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8,495,210 | 8 | 10 | 8. A method according to claim 1 wherein, said analyzing the selected article comprises determining a readability metric for comparison of readability among articles. | 8. A method according to claim 1 wherein, said analyzing the selected article comprises determining a readability metric for comparison of readability among articles. 10. A method according to claim 8 , wherein analyzing the selected article includes determining a readability metric of lexical density based at least in part on determining a ratio of content words divided by a total number of words of the selected article. | 0.5 |
7,546,578 | 1 | 3 | 1. A system for providing mathematical modeling in an object-oriented software environment, comprising: a processor operable to execute instructions contained in computer program code; and at least one computer readable medium including instructions in an object-oriented programming language that, when executed by the processor, cause the processor to: provide at least one library including a model class that when instantiated as a model object provides an interface allowing user interaction with a mathematical programming model, the mathematical programming model configured for generating a solution for a mathematical decision making problem; generate a numerical model, based on instance data associated with one or more parameters and one or more index sets of the mathematical programming model; solve the mathematical programming model using a selected solver running in the object-oriented programming language; and output a result of the solving process, wherein the model class instantiated as a user interface object comprises a set of methods to allow a user to add/remove mathematical expressions, constraints, or objective functions to/from the mathematical programming model, pass the instance data to a selected solver for solving the mathematical programming model, solve the numerical model through the solver and return the solution, and update the mathematical programming model with at least one incremental change to be passed to the selected solver. | 1. A system for providing mathematical modeling in an object-oriented software environment, comprising: a processor operable to execute instructions contained in computer program code; and at least one computer readable medium including instructions in an object-oriented programming language that, when executed by the processor, cause the processor to: provide at least one library including a model class that when instantiated as a model object provides an interface allowing user interaction with a mathematical programming model, the mathematical programming model configured for generating a solution for a mathematical decision making problem; generate a numerical model, based on instance data associated with one or more parameters and one or more index sets of the mathematical programming model; solve the mathematical programming model using a selected solver running in the object-oriented programming language; and output a result of the solving process, wherein the model class instantiated as a user interface object comprises a set of methods to allow a user to add/remove mathematical expressions, constraints, or objective functions to/from the mathematical programming model, pass the instance data to a selected solver for solving the mathematical programming model, solve the numerical model through the solver and return the solution, and update the mathematical programming model with at least one incremental change to be passed to the selected solver. 3. The system of claim 1 , wherein the model object stores, as data members of the model class, one or more abstract formulas associated with the model object without incurring storage costs associated with a numerical instance of the mathematical programming model. | 0.838396 |
7,747,626 | 12 | 13 | 12. The media of claim 11 , wherein the one or more different results are created based on a clustering algorithm associated with the search engine. | 12. The media of claim 11 , wherein the one or more different results are created based on a clustering algorithm associated with the search engine. 13. The media of claim 12 , wherein the one or more different results are selected from a group including manufacturer websites, shopping websites, product review websites, and discussion groups. | 0.5 |
7,840,546 | 70 | 72 | 70. The method in claim 64 , wherein said Inter-Node Consolidation is set up by communicating updated Consolidation Strings to another data-source node in a peer-to-peer fashion. | 70. The method in claim 64 , wherein said Inter-Node Consolidation is set up by communicating updated Consolidation Strings to another data-source node in a peer-to-peer fashion. 72. The method in claim 70 , wherein said peer-to-peer communication of updated Consolidation Strings occurs in a batch process via network communications substantially simultaneously from the communication-originating data-source node to another data-source node. | 0.547945 |
6,016,499 | 1 | 2 | 1. 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; 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 result, 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. | 1. 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; 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 result, 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. 2. The system of claim 1, wherein the directory services repository includes a Novell Directory Services repository and the API includes a Novell Directory Services API. | 0.797362 |
9,087,140 | 5 | 6 | 5. The computer program product of claim 1 , wherein the computer readable program code is further configured to: in response to a request for processing the XML document, retrieve the XML document and the indices associated with the XML document; and use the indices to process the XML document. | 5. The computer program product of claim 1 , wherein the computer readable program code is further configured to: in response to a request for processing the XML document, retrieve the XML document and the indices associated with the XML document; and use the indices to process the XML document. 6. The computer program product of claim 5 , wherein using the indices comprises the computer readable program code being further configured to: determine a number N that is a number of XML consumers available to process the XML document; analyze the indices associated with the XML document to generate N partitions of the XML document without parsing; and process the partitions in parallel, wherein each XML consumer processes one of the partitions. | 0.5 |
9,406,089 | 14 | 15 | 14. The computer-implemented method of claim 1 , further comprising the video/voice processor synchronizing or associating the plurality of video frames and the voice data. | 14. The computer-implemented method of claim 1 , further comprising the video/voice processor synchronizing or associating the plurality of video frames and the voice data. 15. The computer-implemented method of claim 14 , the plurality of video frames and the voice data being synchronized by the video/voice processor based at least in part upon respective elapsed times from a first video frame and a beginning of the voice data. | 0.599071 |
7,698,328 | 15 | 18 | 15. A system, comprising: one or more computers configured to perform operations including: receiving a first search query including one or more search terms; providing a first set of documents responsive to the first query; determining one or more collocations from the first set of documents that include at least one of the search terms, each collocation including at least one other term that is semantically related to the at least one search term; scoring the collocations from the first set of documents, including determining a mutual information score for each collocation using a mutual information test; multiplying at least some collocation scores by frequency counts, a frequency count for a given collocation representing a number of times the collocation occurs in a document of the first set of documents; determining a subset of the first set of documents to present to a user based on the scored collocations; providing one or more user interface elements to be used by a user to include and exclude documents from the first set of documents that contain at least one specified collocation of the collocations; receiving user input specifying inclusion or exclusion of documents from the first set of documents that contain at least one of the collocations; refining the first search query to produce a second query based on the user input; and providing a second set of documents responsive to the second query, where the second set of documents includes or excludes documents containing the specified collocation. | 15. A system, comprising: one or more computers configured to perform operations including: receiving a first search query including one or more search terms; providing a first set of documents responsive to the first query; determining one or more collocations from the first set of documents that include at least one of the search terms, each collocation including at least one other term that is semantically related to the at least one search term; scoring the collocations from the first set of documents, including determining a mutual information score for each collocation using a mutual information test; multiplying at least some collocation scores by frequency counts, a frequency count for a given collocation representing a number of times the collocation occurs in a document of the first set of documents; determining a subset of the first set of documents to present to a user based on the scored collocations; providing one or more user interface elements to be used by a user to include and exclude documents from the first set of documents that contain at least one specified collocation of the collocations; receiving user input specifying inclusion or exclusion of documents from the first set of documents that contain at least one of the collocations; refining the first search query to produce a second query based on the user input; and providing a second set of documents responsive to the second query, where the second set of documents includes or excludes documents containing the specified collocation. 18. The system of claim 15 , the operations further comprising: filtering the collocations based on the frequency count. | 0.730942 |
7,953,694 | 1 | 4 | 1. A computer-implemented method for specifying on-line analytical processing multidimensional calculations, comprising: accessing, using a computer including a processor, measures that include symmetric and asymmetric measures, wherein each of the symmetric measures have a single aggregation, and wherein each of the asymmetric measures have multiple aggregations, wherein a measure is defined by one or more structured query language expressions and wherein the one or more structured query language expressions are used as input to an aggregation of the measure; selecting each of the symmetric and asymmetric measures one at a time; and for the selected one of the symmetric and asymmetric measures, determining whether the selected measure is compatible with previously selected measures, wherein compatible measures have a same specification of aggregation order for dimensions that the measures reference; in response to determining that the selected measure is compatible, selecting another of the symmetric and asymmetric measures; and in response to determining that the selected measure is not compatible, determining whether one or more measures of the symmetric and asymmetric measures can be rewritten so that the selected measure is compatible with the previously selected measures; in response to determining that the one or more measures of the symmetric and asymmetric measures can be rewritten, rewriting the one or more measures of the symmetric and asymmetric measures; and in response to determining that the one or more measures of the symmetric and asymmetric measures cannot be rewritten, generating a first structured query language statement for the symmetric measures; generating a second structured query language statement for the asymmetric measures; and combining the first structured query language statement and the second structured query language statement for the symmetric and asymmetric measures into a single structured query language statement. | 1. A computer-implemented method for specifying on-line analytical processing multidimensional calculations, comprising: accessing, using a computer including a processor, measures that include symmetric and asymmetric measures, wherein each of the symmetric measures have a single aggregation, and wherein each of the asymmetric measures have multiple aggregations, wherein a measure is defined by one or more structured query language expressions and wherein the one or more structured query language expressions are used as input to an aggregation of the measure; selecting each of the symmetric and asymmetric measures one at a time; and for the selected one of the symmetric and asymmetric measures, determining whether the selected measure is compatible with previously selected measures, wherein compatible measures have a same specification of aggregation order for dimensions that the measures reference; in response to determining that the selected measure is compatible, selecting another of the symmetric and asymmetric measures; and in response to determining that the selected measure is not compatible, determining whether one or more measures of the symmetric and asymmetric measures can be rewritten so that the selected measure is compatible with the previously selected measures; in response to determining that the one or more measures of the symmetric and asymmetric measures can be rewritten, rewriting the one or more measures of the symmetric and asymmetric measures; and in response to determining that the one or more measures of the symmetric and asymmetric measures cannot be rewritten, generating a first structured query language statement for the symmetric measures; generating a second structured query language statement for the asymmetric measures; and combining the first structured query language statement and the second structured query language statement for the symmetric and asymmetric measures into a single structured query language statement. 4. The method of claim 1 , wherein each of the one or more structured query language expressions includes a list of columns, attributes, and measures. | 0.765625 |
9,703,673 | 1 | 2 | 1. A system for setting a stack pattern breakpoint for a COBOL program, the system comprising: a processor in communication with one or more types of memory, the processor configured to: provide a static program control flow view of a plurality of COBOL paragraphs of the COBOL program, enable a user to select the stack pattern using the static program control flow view of the plurality of COBOL paragraphs of the COBOL program, and set the stack pattern breakpoint in source code of the COBOL program using information from a compiler compiling the COBOL program to create a pseudo-stack that can be operated on by a debugger to evaluate stack pattern conditions for the plurality of COBOL paragraphs, wherein setting the stack pattern breakpoint further comprises finding a perform save cells section using the information from the compiler to find a plurality of save cells, scanning the plurality of save cells and associating each of the plurality of save cells with at least one of the plurality of paragraphs, and, responsive to a perform being executed, modifying at least one of the save cells to point back to the perform save cells. | 1. A system for setting a stack pattern breakpoint for a COBOL program, the system comprising: a processor in communication with one or more types of memory, the processor configured to: provide a static program control flow view of a plurality of COBOL paragraphs of the COBOL program, enable a user to select the stack pattern using the static program control flow view of the plurality of COBOL paragraphs of the COBOL program, and set the stack pattern breakpoint in source code of the COBOL program using information from a compiler compiling the COBOL program to create a pseudo-stack that can be operated on by a debugger to evaluate stack pattern conditions for the plurality of COBOL paragraphs, wherein setting the stack pattern breakpoint further comprises finding a perform save cells section using the information from the compiler to find a plurality of save cells, scanning the plurality of save cells and associating each of the plurality of save cells with at least one of the plurality of paragraphs, and, responsive to a perform being executed, modifying at least one of the save cells to point back to the perform save cells. 2. The system of claim 1 , wherein the processor is further configured to: enable the user to modify the stack pattern breakpoint using a user interface control. | 0.750774 |
8,983,849 | 11 | 12 | 11. The computer-readable medium of claim 10 , wherein each synchronization message further includes a priority level reflecting the priority of change events in the synchronization message. | 11. The computer-readable medium of claim 10 , wherein each synchronization message further includes a priority level reflecting the priority of change events in the synchronization message. 12. The computer-readable medium of claim 11 , wherein synchronization messages having a high priority level are generated immediately after the master language model is updated with each change message having a high priority level. | 0.5 |
10,102,287 | 16 | 32 | 16. A system for performing an electronic search of a database, said system comprising: a processor; and a memory coupled to the processor; wherein the memory has a set of computer readable instructions stored therein, that when executed by the processor, cause the processor to: (i) process user input acquired through user interaction with an icon selection tool to define at least two selected graphical icons from a set of graphical icons in the database; (ii) process user input to define a search weighting preference for each of the at least two selected graphical icons; (iii) process the at least two selected graphical icons to generate a ranked item list for each of the at least two selected graphical icons based on metadata, wherein the ranked item lists each comprise: items having an associated numerical ranking relative to other items in the ranked item list, wherein the metadata include seed products associated with corresponding graphical icons; (iv) process the search weighting preferences and the ranked item lists for the at least two selected graphical icons to generate a weighted ranked item list for each of the at least two selected graphical icons, the weighted ranked item lists being generated by applying each of the search weighting preferences to the numerical rankings of the items in the ranked item list, and wherein the seed products are weighted, using the keywords and combined into a single ranked list for each corresponding graphical icon, wherein the single ranked list is also used to generate the ranked item list; (v) generate a combined ranked item list by processing the weighted ranked item lists for the at least two selected graphical icons and grouping the items from each of the weighted rank item lists into the combined ranked item list. | 16. A system for performing an electronic search of a database, said system comprising: a processor; and a memory coupled to the processor; wherein the memory has a set of computer readable instructions stored therein, that when executed by the processor, cause the processor to: (i) process user input acquired through user interaction with an icon selection tool to define at least two selected graphical icons from a set of graphical icons in the database; (ii) process user input to define a search weighting preference for each of the at least two selected graphical icons; (iii) process the at least two selected graphical icons to generate a ranked item list for each of the at least two selected graphical icons based on metadata, wherein the ranked item lists each comprise: items having an associated numerical ranking relative to other items in the ranked item list, wherein the metadata include seed products associated with corresponding graphical icons; (iv) process the search weighting preferences and the ranked item lists for the at least two selected graphical icons to generate a weighted ranked item list for each of the at least two selected graphical icons, the weighted ranked item lists being generated by applying each of the search weighting preferences to the numerical rankings of the items in the ranked item list, and wherein the seed products are weighted, using the keywords and combined into a single ranked list for each corresponding graphical icon, wherein the single ranked list is also used to generate the ranked item list; (v) generate a combined ranked item list by processing the weighted ranked item lists for the at least two selected graphical icons and grouping the items from each of the weighted rank item lists into the combined ranked item list. 32. The system of claim 16 wherein the graphical icons represent archetypes. | 0.851563 |
8,612,433 | 11 | 18 | 11. A method that utilizes a processor to provide a search result, the method comprising: receiving a search term from a user; extracting, via the processor, information corresponding to at least one of a first personal network associated with the search term and a second personal network different than the first personal network; extracting information corresponding to at least one neighbor having interests corresponding to interests of the user based, at least in part, on a profile of the user; and providing a document associated with at least one of the first personal network and the second personal network as a search result of the search term, wherein extracting the information corresponding to the at least one neighbor comprises: providing the profile of the user using keywords provided in a document prepared by the user, the keywords being time-variable and corresponding to keywords having the highest frequency of occurrence in the document. | 11. A method that utilizes a processor to provide a search result, the method comprising: receiving a search term from a user; extracting, via the processor, information corresponding to at least one of a first personal network associated with the search term and a second personal network different than the first personal network; extracting information corresponding to at least one neighbor having interests corresponding to interests of the user based, at least in part, on a profile of the user; and providing a document associated with at least one of the first personal network and the second personal network as a search result of the search term, wherein extracting the information corresponding to the at least one neighbor comprises: providing the profile of the user using keywords provided in a document prepared by the user, the keywords being time-variable and corresponding to keywords having the highest frequency of occurrence in the document. 18. The method of claim 11 , wherein the providing comprises providing the document associated with the at least one of the first personal network and the second personal network as the search result of the search term by arranging the document associated with the at least one of the first personal network and the second personal network among documents associated with the search term based on an order of net association comprising an association with respect to the search term and an association between the user providing the search term and the at least one of the first personal network and the second personal network. | 0.5 |
8,533,664 | 7 | 12 | 7. A non-transitory computer-readable storage medium storing instructions which when executed by a particular machine cause the machine to perform a method for automatically generating addressing queries for objects rendered on a GUI, the method comprising: receiving a request to generate an object-addressing query for a target GUI object in an application under test; identifying an application context for the application under test; retrieving a rule document describing GUI object-addressing query rules based at least on the identified application context; parsing the rule document to obtain an applicable query rule set for the application, wherein parsing the rule document comprises: retrieving a rule-identification query defined in the rule entry of a respective rule, executing the rule-identification query against the target GUI object in the context of a markup language document in which the object is represented as a node, verifying whether the query result is true, and adding the rule to the applicable rule set when the query result is true; generating a set of query candidates for the target GUI object based at least on the applicable rule set; and determining a unique object-addressing query for the target GUI object. | 7. A non-transitory computer-readable storage medium storing instructions which when executed by a particular machine cause the machine to perform a method for automatically generating addressing queries for objects rendered on a GUI, the method comprising: receiving a request to generate an object-addressing query for a target GUI object in an application under test; identifying an application context for the application under test; retrieving a rule document describing GUI object-addressing query rules based at least on the identified application context; parsing the rule document to obtain an applicable query rule set for the application, wherein parsing the rule document comprises: retrieving a rule-identification query defined in the rule entry of a respective rule, executing the rule-identification query against the target GUI object in the context of a markup language document in which the object is represented as a node, verifying whether the query result is true, and adding the rule to the applicable rule set when the query result is true; generating a set of query candidates for the target GUI object based at least on the applicable rule set; and determining a unique object-addressing query for the target GUI object. 12. The non-transitory computer-readable storage medium of claim 7 , wherein determining the unique object-addressing query for a GUI object comprises: ranking each query candidate using a predetermined ranking method; and choosing the highest ranked query as the unique object-addressing query for the GUI object. | 0.709259 |
8,971,630 | 18 | 19 | 18. The one or more physical non-transitory computer accessible media of claim 17 , wherein the method further comprises: detecting character gaps in the line of glyph-based character representations; creating a histogram of distances for the detected character gaps; constructing a graph according to the detected character gaps; assigning a penalty to arcs of the graph wherein the penalty is based in part on the histogram of distances; and selecting a path in the graph associated with the character cells based on said penalty and arcs of the graph. | 18. The one or more physical non-transitory computer accessible media of claim 17 , wherein the method further comprises: detecting character gaps in the line of glyph-based character representations; creating a histogram of distances for the detected character gaps; constructing a graph according to the detected character gaps; assigning a penalty to arcs of the graph wherein the penalty is based in part on the histogram of distances; and selecting a path in the graph associated with the character cells based on said penalty and arcs of the graph. 19. The one or more physical non-transitory computer accessible media of claim 18 , wherein the graph is a linear division graph (LDG), which is constructed by performing steps including: isolating values substantially near maxima values in the histogram of distances, wherein the isolated values are associated with respective detected character gaps; creating arcs for each detected character gap; assigning a penalty to the arcs; creating paths for the LDG; calculating aggregate penalties for each path associated with the LDG based on the penalties assigned to the arcs; and selecting a desired path from among the paths associated with the LDG based on the aggregate penalties associated with the paths. | 0.5 |
