a computer device causes the processor to perform the steps including: determining a source language for an item of user-generated content; determining language competency information for a viewing user of the item of user-generated content, wherein determining the language competency information comprises: determining, in a social network system, a number of users connected to the viewing user that are competent in a language based on language competency information for the users connected to the viewing user; determining whether the determined number is greater than a threshold; and responsive to determining that the determined number is greater than the threshold, determining that the viewing user is competent in the language; determining whether the language competency information determined for the viewing user indicates a match for the determined source language; upon a determination that the language competency information for the viewing user indicates a match for the determined source language and indicates that the viewing user's primary language is different from the source language, providing for display an option to vote on one or more previously obtained machine-generated translations of the user-generated content into the primary language; receiving a vote from the viewing user on the one or more translations based on the quality of the translations; and providing for display one of the one or more translations to a subsequent viewer of the item of user-generated content based on the received vote. | 11. A non-transitory computer-readable medium comprising computer program instructions, the computer program instructions when executed by a processor of a computer device causes the processor to perform the steps including: determining a source language for an item of user-generated content; determining language competency information for a viewing user of the item of user-generated content, wherein determining the language competency information comprises: determining, in a social network system, a number of users connected to the viewing user that are competent in a language based on language competency information for the users connected to the viewing user; determining whether the determined number is greater than a threshold; and responsive to determining that the determined number is greater than the threshold, determining that the viewing user is competent in the language; determining whether the language competency information determined for the viewing user indicates a match for the determined source language; upon a determination that the language competency information for the viewing user indicates a match for the determined source language and indicates that the viewing user's primary language is different from the source language, providing for display an option to vote on one or more previously obtained machine-generated translations of the user-generated content into the primary language; receiving a vote from the viewing user on the one or more translations based on the quality of the translations; and providing for display one of the one or more translations to a subsequent viewer of the item of user-generated content based on the received vote. 17. The non-transitory computer-readable storage medium of claim 11 , further comprising determining a quality rating for a translation of the one or more previously obtained translations based at least in part on the received vote. | 0.56391 |
9,268,455 | 1 | 3 | 1. A method for user controlled multi-dimensional navigation of multimedia data, comprising: generating or extracting a multiplicity of node elements out of multimedia data to be registered, a node element comprising one or more extracted search terms, generated search terms or weighting terms that can be logically combined; determining a relevance index parameter for each multimedia data element to be registered for each paired combination of node elements and that is allocated to the respective pair of node elements; determining, in dependence on the relevance index parameters, one- or multi-dimensional distance factors, the absolute value of the corresponding distance factor becoming smaller with increasing relevance of two paired multimedia data elements with respect to one another; generating and graphically displaying, on the basis of at least one of the registered multimedia data elements or node elements, a topological navigation map in dependence on the respective one- or multi-dimensional distance factors; and wherein the topological navigation map is navigable through use of an input device to permit user access to at least one of desired multimedia data elements and node elements, wherein following user-specific selection of at least one of an initiating node element and multimedia data element and produced clusters of node elements and multimedia data elements, the topological navigation map is corrected in a perspective of at least three-dimensions with respect to at least one of the initiating node element and multimedia data element and clusters, and displayed accessible to the user, the topological navigation map displays a dynamic and moveable at least three-dimensional perspective for user navigation therethrough in order to respond in real-time by displaying changes in the distance factors of the relevance index parameters indicative of changes in said relevance of two paired multimedia data elements with respect to one another. | 1. A method for user controlled multi-dimensional navigation of multimedia data, comprising: generating or extracting a multiplicity of node elements out of multimedia data to be registered, a node element comprising one or more extracted search terms, generated search terms or weighting terms that can be logically combined; determining a relevance index parameter for each multimedia data element to be registered for each paired combination of node elements and that is allocated to the respective pair of node elements; determining, in dependence on the relevance index parameters, one- or multi-dimensional distance factors, the absolute value of the corresponding distance factor becoming smaller with increasing relevance of two paired multimedia data elements with respect to one another; generating and graphically displaying, on the basis of at least one of the registered multimedia data elements or node elements, a topological navigation map in dependence on the respective one- or multi-dimensional distance factors; and wherein the topological navigation map is navigable through use of an input device to permit user access to at least one of desired multimedia data elements and node elements, wherein following user-specific selection of at least one of an initiating node element and multimedia data element and produced clusters of node elements and multimedia data elements, the topological navigation map is corrected in a perspective of at least three-dimensions with respect to at least one of the initiating node element and multimedia data element and clusters, and displayed accessible to the user, the topological navigation map displays a dynamic and moveable at least three-dimensional perspective for user navigation therethrough in order to respond in real-time by displaying changes in the distance factors of the relevance index parameters indicative of changes in said relevance of two paired multimedia data elements with respect to one another. 3. The method as claimed in claim 1 , wherein the distance factors are determined by a spring model module. | 0.96203 |
8,321,219 | 17 | 19 | 17. A speech recognition method comprising: initiating, by a computer system, a state of a computer program; selecting, by the computer system, a state recognition set based on the state of the computer program; detecting, by the computer system a gesture of at least one part of a human body; receiving, by the computer system, a speech input signal; and recognizing, by the computer system, the speech input signal in the context of a recognition set, the recognition set being a subset of the state recognition set, the recognizing resulting in a first recognition result; weighting, by the computer system, the first recognition result according to a function associated with the gesture; and determining, by the computer system, a second recognition result based on the weighting. | 17. A speech recognition method comprising: initiating, by a computer system, a state of a computer program; selecting, by the computer system, a state recognition set based on the state of the computer program; detecting, by the computer system a gesture of at least one part of a human body; receiving, by the computer system, a speech input signal; and recognizing, by the computer system, the speech input signal in the context of a recognition set, the recognition set being a subset of the state recognition set, the recognizing resulting in a first recognition result; weighting, by the computer system, the first recognition result according to a function associated with the gesture; and determining, by the computer system, a second recognition result based on the weighting. 19. The method of claim 17 wherein the gesture is a hand gesture, wherein the step of detecting the gesture includes detecting a portion of a human hand. | 0.833333 |
9,519,714 | 1 | 2 | 1. A system comprising a memory comprising instructions for execution by one or more processors, the one or more processors being coupled to the memory and operable to execute the instructions to: identify by a query classifier that a user query comprises a query list intent, wherein the query list intent indicates an intent to view one or more webpages including at least one list, wherein the at least one list is at least a portion of at least one of the one or more webpages that includes one or more of a list, a collection of items, a set of items, or a table; identify by a result identifier a plurality of search results that are relevant to the user query, wherein the plurality of search results comprises the one or more webpages including the at least one list and one or more webpages that do not include the at least one list; identify by a list identifier and a relevancy determiner a first list exceeding a predetermined level of relevance from within each of the one or more webpages including the at least one list; select by a preview selector one or more items from the first list exceeding the predetermined level of relevance to include in a list preview within a search results page, where the list preview is associated with the first list exceeding the predetermined level of relevance and is provided for each of the one or more webpages including the at least one list; select by the preview selector one or more list attributes corresponding to the list preview, wherein the one or more list attributes identifies, for the list preview, a total number of items within the first list exceeding the predetermined level of relevance associated with the list preview; and provide by a result presenter on the search results page each of (1) the one or more webpages including the at least one list, (2) the one or more webpages that do not include the at least one list, (3) the list preview that is automatically provided in the search results page for each of the one or more webpages including the at least one list, and (4) the one or more list attributes corresponding to the first list exceeding the predetermined level of relevance. | 1. A system comprising a memory comprising instructions for execution by one or more processors, the one or more processors being coupled to the memory and operable to execute the instructions to: identify by a query classifier that a user query comprises a query list intent, wherein the query list intent indicates an intent to view one or more webpages including at least one list, wherein the at least one list is at least a portion of at least one of the one or more webpages that includes one or more of a list, a collection of items, a set of items, or a table; identify by a result identifier a plurality of search results that are relevant to the user query, wherein the plurality of search results comprises the one or more webpages including the at least one list and one or more webpages that do not include the at least one list; identify by a list identifier and a relevancy determiner a first list exceeding a predetermined level of relevance from within each of the one or more webpages including the at least one list; select by a preview selector one or more items from the first list exceeding the predetermined level of relevance to include in a list preview within a search results page, where the list preview is associated with the first list exceeding the predetermined level of relevance and is provided for each of the one or more webpages including the at least one list; select by the preview selector one or more list attributes corresponding to the list preview, wherein the one or more list attributes identifies, for the list preview, a total number of items within the first list exceeding the predetermined level of relevance associated with the list preview; and provide by a result presenter on the search results page each of (1) the one or more webpages including the at least one list, (2) the one or more webpages that do not include the at least one list, (3) the list preview that is automatically provided in the search results page for each of the one or more webpages including the at least one list, and (4) the one or more list attributes corresponding to the first list exceeding the predetermined level of relevance. 2. The system of claim 1 , wherein the at least one list comprises a collection of items related to a particular subject matter. | 0.769784 |
9,323,738 | 13 | 17 | 13. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions which, when executed by a processor a device, cause the processor to: receive information identifying a first phrase in a document as being geographically significant, the first phrase being identified as geographically significant based on previous occurrences of the first phrase being determined to be statistically significant to first geographic information; receive information identifying a second phrase in the document as being geographically significant, the second phrase being identified as geographically significant based on previous occurrences of the second phrase being determined to be statistically significant to second geographic information; determine that the first phrase is associated with a first plurality of geographic areas; determine that the second phrase is associated with a second plurality of geographic areas; determine that a geographic area of the first plurality of geographic areas matches a geographic area of the second plurality of geographic areas; associate, based on determining that the geographic area of the first plurality of geographic areas matches the geographic area of the second plurality of geographic areas, the document with a particular geographic area, the particular geographic area corresponding to the geographic area of the first plurality of geographic areas and the geographic area of the second plurality of geographic areas; store information indicating the association of the document with the particular geographic area, the stored information permitting a determination to be made that the document is related to the particular geographic area; generate, based on located geographic information associated with a phrase in a respective document, a histogram for the phrase; and store the generated histogram. | 13. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions which, when executed by a processor a device, cause the processor to: receive information identifying a first phrase in a document as being geographically significant, the first phrase being identified as geographically significant based on previous occurrences of the first phrase being determined to be statistically significant to first geographic information; receive information identifying a second phrase in the document as being geographically significant, the second phrase being identified as geographically significant based on previous occurrences of the second phrase being determined to be statistically significant to second geographic information; determine that the first phrase is associated with a first plurality of geographic areas; determine that the second phrase is associated with a second plurality of geographic areas; determine that a geographic area of the first plurality of geographic areas matches a geographic area of the second plurality of geographic areas; associate, based on determining that the geographic area of the first plurality of geographic areas matches the geographic area of the second plurality of geographic areas, the document with a particular geographic area, the particular geographic area corresponding to the geographic area of the first plurality of geographic areas and the geographic area of the second plurality of geographic areas; store information indicating the association of the document with the particular geographic area, the stored information permitting a determination to be made that the document is related to the particular geographic area; generate, based on located geographic information associated with a phrase in a respective document, a histogram for the phrase; and store the generated histogram. 17. The non-transitory computer-readable medium of claim 13 , where the document is a search query and the instructions further include: one or more instructions to perform a search of documents associated with the particular geographic area using the search query. | 0.71688 |
9,239,862 | 27 | 34 | 27. A method of operating a target user equipment (UE), comprising: receiving a crowd-sourced hints list from a hints server to assist the target UE to perform an initial load of a web page, the crowd-sourced hints list listing one or more hints generated by one or more other UEs based upon web page resource information acquired from a web server by the one or more other UEs that is required to load the web page at the one or more other UEs; obtaining the web page resource information for the web page based on the crowd-sourced hints list without interacting with the web server to acquire the web page resource information; and loading the web page using the web page resource information that is obtained based on the crowd-sourced hints list. | 27. A method of operating a target user equipment (UE), comprising: receiving a crowd-sourced hints list from a hints server to assist the target UE to perform an initial load of a web page, the crowd-sourced hints list listing one or more hints generated by one or more other UEs based upon web page resource information acquired from a web server by the one or more other UEs that is required to load the web page at the one or more other UEs; obtaining the web page resource information for the web page based on the crowd-sourced hints list without interacting with the web server to acquire the web page resource information; and loading the web page using the web page resource information that is obtained based on the crowd-sourced hints list. 34. The method of claim 27 , wherein the crowd-sourced hints list is refined by the hints server based on UE-specific hint list criteria for the target UE. | 0.853774 |
8,046,739 | 1 | 7 | 1. A non-transitory, computer readable memory medium comprising program instructions for creating a graphical program, wherein the program instructions are executable to: display a function block in a graphical program, wherein the function block is configured to perform a first function, wherein the function block comprises one or more inputs and one or more outputs, and wherein the graphical program comprises a first plurality of interconnected blocks which visually indicate the functionality of the graphical program; receive user input selecting the function block to configure the function block; receive user input assembling a second graphical program that visually specifies calculation of attributes of the one or more outputs based on attributes of the one or more inputs, wherein the second graphical program comprises a second plurality of interconnected blocks which visually indicate the calculation of the attributes of the one or more outputs, wherein said receiving user input assembling is performed in response to the user input selecting the function block. | 1. A non-transitory, computer readable memory medium comprising program instructions for creating a graphical program, wherein the program instructions are executable to: display a function block in a graphical program, wherein the function block is configured to perform a first function, wherein the function block comprises one or more inputs and one or more outputs, and wherein the graphical program comprises a first plurality of interconnected blocks which visually indicate the functionality of the graphical program; receive user input selecting the function block to configure the function block; receive user input assembling a second graphical program that visually specifies calculation of attributes of the one or more outputs based on attributes of the one or more inputs, wherein the second graphical program comprises a second plurality of interconnected blocks which visually indicate the calculation of the attributes of the one or more outputs, wherein said receiving user input assembling is performed in response to the user input selecting the function block. 7. The non-transitory, computer readable memory medium of claim 1 , wherein the attributes of the one or more inputs and/or the attributes of at the one or more outputs comprises one or more of: one or more data types; one or more offsets; bit or byte width; one or more maximum values; one or more minimum values; one or more word lengths; one or more fractional word lengths; one or more integer word lengths; one or more representations; or one or more scaling factors. | 0.647235 |
8,959,103 | 11 | 12 | 11. The method of claim 10 , wherein adjusting the skip count for the query term reordering rule comprises incrementing the skip count for the query term reordering rule, and wherein the method comprises assigning a score to the query term reordering rule based on a click count and the skip count. | 11. The method of claim 10 , wherein adjusting the skip count for the query term reordering rule comprises incrementing the skip count for the query term reordering rule, and wherein the method comprises assigning a score to the query term reordering rule based on a click count and the skip count. 12. The method of claim 11 , wherein the score assigned to the query term reordering rule is based on a ratio of (i) the click count to (ii) the click count and the skip count. | 0.933333 |
8,595,006 | 1 | 5 | 1. A speech recognition method implemented in a computer, comprising: receiving a speech input in a first noise environment which comprises a sequence of observations; determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, comprising: providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognise speech in a second noise environment, said model having a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation; adapting the model trained in the second environment to that of the first environment; the speech recognition method further comprising determining the likelihood of a sequence of observations occurring in a given language using a language model; combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein adapting the model trained in the second environment to that of the first environment comprises: adapting the model parameters of the model trained in the second noise environment to those of the first noise environment using transform parameters to produce a target distribution, wherein the transform parameters have a block diagonal form and are regression class dependent, each regression class comprising a plurality of probability distributions; mimicking the target distribution using a linear regression type distribution, said linear regression type distribution comprising mimicked transform parameters; and estimating the mimicked transformed parameters. | 1. A speech recognition method implemented in a computer, comprising: receiving a speech input in a first noise environment which comprises a sequence of observations; determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, comprising: providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognise speech in a second noise environment, said model having a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation; adapting the model trained in the second environment to that of the first environment; the speech recognition method further comprising determining the likelihood of a sequence of observations occurring in a given language using a language model; combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein adapting the model trained in the second environment to that of the first environment comprises: adapting the model parameters of the model trained in the second noise environment to those of the first noise environment using transform parameters to produce a target distribution, wherein the transform parameters have a block diagonal form and are regression class dependent, each regression class comprising a plurality of probability distributions; mimicking the target distribution using a linear regression type distribution, said linear regression type distribution comprising mimicked transform parameters; and estimating the mimicked transformed parameters. 5. The speech recognition method of claim 1 , wherein the target distribution comprises a mean and covariance, and said covariance in the target distribution is diagonalised when determining the mimicked transform parameters. | 0.897354 |
9,313,153 | 20 | 22 | 20. An apparatus for dynamic message routing between publishing nodes and subscribing nodes sent throughout a network without regard to how a topology of the network changes, the apparatus comprising: a processor; and a memory, coupled to the processor, having code and data stored therein, wherein the code is executable by the processor to transform the apparatus into a machine to: receive a plurality of subscription requests at a plurality of brokers; consolidate the received plurality of subscription requests; determining whether to propagate the consolidated subscriptions requests; receive the message and a topic at a broker via a network; identify one or more subscribers for the topic received; obtain up-to-date network path configuration information; reconfigure broker network path information based on revisions to the network path configuration information to determine a path for sending the message via the network, including performing real-time adjustment of the path; and sending the message to the identified subscribers; wherein to perform real-time adjustment of the path comprises to: monitor changes to the topology of the network; determine in real-time whether any connections within the network are unavailable to dynamically maintain subscriptions; and automatically calculate a path for any subscribers affected by any unavailable connections. | 20. An apparatus for dynamic message routing between publishing nodes and subscribing nodes sent throughout a network without regard to how a topology of the network changes, the apparatus comprising: a processor; and a memory, coupled to the processor, having code and data stored therein, wherein the code is executable by the processor to transform the apparatus into a machine to: receive a plurality of subscription requests at a plurality of brokers; consolidate the received plurality of subscription requests; determining whether to propagate the consolidated subscriptions requests; receive the message and a topic at a broker via a network; identify one or more subscribers for the topic received; obtain up-to-date network path configuration information; reconfigure broker network path information based on revisions to the network path configuration information to determine a path for sending the message via the network, including performing real-time adjustment of the path; and sending the message to the identified subscribers; wherein to perform real-time adjustment of the path comprises to: monitor changes to the topology of the network; determine in real-time whether any connections within the network are unavailable to dynamically maintain subscriptions; and automatically calculate a path for any subscribers affected by any unavailable connections. 22. The apparatus of claim 20 , wherein to identify one or more subscribers is performed by comparing the topic to names in a topic/node table. | 0.834873 |
8,239,758 | 7 | 8 | 7. The computer program product of claim 5 further including program instructions for truncating each of the character strings to generate a display list of unique truncated character strings. | 7. The computer program product of claim 5 further including program instructions for truncating each of the character strings to generate a display list of unique truncated character strings. 8. The computer program product of claim 7 wherein determining the truncation location further includes determining the truncation location at the start of the string or at the end of the string or in between, to generate a display list of truncated character strings where each truncated string is unique in relation to other truncated strings in the list. | 0.864875 |
9,465,862 | 1 | 5 | 1. A method for integrating query categories, comprising: executing, at a computer, a reductionist module on a search query to extract a core term from the search query, the core term used to search a hash table that maps core terms to corresponding categories; deriving a first result comprising at least one of the categories from the search of the hash table; executing at the computer an enrichment module on the search query to yield a second result, the enrichment module including searching an index of terms that are mapped to documents and corresponding categories in the index, the second result indicative of one of the corresponding categories in the index based on a probability score; upon determining the core term is present in the hash table, calculating a weighted average for corresponding values of the first result and the second result based on training data acquired from the execution of the reductionist module and the execution of the enrichment module, the calculated weighted average stored in a memory device; and upon determining the core term from the search query is not listed in the hash table, and upon determining the probability score of the one of the corresponding categories in the index for the second result meets a minimum defined confidence value, inserting and storing the core term and the one of the corresponding categories in the hash table and mapping the core term to the one of the corresponding categories in the hash table. | 1. A method for integrating query categories, comprising: executing, at a computer, a reductionist module on a search query to extract a core term from the search query, the core term used to search a hash table that maps core terms to corresponding categories; deriving a first result comprising at least one of the categories from the search of the hash table; executing at the computer an enrichment module on the search query to yield a second result, the enrichment module including searching an index of terms that are mapped to documents and corresponding categories in the index, the second result indicative of one of the corresponding categories in the index based on a probability score; upon determining the core term is present in the hash table, calculating a weighted average for corresponding values of the first result and the second result based on training data acquired from the execution of the reductionist module and the execution of the enrichment module, the calculated weighted average stored in a memory device; and upon determining the core term from the search query is not listed in the hash table, and upon determining the probability score of the one of the corresponding categories in the index for the second result meets a minimum defined confidence value, inserting and storing the core term and the one of the corresponding categories in the hash table and mapping the core term to the one of the corresponding categories in the hash table. 5. The method of claim 1 , wherein the weighted average is applied equally to the first result and the second result based on training data derived from the execution of the reductionist module and the execution of the enrichment module. | 0.738411 |
