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9,275,121 | 1 | 4 |
1. A computer-implemented method executed by at least one processor, the method comprising: receiving, by a computer system, a request to execute a shared query, wherein the shared query comprises one of a plurality of pre-defined shared queries, and the shared query comprises a pre-defined query specification associated with the shared query, the query specification comprising pre-defined connections to a first and a second data sources associated with the shared query, the query specification specifying the shared query on a semantic layer and including search terms, parameters, filters, and aspects of the shared query to be used at runtime upon execution of the shared query, where each pre-defined shared query of the plurality of pre-defined shared queries is associated with a corresponding set of access rights, and wherein the request to execute the shared query represents a specific request to execute a particular shared query from the plurality of pre-defined shared queries from a particular application or user; in response to receiving the request, determining whether the particular application or user is allowed to access the shared query based on the set of access rights associated with the shared query; allowing execution of the shared query upon a determination that the particular application or user is allowed to access the shared query, wherein allowing execution of the share query includes: identifying the pre-defined query specification associated with the shared query; in response to the identifying the pre-defined query specification, identifying the first data source and the second data source based on the identified query specification; generating a native query for each respective data source of the identified first and second data sources based on the identified query specification; executing the generated native queries at the respective data sources to collect a set of query results from the respective data sources; and formatting the set of query results from the respective data sources into a unified set of query results; and rejecting the execution request upon a determination that the particular application or user is not allowed to access the shared query.
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1. A computer-implemented method executed by at least one processor, the method comprising: receiving, by a computer system, a request to execute a shared query, wherein the shared query comprises one of a plurality of pre-defined shared queries, and the shared query comprises a pre-defined query specification associated with the shared query, the query specification comprising pre-defined connections to a first and a second data sources associated with the shared query, the query specification specifying the shared query on a semantic layer and including search terms, parameters, filters, and aspects of the shared query to be used at runtime upon execution of the shared query, where each pre-defined shared query of the plurality of pre-defined shared queries is associated with a corresponding set of access rights, and wherein the request to execute the shared query represents a specific request to execute a particular shared query from the plurality of pre-defined shared queries from a particular application or user; in response to receiving the request, determining whether the particular application or user is allowed to access the shared query based on the set of access rights associated with the shared query; allowing execution of the shared query upon a determination that the particular application or user is allowed to access the shared query, wherein allowing execution of the share query includes: identifying the pre-defined query specification associated with the shared query; in response to the identifying the pre-defined query specification, identifying the first data source and the second data source based on the identified query specification; generating a native query for each respective data source of the identified first and second data sources based on the identified query specification; executing the generated native queries at the respective data sources to collect a set of query results from the respective data sources; and formatting the set of query results from the respective data sources into a unified set of query results; and rejecting the execution request upon a determination that the particular application or user is not allowed to access the shared query. 4. The method of claim 1 , wherein the at least one of the first data source and the second data source includes at least one of a text file, a web service, an extensible markup language (XML) file, and an excel file.
| 0.830469 |
10,152,462 | 15 | 20 |
15. A computing system for generating a documentary of a source document comprising: a processor; and a computer-readable storage medium, coupled with the processor, having instructions stored thereon, which, when executed by the processor, execute actions comprising: receiving the source document, wherein the source document includes source content; determining a source document structure based on an automated analysis of a table of contents (ToC) of the source document, wherein determining the source document structure includes determining a plurality of hierarchical structures of the source content and an arrangement order of the plurality of hierarchical structures of the source content; segmenting the source content into a plurality of hierarchical slices based on the source document structure, wherein each of the plurality of hierarchical structures of the source content is included in one or more of the plurality of hierarchical slices and each of the plurality of hierarchical slices includes at least a rank and an index, wherein the rank represents a level of depth in the determined plurality of hierarchical structures and the index represents an ordered position in the determined arrangement order of the plurality of hierarchical structures; generating one or more presentation slides for each of the plurality of hierarchical slices based on the coding map; populating each of the one or more presentation slides for each of the plurality of hierarchical slices with a portion of the source content corresponding to the hierarchical slice based on at least the rank and the index of each of the plurality of hierarchical slices; and generating a target document that includes at least a portion of the populated one or more presentation slides for each of the plurality of hierarchical slices, wherein the target document includes the documentary of the source document.
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15. A computing system for generating a documentary of a source document comprising: a processor; and a computer-readable storage medium, coupled with the processor, having instructions stored thereon, which, when executed by the processor, execute actions comprising: receiving the source document, wherein the source document includes source content; determining a source document structure based on an automated analysis of a table of contents (ToC) of the source document, wherein determining the source document structure includes determining a plurality of hierarchical structures of the source content and an arrangement order of the plurality of hierarchical structures of the source content; segmenting the source content into a plurality of hierarchical slices based on the source document structure, wherein each of the plurality of hierarchical structures of the source content is included in one or more of the plurality of hierarchical slices and each of the plurality of hierarchical slices includes at least a rank and an index, wherein the rank represents a level of depth in the determined plurality of hierarchical structures and the index represents an ordered position in the determined arrangement order of the plurality of hierarchical structures; generating one or more presentation slides for each of the plurality of hierarchical slices based on the coding map; populating each of the one or more presentation slides for each of the plurality of hierarchical slices with a portion of the source content corresponding to the hierarchical slice based on at least the rank and the index of each of the plurality of hierarchical slices; and generating a target document that includes at least a portion of the populated one or more presentation slides for each of the plurality of hierarchical slices, wherein the target document includes the documentary of the source document. 20. The computing system of claim 15 , wherein the actions further comprise: generating audible narration for at least a portion of textual content included in the source content; and updating at least one of the one or more presentation slides that includes the portion of the textual content to include the audible narration.
| 0.5 |
4,689,743 | 8 | 9 |
8. A method as claimed in claim 7 wherein said length number is obtained by counting the number of code components in the incoming character code.
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8. A method as claimed in claim 7 wherein said length number is obtained by counting the number of code components in the incoming character code. 9. A method as claimed in claim 8 wherein said searching step comprises comparing the incoming character code to each standard character code in said portion of said set and ranking such standard character codes according to the closeness of match with the incoming character code.
| 0.5 |
8,209,664 | 1 | 6 |
1. A machine implemented method for distributed parallel processing, comprising: accessing an expression from a sequential program that is executing at a first machine, the expression invoking at least one extension for distributed parallel processing by a distributed execution engine, wherein the distributed execution engine includes a compute cluster having a plurality of nodes, the at least one extension is an operator specifying a user-defined function using data parallel processing, and wherein the user-defined function is in a high-level programming language and receives a first dataset; automatically generating an execution plan for parallel processing of the expression by the distributed execution engine using the at least one extension, wherein the automatically generating the execution plan includes: specifying a partitioning of the first dataset at a set of nodes from said plurality of nodes; determining whether the user-defined function includes an annotation that the user-defined function is operable on partitions of the first dataset; if the user-defined function includes the annotation, automatically generating code for executing the user-defined function in parallel at the set of nodes; and if the user-defined function does not include the annotation, automatically generating code for streaming partitions of the first dataset to a single node and code for executing the user-defined function at the single node; and providing the execution plan to the distributed execution engine for controlling parallel execution of the expression.
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1. A machine implemented method for distributed parallel processing, comprising: accessing an expression from a sequential program that is executing at a first machine, the expression invoking at least one extension for distributed parallel processing by a distributed execution engine, wherein the distributed execution engine includes a compute cluster having a plurality of nodes, the at least one extension is an operator specifying a user-defined function using data parallel processing, and wherein the user-defined function is in a high-level programming language and receives a first dataset; automatically generating an execution plan for parallel processing of the expression by the distributed execution engine using the at least one extension, wherein the automatically generating the execution plan includes: specifying a partitioning of the first dataset at a set of nodes from said plurality of nodes; determining whether the user-defined function includes an annotation that the user-defined function is operable on partitions of the first dataset; if the user-defined function includes the annotation, automatically generating code for executing the user-defined function in parallel at the set of nodes; and if the user-defined function does not include the annotation, automatically generating code for streaming partitions of the first dataset to a single node and code for executing the user-defined function at the single node; and providing the execution plan to the distributed execution engine for controlling parallel execution of the expression. 6. A machine implemented method according to claim 1 , wherein the automatically generating an execution plan includes: determining whether the user-defined function includes an annotation specifying the function is not stateful; if the user-defined function includes the annotation specifying the function is not stateful, automatically generating a first version of the execution plan; and if the user-defined function does not include the annotation specifying the function as not stateful, automatically generating a second version of the execution plan.
| 0.603693 |
7,930,183 | 15 | 16 |
15. The system of claim 14 wherein the identification module is further adapted to isolate a portion of expected audio and a portion of unexpected audio to form an actual response given by the at least one user.