8,656,267 | 1 | 3 | 1. A computer-implemented method of approximate document generation, comprising: analyzing a document generation template; identifying one or more elements in the document generation template that have processing time that is longer than a threshold value, the one or more elements comprising one or control elements in the document generation template comprising a database query, a loop, or fetching a command from a web site, or combinations thereof, execution of which produces text result; modifying executing of said one or more control elements identified as having processing time that is longer than a threshold value, said modifying including at least: enabling said one or more elements to terminate before completion of processing of said one or more elements; and establishing one or more new rules to produce at least a partial result from processing of said one or more elements, wherein the partial result of said text result is produced in response to a stop command received from a user during document generation processing performed via said document generation template, or in response to receiving a time limit for the document generation processing, or combinations thereof, and the partial result provides a preview or brief summary or combination of both, of corresponding one or more elements' processing and the text result's structure, wherein the partial result comprises content that is less than a full result that running of said one or more control elements to completion would produce. | 1. A computer-implemented method of approximate document generation, comprising: analyzing a document generation template; identifying one or more elements in the document generation template that have processing time that is longer than a threshold value, the one or more elements comprising one or control elements in the document generation template comprising a database query, a loop, or fetching a command from a web site, or combinations thereof, execution of which produces text result; modifying executing of said one or more control elements identified as having processing time that is longer than a threshold value, said modifying including at least: enabling said one or more elements to terminate before completion of processing of said one or more elements; and establishing one or more new rules to produce at least a partial result from processing of said one or more elements, wherein the partial result of said text result is produced in response to a stop command received from a user during document generation processing performed via said document generation template, or in response to receiving a time limit for the document generation processing, or combinations thereof, and the partial result provides a preview or brief summary or combination of both, of corresponding one or more elements' processing and the text result's structure, wherein the partial result comprises content that is less than a full result that running of said one or more control elements to completion would produce. 3. The method of claim 1 , wherein said one or more control elements comprises the loop, and the loop is modified to execute a specified number of iterations. | 0.648889 |
9,858,324 | 1 | 4 | 1. A method of extracting unclassified data from a collection of data including both classified data and unclassified data, the method comprising: providing a plain text format file including a plurality of attributes in a computer system that includes a classified environment having a collection of data, which includes messages of both classified binary data and unclassified binary data, wherein the plain text format file describes each of the attributes in a message data structure in a classified network on a message type basis, wherein at least one of the attributes comprises a security mark; executing a software application within the classified environment, the software application comprising a trusted download toolkit programmed for: (a) processing at least one message contained within the collection of data by receiving target input data associated with the message, wherein the target input data comprises a binary data stream comprising classified binary data, a binary data stream comprising unclassified binary data, or a combination thereof, (b) identifying security mark data in at least one of the binary data streams, and (c) identifying a level of classification for at least a portion of the target input data in response to the security mark data; wherein the trusted download toolkit is independent of the message data structure within the classified environment and extracting at least a portion of the identified unclassified binary data from the collection of data in the classified environment in response to the identified level of classification. | 1. A method of extracting unclassified data from a collection of data including both classified data and unclassified data, the method comprising: providing a plain text format file including a plurality of attributes in a computer system that includes a classified environment having a collection of data, which includes messages of both classified binary data and unclassified binary data, wherein the plain text format file describes each of the attributes in a message data structure in a classified network on a message type basis, wherein at least one of the attributes comprises a security mark; executing a software application within the classified environment, the software application comprising a trusted download toolkit programmed for: (a) processing at least one message contained within the collection of data by receiving target input data associated with the message, wherein the target input data comprises a binary data stream comprising classified binary data, a binary data stream comprising unclassified binary data, or a combination thereof, (b) identifying security mark data in at least one of the binary data streams, and (c) identifying a level of classification for at least a portion of the target input data in response to the security mark data; wherein the trusted download toolkit is independent of the message data structure within the classified environment and extracting at least a portion of the identified unclassified binary data from the collection of data in the classified environment in response to the identified level of classification. 4. The method of claim 1 , wherein the collection of data follows a defined data structure criteria that is consistent with system description documentation. | 0.658696 |
8,145,685 | 34 | 35 | 34. The method of claim 33 wherein the instances of object structures having one-to-one and one-to-many mappings comprise meta data describing data objects and corresponding database schema. | 34. The method of claim 33 wherein the instances of object structures having one-to-one and one-to-many mappings comprise meta data describing data objects and corresponding database schema. 35. The method of claim 34 further comprising reading or setting attributes of instances of data objects with an accessor function by generating an appropriate database command. | 0.5 |
8,046,387 | 1 | 9 | 1. A system to provide portals accessible through web browsers, wherein the system for providing the portals is configured to allow privileged users to set up and configure the portals through which visitors access content, the system comprising processing circuitry configured to operate on instructions stored in a memory to provide: a content repository configured to store electronic content and metadata in a computer-readable storage medium and to associate the stored electronic content with the metadata and with potential audience types for the stored electronic content; a communication portal developer configured to provide browser accessible interfaces usable by the privileged users to create a plurality of customizable portals and configured to provide templates usable by the privileged users to create the plurality of customizable portals without software code development, wherein the browser accessible interfaces provided by the communication portal developer includes an audience interface, a portal content interface and a user interface, wherein for each portal created by the privileged users, the audience interface is configured to provide a list of potential audience types for the portal and enable selection of an audience type for the portal from the list, the portal content interface is configured to provide a list of electronic content associated with the selected audience for potential publication to the portal and enable selection of electronic content from the list to be published for the selected audience type, wherein the portal content interface is usable by the privileged users to search through the electronic content using metadata, and a user interface is usable to add selected visitors to the portal who are authorized to view the published content; and a real-time or near real-time analytic engine configured to provide a browser accessible interface for the privileged users to analyze use of the published electronic content on the customizable portals and visitor behavior while logged into their customizable portal, wherein the analytic engine includes an interface configured to present a list of selectable reports, wherein each customizable portal is accessible to the selected visitors, and each customizable portal is configured to enable the selected visitors to view the published electronic data. | 1. A system to provide portals accessible through web browsers, wherein the system for providing the portals is configured to allow privileged users to set up and configure the portals through which visitors access content, the system comprising processing circuitry configured to operate on instructions stored in a memory to provide: a content repository configured to store electronic content and metadata in a computer-readable storage medium and to associate the stored electronic content with the metadata and with potential audience types for the stored electronic content; a communication portal developer configured to provide browser accessible interfaces usable by the privileged users to create a plurality of customizable portals and configured to provide templates usable by the privileged users to create the plurality of customizable portals without software code development, wherein the browser accessible interfaces provided by the communication portal developer includes an audience interface, a portal content interface and a user interface, wherein for each portal created by the privileged users, the audience interface is configured to provide a list of potential audience types for the portal and enable selection of an audience type for the portal from the list, the portal content interface is configured to provide a list of electronic content associated with the selected audience for potential publication to the portal and enable selection of electronic content from the list to be published for the selected audience type, wherein the portal content interface is usable by the privileged users to search through the electronic content using metadata, and a user interface is usable to add selected visitors to the portal who are authorized to view the published content; and a real-time or near real-time analytic engine configured to provide a browser accessible interface for the privileged users to analyze use of the published electronic content on the customizable portals and visitor behavior while logged into their customizable portal, wherein the analytic engine includes an interface configured to present a list of selectable reports, wherein each customizable portal is accessible to the selected visitors, and each customizable portal is configured to enable the selected visitors to view the published electronic data. 9. The system of claim 1 , further comprising a search engine configured to search for electronic content within the content repository by a keyword and configured to search for electronic content within the content repository by at least one category, the search engine including an interface configured to present a list of selectable options for each category. | 0.5 |
5,555,403 | 12 | 13 | 12. The system as in claim 11 wherein said query engine means includes means for providing a sorts window to permit a user to introduce a sort on a list of objects. | 12. The system as in claim 11 wherein said query engine means includes means for providing a sorts window to permit a user to introduce a sort on a list of objects. 13. The system as in claim 12 wherein said query engine means include means for generating a object selector window which provides a list of business objects of the current universe. | 0.5 |
8,838,625 | 6 | 7 | 6. An apparatus for extracting information from a computer-based data source, comprising: means for intercepting display information transmitted to a computer-implemented display device representing information stored in a data source; wherein the display information includes information to cause particular visual content to be displayed on the computer-implemented display device; and a computer processor executing a sequence of instructions configuring the computer processor as: a grammar inducer producing a representation of a hierarchical structure that underlies the display information, wherein the hierarchical structure produced by the grammar inducer is described by a regular language; wherein the grammar inducer determines how to break up the particular visual content into component parts; wherein the grammar inducer determines how to break up the particular visual content into component parts by: identifying a plurality of tokens in the particular visual content; for each token of the plurality of tokens, determining a frequency at which the token appears within the display information from the data source; and determining how to break up the particular visual content into component parts based, at least in part, on the frequency determined for each token of the plurality of tokens; a parser-generator receiving the representation and configured to generate a parser corresponding thereto; and a screen scraper configured to extract the information from the intercepted display information using the generated parser. | 6. An apparatus for extracting information from a computer-based data source, comprising: means for intercepting display information transmitted to a computer-implemented display device representing information stored in a data source; wherein the display information includes information to cause particular visual content to be displayed on the computer-implemented display device; and a computer processor executing a sequence of instructions configuring the computer processor as: a grammar inducer producing a representation of a hierarchical structure that underlies the display information, wherein the hierarchical structure produced by the grammar inducer is described by a regular language; wherein the grammar inducer determines how to break up the particular visual content into component parts; wherein the grammar inducer determines how to break up the particular visual content into component parts by: identifying a plurality of tokens in the particular visual content; for each token of the plurality of tokens, determining a frequency at which the token appears within the display information from the data source; and determining how to break up the particular visual content into component parts based, at least in part, on the frequency determined for each token of the plurality of tokens; a parser-generator receiving the representation and configured to generate a parser corresponding thereto; and a screen scraper configured to extract the information from the intercepted display information using the generated parser. 7. The apparatus of claim 6 , wherein the sequence of instructions for the grammar inducer further comprise instructions configuring the processor to perform: forming a histogram of tokens according to the frequency of each token; and segmenting the text into records starting with tokens with lower frequency. | 0.616337 |
8,417,948 | 10 | 14 | 10. A method of processing computer scripts by a computer processor, the method comprising: interpreting, by the computer processor, a carrier script that is presented in the clear to generate a first sequence of instructions that are executed by the computer processor to carry out the directives of the carrier script; extracting, by the computer processor, a hidden script that is steganographically coded in the carrier script, the hidden script being different from the carrier script; and interpreting, by the computer processor, the hidden script to generate a second sequence of instructions that are executed by the computer processor to carry out the directives of the hidden script. | 10. A method of processing computer scripts by a computer processor, the method comprising: interpreting, by the computer processor, a carrier script that is presented in the clear to generate a first sequence of instructions that are executed by the computer processor to carry out the directives of the carrier script; extracting, by the computer processor, a hidden script that is steganographically coded in the carrier script, the hidden script being different from the carrier script; and interpreting, by the computer processor, the hidden script to generate a second sequence of instructions that are executed by the computer processor to carry out the directives of the hidden script. 14. The method of claim 10 wherein the carrier script is scripted in a first scripting language and the hidden script is scripted in a second scripting language that is different from the first scripting language. | 0.532895 |
8,799,262 | 24 | 34 | 24. A method for configuring a web crawl, the method comprising the steps of: specifying a starter seed uniform resource locator (URL) and a user-specified web crawl configuration to a configurable web crawler which crawls a web to inspect text of page resources accessible on the web, each page resource identified by a unique URL, the user-specified web crawl configuration comprising user-specified crawling rules specifying crawling behavior, the crawling rules specifying crawling behavior for at least one each of a general crawl behavior, one or more page-specific crawl behavior to be applied during a crawl to one or more identified pages, and one or more element-specific crawl behavior to be applied during a crawl to one or more identified page elements, wherein the received crawling rules define the crawling behavior in terms of whether to record the resource text, whether to follow hyperlinks of the resource, whether to record text description in metadata associated with the page, whether to record keywords identified in the metadata associated with the page, whether to override a page title element, whether to exclude one or more identified resource pages, whether to exclude one or more identified domains; wherein the configurable web crawler is configured to maintain a queue of unprocessed URLs of resources, insert the specified starter seed URL into the queue of unprocessed URLs of resources, retrieve from the queue a next unprocessed URL, retrieve the user-specified web crawl configuration which specifies the crawling rules, and if allowed by the specified general crawl behavior and page-specific crawl behavior of the retrieved crawling rules, fetch the page resource addressed by the retrieved URL and process the fetched page resource on an element-by-element basis by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules, and wherein the default crawl behavior comprises extracting URLs of outbound links and adding the extracted URLs to the queue, storing text to a resource repository for further analysis, the one or more processing units repeating the processing on available unprocessed URLs in the queue. | 24. A method for configuring a web crawl, the method comprising the steps of: specifying a starter seed uniform resource locator (URL) and a user-specified web crawl configuration to a configurable web crawler which crawls a web to inspect text of page resources accessible on the web, each page resource identified by a unique URL, the user-specified web crawl configuration comprising user-specified crawling rules specifying crawling behavior, the crawling rules specifying crawling behavior for at least one each of a general crawl behavior, one or more page-specific crawl behavior to be applied during a crawl to one or more identified pages, and one or more element-specific crawl behavior to be applied during a crawl to one or more identified page elements, wherein the received crawling rules define the crawling behavior in terms of whether to record the resource text, whether to follow hyperlinks of the resource, whether to record text description in metadata associated with the page, whether to record keywords identified in the metadata associated with the page, whether to override a page title element, whether to exclude one or more identified resource pages, whether to exclude one or more identified domains; wherein the configurable web crawler is configured to maintain a queue of unprocessed URLs of resources, insert the specified starter seed URL into the queue of unprocessed URLs of resources, retrieve from the queue a next unprocessed URL, retrieve the user-specified web crawl configuration which specifies the crawling rules, and if allowed by the specified general crawl behavior and page-specific crawl behavior of the retrieved crawling rules, fetch the page resource addressed by the retrieved URL and process the fetched page resource on an element-by-element basis by parsing a next page element from the fetched page resource, and if an element-specific behavior is specified in the retrieved crawling rules for the parsed next page element then operating with regard to the element according to the specified element-specific behavior, and otherwise if a page-specific behavior is specified for the fetched page resource then operating with regard to the element according to the specified page-specific behavior, and otherwise if a global crawl behavior is specified then operating with regard to the element according to the specified global crawl behavior, and otherwise operating with regard to the element according to a default crawl behavior; and repeating the processing until either all elements have been parsed and processed in accordance with the retrieved crawling rules, and wherein the default crawl behavior comprises extracting URLs of outbound links and adding the extracted URLs to the queue, storing text to a resource repository for further analysis, the one or more processing units repeating the processing on available unprocessed URLs in the queue. 34. The method of claim 24 , wherein the fetched page resource is an HMTL page. | 0.974217 |
5,537,586 | 5 | 9 | 5. A method of extracting a preferred set of stored textual records from a database, comprising the steps of: assigning, to selected ones of a plurality of predefined category structures, a priority value, wherein said selected ones of said plurality of predefined category structures and assigned priority values form a profile associated with a subscriber; assigning to each stored textual record a relevance value associated with each category structure; associating each stored textual record with each category structure for which the record's relevance value associated with that category structure exceeds a predetermined threshold; maintaining, for each category structure, a list of associated textual records; retrieving from the database, for each category structure, the textual records associated with that category structure; selecting, from the set of retrieved textual records, a plurality of preferred textual records in a manner responsive to the priority value assigned to each category structure; assembling the plurality of preferred textual records to form the preferred set; collecting usage information from the subscriber for the retrieved textual records forming the preferred set; defining a group of subscribers sharing a common characteristic; compiling usage information for the subscribers of the defined group and analyzing the compiled usage information to detect a usage pattern for the group; defining one or more new category structures in accordance with the detected usage pattern; and assigning a new priority value for the new category structures associated with each subscriber profile for each subscriber belonging to the defined group, this step of assigning comprising: assigning a first numerical weight to each new category structure determined by the original priority values for the original category structures in the associated profile; assigning a second numerical weight to each new category structure determined by the usage of textual records associated with the new category structure by the subscriber; assigning a third numerical weight to each new category structure determined by the usage of the textual records associated with the new category structure by other subscribers previously determined to be peers; and assigning the new priority value for each new category structure determined by summing the first, second, and third numerical weights assigned for each new category structure. | 5. A method of extracting a preferred set of stored textual records from a database, comprising the steps of: assigning, to selected ones of a plurality of predefined category structures, a priority value, wherein said selected ones of said plurality of predefined category structures and assigned priority values form a profile associated with a subscriber; assigning to each stored textual record a relevance value associated with each category structure; associating each stored textual record with each category structure for which the record's relevance value associated with that category structure exceeds a predetermined threshold; maintaining, for each category structure, a list of associated textual records; retrieving from the database, for each category structure, the textual records associated with that category structure; selecting, from the set of retrieved textual records, a plurality of preferred textual records in a manner responsive to the priority value assigned to each category structure; assembling the plurality of preferred textual records to form the preferred set; collecting usage information from the subscriber for the retrieved textual records forming the preferred set; defining a group of subscribers sharing a common characteristic; compiling usage information for the subscribers of the defined group and analyzing the compiled usage information to detect a usage pattern for the group; defining one or more new category structures in accordance with the detected usage pattern; and assigning a new priority value for the new category structures associated with each subscriber profile for each subscriber belonging to the defined group, this step of assigning comprising: assigning a first numerical weight to each new category structure determined by the original priority values for the original category structures in the associated profile; assigning a second numerical weight to each new category structure determined by the usage of textual records associated with the new category structure by the subscriber; assigning a third numerical weight to each new category structure determined by the usage of the textual records associated with the new category structure by other subscribers previously determined to be peers; and assigning the new priority value for each new category structure determined by summing the first, second, and third numerical weights assigned for each new category structure. 9. The method of claim 5, wherein the defined group comprises subscribers having a common profession. | 0.757212 |
9,588,596 | 11 | 14 | 11. A non-transitory computer-readable medium comprising instructions which, when executed by a processor, cause the processor to perform operations including: detecting an ambiguous input including one or more selections of one or more input keys; generating one or more prefix objects corresponding with the ambiguous input; generating an output set including at least some of the one or more prefix objects, wherein each of the at least some of the one or more prefix objects is associated with an identified corresponding word object; determining a quantity of prefix objects in the output set is fewer than a predetermined quantity, and, based on the determination, adding as an orphan prefix object to the output set an additional prefix object of the one or more of prefix objects for which a corresponding word object was not identified; outputting the output set; detecting an additional selection of one or more input keys; determining that a selection input was not detected between the detection of the ambiguous input and the detection of the additional selection; and generating one or more additional prefix objects corresponding with the ambiguous input plus the additional selection without generating an additional prefix object corresponding with the orphan prefix object. | 11. A non-transitory computer-readable medium comprising instructions which, when executed by a processor, cause the processor to perform operations including: detecting an ambiguous input including one or more selections of one or more input keys; generating one or more prefix objects corresponding with the ambiguous input; generating an output set including at least some of the one or more prefix objects, wherein each of the at least some of the one or more prefix objects is associated with an identified corresponding word object; determining a quantity of prefix objects in the output set is fewer than a predetermined quantity, and, based on the determination, adding as an orphan prefix object to the output set an additional prefix object of the one or more of prefix objects for which a corresponding word object was not identified; outputting the output set; detecting an additional selection of one or more input keys; determining that a selection input was not detected between the detection of the ambiguous input and the detection of the additional selection; and generating one or more additional prefix objects corresponding with the ambiguous input plus the additional selection without generating an additional prefix object corresponding with the orphan prefix object. 14. The non-transitory computer-readable medium of claim 11 , wherein each of the at least some of the one or more prefix objects is positioned in the output set at a position corresponding to a frequency object associated with the identified corresponding word object. | 0.797134 |