8,705,863 | 5 | 6 | 5. The system of claim 4 wherein the input receiving component is configured for receiving an indication selecting the I/O layout document view as a third design document view, and wherein the matching component is configured for comparing text in the first design document view to text in the third design document view and, when a substantial match is determined, for identifying the plurality of devices associated with the slot into which the control module is mounted and for identifying which device is associated with each control point of the control module. | 5. The system of claim 4 wherein the input receiving component is configured for receiving an indication selecting the I/O layout document view as a third design document view, and wherein the matching component is configured for comparing text in the first design document view to text in the third design document view and, when a substantial match is determined, for identifying the plurality of devices associated with the slot into which the control module is mounted and for identifying which device is associated with each control point of the control module. 6. The system of claim 5 wherein the at least three design document views further includes an overview schematic document view corresponding to a design layout of the automated system, wherein the overview schematic document view includes design data identifying each device of the plurality of devices and a location associated with each device. | 0.912802 |
8,200,663 | 15 | 19 | 15. A method of rating review items associated with a reference item based upon voting, comprising: opening a voting session; presenting a simultaneous comparison of two or more review items to a voter when determining that an unranked review item is associated with a reference item; presenting the reference item to the voter; obtaining a relevancy preference indication from the voter; closing the voting session; and rating relevance of the review items to the reference item based on an outcome of one or more voting sessions. | 15. A method of rating review items associated with a reference item based upon voting, comprising: opening a voting session; presenting a simultaneous comparison of two or more review items to a voter when determining that an unranked review item is associated with a reference item; presenting the reference item to the voter; obtaining a relevancy preference indication from the voter; closing the voting session; and rating relevance of the review items to the reference item based on an outcome of one or more voting sessions. 19. The method of claim 15 , wherein the reference item is one or more of a search query, a web page, an advertisement, a search resource, a category, a location, and a profile. | 0.832386 |
7,716,532 | 19 | 20 | 19. A system for optimizing contacts between one or more parties, comprising: means for determining one or more expected utilities associated with the contacts based, at least in part, on data associated with one or more contactors, data associated with one or more contactees, and data associated with one or more communication channels, wherein the data associated with the communication channels comprises at least reliability data; means for generating a probability that the contacts between one or more parties will be completed with predetermined desired transmission qualities; means for updating one or more pieces of information that are employed in selecting the communication channels for communication and updating the expected utility that is computed without regard to the reliability data; and means for establishing the contact based upon maximizing the expected utility. | 19. A system for optimizing contacts between one or more parties, comprising: means for determining one or more expected utilities associated with the contacts based, at least in part, on data associated with one or more contactors, data associated with one or more contactees, and data associated with one or more communication channels, wherein the data associated with the communication channels comprises at least reliability data; means for generating a probability that the contacts between one or more parties will be completed with predetermined desired transmission qualities; means for updating one or more pieces of information that are employed in selecting the communication channels for communication and updating the expected utility that is computed without regard to the reliability data; and means for establishing the contact based upon maximizing the expected utility. 20. The system of claim 19 , further comprising: means for applying one or more inference formulae to infer probabilities associated with: one or more pieces of data associated with a contactor, one or more pieces of data associated with a contactee, and one or more pieces of data associated with a communication channel. | 0.613909 |
9,507,824 | 1 | 3 | 1. A method implemented on a computer system, the method comprising, the computer system: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. | 1. A method implemented on a computer system, the method comprising, the computer system: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. 3. The method of claim 1 , wherein creating a profile for the each column further comprises: computing an estimated cardinality of the each column based on the set of m observables included in the profile for the each column; and including the estimated cardinality of the each column in the profile for the each column. | 0.759398 |
9,805,713 | 3 | 5 | 3. The method of claim 1 , wherein determining the score corresponding to the candidate transcription in the particular context comprises: identifying features in the language model that correspond to different words or phrases occurring in the particular context; and accessing scores in the language model for the identified features. | 3. The method of claim 1 , wherein determining the score corresponding to the candidate transcription in the particular context comprises: identifying features in the language model that correspond to different words or phrases occurring in the particular context; and accessing scores in the language model for the identified features. 5. The method of claim 3 , wherein determining the score corresponding to the candidate transcription in the particular context further comprises: identifying the minimum score from among the accessed scores for the identified features; and determining the score corresponding to the candidate transcription in the particular context based on the identified minimum score. | 0.911513 |
9,495,542 | 10 | 13 | 10. A non-transient computer program product comprising computer code for execution on a host computer processor, the computer code for implementing a method of scanning an item of target code prepared from a program written in a programming language having a security specification, the method employing a model checking system, the code comprising: computer code for receiving the item of target code, the target code comprising an item of executable binary code; code for preparing a data structure corresponding to the item target code by parsing the target code to extract executable elements; code for providing a language definition file corresponding to the programming language, the language definition file comprising rules defining the format of instructions in the programming language; code for providing a static model corresponding to the programming language, the static model comprising rules defined from the security specification of the programming language; code for creating a composite model of the target code by supplementing the data structure with information from the language definition file, and with information from the static model, the composite model having a format for processing by the model checking system; code for segmenting the composite model into a plurality of segments including at least a first segment; and code for changing a distribution of instructions among the segments by, for each segment after the first segment, assessing at least the first instruction in each segment, and moving the at least first instruction to an immediately preceding segment if that at least first instruction is not a transfer instruction; code for providing the composite model to the model checker; code for engaging the model checker to analyze the composite model, the code for engaging the model checker comprising: code for analyzing each of the plurality of segments individually; and code for analyzing boundaries of the segments; the model checker producing a result; and code for generating an output based on the result produced by the model checker, the output indicating a measure of whether the model checker identified an indication that the target contains malware. | 10. A non-transient computer program product comprising computer code for execution on a host computer processor, the computer code for implementing a method of scanning an item of target code prepared from a program written in a programming language having a security specification, the method employing a model checking system, the code comprising: computer code for receiving the item of target code, the target code comprising an item of executable binary code; code for preparing a data structure corresponding to the item target code by parsing the target code to extract executable elements; code for providing a language definition file corresponding to the programming language, the language definition file comprising rules defining the format of instructions in the programming language; code for providing a static model corresponding to the programming language, the static model comprising rules defined from the security specification of the programming language; code for creating a composite model of the target code by supplementing the data structure with information from the language definition file, and with information from the static model, the composite model having a format for processing by the model checking system; code for segmenting the composite model into a plurality of segments including at least a first segment; and code for changing a distribution of instructions among the segments by, for each segment after the first segment, assessing at least the first instruction in each segment, and moving the at least first instruction to an immediately preceding segment if that at least first instruction is not a transfer instruction; code for providing the composite model to the model checker; code for engaging the model checker to analyze the composite model, the code for engaging the model checker comprising: code for analyzing each of the plurality of segments individually; and code for analyzing boundaries of the segments; the model checker producing a result; and code for generating an output based on the result produced by the model checker, the output indicating a measure of whether the model checker identified an indication that the target contains malware. 13. The non-transient computer program product according to claim 10 , wherein the code for analyzing each of the plurality of segments individually comprises code for analyzing each of the segments in parallel using a plurality of model checking systems. | 0.855114 |
8,650,484 | 1 | 14 | 1. A computer implemented method comprising: presenting a first editing context within a graphical user interface, the first editing context comprising a set of one or more objects that can be edited within the first editing context; receiving a request to edit an item associated with a first object, wherein editing the item associated with the first object occurs in a second editing context different from the first editing context; in response to the request, entering the second editing context wherein only items associated with the first object are accessible for editing, wherein a second object is not accessible for editing while in the second editing context; and while in the second editing context, associating the second object with the first object, wherein associating the second object with the first object changes the second object to be accessible for editing while in the second editing context; wherein, while in the second editing context, objects not accessible for editing are distinguished from the items that are editable in the second editing context. | 1. A computer implemented method comprising: presenting a first editing context within a graphical user interface, the first editing context comprising a set of one or more objects that can be edited within the first editing context; receiving a request to edit an item associated with a first object, wherein editing the item associated with the first object occurs in a second editing context different from the first editing context; in response to the request, entering the second editing context wherein only items associated with the first object are accessible for editing, wherein a second object is not accessible for editing while in the second editing context; and while in the second editing context, associating the second object with the first object, wherein associating the second object with the first object changes the second object to be accessible for editing while in the second editing context; wherein, while in the second editing context, objects not accessible for editing are distinguished from the items that are editable in the second editing context. 14. The method of claim 1 , wherein, in the second editing context, layers of the first object are accessible for editing. | 0.808777 |
10,147,036 | 16 | 17 | 16. The information handling system of claim 12 , wherein the set of instructions are executable to sort vectors V′k+1, . . . , V′k+b from the first concept vector set to identify one or more additional disruptive concepts based on a computed cosine distance from high to low to a normalized sum of vectors (VL 1 + . . . +VLh) from the second concept vector set. | 16. The information handling system of claim 12 , wherein the set of instructions are executable to sort vectors V′k+1, . . . , V′k+b from the first concept vector set to identify one or more additional disruptive concepts based on a computed cosine distance from high to low to a normalized sum of vectors (VL 1 + . . . +VLh) from the second concept vector set. 17. The information handling system of claim 16 , wherein the set of instructions are executable to generate a list of R 1 new concepts corresponding to R 1 sorted vectors V′k+1, . . . , V′k+b. | 0.949291 |
6,157,905 | 28 | 35 | 28. A method in a computer system for transforming a sequence of source values representing text into a sequence of target values that characterizes the sequence of source values in a manner useful for n-gram analysis techniques, the method comprising the steps of: for each distinct source value occurring in the sequence of source values, identifying a single target value corresponding to the distinct source value, such that target value corresponds to one or more distinct source values and at least one target value corresponds to two or more distinct source values; for each occurrence of the distinct source value in the sequence of source values, writing the target value identified as corresponding to the distinct source value to a position in the sequence of target values corresponding to the position of the occurrence of the distinct source value in the sequence of source values; and subjecting the sequence of target values to an n-gram analysis technique in order to analyze the representation of text constituted by the sequence of source values. | 28. A method in a computer system for transforming a sequence of source values representing text into a sequence of target values that characterizes the sequence of source values in a manner useful for n-gram analysis techniques, the method comprising the steps of: for each distinct source value occurring in the sequence of source values, identifying a single target value corresponding to the distinct source value, such that target value corresponds to one or more distinct source values and at least one target value corresponds to two or more distinct source values; for each occurrence of the distinct source value in the sequence of source values, writing the target value identified as corresponding to the distinct source value to a position in the sequence of target values corresponding to the position of the occurrence of the distinct source value in the sequence of source values; and subjecting the sequence of target values to an n-gram analysis technique in order to analyze the representation of text constituted by the sequence of source values. 35. The method of claim 28 wherein a portion of the distinct source values among the sequence of source values represent letters, and wherein a portion of the distinct source values among the sequence of source values represent extended characters, and wherein the identifying step includes the steps of: for each distinct letter, identifying a single target value associated with the distinct letter as corresponding to any distinct source values representing the distinct letter; for each distinct extended character, identifying a single target value associated with the distinct extended character as corresponding to any distinct source values representing the distinct extended character; and identifying a single target value as corresponding to any distinct source values representing neither a letter nor an extended character. | 0.649034 |
9,542,381 | 17 | 18 | 17. The non-transitory computer-readable medium of claim 16 , wherein the quality of the resulting translation is based on a BLEU score of the resulting translation and a number of emergency sentences. | 17. The non-transitory computer-readable medium of claim 16 , wherein the quality of the resulting translation is based on a BLEU score of the resulting translation and a number of emergency sentences. 18. The non-transitory computer-readable medium of claim 17 , wherein the emergency sentences comprise at least one sentence that is generated during an emergency mode, wherein the emergency mode is automatically engaged if the NLC system encounters an error during translation. | 0.916617 |
8,423,366 | 8 | 9 | 8. The method of claim 1 , wherein the voicemail is received by the system from a first application, the method further comprising: receiving, by the system, a textual message from a second application; identifying, by the system, an identifier of the user based on the textual message; selecting, by the system, the speech synthesis voice associated with the user based on the identifier; and synthesizing, by the system, an audio sample of the textual message being spoken using the speech synthesis voice associated with the user. | 8. The method of claim 1 , wherein the voicemail is received by the system from a first application, the method further comprising: receiving, by the system, a textual message from a second application; identifying, by the system, an identifier of the user based on the textual message; selecting, by the system, the speech synthesis voice associated with the user based on the identifier; and synthesizing, by the system, an audio sample of the textual message being spoken using the speech synthesis voice associated with the user. 9. The method of claim 8 , wherein synthesizing the audio sample of the textual message being spoken comprises inputting the speech synthesis voice associated with the user and the textual message into a text-to-speech system and outputting from the text-to-speech system the audio sample of the textual message being spoken. | 0.916409 |
10,121,465 | 14 | 18 | 14. A system comprising: one or more processors; memory; and computer-executable instructions stored in the memory that, when executed by the one or more processors, causes the one or more processors to perform acts comprising: receiving input audio data captured via a microphone at a first device, the input audio data representing a voice command; and transmitting output audio data to the first device, the output audio data representing at least a query result and an audio indication that visual content that is associated with the query result is to be presented via a second device that is associated with first device. | 14. A system comprising: one or more processors; memory; and computer-executable instructions stored in the memory that, when executed by the one or more processors, causes the one or more processors to perform acts comprising: receiving input audio data captured via a microphone at a first device, the input audio data representing a voice command; and transmitting output audio data to the first device, the output audio data representing at least a query result and an audio indication that visual content that is associated with the query result is to be presented via a second device that is associated with first device. 18. The system as recited in claim 14 , wherein the output audio data further represents: a summary of the visual content; and additional content related to the visual content. | 0.6 |
8,041,699 | 9 | 21 | 9. A method for retrieving information from databases, said databases being structured or unstructured, said databases being homogeneous or heterogeneous, wherein retrieval is performed through visual queries on dynamic taxonomies, said dynamic taxonomies being an organization of concepts that ranges from a most general concept to a most specific concept, said concepts and their organization being called an intension, items in said databases being classified under one or more concepts, said items and their classification being called an extension, said method comprising, given an initial current subset of interest: using a computer for providing a reduced taxonomy for the current subset of interest; using the computer for refining the current subset of interest of said reduced taxonomy with the combination of one or more taxonomy concepts through Boolean operations; and using the computer for iteratively repeating said steps of providing a reduced taxonomy for the current subset of interest to further refine said retrieval and of refining the current subset of interest, wherein: said initial subset of interest includes all the items in the extension of the dynamic taxonomy or a subset of them; said reduced taxonomy being derived from said taxonomy by using the computer for pruning concepts under which no item in said current subset of interest is classified; said step of pruning concepts includes eliminating from the taxonomy all the concepts under which no item in the current subset of interest is classified, or preventing said concepts from being displayed, or preventing said concepts from being selected in order to refine interest sets; said step of providing a reduced taxonomy either reports only the concepts belonging to the reduced taxonomy or, for each such concept also reports how many items in the current interest set are classified under the concept; said intension is organized as a hierarchy of concepts or as a directed acyclic graph of concepts, thereby allowing a concept to have multiple fathers; in said extension, there exists at least one item such that said item is classified under at least two different concepts such that each of said two concepts is neither an ancestor nor a descendant of the other concept in the intension. | 9. A method for retrieving information from databases, said databases being structured or unstructured, said databases being homogeneous or heterogeneous, wherein retrieval is performed through visual queries on dynamic taxonomies, said dynamic taxonomies being an organization of concepts that ranges from a most general concept to a most specific concept, said concepts and their organization being called an intension, items in said databases being classified under one or more concepts, said items and their classification being called an extension, said method comprising, given an initial current subset of interest: using a computer for providing a reduced taxonomy for the current subset of interest; using the computer for refining the current subset of interest of said reduced taxonomy with the combination of one or more taxonomy concepts through Boolean operations; and using the computer for iteratively repeating said steps of providing a reduced taxonomy for the current subset of interest to further refine said retrieval and of refining the current subset of interest, wherein: said initial subset of interest includes all the items in the extension of the dynamic taxonomy or a subset of them; said reduced taxonomy being derived from said taxonomy by using the computer for pruning concepts under which no item in said current subset of interest is classified; said step of pruning concepts includes eliminating from the taxonomy all the concepts under which no item in the current subset of interest is classified, or preventing said concepts from being displayed, or preventing said concepts from being selected in order to refine interest sets; said step of providing a reduced taxonomy either reports only the concepts belonging to the reduced taxonomy or, for each such concept also reports how many items in the current interest set are classified under the concept; said intension is organized as a hierarchy of concepts or as a directed acyclic graph of concepts, thereby allowing a concept to have multiple fathers; in said extension, there exists at least one item such that said item is classified under at least two different concepts such that each of said two concepts is neither an ancestor nor a descendant of the other concept in the intension. 21. The method of claim 9 , said method allowing tracking of user interests by keeping track of all the concepts used to define each focus, or selected subset of items. | 0.965275 |
8,880,537 | 5 | 6 | 5. A system for use of semantic understanding in searching and providing of content, comprising: a computer including a microprocessor; a syntactic parser or word tokenizer for data retrieval and parsing; a syntax to semantics transformational algebra-based semantic rule set; an associative database of linearized tuple conceptual graphs (TCG) which defines a plurality of tuple conceptual graphs (TCGs) corresponding to text data, ordered within branches of the TCG hierarchy so that those TCGs that are more specific are stored logically below TCGs that are less specific; an interface for allowing a user to input one or more additional data, or requests for new data, to be added to or matched against the associative database; wherein the system semantically interprets an original data, including an original Web page or other content, and uses a link grammar, rules, and algebra-based transformations to automatically populate the associative database with semantic links; and wherein when the one or more additional data or requests for new data is received, the system uses the information therein to one or more of modify the database or prepare a response to the request which includes semantically related web pages or content, or advertising, and which is then provided as, or in addition to, a response to the request. | 5. A system for use of semantic understanding in searching and providing of content, comprising: a computer including a microprocessor; a syntactic parser or word tokenizer for data retrieval and parsing; a syntax to semantics transformational algebra-based semantic rule set; an associative database of linearized tuple conceptual graphs (TCG) which defines a plurality of tuple conceptual graphs (TCGs) corresponding to text data, ordered within branches of the TCG hierarchy so that those TCGs that are more specific are stored logically below TCGs that are less specific; an interface for allowing a user to input one or more additional data, or requests for new data, to be added to or matched against the associative database; wherein the system semantically interprets an original data, including an original Web page or other content, and uses a link grammar, rules, and algebra-based transformations to automatically populate the associative database with semantic links; and wherein when the one or more additional data or requests for new data is received, the system uses the information therein to one or more of modify the database or prepare a response to the request which includes semantically related web pages or content, or advertising, and which is then provided as, or in addition to, a response to the request. 6. The system of claim 5 , wherein the content includes advertising categories. | 0.831197 |
8,694,303 | 3 | 4 | 3. The method of claim 1 , further comprising ranking the initial weighting values for two or more candidate translation units, wherein the ranking is based on a ranking of results of scoring functions for one or more pairs of candidate translation units. | 3. The method of claim 1 , further comprising ranking the initial weighting values for two or more candidate translation units, wherein the ranking is based on a ranking of results of scoring functions for one or more pairs of candidate translation units. 4. The method of claim 3 , wherein the ranking is applied to translation parameters of the sampled candidate translation units. | 0.924941 |