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15. The system of claim 14 wherein the identification module is further adapted to isolate a portion of expected audio and a portion of unexpected audio to form an actual response given by the at least one user. 16. The system of claim 15 , wherein the recognizer is adapted to perform recognition on the actual response.
| 0.5 |
9,413,771 | 3 | 11 |
3. The method of claim 1 comprising: using the policy enforcer, determining if the application program can be trusted to protect unencrypted content of the encrypted document based on a first policy of the plurality of policies stored at the policy server; and the controlling access to the unencrypted content based on the first policy is replaced by if the application program is determined to be trusted, controlling access to the unencrypted content based on the first policy.
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3. The method of claim 1 comprising: using the policy enforcer, determining if the application program can be trusted to protect unencrypted content of the encrypted document based on a first policy of the plurality of policies stored at the policy server; and the controlling access to the unencrypted content based on the first policy is replaced by if the application program is determined to be trusted, controlling access to the unencrypted content based on the first policy. 11. The method of claim 3 wherein an application program that is determined to be trusted at a first time T 1 , and after an elapsed time T 2 after T 1 , the application program will be determined not to be trusted, and T 2 is a configurable parameter.
| 0.58 |
9,437,206 | 15 | 16 |
15. The development system of claim 11 , further comprising a data store comprising: an application action-context pair that holds a plurality of application action-context pairs selected by an application developer for a VCA from the framework action-context pairs, that define voice control of the VCA, wherein each application action-context pair defines an action and a list of parameters related to the action and respective value types of the parameters; an application handler of the VCA associated with each of the application action-context pairs; and a VCA executable file that uses the action-context pairs and associated application handler.
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15. The development system of claim 11 , further comprising a data store comprising: an application action-context pair that holds a plurality of application action-context pairs selected by an application developer for a VCA from the framework action-context pairs, that define voice control of the VCA, wherein each application action-context pair defines an action and a list of parameters related to the action and respective value types of the parameters; an application handler of the VCA associated with each of the application action-context pairs; and a VCA executable file that uses the action-context pairs and associated application handler. 16. The development system of claim 15 , wherein the data store further comprises: a new application action-context pair defined by an application developer that is not present in the framework action-context pairs; an application grammar for the new application action-context pair that uses the natural language library to match the new application action-context pair with new semantically related vocabulary; a registration mechanism that registers the new application action-context pair and associated grammar with the application action-context pairs; and a new application handler association link that links the new application action-context pair.
| 0.5 |
5,404,295 | 1 | 5 |
1. A method for facilitating computer retrieval of database material comprising the steps of: selecting subdivisions for the material; generating for each of said subdivisions which is to be recovered at least one annotation containing words having a selected annotator determined relationship and being in a language selected from the group of a natural language and an artificial language; storing the annotations in a predetermined structured form which retains said selected relationship, the, stored annotations being readable by a computer to search for desired annotations; and adding to the stored annotations a connection to corresponding material subdivisions.
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1. A method for facilitating computer retrieval of database material comprising the steps of: selecting subdivisions for the material; generating for each of said subdivisions which is to be recovered at least one annotation containing words having a selected annotator determined relationship and being in a language selected from the group of a natural language and an artificial language; storing the annotations in a predetermined structured form which retains said selected relationship, the, stored annotations being readable by a computer to search for desired annotations; and adding to the stored annotations a connection to corresponding material subdivisions. 5. A method as claimed in claim 1 wherein the annotations for a given subdivision are a collection of one or more questions, assertions and noun phrases.
| 0.71875 |
9,038,907 | 1 | 2 |
1. A scanning method for checking transparency of a document comprising: a. a single optical sensor to capture both surfaces of said document; b. illuminating any one surface of said document through an illumination source facing said surface; c. imaging of opposite surface of said document wherein an illumination source facing said opposite surface is turned off; d. processing said imaging of opposite surface of said document in a data processor; said processing comprising i. measuring bleed-through in said imaging of opposite surface; ii. contrasting said measured bleed-through with a measured bleed-through of reference image stored in said data processor.
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1. A scanning method for checking transparency of a document comprising: a. a single optical sensor to capture both surfaces of said document; b. illuminating any one surface of said document through an illumination source facing said surface; c. imaging of opposite surface of said document wherein an illumination source facing said opposite surface is turned off; d. processing said imaging of opposite surface of said document in a data processor; said processing comprising i. measuring bleed-through in said imaging of opposite surface; ii. contrasting said measured bleed-through with a measured bleed-through of reference image stored in said data processor. 2. The scanning method of claim 1 , wherein said single optical sensor is 2D camera or linear camera.
| 0.81769 |
7,966,348 | 6 | 8 |
6. An information system, comprising: at least one processor within the information system; at least one memory store within the information system having instructions operable with the at least one processor for utilizing an ontology to classify and enforce template requirements for new content items, the instructions being executed on hardware components within the storage management system for: categorizing content contained within a plurality of electronic content files provided to an information system with an defined an ontology; processing an electronic content file at the information system, the electronic content file containing new content; assigning an ontology classification to the electronic content file from a level of the ontology based on the new content contained in the electronic content file; selecting a template for the electronic content file from a set of templates within the information system based on the ontology classification of the electronic content file, each template classified to at least one level of the ontology, and each template specifying requirements for new content added to the information system using the template, wherein the requirements define content structure, minimum content specifications, and additional contents required for inclusion within the information system, and wherein selecting a template for the electronic content file includes: identifying a template classified at the ontology level of the electronic content file if a template is classified therein; identifying a template classified elsewhere within the ontology if a template is not classified at the ontology level of the electronic content file by traversing the ontology to locate a template at a nearest ancestor of the ontology level of the electronic content file; and applying, if a template was identified within the ontology, the selected template and the requirements of the selected template to the electronic content file; and implementing any applicable changes to the new content of the electronic content file resulting from applying the requirements of the selected template to the new content of the electronic content file, the applicable changes to the new content implemented prior to addition of the electronic content file to the information system.
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6. An information system, comprising: at least one processor within the information system; at least one memory store within the information system having instructions operable with the at least one processor for utilizing an ontology to classify and enforce template requirements for new content items, the instructions being executed on hardware components within the storage management system for: categorizing content contained within a plurality of electronic content files provided to an information system with an defined an ontology; processing an electronic content file at the information system, the electronic content file containing new content; assigning an ontology classification to the electronic content file from a level of the ontology based on the new content contained in the electronic content file; selecting a template for the electronic content file from a set of templates within the information system based on the ontology classification of the electronic content file, each template classified to at least one level of the ontology, and each template specifying requirements for new content added to the information system using the template, wherein the requirements define content structure, minimum content specifications, and additional contents required for inclusion within the information system, and wherein selecting a template for the electronic content file includes: identifying a template classified at the ontology level of the electronic content file if a template is classified therein; identifying a template classified elsewhere within the ontology if a template is not classified at the ontology level of the electronic content file by traversing the ontology to locate a template at a nearest ancestor of the ontology level of the electronic content file; and applying, if a template was identified within the ontology, the selected template and the requirements of the selected template to the electronic content file; and implementing any applicable changes to the new content of the electronic content file resulting from applying the requirements of the selected template to the new content of the electronic content file, the applicable changes to the new content implemented prior to addition of the electronic content file to the information system. 8. The information system of claim 6 , further comprising instructions being executed for defining a template responsive to creation of a new ontology or a new level of an existing ontology within the information system.
| 0.556452 |
8,234,120 | 1 | 9 |
1. A method for use in a voice-enabled system that permits a user to define one or more new voice commands, the method comprising acts of: identifying a user attempt to define a new voice command that is not yet defined in the voice-enabled system, the user attempt comprising a proposed voice command to be associated with a voice-enabled capability in the voice-enabled system, wherein the user attempt fully specifies the proposed voice command; in response to the user providing the proposed voice command as part of the user attempt to define a new voice command, performing, by at least one processor, a safety analysis on the proposed voice command to determine a likelihood that the proposed voice command would be confused with at least one existing voice command that the voice-enabled system was programmed to recognize prior to the act of identifying a user attempt to define a new voice command, wherein the safety analysis is performed after the act of identifying the user attempt; and parsing the proposed voice command into a plurality of component parts, wherein the safety analysis is performed against at least one component part; and when a high likelihood of confusion is determined by the safety analysis, presenting a notification that the proposed voice command is subject to potential confusion.