9,292,797 | 8 | 11 | 8. A computer program product for providing a semi-supervised data integration model for named entity classification from a first repository of entity information in view of an auxiliary repository of classification assistance data, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code being executable by a computer to perform a method comprising: comparing training data to named entity candidates taken from the first repository, thereby forming a positive training seed set in view of identified commonality between the training data and the named entity candidates; in view of the positive training seed set, populating a decision tree; in view of populating the decision tree, creating classification rules for classifying the named entity candidates; sampling a number of entities from the named entity candidates; in view of the classification rules, labeling the sampled entities as positive examples and/or negative examples; in view of the positive examples and the auxiliary repository, updating the positive training seed set to include identified commonality between the positive examples and the auxiliary repository; in view of the negative examples and the auxiliary repository, updating a negative training seed set to include negative examples which lack commonality with the auxiliary repository; and in view of both the updated positive and negative training seed sets, updating the decision tree and the classification rules. | 8. A computer program product for providing a semi-supervised data integration model for named entity classification from a first repository of entity information in view of an auxiliary repository of classification assistance data, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code being executable by a computer to perform a method comprising: comparing training data to named entity candidates taken from the first repository, thereby forming a positive training seed set in view of identified commonality between the training data and the named entity candidates; in view of the positive training seed set, populating a decision tree; in view of populating the decision tree, creating classification rules for classifying the named entity candidates; sampling a number of entities from the named entity candidates; in view of the classification rules, labeling the sampled entities as positive examples and/or negative examples; in view of the positive examples and the auxiliary repository, updating the positive training seed set to include identified commonality between the positive examples and the auxiliary repository; in view of the negative examples and the auxiliary repository, updating a negative training seed set to include negative examples which lack commonality with the auxiliary repository; and in view of both the updated positive and negative training seed sets, updating the decision tree and the classification rules. 11. The computer program product of claim 8 , comprising: removing aliases from the first repository to determine the named entity candidates; eliminating common stop words and non-content-bearing words from candidate entity content of the named entity candidates; populating a feature dictionary in view of high frequency words in the candidate entity content of the named entity candidates; representing the candidate entity content as a vector space model by applying weights to each word of the feature dictionary in the candidate entity content; and preprocessing the auxiliary repository to remove false positive examples. | 0.5 |
7,996,246 | 7 | 18 | 7. A method for generating information for determining resource allocation in a resident care facility, the method comprising: providing a set of assessment questions to an assessor, the set of assessment questions being: based on a base assessment model having questions relating to a plurality of resident care areas; and related to at least a portion of the plurality of resident care areas; receiving responses to at least a portion of the set of assessment questions from a number of respondents; processing the responses to generate an assessment dataset; generating, with a computer, a quality score for at least one of the resident care areas based on the assessment dataset; generating, with a computer, a likelihood of citation in the resident care area associated with the quality score, as a function of the quality score, the number of respondents, a model threshold, and a model sample size, the model threshold and the model sample size being derived from the base assessment model; and displaying the likelihood of citation for the resident care area associated with the quality score. | 7. A method for generating information for determining resource allocation in a resident care facility, the method comprising: providing a set of assessment questions to an assessor, the set of assessment questions being: based on a base assessment model having questions relating to a plurality of resident care areas; and related to at least a portion of the plurality of resident care areas; receiving responses to at least a portion of the set of assessment questions from a number of respondents; processing the responses to generate an assessment dataset; generating, with a computer, a quality score for at least one of the resident care areas based on the assessment dataset; generating, with a computer, a likelihood of citation in the resident care area associated with the quality score, as a function of the quality score, the number of respondents, a model threshold, and a model sample size, the model threshold and the model sample size being derived from the base assessment model; and displaying the likelihood of citation for the resident care area associated with the quality score. 18. The method of claim 7 , wherein at least a portion of the responses relate to personal observations made by the assessor. | 0.909157 |
9,195,943 | 16 | 17 | 16. A method for determining causal relationships among system entities, the method comprising: receiving, by at least one processor, events from a computing environment having a plurality of entities; detecting, by the at least one processor, causal relationships among the plurality of entities, during runtime of the computing environment including creating vertices and arcs connecting temporally adjacent vertices, and annotating each arc with a coefficient value representing a level of connectivity between the temporally adjacent vertices based on the events; and converting, by the at least one processor, one or more of the causal relationships into at least one behavioral rule including mapping the temporally adjacent vertices to corresponding entities of the plurality of entities that generated the temporally adjacent vertices when the coefficient value is above a threshold value, the at least one behavioral rule indicating a causal relationship between the corresponding entities. | 16. A method for determining causal relationships among system entities, the method comprising: receiving, by at least one processor, events from a computing environment having a plurality of entities; detecting, by the at least one processor, causal relationships among the plurality of entities, during runtime of the computing environment including creating vertices and arcs connecting temporally adjacent vertices, and annotating each arc with a coefficient value representing a level of connectivity between the temporally adjacent vertices based on the events; and converting, by the at least one processor, one or more of the causal relationships into at least one behavioral rule including mapping the temporally adjacent vertices to corresponding entities of the plurality of entities that generated the temporally adjacent vertices when the coefficient value is above a threshold value, the at least one behavioral rule indicating a causal relationship between the corresponding entities. 17. The method of claim 16 , wherein the detecting, by the at least one processor, causal relationships among the plurality of entities, during runtime of the computing environment, based on the events includes: generating one or more graphs based on the events, each graph including the vertices and the arcs connecting the temporally adjacent vertices, each vertex representing an event instance of one or more events, and each arc representing the level of causal connectivity between at least two vertices; and detecting the causal relationships based on the one or more graphs. | 0.5 |
8,316,358 | 1 | 3 | 1. A server for creating a Document Object Model of an XML document of predetermined type, comprising: a memory; and a processor configured to execute a distiller, said distiller comprising: a first process for receiving and opening a compressed input file containing said XML document; a second process for opening and parsing the contents of a relationships file to create a map of name-value pairs and detecting a value for identifying said predetermined type from among a plurality of types of XML documents, wherein said second process includes a Data XML Map class for detecting (i) a name-value pair with a value for identifying a Word™ 2007 XML file, (ii) a name-value pair with a value for identifying an Excel™ 2007 XML file and (iii) a name-value pair with a value for identifying a PowerPoint™ 2007 XML document; and a further process for parsing data in said XML document according to said predetermined type, and building said Document Object Model for storage in said memory. | 1. A server for creating a Document Object Model of an XML document of predetermined type, comprising: a memory; and a processor configured to execute a distiller, said distiller comprising: a first process for receiving and opening a compressed input file containing said XML document; a second process for opening and parsing the contents of a relationships file to create a map of name-value pairs and detecting a value for identifying said predetermined type from among a plurality of types of XML documents, wherein said second process includes a Data XML Map class for detecting (i) a name-value pair with a value for identifying a Word™ 2007 XML file, (ii) a name-value pair with a value for identifying an Excel™ 2007 XML file and (iii) a name-value pair with a value for identifying a PowerPoint™ 2007 XML document; and a further process for parsing data in said XML document according to said predetermined type, and building said Document Object Model for storage in said memory. 3. The server of claim 1 , wherein said further process includes a Data XML class. | 0.848148 |
9,723,303 | 26 | 27 | 26. A method for generating video test patterns, comprising: accepting a text definition file that contains a series of attributes of a particular test pattern to be generated; retrieving the series of attributes from the text definition file; generating pixel data representing portions of the particular test pattern based on the retrieved series of attributes in an image generator; populating a memory with the generated pixel data; retrieving the pixel data from the memory; and sequentially outputting the particular test pattern based on the retrieved pixel data. | 26. A method for generating video test patterns, comprising: accepting a text definition file that contains a series of attributes of a particular test pattern to be generated; retrieving the series of attributes from the text definition file; generating pixel data representing portions of the particular test pattern based on the retrieved series of attributes in an image generator; populating a memory with the generated pixel data; retrieving the pixel data from the memory; and sequentially outputting the particular test pattern based on the retrieved pixel data. 27. The system for generating video test patterns of claim 26 in which accepting a text definition file comprises accepting an XML file. | 0.5 |
7,711,573 | 76 | 107 | 76. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute, by the computer, a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; storing the resume in the resume database; creating a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; storing the parsed resume in the resume database; sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 76. A method for using a computer to improve a precision ratio when searching a resume database, comprising: receiving a resume in a memory device resident in the computer; parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute, by the computer, a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; storing the resume in the resume database; creating a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; storing the parsed resume in the resume database; sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 107. The method of claim 76 , further comprising: sending a portion of the parsed resume to a candidate. | 0.890756 |
9,905,220 | 4 | 6 | 4. The system of claim 2 , wherein the operations further comprise identifying one or more groups of phonetic units from among the sequence of phonetic units that form the phonetic representation of the text in the first language; and wherein providing, by the one or more computers, input to the neural network, comprises providing, by the one or more computers, input to the neural network that includes (i) the sequence of phonetic units that form the phonetic representation of the text in the first language, (ii) the language identifier for the first language, and (iii) data indicating the one or more groups of phonetic units. | 4. The system of claim 2 , wherein the operations further comprise identifying one or more groups of phonetic units from among the sequence of phonetic units that form the phonetic representation of the text in the first language; and wherein providing, by the one or more computers, input to the neural network, comprises providing, by the one or more computers, input to the neural network that includes (i) the sequence of phonetic units that form the phonetic representation of the text in the first language, (ii) the language identifier for the first language, and (iii) data indicating the one or more groups of phonetic units. 6. The system of claim 4 , wherein the operations further comprise identifying one or more phonetic units that represent stressed sounds in the sequence of phonetic units that form the phonetic representation of the text in the first language; and wherein identifying the one or more groups of phonetic units comprises identifying the one or more groups of phonetic units based on positions of the one or more phonetic units that represent stressed sounds within the sequence of phonetic units that form the phonetic representation of the text in the first language. | 0.5472 |
8,219,068 | 8 | 15 | 8. A mobile station, comprising: a message input configured to receive a compact text representation of a voice message and a voice message identifier, wherein the voice message is associated with a message profile; and a display configured to display the compact text representation and an indicator associated with an availability of the associated voice message, wherein the compact text representation includes an abbreviation selected from an abbreviation library associated with the message profile, and wherein an extent to which the voice message is abbreviated is based on network capacity. | 8. A mobile station, comprising: a message input configured to receive a compact text representation of a voice message and a voice message identifier, wherein the voice message is associated with a message profile; and a display configured to display the compact text representation and an indicator associated with an availability of the associated voice message, wherein the compact text representation includes an abbreviation selected from an abbreviation library associated with the message profile, and wherein an extent to which the voice message is abbreviated is based on network capacity. 15. The mobile station of claim 8 , further comprising a transceiver configured to request delivery of the voice message by transmitting the voice identifier associated with the compact text representation. | 0.6171 |
9,846,840 | 17 | 18 | 17. In a digital medium classification environment, a method implemented by at least one computing device, the method comprising: aggregating, by the at least one computing device, patterns of neurons in a neural network by progressing through a sequence of layers of the neural network to classify an image as relating to a semantic class; communicating, by the at least one computing device, positive relevancy of the patterns formed by respective said neurons to the semantic class by progressing backwards through the sequence of layers of the neural network, wherein the positive relevancy of the patterns to the semantic class is defined using an activation relevancy map of the image, wherein the communicating including communicating a contrastive activation relevancy map that is self-contrastive as describing a lack of relevancy of respective said neurons in a respective said layer to the semantic class; localizing, by the at least one computing device, the semantic class within the image based on the communicated positive relevancy of the aggregated patterns to the semantic class, wherein the localizing is based at least in part on the aggregated patterns, the activation relevancy map, and the contrastive activation relevancy map; and generating, by the at least one computing device, digital content based on localization of the semantic class within the image. | 17. In a digital medium classification environment, a method implemented by at least one computing device, the method comprising: aggregating, by the at least one computing device, patterns of neurons in a neural network by progressing through a sequence of layers of the neural network to classify an image as relating to a semantic class; communicating, by the at least one computing device, positive relevancy of the patterns formed by respective said neurons to the semantic class by progressing backwards through the sequence of layers of the neural network, wherein the positive relevancy of the patterns to the semantic class is defined using an activation relevancy map of the image, wherein the communicating including communicating a contrastive activation relevancy map that is self-contrastive as describing a lack of relevancy of respective said neurons in a respective said layer to the semantic class; localizing, by the at least one computing device, the semantic class within the image based on the communicated positive relevancy of the aggregated patterns to the semantic class, wherein the localizing is based at least in part on the aggregated patterns, the activation relevancy map, and the contrastive activation relevancy map; and generating, by the at least one computing device, digital content based on localization of the semantic class within the image. 18. The method as described in claim 17 , wherein the localizing includes removing portions of the aggregated patterns in the activation relevancy map that are in common with corresponding said neurons of patterns in the contrastive activation relevancy map that describe the lack of relevancy of the respective said neurons in the respective said layer. | 0.5 |
8,341,160 | 9 | 10 | 9. A computer-implemented method to generate an index for a closest match search, the method comprising: receiving a corpus of information including a plurality of member information, the plurality of member information including first member information that describes a first member and other member information that describes a plurality of other members; using a data processor to generate a plurality of candidate signatures based on the corpus of information, the plurality of candidate signatures including a first plurality of candidate signatures and a second plurality of candidate signatures, the generating of the first plurality of candidate signatures based on the first member information and the generating of the second plurality of candidate signatures based on the other member information; identifying a plurality of index signatures based on the plurality of candidate signatures, the plurality of index signatures including a first plurality of index signatures, the first plurality of index signatures further included in the first plurality of candidate signatures and not included in the second plurality of candidate signatures to signify the first member and not any of the plurality of other members; storing the plurality of index signatures in the index in association with the first member to enable a closest match of input information to at least one of the plurality of index signatures to identify a closest match of the input information to the first member over the plurality of other members; and generating a first plurality of candidate signature scores respectively associated with the first plurality of candidate signatures, the first plurality of candidate signatures including a first candidate signature and a first candidate signature score that is associated with the first candidate signature, the first candidate signature score represents a percentage of coverage of the first signature over the first member information. | 9. A computer-implemented method to generate an index for a closest match search, the method comprising: receiving a corpus of information including a plurality of member information, the plurality of member information including first member information that describes a first member and other member information that describes a plurality of other members; using a data processor to generate a plurality of candidate signatures based on the corpus of information, the plurality of candidate signatures including a first plurality of candidate signatures and a second plurality of candidate signatures, the generating of the first plurality of candidate signatures based on the first member information and the generating of the second plurality of candidate signatures based on the other member information; identifying a plurality of index signatures based on the plurality of candidate signatures, the plurality of index signatures including a first plurality of index signatures, the first plurality of index signatures further included in the first plurality of candidate signatures and not included in the second plurality of candidate signatures to signify the first member and not any of the plurality of other members; storing the plurality of index signatures in the index in association with the first member to enable a closest match of input information to at least one of the plurality of index signatures to identify a closest match of the input information to the first member over the plurality of other members; and generating a first plurality of candidate signature scores respectively associated with the first plurality of candidate signatures, the first plurality of candidate signatures including a first candidate signature and a first candidate signature score that is associated with the first candidate signature, the first candidate signature score represents a percentage of coverage of the first signature over the first member information. 10. The method of claim 9 , wherein identifying the plurality of index signatures further includes comparing the first plurality of candidate signature scores with a predetermined threshold. | 0.699367 |
6,073,127 | 1 | 4 | 1. A method for creating a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a dynamic, goal based educational learning experience, comprising the steps of: (a) accessing the information in the spreadsheet object component of the rule-based expert system to retrieve information indicative of a goal and presenting the goal on a display; (b) utilizing the information in the spreadsheet object component of the rule-based expert system to integrate goal-based remediation learning information feedback in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) monitoring answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and providing dynamic, goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further motivates accomplishment of the goal; and (d) analyzing the answers from the student utilizing system tools to compare the answers with a standard for achieving the goal. | 1. A method for creating a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a dynamic, goal based educational learning experience, comprising the steps of: (a) accessing the information in the spreadsheet object component of the rule-based expert system to retrieve information indicative of a goal and presenting the goal on a display; (b) utilizing the information in the spreadsheet object component of the rule-based expert system to integrate goal-based remediation learning information feedback in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) monitoring answers to questions posed to evaluate progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and providing dynamic, goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further motivates accomplishment of the goal; and (d) analyzing the answers from the student utilizing system tools to compare the answers with a standard for achieving the goal. 4. A method for creating a business simulation utilizing a rule-based expert system with a spreadsheet object component to provide a goal based educational learning experience as recited in claim 1, wherein the dynamic information includes simulation information. | 0.530357 |
7,853,586 | 7 | 10 | 7. A method performed by a device, comprising: providing, on a display associated with the device, a web browser application window that includes an input box and a button to initiate a highlighting operation; presenting a document within the web browser application window on the display; receiving one or more characters within the input box after presenting the document within the web browser application window; receiving selection of the button to initiate the highlighting operation after receiving the one or more characters within the input box; automatically locating and highlighting occurrences of the one or more characters within the document presented within the web browser application window in response to receiving the selection of the button; and presenting the document with the highlighted one or more characters on the display. | 7. A method performed by a device, comprising: providing, on a display associated with the device, a web browser application window that includes an input box and a button to initiate a highlighting operation; presenting a document within the web browser application window on the display; receiving one or more characters within the input box after presenting the document within the web browser application window; receiving selection of the button to initiate the highlighting operation after receiving the one or more characters within the input box; automatically locating and highlighting occurrences of the one or more characters within the document presented within the web browser application window in response to receiving the selection of the button; and presenting the document with the highlighted one or more characters on the display. 10. The method of claim 7 , where the document includes a web page. | 0.897554 |
8,930,176 | 1 | 6 | 1. One or more computer-readable storage devices storing processor-executable instructions that, when executed, cause one or more processors to perform operations that facilitate interactive exposing of word-alignments between a bilingual sentence pair, the operations comprising: concurrently displaying each sentence of the bilingual sentence pair via a user-interface (UI); receiving a user selection of an of-interest word or phrase of a first sentence of the bilingual sentence pair; in response to the receiving, performing actions including: highlighting the of-interest word or phrase via the UI; finding a linked word in a second sentence of the bilingual sentence pair that corresponds to the of-interest word; and highlighting the linked word via the UI; and presenting to a user, via the UI, a control to reassign the highlighted word-alignment between the bilingual sentence pair. | 1. One or more computer-readable storage devices storing processor-executable instructions that, when executed, cause one or more processors to perform operations that facilitate interactive exposing of word-alignments between a bilingual sentence pair, the operations comprising: concurrently displaying each sentence of the bilingual sentence pair via a user-interface (UI); receiving a user selection of an of-interest word or phrase of a first sentence of the bilingual sentence pair; in response to the receiving, performing actions including: highlighting the of-interest word or phrase via the UI; finding a linked word in a second sentence of the bilingual sentence pair that corresponds to the of-interest word; and highlighting the linked word via the UI; and presenting to a user, via the UI, a control to reassign the highlighted word-alignment between the bilingual sentence pair. 6. One or more computer-readable storage devices as recited in claim 1 , the operations further comprising, in response to the receiving, performing an online search engine query of the of-interest word and displaying the results of the query. | 0.827169 |