9,355,272 | 1 | 6 | 1. A computing system comprising: a control unit including processor configured to: determine a sharing context for representing a scenario surrounding sharing of a content; determine a user's past sharing selection for the sharing context, wherein the user's past sharing selection is for representing prior sharing of previous information similar to the content or associated with same instance of the sharing context; calculate a personalization degree for representing a match between a current personalization setting and the sharing context; generate a sharing option for the sharing context based on a default set for the sharing context, the user's past sharing selection for the sharing context, and the personalization degree for the sharing context; estimate a user's privacy preference based on the sharing option; and a memory, coupled to the control unit, configured to store the user's privacy preference. | 1. A computing system comprising: a control unit including processor configured to: determine a sharing context for representing a scenario surrounding sharing of a content; determine a user's past sharing selection for the sharing context, wherein the user's past sharing selection is for representing prior sharing of previous information similar to the content or associated with same instance of the sharing context; calculate a personalization degree for representing a match between a current personalization setting and the sharing context; generate a sharing option for the sharing context based on a default set for the sharing context, the user's past sharing selection for the sharing context, and the personalization degree for the sharing context; estimate a user's privacy preference based on the sharing option; and a memory, coupled to the control unit, configured to store the user's privacy preference. 6. The system as claimed in claim 1 wherein the control unit is configured to: provide a sharing set with the sharing option; and detect a user's past sharing selection different from the sharing set. | 0.819168 |
9,483,239 | 1 | 2 | 1. A method that facilitates development of a graphical user interface (GUI) for an executable application, the method comprising: providing a user interface design tool to design a user interface (UI) control of a GUI, the UI control having a multiple layer model referred to as an active design-time object model comprising, a base layer displays the UI control with runtime appearance and handling events for runtime actions, a border layer comprising a border design-time adjustment indicator, the border layer handles events for design-time actions to adjust design-time properties of the UI control, and an anchor layer comprising an anchor design-time adjustment indicator which serves as another design-time adjustment indicator, the anchor layer handles events which are defined to be handled by the anchor layer for design-time actions to adjust design-time properties of the UI control, wherein the anchor layer overlays the border layer and the border layer overlays the base layer, the layers are depicted as overlapping layers on a two-dimensional display, and wherein the UI control is presented on the base layer; and performing, by a user, a UI interaction, the UI interaction includes a performed event on the UI control, the performed event corresponds to one of the events, wherein in design-time, the performed event causes performance of a corresponding design-time action, and if the performed event occurs at the anchor design-time adjustment indicator, the anchor layer handles the performed event if the performed event is one of the events defined for the anchor layer, and the anchor layer passes the performed event to the border layer for handling if the performed event is not one of the events defined for the anchor layer, if the performed event occurs at the border design-time adjustment indicator, the border layer handles the performed event, and if the performed event occurs at the UI control other than the anchor and border design-time adjustment indicators, the base layer handles the performed event as if during runtime. | 1. A method that facilitates development of a graphical user interface (GUI) for an executable application, the method comprising: providing a user interface design tool to design a user interface (UI) control of a GUI, the UI control having a multiple layer model referred to as an active design-time object model comprising, a base layer displays the UI control with runtime appearance and handling events for runtime actions, a border layer comprising a border design-time adjustment indicator, the border layer handles events for design-time actions to adjust design-time properties of the UI control, and an anchor layer comprising an anchor design-time adjustment indicator which serves as another design-time adjustment indicator, the anchor layer handles events which are defined to be handled by the anchor layer for design-time actions to adjust design-time properties of the UI control, wherein the anchor layer overlays the border layer and the border layer overlays the base layer, the layers are depicted as overlapping layers on a two-dimensional display, and wherein the UI control is presented on the base layer; and performing, by a user, a UI interaction, the UI interaction includes a performed event on the UI control, the performed event corresponds to one of the events, wherein in design-time, the performed event causes performance of a corresponding design-time action, and if the performed event occurs at the anchor design-time adjustment indicator, the anchor layer handles the performed event if the performed event is one of the events defined for the anchor layer, and the anchor layer passes the performed event to the border layer for handling if the performed event is not one of the events defined for the anchor layer, if the performed event occurs at the border design-time adjustment indicator, the border layer handles the performed event, and if the performed event occurs at the UI control other than the anchor and border design-time adjustment indicators, the base layer handles the performed event as if during runtime. 2. The method according to claim 1 wherein in runtime, the performed event causes performance of a corresponding runtime action. | 0.908832 |
7,917,847 | 76 | 77 | 76. The computer program product according to claim 67 , further comprising instructions for: storing information regarding a focus position and a scrolling position in the first browsing mode; and restoring the focus position and the scrolling position, based on the stored information, in the second browsing mode. | 76. The computer program product according to claim 67 , further comprising instructions for: storing information regarding a focus position and a scrolling position in the first browsing mode; and restoring the focus position and the scrolling position, based on the stored information, in the second browsing mode. 77. The computer program product according to claim 76 , wherein the restoring includes: judging whether or not the focus position is within a displaying area defined by the scrolling position; and adjusting the focus position so that the focus position is within the displaying area if it is judged that the focus position is not within the displaying area. | 0.864804 |
9,552,417 | 2 | 6 | 2. The system according to claim 1 , further comprising: a data normalization processor configured to atomize the data record for the monitored telephone conversation with respect to the multimedia data warehouse; and a link creation processor configured to create one or more logical links between the data record for the monitored telephone conversation and one or more data records within the multimedia data warehouse. | 2. The system according to claim 1 , further comprising: a data normalization processor configured to atomize the data record for the monitored telephone conversation with respect to the multimedia data warehouse; and a link creation processor configured to create one or more logical links between the data record for the monitored telephone conversation and one or more data records within the multimedia data warehouse. 6. The system according to claim 2 , wherein the data normalization processor is configured to utilize a natural language processing algorithm to atomize the data record for the monitored telephone conversation with respect to the multimedia data warehouse. | 0.922027 |
8,751,407 | 11 | 20 | 11. A computer-implemented method for facilitating creation of an ad hoc social networking forum for a cohort of users, the method being implemented in a computer system comprising one or more physical processors programmed with computer readable instructions to, the method comprising: obtaining, by the one or more physical processors, from one or more publicly available sources, information related to a first cohort prior to receiving a user request to join a first social networking forum that is related to the first cohort, the first cohort comprising a plurality of users that have a pre-established association with a first experience scheduled to occur at a first time, first date, and a first location, the information related to the first cohort comprising information related to the first experience; and receiving, by the one or more physical processors, a request from a first user of the first cohort to join the first social networking forum associated with the first cohort; determining, by the one or more physical processors, whether the first social networking forum has been created; and responsive to a determination that the first social networking forum has not been created: creating, by the one or more physical processors, the first social networking forum; and adding, by the one or more physical processors, the first user as a member of the first social networking forum; and facilitating, by the one or more physical processors, sharing of one or more items of content via the first social networking forum. | 11. A computer-implemented method for facilitating creation of an ad hoc social networking forum for a cohort of users, the method being implemented in a computer system comprising one or more physical processors programmed with computer readable instructions to, the method comprising: obtaining, by the one or more physical processors, from one or more publicly available sources, information related to a first cohort prior to receiving a user request to join a first social networking forum that is related to the first cohort, the first cohort comprising a plurality of users that have a pre-established association with a first experience scheduled to occur at a first time, first date, and a first location, the information related to the first cohort comprising information related to the first experience; and receiving, by the one or more physical processors, a request from a first user of the first cohort to join the first social networking forum associated with the first cohort; determining, by the one or more physical processors, whether the first social networking forum has been created; and responsive to a determination that the first social networking forum has not been created: creating, by the one or more physical processors, the first social networking forum; and adding, by the one or more physical processors, the first user as a member of the first social networking forum; and facilitating, by the one or more physical processors, sharing of one or more items of content via the first social networking forum. 20. The method of claim 11 , further comprising: managing, by the one or more physical processors, access of a third party to the first social networking forum; and facilitating, by the one or more physical processors, provision of advertising content by the third party to the first social networking forum. | 0.928538 |
8,669,888 | 19 | 20 | 19. The Hangeul input method of claim 17 , wherein, when selecting a consonant key among a plurality of consonant keys in the input of the basic consonants and the extended consonants, the basic consonants assigned to the selected consonant key and the extended consonants converted from the basic convertible consonants assigned to the selected basic convertible consonant key are sequentially and circularly selected by repeatedly operating the selected basic convertible consonant key; and when selecting a vowel key among a plurality of vowel keys in the input of the basic vowels and the combined vowels, the basic vowels assigned to the selected vowel key and the combined vowels having the basic vowels assigned to the selected key as the first basic vowel are sequentially and circularly selected by repeatedly operating the selected vowel key. | 19. The Hangeul input method of claim 17 , wherein, when selecting a consonant key among a plurality of consonant keys in the input of the basic consonants and the extended consonants, the basic consonants assigned to the selected consonant key and the extended consonants converted from the basic convertible consonants assigned to the selected basic convertible consonant key are sequentially and circularly selected by repeatedly operating the selected basic convertible consonant key; and when selecting a vowel key among a plurality of vowel keys in the input of the basic vowels and the combined vowels, the basic vowels assigned to the selected vowel key and the combined vowels having the basic vowels assigned to the selected key as the first basic vowel are sequentially and circularly selected by repeatedly operating the selected vowel key. 20. The Hangeul input method of claim 19 , wherein, in the input of the basic consonants and the extended consonants, circular selection according to the repeated selection of the selected consonant key is performed in the sequence of the basic consonants, aspirates of the basic consonants, and fortises of the basic consonants assigned to the selected consonant key. | 0.905834 |
6,134,540 | 12 | 15 | 12. A program having computer readable program code means on a computer usable medium, the program comprising: means having a capability to build objects in a memory based upon a view type referenced in a query received from an application; and means for applying query rewrite optimizations to the query referencing the view type, wherein the query rewrite optimizations determine which portions of the query to push down to a database at a second tier for resolution and which portions of the query are to be processed by the query engine at a first tier to build objects from the view types. | 12. A program having computer readable program code means on a computer usable medium, the program comprising: means having a capability to build objects in a memory based upon a view type referenced in a query received from an application; and means for applying query rewrite optimizations to the query referencing the view type, wherein the query rewrite optimizations determine which portions of the query to push down to a database at a second tier for resolution and which portions of the query are to be processed by the query engine at a first tier to build objects from the view types. 15. The program of claim 12 further comprising: means for giving all of the query to a data source to resolve without performing any object building, even though the query references the view type, if the query does not request a handle on an object and if the query does not reference a method. | 0.737077 |
7,987,416 | 16 | 17 | 16. A computer-implemented method of extracting information comprising: defining a plurality of reusable operators, wherein each operator performs a predefined information extraction task different from the other operators; specifying a composition of said reusable operators to form a composite annotator, wherein each operator receives a searchable item and generates one or more output annotations; and storing the output annotations for use during a search, wherein the plurality of reusable operators include an composition operator, the searchable items comprising text, and wherein the composition operator receives an input annotation and two reference annotation types and generates one or more output annotations comprising text between the two reference annotation types. | 16. A computer-implemented method of extracting information comprising: defining a plurality of reusable operators, wherein each operator performs a predefined information extraction task different from the other operators; specifying a composition of said reusable operators to form a composite annotator, wherein each operator receives a searchable item and generates one or more output annotations; and storing the output annotations for use during a search, wherein the plurality of reusable operators include an composition operator, the searchable items comprising text, and wherein the composition operator receives an input annotation and two reference annotation types and generates one or more output annotations comprising text between the two reference annotation types. 17. The method of claim 16 , the two reference annotation types each comprising a set comprising a plurality of annotations. | 0.936799 |
7,542,979 | 34 | 35 | 34. A method as in claim 33 , wherein the variable rule comprises a condition, a parsedescriptor, and a values clause. | 34. A method as in claim 33 , wherein the variable rule comprises a condition, a parsedescriptor, and a values clause. 35. A method as in claim 34 , wherein the variable rule further includes an endcondition. | 0.97899 |
8,171,451 | 18 | 19 | 18. The method as recited in claim 17 , wherein the converting step converts the definitions of the objects by mapping a report definition format of each provider, from elements and containment hierarchy defined in the report definition, to a representation of the elements in a common representation format; and the object model generating step generates the object model using the common representation format. | 18. The method as recited in claim 17 , wherein the converting step converts the definitions of the objects by mapping a report definition format of each provider, from elements and containment hierarchy defined in the report definition, to a representation of the elements in a common representation format; and the object model generating step generates the object model using the common representation format. 19. The method as recited in claim 18 , wherein the WSDL generating step generates the WSDL definition by defining web service operations for each named report element object in the object mode. | 0.92836 |
8,555,250 | 1 | 15 | 1. In a computing environment, a processor-implemented method of analyzing dynamic source code, the method comprising: parsing source code to generate one or more syntax trees defining constructs in a body of dynamic language source code; from the one or more syntax trees, extracting identifier information for one or more of the defined constructs; augmenting knowledge about the constructs by at least one of explicit inspection of the body of source code or implied references related to the source code; producing a correlation between identifiers and augmented knowledge; using the identifier information and augmented knowledge, generating metadata about the body of the dynamic language source code, the generated metadata being represented as a symbol table; parsing symbol table to compute metrics about the one or more syntax trees; and providing the metrics about the one or more syntax trees to a user, wherein the metrics provide code correctness analysis, and wherein the correctness analysis indicates parameter count mismatches. | 1. In a computing environment, a processor-implemented method of analyzing dynamic source code, the method comprising: parsing source code to generate one or more syntax trees defining constructs in a body of dynamic language source code; from the one or more syntax trees, extracting identifier information for one or more of the defined constructs; augmenting knowledge about the constructs by at least one of explicit inspection of the body of source code or implied references related to the source code; producing a correlation between identifiers and augmented knowledge; using the identifier information and augmented knowledge, generating metadata about the body of the dynamic language source code, the generated metadata being represented as a symbol table; parsing symbol table to compute metrics about the one or more syntax trees; and providing the metrics about the one or more syntax trees to a user, wherein the metrics provide code correctness analysis, and wherein the correctness analysis indicates parameter count mismatches. 15. The method of claim 1 , wherein the metrics are embedded into the specific metadata format data structure. | 0.8625 |
7,580,830 | 1 | 3 | 1. A method comprising: obtaining a named entity from text input of a source language; generating, with a potential translation generator, potential translations of the named entity from the source language to a target language using a pronunciation-based and spelling-based transliteration model; searching a monolingual resource in the target language for information relating to usage frequency; and providing output comprising at least one of the potential translations based on the usage frequency information. | 1. A method comprising: obtaining a named entity from text input of a source language; generating, with a potential translation generator, potential translations of the named entity from the source language to a target language using a pronunciation-based and spelling-based transliteration model; searching a monolingual resource in the target language for information relating to usage frequency; and providing output comprising at least one of the potential translations based on the usage frequency information. 3. The method of claim 1 , wherein providing the output based on the usage frequency information comprises adjusting probability scores of the potential translations based on the usage frequency information. | 0.893409 |
8,688,444 | 1 | 4 | 1. A method comprising: transmitting automatic speech recognition data from a first device to a second device, wherein the first device performs speech recognition using automatic speech recognition parameters based on the automatic speech recognition data; receiving, at the first device, a new set of automatic speech recognition adaptation parameters from the second device, wherein the new set of automatic speech recognition adaptation parameters is based on the automatic speech recognition data; and using the new set of automatic speech recognition adaptation parameters to update the automatic speech recognition adaptation parameters on the first device. | 1. A method comprising: transmitting automatic speech recognition data from a first device to a second device, wherein the first device performs speech recognition using automatic speech recognition parameters based on the automatic speech recognition data; receiving, at the first device, a new set of automatic speech recognition adaptation parameters from the second device, wherein the new set of automatic speech recognition adaptation parameters is based on the automatic speech recognition data; and using the new set of automatic speech recognition adaptation parameters to update the automatic speech recognition adaptation parameters on the first device. 4. The method of claim 1 , wherein the first device is remote from the second device. | 0.886667 |
8,041,781 | 14 | 15 | 14. The method of claim 8 wherein receiving the request for performing the web system service on the web application document comprises receiving a request for restoring the content and context information of the web application document stored on a web server to an application operating on one of the client devices. | 14. The method of claim 8 wherein receiving the request for performing the web system service on the web application document comprises receiving a request for restoring the content and context information of the web application document stored on a web server to an application operating on one of the client devices. 15. The method of claim 14 wherein receiving the request for performing the web system service on the web application document comprises receiving a request for restoring the content and context information of the web application document stored on a web server to a different application operating on a client device different from the client device that stored the web application document. | 0.863224 |
9,008,429 | 1 | 7 | 1. A method for comparing a text image and a character string comprising: embedding a character string into a vectorial space, comprising extracting a set of features from the character string and generating a character string representation based on the extracted character string features; embedding a text image into a vectorial space, comprising extracting a set of features from the text image and generating a text image representation based on the extracted text image features; and computing a compatibility between the text image representation and character string representation comprising computing a function of the text image representation and character string representation, the function including an embedding parameter w which is a DE-dimensional vector or a D×E matrix W which embeds the text image representation and character string representation into a new space, where D is the dimensionality of the text image representation and E is the dimensionality of the character string representation, wherein at least one of the embedding and the computing of the compatibility is performed with a processor. | 1. A method for comparing a text image and a character string comprising: embedding a character string into a vectorial space, comprising extracting a set of features from the character string and generating a character string representation based on the extracted character string features; embedding a text image into a vectorial space, comprising extracting a set of features from the text image and generating a text image representation based on the extracted text image features; and computing a compatibility between the text image representation and character string representation comprising computing a function of the text image representation and character string representation, the function including an embedding parameter w which is a DE-dimensional vector or a D×E matrix W which embeds the text image representation and character string representation into a new space, where D is the dimensionality of the text image representation and E is the dimensionality of the character string representation, wherein at least one of the embedding and the computing of the compatibility is performed with a processor. 7. The method of claim 1 , wherein the character string comprises a license plate number. | 0.857827 |
6,078,746 | 1 | 5 | 1. A method in a computer system for determining an operand for an operator during data entry of the nodes of an intentional program tree, the method comprising: receiving a sequence of tokens, each token indicating a computational construct corresponding to a node of the intentional program tree; when receiving an indication of a selection of a subtree of the intentional program tree, selecting the indicated subtree; and when receiving an indication of a next token to be appended to the sequence of tokens, when a subtree is currently selected, identifying the selected subtree as an operand of the operator represented by the next token; when a subtree is not currently selected, identifying according to predefined rules of operator precedence an operand of the operator represented by the next token; and adding a node to the intentional program tree indicating the operator represented by the next token and indicating the identified operand whereby predefined rules of operator precedence may be overridden by selection of a subtree. | 1. A method in a computer system for determining an operand for an operator during data entry of the nodes of an intentional program tree, the method comprising: receiving a sequence of tokens, each token indicating a computational construct corresponding to a node of the intentional program tree; when receiving an indication of a selection of a subtree of the intentional program tree, selecting the indicated subtree; and when receiving an indication of a next token to be appended to the sequence of tokens, when a subtree is currently selected, identifying the selected subtree as an operand of the operator represented by the next token; when a subtree is not currently selected, identifying according to predefined rules of operator precedence an operand of the operator represented by the next token; and adding a node to the intentional program tree indicating the operator represented by the next token and indicating the identified operand whereby predefined rules of operator precedence may be overridden by selection of a subtree. 5. The method of claim 1 wherein the predefined rules of operator precedence are in accordance with the C programming language. | 0.503906 |
7,680,307 | 1 | 25 | 1. A method for identifying a distinctive region in a medical image data set for a patient, comprising: applying a first classifier to a medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a first specified distinctive region, wherein the first classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof; passing the identified first subset to a second classifier; applying the second classifier to the first subset, the second classifier having a specificity configured to confirm the presence, or absence of the first specified distinctive region within one or more portions of the first subset, wherein the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, and wherein the first specified distinctive region is selected from an occlusive plague region and a vulnerable plague region; applying a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, wherein the second specified distinctive region is a different type of region than the first specified distinctive region, wherein the third classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof; passing the identified second subset to a fourth classifier; applying the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region; and displaying a medical image based on the medical image data set and showing one or more first specified distinctive regions as identified by the first and second classifiers and one or more second specified distinctive regions as identified by the third and fourth classifiers, wherein the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof. | 1. A method for identifying a distinctive region in a medical image data set for a patient, comprising: applying a first classifier to a medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a first specified distinctive region, wherein the first classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof; passing the identified first subset to a second classifier; applying the second classifier to the first subset, the second classifier having a specificity configured to confirm the presence, or absence of the first specified distinctive region within one or more portions of the first subset, wherein the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, and wherein the first specified distinctive region is selected from an occlusive plague region and a vulnerable plague region; applying a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, wherein the second specified distinctive region is a different type of region than the first specified distinctive region, wherein the third classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof; passing the identified second subset to a fourth classifier; applying the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region; and displaying a medical image based on the medical image data set and showing one or more first specified distinctive regions as identified by the first and second classifiers and one or more second specified distinctive regions as identified by the third and fourth classifiers, wherein the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof. 25. The method of claim 1 , wherein the second specified distinctive region is a calcified tissue region. | 0.92268 |