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1. A method for use in a voice-enabled system that permits a user to define one or more new voice commands, the method comprising acts of: identifying a user attempt to define a new voice command that is not yet defined in the voice-enabled system, the user attempt comprising a proposed voice command to be associated with a voice-enabled capability in the voice-enabled system, wherein the user attempt fully specifies the proposed voice command; in response to the user providing the proposed voice command as part of the user attempt to define a new voice command, performing, by at least one processor, a safety analysis on the proposed voice command to determine a likelihood that the proposed voice command would be confused with at least one existing voice command that the voice-enabled system was programmed to recognize prior to the act of identifying a user attempt to define a new voice command, wherein the safety analysis is performed after the act of identifying the user attempt; and parsing the proposed voice command into a plurality of component parts, wherein the safety analysis is performed against at least one component part; and when a high likelihood of confusion is determined by the safety analysis, presenting a notification that the proposed voice command is subject to potential confusion. 9. The method of claim 1 , wherein the safety analysis is performed against each component part.
| 0.880893 |
9,594,835 | 1 | 25 |
1. A method, comprising: receiving a search query via a web browser of a client; obtaining a set of search results corresponding to the search query; providing the set of search results corresponding to the search query; automatically storing information pertaining to a bookmark in user data of the web browser, wherein the bookmark identifies the search query that was received via the web browser of the client; retrieving information pertaining to a set of bookmarks including the bookmark from the user data of the web browser; and providing, by the web browser, the set of bookmarks underneath a search text box of a user interface, wherein each of the set of bookmarks is user-selectable, wherein each of the set of bookmarks identifies a corresponding search query that was previously received via the web browser of the client; wherein bookmarks provided by the web browser do not identify search queries received via other web browsers or client devices.
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1. A method, comprising: receiving a search query via a web browser of a client; obtaining a set of search results corresponding to the search query; providing the set of search results corresponding to the search query; automatically storing information pertaining to a bookmark in user data of the web browser, wherein the bookmark identifies the search query that was received via the web browser of the client; retrieving information pertaining to a set of bookmarks including the bookmark from the user data of the web browser; and providing, by the web browser, the set of bookmarks underneath a search text box of a user interface, wherein each of the set of bookmarks is user-selectable, wherein each of the set of bookmarks identifies a corresponding search query that was previously received via the web browser of the client; wherein bookmarks provided by the web browser do not identify search queries received via other web browsers or client devices. 25. The method as recited in claim 1 , wherein upon receiving a selection of one of the set of bookmarks, providing a set of links to a set of documents that have previously been selected via the web browser in association with the search query identified by the corresponding bookmark and an indication of a frequency with which each of the set of one or more documents has been selected via the web browser.
| 0.77844 |
8,799,787 | 1 | 4 |
1. A method for facilitating use of a plurality of user context objects determined for an avatar that is online in a virtual universe, comprising: presenting the plurality of user context objects to the avatar, wherein the presenting of the plurality of user context objects to the avatar includes deriving the plurality of user context objects from all of the following: inventory items belonging to the avatar, teleportation history of the avatar, motion history of the avatar and social tagging behavior exhibited by a user of the avatar in the real world; receiving a user context object selection from the avatar, wherein the user context object selection contains one of the plurality of user context objects determined for the avatar and any desired modifications made to the user context object selected by the avatar; and permitting the avatar to interact with the virtual universe in accordance with the user context object selection, wherein the permitting of the avatar to interact with the virtual universe includes applying the user context object selection to a robot avatar that is configured to allow the avatar to interact anonymously and semi-autonomously within the virtual universe.
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1. A method for facilitating use of a plurality of user context objects determined for an avatar that is online in a virtual universe, comprising: presenting the plurality of user context objects to the avatar, wherein the presenting of the plurality of user context objects to the avatar includes deriving the plurality of user context objects from all of the following: inventory items belonging to the avatar, teleportation history of the avatar, motion history of the avatar and social tagging behavior exhibited by a user of the avatar in the real world; receiving a user context object selection from the avatar, wherein the user context object selection contains one of the plurality of user context objects determined for the avatar and any desired modifications made to the user context object selected by the avatar; and permitting the avatar to interact with the virtual universe in accordance with the user context object selection, wherein the permitting of the avatar to interact with the virtual universe includes applying the user context object selection to a robot avatar that is configured to allow the avatar to interact anonymously and semi-autonomously within the virtual universe. 4. The method according to claim 1 , wherein the modifications include changes to attribute values associated with the selected user context object that describe behavioral, search and informational needs of the avatar.
| 0.851626 |
9,483,803 | 1 | 2 |
1. A method comprising, by a computing device: receiving, from a client system of a first user, a structured query comprising references to one or more selected objects accessible by the computing device; generating one or more search results corresponding to the structured query, wherein each search result corresponds to a particular object accessible by the computing device; determining one or more search intents based at least on whether one or more of the selected objects referenced in the structured query match objects corresponding to a search intent indexed in a pattern-detection model; and scoring the search results based on one or more of the search intents.
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1. A method comprising, by a computing device: receiving, from a client system of a first user, a structured query comprising references to one or more selected objects accessible by the computing device; generating one or more search results corresponding to the structured query, wherein each search result corresponds to a particular object accessible by the computing device; determining one or more search intents based at least on whether one or more of the selected objects referenced in the structured query match objects corresponding to a search intent indexed in a pattern-detection model; and scoring the search results based on one or more of the search intents. 2. The method of claim 1 , further comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to the first user; and a plurality of second nodes corresponding to a plurality of objects accessible by the computing device, respectively.
| 0.558233 |
9,766,879 | 13 | 16 |
13. A system for providing supplemental functionalities for an executable program via an ontology instance, the system comprising: a computer system comprising one or more processors programmed with computer program instructions which, when executed, cause the computer system to: cause an executable program to be run; obtain a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; validate the general ontology; obtain an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; generate, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; and provide the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application be made available via the executable program.
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13. A system for providing supplemental functionalities for an executable program via an ontology instance, the system comprising: a computer system comprising one or more processors programmed with computer program instructions which, when executed, cause the computer system to: cause an executable program to be run; obtain a general ontology and a domain-specific ontology, wherein the domain-specific ontology is associated with a domain of interest, and the executable program is configured to use at least a portion of the general ontology to interpret the domain-specific ontology; validate the general ontology; obtain an instance of the general ontology, wherein the general ontology instance is based on the domain-specific ontology and corresponds to an application associated with the domain of interest; generate, based on the general ontology instance, supplemental information for the executable program, wherein the supplemental information is related to one or more functionalities of the application to be added to the executable program; and provide the supplemental information as input to the executable program, wherein the supplemental information, at least in part, causes the one or more functionalities of the application be made available via the executable program. 16. The system of claim 13 , wherein the executable program obtains the supplemental information from working memory at runtime.
| 0.940905 |
9,063,637 | 1 | 5 |
1. A method that alters a view of a document comprising: providing on a display of a computer processing device an editing view of a document at a zoom level such that input from a user can be received to edit content of the document; receiving a first input from the user requesting to zoom-out the editing view of the document from the zoom level; testing whether a resulting zoom level of the document is less than a threshold zoom level; altering the view of the document to provide a semantic zoom view of the document in response to determining the resulting zoom level is less than the threshold zoom level, wherein the semantic view of the document provides a plurality of thumbnails pages on the display and a heading pane comprising a plurality of headings contained in one or more pages of the document; receiving a second input from the user indicating a selection of one of the plurality of headings in the heading pane; and providing on the display of the computer processing device a subset of the plurality of thumbnail pages in the thumbnail pane in response to receiving the second input, wherein the subset of the plurality of thumbnail pages comprises a thumbnail page corresponding to the selection of one of the plurality of headings in the heading pane and a plurality of and preceeding and succeeding thumbnail pages to the thumbnail page.