9,910,589 | 1 | 7 | 1. A computer implemented method of recognizing user input through interaction with a graphical user interface (GUI), the method comprising: rendering a GUI for display on a display device, wherein the GUI comprises a virtual keyboard comprising a plurality of characters arranged in a layout, wherein each character is associated with a recognition zone, wherein a user interaction detected within a recognition zone causes an associated character to be selected as an input character; receiving a first user interaction with the GUI on a first location within the virtual keyboard; selecting a first character as a first input character, wherein the first character is associated with a first recognition zone encompassing the first location, wherein the first location is encompassed by an overlap zone of a plurality of recognition zones comprising the first recognition zone; computing distances from the first location to respective centers of the plurality of recognition zones; computing nonlinear normalization values of the distances; and determining weights based on the nonlinear normalization values of the distances, wherein the first character is selected based on the weights; automatically predicting one or more next characters based on the first input character; and adjusting recognition zones of the one or more next characters based on the predicting. | 1. A computer implemented method of recognizing user input through interaction with a graphical user interface (GUI), the method comprising: rendering a GUI for display on a display device, wherein the GUI comprises a virtual keyboard comprising a plurality of characters arranged in a layout, wherein each character is associated with a recognition zone, wherein a user interaction detected within a recognition zone causes an associated character to be selected as an input character; receiving a first user interaction with the GUI on a first location within the virtual keyboard; selecting a first character as a first input character, wherein the first character is associated with a first recognition zone encompassing the first location, wherein the first location is encompassed by an overlap zone of a plurality of recognition zones comprising the first recognition zone; computing distances from the first location to respective centers of the plurality of recognition zones; computing nonlinear normalization values of the distances; and determining weights based on the nonlinear normalization values of the distances, wherein the first character is selected based on the weights; automatically predicting one or more next characters based on the first input character; and adjusting recognition zones of the one or more next characters based on the predicting. 7. The computer implemented method according to claim 1 further comprising decreasing recognition zones of adjacent characters that are adjacent to the one or more next characters, wherein the recognition zones of the adjacent characters do not overlap with the recognition zones of the one or more next characters. | 0.516871 |
8,914,398 | 9 | 11 | 9. A system, comprising: at least one processor; and a memory comprising program instructions, wherein the program instructions are executable by the at least one processor to: receive text input, the text input including content associated with an input source; provide the text input to a keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the text input; apply a text reduction function to the text input to generate a reduced text that is a subset of the text input, wherein the text reduction function is based on a term importance score of terms in the text input; provide the reduced text to the keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the reduced text, the one or more keywords generated based on the reduced text generated independently from the one or more keywords generated based on the text input; and generate a keyword set output from a combination of the one or more keywords based on the text input and the one or more keywords based on the reduced text. | 9. A system, comprising: at least one processor; and a memory comprising program instructions, wherein the program instructions are executable by the at least one processor to: receive text input, the text input including content associated with an input source; provide the text input to a keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the text input; apply a text reduction function to the text input to generate a reduced text that is a subset of the text input, wherein the text reduction function is based on a term importance score of terms in the text input; provide the reduced text to the keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the reduced text, the one or more keywords generated based on the reduced text generated independently from the one or more keywords generated based on the text input; and generate a keyword set output from a combination of the one or more keywords based on the text input and the one or more keywords based on the reduced text. 11. The system of claim 9 , wherein the program instructions for the text reduction function are further executable by the at least one processor to: calculate the term importance score for each term within the text input by determining a frequency of the term within the text input and by offsetting the term importance score by a frequency of the term within a corpus of input texts. | 0.5 |
9,177,557 | 1 | 7 | 1. A method of providing speech recognition functionality for an utterance spoken in a noisy environment having multiple human speakers, the method comprising: receiving speech energy corresponding to the utterance, the received speech energy comprising contributions from multiple human speakers; converting the received speech energy to an electronic form; digitizing the electronic form of the received speech energy to render a digitization of the received speech energy; decomposing the digitization of the received speech energy to produce feature data representative of features in the digitization of the received speech energy, wherein the feature data does not distinguish between different speakers and between speech and background noise; processing the feature data to produce speaker dependent feature data and speaker independent feature data; projecting only the speaker independent feature data into a feature space, the feature space having multiple human speaker subspaces for multiple human speakers, wherein each one of the multiple human speakers is associated with a distinct one of the multiple human speaker subspaces and wherein the features of the speaker independent feature data project either into one of the multiple human speaker subspaces or outside of all human speaker subspaces; identifying the speaker independent feature data associated with a speaker subspace associated with a primary human speaker; and performing a speech recognition operation on speaker independent feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data, wherein the speaker independent feature data includes contributions from at least two speakers, and wherein performing a speech recognition operation on the feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data comprises removing all feature data not associated with the speaker subspace associated with the primary human speaker. | 1. A method of providing speech recognition functionality for an utterance spoken in a noisy environment having multiple human speakers, the method comprising: receiving speech energy corresponding to the utterance, the received speech energy comprising contributions from multiple human speakers; converting the received speech energy to an electronic form; digitizing the electronic form of the received speech energy to render a digitization of the received speech energy; decomposing the digitization of the received speech energy to produce feature data representative of features in the digitization of the received speech energy, wherein the feature data does not distinguish between different speakers and between speech and background noise; processing the feature data to produce speaker dependent feature data and speaker independent feature data; projecting only the speaker independent feature data into a feature space, the feature space having multiple human speaker subspaces for multiple human speakers, wherein each one of the multiple human speakers is associated with a distinct one of the multiple human speaker subspaces and wherein the features of the speaker independent feature data project either into one of the multiple human speaker subspaces or outside of all human speaker subspaces; identifying the speaker independent feature data associated with a speaker subspace associated with a primary human speaker; and performing a speech recognition operation on speaker independent feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data, wherein the speaker independent feature data includes contributions from at least two speakers, and wherein performing a speech recognition operation on the feature data associated with the speaker subspace associated with the primary human speaker to resolve the utterance to a command or data comprises removing all feature data not associated with the speaker subspace associated with the primary human speaker. 7. The method of providing speech recognition functionality according to claim 1 , wherein the step of projecting only the speaker independent feature data into the feature space comprises projecting the speaker independent feature data into the multiple human speaker subspaces by using eigenvalues and orthonormal bases. | 0.668041 |
9,098,571 | 21 | 29 | 21. A computer-readable storage medium including instructions for analyzing search query relationships, which, when executed by at least one processor, cause the processor to perform steps comprising: receiving, over an electronic network, log data relating to a plurality of search queries received from users; generating a click graph representing relationships among a plurality of queries and a plurality of visited query results associated with each of the plurality of queries, wherein the click graph depicts at least one first layer relationship between a first query and a second query in the plurality of queries, the first layer relationship indicating that at least one of the plurality of visited query results is associated with both the first query and the second query, and further wherein the click graph depicts at least one second layer relationship between the first query and second query in the plurality of queries, the second layer relationship indicating that each of the first and second queries has a first layer relationship to a third query; computing a numeric value representing a degree of the at least one second layer relationship; identifying temporal similarities between at least one pair of the plurality of queries, the temporal similarities determined based on a temporal distance between peaks in frequency of occurrence for both queries in the at least one pair of the plurality of queries; evaluating the at least one pair of queries based on the generated click graph and the identified temporal similarities to determine whether the at least one pair of queries are related; and designating the queries in the at least one pair of queries as related based on the computed value being greater than zero and the temporal distance being below a threshold value. | 21. A computer-readable storage medium including instructions for analyzing search query relationships, which, when executed by at least one processor, cause the processor to perform steps comprising: receiving, over an electronic network, log data relating to a plurality of search queries received from users; generating a click graph representing relationships among a plurality of queries and a plurality of visited query results associated with each of the plurality of queries, wherein the click graph depicts at least one first layer relationship between a first query and a second query in the plurality of queries, the first layer relationship indicating that at least one of the plurality of visited query results is associated with both the first query and the second query, and further wherein the click graph depicts at least one second layer relationship between the first query and second query in the plurality of queries, the second layer relationship indicating that each of the first and second queries has a first layer relationship to a third query; computing a numeric value representing a degree of the at least one second layer relationship; identifying temporal similarities between at least one pair of the plurality of queries, the temporal similarities determined based on a temporal distance between peaks in frequency of occurrence for both queries in the at least one pair of the plurality of queries; evaluating the at least one pair of queries based on the generated click graph and the identified temporal similarities to determine whether the at least one pair of queries are related; and designating the queries in the at least one pair of queries as related based on the computed value being greater than zero and the temporal distance being below a threshold value. 29. The computer-readable storage medium of claim 21 , wherein the step of evaluating the at least one pair of queries comprises: computing a value representing a first layer similarity between the queries in the at least one pair of queries; and designating the queries in the at least one pair of queries as related if the computed value is greater than zero. | 0.586957 |
8,352,269 | 2 | 7 | 2. The method of claim 1 , further comprising: processing, by the one or more computers, a second indicium in the document to determine a second portion of words in the document, the second portion of words being different from the first portion of words; determining, by the one or more computers, a second, different voice model to associate with the second portion of words based on the second indicia; and generating, by the one or more computers, an audible output corresponding to the words in the second portion of words using the second, different voice model associated with the second portion of words. | 2. The method of claim 1 , further comprising: processing, by the one or more computers, a second indicium in the document to determine a second portion of words in the document, the second portion of words being different from the first portion of words; determining, by the one or more computers, a second, different voice model to associate with the second portion of words based on the second indicia; and generating, by the one or more computers, an audible output corresponding to the words in the second portion of words using the second, different voice model associated with the second portion of words. 7. The method of claim 2 , wherein the voice model associated with the first portion of words comprises a voice model configured to generate an audible output at a first volume and the voice model associated with the second portion of words comprises a voice model configured to generate an audible output at a second volume that is different from the first volume. | 0.528424 |
8,155,943 | 20 | 21 | 20. The computer system for converting a computer aided design drawing file of an electrical power system into one or more component objects for power analytic analysis and simulation, as recited in claim 1 , wherein the analytics engine is further configured to simulate an operational event of the electrical power system. | 20. The computer system for converting a computer aided design drawing file of an electrical power system into one or more component objects for power analytic analysis and simulation, as recited in claim 1 , wherein the analytics engine is further configured to simulate an operational event of the electrical power system. 21. The computer system for converting a computer aided design drawing file of an electrical power system into one or more component objects for power analytic analysis and simulation, as recited in claim 20 , wherein the event is a power system short circuit. | 0.509434 |
9,020,944 | 1 | 7 | 1. A system comprising: one or more processors; a program storage device tangibly embodying a program of instructions executable by the one or more processors, the program of instructions comprising: computer program code configured to extract process descriptions from process documents, the process descriptions comprising process fragments, the process documents comprising at least one flow document and at least one text document, wherein the process description of the at least one flow document comprises a graphical process description; computer program code configured to represent the process description from the at least one text document and the graphical process description from the at least one flow document in separate canonical representations; computer program code configured to compare process fragments from the separate canonical representations; wherein the computer program code configured to compare the process fragments from the separate canonical representations is further configured to assign separate canonical representations to the process fragments from the at least one flow document and the at least one text document; computer program code configured to determine compatibility of process fragments between the at least one text document and the at least one flow document; wherein the computer program code configured to determine compatibility of process fragments between the at least one text document and the at least one flow document is further configured to assign similarity scores among pairs of fragments in response to comparing the process fragments; computer program code configured to link compatible process fragments of the at least one flow document and the at least one process document, via linking at least one process fragment from the graphical process description from the at least one flow document with at least one process fragment from the process description from the at least one text document; and computer program code configured to compute from the assigned similarity scores an aggregated similarity score between the at least one text document and the at least one flow document. | 1. A system comprising: one or more processors; a program storage device tangibly embodying a program of instructions executable by the one or more processors, the program of instructions comprising: computer program code configured to extract process descriptions from process documents, the process descriptions comprising process fragments, the process documents comprising at least one flow document and at least one text document, wherein the process description of the at least one flow document comprises a graphical process description; computer program code configured to represent the process description from the at least one text document and the graphical process description from the at least one flow document in separate canonical representations; computer program code configured to compare process fragments from the separate canonical representations; wherein the computer program code configured to compare the process fragments from the separate canonical representations is further configured to assign separate canonical representations to the process fragments from the at least one flow document and the at least one text document; computer program code configured to determine compatibility of process fragments between the at least one text document and the at least one flow document; wherein the computer program code configured to determine compatibility of process fragments between the at least one text document and the at least one flow document is further configured to assign similarity scores among pairs of fragments in response to comparing the process fragments; computer program code configured to link compatible process fragments of the at least one flow document and the at least one process document, via linking at least one process fragment from the graphical process description from the at least one flow document with at least one process fragment from the process description from the at least one text document; and computer program code configured to compute from the assigned similarity scores an aggregated similarity score between the at least one text document and the at least one flow document. 7. The system according to claim 1 , wherein the process fragments from the separate canonical representations comprise one or more of single content strings, single content parts, content list parts, and content table parts extracted from the process documents; and wherein the computer program code configured to compare the process fragments from the separate canonical representations is further configured to compare: two single content strings; single content parts and content list parts; single content parts and content table parts; parts of two content lists; content list parts and content table parts; and parts of two content tables. | 0.5 |
8,676,722 | 26 | 31 | 26. A computer implemented method for synthesizing media utilizing a semantic network, the method comprising: (a) generating, or facilitating the generation of, by one or more computer processors, a thought network including: an active concept translated from a text query received from a human user, selected data entities from an information domain, and relationships derived between the active concept and the selected data entities, the generating comprising: including the active concept as a node in the thought network, and populating the thought network at least in part with the selected data entities from the information domain and the derived relationships between the active concept and the selected data entities; and (b) transforming the thought network to generate and provide one or more forms of synthesized media to the human user. | 26. A computer implemented method for synthesizing media utilizing a semantic network, the method comprising: (a) generating, or facilitating the generation of, by one or more computer processors, a thought network including: an active concept translated from a text query received from a human user, selected data entities from an information domain, and relationships derived between the active concept and the selected data entities, the generating comprising: including the active concept as a node in the thought network, and populating the thought network at least in part with the selected data entities from the information domain and the derived relationships between the active concept and the selected data entities; and (b) transforming the thought network to generate and provide one or more forms of synthesized media to the human user. 31. The computer implemented method of claim 26 , wherein the synthesized media is produced in batches. | 0.85452 |
9,075,601 | 15 | 16 | 15. The computer program product of claim 12 , wherein the software application is free of a scripting environment for execution of the script prior to the code injection of the scripting engine. | 15. The computer program product of claim 12 , wherein the software application is free of a scripting environment for execution of the script prior to the code injection of the scripting engine. 16. The computer program product of claim 15 , wherein the software application is based on a static programming language, and wherein the script is based on a dynamic programming language. | 0.5 |
9,471,566 | 27 | 28 | 27. The system as recited in claim 26 , wherein, for each word in the language model with alternative pronunciations, each word/pronunciation alternative is assigned one of two or more pronunciation types. | 27. The system as recited in claim 26 , wherein, for each word in the language model with alternative pronunciations, each word/pronunciation alternative is assigned one of two or more pronunciation types. 28. The system as recited in claim 27 , wherein a single most common word/pronunciation alternative is assigned a major pronunciation type, wherein one or more relatively rare word/pronunciation alternatives are assigned an ignored pronunciation type, and wherein other word/pronunciation alternatives are assigned a normal pronunciation type. | 0.800349 |
8,812,493 | 1 | 4 | 1. A computer-implemented relevance system, comprising: one or more processors; and a memory coupled to the one or more processors, the memory storing instructions which, when executed by the one or more processors, cause the one or more processors to: extract document information from a document received as search results based on a query string, the document information including a universal resource locator wherein the universal resource locator includes a compound term; split the compound term into multiple, separate terms; find at least one of the multiple, separate terms in a dictionary of terms; generate a target data string based on the extracted document information, the target data string including one of the multiple, separate terms found in the dictionary; and compute edit distance between the target data string and the query string, the edit distance employed in determining relevance of a document as part of result ranking. | 1. A computer-implemented relevance system, comprising: one or more processors; and a memory coupled to the one or more processors, the memory storing instructions which, when executed by the one or more processors, cause the one or more processors to: extract document information from a document received as search results based on a query string, the document information including a universal resource locator wherein the universal resource locator includes a compound term; split the compound term into multiple, separate terms; find at least one of the multiple, separate terms in a dictionary of terms; generate a target data string based on the extracted document information, the target data string including one of the multiple, separate terms found in the dictionary; and compute edit distance between the target data string and the query string, the edit distance employed in determining relevance of a document as part of result ranking. 4. The system of claim 1 , further comprising instructions for filtering anchor text of the document information at index time to compute a top-ranked set of anchor text. | 0.796163 |