7,852,416 | 11 | 12 | 11. A control system that interacts with an entertainment system having at least one audio unit, the control system comprising: a remote control device comprising: a remote control screen; a communication interface; a user input interface; and at least one module operable to: receive, via the communication interface; a list identifying a plurality of media elements and a plurality of languages in which the plurality of media elements are available; display the received list on the remote control screen; receive, via the user input interface, a media selection and a language selection from the displayed list; and transmit a control signal via the communication interface that triggers delivery of a media element in a language to the at least one audio unit of the entertainment system, where the media element corresponds to the media selection and the language corresponds to the language selection. | 11. A control system that interacts with an entertainment system having at least one audio unit, the control system comprising: a remote control device comprising: a remote control screen; a communication interface; a user input interface; and at least one module operable to: receive, via the communication interface; a list identifying a plurality of media elements and a plurality of languages in which the plurality of media elements are available; display the received list on the remote control screen; receive, via the user input interface, a media selection and a language selection from the displayed list; and transmit a control signal via the communication interface that triggers delivery of a media element in a language to the at least one audio unit of the entertainment system, where the media element corresponds to the media selection and the language corresponds to the language selection. 12. The control system according to claim 11 , wherein: the at least one module is operable to receive, via the user input interface, a second media selection different from said media selection; and display a second media element received via the communication interface and corresponding to the second media selection on the remote control screen. | 0.649598 |
9,256,415 | 1 | 2 | 1. A method for generating an installation script for installing an application component to a specific target platform, the method comprising the steps of: retrieving a semantic model for the application component from a communicatively coupled repository of semantic models for interdependent ones of application components, the semantic model including a set of individual listings formatted within a markup language with different interdependent ones of application components being specified according to a respective network addressing scheme, the set of individual listings comprising a listing of component relationships and a listing of target platform requirements specifying a minimum requisite type and a level of resources required for operation of the application component on a target platform; determining from the listing of component relationships from the set of individual listings in said semantic model, a set of dependent components upon which the application component depends that are required to be present in the specific target platform; further determining from the listing of target platform requirements from the set of individual listings in said semantic model, a set of resource requirements required to be met by the specific target platform; and, mapping said set of dependent components and said set of resource requirements into platform specific instructions in a platform specific installation script. | 1. A method for generating an installation script for installing an application component to a specific target platform, the method comprising the steps of: retrieving a semantic model for the application component from a communicatively coupled repository of semantic models for interdependent ones of application components, the semantic model including a set of individual listings formatted within a markup language with different interdependent ones of application components being specified according to a respective network addressing scheme, the set of individual listings comprising a listing of component relationships and a listing of target platform requirements specifying a minimum requisite type and a level of resources required for operation of the application component on a target platform; determining from the listing of component relationships from the set of individual listings in said semantic model, a set of dependent components upon which the application component depends that are required to be present in the specific target platform; further determining from the listing of target platform requirements from the set of individual listings in said semantic model, a set of resource requirements required to be met by the specific target platform; and, mapping said set of dependent components and said set of resource requirements into platform specific instructions in a platform specific installation script. 2. The method of claim 1 , further comprising the steps of: yet further determining from said semantic model a set of platform neutral installation operations; and, further mapping said set of platform neutral installation operations into said platform specific instructions. | 0.705567 |
5,560,037 | 2 | 4 | 2. A system comprising: memory for storing data; the data stored in memory comprising word data representing a large set of words; the large set of words including a set of shared suffix branches, each shared suffix branch occurring at least twice in the large set of word; a first one of the words in the large set having two or more characters and a hyphenation point between a preceding character and a subsequent character; the hyphenation point of the first word being a point at which the first word can properly be hyphenated; the first word and a second one of the words in the large set both including a shared suffix that occurs in a first one of the shared suffix branches; the shared suffix following a first word character in the first word and following a second word character in the second word; and a processor connected for accessing the word data to determine the hyphenation point of the first word; the word data including codes, each code being one of a set of codes that includes character codes for representing characters of words, location codes for indicating locations in the memory, and a hyphenation code for representing hyphenation points of words; the word data comprising: a first sequence of codes representing the first word; the first sequence of codes including a preceding character code representing the preceding character, a following character code representing the subsequent character, a first word hyphenation code representing the hyphenation point of the first word, and a first word character code representing the first word character; the first word hyphenation code being positioned between the preceding character code and the following character code in the first sequence of codes so that the processor can determine the hyphenation point of the first word from the position of the hyphenation code; and a second sequence of codes representing the second word; the second sequence of codes including a second word character code representing the second word character; the first sequence of codes and the second sequence of codes both including shared suffix codes; the shared suffix codes representing the shared suffix in both the first word and the second word as a result of an operation that detects each of the set of shared suffix branches and determines, for each detected shared suffix branch, whether to represent it only once; the shared suffix codes beginning at a first location in the memory; the first sequence of codes including information that the processor can use, after accessing the first word character code, to continue search by accessing the shared suffix codes at the first location; the second sequence of codes including information that the processor can use, after accessing the second word character code, to continue search by accessing the shared suffix codes at the first location; at least one of the first and second word character codes being followed by a first location code indicating the first location so that the processor can use the first location code to continue search by accessing the shared suffix codes at the first location; the processor being operable to search the word data for the first sequence of codes and to determine the hyphenation point of the first word from the position of the hyphenation code in the first sequence of codes. | 2. A system comprising: memory for storing data; the data stored in memory comprising word data representing a large set of words; the large set of words including a set of shared suffix branches, each shared suffix branch occurring at least twice in the large set of word; a first one of the words in the large set having two or more characters and a hyphenation point between a preceding character and a subsequent character; the hyphenation point of the first word being a point at which the first word can properly be hyphenated; the first word and a second one of the words in the large set both including a shared suffix that occurs in a first one of the shared suffix branches; the shared suffix following a first word character in the first word and following a second word character in the second word; and a processor connected for accessing the word data to determine the hyphenation point of the first word; the word data including codes, each code being one of a set of codes that includes character codes for representing characters of words, location codes for indicating locations in the memory, and a hyphenation code for representing hyphenation points of words; the word data comprising: a first sequence of codes representing the first word; the first sequence of codes including a preceding character code representing the preceding character, a following character code representing the subsequent character, a first word hyphenation code representing the hyphenation point of the first word, and a first word character code representing the first word character; the first word hyphenation code being positioned between the preceding character code and the following character code in the first sequence of codes so that the processor can determine the hyphenation point of the first word from the position of the hyphenation code; and a second sequence of codes representing the second word; the second sequence of codes including a second word character code representing the second word character; the first sequence of codes and the second sequence of codes both including shared suffix codes; the shared suffix codes representing the shared suffix in both the first word and the second word as a result of an operation that detects each of the set of shared suffix branches and determines, for each detected shared suffix branch, whether to represent it only once; the shared suffix codes beginning at a first location in the memory; the first sequence of codes including information that the processor can use, after accessing the first word character code, to continue search by accessing the shared suffix codes at the first location; the second sequence of codes including information that the processor can use, after accessing the second word character code, to continue search by accessing the shared suffix codes at the first location; at least one of the first and second word character codes being followed by a first location code indicating the first location so that the processor can use the first location code to continue search by accessing the shared suffix codes at the first location; the processor being operable to search the word data for the first sequence of codes and to determine the hyphenation point of the first word from the position of the hyphenation code in the first sequence of codes. 4. The system of claim 2 in which the processor is operable for accessing the word data with a token to obtain the first word and to retrieve the hyphenation code. | 0.930638 |
8,352,268 | 19 | 22 | 19. A system, comprising: one or more processors; and memory, the memory storing one or more programs, the one or more programs comprising instructions, which when executed by the one or more processors, cause the one or more processors to: generate a speech segment from one or more text strings describing or identifying a media asset having audio data distinct from the generated speech segment; obtain user input requesting a variation in speech delivery accompanying the media asset; in response to the user input, customize the speech segment by modifying selected portions of the speech segment at a server device, wherein the customizing further comprises: automatically detecting one or more repeated portions in the speech segment; and automatically modifying the speech segment by performing one or more of: (1) omitting at least one of the repeated portions from the speech segment, (2) using faster speech patterns for at least one of the repeated portions, (3) shortening breaks between words in at least one of the repeated portions, and (4) truncating one or more phrases in at least one of the repeated portions; and provide the customized speech segment from the server device to a user device for playback with the media asset. | 19. A system, comprising: one or more processors; and memory, the memory storing one or more programs, the one or more programs comprising instructions, which when executed by the one or more processors, cause the one or more processors to: generate a speech segment from one or more text strings describing or identifying a media asset having audio data distinct from the generated speech segment; obtain user input requesting a variation in speech delivery accompanying the media asset; in response to the user input, customize the speech segment by modifying selected portions of the speech segment at a server device, wherein the customizing further comprises: automatically detecting one or more repeated portions in the speech segment; and automatically modifying the speech segment by performing one or more of: (1) omitting at least one of the repeated portions from the speech segment, (2) using faster speech patterns for at least one of the repeated portions, (3) shortening breaks between words in at least one of the repeated portions, and (4) truncating one or more phrases in at least one of the repeated portions; and provide the customized speech segment from the server device to a user device for playback with the media asset. 22. The system of claim 19 wherein the user input requests at least one of fast forwarding and skipping playback of speech content at the user device. | 0.810606 |
8,510,096 | 10 | 14 | 10. An apparatus for selecting an interface language of software, comprising: a starting module, which is configured to start the software and judge whether the software is started for the first time; an obtaining module, which is configured to: when the starting module judges that the software is started for the first time, obtain an interface language used currently by an operation system; a matching module, which is configured to match the interface language used currently by the operation system to multiple languages pre-configured for the software; a selecting module, which is configured to: when the matching module matches successfully, select the interface language used currently by the operation system as the interface language of the software, and if the match is unsuccessful, select a default interface language of the software as the interface language of the software; and when the starting module judges that the software is not started for the first time, use a pre-configured interface language recorded by the software as an interface display language of the software; a writing module is configured to write the interface language selected by the selecting module into the configuration file of the software as a current language configuration option; a configuration file storing module is configured to store the configuration file of the software. | 10. An apparatus for selecting an interface language of software, comprising: a starting module, which is configured to start the software and judge whether the software is started for the first time; an obtaining module, which is configured to: when the starting module judges that the software is started for the first time, obtain an interface language used currently by an operation system; a matching module, which is configured to match the interface language used currently by the operation system to multiple languages pre-configured for the software; a selecting module, which is configured to: when the matching module matches successfully, select the interface language used currently by the operation system as the interface language of the software, and if the match is unsuccessful, select a default interface language of the software as the interface language of the software; and when the starting module judges that the software is not started for the first time, use a pre-configured interface language recorded by the software as an interface display language of the software; a writing module is configured to write the interface language selected by the selecting module into the configuration file of the software as a current language configuration option; a configuration file storing module is configured to store the configuration file of the software. 14. The apparatus according to claim 10 , further comprising: a switching module, which is configured to, when receiving an operation instruction for switching the interface language of the software sent by a user, analyze the interface language needing to be switched to that is instructed by the operation instruction; the writing module is further configured to update a record of the current language configuration option in the software configuration file by using the interface language analyzed by the switching module; the loading module is further configured to load a language resource file corresponding to the interface language analyzed by the switching module, refresh the interface of the software, and display the character string in the loaded language resource file on the interface of the software. | 0.500611 |
7,516,145 | 19 | 24 | 19. A method comprising: applying a transformation file on a hierarchical data file having first and second nodes to produce a first rendering file; rendering the first rendering file to show a rendered form having a first data-entry field associated with the first node of the hierarchical data file and a second data-entry field associated with the second node of the hierarchical data file; enabling a user to input data into the first data-entry field; changing the hierarchical data file by retaining the data in the first node of the hierarchical data file; applying the transformation file on the changed hierarchical data file to produce a second rendering file; determining a difference between the first rendering file and the second rendering file; attempting to map the difference on the first rendering file; producing a third rendering file, the third rendering file comprising a partial rendering file based on the difference if the map is successful and comprising a full rendering file if the map is not successful; rendering the third rendering file to show a second rendered form reflecting the change to the hierarchical data file; and enabling the user to input data into the second data-entry field. | 19. A method comprising: applying a transformation file on a hierarchical data file having first and second nodes to produce a first rendering file; rendering the first rendering file to show a rendered form having a first data-entry field associated with the first node of the hierarchical data file and a second data-entry field associated with the second node of the hierarchical data file; enabling a user to input data into the first data-entry field; changing the hierarchical data file by retaining the data in the first node of the hierarchical data file; applying the transformation file on the changed hierarchical data file to produce a second rendering file; determining a difference between the first rendering file and the second rendering file; attempting to map the difference on the first rendering file; producing a third rendering file, the third rendering file comprising a partial rendering file based on the difference if the map is successful and comprising a full rendering file if the map is not successful; rendering the third rendering file to show a second rendered form reflecting the change to the hierarchical data file; and enabling the user to input data into the second data-entry field. 24. A computer-readable medium comprising computer-executable instructions that perform the method of claim 19 when executed by a computer. | 0.876114 |
8,935,272 | 9 | 10 | 9. A method of a curated answers system, comprising: automatically populating a profile markup page of a user with information describing an initial query of a database that the user has generated using a processor and a memory; determining that another user of the database has submitted a similar query that is semantically proximate to the initial query of the database that the user has generated; presenting the profile markup page of the user to the another user; enabling the another user to communicate with the user through a communication channel on the profile markup page; publishing a question of the another user to the user on the profile markup page of the user, and another profile markup page of the another user; associating the question as being posted by the another user; processing a response of the user to the question; publishing the response of the user to the question on the profile markup page of the user and the another profile markup page of the another user; associating the response as being posted by the user; generating a social data catalog table of information about how users are interacting with at least one of the database and a sample database; populating the social data catalog table with a meta data, a logical definition and description of attributes, information about usage, page views between users, a social data network, and a statistical data profile; and crowdsourcing information from a ranked list of knowledgeable users to generate a ranked order of priority of information presented in profile pages of the curated answers system, wherein the information about usage includes related tables and join predicates as well as relevant filters associated with each table of at least one of the database and the sample database, wherein the social data network includes a list of users who are knowledgeable about a particular object related to the another query, and wherein the information is a metadata is at least one of a schema name, a table in a schema, a name of an attribute, a data type of an attribute, a primary key associated with an attribute, a constraint of an attribute, a functional dependency between attributes, an index, a foreign key, a field name, a column name, a table name, and a query description. | 9. A method of a curated answers system, comprising: automatically populating a profile markup page of a user with information describing an initial query of a database that the user has generated using a processor and a memory; determining that another user of the database has submitted a similar query that is semantically proximate to the initial query of the database that the user has generated; presenting the profile markup page of the user to the another user; enabling the another user to communicate with the user through a communication channel on the profile markup page; publishing a question of the another user to the user on the profile markup page of the user, and another profile markup page of the another user; associating the question as being posted by the another user; processing a response of the user to the question; publishing the response of the user to the question on the profile markup page of the user and the another profile markup page of the another user; associating the response as being posted by the user; generating a social data catalog table of information about how users are interacting with at least one of the database and a sample database; populating the social data catalog table with a meta data, a logical definition and description of attributes, information about usage, page views between users, a social data network, and a statistical data profile; and crowdsourcing information from a ranked list of knowledgeable users to generate a ranked order of priority of information presented in profile pages of the curated answers system, wherein the information about usage includes related tables and join predicates as well as relevant filters associated with each table of at least one of the database and the sample database, wherein the social data network includes a list of users who are knowledgeable about a particular object related to the another query, and wherein the information is a metadata is at least one of a schema name, a table in a schema, a name of an attribute, a data type of an attribute, a primary key associated with an attribute, a constraint of an attribute, a functional dependency between attributes, an index, a foreign key, a field name, a column name, a table name, and a query description. 10. The method of the curated answers system of claim 9 further comprising: automatically generating a table indicating a set of profiles associated with different users that have queried the database with a semantically proximate query to the similar query; presenting the table to the another user; and enabling the another user to communicate with any one of the different users associated with the set of profiles. | 0.501193 |
9,817,887 | 1 | 8 | 1. A method comprising: receiving a document in a first format, wherein the document comprises a text supported non-text data, and unsupported non-text data; creating, using a first filter associated with the first format, a universal text representation of the document, wherein the universal text representation presents the text and the supported non-text data, wherein the universal text representation preserves the unsupported non-text data by storing an association of the unsupported non-text data with supported data from the document, wherein the universal text representation comprises a text tree, wherein the text tree comprises nodes that comprise one or more words and locations of the words, and wherein one or more of the nodes comprise attributes associated with formatting of the words; modifying the universal text representation based upon input from a user of a program in a what you see is what you get (WYSIWYG) mode, wherein a location of where the supported data and the unsupported non-text data are kept is presented to the user, wherein modifying the universal text representation comprises translating the text presented in the universal text representation from a first language to a second language, wherein the first language is different than the second language, and wherein translating the text comprises: receiving a translation table representing the text in the second language, wherein the translation table comprises a correspondence between the words in the first language and translated words in the second language; creating a copy of the text tree, wherein the copy of the text tree preserves the formatting of the words; and for each node among the nodes in the copy of the text tree, replacing the words in the first language with the translated words based upon the translation table; and exporting, by at least one processor, the modified universal text representation using a second filter associated with a second format, wherein the supported data and the unsupported non-text data are exported. | 1. A method comprising: receiving a document in a first format, wherein the document comprises a text supported non-text data, and unsupported non-text data; creating, using a first filter associated with the first format, a universal text representation of the document, wherein the universal text representation presents the text and the supported non-text data, wherein the universal text representation preserves the unsupported non-text data by storing an association of the unsupported non-text data with supported data from the document, wherein the universal text representation comprises a text tree, wherein the text tree comprises nodes that comprise one or more words and locations of the words, and wherein one or more of the nodes comprise attributes associated with formatting of the words; modifying the universal text representation based upon input from a user of a program in a what you see is what you get (WYSIWYG) mode, wherein a location of where the supported data and the unsupported non-text data are kept is presented to the user, wherein modifying the universal text representation comprises translating the text presented in the universal text representation from a first language to a second language, wherein the first language is different than the second language, and wherein translating the text comprises: receiving a translation table representing the text in the second language, wherein the translation table comprises a correspondence between the words in the first language and translated words in the second language; creating a copy of the text tree, wherein the copy of the text tree preserves the formatting of the words; and for each node among the nodes in the copy of the text tree, replacing the words in the first language with the translated words based upon the translation table; and exporting, by at least one processor, the modified universal text representation using a second filter associated with a second format, wherein the supported data and the unsupported non-text data are exported. 8. The method of claim 1 , further comprising creating parallel fragments between the text tree and the copy of the text tree representing the text in the text tree that corresponds with the text in the copy of the text tree. | 0.826923 |