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1. A method that alters a view of a document comprising: providing on a display of a computer processing device an editing view of a document at a zoom level such that input from a user can be received to edit content of the document; receiving a first input from the user requesting to zoom-out the editing view of the document from the zoom level; testing whether a resulting zoom level of the document is less than a threshold zoom level; altering the view of the document to provide a semantic zoom view of the document in response to determining the resulting zoom level is less than the threshold zoom level, wherein the semantic view of the document provides a plurality of thumbnails pages on the display and a heading pane comprising a plurality of headings contained in one or more pages of the document; receiving a second input from the user indicating a selection of one of the plurality of headings in the heading pane; and providing on the display of the computer processing device a subset of the plurality of thumbnail pages in the thumbnail pane in response to receiving the second input, wherein the subset of the plurality of thumbnail pages comprises a thumbnail page corresponding to the selection of one of the plurality of headings in the heading pane and a plurality of and preceeding and succeeding thumbnail pages to the thumbnail page. 5. The method of claim 1 , wherein the threshold level is 15%.
| 0.908824 |
9,275,018 | 1 | 3 |
1. A computer-implemented method, comprising: intercepting, at a proxy server including one or more processors, a request for a source document representing a web page, the request being transmitted from a remote computing device to a remote web server via a network, the request including web browser information indicating web browser software executing on the remote computing device; intercepting, at the proxy server, the source document being transmitted from the remote web server to the remote computing device via the network in response to the request, the source document including a text and specifying one or more fonts in which to display the text; rendering, at the proxy server, the web page using the source document, the web page including the text displayed in the one or more fonts; determining, at the proxy server, unique characters displayed at the web page for each of the specified one or more fonts in which the text is displayed; obtaining, at the proxy server, one or more font subsets based on the unique characters, wherein at least one of the one or more font subsets includes the unique characters in the source document and one or more additional characters related to the unique characters in the source document, and wherein the one or more additional characters related to the unique characters include at least one of (i) one or more characters having a different case than one or more of the unique characters and (ii) one or more characters having a different accent than one or more of the unique characters; determining, at the proxy server, whether the one or more fonts in which the text is displayed form a font family having a plurality of fonts, each of the plurality of fonts having at least one of a different weight and a different style; determining, at the proxy server, whether the web browser software indicated by the web browser information is capable of displaying the font family having the plurality of fonts; and modifying, at the proxy server, the source document by embedding the plurality of fonts therein to obtain a modified source document when the one or more fonts displayed at the web page form the font family having the plurality of fonts and the web browser software indicated by the web browser information is incapable of displaying the font family having the plurality of fonts; and transmitting, from the proxy server to the remote computing device, information specifying the one or more font subsets when the web browser software indicated by the web browser information is capable of displaying the font family having the plurality of fonts, the modified source document, or a command and a single font subset.
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1. A computer-implemented method, comprising: intercepting, at a proxy server including one or more processors, a request for a source document representing a web page, the request being transmitted from a remote computing device to a remote web server via a network, the request including web browser information indicating web browser software executing on the remote computing device; intercepting, at the proxy server, the source document being transmitted from the remote web server to the remote computing device via the network in response to the request, the source document including a text and specifying one or more fonts in which to display the text; rendering, at the proxy server, the web page using the source document, the web page including the text displayed in the one or more fonts; determining, at the proxy server, unique characters displayed at the web page for each of the specified one or more fonts in which the text is displayed; obtaining, at the proxy server, one or more font subsets based on the unique characters, wherein at least one of the one or more font subsets includes the unique characters in the source document and one or more additional characters related to the unique characters in the source document, and wherein the one or more additional characters related to the unique characters include at least one of (i) one or more characters having a different case than one or more of the unique characters and (ii) one or more characters having a different accent than one or more of the unique characters; determining, at the proxy server, whether the one or more fonts in which the text is displayed form a font family having a plurality of fonts, each of the plurality of fonts having at least one of a different weight and a different style; determining, at the proxy server, whether the web browser software indicated by the web browser information is capable of displaying the font family having the plurality of fonts; and modifying, at the proxy server, the source document by embedding the plurality of fonts therein to obtain a modified source document when the one or more fonts displayed at the web page form the font family having the plurality of fonts and the web browser software indicated by the web browser information is incapable of displaying the font family having the plurality of fonts; and transmitting, from the proxy server to the remote computing device, information specifying the one or more font subsets when the web browser software indicated by the web browser information is capable of displaying the font family having the plurality of fonts, the modified source document, or a command and a single font subset. 3. The computer-implemented method of claim 1 , further comprising in response to being unable to locate or identify one or more particular characters, obtaining the one or more font subsets having less than all of the unique characters in the source document.
| 0.579288 |
10,065,104 | 15 | 17 |
15. A computer-implemented method of determining game objects to be displayed on a display comprising: responsive to user input received via a user interface of said user device, determining a game level of a plurality of game levels which is to be provided, each game level having an associated difficulty; causing a processor to use at least one dictionary stored in a memory to select one or more words stored in the at least one dictionary to seed an initial game board which is to be displayed on a display for the determined game level, the at least one dictionary comprising a plurality of words of a first type and a plurality of words of a second type, said words of the first type and the second type being in a common language, the plurality of words of the second type categorised as more common than the plurality of words of the first type, wherein at least one of a type of said selected at least one word and orientation in which said at least one word is displayed is dependent on the associated difficulty of the determined game level; causing to be displayed on the display a plurality of selectable game objects comprising tiles arranged on the initial game board, each tile having a letter, said tiles in said game board being arranged to enable a user to select one or more of the tiles in a manner that spells a word, the initial game board including said selected at least one word; receiving user input, via a user interface, selecting a plurality of said tiles of said initial game board to spell a word; determining if the spelled word comprises a valid input, said spelled word being a valid input if the spelled word is in said at least one dictionary, wherein words of said first type and words of said second type both comprise valid inputs; in response to determining that said spelled word is a valid input, said at least one processor is configured to cause said selected tiles to be removed from said game board; and causing said game board to be replenished after said selected tiles have been removed.
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15. A computer-implemented method of determining game objects to be displayed on a display comprising: responsive to user input received via a user interface of said user device, determining a game level of a plurality of game levels which is to be provided, each game level having an associated difficulty; causing a processor to use at least one dictionary stored in a memory to select one or more words stored in the at least one dictionary to seed an initial game board which is to be displayed on a display for the determined game level, the at least one dictionary comprising a plurality of words of a first type and a plurality of words of a second type, said words of the first type and the second type being in a common language, the plurality of words of the second type categorised as more common than the plurality of words of the first type, wherein at least one of a type of said selected at least one word and orientation in which said at least one word is displayed is dependent on the associated difficulty of the determined game level; causing to be displayed on the display a plurality of selectable game objects comprising tiles arranged on the initial game board, each tile having a letter, said tiles in said game board being arranged to enable a user to select one or more of the tiles in a manner that spells a word, the initial game board including said selected at least one word; receiving user input, via a user interface, selecting a plurality of said tiles of said initial game board to spell a word; determining if the spelled word comprises a valid input, said spelled word being a valid input if the spelled word is in said at least one dictionary, wherein words of said first type and words of said second type both comprise valid inputs; in response to determining that said spelled word is a valid input, said at least one processor is configured to cause said selected tiles to be removed from said game board; and causing said game board to be replenished after said selected tiles have been removed. 17. A method as set forth in claim 15 wherein the plurality of words of the first type and the plurality of words of the second type are stored in the same dictionary, and distinguished from each other by means of one or more flags.
| 0.5 |
8,549,397 | 5 | 9 |
5. A system comprising: one or more processors; one or more computer storage media for storing instructions, which when executed by the one or more processors, cause the one or more processors to: compute style rules for a plurality of elements of an original markup language video content to define pseudo-classes which preserve a dynamic layout, presentation, rendering, and user interface interaction of a plurality of elements of the content; transcode the plurality of elements and the style rules into a binary format video content with a document object model hierarchy via a routine specific to a predetermined client, the binary format video content including a list of the pseudo-classes for preserving a layout, rendering, user interface (UI) interaction, and dynamic aspect of the original markup language video, wherein the document object model hierarchy includes nodes having pre-cascaded style rules; and a network interface to communicate the binary format video content for presentation over a network to the predetermined client.
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5. A system comprising: one or more processors; one or more computer storage media for storing instructions, which when executed by the one or more processors, cause the one or more processors to: compute style rules for a plurality of elements of an original markup language video content to define pseudo-classes which preserve a dynamic layout, presentation, rendering, and user interface interaction of a plurality of elements of the content; transcode the plurality of elements and the style rules into a binary format video content with a document object model hierarchy via a routine specific to a predetermined client, the binary format video content including a list of the pseudo-classes for preserving a layout, rendering, user interface (UI) interaction, and dynamic aspect of the original markup language video, wherein the document object model hierarchy includes nodes having pre-cascaded style rules; and a network interface to communicate the binary format video content for presentation over a network to the predetermined client. 9. The system as recited in claim 5 , wherein the network is at least one of: a cable television broadcasting network; a satellite television broadcasting network; a cellular telephone network; a terrestrial analog or digital broadcasting television network; a local area network (LAN); a wide area network (WAN); or an Internet.
| 0.630337 |
8,176,074 | 13 | 15 |
13. A computer-readable storage medium including instructions executed by a processor for implementing a method for querying a tag database, the method comprising: storing the tag database in a storage device; receiving an XML document including a database query written in a query language supported by an agent of the tag database, the query language supporting database features, tag features, and text features, the database query including a request for at least one feature of the query language that is supported by the agent; parsing the XML document to extract the database query from the XML document; accessing, using the processor, the tag database to perform at least one of a read or write operation on the tag database, based on the database query; and in response to receipt of the database query, returning a list of features, the list of features indicating the features of the query language that are supported by the agent, wherein the tag features include tag query language directives, the tag query language directives including at least one of retrieve, aggregate, call, partition, continue, list, override, or return.