8,090,873 | 1 | 14 | 1. A method for processing messages, the method comprising the steps of: a computer system: receiving, from a plurality of different data sources in a data network, a plurality of data messages each having a data type associated therewith and comprising a payload, wherein the plurality of data messages comprises different data formats; for each of the data messages, determining a classification of the data message by parsing out information identifying the data type; re-formatting each of the data messages, each of the re-formatted messages having a uniform data structure comprising an identifier, the classification, and the payload; selecting a message service queue for each of the reformatted messages from a plurality of message service queues each dedicated to storing messages of a particular data type according to the classifications of the reformatted messages such that each of the selected service queues store a subset of the reformatted messages of a single data type; with a parsing processor, monitoring the plurality of message service queues; and with a parsing processor, selecting one of the message service queues based on the monitoring and then retrieving and parsing a next one of the reformatted messages from the selected one of the message service queues in accordance with a target output data model, wherein the parsing processor comprises a plurality of parsers each operable to parse data messages having a different data type and wherein the parsing processor parses the next one of the reformatted messages using one of the plurality of parsers that is configured for parsing the data type associated with the selected service queue and is dynamically selected and allocated during the parsing step, wherein the parsing processor, during the parsing step, selects one of the parsers to use for parsing the next one of the reformatted messages based on the data type and at least one parsing rule applied to one or more characteristics of the next one of the reformatted messages and wherein the plurality of parsers includes at least two parsers adapted for parsing the data type associated with the selected service queue, and wherein the parsing includes extracting a subset of information in the payload of the next one of the reformatted messages defined in the target output data model, whereby throughput of the parsing processor is enhanced by extracting only select information from each of the data messages. | 1. A method for processing messages, the method comprising the steps of: a computer system: receiving, from a plurality of different data sources in a data network, a plurality of data messages each having a data type associated therewith and comprising a payload, wherein the plurality of data messages comprises different data formats; for each of the data messages, determining a classification of the data message by parsing out information identifying the data type; re-formatting each of the data messages, each of the re-formatted messages having a uniform data structure comprising an identifier, the classification, and the payload; selecting a message service queue for each of the reformatted messages from a plurality of message service queues each dedicated to storing messages of a particular data type according to the classifications of the reformatted messages such that each of the selected service queues store a subset of the reformatted messages of a single data type; with a parsing processor, monitoring the plurality of message service queues; and with a parsing processor, selecting one of the message service queues based on the monitoring and then retrieving and parsing a next one of the reformatted messages from the selected one of the message service queues in accordance with a target output data model, wherein the parsing processor comprises a plurality of parsers each operable to parse data messages having a different data type and wherein the parsing processor parses the next one of the reformatted messages using one of the plurality of parsers that is configured for parsing the data type associated with the selected service queue and is dynamically selected and allocated during the parsing step, wherein the parsing processor, during the parsing step, selects one of the parsers to use for parsing the next one of the reformatted messages based on the data type and at least one parsing rule applied to one or more characteristics of the next one of the reformatted messages and wherein the plurality of parsers includes at least two parsers adapted for parsing the data type associated with the selected service queue, and wherein the parsing includes extracting a subset of information in the payload of the next one of the reformatted messages defined in the target output data model, whereby throughput of the parsing processor is enhanced by extracting only select information from each of the data messages. 14. The method of claim 1 , wherein the at least one parsing rule defines messages to process with a grid parser and wherein the plurality of parsers includes two or more grid parsers. | 0.727003 |
9,524,335 | 1 | 3 | 1. One or more computer-readable storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method for entity conflation using a persistent entity index, the method comprising: receiving information about an entity, the information including at least one attribute associated with the entity, the at least one attribute describing a characteristic of the entity; matching the entity with one or more existing entities in the persistent entity index, wherein the persistent entity index includes entity-attribute pairs associated therewith and the entity-attribute pairs include all received attributes that describe one or more characteristics of an associated entity; determining whether the at least one attribute describing the one or more characteristics of the entity is present within the persistent entity index; aggregating the at least one attribute associated with the entity with the entity-attribute pairs within the persistent entity index; and incrementally updating the persistent entity index to include updated entity-attribute pairs including any subsequently received attributes describing one or more characteristics of the entity at a predetermined time interval. | 1. One or more computer-readable storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method for entity conflation using a persistent entity index, the method comprising: receiving information about an entity, the information including at least one attribute associated with the entity, the at least one attribute describing a characteristic of the entity; matching the entity with one or more existing entities in the persistent entity index, wherein the persistent entity index includes entity-attribute pairs associated therewith and the entity-attribute pairs include all received attributes that describe one or more characteristics of an associated entity; determining whether the at least one attribute describing the one or more characteristics of the entity is present within the persistent entity index; aggregating the at least one attribute associated with the entity with the entity-attribute pairs within the persistent entity index; and incrementally updating the persistent entity index to include updated entity-attribute pairs including any subsequently received attributes describing one or more characteristics of the entity at a predetermined time interval. 3. The one or more computer-readable storage media of claim 1 , wherein ranking the entity with respect to the one or more matched existing entities comprises ranking the entity utilizing the at least one attribute and using the machine-learning approach. | 0.5 |
7,475,062 | 14 | 16 | 14. A computer implemented method comprising: specifying a reporting objective; receiving metadata for a first set of report templates; and applying the reporting objective to select a subset of report templates from the first set of report templates based on the metadata; wherein the metadata includes an element of metadata selected from the group consisting of: a second set of report templates; a selection rule; a question; a rating for the question; and a model determining costs associated with deploying the subset of report templates. | 14. A computer implemented method comprising: specifying a reporting objective; receiving metadata for a first set of report templates; and applying the reporting objective to select a subset of report templates from the first set of report templates based on the metadata; wherein the metadata includes an element of metadata selected from the group consisting of: a second set of report templates; a selection rule; a question; a rating for the question; and a model determining costs associated with deploying the subset of report templates. 16. The method of claim 14 further comprising constructing a selection table for the set of report templates based on the metadata. | 0.691038 |
7,640,158 | 1 | 9 | 1. A method performed by a computer processor executing computer program instructions tangibly stored on a first computer-readable medium, the method comprising steps of: (A) tangibly storing, on a second computer-readable medium, a data structure representing a plurality of editing patterns of the form T=(D,E,C), wherein each of the plurality of editing patterns relates particular content D in an original document corpus to corresponding content E in an edited document corpus in a context C shared by contents D and E, wherein the original document corpus and the edited document corpus are tangibly stored on a third and fourth computer-readable medium, respectively; (B) deriving a plurality of correction rules, tangibly stored on a fifth computer-readable medium, from the plurality of editing patterns; and (C) deriving a classifier, tangibly stored on a sixth computer-readable medium, for particular content D based on the data structure representing the plurality of editing patterns, the classifier defining decision criteria for selecting one of the plurality of correction rules to apply to content D based on a context C* of content D. | 1. A method performed by a computer processor executing computer program instructions tangibly stored on a first computer-readable medium, the method comprising steps of: (A) tangibly storing, on a second computer-readable medium, a data structure representing a plurality of editing patterns of the form T=(D,E,C), wherein each of the plurality of editing patterns relates particular content D in an original document corpus to corresponding content E in an edited document corpus in a context C shared by contents D and E, wherein the original document corpus and the edited document corpus are tangibly stored on a third and fourth computer-readable medium, respectively; (B) deriving a plurality of correction rules, tangibly stored on a fifth computer-readable medium, from the plurality of editing patterns; and (C) deriving a classifier, tangibly stored on a sixth computer-readable medium, for particular content D based on the data structure representing the plurality of editing patterns, the classifier defining decision criteria for selecting one of the plurality of correction rules to apply to content D based on a context C* of content D. 9. The method of claim 1 , wherein the step (C) comprises a step of using an automated transcription system to transcribe speech to produce the original document corpus. | 0.847197 |
8,560,372 | 1 | 4 | 1. A computer-implemented method for implementation by one or more data processors comprising: receiving, by at least one of the data processors, data characterizing a workflow of a process; and generating, by at least one of the data processors, a network representation of event-condition-action rules representing the workflow; wherein the network representation of event-condition-action rules comprises a combination of source nodes representing events, operator nodes representing conditions, and action nodes representing transactions, and wherein the events of the source nodes are represented as types of objects of a type language. | 1. A computer-implemented method for implementation by one or more data processors comprising: receiving, by at least one of the data processors, data characterizing a workflow of a process; and generating, by at least one of the data processors, a network representation of event-condition-action rules representing the workflow; wherein the network representation of event-condition-action rules comprises a combination of source nodes representing events, operator nodes representing conditions, and action nodes representing transactions, and wherein the events of the source nodes are represented as types of objects of a type language. 4. The method of claim 1 , wherein the generating comprises generating, by at least one of the data processors, a network of event-condition-action rules for each component of the workflow to generate a set of networks and linking the networks to reflect a linking of components of the workflow. | 0.5 |
7,971,195 | 8 | 16 | 8. A computer-implemented method for compiling instructions in an asynchronous transactional messaging language, said method comprising: iteratively compiling a predetermined number of times said instructions in said asynchronous transactional messaging language for providing compilation units, wherein said predetermined number is determined in accordance with a level of dependency of variables within said asynchronous transactional messaging language; organizing said compilation units into a tree; traversing said tree in depth first traversal order; and translating selected encountered compilation units into corresponding second instructions compatible with web services. | 8. A computer-implemented method for compiling instructions in an asynchronous transactional messaging language, said method comprising: iteratively compiling a predetermined number of times said instructions in said asynchronous transactional messaging language for providing compilation units, wherein said predetermined number is determined in accordance with a level of dependency of variables within said asynchronous transactional messaging language; organizing said compilation units into a tree; traversing said tree in depth first traversal order; and translating selected encountered compilation units into corresponding second instructions compatible with web services. 16. A method in accordance with claim 8 , wherein said asynchronous transactional messaging language is an XLANG/s-like language. | 0.881434 |
9,135,469 | 1 | 4 | 1. A system comprising: a hardware processor; a parser to, parse user interface information to be included within a user interface to be displayed to a user by an information display application; and identify at least one field, within the user interface, to receive user information from a user; a memory storage device to store data, the data including: the user information, the user interface information, a predefined authorized set of fields to receive the user information, predefined information corresponding to the predefined authorized set of fields, a list of addresses of fraudulent sources of the user interface information, and a list of addresses of verified sources of the user interface information; a detection module to determine, based on the list of addresses of fraudulent sources and based on the list of addresses of verified sources, whether the user interface information is associated with fraudulent activity or originates from a verified source; a form fill module to, in response to determining that the user interface information is associated with fraudulent activity, provide, using the hardware processor, a warning indicia relative to the at least one field of the user interface displayed to the user by the information display application, disable automatic provision of the user information into the at least one field, and prevent the user from manually inputting information into the at least one field that is displayed to the user by the information display application, and in response to determining that the user interface information originates from a verified source, enable automatic provision of the user information into the at least one field based on the at least one field corresponding to the predefined authorized set of fields and based on predefined information that corresponds to the at least one field; and a disposable credit card number module to, generate, in response to the determining that the user interface information originates from a verified source, a limited use credit card number for a financial transaction, and provide the limited use credit card number to the form fill module, wherein the form fill module is configured to automatically fill the limited use credit card number into a credit card number field, designated as such by the detection module, for the financial transaction in response to receiving the limited use credit card number from the disposable credit card number module and based on the credit card number field corresponding to the predefined authorized set of fields. | 1. A system comprising: a hardware processor; a parser to, parse user interface information to be included within a user interface to be displayed to a user by an information display application; and identify at least one field, within the user interface, to receive user information from a user; a memory storage device to store data, the data including: the user information, the user interface information, a predefined authorized set of fields to receive the user information, predefined information corresponding to the predefined authorized set of fields, a list of addresses of fraudulent sources of the user interface information, and a list of addresses of verified sources of the user interface information; a detection module to determine, based on the list of addresses of fraudulent sources and based on the list of addresses of verified sources, whether the user interface information is associated with fraudulent activity or originates from a verified source; a form fill module to, in response to determining that the user interface information is associated with fraudulent activity, provide, using the hardware processor, a warning indicia relative to the at least one field of the user interface displayed to the user by the information display application, disable automatic provision of the user information into the at least one field, and prevent the user from manually inputting information into the at least one field that is displayed to the user by the information display application, and in response to determining that the user interface information originates from a verified source, enable automatic provision of the user information into the at least one field based on the at least one field corresponding to the predefined authorized set of fields and based on predefined information that corresponds to the at least one field; and a disposable credit card number module to, generate, in response to the determining that the user interface information originates from a verified source, a limited use credit card number for a financial transaction, and provide the limited use credit card number to the form fill module, wherein the form fill module is configured to automatically fill the limited use credit card number into a credit card number field, designated as such by the detection module, for the financial transaction in response to receiving the limited use credit card number from the disposable credit card number module and based on the credit card number field corresponding to the predefined authorized set of fields. 4. The system of claim 1 , wherein the parser forms part of the form fill module. | 0.870607 |
9,152,763 | 8 | 10 | 8. Apparatus comprising: a processor; and a memory storing processor-executable instructions that, when executed by the processor, perform a method comprising: collecting an initial set of clinical information documenting a medical practitioner's encounter with a patient, the encounter being of a particular type; determining, based on the particular type of the encounter, information that one or more reporting standards specify for inclusion in documentation of encounters of the particular type; analyzing the initial set of clinical information with respect to the information specified by the one or more reporting standards, using a processor, to identify additional information that is specified by the one or more reporting standards for documenting the particular type of patient encounter and that is not included in the initial set of clinical information documenting the encounter; and prompting a user to record the additional information specified by the one or more reporting standards for documenting the encounter between the medical practitioner and the patient. | 8. Apparatus comprising: a processor; and a memory storing processor-executable instructions that, when executed by the processor, perform a method comprising: collecting an initial set of clinical information documenting a medical practitioner's encounter with a patient, the encounter being of a particular type; determining, based on the particular type of the encounter, information that one or more reporting standards specify for inclusion in documentation of encounters of the particular type; analyzing the initial set of clinical information with respect to the information specified by the one or more reporting standards, using a processor, to identify additional information that is specified by the one or more reporting standards for documenting the particular type of patient encounter and that is not included in the initial set of clinical information documenting the encounter; and prompting a user to record the additional information specified by the one or more reporting standards for documenting the encounter between the medical practitioner and the patient. 10. The apparatus of claim 8 , wherein the additional information corresponds to at least one standard code. | 0.76 |
7,506,022 | 7 | 8 | 7. The system of claim 6 wherein the recognition server receives the input speech data and the indication of the grammar. | 7. The system of claim 6 wherein the recognition server receives the input speech data and the indication of the grammar. 8. The system of claim 7 wherein the grammar is stored on each of the client devices and transferred to the recognition server with the input speech data. | 0.5 |
8,924,330 | 1 | 12 | 1. A method of operating a computer to provide a response to a received user input, the method comprising: automatically with the computer: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a complete user input representing the entire answerable statement, calculating for each of a plurality of predefined answerable statements, a metric that is, at least in part, based on a frequency with which the predefined answerable statement had been selected by previous users; (b) if the metric for none of the predefined answerable statements exceeds a threshold, sending, to the user's device, information representing a selected plurality of the predefined answerable statements, which predefined answerable statements are selected based on the respective associated metrics; and (c) if the metric for one of the predefined answerable statements exceeds the threshold and not otherwise, sending, to the user's device, information representing a response associated with said one of the predefined answerable statements. | 1. A method of operating a computer to provide a response to a received user input, the method comprising: automatically with the computer: (a) in response to receiving, from a user's device, a partial user input signifying a portion of an answerable statement, before receiving a complete user input representing the entire answerable statement, calculating for each of a plurality of predefined answerable statements, a metric that is, at least in part, based on a frequency with which the predefined answerable statement had been selected by previous users; (b) if the metric for none of the predefined answerable statements exceeds a threshold, sending, to the user's device, information representing a selected plurality of the predefined answerable statements, which predefined answerable statements are selected based on the respective associated metrics; and (c) if the metric for one of the predefined answerable statements exceeds the threshold and not otherwise, sending, to the user's device, information representing a response associated with said one of the predefined answerable statements. 12. The method of claim 1 wherein the information sent to the user's device in part (b) consists of the selected plurality of predefined answerable statements ranked in order of their respective metrics. | 0.768793 |
9,965,465 | 1 | 2 | 1. A language understanding system, the language understanding system comprising: a trained language understanding server, the trained language understanding server comprising: at least one processor; and memory encoding computer executable instructions that, when executed by the at least one processor, perform a method comprising: receiving a natural language input from a client device; sending the natural language input to a plurality of feature extractors in response to receiving the natural language input; receiving potential features from the plurality of feature extractors after sending the natural language input to the plurality of feature extractors; evaluating the potential features to determine input features for the natural language input; determining a semantic meaning of the natural language input based on the input features; and sending a response to the client device that includes the semantic meaning of the natural language input. | 1. A language understanding system, the language understanding system comprising: a trained language understanding server, the trained language understanding server comprising: at least one processor; and memory encoding computer executable instructions that, when executed by the at least one processor, perform a method comprising: receiving a natural language input from a client device; sending the natural language input to a plurality of feature extractors in response to receiving the natural language input; receiving potential features from the plurality of feature extractors after sending the natural language input to the plurality of feature extractors; evaluating the potential features to determine input features for the natural language input; determining a semantic meaning of the natural language input based on the input features; and sending a response to the client device that includes the semantic meaning of the natural language input. 2. The language understanding system of claim 1 , wherein the plurality of feature extractors are each located on different feature servers, and wherein the trained language understanding server is separate from the different feature servers. | 0.5 |
9,317,555 | 4 | 5 | 4. The method of claim 1 , further comprising: updating, by one or more processors, the status information of each copy of each database table in the distributed database system. | 4. The method of claim 1 , further comprising: updating, by one or more processors, the status information of each copy of each database table in the distributed database system. 5. The method of claim 4 , further comprising: requesting, by one or more processors, status information of each copy, of said each database table in the distributed database system, from the database device which stores said each copy; receiving, by one or more processors, a latest status information of a copy of the database table that is sent by the database device in response to the received request; and updating, by one or more processors, current status information of a copy of the database table with received latest status information of the copy of the database table. | 0.5 |
8,468,142 | 2 | 3 | 2. The method of claim 1 , wherein: the sixth BDD comprises: a binary 0 terminal node; a binary 1 terminal node; and a plurality of paths, each path comprising a plurality of decision nodes and leading to either the 0 terminal node or the 1 terminal node, and for each of the paths that leads to the 1 terminal node, a web page represented by first one or more of the decision nodes on the path is included in a search result for a search query represented by second one or more of the decision nodes on the path. | 2. The method of claim 1 , wherein: the sixth BDD comprises: a binary 0 terminal node; a binary 1 terminal node; and a plurality of paths, each path comprising a plurality of decision nodes and leading to either the 0 terminal node or the 1 terminal node, and for each of the paths that leads to the 1 terminal node, a web page represented by first one or more of the decision nodes on the path is included in a search result for a search query represented by second one or more of the decision nodes on the path. 3. The method of claim 2 , further comprising: receiving, by the one or more computer systems, a new search query, the new search query comprising one or more of the words; searching, by the one or more computer systems, through the sixth BDD; for each of the paths that leads to the 1 terminal node, if the search query on the path equals the new search query, then including, by the one or more computer systems, all web pages on the path in a search result for the new search query; and returning, by the one or more computer systems, the search result in response to the new search query. | 0.5 |
5,434,929 | 1 | 3 | 1. A method for indicating preferred character handwriting styles in a pen-based computer system that includes an input screen, a stylus for engaging the screen to input handwritten text to the computer system, and a recognizer for recognizing handwritten text, the method comprising the steps of: activating a character style preference editor; displaying a plurality of variant character styles for a selected character, each variant character style representing a distinct style of writing the selected character that is recognizable by the recognizer; and receiving inputs indicative of the likelihood that a handwritten character input with the stylus will have a form analogous to a selected variant character style and setting a use probability factor associated with the selected variant character style in accordance with the input. | 1. A method for indicating preferred character handwriting styles in a pen-based computer system that includes an input screen, a stylus for engaging the screen to input handwritten text to the computer system, and a recognizer for recognizing handwritten text, the method comprising the steps of: activating a character style preference editor; displaying a plurality of variant character styles for a selected character, each variant character style representing a distinct style of writing the selected character that is recognizable by the recognizer; and receiving inputs indicative of the likelihood that a handwritten character input with the stylus will have a form analogous to a selected variant character style and setting a use probability factor associated with the selected variant character style in accordance with the input. 3. A method as recited in claim 1 further including processing inputs made to said character style preference editor. | 0.768775 |