9,002,698 | 1 | 5 | 1. A speech translation apparatus comprising: an acquisition unit configured to acquire speech in a first language as a speech signal; a speech recognition unit configured to successively perform speech recognition on the speech signal to obtain a first language word string which is a result of the speech recognition; a translation unit configured to translate the first language word string into a second language to obtain a second language word string which is a result of translation; a search unit configured to search for at least one similar example for each first language word string, and, if there is the similar example, to acquire the similar example and a translation example which is a result of the translation of the similar example in the second language, the similar example indicating a word string that is similar to the first language word string in the first language; a selection unit configured to select, in accordance with a user instruction, at least one of the first language word string associated with the similar example and the second language word string associated with the translation example, as a selected word string; and a presentation unit configured to present one or more similar examples and one or more translation examples associated with the selected word string. | 1. A speech translation apparatus comprising: an acquisition unit configured to acquire speech in a first language as a speech signal; a speech recognition unit configured to successively perform speech recognition on the speech signal to obtain a first language word string which is a result of the speech recognition; a translation unit configured to translate the first language word string into a second language to obtain a second language word string which is a result of translation; a search unit configured to search for at least one similar example for each first language word string, and, if there is the similar example, to acquire the similar example and a translation example which is a result of the translation of the similar example in the second language, the similar example indicating a word string that is similar to the first language word string in the first language; a selection unit configured to select, in accordance with a user instruction, at least one of the first language word string associated with the similar example and the second language word string associated with the translation example, as a selected word string; and a presentation unit configured to present one or more similar examples and one or more translation examples associated with the selected word string. 5. The apparatus according to claim 1 , further comprising a storage configured to store the similar example and the translation example in association with each other. | 0.825 |
6,016,499 | 24 | 27 | 24. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called, the API including a Java Naming and Directory Interface API; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database results, wherein the directory services repository component includes an effective class and an object having a context the relational database language statement identifies a table and a subset restriction, and the driver and the API together map the effective class to the table and also map the context to the subset restriction. | 24. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called, the API including a Java Naming and Directory Interface API; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database results, wherein the directory services repository component includes an effective class and an object having a context the relational database language statement identifies a table and a subset restriction, and the driver and the API together map the effective class to the table and also map the context to the subset restriction. 27. The system of claim 24, wherein the directory services repository includes an X.500 directory services repository and the API includes an X.500 directory services API. | 0.796429 |
9,037,450 | 1 | 3 | 1. A system, comprising: a recognition system configured to recognize text in an image, the text of a first language written in a first direction; a translator configured to translate the text of the first language into text of a second language; an overlay algorithm configured to determine orientation and alignment between the text of the first language and the text of the second language, and overlays the text of the second language on the text of the first language as viewed in a display, such that each translated word corresponds to respective original text words; wherein the recognition system, the translator, and the overlay algorithm are configured to overlay the text of the second language on top of the text of the first language in realtime for viewing with graphical emphasis applied to differentiate the overlaid languages to the viewer; and a microprocessor configured to execute computer-executable instructions in a memory, the instructions executed to enable the recognition system, the translator, and the overlay algorithm. | 1. A system, comprising: a recognition system configured to recognize text in an image, the text of a first language written in a first direction; a translator configured to translate the text of the first language into text of a second language; an overlay algorithm configured to determine orientation and alignment between the text of the first language and the text of the second language, and overlays the text of the second language on the text of the first language as viewed in a display, such that each translated word corresponds to respective original text words; wherein the recognition system, the translator, and the overlay algorithm are configured to overlay the text of the second language on top of the text of the first language in realtime for viewing with graphical emphasis applied to differentiate the overlaid languages to the viewer; and a microprocessor configured to execute computer-executable instructions in a memory, the instructions executed to enable the recognition system, the translator, and the overlay algorithm. 3. The system of claim 1 , wherein the recognition system creates a first bounding box that circumscribes the text of the first language and a second bounding box that circumscribes the text of the second language, and the overlay algorithm aligns the second bounding box to the first bounding box as part of overlaying the text of the second language on the text of the first language. | 0.501292 |
9,256,366 | 1 | 20 | 1. A method comprising: providing, by an electronic device and for display in a seek area of a touch-sensitive display, a subset from a full range of a set of symbolic elements, wherein the subset has fewer symbolic elements than the full range; receiving, by the electronic device and in the seek area of the touch-sensitive display, a first user input specifying a first target range of the set of symbolic elements, wherein the first target range comprises a first alphabetized range between at least two symbolic elements of the subset that are presented in the seek area of the touch-sensitive display, and wherein the first target range includes the at least two symbolic elements; based on the first user input, providing, by the electronic device and for display in a selection area of the touch-sensitive display that is distinct from the seek area, individual symbolic elements from the first target range, wherein the individual symbolic elements from the first target range include the at least two symbolic elements of the first target range that are presented in the seek area of the touch-sensitive display, wherein the individual symbolic elements from the first target range further include at least one symbolic element of the first target range that is not included in the subset presented in the seek area of the touch-sensitive display, and wherein symbolic elements presented in the selection area are larger in size than symbolic elements presented in the seek area; receiving, by the electronic device, a second user input specifying a second target range of the set of symbolic elements that is different from the first target range, wherein the second target range comprises a second alphabetized range of the subset that is presented in the seek area of the touch-sensitive display; responsive to receiving the second user input: removing, by the electronic device and from the selection area of the touch-sensitive display, at least one of the individual symbolic elements from the first target range; and providing, by the electronic device and for display in the selection area of the touch-sensitive display, individual symbolic elements from the second target range, wherein the individual symbolic elements from the second target range include at least one symbolic element of the second target range that is not included in the subset presented in the seek area, and wherein the second target range includes at least one symbolic element that is also included in the first target range; receiving, by the electronic device and in the selection area of the touch-sensitive display, a third user input indicating a selected symbolic element from the individual symbolic elements from the second target range; and based on the third user input, inserting, by the electronic device, the selected symbolic element in a data object. | 1. A method comprising: providing, by an electronic device and for display in a seek area of a touch-sensitive display, a subset from a full range of a set of symbolic elements, wherein the subset has fewer symbolic elements than the full range; receiving, by the electronic device and in the seek area of the touch-sensitive display, a first user input specifying a first target range of the set of symbolic elements, wherein the first target range comprises a first alphabetized range between at least two symbolic elements of the subset that are presented in the seek area of the touch-sensitive display, and wherein the first target range includes the at least two symbolic elements; based on the first user input, providing, by the electronic device and for display in a selection area of the touch-sensitive display that is distinct from the seek area, individual symbolic elements from the first target range, wherein the individual symbolic elements from the first target range include the at least two symbolic elements of the first target range that are presented in the seek area of the touch-sensitive display, wherein the individual symbolic elements from the first target range further include at least one symbolic element of the first target range that is not included in the subset presented in the seek area of the touch-sensitive display, and wherein symbolic elements presented in the selection area are larger in size than symbolic elements presented in the seek area; receiving, by the electronic device, a second user input specifying a second target range of the set of symbolic elements that is different from the first target range, wherein the second target range comprises a second alphabetized range of the subset that is presented in the seek area of the touch-sensitive display; responsive to receiving the second user input: removing, by the electronic device and from the selection area of the touch-sensitive display, at least one of the individual symbolic elements from the first target range; and providing, by the electronic device and for display in the selection area of the touch-sensitive display, individual symbolic elements from the second target range, wherein the individual symbolic elements from the second target range include at least one symbolic element of the second target range that is not included in the subset presented in the seek area, and wherein the second target range includes at least one symbolic element that is also included in the first target range; receiving, by the electronic device and in the selection area of the touch-sensitive display, a third user input indicating a selected symbolic element from the individual symbolic elements from the second target range; and based on the third user input, inserting, by the electronic device, the selected symbolic element in a data object. 20. The method of claim 1 , wherein receiving the second user input specifying the second target range of the set of symbolic elements comprises receiving the second user input in the selection area. | 0.84306 |
9,286,373 | 1 | 3 | 1. An electronic device comprising: one or more computer-readable storage media configured to store instructions; and one or more processors configured to execute the instructions to cause the electronic device to: execute, using the one or more processors, for each object within a plurality of objects, the following steps: create a data structure of a first type comprising information for identifying one or more objects comprising a set of properties, wherein the data structure of a first type is created based at least in part on one or more properties associated with the object; and input the data structure of a first type into a data structure of a second type configured to determine objects associated with the data structure of a first type; and create, using the one or more processors, an association between a first object and a second object based at least in part on adding a data structure of a first type for the first object and a data structure of a first type for the second object into a same bin in the data structure of a second type, wherein the first object comprises a first set of properties, and wherein the second object comprises a second set of properties that include at least a portion of the first set of properties. | 1. An electronic device comprising: one or more computer-readable storage media configured to store instructions; and one or more processors configured to execute the instructions to cause the electronic device to: execute, using the one or more processors, for each object within a plurality of objects, the following steps: create a data structure of a first type comprising information for identifying one or more objects comprising a set of properties, wherein the data structure of a first type is created based at least in part on one or more properties associated with the object; and input the data structure of a first type into a data structure of a second type configured to determine objects associated with the data structure of a first type; and create, using the one or more processors, an association between a first object and a second object based at least in part on adding a data structure of a first type for the first object and a data structure of a first type for the second object into a same bin in the data structure of a second type, wherein the first object comprises a first set of properties, and wherein the second object comprises a second set of properties that include at least a portion of the first set of properties. 3. The electronic device of claim 1 , wherein the one or more processors are further configured to execute the instructions to cause the electronic device to: cause the data structure of a second type to add each data structure of a first type into a bin in the data structure of a second type, the bin being one of a plurality of bins in the data structure of a second type; and for each bin comprising two or more data structures of a first type: add the two or more data structures of a first type to a multimap. | 0.500969 |
8,195,555 | 11 | 13 | 11. A computer implemented system for enabling collaboration between advisors and clients, wherein the system comprises one or more processors configured to: receive requests to define a collaboration team that includes advisors associated with a client, wherein the requests further define different scopes of authorization for the advisors to access financial documents including financial information associated with the client; host, over a network, an electronic collaboration forum configured to enable collaboration between the advisors and the client, and, responsive to receipt of the selections, selectively provide the advisors access to stored financial documents associated with the client in accordance with the scopes of authorization for the advisors defined in the requests; provide a first advisor access to a first financial document associated with the client through the electronic collaboration forum, responsive to reception of a request for the first financial document from the first advisor and to the scope of authorization for the first advisor permitting access to the first financial document; receive a modification to the first financial document from the first advisor via the electronic collaboration forum; modify the first financial document accessible through the electronic collaboration forum in accordance with the received modification; and provide the access to the modified first financial document via the electronic collaboration forum for (i) the client and (ii) the advisors associated with scopes of authorization that permit access to the first financial document. | 11. A computer implemented system for enabling collaboration between advisors and clients, wherein the system comprises one or more processors configured to: receive requests to define a collaboration team that includes advisors associated with a client, wherein the requests further define different scopes of authorization for the advisors to access financial documents including financial information associated with the client; host, over a network, an electronic collaboration forum configured to enable collaboration between the advisors and the client, and, responsive to receipt of the selections, selectively provide the advisors access to stored financial documents associated with the client in accordance with the scopes of authorization for the advisors defined in the requests; provide a first advisor access to a first financial document associated with the client through the electronic collaboration forum, responsive to reception of a request for the first financial document from the first advisor and to the scope of authorization for the first advisor permitting access to the first financial document; receive a modification to the first financial document from the first advisor via the electronic collaboration forum; modify the first financial document accessible through the electronic collaboration forum in accordance with the received modification; and provide the access to the modified first financial document via the electronic collaboration forum for (i) the client and (ii) the advisors associated with scopes of authorization that permit access to the first financial document. 13. The system of claim 11 , wherein the one or more processors are further configured to track one or more actions taken by the first advisor via the electronic collaboration forum, wherein the tracked one or more actions comprise one or both of accessing and/or modifying the first financial document. | 0.737889 |
9,589,305 | 15 | 18 | 15. At least one computer-readable storage medium comprising instructions that, when executed, cause a system to: receive a network query at a network system, the network query to include a natural language user request from a device and a request to match the natural language user request against an object graph; match the natural language user request to one or more objects in the object graph, the object graph comprising token mappings for objects within the object graph, the token mappings based on data extracted from a plurality of interactions by a plurality of users of the network system, wherein the one or more objects are matched with the natural language user request based on the token mappings; and transmit the matched one or more objects to the device for execution of the natural language user request based on the matched one or more objects. | 15. At least one computer-readable storage medium comprising instructions that, when executed, cause a system to: receive a network query at a network system, the network query to include a natural language user request from a device and a request to match the natural language user request against an object graph; match the natural language user request to one or more objects in the object graph, the object graph comprising token mappings for objects within the object graph, the token mappings based on data extracted from a plurality of interactions by a plurality of users of the network system, wherein the one or more objects are matched with the natural language user request based on the token mappings; and transmit the matched one or more objects to the device for execution of the natural language user request based on the matched one or more objects. 18. The computer-readable storage medium of claim 15 , the matched one or more objects comprising a business object corresponding to a business entity, the business object represented in the object graph, comprising further instructions that, when executed, cause a system to: retrieve automated interaction instructions for the business entity based on the business object; and execute the natural language user request by performing at least one of a purchase and a reservation with a network server for the business entity based on the retrieved automated interaction instructions. | 0.538705 |
7,506,257 | 1 | 3 | 1. A computer-readable medium having computer-executable components for execution on a computer for presenting a plurality of help topics for software components installed on the computer and hardware components installed on the computer, comprising: a help content store for storing help contents for the help topics, the help content store having a plurality of separate vendor folders corresponding to different vendors of a plurality of different software components installed on the computer and a plurality of different hardware components installed on the computer, each vendor folder containing help contents of respective help topics provided by a corresponding vendor, the help contents usable by a unified taxonomy structure of help categories and help topics, wherein a first vendor corresponds to a first component selected from the plurality of different software components and the plurality of different hardware components and a second vendor corresponds to a second component selected from the plurality of different software components and the plurality of different hardware components, the first vendor and the second vendor being included in the different vendors; a help database containing mapping data for mapping the help topics from the different vendors into the unified taxonomy structure of help categories and help topics, the unified taxonomy structure being common to and inclusive of the help topics provided by the different vendors, and a first level of categories and a second level of categories in the unified taxonomy structure being predefined, static, and used by all the different vendors of software components installed on the computer and hardware components installed on the computer, the mapping data including data for each help topic for identifying a node position of said each help topic in the unified taxonomy structure and a location of corresponding help content of said each help topic in the help content store; a help content update module for updating the help contents in the help content store and the mapping data in the help database based on update packets received from the vendors; a help application for providing a user interface for presenting the help topics to a user, the help application being programmed to interactively display the unified taxonomy structure using the mapping data in the help database and the help contents in the content store, including displaying the help categories and the help topics in the unified taxonomy structure in response to user selections, retrieving a user-selected help topic contents, and displaying the user-selected help topic contents; and a script library for storing a plurality of script library objects used in the help contents of the help topics stored in the help content store, wherein the script library objects are operative to collect system operation information, and upload the system operation information to a vendor associated with the script library object; and an authorization store for storing information identifying which of the help contents are authorized to access the script library objects, wherein accessing the script library objects comprises accessing at least one of the following: a local database, and a remote database, wherein accessing the remote database requires that a Uniform Resource Locator (URL) associated with the remote database is listed in a local content store. | 1. A computer-readable medium having computer-executable components for execution on a computer for presenting a plurality of help topics for software components installed on the computer and hardware components installed on the computer, comprising: a help content store for storing help contents for the help topics, the help content store having a plurality of separate vendor folders corresponding to different vendors of a plurality of different software components installed on the computer and a plurality of different hardware components installed on the computer, each vendor folder containing help contents of respective help topics provided by a corresponding vendor, the help contents usable by a unified taxonomy structure of help categories and help topics, wherein a first vendor corresponds to a first component selected from the plurality of different software components and the plurality of different hardware components and a second vendor corresponds to a second component selected from the plurality of different software components and the plurality of different hardware components, the first vendor and the second vendor being included in the different vendors; a help database containing mapping data for mapping the help topics from the different vendors into the unified taxonomy structure of help categories and help topics, the unified taxonomy structure being common to and inclusive of the help topics provided by the different vendors, and a first level of categories and a second level of categories in the unified taxonomy structure being predefined, static, and used by all the different vendors of software components installed on the computer and hardware components installed on the computer, the mapping data including data for each help topic for identifying a node position of said each help topic in the unified taxonomy structure and a location of corresponding help content of said each help topic in the help content store; a help content update module for updating the help contents in the help content store and the mapping data in the help database based on update packets received from the vendors; a help application for providing a user interface for presenting the help topics to a user, the help application being programmed to interactively display the unified taxonomy structure using the mapping data in the help database and the help contents in the content store, including displaying the help categories and the help topics in the unified taxonomy structure in response to user selections, retrieving a user-selected help topic contents, and displaying the user-selected help topic contents; and a script library for storing a plurality of script library objects used in the help contents of the help topics stored in the help content store, wherein the script library objects are operative to collect system operation information, and upload the system operation information to a vendor associated with the script library object; and an authorization store for storing information identifying which of the help contents are authorized to access the script library objects, wherein accessing the script library objects comprises accessing at least one of the following: a local database, and a remote database, wherein accessing the remote database requires that a Uniform Resource Locator (URL) associated with the remote database is listed in a local content store. 3. A computer-readable medium as in claim 1 , wherein the mapping data for each help topic include a parent ID identifying a parent node of said each help topic in the unified taxonomy structure, and a URL identifying a location of the help content of said each help topic in the help content store. | 0.669248 |
9,111,144 | 1 | 11 | 1. A method of determining paternity based on eye color, the method comprising: electronically accessing a color digital image of at least one of a male parental candidate, a female parental candidate, and a child candidate; digitally processing the color digital image to determine an eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate, wherein the eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate is determined based on the accessed color digital image by comparing a portion of the color digital image to a set of predefined human eye colors; determining a paternity likelihood of the male parental candidate and the female parental candidate with regard to the child candidate based on the determined eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate; and displaying the paternity likelihood of the male parental candidate and the female parental candidate with regard to the child candidate on an electronic device. | 1. A method of determining paternity based on eye color, the method comprising: electronically accessing a color digital image of at least one of a male parental candidate, a female parental candidate, and a child candidate; digitally processing the color digital image to determine an eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate, wherein the eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate is determined based on the accessed color digital image by comparing a portion of the color digital image to a set of predefined human eye colors; determining a paternity likelihood of the male parental candidate and the female parental candidate with regard to the child candidate based on the determined eye color of the at least one of the male parental candidate, the female parental candidate, and the child candidate; and displaying the paternity likelihood of the male parental candidate and the female parental candidate with regard to the child candidate on an electronic device. 11. The method of claim 1 , wherein determining the eye color of at least one of the male parental candidate, the female parental candidate, and the child candidate based on the accessed color digital image comprises: displaying the captured digital image of the eye of the at least one of the male parental candidate, the female parental candidate, and the child candidate on an electronic display; receiving input from a user to select a portion of the digital image that represents the eye color of the eye of the at least one of the male parental candidate, the female parental candidate, and the child candidate; and selecting a color that best matches the color of the selected portion of the digital image. | 0.5007 |