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13. A computer-readable storage medium including instructions executed by a processor for implementing a method for querying a tag database, the method comprising: storing the tag database in a storage device; receiving an XML document including a database query written in a query language supported by an agent of the tag database, the query language supporting database features, tag features, and text features, the database query including a request for at least one feature of the query language that is supported by the agent; parsing the XML document to extract the database query from the XML document; accessing, using the processor, the tag database to perform at least one of a read or write operation on the tag database, based on the database query; and in response to receipt of the database query, returning a list of features, the list of features indicating the features of the query language that are supported by the agent, wherein the tag features include tag query language directives, the tag query language directives including at least one of retrieve, aggregate, call, partition, continue, list, override, or return. 15. The computer-readable storage medium of claim 13 , wherein the database query includes a mask.
| 0.791489 |
9,996,611 | 1 | 15 |
1. A method using a computer having a hardware processor to classify a plurality of users in social media, the method comprising the steps of: generating, using the hardware processor, a content feature vector for each of a portion of users of the plurality of users on the basis of content associated with the portion of users; generating, using the hardware processor, a plurality of clusters on the basis of the content feature vectors; mapping, using the hardware processor the portion of users to the plurality of clusters on the basis of the content feature vectors; generating, using the hardware processor, a first profile feature vector for each of the plurality of clusters on the basis of profiles associated with corresponding users within the portion of users mapped to each cluster; and classifying, using the hardware processor, each of the other users excluding the portion of users into the plurality of clusters on the basis of profiles associated with the other users and the first profile feature vectors, and outputting, via display device associated with said computer, clusters corresponding to the classified other users.
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1. A method using a computer having a hardware processor to classify a plurality of users in social media, the method comprising the steps of: generating, using the hardware processor, a content feature vector for each of a portion of users of the plurality of users on the basis of content associated with the portion of users; generating, using the hardware processor, a plurality of clusters on the basis of the content feature vectors; mapping, using the hardware processor the portion of users to the plurality of clusters on the basis of the content feature vectors; generating, using the hardware processor, a first profile feature vector for each of the plurality of clusters on the basis of profiles associated with corresponding users within the portion of users mapped to each cluster; and classifying, using the hardware processor, each of the other users excluding the portion of users into the plurality of clusters on the basis of profiles associated with the other users and the first profile feature vectors, and outputting, via display device associated with said computer, clusters corresponding to the classified other users. 15. The method according to claim 1 further comprising the step of connecting a server hosting the social media to a computer classifying the plurality of users in a plurality of clusters via a network, the computer receiving information sent by the server in response to a request from the computer.
| 0.615385 |
10,068,016 | 5 | 6 |
5. The method of claim 3 , wherein: the electronic object comprises a list; and the metadata includes descriptive information regarding content of the list to enable construction by the computing device, using the metadata, of the sentence or statement so that the sentence or statement describes content of the list.
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5. The method of claim 3 , wherein: the electronic object comprises a list; and the metadata includes descriptive information regarding content of the list to enable construction by the computing device, using the metadata, of the sentence or statement so that the sentence or statement describes content of the list. 6. The method of claim 5 , wherein the metadata further includes an indication of a subset of items in the list to include in the sentence or statement.
| 0.5 |
8,949,357 | 1 | 17 |
1. A method of conducting a real-time private group chat conversation using a social networking service to connect users to the conversation, the method comprising: monitoring, using a controller, a stream of text strings published by a public social networking service; scanning the text strings to determine whether any of the text strings include an action tag that includes a predetermined combination of characters; responsive to determining that a first of the text strings includes the action tag, determining a creator user account name that is attempting to initiate a private conversation and reading at least one user account name in the first text string and a title for the private conversation to be initiated, the creator user account name being associated with an externally published creator user account in the social networking service and the user account name being associated with an externally published user account in the social networking service; causing a request to be sent to the user account in the social networking service, the request including an indication of the request for the private conversation and the creator user account name and a uniform resource locator (URL) for joining the private conversation; responsive to the user account accepting the request by directing a browser to access the URL provided in the request from the social networking service, connecting the user account with a creator user account associated with the creator user account name in a private conversation; and communicating, using the controller, messages of the private conversation between the user account and the creator user account, wherein the action tag starts with at least one non-alphanumeric character, includes at least one alphanumeric character, and is at the beginning of the text string such that the predetermined combination of characters are the first characters of the text string, and wherein the user account names are preceded by a hashtag.
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1. A method of conducting a real-time private group chat conversation using a social networking service to connect users to the conversation, the method comprising: monitoring, using a controller, a stream of text strings published by a public social networking service; scanning the text strings to determine whether any of the text strings include an action tag that includes a predetermined combination of characters; responsive to determining that a first of the text strings includes the action tag, determining a creator user account name that is attempting to initiate a private conversation and reading at least one user account name in the first text string and a title for the private conversation to be initiated, the creator user account name being associated with an externally published creator user account in the social networking service and the user account name being associated with an externally published user account in the social networking service; causing a request to be sent to the user account in the social networking service, the request including an indication of the request for the private conversation and the creator user account name and a uniform resource locator (URL) for joining the private conversation; responsive to the user account accepting the request by directing a browser to access the URL provided in the request from the social networking service, connecting the user account with a creator user account associated with the creator user account name in a private conversation; and communicating, using the controller, messages of the private conversation between the user account and the creator user account, wherein the action tag starts with at least one non-alphanumeric character, includes at least one alphanumeric character, and is at the beginning of the text string such that the predetermined combination of characters are the first characters of the text string, and wherein the user account names are preceded by a hashtag. 17. The method of claim 1 , wherein the monitoring is carried out using an application programming interface (API) connected to the social networking service.
| 0.863558 |
8,768,708 | 8 | 9 |
8. The method of claim 1 , wherein the output indicator of the personality profile of the speaker is compared to results of a questionnaire.
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8. The method of claim 1 , wherein the output indicator of the personality profile of the speaker is compared to results of a questionnaire. 9. The method of claim 8 , wherein the output indicator of the personality profile of the speaker is compared to the results of the questionnaire to validate the results of the questionnaire.
| 0.510256 |
8,370,347 | 16 | 17 |
16. A method for assessing information in natural language contents, comprising: receiving an object name as a query term from a user interface by a computer processing system; retrieving an object-specific data set related to the object name from a computer storage system, wherein the object-specific data set includes a plurality of property names and association-strength values, each property name being associated with an association-strength value, wherein the association strength values of the plurality of property names are above a predetermined threshold value, wherein the plurality of property names includes a first property name and a second property name; retrieving, by the computer processing system, a plurality of documents containing text in a natural language; counting a first frequency of the first property name in one of the plurality of documents by the computer processing system; counting a second frequency of the second property name in the in one of the plurality of documents by the computer processing system; calculating a relevance score as a function of the first frequency and the second frequency; ranking the plurality of documents using their respective relevance scores; and returning one or more documents to the user interface based on the ranking of the plurality of documents.
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16. A method for assessing information in natural language contents, comprising: receiving an object name as a query term from a user interface by a computer processing system; retrieving an object-specific data set related to the object name from a computer storage system, wherein the object-specific data set includes a plurality of property names and association-strength values, each property name being associated with an association-strength value, wherein the association strength values of the plurality of property names are above a predetermined threshold value, wherein the plurality of property names includes a first property name and a second property name; retrieving, by the computer processing system, a plurality of documents containing text in a natural language; counting a first frequency of the first property name in one of the plurality of documents by the computer processing system; counting a second frequency of the second property name in the in one of the plurality of documents by the computer processing system; calculating a relevance score as a function of the first frequency and the second frequency; ranking the plurality of documents using their respective relevance scores; and returning one or more documents to the user interface based on the ranking of the plurality of documents. 17. The method of claim 16 , further comprising: receiving a value for a customized ranking parameter from a user by the computer processing system; and calculating the relevance score as a function of the first frequency, the second frequency, and the customized ranking parameter.
| 0.839955 |
6,058,166 | 1 | 2 |
1. A method for playing prompts during execution of a call flow of a network application, comprising the steps of: storing a plurality of subsets of prompt definitions associated with a particular language, each subset containing prompt definitions for prompts to be played during the call low, one of said subsets being designated as a base subset; designating, at a point in the call flow, one of said subsets of prompt definitions, other than the base subset, as an alternate subset; and thereafter, in response to a request to play a particular prompt, first searching the alternate subset to determine whether it contains a prompt definition for the requested prompt, and if so, playing the prompt according to the prompt definition in the alternate subset, but if the alternate subset does not contain a prompt definition for the requested prompt, then searching the base subset for a prompt definition for the requested prompt and playing the prompt according to the prompt definition in the base subset.