8,046,736 | 13 | 16 | 13. A non-transitory computer-readable medium holding executable instructions for performing a method for reproducing a result using generated dynamically typed programming language code, the medium comprising: instructions for receiving a user selection via a graphical user interface (GUI), where the user selection is related to a processing choice that produces the result when the processing choice is applied to data; instructions for storing the user selection, the processing choice, the result, or the data in a data structure; and instructions for generating the dynamically typed programming language code, where the generated dynamically typed programming language code is used to process the data when the processing choice is received from the data structure, wherein the generated dynamically typed programming language code reproduces the result when the generated dynamically typed programming language code is used with the data. | 13. A non-transitory computer-readable medium holding executable instructions for performing a method for reproducing a result using generated dynamically typed programming language code, the medium comprising: instructions for receiving a user selection via a graphical user interface (GUI), where the user selection is related to a processing choice that produces the result when the processing choice is applied to data; instructions for storing the user selection, the processing choice, the result, or the data in a data structure; and instructions for generating the dynamically typed programming language code, where the generated dynamically typed programming language code is used to process the data when the processing choice is received from the data structure, wherein the generated dynamically typed programming language code reproduces the result when the generated dynamically typed programming language code is used with the data. 16. The computer-readable medium of claim 13 , wherein the string arrays are written to a file. | 0.817308 |
8,260,790 | 16 | 17 | 16. The method of claim 14 , wherein the identifier values are arbitrary, non-integer values, further comprising: estimating a size of the index file, whereby a number of locations in the index file is estimated; filling each location in the index file with an invalid entry value; parsing the static XML document, comprising; using a hashing scheme, converting the identifier values to integer values, and dividing the integer values by the number of locations in the index file; storing the divided integer values at locations having invalid entries; and if required, resizing the index file and reparsing the static XML document. | 16. The method of claim 14 , wherein the identifier values are arbitrary, non-integer values, further comprising: estimating a size of the index file, whereby a number of locations in the index file is estimated; filling each location in the index file with an invalid entry value; parsing the static XML document, comprising; using a hashing scheme, converting the identifier values to integer values, and dividing the integer values by the number of locations in the index file; storing the divided integer values at locations having invalid entries; and if required, resizing the index file and reparsing the static XML document. 17. The method of claim 16 , further comprising storing hash values in the index file. | 0.674242 |
7,523,137 | 15 | 16 | 15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event. | 15. A computer implemented method for event analysis comprising: reading from a computer readable memory an information source model to determine an information source; retrieving an article from the information source; reading from a computer readable memory an environment model comprising a first model entity and a focus entity, and a focus relationship from the focus entity to the first model entity; initiating, with a processor coupled to the computer readable memory, execution of an event detection engine on the article to detect an event involving the first model entity represented in the article which is relevant to the focus entity based on the focus relationship and generate an event object comprising: an event type field; an event type probability field; an importance field; and a public interest field; reading from a computer readable memory an event implication model; initiating execution, with a processor, of an event implication engine on the event object to determine an inferred event on behalf of the focus entity in view of the focus relationship and an implication message which are relevant to the focus entity; recognizing that the focus relationship exists between the focus entity and the first model entity and responsively generating the inferred event due to detection of the event involving the first model entity; and creating a new event object from the inferred event. 16. The method of claim 15 , where reading an event implication model comprises: reading a trigger constraint and a resulting implication. | 0.713693 |
7,977,562 | 1 | 5 | 1. A method for creating a synthesized singing voice waveform, comprising: receiving a request to create the synthesized singing voice waveform; receiving lyrics of a song and a digital melody file for the lyrics; determining a sequence of contextual parametric models that corresponds to sub-phonemic units of the received lyrics; determining a sequence of notes from the received digital melody; determining a duration time for each of the notes from the received digital melody; generating a sequence of line spectral pair coefficients from the sequence of contextual parametric models and from the duration times; and synthesizing the synthesized singing voice waveform based on linear predictive coding of the sequence of line spectral pair coefficients and the sequence of notes. | 1. A method for creating a synthesized singing voice waveform, comprising: receiving a request to create the synthesized singing voice waveform; receiving lyrics of a song and a digital melody file for the lyrics; determining a sequence of contextual parametric models that corresponds to sub-phonemic units of the received lyrics; determining a sequence of notes from the received digital melody; determining a duration time for each of the notes from the received digital melody; generating a sequence of line spectral pair coefficients from the sequence of contextual parametric models and from the duration times; and synthesizing the synthesized singing voice waveform based on linear predictive coding of the sequence of line spectral pair coefficients and the sequence of notes. 5. The method of claim 1 , wherein synthesizing the lyrics with the melody comprises: breaking down words in the lyrics into sub-phonemic units; converting the sub-phonemic units into a sequence of contextual labels; and determining a matching contextual parametric model for each contextual label, wherein the sequence of contextual parametric models is comprised of the matching contextual model for each contextual label. | 0.5 |
8,160,877 | 12 | 13 | 12. The non-transitory computer readable medium of claim 9 , the instructions when executed by the processor further comprising functionality for: generating pre-processed speech data by removing silence frames and oversaturation frames from the speech data as well as normalizing loudness of the speech data, wherein the plurality of MFCC and the plurality of GMM components are extracted from the pre-processed speech data. | 12. The non-transitory computer readable medium of claim 9 , the instructions when executed by the processor further comprising functionality for: generating pre-processed speech data by removing silence frames and oversaturation frames from the speech data as well as normalizing loudness of the speech data, wherein the plurality of MFCC and the plurality of GMM components are extracted from the pre-processed speech data. 13. The non-transitory computer readable medium of claim 12 , wherein the speech data is less than 3 seconds in duration. | 0.5 |
8,214,349 | 1 | 5 | 1. A computer implemented method for processing data, the method comprising the steps of: receiving one or more data objects associated with a term database, wherein the one or more data objects contain data associated with one or more terms; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term; and associating the at least one term with the identified content; wherein the one or more data objects associated with the term database provide a representation of at least a portion of the term database at one or more remote computers and are used to link the identified content with the at least one term. | 1. A computer implemented method for processing data, the method comprising the steps of: receiving one or more data objects associated with a term database, wherein the one or more data objects contain data associated with one or more terms; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term; and associating the at least one term with the identified content; wherein the one or more data objects associated with the term database provide a representation of at least a portion of the term database at one or more remote computers and are used to link the identified content with the at least one term. 5. The method of claim 1 , wherein the content comprises one or more of definitions, related products, related services, sponsorship information, translation, and reference works. | 0.58945 |
8,862,582 | 9 | 12 | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving scene description information associated with an image, the scene description information comprising semantic data for a plurality of objects within the images; assigning a weight to each object in the plurality of objects based on the semantic data, the weight being independent of a geographic location, to yield weighted scene description information; organizing the image and the weighted scene description information into a data structure, wherein the data structure comprises, for each object in the plurality of objects, a storage array as an infinite array of the each object; classifying the image based on the data structure to, yield a classified image; modifying the weight of a specific object in the plurality of objects based on user search preferences and repeated searching for the specific object, to yield a modified object weight; storing the modified object weight for the specific object in the infinite array for the specific object; and upon receiving a search query, responding to the search query by returning matching images in the image database based on a comparison of the search query to the data structure using the modified object weight. | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving scene description information associated with an image, the scene description information comprising semantic data for a plurality of objects within the images; assigning a weight to each object in the plurality of objects based on the semantic data, the weight being independent of a geographic location, to yield weighted scene description information; organizing the image and the weighted scene description information into a data structure, wherein the data structure comprises, for each object in the plurality of objects, a storage array as an infinite array of the each object; classifying the image based on the data structure to, yield a classified image; modifying the weight of a specific object in the plurality of objects based on user search preferences and repeated searching for the specific object, to yield a modified object weight; storing the modified object weight for the specific object in the infinite array for the specific object; and upon receiving a search query, responding to the search query by returning matching images in the image database based on a comparison of the search query to the data structure using the modified object weight. 12. The system of claim 9 , the computer-readable storage medium having additional instructions stored which result in the operations further comprising: after storing the classified image in the database and upon retrieval of the image from the image database, receiving second scene description information associated with the image and storing the second scene description information into the data structure. | 0.576132 |
8,346,683 | 1 | 3 | 1. A computer system tangibly operating in an information technology hardware and software environment, comprising: a knowledge base model for representation and storage of regulatory knowledge, the regulatory knowledge including the following knowledge base model entities: regulations, procedures, parameters, concepts, decisions, rules, service calls, and their features and relationships to other knowledge base model entities; a data interface model for representation and storage of regulatory data, the regulatory data including the following groups of data interface model entities: simple transactional events, complex events, referential entities, profiles, and their features and their relationships to other data interface model entities and their relationships to knowledge base model entities; a reasoning session data model for representation and storage of the reasoning session data, the reasoning session data including the following reasoning session data model entities: reasoning sessions, session events, and their features and their relationships to other session data model entities and their relationships to data interface model entities and their relationships to knowledge base model entities; an interface configured to receive a request in the form of a structured or semi-structured message from an external source, to pass the received message to a reasoning session controller, and upon receiving a response from the reasoning session controller, pass that response to the external source; a reasoning session controller configured to receive an input request from the interface and to match the input request to a decision record from the knowledge base model decision entity, execute programmable instructions from the decision record, perform post-processing tasks after execution of the programmable instructions is completed, and select a next new session event for execution; a library of procedures configured to be invoked by a service call, take a subset of parameters established by a reasoning session and use those parameters to call external services, and place results returned by the external services in a data interface repository. | 1. A computer system tangibly operating in an information technology hardware and software environment, comprising: a knowledge base model for representation and storage of regulatory knowledge, the regulatory knowledge including the following knowledge base model entities: regulations, procedures, parameters, concepts, decisions, rules, service calls, and their features and relationships to other knowledge base model entities; a data interface model for representation and storage of regulatory data, the regulatory data including the following groups of data interface model entities: simple transactional events, complex events, referential entities, profiles, and their features and their relationships to other data interface model entities and their relationships to knowledge base model entities; a reasoning session data model for representation and storage of the reasoning session data, the reasoning session data including the following reasoning session data model entities: reasoning sessions, session events, and their features and their relationships to other session data model entities and their relationships to data interface model entities and their relationships to knowledge base model entities; an interface configured to receive a request in the form of a structured or semi-structured message from an external source, to pass the received message to a reasoning session controller, and upon receiving a response from the reasoning session controller, pass that response to the external source; a reasoning session controller configured to receive an input request from the interface and to match the input request to a decision record from the knowledge base model decision entity, execute programmable instructions from the decision record, perform post-processing tasks after execution of the programmable instructions is completed, and select a next new session event for execution; a library of procedures configured to be invoked by a service call, take a subset of parameters established by a reasoning session and use those parameters to call external services, and place results returned by the external services in a data interface repository. 3. The system of claim 1 , wherein the procedure entity comprises multiple business procedures described by feature-value pairs that correspond to features of a business procedure formal definition and by relations to knowledge base model regulations, concepts, decisions, and parameters. | 0.792806 |
8,966,589 | 1 | 13 | 1. A method for providing for exception handling of interactive user communications privileges in a domain server governing interactive user communications privileges with entities outside a domain, comprising: monitoring a communication between a first user entity inside the domain and a second user entity outside the domain; in response to the communication, gathering insight information about the second user entity outside the domain; determining allowed interactive user communications privileges that identify one or more allowed types of interactive user communications between the first user entity and the second user entity outside the domain based on the insight information; receiving, in the domain server from the first user entity inside the domain, an interactive user communications privilege exception request comprising at least one non-allowed interactive user communications privilege for the second user entity outside the domain; sending, to a domain administrator, a permission request that identifies the at least one non-allowed interactive user communications privilege for the second user entity outside the domain: receiving, by the domain server, a message that indicates whether the interactive user communications privilege exception request is approved or declined; and storing, in the domain server, the interactive user communications privilege exception request as interactive user communications privileges for the second user entity outside the domain if the interactive user communications privilege exception request is approved. | 1. A method for providing for exception handling of interactive user communications privileges in a domain server governing interactive user communications privileges with entities outside a domain, comprising: monitoring a communication between a first user entity inside the domain and a second user entity outside the domain; in response to the communication, gathering insight information about the second user entity outside the domain; determining allowed interactive user communications privileges that identify one or more allowed types of interactive user communications between the first user entity and the second user entity outside the domain based on the insight information; receiving, in the domain server from the first user entity inside the domain, an interactive user communications privilege exception request comprising at least one non-allowed interactive user communications privilege for the second user entity outside the domain; sending, to a domain administrator, a permission request that identifies the at least one non-allowed interactive user communications privilege for the second user entity outside the domain: receiving, by the domain server, a message that indicates whether the interactive user communications privilege exception request is approved or declined; and storing, in the domain server, the interactive user communications privilege exception request as interactive user communications privileges for the second user entity outside the domain if the interactive user communications privilege exception request is approved. 13. The method of claim 1 , further comprising establishing a requested communications session between the second user entity outside the domain and the first user entity inside the domain if the interactive user communications privileges allow the requested communications session between the second user entity outside the domain and the first user entity inside the domain. | 0.555556 |
6,162,059 | 1 | 2 | 1. A problem solving skills development system using a tactile recognition language, comprising: a supporting board; a plurality of sliding pieces slidably disposed on said supporting board and arranged in a grid having positions, wherein at least one of said positions is an empty position and said sliding pieces adjacent each said empty position are slidable into said empty position, whereby said sliding pieces are movable to any of said positions by shifting appropriate ones of said sliding pieces; and a plurality of tactile recognition blocks for removably engaging said sliding pieces, each of said tactile recognition blocks having a tactilly recognizable region on a surface thereof, wherein said tactilly recognizable regions on said tactile recognition blocks are arranged into a predetermined pattern by shifting said appropriate ones of said sliding pieces. | 1. A problem solving skills development system using a tactile recognition language, comprising: a supporting board; a plurality of sliding pieces slidably disposed on said supporting board and arranged in a grid having positions, wherein at least one of said positions is an empty position and said sliding pieces adjacent each said empty position are slidable into said empty position, whereby said sliding pieces are movable to any of said positions by shifting appropriate ones of said sliding pieces; and a plurality of tactile recognition blocks for removably engaging said sliding pieces, each of said tactile recognition blocks having a tactilly recognizable region on a surface thereof, wherein said tactilly recognizable regions on said tactile recognition blocks are arranged into a predetermined pattern by shifting said appropriate ones of said sliding pieces. 2. The problem solving skills development system of claim 1 wherein each of said sliding pieces include block engaging members for engaging said tactile recognition blocks. | 0.667954 |
7,571,455 | 11 | 13 | 11. A TV having a language selection function, comprising: a network interface unit configured to contact a translation site; a storing unit configured to store contact information for at least one translation site which corresponds to a plurality of languages and an operation program related to translation; a control unit configured to contact a translation site corresponding to a selected language based on the contact information stored in the storing unit, to transmit closed caption character information to be translated in accordance with the operation program stored in the storing unit, and to receive translated closed caption character information from the translation site; and a video processing unit configured to display the translated closed caption character information on a screen substantially in synch with corresponding audio information. | 11. A TV having a language selection function, comprising: a network interface unit configured to contact a translation site; a storing unit configured to store contact information for at least one translation site which corresponds to a plurality of languages and an operation program related to translation; a control unit configured to contact a translation site corresponding to a selected language based on the contact information stored in the storing unit, to transmit closed caption character information to be translated in accordance with the operation program stored in the storing unit, and to receive translated closed caption character information from the translation site; and a video processing unit configured to display the translated closed caption character information on a screen substantially in synch with corresponding audio information. 13. The TV having the language selection function according to claim 11 , wherein the control unit is configured to generate an OSD (On Screen Display) including the received closed caption character information, and to provide the OSD to the video processing unit in order to display the on OSD the screen. | 0.5 |
8,346,764 | 11 | 16 | 11. A computer-implemented method of retrieving documents, the method comprising: caching in a data structure a uniform resource locator for a document predefined to be relevant to at least a portion of a taxonomy; selecting by a server the taxonomy for a query received from an application presented by a client access device based on provenance of the application; processing the query against at least one database storing documents using at least one content-based search engine to generate a search result that identifies at least one document relevant to the query according to a ranking order; extracting the uniform resource locator for the document predefined to be relevant from the search result if the uniform resource locator exists in the search result; associating at a position of the ranking order in the search result the uniform resource locator for the document predefined to be relevant to the at least a portion of the taxonomy; and returning the search result with the associated uniform resource locator for the document predefined to be relevant to the client access device. | 11. A computer-implemented method of retrieving documents, the method comprising: caching in a data structure a uniform resource locator for a document predefined to be relevant to at least a portion of a taxonomy; selecting by a server the taxonomy for a query received from an application presented by a client access device based on provenance of the application; processing the query against at least one database storing documents using at least one content-based search engine to generate a search result that identifies at least one document relevant to the query according to a ranking order; extracting the uniform resource locator for the document predefined to be relevant from the search result if the uniform resource locator exists in the search result; associating at a position of the ranking order in the search result the uniform resource locator for the document predefined to be relevant to the at least a portion of the taxonomy; and returning the search result with the associated uniform resource locator for the document predefined to be relevant to the client access device. 16. The method of claim 11 , wherein the method further comprises caching in a data structure a uniform resource locator for a document predefined to be relevant to at least a portion of the query. | 0.641818 |
9,177,022 | 1 | 5 | 1. A method for processing queries, comprising: receiving user input creating a pipeline configuration for executing a query from an input device; receiving a first query; obtaining a context and conditions of the first query; determining rules based on the context and the conditions of the first query by utilizing the pipeline configuration, wherein the rules are triggered in response to receiving the first query; applying the rules to the first query to determine additional queries to execute; executing the additional queries; receiving supplemental results from execution of each of the additional queries; receiving core results from execution of the first query; and mixing the received supplemental results with the core results to form mixed results. | 1. A method for processing queries, comprising: receiving user input creating a pipeline configuration for executing a query from an input device; receiving a first query; obtaining a context and conditions of the first query; determining rules based on the context and the conditions of the first query by utilizing the pipeline configuration, wherein the rules are triggered in response to receiving the first query; applying the rules to the first query to determine additional queries to execute; executing the additional queries; receiving supplemental results from execution of each of the additional queries; receiving core results from execution of the first query; and mixing the received supplemental results with the core results to form mixed results. 5. The method of claim 1 , wherein obtaining the context of the first query comprises obtaining another pipeline configuration that is associated with the first query from a cache that specifies the rules to apply to the first query. | 0.5 |