5,495,577 | 16 | 17 | 16. The method as recited in claim 15, including the step of displaying a user selectable option for special character processing on said display. | 16. The method as recited in claim 15, including the step of displaying a user selectable option for special character processing on said display. 17. The method as recited in claim 16, wherein step (d) further comprises the steps of: (d5) selecting a third test character from said plurality of characters in said text string which third test character follows said insertion point; (d6) selecting a second font from said plurality of fonts stored in said storage, which second font is used to display said third test character; (d7) determining if said particular character can be displayed in said second font by searching said ordered font table utilizing said character code as an index to determine if there is a second associated glyph for said second font, and if an associated glyph is found, then displaying said particular character in said second font by displaying said second associated glyph on said display; and (d8) selecting another test character from said plurality of characters in said text string which other test character follows said insertion point if said particular character does not have an associated glyph in said second font, and repeating steps (d5) to (d7) for said other test character until all characters following the insertion point have been tested. | 0.784476 |
7,962,328 | 16 | 18 | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. | 16. An apparatus comprising: discriminant representation means for providing, to a user, representations of a plurality of discriminants of meanings of a plurality of symbols in a natural language, wherein each of the plurality of discriminants is associated with a corresponding finite set of mutually exclusive answers to the discriminant, and wherein the plurality of discriminants are orthogonal to each other; means for receiving, from the user, input representing a plurality of answers to the plurality of discriminants, wherein each of the plurality of answers from the user is selected from the finite set of mutually exclusive answers to the corresponding discriminant, wherein the means for receiving comprises: means for receiving first input from the user representing a first answer to a first one of the plurality of discriminants; and means for receiving second input, independent of the first input, from the user representing a second answer to a second one of the plurality of discriminants; and means for generating, in response to the input, a data structure tangibly stored in a computer-readable memory, the data structure comprising data representing the plurality of answers from the user, including the first answer and the second answer, and thereby representing a meaning of one of the plurality of symbols in the natural language; wherein the plurality of discriminants includes at least one Realm-related discriminant and one discriminant for distinguishing between composite and characteristic meanings in the natural language, wherein Realm-related discriminants include a discriminant for distinguishing between natural and artificial meanings in the natural language and a discriminant for distinguishing between concrete and information meanings in the natural language. 18. The apparatus of claim 16 , wherein the plurality of symbols comprises a plurality of words in the natural language. | 0.918699 |
8,392,352 | 20 | 21 | 20. The computer-implemented method of claim 19 , further comprising: receiving from a user interface a selection-for whether a given input data type is at least one of a crisp continuous data type, a crisp categorical data type, and a fuzzy data type, and a given input data structure of input data is at least one of text file, a spreadsheet, a relational database, an online analytical processing (OLAP) cube, a multidimensional database, and a chart, wherein the user interface permits a designation, from the given input data structure, of both at least a single piece of information for input attributes, and at least a single piece of information for output attributes. | 20. The computer-implemented method of claim 19 , further comprising: receiving from a user interface a selection-for whether a given input data type is at least one of a crisp continuous data type, a crisp categorical data type, and a fuzzy data type, and a given input data structure of input data is at least one of text file, a spreadsheet, a relational database, an online analytical processing (OLAP) cube, a multidimensional database, and a chart, wherein the user interface permits a designation, from the given input data structure, of both at least a single piece of information for input attributes, and at least a single piece of information for output attributes. 21. The computer-implemented method of claim 20 , wherein the generating a neuro-fuzzy expert system from the input data with a neural network structure comprising a plurality of layers including: an initial layer with a number of initial layer nodes equal to a number of input attributes, and the each initial layer node receiving the input values of at least one input attribute and passing the input values as input attributes to a next layer; an intermediate layer with a plurality of intermediate layer nodes with each intermediate layer node representing a unique combination of nodes in the second layer that belong to different input attributes, and links established between at least one intermediate layer node and at least one second layer node from a corresponding unique combination for integrating inputs from second layer nodes and passing them to a subsequent layer; and a final layer with at least one final layer node with a number of final layer nodes determined by a number of output attributes, and links established between each previous layer node and one final layer node. | 0.741021 |
9,177,320 | 17 | 18 | 17. A computing device comprising: a processor; and a memory configured to be in communication with the processor, and effective to store instructions; the processor effective to, in accordance with the instructions: perform a first search with use of a first search term related to a particular entity, wherein performance of the first search includes transmission of the first search term over a network; receive first results from the first search, wherein the first results relate to the particular entity and wherein the first results include first data in a first structure; parse the first data from the first structure to produce first pieces of unstructured data; receive second results from the first search, wherein the second results relate to the particular entity and wherein the second results include second data in a second structure, wherein the second structure is different from the first structure; parse the second data from the second structure to produce second pieces of unstructured data; identify matching pieces of data from among the first and second pieces of unstructured data; combine the matching pieces of data to form combined data with a third structure different from the first structure and the second structure, wherein the third structure relates to the particular entity as opposed to other entities, and wherein the combined data in the third structure relates to the particular entity; store the combined data in the third structure in a memory; receive a second search query related to the entity; perform the second search of the combined data in the third structure with use of the second search query related to the entity; produce a data file based on the results of the second search, wherein the data file includes at least some of the first and second pieces of unstructured data; and store the data file in the memory. | 17. A computing device comprising: a processor; and a memory configured to be in communication with the processor, and effective to store instructions; the processor effective to, in accordance with the instructions: perform a first search with use of a first search term related to a particular entity, wherein performance of the first search includes transmission of the first search term over a network; receive first results from the first search, wherein the first results relate to the particular entity and wherein the first results include first data in a first structure; parse the first data from the first structure to produce first pieces of unstructured data; receive second results from the first search, wherein the second results relate to the particular entity and wherein the second results include second data in a second structure, wherein the second structure is different from the first structure; parse the second data from the second structure to produce second pieces of unstructured data; identify matching pieces of data from among the first and second pieces of unstructured data; combine the matching pieces of data to form combined data with a third structure different from the first structure and the second structure, wherein the third structure relates to the particular entity as opposed to other entities, and wherein the combined data in the third structure relates to the particular entity; store the combined data in the third structure in a memory; receive a second search query related to the entity; perform the second search of the combined data in the third structure with use of the second search query related to the entity; produce a data file based on the results of the second search, wherein the data file includes at least some of the first and second pieces of unstructured data; and store the data file in the memory. 18. The computing device of claim 17 , wherein the processor is further effective to: receive a third search query related to the particular entity; identify the third structure from among other third structures as relating to the particular entity; perform the third search with use of the third search query related to the particular entity, wherein performance of the third search includes transmission of the third search query over the network; receive third results from the third search, wherein the third results relate to the particular entity, and wherein the third results include third data in a fourth structure; parse the third data from the fourth structure to produce third pieces of unstructured data; and modify the data file based on the third pieces of unstructured data. | 0.615646 |
7,844,464 | 6 | 7 | 6. The method of claim 1 , further comprising a step of: (D) modifying an emphasis of the region of the spoken audio stream in accordance with the emphasis factor to produce an emphasis-adjusted audio stream. | 6. The method of claim 1 , further comprising a step of: (D) modifying an emphasis of the region of the spoken audio stream in accordance with the emphasis factor to produce an emphasis-adjusted audio stream. 7. The method of claim 6 , further comprising a step of: (E) modifying an emphasis of the region of the document in accordance with the emphasis factor to produce an emphasis-adjusted document region. | 0.947006 |
8,725,736 | 1 | 3 | 1. A computer-implemented system for clustering similar documents, comprising: concepts for a set of documents; an occurrence module to determine occurrence frequencies of each concept in the document set; a distance module to calculate an inner product quantifying a similarity for each of the documents in the set with one or more clusters of documents based on the occurrence frequencies of the concepts; a map module to map each document to each of the document clusters based on the inner product, to identify those documents with the smallest inner products as most relevant to a theme, and to generate a matrix as a representation of the document and cluster mappings; and a processor to execute the modules. | 1. A computer-implemented system for clustering similar documents, comprising: concepts for a set of documents; an occurrence module to determine occurrence frequencies of each concept in the document set; a distance module to calculate an inner product quantifying a similarity for each of the documents in the set with one or more clusters of documents based on the occurrence frequencies of the concepts; a map module to map each document to each of the document clusters based on the inner product, to identify those documents with the smallest inner products as most relevant to a theme, and to generate a matrix as a representation of the document and cluster mappings; and a processor to execute the modules. 3. A system according to claim 1 , further comprising: a database record for each concept; and a database to store the database records. | 0.735409 |
9,953,631 | 8 | 9 | 8. The computing device of claim 6 , wherein the operations further comprise displaying the text in the detected language in response to obtaining the text, wherein the text is displayed in a first area on a display of the computing device, and wherein the translated text is displayed in a separate second area on the display. | 8. The computing device of claim 6 , wherein the operations further comprise displaying the text in the detected language in response to obtaining the text, wherein the text is displayed in a first area on a display of the computing device, and wherein the translated text is displayed in a separate second area on the display. 9. The computing device of claim 8 , wherein the text is displayed in at least one of a first color and a first style, and wherein the translated text is displayed in at least one of a different second color and a different second style. | 0.935352 |
9,367,797 | 23 | 26 | 23. A computer-program product for learning using a spiking neural network, comprising a non-transitory computer-readable medium comprising instructions executable to: (a) delay an input spike in an artificial neuron according to a current delay associated with an input to the artificial neuron, wherein the input spike occurs at an input spike time relative to a reference time for the artificial neuron; (b) emit an output spike from the artificial neuron based, at least in part, on the delayed input spike; (c) determine an actual time difference between the emission of the output spike from the artificial neuron and the reference time for the artificial neuron; and (d) adjust the current delay associated with the input based on a difference between a target time difference and the actual time difference, the current delay, and an input spike time for the input spike. | 23. A computer-program product for learning using a spiking neural network, comprising a non-transitory computer-readable medium comprising instructions executable to: (a) delay an input spike in an artificial neuron according to a current delay associated with an input to the artificial neuron, wherein the input spike occurs at an input spike time relative to a reference time for the artificial neuron; (b) emit an output spike from the artificial neuron based, at least in part, on the delayed input spike; (c) determine an actual time difference between the emission of the output spike from the artificial neuron and the reference time for the artificial neuron; and (d) adjust the current delay associated with the input based on a difference between a target time difference and the actual time difference, the current delay, and an input spike time for the input spike. 26. The computer-program product of claim 23 , further comprising instructions executable to: determine a scalar value based on the adjusted current delay, wherein the scalar value is an inverse of an exponential value of a coefficient of change of a membrane potential for the artificial neuron, the exponential raised to a power of the adjusted current delay before taking the inverse. | 0.501289 |
9,081,411 | 16 | 17 | 16. A virtual personal assistant (VPA) computer application for a domain of interest, embodied in one or more non-transitory machine-accessible storage media, the VPA computer application comprising: a user interface through which a conversational natural language dialog may be conducted between a computing device and a user to provide a service or information to the user with the computing device; a VPA engine to conduct the conversational natural language dialog and initiate the providing of the service or information to the computing device user; and a re-usable VPA component accessible by the VPA engine to enable the VPA computer application to determine a likely intended goal of the computing device user based on conversational natural language input of the computing device user, execute a task on behalf of the user, and/or generate a likely appropriate system response to the conversational natural language input; wherein the re-usable VPA component is adapted for use in the domain of interest in an automated fashion by a computerized agent configured to analyze content displayed on an Internet web page, identify domain-specific content displayed on the Internet web page, and establish a data relationship between the identified domain-specific web content and the re-usable VPA component. | 16. A virtual personal assistant (VPA) computer application for a domain of interest, embodied in one or more non-transitory machine-accessible storage media, the VPA computer application comprising: a user interface through which a conversational natural language dialog may be conducted between a computing device and a user to provide a service or information to the user with the computing device; a VPA engine to conduct the conversational natural language dialog and initiate the providing of the service or information to the computing device user; and a re-usable VPA component accessible by the VPA engine to enable the VPA computer application to determine a likely intended goal of the computing device user based on conversational natural language input of the computing device user, execute a task on behalf of the user, and/or generate a likely appropriate system response to the conversational natural language input; wherein the re-usable VPA component is adapted for use in the domain of interest in an automated fashion by a computerized agent configured to analyze content displayed on an Internet web page, identify domain-specific content displayed on the Internet web page, and establish a data relationship between the identified domain-specific web content and the re-usable VPA component. 17. The VPA computer application of claim 16 , wherein the re-usable VPA component is selected for use in the VPA computer application for the domain of interest based on a link between the re-usable VPA component and a computerized ontology, the ontology defines a structure for representing knowledge relating to the domain of interest, and the domain of interest refers to a category of information and/or activities in relation to which the VPA application may conduct the conversational natural language dialog with the computing device user. | 0.666056 |
9,105,268 | 12 | 13 | 12. The method of claim 1 , further comprising: performing a feature extraction from said text and generating a probability score, A of said customer's intent based upon a feature vector X of said text:
A=p ( Ii|X ) where Ii is ith intent I and X is the feature vector. | 12. The method of claim 1 , further comprising: performing a feature extraction from said text and generating a probability score, A of said customer's intent based upon a feature vector X of said text:
A=p ( Ii|X ) where Ii is ith intent I and X is the feature vector. 13. The method of claim 12 , further comprising: computing, by said IVR system, a probability of intent Ii based on a historical behavior of said customer. | 0.959403 |
9,626,431 | 7 | 13 | 7. A system comprising: at least one computing device; and a search application executable in the at least one computing device, the search application configured to at least: obtain a search query comprising at least one search term; detect a language associated with the search query; determine that the language associated with the search query differs from an expected language; in response to determining that the language differs from the expected language, generate a plurality of search results from a catalog comprising at least one alternative search result, wherein the at least one alternative search result comprises at least one search result differing from a search using the search query in the expected language; identify a foreign language page template associated with the language; and generate a page for display including the plurality of search results based at least in part on the foreign language template corresponding to the language. | 7. A system comprising: at least one computing device; and a search application executable in the at least one computing device, the search application configured to at least: obtain a search query comprising at least one search term; detect a language associated with the search query; determine that the language associated with the search query differs from an expected language; in response to determining that the language differs from the expected language, generate a plurality of search results from a catalog comprising at least one alternative search result, wherein the at least one alternative search result comprises at least one search result differing from a search using the search query in the expected language; identify a foreign language page template associated with the language; and generate a page for display including the plurality of search results based at least in part on the foreign language template corresponding to the language. 13. The system of claim 7 , wherein the foreign language page template comprises at least one of a string or an image varying in size from an expected language page template. | 0.830078 |
9,390,630 | 15 | 17 | 15. An apparatus, comprising: at least one processors; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: receive a recorded signal, the recorded signal being a signal generated for recording during a performance of an event dependent on a detected change in position of a body member of a performer relative to a performance element of a performance object with which the event was performed; determine the a first sensory cue dependent on the recorded signal; apply the first sensory cue to indicate to a user during a learning session the change in position of the body member of the performer during the performance of the event, wherein the first sensory cue is one of a haptic, auditory and visual sensory cue effective for stimulating a first processing center of a brain of the user; receive a visual sensory data; determine from the received visual sensory data a visual sensory cue capable of being displayed to the user on, a video display device; and display the visual sensory cue to the user during the learning session wherein the visual sensory cue provides a virtual visual indication to the user of the change in position of the body member of the performer during the performance, the visual sensory cue being effective for stimulating the visual processing center of the brain of the user, the visual sensory cue being synchronized with the first sensory cue so that the chance in position of body member of the performer is virtually indicated in synhronization with the first sensory cue and so that the visual processing center is stimulated with a visual sensor cue in synchronization with a first sensory cue stimulating the first processing center, wherein the synchronization stimulation of the first processing center and the visual processing center is effective for teaching the user to perform a version of the event. | 15. An apparatus, comprising: at least one processors; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: receive a recorded signal, the recorded signal being a signal generated for recording during a performance of an event dependent on a detected change in position of a body member of a performer relative to a performance element of a performance object with which the event was performed; determine the a first sensory cue dependent on the recorded signal; apply the first sensory cue to indicate to a user during a learning session the change in position of the body member of the performer during the performance of the event, wherein the first sensory cue is one of a haptic, auditory and visual sensory cue effective for stimulating a first processing center of a brain of the user; receive a visual sensory data; determine from the received visual sensory data a visual sensory cue capable of being displayed to the user on, a video display device; and display the visual sensory cue to the user during the learning session wherein the visual sensory cue provides a virtual visual indication to the user of the change in position of the body member of the performer during the performance, the visual sensory cue being effective for stimulating the visual processing center of the brain of the user, the visual sensory cue being synchronized with the first sensory cue so that the chance in position of body member of the performer is virtually indicated in synhronization with the first sensory cue and so that the visual processing center is stimulated with a visual sensor cue in synchronization with a first sensory cue stimulating the first processing center, wherein the synchronization stimulation of the first processing center and the visual processing center is effective for teaching the user to perform a version of the event. 17. An apparatus according to claim 15 : wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to further: receive at least one of haptic, auditory and visual data related to the performance of the event; determine at least a second sensory cue dependent on the at least one of haptic, auditory and visual data; and apply, during the learning session, the at least said second sensory cue synchronized with the application of the first sensory cue effective for stimulating at least a second processing center of the brain of the user. | 0.826281 |
8,949,108 | 1 | 11 | 1. An electronic document processing method, comprising steps of: acquiring an electronic template comprising a set of semantic items, wherein (i) candidate values of the set of semantic items and relations among a plurality of semantic items in the set of semantic items are associated with one or more electronic semantic codes, and (ii) the electronic template is associated with a natural language expression mode; receiving an electronic input value for at least one semantic item in the set of semantic items, wherein the electronic input value comprises one or more constituent values; generating a first electronic document comprising (i) a first set of electronic semantic codes corresponding to the electronic input value, (ii) the relations among the plurality of semantic items, and (iii) a second set of electronic semantic codes corresponding to the relations among the plurality of semantic items; and generating, based on the electronic input value and based on the natural language electronic expression mode, a second electronic document comprising the electronic input value. | 1. An electronic document processing method, comprising steps of: acquiring an electronic template comprising a set of semantic items, wherein (i) candidate values of the set of semantic items and relations among a plurality of semantic items in the set of semantic items are associated with one or more electronic semantic codes, and (ii) the electronic template is associated with a natural language expression mode; receiving an electronic input value for at least one semantic item in the set of semantic items, wherein the electronic input value comprises one or more constituent values; generating a first electronic document comprising (i) a first set of electronic semantic codes corresponding to the electronic input value, (ii) the relations among the plurality of semantic items, and (iii) a second set of electronic semantic codes corresponding to the relations among the plurality of semantic items; and generating, based on the electronic input value and based on the natural language electronic expression mode, a second electronic document comprising the electronic input value. 11. The method of claim 1 , wherein the electronic template is generated from a natural language electronic document sample, by a method comprising steps of: displaying the natural language electronic document sample via an electronic display device; selecting an interested sentence element in the natural language electronic document sample as a core concept and as a semantic item in the set of semantic items of the electronic template; determining a relation between a current concept of one or more semantic items in the set of semantic items, and the core concept; searching in a concept library for a qualifier concept, wherein a relation between the qualifier concept and the core concept identical to the relation between the current concept and the core concept; and generating, based on the qualifier concept, candidate values of the one or more semantic items in the set of semantic items. | 0.51919 |
8,566,780 | 15 | 18 | 15. A computer-readable storage device which stores a set of instructions which when executed performs a method for providing object model based mapping, the method executed by the set of instructions comprising: receiving backend data defining data constructs in a backend system, the backend data configured to define the backend system and to define how to access the backend system; receiving entity data defining data constructs in an entity model, the entity data comprising one of the following: entity classes and data logical classes; receiving user selectable elements defining a process associating the backend data with the entity data, the user selectable elements defining a flow chart of the process comprising at least one activity describing the process comprising a state machines process enabling bi-directional data transforms between the backend data and the entity data, the flow chart being configured to be translated to machine code for computer execution and being representative of a work flow between the backend system and the entity model; and producing code, based on the received user selectable elements, configured to implement the process, wherein producing the code comprises producing code that enables the bi-directional data transforms by allowing data flow from the backend system to the entity model and from the entity model to the backend system based on the flow chart process as defined by the user selectable elements. | 15. A computer-readable storage device which stores a set of instructions which when executed performs a method for providing object model based mapping, the method executed by the set of instructions comprising: receiving backend data defining data constructs in a backend system, the backend data configured to define the backend system and to define how to access the backend system; receiving entity data defining data constructs in an entity model, the entity data comprising one of the following: entity classes and data logical classes; receiving user selectable elements defining a process associating the backend data with the entity data, the user selectable elements defining a flow chart of the process comprising at least one activity describing the process comprising a state machines process enabling bi-directional data transforms between the backend data and the entity data, the flow chart being configured to be translated to machine code for computer execution and being representative of a work flow between the backend system and the entity model; and producing code, based on the received user selectable elements, configured to implement the process, wherein producing the code comprises producing code that enables the bi-directional data transforms by allowing data flow from the backend system to the entity model and from the entity model to the backend system based on the flow chart process as defined by the user selectable elements. 18. The computer-readable storage device of claim 15 , wherein receiving the user selectable elements defining the process comprises receiving the user selectable elements defining the process configured to map to a database on the backend system. | 0.686548 |