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1. A method for playing prompts during execution of a call flow of a network application, comprising the steps of: storing a plurality of subsets of prompt definitions associated with a particular language, each subset containing prompt definitions for prompts to be played during the call low, one of said subsets being designated as a base subset; designating, at a point in the call flow, one of said subsets of prompt definitions, other than the base subset, as an alternate subset; and thereafter, in response to a request to play a particular prompt, first searching the alternate subset to determine whether it contains a prompt definition for the requested prompt, and if so, playing the prompt according to the prompt definition in the alternate subset, but if the alternate subset does not contain a prompt definition for the requested prompt, then searching the base subset for a prompt definition for the requested prompt and playing the prompt according to the prompt definition in the base subset. 2. The method recited in claim 1 wherein at least one of the subsets contains prompt definitions for prompts to be played during only a part of the call flow.
| 0.799492 |
9,015,190 | 10 | 12 |
10. An electronic discovery computing system comprising: one or more processors; and one or more memory resources storing instructions that, when executed by the one or more processors, cause the electronic discovery computing system to perform operations comprising: providing a user interface to enable execution of input queries to search for relevant documents in a document repository of the electronic discovery computing system; receiving an input query from a first portion of the user interface, the input query including a number of terms and operators that, when executed via a selectable feature on the user interface, cause the electronic discovery computing system to perform a search in the document repository based on the input query; and while receiving the input query, generating a graphical representation of the input query to be displayed on a second portion of the user interface in real-time, the graphical representation showing how the terms and operators are to be interpreted by the electronic discovery computing system upon execution of the search; wherein generating the graphical representation includes generating a distinct visual indicator for each term operated by a Boolean NOT operator of the input query.
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10. An electronic discovery computing system comprising: one or more processors; and one or more memory resources storing instructions that, when executed by the one or more processors, cause the electronic discovery computing system to perform operations comprising: providing a user interface to enable execution of input queries to search for relevant documents in a document repository of the electronic discovery computing system; receiving an input query from a first portion of the user interface, the input query including a number of terms and operators that, when executed via a selectable feature on the user interface, cause the electronic discovery computing system to perform a search in the document repository based on the input query; and while receiving the input query, generating a graphical representation of the input query to be displayed on a second portion of the user interface in real-time, the graphical representation showing how the terms and operators are to be interpreted by the electronic discovery computing system upon execution of the search; wherein generating the graphical representation includes generating a distinct visual indicator for each term operated by a Boolean NOT operator of the input query. 12. The electronic discovery computing system of claim 10 , wherein the instructions, when executed by the one or more processors, cause the electronic discovery computing system to perform further operations comprising: receiving, via a third portion of the user interface, metadata values associated with filters to be applied, by the electronic discovery computing system, in conjunction with execution of the terms and operators of the input query during the search.
| 0.561567 |
9,588,999 | 15 | 19 |
15. A computer system for a database storage reclaiming program, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on one or more of the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to retrieve a list of data elements for deletion from a database catalog, wherein the list of data elements for deletion details one or more data elements contained in a database; program instructions to determine whether first data elements of the one or more data elements on the list of data elements for deletion have been active in one or more static Structured Query Language (SQL) statements, wherein the one or more static SQL statements are persistent and created before runtime; program instructions to remove the first data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more static SQL statements; program instructions to determine whether second data elements of the one or more data elements on the list of data elements for deletion have been active in one or more dynamic SQL statements, wherein the one or more dynamic SQL statements are non-persistent and created at runtime; program instructions to remove the second data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more dynamic SQL statements; program instructions to determine whether third data elements of the one or more data elements on the list of data elements for deletion are associated with one or more data elements not on the list of data elements for deletion; program instructions to remove the third data elements of the one or more data elements from the list of data elements for deletion that are determined to be associated with the one or more data elements not on the list of data elements for deletion; program instructions to determine whether fourth data elements of the one or more data elements on the list of data elements for deletion are used in a source code of one or more applications; and program instructions to remove the fourth data elements of the one or more data elements from the list of data elements for deletion that are determined to be used in the source code of the one or more applications.
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15. A computer system for a database storage reclaiming program, the computer system comprising: one or more computer processors, one or more computer-readable storage media, and program instructions stored on one or more of the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to retrieve a list of data elements for deletion from a database catalog, wherein the list of data elements for deletion details one or more data elements contained in a database; program instructions to determine whether first data elements of the one or more data elements on the list of data elements for deletion have been active in one or more static Structured Query Language (SQL) statements, wherein the one or more static SQL statements are persistent and created before runtime; program instructions to remove the first data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more static SQL statements; program instructions to determine whether second data elements of the one or more data elements on the list of data elements for deletion have been active in one or more dynamic SQL statements, wherein the one or more dynamic SQL statements are non-persistent and created at runtime; program instructions to remove the second data elements of the one or more data elements from the list of data elements for deletion that have been determined to be active in the one or more dynamic SQL statements; program instructions to determine whether third data elements of the one or more data elements on the list of data elements for deletion are associated with one or more data elements not on the list of data elements for deletion; program instructions to remove the third data elements of the one or more data elements from the list of data elements for deletion that are determined to be associated with the one or more data elements not on the list of data elements for deletion; program instructions to determine whether fourth data elements of the one or more data elements on the list of data elements for deletion are used in a source code of one or more applications; and program instructions to remove the fourth data elements of the one or more data elements from the list of data elements for deletion that are determined to be used in the source code of the one or more applications. 19. The computer system of claim 15 , wherein the determining whether the third data elements of the one or more data elements on the list of data elements for deletion are associated with the one or more data elements not on the list of data elements for deletion includes cross referencing the one or more data elements on the list of candidates for deletion with the database catalog, wherein the database catalog details relationships of the one or more data elements contained in the database.
| 0.543119 |
5,429,513 | 1 | 2 |
1. An interactive teaching apparatus for teaching graphemes, grapheme names, phonemes, and phonetics comprising: a display of graphemes wherein each of said graphemes is color-coded with at least one of a plurality of distinctive colors and each of said distinctive colors corresponds to a characteristic of sound production associated with at least one phoneme of at least one of said graphemes; a plurality of visually perceivable images, each of which is positioned adjacent to at least one of said graphemes, such that said adjacent image has a name including at least one phoneme of said at least one adjacent grapheme; a plurality of individually-activated, sound generating devices, each of which is associated with one of said graphemes and generates the name of said grapheme; and at least one sound pattern generating device for generating patterns of sounds comprising more than one of the names generated by said plurality of sound generating devices.
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1. An interactive teaching apparatus for teaching graphemes, grapheme names, phonemes, and phonetics comprising: a display of graphemes wherein each of said graphemes is color-coded with at least one of a plurality of distinctive colors and each of said distinctive colors corresponds to a characteristic of sound production associated with at least one phoneme of at least one of said graphemes; a plurality of visually perceivable images, each of which is positioned adjacent to at least one of said graphemes, such that said adjacent image has a name including at least one phoneme of said at least one adjacent grapheme; a plurality of individually-activated, sound generating devices, each of which is associated with one of said graphemes and generates the name of said grapheme; and at least one sound pattern generating device for generating patterns of sounds comprising more than one of the names generated by said plurality of sound generating devices. 2. The teaching apparatus of claim 1 wherein said individually-activated, sound generating device is activated by pressure.
| 0.883743 |
7,797,724 | 1 | 2 |
1. A method for securely providing access to a content file, the method comprising: (a) requesting, by a user via a client device, access to a content file; (b) creating, by a transport mechanism executing on the client device, a document container on the client device; (c) receiving, by the document container from a server, the content file; (d) storing, by a storage buffer on the client device, the received content file in a volatile memory element; (e) invoking, by the document container, an application program associated with the content file, the application program providing a set of menu commands for interacting with the application program; and (f) generating, by the document container, a replacement set of menu commands comprising a subset of the set of menu commands provided by the application program.