8,166,036 | 1 | 8 | 1. A computer-implemented method for enabling satisfaction of a search responsive to a query based on classification of the query, the method comprising: receiving, based on user input, a query phrase; parsing, with a processor, the received query phrase into at least a first constituent part and a second constituent part; determining, with a processor, a first category associated with the received query phrase by performing a first classification process that uses the first constituent part and the second constituent part, wherein the first classification process includes: accessing, from classification information stored in a storage medium that includes patterns, a pattern that is associated with at least one category, the pattern including a first part and a second part; comparing the determined definitional information of the first constituent part with the first part included in the accessed pattern and comparing the second constituent part with the second part included in the accessed pattern; based on the comparison results, determining whether the second constituent part and the determined definitional information of the first constituent part correspond to at least a subportion of the accessed pattern; and based on a determination that the second constituent part and the determined definitional information of the first constituent part correspond to at least a subportion of the accessed pattern, identifying the at least one category that is associated with the pattern as the first category associated with the received query phrase; determining a second category associated with the received query phrase by performing a second classification process that uses the first constituent part and the second constituent part, the second classification process being different than the first classification process; determining whether the first category determined by the first classification process matches the second category determined by the second classification process; in response to a determination that the first category matches the second category, associating the received query phrase with a category that corresponds to the first category and the second category; in response to a determination that the first category does not match the second category: selecting, from among the first category and the second category, a single category; and associating the received query phrase with the single category selected; and processing the received query phrase based on the associated category. | 1. A computer-implemented method for enabling satisfaction of a search responsive to a query based on classification of the query, the method comprising: receiving, based on user input, a query phrase; parsing, with a processor, the received query phrase into at least a first constituent part and a second constituent part; determining, with a processor, a first category associated with the received query phrase by performing a first classification process that uses the first constituent part and the second constituent part, wherein the first classification process includes: accessing, from classification information stored in a storage medium that includes patterns, a pattern that is associated with at least one category, the pattern including a first part and a second part; comparing the determined definitional information of the first constituent part with the first part included in the accessed pattern and comparing the second constituent part with the second part included in the accessed pattern; based on the comparison results, determining whether the second constituent part and the determined definitional information of the first constituent part correspond to at least a subportion of the accessed pattern; and based on a determination that the second constituent part and the determined definitional information of the first constituent part correspond to at least a subportion of the accessed pattern, identifying the at least one category that is associated with the pattern as the first category associated with the received query phrase; determining a second category associated with the received query phrase by performing a second classification process that uses the first constituent part and the second constituent part, the second classification process being different than the first classification process; determining whether the first category determined by the first classification process matches the second category determined by the second classification process; in response to a determination that the first category matches the second category, associating the received query phrase with a category that corresponds to the first category and the second category; in response to a determination that the first category does not match the second category: selecting, from among the first category and the second category, a single category; and associating the received query phrase with the single category selected; and processing the received query phrase based on the associated category. 8. The computer-implemented method of claim 1 further comprising modifying the received query phrase by at least one of adding words to the received query phrase, eliminating words from the received query phrase, and re-ordering words in the received query phrase; and processing a modified version of the received query phrase to generate at least one search result. | 0.829777 |
8,332,393 | 1 | 8 | 1. A method performed by a computer processor for refining a search, said method comprising: receiving a first search query comprising a first set of keywords; causing a first search to be performed using said first search query on a first search engine; receiving a first set of search results from said first search engine in response to said first search query; causing at least a portion of said first set of search results to be presented on a computer display; analyzing content contained in said first set of search results to derive a first set of related keywords related to the first set of keywords, the first set of related keywords for categorizing portions of the first set of search results into different categories; causing at least a portion of said first set of related keywords to be presented on said computer display, said related keywords being presented to indicate how the first search results are divided into different categories such that a user may select related keywords to refine the first search within specified categories from among the different categories; receiving at least one of said related keywords selected by said user, said at least one related keyword corresponding to one or more categories from among the different categories; refining the first search query based on said selected at least one of said related keywords to create a second search query; causing a second search to be performed using said second search query; receiving a second set of search results in response to said second search query, the second set of search results including content from the first set of search results refined into the one or more categories; causing at least a portion of said second set of search results to be presented on said computer display; determining a second set of related keywords; and causing at least a portion of said second set of related keywords to be presented on said computer display, said related keywords being presented such that a user may select at least one of said related keywords. | 1. A method performed by a computer processor for refining a search, said method comprising: receiving a first search query comprising a first set of keywords; causing a first search to be performed using said first search query on a first search engine; receiving a first set of search results from said first search engine in response to said first search query; causing at least a portion of said first set of search results to be presented on a computer display; analyzing content contained in said first set of search results to derive a first set of related keywords related to the first set of keywords, the first set of related keywords for categorizing portions of the first set of search results into different categories; causing at least a portion of said first set of related keywords to be presented on said computer display, said related keywords being presented to indicate how the first search results are divided into different categories such that a user may select related keywords to refine the first search within specified categories from among the different categories; receiving at least one of said related keywords selected by said user, said at least one related keyword corresponding to one or more categories from among the different categories; refining the first search query based on said selected at least one of said related keywords to create a second search query; causing a second search to be performed using said second search query; receiving a second set of search results in response to said second search query, the second set of search results including content from the first set of search results refined into the one or more categories; causing at least a portion of said second set of search results to be presented on said computer display; determining a second set of related keywords; and causing at least a portion of said second set of related keywords to be presented on said computer display, said related keywords being presented such that a user may select at least one of said related keywords. 8. The method of claim 1 further comprising: causing a third search to be performed using said first search query on a second search engine; receiving a third set of search results from said second search engine in response to said first search query; and causing at least a portion of said third set of search results to be presented on said computer display. | 0.621053 |
9,085,303 | 23 | 32 | 23. A vehicle personal assistant embodied in one or more non-transitory machine readable storage media, the vehicle personal assistant executable by a computing system to: receive a human-generated spoken natural language phrase; execute a semantic interpretation process on the human-generated spoken natural language phrase to derive, from the human-generated spoken natural language phrase, a trigger condition, a search action, and a search parameter to be used in executing the search action if the trigger condition is met, the trigger condition comprising a data value; monitor one or more vehicle-related real-time sensor inputs; compare a first vehicle-related real-time sensor input to the data value to determine whether the vehicle-related trigger condition has occurred; and in response to determining that the trigger condition has occurred: determine a current value of a second real-time input associated with the occurrence of the trigger condition; and execute the search action using (i) the current value of the second real-time input and (ii) the search parameter derived from the human-generated spoken natural language phrase. | 23. A vehicle personal assistant embodied in one or more non-transitory machine readable storage media, the vehicle personal assistant executable by a computing system to: receive a human-generated spoken natural language phrase; execute a semantic interpretation process on the human-generated spoken natural language phrase to derive, from the human-generated spoken natural language phrase, a trigger condition, a search action, and a search parameter to be used in executing the search action if the trigger condition is met, the trigger condition comprising a data value; monitor one or more vehicle-related real-time sensor inputs; compare a first vehicle-related real-time sensor input to the data value to determine whether the vehicle-related trigger condition has occurred; and in response to determining that the trigger condition has occurred: determine a current value of a second real-time input associated with the occurrence of the trigger condition; and execute the search action using (i) the current value of the second real-time input and (ii) the search parameter derived from the human-generated spoken natural language phrase. 32. The vehicle personal assistant of claim 23 , executable by the computing system to present further system-generated output in response to the further human-generated input. | 0.740413 |
8,226,416 | 3 | 32 | 3. A non-transitory computer readable medium containing an executable program for recognizing an utterance spoken by a reader, where the program performs the steps of: receiving text comprising one or more words to be read by the reader; generating a grammar for speech recognition, in accordance with the text; inserting at least one reading learner grammar feature into the grammar, wherein the at least one reading learner grammar feature comprises a recognition of at least one reading learner mistake; receiving the utterance; interpreting the utterance in accordance with the grammar; and outputting feedback indicative of reader performance. | 3. A non-transitory computer readable medium containing an executable program for recognizing an utterance spoken by a reader, where the program performs the steps of: receiving text comprising one or more words to be read by the reader; generating a grammar for speech recognition, in accordance with the text; inserting at least one reading learner grammar feature into the grammar, wherein the at least one reading learner grammar feature comprises a recognition of at least one reading learner mistake; receiving the utterance; interpreting the utterance in accordance with the grammar; and outputting feedback indicative of reader performance. 32. The non-transitory computer readable medium of claim 3 , wherein the text is received from a remote computing device. | 0.759921 |
8,775,328 | 33 | 37 | 33. A method comprising: verifying that a user lives at a residence associated with a residential address claimed by the user of an online neighborhood social network using a processor and a memory; creating a social network page of the user once verified in the online neighborhood social network; distributing, via the processor and the memory, a message from the user to neighboring users that are verified to live within a neighborhood boundary of the residence; designating, via the processor and the memory, the user as a lead user having an additional privilege in a private website of the online neighborhood social network confined by the neighborhood boundary based on at least one of a participation level of the user in the online neighborhood social network and an activity level of the user associated with encouraging neighboring users to participate in the online neighborhood social network; automatically determining, via the processor and memory, a set of access privileges in the private website of the online neighborhood social network associated with the user; and restricting access, via the processor and the memory, to a particular neighborhood in the private website of the online neighborhood social network to the user and to neighboring users living within the neighborhood boundary of the residence, permitting, via the processor and the memory, the user of the online neighborhood social network to mark certain information communicated to a particular neighboring user as private; and designating, via the processor and the memory, the certain information shared only with the particular neighboring user as non-public to other neighboring users of the online neighborhood social network, wherein the neighboring users are determined based on each residence associated with each geographic location claimed by each neighboring user of the online neighborhood social network that is within the neighborhood boundary. | 33. A method comprising: verifying that a user lives at a residence associated with a residential address claimed by the user of an online neighborhood social network using a processor and a memory; creating a social network page of the user once verified in the online neighborhood social network; distributing, via the processor and the memory, a message from the user to neighboring users that are verified to live within a neighborhood boundary of the residence; designating, via the processor and the memory, the user as a lead user having an additional privilege in a private website of the online neighborhood social network confined by the neighborhood boundary based on at least one of a participation level of the user in the online neighborhood social network and an activity level of the user associated with encouraging neighboring users to participate in the online neighborhood social network; automatically determining, via the processor and memory, a set of access privileges in the private website of the online neighborhood social network associated with the user; and restricting access, via the processor and the memory, to a particular neighborhood in the private website of the online neighborhood social network to the user and to neighboring users living within the neighborhood boundary of the residence, permitting, via the processor and the memory, the user of the online neighborhood social network to mark certain information communicated to a particular neighboring user as private; and designating, via the processor and the memory, the certain information shared only with the particular neighboring user as non-public to other neighboring users of the online neighborhood social network, wherein the neighboring users are determined based on each residence associated with each geographic location claimed by each neighboring user of the online neighborhood social network that is within the neighborhood boundary. 37. The method of claim 33 : utilizing a postcard method through which the computer server generates a physical postcard that is postal mailed to neighboring users living within the neighborhood boundary of the online neighborhood social network. | 0.830812 |
9,003,339 | 1 | 9 | 1. A non-transitory computer-readable storage medium having instructions stored therein for causing a processor to perform a process of synthesizing a behavioral description of a circuit into a structural description of the circuit, the process comprising: receiving the behavioral description of the circuit, the behavioral description including a first statement that is associated with a condition; identifying the condition associated with the first statement; identifying one or more other statements associated with the first statement, including: determining a downstream statement that depends on the first statement, and/or determining an upstream statement upon which the first statement depends; inferring one or more potential clock domains gated by the condition for logic associated with the first statement and the one or more other statements; scheduling the logic associated with the first statement and the one or more other statements according to the one or more potential clock domains; and generating the structural description of the circuit, the structural description including a structural description of the scheduled logic. | 1. A non-transitory computer-readable storage medium having instructions stored therein for causing a processor to perform a process of synthesizing a behavioral description of a circuit into a structural description of the circuit, the process comprising: receiving the behavioral description of the circuit, the behavioral description including a first statement that is associated with a condition; identifying the condition associated with the first statement; identifying one or more other statements associated with the first statement, including: determining a downstream statement that depends on the first statement, and/or determining an upstream statement upon which the first statement depends; inferring one or more potential clock domains gated by the condition for logic associated with the first statement and the one or more other statements; scheduling the logic associated with the first statement and the one or more other statements according to the one or more potential clock domains; and generating the structural description of the circuit, the structural description including a structural description of the scheduled logic. 9. The non-transitory computer-readable storage medium of claim 1 , wherein the scheduling comprises: iteratively: evaluating the scheduled logic against at least a timing constraint and/or a power constraint; and scheduling the logic associated with the first statement and the one or more other statements to a subset of the one or more inferred potential clock domains based on the evaluating. | 0.672727 |
9,537,674 | 32 | 33 | 32. A non-transitory computer readable storage medium as defined in claim 31 , wherein the input interface sends a request to the message service to prompt the message service to generate the size information. | 32. A non-transitory computer readable storage medium as defined in claim 31 , wherein the input interface sends a request to the message service to prompt the message service to generate the size information. 33. A non-transitory computer readable storage medium as defined in claim 32 , wherein the input interface sends the request to the message service periodically. | 0.5625 |
10,127,928 | 19 | 20 | 19. The system of claim 11 , wherein the determined first emotional state is indicated using a first emotionally indicative icon, and wherein the second determined emotional state is indicated using a second emotionally indicative icon. | 19. The system of claim 11 , wherein the determined first emotional state is indicated using a first emotionally indicative icon, and wherein the second determined emotional state is indicated using a second emotionally indicative icon. 20. The system of claim 19 , wherein a color hue and color intensity of at least one of the first emotionally indicative icon and the second indicative icon are varied. | 0.5 |
7,516,065 | 22 | 25 | 22. A speech correcting method for a speech correction apparatus comprising: a speaker for generating speech to be corrected; a microphone set at a hearing position; a filter having an acoustic characteristic as an impulse response of an acoustic system between the speaker and the microphone; and an operating unit for subtracting a signal which is obtained by passing a signal supplied to the speaker according to the speech to be corrected through the filter from a signal received from the microphone when the speech to be corrected is generated by the speaker, the speech correcting method comprising: an act of separating, by a signal separating unit, the ambient noise from the speech to be corrected at the hearing position by supplying a signal corresponding to the speech to be corrected from the filter and supplying a signal corresponding to the ambient noise from the operating unit; an act of updating, by a coefficient update unit, a filter coefficient of the filter so as to minimize the power of the signal supplied from the operating unit; an act of setting an initial value of the filter coefficient, which is updated by the coefficient update unit, at a value other than 0 by a filter initial setting unit; and an act of correcting a sound pressure level of the speech to be corrected generated by the speaker based on a comparison between a time length Ls for calculating an average power of the speech to be corrected and a time length Ln for calculating an average power of the ambient noise, which are separated by the signal separating unit, the correction being performed by a speech correcting unit. | 22. A speech correcting method for a speech correction apparatus comprising: a speaker for generating speech to be corrected; a microphone set at a hearing position; a filter having an acoustic characteristic as an impulse response of an acoustic system between the speaker and the microphone; and an operating unit for subtracting a signal which is obtained by passing a signal supplied to the speaker according to the speech to be corrected through the filter from a signal received from the microphone when the speech to be corrected is generated by the speaker, the speech correcting method comprising: an act of separating, by a signal separating unit, the ambient noise from the speech to be corrected at the hearing position by supplying a signal corresponding to the speech to be corrected from the filter and supplying a signal corresponding to the ambient noise from the operating unit; an act of updating, by a coefficient update unit, a filter coefficient of the filter so as to minimize the power of the signal supplied from the operating unit; an act of setting an initial value of the filter coefficient, which is updated by the coefficient update unit, at a value other than 0 by a filter initial setting unit; and an act of correcting a sound pressure level of the speech to be corrected generated by the speaker based on a comparison between a time length Ls for calculating an average power of the speech to be corrected and a time length Ln for calculating an average power of the ambient noise, which are separated by the signal separating unit, the correction being performed by a speech correcting unit. 25. A speech correcting method according to claim 22 , wherein the initial value set by the filter initial setting unit is a filter coefficient which corresponds to the model of a car carrying the apparatus. | 0.778373 |
7,783,614 | 1 | 11 | 1. A method of linking elements in a computer-generated document to corresponding data in a database, comprising: attaching a schema file associated with at least one intended use of the document to a document defining rules associated with a markup language to be applied to the document, wherein the markup language is XML and wherein the rules associated with the markup language to be applied to the document comprise names of elements of the markup language and data types associated with the names of the elements of the markup language; applying the elements of the markup language to the document; establishing data fields within the database for linking to corresponding markup language elements in the document; writing a unique document identifier number to the document for linking the data fields in the database to the document, wherein linking the data fields in the database to the document comprises: determining if a table associated with the document exists within a document library; if no table is associated with the document, creating a table containing user-defined elements associated with the document; selecting a table within a document library, the document library being maintained in the database where the table is associated with the document, and linking at least one markup language element in the document to corresponding data in the database; when data is entered into the database associated with the given markup language element in the document, automatically writing the data to the document in a location in the document associated with the given markup language element; when the given markup language element in the document is modified, automatically updating the corresponding data in the database; providing at least one suggested document element according to the schema file associated with the at least one intended use of the document, wherein the at least one suggested document element comprises an element structure linked to at least one corresponding data field in the database; and enforcing at least one element constraint according to the schema file, wherein the element constraint comprises at least one piece of required data for at least one document element. | 1. A method of linking elements in a computer-generated document to corresponding data in a database, comprising: attaching a schema file associated with at least one intended use of the document to a document defining rules associated with a markup language to be applied to the document, wherein the markup language is XML and wherein the rules associated with the markup language to be applied to the document comprise names of elements of the markup language and data types associated with the names of the elements of the markup language; applying the elements of the markup language to the document; establishing data fields within the database for linking to corresponding markup language elements in the document; writing a unique document identifier number to the document for linking the data fields in the database to the document, wherein linking the data fields in the database to the document comprises: determining if a table associated with the document exists within a document library; if no table is associated with the document, creating a table containing user-defined elements associated with the document; selecting a table within a document library, the document library being maintained in the database where the table is associated with the document, and linking at least one markup language element in the document to corresponding data in the database; when data is entered into the database associated with the given markup language element in the document, automatically writing the data to the document in a location in the document associated with the given markup language element; when the given markup language element in the document is modified, automatically updating the corresponding data in the database; providing at least one suggested document element according to the schema file associated with the at least one intended use of the document, wherein the at least one suggested document element comprises an element structure linked to at least one corresponding data field in the database; and enforcing at least one element constraint according to the schema file, wherein the element constraint comprises at least one piece of required data for at least one document element. 11. The method of claim 1 , wherein the markup language is the Extendable Markup Language. | 0.941634 |