9,405,532 | 1 | 5 | 1. A multi-tenant data processing system, comprising: one or more business related data processing applications installed in the system and accessible by a plurality of tenants of the multi-tenant data processing system; a data storage element accessible by a plurality of tenants of the multitenant data processing system; a set of software development tools to enable a tenant to develop one or more of a new business related data processing application, an extension to one of the one or more business related data processing applications, a new user interface, an extension to an existing user interface, or content related to an application or user interface; a plurality of language segments in one or more languages stored in the data storage element; and a processor programmed with a set of instructions, wherein when executed by the processor the instructions cause the system to receive a request from a first tenant for a language segment in a specified language; determine if the request can be satisfied by a language segment contained in the data storage element; provide the language segment contained in the data storage element if the request can be satisfied; generate a request for translation services if the request cannot be satisfied by a language segment contained in the data storage element; transfer the request to a provider of the translation services; receive a response to the request from the provider of the translation services; process the received response to validate the contents of the response; provide the translated language segment to the first tenant; determine if the translated language segment is to be stored suitable in the data storage element based on a likelihood of interest for use of content expressed in the translated language for a similar purpose by other tenants of the plurality of tenants; store the translated language segment in the data storage element if the translated language segment meets a threshold for including in the data storage element; receive a request from a second tenant for a language segment in a specified language; and provide the translated language segment received in response to the request for translation services to the second tenant in response to the request from the second tenant. | 1. A multi-tenant data processing system, comprising: one or more business related data processing applications installed in the system and accessible by a plurality of tenants of the multi-tenant data processing system; a data storage element accessible by a plurality of tenants of the multitenant data processing system; a set of software development tools to enable a tenant to develop one or more of a new business related data processing application, an extension to one of the one or more business related data processing applications, a new user interface, an extension to an existing user interface, or content related to an application or user interface; a plurality of language segments in one or more languages stored in the data storage element; and a processor programmed with a set of instructions, wherein when executed by the processor the instructions cause the system to receive a request from a first tenant for a language segment in a specified language; determine if the request can be satisfied by a language segment contained in the data storage element; provide the language segment contained in the data storage element if the request can be satisfied; generate a request for translation services if the request cannot be satisfied by a language segment contained in the data storage element; transfer the request to a provider of the translation services; receive a response to the request from the provider of the translation services; process the received response to validate the contents of the response; provide the translated language segment to the first tenant; determine if the translated language segment is to be stored suitable in the data storage element based on a likelihood of interest for use of content expressed in the translated language for a similar purpose by other tenants of the plurality of tenants; store the translated language segment in the data storage element if the translated language segment meets a threshold for including in the data storage element; receive a request from a second tenant for a language segment in a specified language; and provide the translated language segment received in response to the request for translation services to the second tenant in response to the request from the second tenant. 5. The system of claim 1 , wherein determining if the request can be satisfied by a language segment contained in the data storage element further comprises determining if the data storage element contains a language segment in the specified language that is a match for the requested language segment. | 0.569801 |
4,803,643 | 15 | 25 | 15. A method for converting the graphic illustrations on paper and associated magnetic media retained text typesetting data from which has been derived a printed assemblage of articles, into device independent digital data form retained in master memory, comprising the steps of: identifying the insertion locations within said magnetic media retained text typesetting data for each said graphic illustration and generating a corresponding whatgraph file; scanning each said graphic illustration and deriving digital graphic data corresponding therewith; generating graphic property data representing the graphics size characteristics of said digital graphic data; providing font size data; providing font image defining data; formatting said text typesetting data, said whatgraph file, said graphic property data, and said font size data to provide device independent formatted page files; and combining said device independent formatted page files, said font image defining data, and said digital graphic data in magnetic media for retention in said master memory. | 15. A method for converting the graphic illustrations on paper and associated magnetic media retained text typesetting data from which has been derived a printed assemblage of articles, into device independent digital data form retained in master memory, comprising the steps of: identifying the insertion locations within said magnetic media retained text typesetting data for each said graphic illustration and generating a corresponding whatgraph file; scanning each said graphic illustration and deriving digital graphic data corresponding therewith; generating graphic property data representing the graphics size characteristics of said digital graphic data; providing font size data; providing font image defining data; formatting said text typesetting data, said whatgraph file, said graphic property data, and said font size data to provide device independent formatted page files; and combining said device independent formatted page files, said font image defining data, and said digital graphic data in magnetic media for retention in said master memory. 25. The method of claim 15 including steps of: generating a graphic readout from said digital graphic data, said whatgraph file and said graphic property data for each said graphic illustration; rescanning said grahic illustration in the event of a defect represented in said visual graphic readout; generating a page visual readout from said device independent formatted page files, said font image defining data, and said digital graphic data; and applying corrections to effect alteration of said page visual readout in the event of a defect represented in said page visual readout. | 0.722486 |
8,768,919 | 1 | 2 | 1. A method, comprising: computing a click relevance ranking of a first pair and a second pair based upon user log data, the first pair comprising a query and a first URL, the second pair comprising the query and a second URL, the computing comprising: reducing click bias associated with at least one of the first pair or the second pair by determining a normalized click rate from the user log data; creating, after the reducing, a directed acyclic graph of a relevance relationship between the first pair and the second pair, the directed acyclic graph comprising a representation of at least one of the first URL or the second URL, the representation in the directed acyclic graph directly connected in the directed acyclic graph to a second representation of one or more URLs in the directed acyclic graph; and mapping the directed acyclic graph into a linear ordering to ascertain the click relevance ranking. | 1. A method, comprising: computing a click relevance ranking of a first pair and a second pair based upon user log data, the first pair comprising a query and a first URL, the second pair comprising the query and a second URL, the computing comprising: reducing click bias associated with at least one of the first pair or the second pair by determining a normalized click rate from the user log data; creating, after the reducing, a directed acyclic graph of a relevance relationship between the first pair and the second pair, the directed acyclic graph comprising a representation of at least one of the first URL or the second URL, the representation in the directed acyclic graph directly connected in the directed acyclic graph to a second representation of one or more URLs in the directed acyclic graph; and mapping the directed acyclic graph into a linear ordering to ascertain the click relevance ranking. 2. The method of claim 1 , comprising identifying one or more mislabeled pairs in a pre-existing relevance ranking. | 0.88313 |
9,324,365 | 1 | 2 | 1. A data processor for processing a data stream comprising audio and video data, comprising: an input buffer configured to buffer the data stream; a data stream analyzer programmed and configured to analyze the data stream to find information on a plurality of language-specific contents in different languages; a queuing buffer configured to queue a plurality of parallel queues, each queue including only references to language-specific contents in the same distinct language, wherein the reference point to input buffer items in the input buffer; and a feeder programmed and configured to extract the references to language-specific contents from a selected queue in accordance with a language selection signal and to feed the extracted references to the language-specific contents to subsequent data processing stages, wherein the references to the language-specific contents in a non-selected queue are not fed to the subsequent data processing stages; wherein at least one of the input buffer, the data stream analyzer, the queuing buffer, and the feeder comprises a hardware implementation. | 1. A data processor for processing a data stream comprising audio and video data, comprising: an input buffer configured to buffer the data stream; a data stream analyzer programmed and configured to analyze the data stream to find information on a plurality of language-specific contents in different languages; a queuing buffer configured to queue a plurality of parallel queues, each queue including only references to language-specific contents in the same distinct language, wherein the reference point to input buffer items in the input buffer; and a feeder programmed and configured to extract the references to language-specific contents from a selected queue in accordance with a language selection signal and to feed the extracted references to the language-specific contents to subsequent data processing stages, wherein the references to the language-specific contents in a non-selected queue are not fed to the subsequent data processing stages; wherein at least one of the input buffer, the data stream analyzer, the queuing buffer, and the feeder comprises a hardware implementation. 2. The data processor according to claim 1 , wherein the data stream originates from one of an optical disk, a magnetic disk, a hard drive, a network, a Digital Versatile Disk, and a Blu-ray disk. | 0.766667 |
7,509,572 | 5 | 7 | 5. A computer-implemented method for generating summaries for a plurality of documents comprising text, the method comprising: a) for each document in the plurality of documents, generating text structure tags for the document including generating text structure tags in accordance with Text Encoding Initiative (TEI), the text structure tags identifying a plurality of argumentative text types, wherein a text type comprises a type of argumentative content for an associated portion of a document, the types of argumentative content comprising an argument premise giving support, evidence, or reasoning for or against a conclusion or the conclusion comprising a resulting determination made using one or more argument premises; b) for each document in the plurality of documents, encoding the document to generate a tree structure comprising a plurality of nodes, wherein the nodes correspond with the text types and hierarchical relationships among the nodes reflect argumentative relationships among the text types, and wherein encoding the document comprises mapping a base hierarchical structure, utilizing DTD of the eXtensible Markup Language (“XML”), to reflect said hierarchical relationships; and processing the document to generate the tree structure in accordance with the base hierarchical structure; c) selecting a plurality of tree structures for the plurality of documents; d) combing, as a single logical tree structure, the plurality of tree structures; and e) generating a summary for the plurality of documents by: i) receiving from a user a selection of one or more particular text types for summarization, the one or more particular text types comprising the argument premise text type; and ii) identifying, based upon the text type tags, a set of nodes from the plurality of tree structures corresponding to the one or more selected text types including one or more nodes corresponding to the argument premise text type; and iii) extracting portions of text from the plurality of documents that correspond to the identified set of nodes selected to form the summary of the plurality of documents. | 5. A computer-implemented method for generating summaries for a plurality of documents comprising text, the method comprising: a) for each document in the plurality of documents, generating text structure tags for the document including generating text structure tags in accordance with Text Encoding Initiative (TEI), the text structure tags identifying a plurality of argumentative text types, wherein a text type comprises a type of argumentative content for an associated portion of a document, the types of argumentative content comprising an argument premise giving support, evidence, or reasoning for or against a conclusion or the conclusion comprising a resulting determination made using one or more argument premises; b) for each document in the plurality of documents, encoding the document to generate a tree structure comprising a plurality of nodes, wherein the nodes correspond with the text types and hierarchical relationships among the nodes reflect argumentative relationships among the text types, and wherein encoding the document comprises mapping a base hierarchical structure, utilizing DTD of the eXtensible Markup Language (“XML”), to reflect said hierarchical relationships; and processing the document to generate the tree structure in accordance with the base hierarchical structure; c) selecting a plurality of tree structures for the plurality of documents; d) combing, as a single logical tree structure, the plurality of tree structures; and e) generating a summary for the plurality of documents by: i) receiving from a user a selection of one or more particular text types for summarization, the one or more particular text types comprising the argument premise text type; and ii) identifying, based upon the text type tags, a set of nodes from the plurality of tree structures corresponding to the one or more selected text types including one or more nodes corresponding to the argument premise text type; and iii) extracting portions of text from the plurality of documents that correspond to the identified set of nodes selected to form the summary of the plurality of documents. 7. The method as set forth in claim 5 , wherein: receiving a selection of one or more particular text types for summarization comprises receiving a selection for said conclusion text type for summarization; and extracting portions of text from the plurality of documents comprises extracting portions of text from the plurality of documents that correspond to nodes corresponding to said conclusion text type. | 0.608987 |
9,823,910 | 1 | 2 | 1. A method, comprising: implementing a function not present in a compiler for a first language-using a compiler for a second language, the implementing further comprising: generating, by the compiler for the first language, a first abstract syntax tree; converting the first abstract syntax tree to a second abstract syntax tree of the compiler for the second language using a conversion table; when a compilation error occurs in the compiler for the second language, generating therein a special node for error processing in the second abstract syntax tree and storing an error token indicating information of the compilation error in the special node; and when unparsing by the compiler for the second language, outputting the error token stored in the special node. | 1. A method, comprising: implementing a function not present in a compiler for a first language-using a compiler for a second language, the implementing further comprising: generating, by the compiler for the first language, a first abstract syntax tree; converting the first abstract syntax tree to a second abstract syntax tree of the compiler for the second language using a conversion table; when a compilation error occurs in the compiler for the second language, generating therein a special node for error processing in the second abstract syntax tree and storing an error token indicating information of the compilation error in the special node; and when unparsing by the compiler for the second language, outputting the error token stored in the special node. 2. The method of claim 1 , further comprising generating optimized code for the function in the second language. | 0.831325 |
8,909,566 | 19 | 20 | 19. The non-transitory computer-readable storage medium of claim 12 , wherein the computer system includes a computer resource, and a particular message directed to the computer system comprises machine instructions that attempt to gain access to the computer resource. | 19. The non-transitory computer-readable storage medium of claim 12 , wherein the computer system includes a computer resource, and a particular message directed to the computer system comprises machine instructions that attempt to gain access to the computer resource. 20. The non-transitory computer-readable storage medium of claim 19 , wherein the computer resource is a relational database and the message comprises Structured Query Language. | 0.93665 |
9,619,515 | 10 | 11 | 10. A method of expanding a search, the method comprising: calculating a diversity index for a plurality of query terms included in a plurality of other queries associated with a query, the diversity index being a measure of diversity among the plurality of query terms, the diversity relating to differences among the plurality of query terms; comparing the diversity index to a threshold value; and expanding the query with one or more of the plurality of query terms based on the comparison. | 10. A method of expanding a search, the method comprising: calculating a diversity index for a plurality of query terms included in a plurality of other queries associated with a query, the diversity index being a measure of diversity among the plurality of query terms, the diversity relating to differences among the plurality of query terms; comparing the diversity index to a threshold value; and expanding the query with one or more of the plurality of query terms based on the comparison. 11. The method of claim 10 , wherein the expanding the query is responsive to the diversity index being less than the threshold value. | 0.768966 |
9,922,288 | 20 | 22 | 20. A computer system comprising: a computer having at least one computer processor, wherein the computer is configured to at least: cause a display of at least a portion of a body of text of an electronic document within a first user interface on a display associated with the computer; receive a selection of at least one external resource; receive a selection of at least a portion of the body of text within the first user interface; identify at least two established facts within the selected portion of the body of text using the at least one computer processor; identify a contradiction between the at least two established facts within the body of text using the at least one computer processor; determine whether the at least one external resource comprises information regarding the contradiction; in response to determining that the at least one external resource comprises information regarding the contradiction, generate information regarding a first change to the electronic document based at least in part on the information regarding the contradiction; and cause a display of at least a second user interface on the display, wherein the second user interface is superimposed over at least a portion of the first user interface, and wherein the second user interface comprises at least some of the information regarding the first change to the electronic document to address the contradiction; and receive a first instruction to implement the first change to the electronic document via the second user interface. | 20. A computer system comprising: a computer having at least one computer processor, wherein the computer is configured to at least: cause a display of at least a portion of a body of text of an electronic document within a first user interface on a display associated with the computer; receive a selection of at least one external resource; receive a selection of at least a portion of the body of text within the first user interface; identify at least two established facts within the selected portion of the body of text using the at least one computer processor; identify a contradiction between the at least two established facts within the body of text using the at least one computer processor; determine whether the at least one external resource comprises information regarding the contradiction; in response to determining that the at least one external resource comprises information regarding the contradiction, generate information regarding a first change to the electronic document based at least in part on the information regarding the contradiction; and cause a display of at least a second user interface on the display, wherein the second user interface is superimposed over at least a portion of the first user interface, and wherein the second user interface comprises at least some of the information regarding the first change to the electronic document to address the contradiction; and receive a first instruction to implement the first change to the electronic document via the second user interface. 22. The computer system of claim 20 , wherein the computer is further configured to at least: in response to determining that the at least one external resource does not comprise information regarding the contradiction, cause a display of at least a third user interface on the at least one computer display, wherein the third user interface is superimposed over at least a portion of the first user interface, and wherein the third user interface comprises a request for a second change to the electronic document to address the contradiction; and receive a second instruction to implement the second change to the electronic document via the third user interface; and implement the second change to the electronic document. | 0.513423 |
7,849,398 | 1 | 4 | 1. A method for selecting fields of an electronic form for automatic population with candidate text segments that are obtained by capturing an image of a document, applying optical character recognition to the captured image to identify textual content, and tagging candidate text segments in the textual content for fields of the form, the method comprising: for each of a plurality of fields of an electronic form, estimating a manual entry time and a manual correction time for the field, wherein the estimated manual entry time is an estimated time period for a user to enter a text segment into the field without automatic population and the estimated manual correction time is an estimated time period for a user to correct a text segment in the field after automatic population; computing a field exclusion function based on the estimated manual entry time and the estimated manual correction time, the computation of the field exclusion function further based on at least one parameter selected from: a text length parameter, an optical character recognition error rate, a computed tagging error rate, and a field relevance parameter which has been assigned to a respective field; and determining whether to select the field for automatic population based on the computed field exclusion function. | 1. A method for selecting fields of an electronic form for automatic population with candidate text segments that are obtained by capturing an image of a document, applying optical character recognition to the captured image to identify textual content, and tagging candidate text segments in the textual content for fields of the form, the method comprising: for each of a plurality of fields of an electronic form, estimating a manual entry time and a manual correction time for the field, wherein the estimated manual entry time is an estimated time period for a user to enter a text segment into the field without automatic population and the estimated manual correction time is an estimated time period for a user to correct a text segment in the field after automatic population; computing a field exclusion function based on the estimated manual entry time and the estimated manual correction time, the computation of the field exclusion function further based on at least one parameter selected from: a text length parameter, an optical character recognition error rate, a computed tagging error rate, and a field relevance parameter which has been assigned to a respective field; and determining whether to select the field for automatic population based on the computed field exclusion function. 4. The method of claim 1 , wherein the optical character recognition error rate is estimated from information provided by an optical character recognition device. | 0.778689 |
7,890,499 | 29 | 31 | 29. The method of claim 1 , further comprising: identifying, by the search engine, the resources from a corpus of resources that are responsive to the search query; identifying the particular subject matter based on the first results; and selecting the particular collection of records from among the multiple collection of records. | 29. The method of claim 1 , further comprising: identifying, by the search engine, the resources from a corpus of resources that are responsive to the search query; identifying the particular subject matter based on the first results; and selecting the particular collection of records from among the multiple collection of records. 31. The method of claim 29 , wherein identifying the particular subject matter based on the first search results further comprises: determining that one or more of the first search results refer to one or more records of the particular collection of records. | 0.936827 |
9,881,616 | 16 | 17 | 16. The apparatus according to claim 13 , wherein said voice biometrics system is configured to determine, at predefined intervals during said provision of the audio signal by the directional sound capturing system, that sound within the received at least one microphone output signal matches the voice model. | 16. The apparatus according to claim 13 , wherein said voice biometrics system is configured to determine, at predefined intervals during said provision of the audio signal by the directional sound capturing system, that sound within the received at least one microphone output signal matches the voice model. 17. The apparatus according to claim 16 , wherein said predefined intervals are predetermined amounts of time. | 0.970714 |