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1. A method for securely providing access to a content file, the method comprising: (a) requesting, by a user via a client device, access to a content file; (b) creating, by a transport mechanism executing on the client device, a document container on the client device; (c) receiving, by the document container from a server, the content file; (d) storing, by a storage buffer on the client device, the received content file in a volatile memory element; (e) invoking, by the document container, an application program associated with the content file, the application program providing a set of menu commands for interacting with the application program; and (f) generating, by the document container, a replacement set of menu commands comprising a subset of the set of menu commands provided by the application program. 2. The method of claim 1 wherein step (a) further comprises requesting access to a content file using an URL moniker.
| 0.576087 |
10,002,132 | 7 | 9 |
7. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: displaying a graphical user interface for language translation on a user device that includes (i) one or more automated speech recognizers that recognize speech in a source language only when in a first mode and to recognize speech in a target language only when in a second mode, (ii) a microphone that receives audio, and (iii) a speaker that outputs audio, the graphical user interface comprising a source language visual indicator and a target language visual indicator; in the first mode in which the one or more automated speech recognizers recognize speech in the source language only, highlighting the source language visual indicator and displaying an input visual indicator on the graphical user interface to provide a visual indication that the user device receives audio input in the source language only; and in response to an endpointer on the user device automatically determining that the input in the source language only has completed, and without requiring the user to manually switch between the first mode and the second mode, automatically activating the second mode in which the one or more automated speech recognizers recognize speech in the target language only, removing highlighting from the source language visual indicator, highlighting the target language visual indicator, and replacing the input visual indicator with an output visual indicator on the graphical user interface to provide a visual indication that the user device provides audio output in the target language.
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7. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: displaying a graphical user interface for language translation on a user device that includes (i) one or more automated speech recognizers that recognize speech in a source language only when in a first mode and to recognize speech in a target language only when in a second mode, (ii) a microphone that receives audio, and (iii) a speaker that outputs audio, the graphical user interface comprising a source language visual indicator and a target language visual indicator; in the first mode in which the one or more automated speech recognizers recognize speech in the source language only, highlighting the source language visual indicator and displaying an input visual indicator on the graphical user interface to provide a visual indication that the user device receives audio input in the source language only; and in response to an endpointer on the user device automatically determining that the input in the source language only has completed, and without requiring the user to manually switch between the first mode and the second mode, automatically activating the second mode in which the one or more automated speech recognizers recognize speech in the target language only, removing highlighting from the source language visual indicator, highlighting the target language visual indicator, and replacing the input visual indicator with an output visual indicator on the graphical user interface to provide a visual indication that the user device provides audio output in the target language. 9. The system of claim 7 , wherein the visual indication that the user device receives audio input in the source language is provided by highlighting the input visual indicator on the graphical user interface while highlighting the source language visual indicator.
| 0.710699 |
9,575,563 | 1 | 12 |
1. A method carried out by a head-mountable device comprising: sending, a speech-segment message to a hybrid response system in response to detecting a first singular touch gesture on a touchpad of the head-mountable device (HMD), wherein the HMD comprises a near-eye display, and wherein the touchpad is located on a side-arm of the HMD, wherein the speech-segment message is indicative of a speech-segment detected in audio data captured at the HMD by at least one microphone, wherein the speech-segment is associated with a first user-account with the hybrid response system, and wherein the speech-segment message comprises an initial query; receiving, at the HMD, a response message from the hybrid response system, wherein the response message comprises: both (a) an answer to the initial query and (b) an indication of a next action to be cued in anticipation of the initial query, wherein the next action is an anticipated actionable follow-up request related to the answer of the initial query; and in response to receiving the response message: displaying, on the HMD, a first card interface that includes an indication of the answer to the initial query; and while displaying the first card interface that indicates the answer to the initial query, detecting touchpad data corresponding to a second singular touch gesture on the touchpad and responsively initiating the next action corresponding to the anticipated follow-up request originally indicated in the response message by displaying a second card interface of a cued next action.
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1. A method carried out by a head-mountable device comprising: sending, a speech-segment message to a hybrid response system in response to detecting a first singular touch gesture on a touchpad of the head-mountable device (HMD), wherein the HMD comprises a near-eye display, and wherein the touchpad is located on a side-arm of the HMD, wherein the speech-segment message is indicative of a speech-segment detected in audio data captured at the HMD by at least one microphone, wherein the speech-segment is associated with a first user-account with the hybrid response system, and wherein the speech-segment message comprises an initial query; receiving, at the HMD, a response message from the hybrid response system, wherein the response message comprises: both (a) an answer to the initial query and (b) an indication of a next action to be cued in anticipation of the initial query, wherein the next action is an anticipated actionable follow-up request related to the answer of the initial query; and in response to receiving the response message: displaying, on the HMD, a first card interface that includes an indication of the answer to the initial query; and while displaying the first card interface that indicates the answer to the initial query, detecting touchpad data corresponding to a second singular touch gesture on the touchpad and responsively initiating the next action corresponding to the anticipated follow-up request originally indicated in the response message by displaying a second card interface of a cued next action. 12. The method of claim 1 , wherein the HMD does not display any indication of the cued next action before detecting the second singular touch gesture and responsively initiating the next action.
| 0.835304 |
8,612,468 | 7 | 9 |
7. The method of claim 6 , wherein identifying logically derived associations further comprises: creating a stack for storing logically derived associations; upon encountering a logically derived association in the metadata file, searching the stack for any occurrences of the logically derived association; if no occurrence of the logically derived association is found in the stack, then pushing the logically derived association onto the stack; and if the newly defined logically derived association is present in the stack, then generating an error.
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7. The method of claim 6 , wherein identifying logically derived associations further comprises: creating a stack for storing logically derived associations; upon encountering a logically derived association in the metadata file, searching the stack for any occurrences of the logically derived association; if no occurrence of the logically derived association is found in the stack, then pushing the logically derived association onto the stack; and if the newly defined logically derived association is present in the stack, then generating an error. 9. The method of claim 7 , further comprising if an error is generated, then: examining all intervening entries in the stack between the two occurrences of the logically derived association; and identifying intervening entries that are potentially responsible for the error.
| 0.716356 |
7,853,541 | 1 | 2 |
1. An article comprising a non-transitory machine-readable storage medium operable to cause one or more machines to result in operations comprising: arranging objects which are realizations of a first variable and a second variable into a current clustering to aid in solving a problem; constructing a shortlist of destination clusters, the shortlist containing a predetermined number, N, of destination clusters for a current object, each destination cluster associated with a score, each destination cluster in the shortlist having an associated score that is greater than an associated score of each destination cluster not in the shortlist; picking randomly a destination cluster from said shortlist of destination clusters; determining if said picked destination cluster is acceptable according to a probabilistic acceptance criteria at a current temperature, T, the current temperature representing an iteration of temperature out of a plurality of iterations of temperature from a first temperature to a second temperature; replacing said current clustering with said picked destination clustering, if said picked destination clustering is acceptable; repeating, at each iteration of temperature, the picking, the determining, and the replacing until no acceptable destination clusters from said shortlist of destination clusters remain; establishing said current clustering of objects as an output clustering, wherein said output clustering has a high confidence level of having a maximum of mutual information between said variables for predicting relationships between said variables; and outputting said output clustering for display to a user for use in solving said problem based on maximally predictive feature sets.
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1. An article comprising a non-transitory machine-readable storage medium operable to cause one or more machines to result in operations comprising: arranging objects which are realizations of a first variable and a second variable into a current clustering to aid in solving a problem; constructing a shortlist of destination clusters, the shortlist containing a predetermined number, N, of destination clusters for a current object, each destination cluster associated with a score, each destination cluster in the shortlist having an associated score that is greater than an associated score of each destination cluster not in the shortlist; picking randomly a destination cluster from said shortlist of destination clusters; determining if said picked destination cluster is acceptable according to a probabilistic acceptance criteria at a current temperature, T, the current temperature representing an iteration of temperature out of a plurality of iterations of temperature from a first temperature to a second temperature; replacing said current clustering with said picked destination clustering, if said picked destination clustering is acceptable; repeating, at each iteration of temperature, the picking, the determining, and the replacing until no acceptable destination clusters from said shortlist of destination clusters remain; establishing said current clustering of objects as an output clustering, wherein said output clustering has a high confidence level of having a maximum of mutual information between said variables for predicting relationships between said variables; and outputting said output clustering for display to a user for use in solving said problem based on maximally predictive feature sets. 2. The article of claim 1 , wherein a simulated annealing process is approximated by setting the predetermined number, N, to infinity.
| 0.857447 |
9,230,540 | 15 | 16 |
15. An apparatus comprising: at least one processor; and at least one storage medium having encoded thereon processor-executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method of processing results of a recognition by an automatic speech recognition (ASR) system on an utterance, the results comprising a first recognition result identified by the ASR system as most likely to be a correct recognition result for the utterance, the results further comprising at least one alternative recognition result identified by the ASR system, the method comprising: determining whether the first recognition result includes a member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and whether the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, wherein the first recognition result includes at least one first word or phrase other than the member of the set of words or phrases and each of the at least one alternative recognition result includes at least one second word or phrase other than the at least one other member, the at least one first word or phrase and the at least one second word or phrase being the same or different; and in response to determining that the first recognition result includes the member of the set of words or phrases and that the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, triggering an alert.