9,244,931 | 1 | 6 | 1. One or more computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: modeling query behavior over time to create a time-aware query model the modeling of query behavior being based at least in part on timing and frequency that queries are submitted to a search service over time; modeling uniform resource locator (URL) behavior over time to create a time-aware URL model, the modeling of URL behavior being based at least in part on timing and frequency that URLs are selected in response to the queries over time; determining a time-aware query-URL relationship based at least in part on the time-aware query model and the time-aware URL model, wherein the determined time-aware query-URL relationship indicates, for a query, a future change that elevates a first URL to a popularity level greater than a second URL; performing a search in response to the query; and ranking results of the search according to the time-aware query-URL relationship, wherein the ranked results include the first URL ranked higher than the second URL. | 1. One or more computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: modeling query behavior over time to create a time-aware query model the modeling of query behavior being based at least in part on timing and frequency that queries are submitted to a search service over time; modeling uniform resource locator (URL) behavior over time to create a time-aware URL model, the modeling of URL behavior being based at least in part on timing and frequency that URLs are selected in response to the queries over time; determining a time-aware query-URL relationship based at least in part on the time-aware query model and the time-aware URL model, wherein the determined time-aware query-URL relationship indicates, for a query, a future change that elevates a first URL to a popularity level greater than a second URL; performing a search in response to the query; and ranking results of the search according to the time-aware query-URL relationship, wherein the ranked results include the first URL ranked higher than the second URL. 6. One or more computer-readable media as recited in claim 1 , further comprising: switching between two time-aware query models based on a change in the query behavior over time; and switching between two time-aware URL models based on a change in the URL behavior over time. | 0.660099 |
9,141,662 | 7 | 8 | 7. The method of claim 1 , further comprising monitoring the first evidence to detect the change. | 7. The method of claim 1 , further comprising monitoring the first evidence to detect the change. 8. The method of claim 7 , wherein the first evidence is monitored upon determining that a relevance score of the first evidence exceeds a relevance threshold, wherein the first evidence comprises a content of at least one of: (i) a document, (ii) a variable, (iii) an article, and (iv) a web page, and wherein the first question is part of a first case comprising at least the first question. | 0.5 |
9,542,440 | 8 | 9 | 8. An apparatus comprising: a processing system; and one or more computer readable storage media including program instructions stored on the one or more computer readable media that, when executed by the processing system, direct the processing system to at least: generate an enterprise graph representative of a plurality of objects associated with an enterprise and a plurality of actors associated with the enterprise and further representative of which of the plurality of actors performed which of a plurality of actions with respect to each of the plurality of objects; search at least a portion of the enterprise graph to identify a subset of the plurality of objects that relate to the plurality of actors as defined by a graph query expression in a graph query in terms of at least the plurality of actors and the plurality of actions; generate graph results indicative of the subset of the plurality of objects that relate to the plurality of actors as defined by the graph query expression; search at least a portion of a full-text database to identify an additional subset of the plurality of objects based at least in part on the full-text query; and generate full-text results indicative of the additional subset of the plurality of objects; and merge the graph results and the full-text results to produce search results. | 8. An apparatus comprising: a processing system; and one or more computer readable storage media including program instructions stored on the one or more computer readable media that, when executed by the processing system, direct the processing system to at least: generate an enterprise graph representative of a plurality of objects associated with an enterprise and a plurality of actors associated with the enterprise and further representative of which of the plurality of actors performed which of a plurality of actions with respect to each of the plurality of objects; search at least a portion of the enterprise graph to identify a subset of the plurality of objects that relate to the plurality of actors as defined by a graph query expression in a graph query in terms of at least the plurality of actors and the plurality of actions; generate graph results indicative of the subset of the plurality of objects that relate to the plurality of actors as defined by the graph query expression; search at least a portion of a full-text database to identify an additional subset of the plurality of objects based at least in part on the full-text query; and generate full-text results indicative of the additional subset of the plurality of objects; and merge the graph results and the full-text results to produce search results. 9. The apparatus of claim 8 further comprising the processing system configured to execute the program instructions, wherein the program instructions further direct the processing system to receive a search request comprising the graph query and reply to the graph query with the graph results. | 0.5 |
9,037,593 | 6 | 7 | 6. A computer-readable, non-transitory medium storing a program which, when executed by a computer, causes the computer to perform a process comprising: splitting a first character string and a second character string into words; acquiring information including a semantic attribute that represents a semantic nature of each of the words and a conceptual code that semantically identifies said each of the words, from a storage device; identifying a pair of the words having a common semantic attribute between the first character string and the second character string; comparing the conceptual codes of the specified pair of the words between the first character string and the second character string; and generating a comparison result between the first character string and the second character string based upon a comparison result of the conceptual codes, wherein the process further includes determining a comparison value representing the comparison result of the conceptual codes for each of multiple conceptual code pairs between the first character string and the second character string; and calculating an evaluation value by summing the comparison values of the multiple conceptual code pairs, wherein the generation of the comparison result includes generating the comparison result between the first character string and the second character string by comparing the evaluation value and a determination threshold value, and wherein the comparing the conceptual code includes every time the comparison value is determined for each of the conceptual code pairs, adding a summation of the determined comparison values to a maximum possible value of a comparison result of an unprocessed conceptual code pair, and if the added value is less than a cutoff level, the comparing process between the conceptual codes is stopped. | 6. A computer-readable, non-transitory medium storing a program which, when executed by a computer, causes the computer to perform a process comprising: splitting a first character string and a second character string into words; acquiring information including a semantic attribute that represents a semantic nature of each of the words and a conceptual code that semantically identifies said each of the words, from a storage device; identifying a pair of the words having a common semantic attribute between the first character string and the second character string; comparing the conceptual codes of the specified pair of the words between the first character string and the second character string; and generating a comparison result between the first character string and the second character string based upon a comparison result of the conceptual codes, wherein the process further includes determining a comparison value representing the comparison result of the conceptual codes for each of multiple conceptual code pairs between the first character string and the second character string; and calculating an evaluation value by summing the comparison values of the multiple conceptual code pairs, wherein the generation of the comparison result includes generating the comparison result between the first character string and the second character string by comparing the evaluation value and a determination threshold value, and wherein the comparing the conceptual code includes every time the comparison value is determined for each of the conceptual code pairs, adding a summation of the determined comparison values to a maximum possible value of a comparison result of an unprocessed conceptual code pair, and if the added value is less than a cutoff level, the comparing process between the conceptual codes is stopped. 7. The computer-readable, non-transitory medium according to claim 6 , wherein the comparing the conceptual code includes: determining the comparison value successively in descending order beginning from a conceptual code with a greatest weight of a corresponding word; adding the summation of the weighted comparison values to the maximum possible value of the comparison value of the unprocessed conceptual code pair, and if the added value is less than the cutoff level, the comparing process between the conceptual codes is stopped. | 0.5 |
7,735,621 | 5 | 6 | 5. A method of sorting currency bills, each having an associated denomination, using a currency bill evaluating device, the currency evaluating device comprising an input receptacle, a plurality of output receptacles, and a transport mechanism positioned to individually transport bills from the input receptacle to the output receptacles, the method comprising the acts of: (A) transporting a bill from the input receptacle past a bill denominating sensor; (B) determining the denomination of the transported bill; (C) determining whether the denomination of the bill has been assigned to a non-full output receptacle and (i) if so, transporting the bill to the assigned non-full output receptacle; (ii) if not, determining whether there is an open output receptacle and (a) if so, assigning the denomination of the bill to an open output receptacle and transporting the bill to the assigned output receptacle; (b) if not, stopping the operation of the device; (D) repeating steps (A)–(C). | 5. A method of sorting currency bills, each having an associated denomination, using a currency bill evaluating device, the currency evaluating device comprising an input receptacle, a plurality of output receptacles, and a transport mechanism positioned to individually transport bills from the input receptacle to the output receptacles, the method comprising the acts of: (A) transporting a bill from the input receptacle past a bill denominating sensor; (B) determining the denomination of the transported bill; (C) determining whether the denomination of the bill has been assigned to a non-full output receptacle and (i) if so, transporting the bill to the assigned non-full output receptacle; (ii) if not, determining whether there is an open output receptacle and (a) if so, assigning the denomination of the bill to an open output receptacle and transporting the bill to the assigned output receptacle; (b) if not, stopping the operation of the device; (D) repeating steps (A)–(C). 6. The method claim 5 further comprising the act of disabling an output receptacle thereby making the output receptacle unavailable to receive bills during normal operation. | 0.5 |
8,374,859 | 7 | 8 | 7. The automatic answering device according to claim 1 , further comprising: a conversation process unit configured to transmit the user utterance accepted by the input unit, and to receive the reply sentence corresponding to the transmitted user utterance and operation control information which is information describing an operation to be executed corresponding to the reply sentence by the automatic answering device; and an operation control unit configured to receive the operation control information from the conversation process unit, and to execute the operation in accordance with the received operation control information. | 7. The automatic answering device according to claim 1 , further comprising: a conversation process unit configured to transmit the user utterance accepted by the input unit, and to receive the reply sentence corresponding to the transmitted user utterance and operation control information which is information describing an operation to be executed corresponding to the reply sentence by the automatic answering device; and an operation control unit configured to receive the operation control information from the conversation process unit, and to execute the operation in accordance with the received operation control information. 8. The automatic answering device according to claim 7 , further comprising: a browser unit configured to receive data of a content, and to allow the user to browse the received content, wherein the operation control unit drives the browser unit to execute processing determined by the received operation control information. | 0.877266 |
9,304,736 | 17 | 21 | 17. A computer-implemented method comprising: at a computing device: receiving a verbal request to perform a function; causing speech processing to be performed on the verbal request; transmitting a code to an end-user device separate from the computing device; prompting to enter the code; detecting manual manipulation of a control element on the computing device, wherein the control element is used to cause entry of multiple values; emitting light externally of the computing device according to multiple appearance states, wherein a first appearance state corresponding to a first value is emitted upon detection of a first manual manipulation of the control element, and a second appearance state corresponding to a second value is emitted upon detection of a second manual manipulation of the control element; determining that at least one of the first or second values match the code; and performing the function. | 17. A computer-implemented method comprising: at a computing device: receiving a verbal request to perform a function; causing speech processing to be performed on the verbal request; transmitting a code to an end-user device separate from the computing device; prompting to enter the code; detecting manual manipulation of a control element on the computing device, wherein the control element is used to cause entry of multiple values; emitting light externally of the computing device according to multiple appearance states, wherein a first appearance state corresponding to a first value is emitted upon detection of a first manual manipulation of the control element, and a second appearance state corresponding to a second value is emitted upon detection of a second manual manipulation of the control element; determining that at least one of the first or second values match the code; and performing the function. 21. A computer-implemented method as recited in claim 17 , further comprising one of displaying or audibly outputting the code on the end-user device separate from the computing device. | 0.555288 |
8,407,042 | 4 | 5 | 4. The cross-language system of claim 3 , wherein the user interface is configured for allowing a user to enter a query in the user's language, and for displaying a representation of responses to the queries retrieved from the archives by the search engine. | 4. The cross-language system of claim 3 , wherein the user interface is configured for allowing a user to enter a query in the user's language, and for displaying a representation of responses to the queries retrieved from the archives by the search engine. 5. The cross-language system of claim 4 , wherein the responses each comprise at least one of a question and an answer. | 0.5 |
7,673,230 | 14 | 18 | 14. The method of claim 12 , wherein the visual indication is a focus shape. | 14. The method of claim 12 , wherein the visual indication is a focus shape. 18. The method of claim 14 , wherein a given hyperlink has an associated hot region and wherein the focus shape is drawn around the hot region. | 0.5 |
9,946,971 | 23 | 24 | 23. The system according to claim 22 , wherein the project repository stores the available electronic document and updates the project repository interface when one or more new electronic documents are implemented in the project. | 23. The system according to claim 22 , wherein the project repository stores the available electronic document and updates the project repository interface when one or more new electronic documents are implemented in the project. 24. The system according to claim 23 , wherein the management processor associates one or more tags with a new electronic document uploaded from the first client device according to a participant input, and wherein the electronic document database stores the new electronic document in the database and is associated with knowledge in the knowledge database on the tags. | 0.711388 |
8,850,606 | 1 | 2 | 1. A non-transitory computer readable medium storing a program causing a computer to execute a process for information processing, the process comprising: receiving a first characteristic value calculated on the basis of first document information for use in detecting whether tampering with the first document information has occurred; receiving a second characteristic value calculated on the basis of second document information for use in detecting whether tampering with the second document information has occurred; calculating a third characteristic value for use in detecting whether tampering with third document information has occurred on the basis of the first characteristic value, the second characteristic value and the third document information related to integration of the first document information and the second document information; and generating the third document information, indicating integration of the first document information and the second document information when an instruction to integrate the first document information and the second document information is received, wherein the third document information is generated to include first user information for identifying a first user that initiated the integration of the first document information and the second document information, and wherein the third document information comprises: an execution request document created in response to the first user initiating the integration of the first document information and the second document information; and an execution confirmation document created in response to a second user confirming the integration of the first document information and the second document information initiated by the first user. | 1. A non-transitory computer readable medium storing a program causing a computer to execute a process for information processing, the process comprising: receiving a first characteristic value calculated on the basis of first document information for use in detecting whether tampering with the first document information has occurred; receiving a second characteristic value calculated on the basis of second document information for use in detecting whether tampering with the second document information has occurred; calculating a third characteristic value for use in detecting whether tampering with third document information has occurred on the basis of the first characteristic value, the second characteristic value and the third document information related to integration of the first document information and the second document information; and generating the third document information, indicating integration of the first document information and the second document information when an instruction to integrate the first document information and the second document information is received, wherein the third document information is generated to include first user information for identifying a first user that initiated the integration of the first document information and the second document information, and wherein the third document information comprises: an execution request document created in response to the first user initiating the integration of the first document information and the second document information; and an execution confirmation document created in response to a second user confirming the integration of the first document information and the second document information initiated by the first user. 2. The non-transitory computer readable medium according to claim 1 , wherein the third document information is generated to include an indication that a subject of the second document information is a subject of the first document information. | 0.760784 |
9,009,197 | 14 | 18 | 14. A data structure embedded in computer-readable storage device, for a unified compliance framework, the structure comprising: an authority document table in the computer-readable storage device, including references to a plurality of authority documents; and a citation table in the computer-readable storage device including: authority document fields, each authority document field to indicate a unique authority document of the plurality of authority documents, guidance fields, each guidance field to indicate at least a noun-verb pair of a citation in one or more of the plurality of authority documents, citation fields, each citation field to indicate the citation to the noun-verb pair in the one or more of the plurality of authority documents, noun ID fields, each noun ID field to indicate a unique identification for representing substantially similar nouns pairs in the guidance fields, and citation ID fields, each citation ID field representing a unique identification for mapping an individual noun-verb pair with the: authority document field, guidance field, citation field, and noun id field, that correspond with the individual noun-verb pair, such that the contents are usable to automatically analyze compliance with at least one noun-verb pair. | 14. A data structure embedded in computer-readable storage device, for a unified compliance framework, the structure comprising: an authority document table in the computer-readable storage device, including references to a plurality of authority documents; and a citation table in the computer-readable storage device including: authority document fields, each authority document field to indicate a unique authority document of the plurality of authority documents, guidance fields, each guidance field to indicate at least a noun-verb pair of a citation in one or more of the plurality of authority documents, citation fields, each citation field to indicate the citation to the noun-verb pair in the one or more of the plurality of authority documents, noun ID fields, each noun ID field to indicate a unique identification for representing substantially similar nouns pairs in the guidance fields, and citation ID fields, each citation ID field representing a unique identification for mapping an individual noun-verb pair with the: authority document field, guidance field, citation field, and noun id field, that correspond with the individual noun-verb pair, such that the contents are usable to automatically analyze compliance with at least one noun-verb pair. 18. The data structure of claim 14 , further comprising a Meta Data portion including: live values; and revision fields, each revision field indicating a status of a noun-verb pair in the citation table relative to a previous noun-verb pair having the same unique citation id. | 0.660099 |
9,582,608 | 4 | 27 | 4. The method of claim 1 , wherein calculating the respective phrase indexing power across the plurality of domains for each complete input phrase P j of the collection of complete input phrases further comprises: distinguishing template words from normal words in the complete input phrase P j , a template word being a word that is used to represent a respective category of normal words in a particular complete input phrase and that is substituted by one or more normal words when provided as an input to the digital assistant by a user; calculating the respective phrase indexing power, for the complete input phrase P j based on a respective formula μ j = b T n T ( j ) + 1 n N ( j ) + n T ( j ) [ ∑ i = 1 n N ( j ) ( 1 - ɛ i ) + ∑ i = 1 n T ( j ) ( 1 - ɛ i ) ] , wherein n N (j) is a total number of normal words present in the complete input phrase P j , n T (j) is a total number of template words present in the complete input phrase P j , (1−ε i ) is the respective word indexing power of each word w i , and b T is a respective template bias multiplier used to calculate the weight bias b T n T (j) for the input phrase P j . | 4. The method of claim 1 , wherein calculating the respective phrase indexing power across the plurality of domains for each complete input phrase P j of the collection of complete input phrases further comprises: distinguishing template words from normal words in the complete input phrase P j , a template word being a word that is used to represent a respective category of normal words in a particular complete input phrase and that is substituted by one or more normal words when provided as an input to the digital assistant by a user; calculating the respective phrase indexing power, for the complete input phrase P j based on a respective formula μ j = b T n T ( j ) + 1 n N ( j ) + n T ( j ) [ ∑ i = 1 n N ( j ) ( 1 - ɛ i ) + ∑ i = 1 n T ( j ) ( 1 - ɛ i ) ] , wherein n N (j) is a total number of normal words present in the complete input phrase P j , n T (j) is a total number of template words present in the complete input phrase P j , (1−ε i ) is the respective word indexing power of each word w i , and b T is a respective template bias multiplier used to calculate the weight bias b T n T (j) for the input phrase P j . 27. The method of claim 4 , wherein receiving a training corpus further comprises: collecting a plurality of user input phrases from a usage log of a digital assistant; identifying at least one template input phrase based on a common phrase pattern present in two or more of the plurality of user input phrases; and normalizing the plurality of user input phrases by substituting at least one word in each of said two or more user input phrases with a respective template word representing a generalization of the at least one word. | 0.5 |
10,122,670 | 11 | 12 | 11. A non-transitory computer-readable storage medium storing instructions thereon that, when executed by at least one processor, cause a system to: receive a first version of an electronic message, wherein the first version of the electronic message is in a first language; identify, based on previous social networking activities of a sender, social networking information associated with the sender; identify a recipient of the electronic message; identify, based on previous social networking activities of a recipient of the electronic message, social networking information associated with the recipient; and determine, based on an analysis of the social networking information associated with the sender and the social networking information associated with the recipient, whether to generate a second version of the electronic message in a second language for identified recipient. | 11. A non-transitory computer-readable storage medium storing instructions thereon that, when executed by at least one processor, cause a system to: receive a first version of an electronic message, wherein the first version of the electronic message is in a first language; identify, based on previous social networking activities of a sender, social networking information associated with the sender; identify a recipient of the electronic message; identify, based on previous social networking activities of a recipient of the electronic message, social networking information associated with the recipient; and determine, based on an analysis of the social networking information associated with the sender and the social networking information associated with the recipient, whether to generate a second version of the electronic message in a second language for identified recipient. 12. The non-transitory computer-readable storage medium as recited in claim 11 , wherein identifying a recipient of the electronic message comprises identifying a co-user associated with a sender of the first version of the electronic message via a social networking system. | 0.5 |
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