7,814,116 | 1 | 18 | 1. A computer system for electronically delivering personalized periodic news digest documents to a plurality of registered users, the computer system comprising: at least one processor arranged to: receive a delivery preference of each of the plurality of the registered users, the delivery preference indicating how each registered user desires to receive the personalized periodic news digest document, wherein a registered user is one who has registered personal information in a user profile, said personal information comprising the registered user's name, age, sex, zip code, time zone, and email; receive the personal information of each registered user and a news article preference of the registered use, wherein the news article preference comprises sports, local and foreign affairs, and legal; search at least one location for news items that match the at least one of: the personal information and the news article preference of the registered user; receive the news items that match; automatically generate, from the matching news items that are received, a print-ready personalized periodic news digest document that comprises the matching news items, the personalized periodic news digest document being generated as a document selected from a group consisting of: an email, a web page, an electronic file, and a fax, in accordance with the delivery preference of the registered user; and electronically push the personalized periodic news digest document directly to the registered user in accordance with the delivery preference of said registered user; wherein the news article preference indicates at least one type of news article that the registered user desires to receive. | 1. A computer system for electronically delivering personalized periodic news digest documents to a plurality of registered users, the computer system comprising: at least one processor arranged to: receive a delivery preference of each of the plurality of the registered users, the delivery preference indicating how each registered user desires to receive the personalized periodic news digest document, wherein a registered user is one who has registered personal information in a user profile, said personal information comprising the registered user's name, age, sex, zip code, time zone, and email; receive the personal information of each registered user and a news article preference of the registered use, wherein the news article preference comprises sports, local and foreign affairs, and legal; search at least one location for news items that match the at least one of: the personal information and the news article preference of the registered user; receive the news items that match; automatically generate, from the matching news items that are received, a print-ready personalized periodic news digest document that comprises the matching news items, the personalized periodic news digest document being generated as a document selected from a group consisting of: an email, a web page, an electronic file, and a fax, in accordance with the delivery preference of the registered user; and electronically push the personalized periodic news digest document directly to the registered user in accordance with the delivery preference of said registered user; wherein the news article preference indicates at least one type of news article that the registered user desires to receive. 18. The computer system according to claim 1 , wherein the at least one processor is further arranged to: analyze at least one of: the personal information and the news article preference to determine an advertisement to be included within the personalized periodic news digest document; and select a location within the personalized periodic news digest document for the advertisement based on where one of the content items will appear in the personalized periodic news digest document, wherein the print-ready personalized periodic news digest document that is generated also includes the advertisement at the location that is selected. | 0.607494 |
7,725,307 | 18 | 27 | 18. A method of recognizing a speech query comprising the steps of: (a) recognizing text in an articulated speech utterance; and (b) processing said recognized text to generate at least two different types of search predicates for said articulate speech utterance; wherein said search predicates correspond to logical operators to be satisfied by a potential recognition match; (c) generating a query to identify a potential match for said speech utterance, said query being based on said recognized text and said search predicates; (d) determining a final match for said speech utterance by comparing any potential matches identified by said query with said articulated speech utterance; wherein both semantic decoding and statistical based processing operations are used to determine said final match; further wherein said semantic decoding is performed on entire word sentences contained in said articulated speech utterance to determine semantic variants of said word sentences in said potential matches, and is based on a combined metric that includes term frequency, semantic coverage, and semantic distance, the semantic decoding using a lexical dictionary. | 18. A method of recognizing a speech query comprising the steps of: (a) recognizing text in an articulated speech utterance; and (b) processing said recognized text to generate at least two different types of search predicates for said articulate speech utterance; wherein said search predicates correspond to logical operators to be satisfied by a potential recognition match; (c) generating a query to identify a potential match for said speech utterance, said query being based on said recognized text and said search predicates; (d) determining a final match for said speech utterance by comparing any potential matches identified by said query with said articulated speech utterance; wherein both semantic decoding and statistical based processing operations are used to determine said final match; further wherein said semantic decoding is performed on entire word sentences contained in said articulated speech utterance to determine semantic variants of said word sentences in said potential matches, and is based on a combined metric that includes term frequency, semantic coverage, and semantic distance, the semantic decoding using a lexical dictionary. 27. The method of claim 18 , wherein said final match is also based on evaluating a degree of coverage of N words presented in said utterance with each of said one or more corresponding recognized matches having one or more variable word lengths. | 0.795 |
10,027,688 | 12 | 13 | 12. A computerized system for performing malware analysis on at least one guest environment, the system comprising: at least one server coupled to at least one network; at least one user terminal coupled to the at least one network; at least one application coupled to the at least one server and/or the at least one user terminal, wherein the at least one application is configured for: performing processing associated with collecting at least one domain name by monitoring Domain Name System (DNS) traffic in at least one network; performing processing associated with obtaining information about the at least one domain name, wherein the information is utilized to classify the at least one domain name, and the information is information about the at least one domain name in at least one domain name white list; wherein the obtained information further comprises statistics related to the at least one domain name comprising a total number of queries to the at least one domain name during the time period and a total number of distinct source IP addresses that queried the at least one domain name during the time period; responsive to determining that the at least one domain name is not in the at least one domain name white list, performing processing associated with automatically obtaining, using at least one Internet search engine, search results for the at least one domain name; performing processing associated with analyzing the search results to determine whether at least one search result associated with the at least one domain name comprises a known malware site; and performing processing associated with determining at least one likelihood that the at least one domain name is being used as at least one command and control domain for at least one botnet based at least in part on the analyzed search results. | 12. A computerized system for performing malware analysis on at least one guest environment, the system comprising: at least one server coupled to at least one network; at least one user terminal coupled to the at least one network; at least one application coupled to the at least one server and/or the at least one user terminal, wherein the at least one application is configured for: performing processing associated with collecting at least one domain name by monitoring Domain Name System (DNS) traffic in at least one network; performing processing associated with obtaining information about the at least one domain name, wherein the information is utilized to classify the at least one domain name, and the information is information about the at least one domain name in at least one domain name white list; wherein the obtained information further comprises statistics related to the at least one domain name comprising a total number of queries to the at least one domain name during the time period and a total number of distinct source IP addresses that queried the at least one domain name during the time period; responsive to determining that the at least one domain name is not in the at least one domain name white list, performing processing associated with automatically obtaining, using at least one Internet search engine, search results for the at least one domain name; performing processing associated with analyzing the search results to determine whether at least one search result associated with the at least one domain name comprises a known malware site; and performing processing associated with determining at least one likelihood that the at least one domain name is being used as at least one command and control domain for at least one botnet based at least in part on the analyzed search results. 13. The system of claim 12 , wherein the at least one domain name is monitored and statistics are gathered related to the at least one domain name. | 0.822034 |
7,505,463 | 1 | 8 | 1. A method, comprising: receiving a plurality of packet flow rules from multiple network services, wherein each packet flow rule comprises a packet filter and an action list including one or more prioritized actions, wherein each network service has a priority, and wherein the packet flow rules from each network service comprise a priority expressed either by longest prefix, or ordered precedence; generating a unified rule set according to the received packet flow rules, wherein said generating comprises: identifying conflicts between rule pairs, wherein each rule pair includes a higher priority rule and a lower priority rule; and resolving the identified conflicts according to a priority relationship between the higher priority rule and the lower priority rule. | 1. A method, comprising: receiving a plurality of packet flow rules from multiple network services, wherein each packet flow rule comprises a packet filter and an action list including one or more prioritized actions, wherein each network service has a priority, and wherein the packet flow rules from each network service comprise a priority expressed either by longest prefix, or ordered precedence; generating a unified rule set according to the received packet flow rules, wherein said generating comprises: identifying conflicts between rule pairs, wherein each rule pair includes a higher priority rule and a lower priority rule; and resolving the identified conflicts according to a priority relationship between the higher priority rule and the lower priority rule. 8. The method of claim 1 , wherein the priority of each of the rules is based upon one or more of the following: a priority associated with the network service from which the rule originated; the length of the prefix specified by the packet filter of the rule; and the order in which the rule was received from its originating network service. | 0.769489 |
7,698,315 | 1 | 5 | 1. A method for an advertising campaign management system, the method comprising: storing account information for one or more advertisers; in association with account information, storing data defining a plurality of advertisements associated with an advertiser, the data being linked together as an advertising group, to include at least one advertisement category, according to a grouping indication received from the advertiser; producing a display for a computer display device showing the account information along with the associated data for the advertising group when the account information is accessed by the advertiser, wherein the display includes a quick-fill button to simultaneously set a category for a plurality of displayed advertisements; and enabling the advertiser to simultaneously modify a plurality of advertisements, to include simultaneously setting a category for the plurality of advertisements with the quick-fill button, wherein submission of a modification through the display operates commonly on the plurality of advertisements in response to information received from the advertiser. | 1. A method for an advertising campaign management system, the method comprising: storing account information for one or more advertisers; in association with account information, storing data defining a plurality of advertisements associated with an advertiser, the data being linked together as an advertising group, to include at least one advertisement category, according to a grouping indication received from the advertiser; producing a display for a computer display device showing the account information along with the associated data for the advertising group when the account information is accessed by the advertiser, wherein the display includes a quick-fill button to simultaneously set a category for a plurality of displayed advertisements; and enabling the advertiser to simultaneously modify a plurality of advertisements, to include simultaneously setting a category for the plurality of advertisements with the quick-fill button, wherein submission of a modification through the display operates commonly on the plurality of advertisements in response to information received from the advertiser. 5. The method of claim 1 wherein producing a display comprises: producing a display showing a menu selector for actuation by the advertiser to switch between multiple accounts; and producing a display showing details of each account upon actuation of the menu selector. | 0.720374 |
9,658,988 | 26 | 28 | 26. The system of claim 22 , wherein a second regular expression in the plurality of regular expressions matches a Chinese, Japanese, or Korean word. | 26. The system of claim 22 , wherein a second regular expression in the plurality of regular expressions matches a Chinese, Japanese, or Korean word. 28. The system of claim 26 , wherein the word cannot follow a line break. | 0.973102 |
7,644,391 | 8 | 9 | 8. The system of claim 7 wherein the user display further comprises a third user interface corresponding to a part picker, the secondary user interface of the gadget being rendered within the third user interface. | 8. The system of claim 7 wherein the user display further comprises a third user interface corresponding to a part picker, the secondary user interface of the gadget being rendered within the third user interface. 9. The system of claim 8 wherein selection of the gadget via the third user interface causes the gadget to be rendered within the host user interface. | 0.963271 |
10,083,398 | 7 | 9 | 7. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: generating a plurality of term tokens from a plurality of terms that are located at a plurality of term locations in an original text stream; generating a plurality of annotation tokens from a plurality of annotations corresponding to the plurality of terms, wherein each of the plurality of annotation tokens includes term location information based on one or more of the plurality of term locations of its corresponding one or more of the plurality of terms; generating a knowledge structure that stores the plurality of term tokens in a plurality of original text fields and stores the plurality of annotation tokens in a plurality of parallel fields, wherein each of the plurality of annotation tokens align to at least one of the plurality of original text fields based upon its corresponding term location information; receiving a search request that comprises a set of query terms, a set of query annotation types, and a relative annotation position parameter; creating a plurality of sub queries based on the set of query terms and the set of query annotation types; searching the knowledge structure using the plurality of sub queries, resulting in one or more term token matches and one or more annotation token matches; and generating search results based upon the one or more term token matches and the one or more annotation token matches, wherein the generation of the search results further comprises: determining that a first one of the plurality of annotation tokens corresponds to one of the plurality of sub queries; identifying a position increment value corresponding to the first annotation token, wherein the position increment value indicates a relative position of the first annotation token to a second annotation token; and including the first annotation token in the search results in response to determining that the position increment value adheres to the relative annotation position parameter. | 7. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; and a set of computer program instructions stored in the memory and executed by at least one of the processors in order to perform actions of: generating a plurality of term tokens from a plurality of terms that are located at a plurality of term locations in an original text stream; generating a plurality of annotation tokens from a plurality of annotations corresponding to the plurality of terms, wherein each of the plurality of annotation tokens includes term location information based on one or more of the plurality of term locations of its corresponding one or more of the plurality of terms; generating a knowledge structure that stores the plurality of term tokens in a plurality of original text fields and stores the plurality of annotation tokens in a plurality of parallel fields, wherein each of the plurality of annotation tokens align to at least one of the plurality of original text fields based upon its corresponding term location information; receiving a search request that comprises a set of query terms, a set of query annotation types, and a relative annotation position parameter; creating a plurality of sub queries based on the set of query terms and the set of query annotation types; searching the knowledge structure using the plurality of sub queries, resulting in one or more term token matches and one or more annotation token matches; and generating search results based upon the one or more term token matches and the one or more annotation token matches, wherein the generation of the search results further comprises: determining that a first one of the plurality of annotation tokens corresponds to one of the plurality of sub queries; identifying a position increment value corresponding to the first annotation token, wherein the position increment value indicates a relative position of the first annotation token to a second annotation token; and including the first annotation token in the search results in response to determining that the position increment value adheres to the relative annotation position parameter. 9. The information handling system of claim 7 wherein the one or more processors perform additional actions comprising: adding a first set of parallel fields to the knowledge structure, the first set of parallel fields comprised in the plurality of parallel fields; indexing a first set of annotation tokens corresponding to the first annotation type into the first set of parallel fields; adding a second set of parallel fields to the knowledge structure, the second set of parallel fields comprised in the plurality of parallel fields; and indexing a second set of annotation tokens corresponding to the second annotation type into the second set of parallel fields, wherein the first set of annotation tokens and the second set of annotation tokens are included in the plurality of annotation tokens. | 0.500622 |
8,229,952 | 15 | 16 | 15. A system comprising: a database of physical data tables; a logical database schema of logical tables associated with the physical data tables; an abstraction layer comprising a plurality of objects mapped to the logical tables and one or more properties associating one or more of the plurality of objects to one or more others of the plurality of objects; and a query generator to: receive a query comprising a first plurality of objects of the abstraction layer, and a first one or more properties associating one of the first plurality of objects with another one of the plurality of objects, the query comprising two or more instances of a first one of the first plurality of objects; modify a dynamic representation of the logical database schema to include an alias of the first one of the plurality of objects; modify the query to include the alias; identify one or more functional dependencies of the abstraction layer within a reverse chain or a direct chain of the modified query, or relating to initial objects of the modified query; edit the modified dynamic representation by removing joins of the modified dynamic representation of logical database schema associated with non-identified functional dependencies of the modified query; and generate a database query based on the modified query and the edited dynamic representation. | 15. A system comprising: a database of physical data tables; a logical database schema of logical tables associated with the physical data tables; an abstraction layer comprising a plurality of objects mapped to the logical tables and one or more properties associating one or more of the plurality of objects to one or more others of the plurality of objects; and a query generator to: receive a query comprising a first plurality of objects of the abstraction layer, and a first one or more properties associating one of the first plurality of objects with another one of the plurality of objects, the query comprising two or more instances of a first one of the first plurality of objects; modify a dynamic representation of the logical database schema to include an alias of the first one of the plurality of objects; modify the query to include the alias; identify one or more functional dependencies of the abstraction layer within a reverse chain or a direct chain of the modified query, or relating to initial objects of the modified query; edit the modified dynamic representation by removing joins of the modified dynamic representation of logical database schema associated with non-identified functional dependencies of the modified query; and generate a database query based on the modified query and the edited dynamic representation. 16. A system according to claim 15 , wherein modification of the query to include the alias comprises replacement of one of the two or more instances of the first one of the first plurality of objects with the alias. | 0.876005 |
9,633,671 | 1 | 2 | 1. A media device having a loudspeaker, a microphone, and a digital signal processor comprising: an echo canceller arranged to receive an input signal from the microphone and to receive a reference signal, wherein the echo canceller is configured to subtract one or more linear components of the reference signal from the input signal; a noise suppressor configured to suppress non-linear effects of the reference signal in each of a plurality of frequency bins in the input signal, wherein a degree of suppression provided by the noise suppressor for each frequency bin corresponds to an estimate of residual echo remaining in the respective frequency bin after the one or more linear components of the reference signal have been subtracted from the input signal, to an estimated double-talk probability, and to an estimated signal-to-noise ratio of near-end speech in the input signal for each respective frequency bin; and a speech recognizer arranged to receive a processed input signal from the noise suppressor and to recognize an utterance from the processed input signal, wherein the media device is configured to be controlled responsively to the cognized utterance. | 1. A media device having a loudspeaker, a microphone, and a digital signal processor comprising: an echo canceller arranged to receive an input signal from the microphone and to receive a reference signal, wherein the echo canceller is configured to subtract one or more linear components of the reference signal from the input signal; a noise suppressor configured to suppress non-linear effects of the reference signal in each of a plurality of frequency bins in the input signal, wherein a degree of suppression provided by the noise suppressor for each frequency bin corresponds to an estimate of residual echo remaining in the respective frequency bin after the one or more linear components of the reference signal have been subtracted from the input signal, to an estimated double-talk probability, and to an estimated signal-to-noise ratio of near-end speech in the input signal for each respective frequency bin; and a speech recognizer arranged to receive a processed input signal from the noise suppressor and to recognize an utterance from the processed input signal, wherein the media device is configured to be controlled responsively to the cognized utterance. 2. A media device according to claim 1 , wherein the noise suppressor applies a spectral gain or a binary mask to the input signal in correspondence with the estimated signal-to-noise ratio of near-end speech in the input signal. | 0.76046 |
9,002,821 | 8 | 9 | 8. A computer-implemented method performed by data processing apparatus comprising one or more computers in data communication, the method comprising: receiving first search results responsive to a search query, each of the search results referencing a resource that can be rendered in a browser application on a user device and including a link to the resource, the first search results generated in response to a search of a first index of resources that can be rendered in the browser application; receiving at least one second search result responsive to the query, the second search result specifying a native application operating independent of a browser application that can operate on the user device, the second search result generated in response to a search of a second index of application pages that can be display on a user device within the native application, wherein the second index includes a combination of a uniform resource identifiers (URI) of the application pages and a unique application identifier that identifies the native application; and providing the first search results and the second search result for display on a user device. | 8. A computer-implemented method performed by data processing apparatus comprising one or more computers in data communication, the method comprising: receiving first search results responsive to a search query, each of the search results referencing a resource that can be rendered in a browser application on a user device and including a link to the resource, the first search results generated in response to a search of a first index of resources that can be rendered in the browser application; receiving at least one second search result responsive to the query, the second search result specifying a native application operating independent of a browser application that can operate on the user device, the second search result generated in response to a search of a second index of application pages that can be display on a user device within the native application, wherein the second index includes a combination of a uniform resource identifiers (URI) of the application pages and a unique application identifier that identifies the native application; and providing the first search results and the second search result for display on a user device. 9. The computer-implemented method of claim 8 , wherein the second search result includes an image of an application page that includes content responsive to the search query and selection data that causes, in response to a selection of the image at the user device, the native application to launch and generate an instance of the application page that includes content that is relevant to the search query. | 0.621521 |
9,558,264 | 1 | 9 | 1. A method, in a data processing system, for identifying commonalities between candidate answers generated by a Question and Answer (QA) system in response to an input question, the method comprising: receiving, by the data processing system, a plurality of candidate answers for an input question from the QA system; identifying, by the data processing system, terms present in the candidate answers; determining, by the data processing system, relationships between terms in each of the candidate answers; determining, by the data processing system, a common relationship between a first term and a second term, the common relationship being common amongst at least a subset of the plurality of candidate answers, based on the determined relationships between terms in each of the candidate answers; and presenting, by the data processing system, the plurality of candidate answers and the common relationship to a user. | 1. A method, in a data processing system, for identifying commonalities between candidate answers generated by a Question and Answer (QA) system in response to an input question, the method comprising: receiving, by the data processing system, a plurality of candidate answers for an input question from the QA system; identifying, by the data processing system, terms present in the candidate answers; determining, by the data processing system, relationships between terms in each of the candidate answers; determining, by the data processing system, a common relationship between a first term and a second term, the common relationship being common amongst at least a subset of the plurality of candidate answers, based on the determined relationships between terms in each of the candidate answers; and presenting, by the data processing system, the plurality of candidate answers and the common relationship to a user. 9. The method of claim 1 , wherein determining a common relationship between the first term and the second term further comprises: presenting a graphical user interface (GUI) providing a first portion of the GUI for outputting the candidate answers, a second portion of the GUI for outputting a plurality of user selectable options for specifying a desired common relationship that a user wishes to have identified between the candidate answers, a third portion of the GUI for outputting the relationships between terms in the candidate answers and the common relationship, and a fourth portion of the GUI for outputting evidence text passages from documents of a corpus that support the common relationship. | 0.500705 |
9,633,674 | 11 | 12 | 11. The method of claim 1 , further comprising: upon determining that the user interaction indicates an absence of a problem, performing at least one of: avoiding to store the information relating to the request in the repository, and removing the information relating to the request from the repository. | 11. The method of claim 1 , further comprising: upon determining that the user interaction indicates an absence of a problem, performing at least one of: avoiding to store the information relating to the request in the repository, and removing the information relating to the request from the repository. 12. The method of claim 11 , wherein performing at least one of: avoiding to store the information relating to the request in the repository, and removing the information relating to the request from the repository comprises: if the information relating to the request is absent in the repository, avoiding to store information relating to the request in the repository; or if the information relating to the request is stored in the repository, removing the information relating to the request from the repository. | 0.704023 |
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