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15. An apparatus comprising: at least one processor; and at least one storage medium having encoded thereon processor-executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method of processing results of a recognition by an automatic speech recognition (ASR) system on an utterance, the results comprising a first recognition result identified by the ASR system as most likely to be a correct recognition result for the utterance, the results further comprising at least one alternative recognition result identified by the ASR system, the method comprising: determining whether the first recognition result includes a member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and whether the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, wherein the first recognition result includes at least one first word or phrase other than the member of the set of words or phrases and each of the at least one alternative recognition result includes at least one second word or phrase other than the at least one other member, the at least one first word or phrase and the at least one second word or phrase being the same or different; and in response to determining that the first recognition result includes the member of the set of words or phrases and that the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, triggering an alert. 16. The apparatus of claim 15 , wherein: the at least one alternative recognition result comprises a second recognition result; the member of the set is a first member of the set; the at least one other member of the set associated with the member comprises a second member of the set; and the determining whether the first recognition result includes a member of the set and whether the at least one alternative recognition result includes any of the at least one other member comprises determining whether the ASR system recognized a segment of the speech input as the first member for the first recognition result and as the second member of the set for the second recognition result.
| 0.5 |
8,934,278 | 7 | 22 |
7. A hybrid ternary content addressable memory (TCAM), comprising: a first TCAM stage configured to compare a first portion of a search word to a first portion of a stored word; and a second TCAM stage configured to compare a second portion of the search word to a second portion of the stored word when the first portion of the search word matches the first portion of the stored word, the first portion of the search word being different than the second portion of the search word, and the first TCAM stage being configured as a first type TCAM and the second TCAM stage being configured as a second type TCAM, the first type TCAM being different than the second type TCAM.
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7. A hybrid ternary content addressable memory (TCAM), comprising: a first TCAM stage configured to compare a first portion of a search word to a first portion of a stored word; and a second TCAM stage configured to compare a second portion of the search word to a second portion of the stored word when the first portion of the search word matches the first portion of the stored word, the first portion of the search word being different than the second portion of the search word, and the first TCAM stage being configured as a first type TCAM and the second TCAM stage being configured as a second type TCAM, the first type TCAM being different than the second type TCAM. 22. The TCAM of claim 7 , wherein the first TCAM stage is configured to consume more power evaluating comparisons as matches than evaluating comparisons as mismatches, and wherein the second TCAM stage is configured to consume more power evaluating comparisons as mismatches than evaluating comparisons as matches.
| 0.899872 |
8,855,997 | 13 | 14 |
13. The method of claim 12 , wherein the plurality of tokens each correspond to a word of the first sentence.
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13. The method of claim 12 , wherein the plurality of tokens each correspond to a word of the first sentence. 14. The computing device of claim 13 , wherein the first numerical value is calculated using an equation having a form:
P ( a,b,c,d,e,f , . . . )= P ( a ) P ( b|a ) P ( c|a,b ) P ( d|a,b,c ) P ( e|a,b,c,d ) P ( f|a,b,c,d,e )= P ( a ) P ( b|a ) P ( c|a,b ) P ( d|b,c ) P ( e|c,d ) P ( f|d,e ), wherein terms having the form P(a) correspond to a uni-gram probability, terms having the form P(b|a) correspond to a bi-gram probability, and terms having the form P(c|a, b) correspond to a tri-gram probability.
| 0.611792 |
9,697,648 | 8 | 13 |
8. A method of implementing text functions in augmented reality, the method comprising: detecting, at a user device, a selection gesture performed by a user of the user device, the user device displaying a field of view to a user of the user device, and the selection gesture defining a selection area in the field of view; capturing an image of the selection area; performing a text operation on text identified in the image; and presenting, via the user device, an indication of the text operation to the user, wherein performing the text operation comprises: identifying a portion from the text identified in the image; and copying the portion from the text identified in the image to a memory buffer, the memory buffer used for copy and paste operations; and wherein presenting the indication of the text operation comprises: presenting a notification to the user.
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8. A method of implementing text functions in augmented reality, the method comprising: detecting, at a user device, a selection gesture performed by a user of the user device, the user device displaying a field of view to a user of the user device, and the selection gesture defining a selection area in the field of view; capturing an image of the selection area; performing a text operation on text identified in the image; and presenting, via the user device, an indication of the text operation to the user, wherein performing the text operation comprises: identifying a portion from the text identified in the image; and copying the portion from the text identified in the image to a memory buffer, the memory buffer used for copy and paste operations; and wherein presenting the indication of the text operation comprises: presenting a notification to the user. 13. The method of claim 8 , wherein the selection gesture comprises a point-and-loop motion, and the selection area comprises a character block.
| 0.827751 |
4,118,788 | 2 | 3 |
2. The invention defined in claim 1 wherein said combining means is arranged to logically OR said binary words together on a bit-by-bit basis.
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2. The invention defined in claim 1 wherein said combining means is arranged to logically OR said binary words together on a bit-by-bit basis. 3. The invention defined in claim 2 wherein said mapping means includes a hashing circuit adapted to convert an input word having a variable length to an output word having a predetermined length.
| 0.5 |
9,411,563 | 1 | 9 |
1. A method for automatic computer translation of input code including constraints to a computer executable imperative output program representation, the method comprising: providing one or more computer processors with an input source program, wherein the input source program is expressed in a programming language that provides for imperative specifications and also provides for declarative specification of constraints, and wherein the input source program includes one or more declaratively specified constraints in accordance with the programming language; translating, using the one or more computer processors, the input source program to the computer executable imperative output program representation, including: during compilation-time, automatically generating code comprising constraint representations based at least in part on the one or more declaratively specified constraints, including automatically generating code comprising one or more corresponding constraint reactor code objects to register input change notification upon instantiation, the one or more corresponding constraint reactor code objects being included in the computer executable imperative output program presentation and having imperative procedures that enforce the declaratively specified constraints; and for at least some of program data members of the input source program, automatically generating corresponding notification code to provide change notification and to accommodate registration for input change notification by constraint representations; and providing the computer executable imperative output program representation as an output.
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1. A method for automatic computer translation of input code including constraints to a computer executable imperative output program representation, the method comprising: providing one or more computer processors with an input source program, wherein the input source program is expressed in a programming language that provides for imperative specifications and also provides for declarative specification of constraints, and wherein the input source program includes one or more declaratively specified constraints in accordance with the programming language; translating, using the one or more computer processors, the input source program to the computer executable imperative output program representation, including: during compilation-time, automatically generating code comprising constraint representations based at least in part on the one or more declaratively specified constraints, including automatically generating code comprising one or more corresponding constraint reactor code objects to register input change notification upon instantiation, the one or more corresponding constraint reactor code objects being included in the computer executable imperative output program presentation and having imperative procedures that enforce the declaratively specified constraints; and for at least some of program data members of the input source program, automatically generating corresponding notification code to provide change notification and to accommodate registration for input change notification by constraint representations; and providing the computer executable imperative output program representation as an output. 9. The method of claim 1 , wherein at least one of the constraints is a representation-specific constraint relating to constraint data members having different representations.
| 0.815514 |
9,953,027 | 15 | 16 |
15. A computer program product for generating paraphrases, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to: receive a plurality of bidirectional disjunctive logical forms, wherein the plurality of bidirectional disjunctive logical forms includes two directional disjunctions of differences between a first logical form of a first sentence and a second logical form of a second sentence; realize the plurality of bidirectional disjunctive logical forms to generate a first plurality of paraphrases of the first and second sentences; determine a first score for a third paraphrase of the first paraphrases; determine a second score for a fourth paraphrase of the first paraphrases, wherein the first score is higher than the second score based in part on a first syntactic variation between the third paraphrase and the first sentence and the second sentence being greater than a second syntactic variation between the fourth paraphrase and the first sentence and the second sentence; and prune the first paraphrases to generate second paraphrases, wherein the first paraphrases are pruned based on the first score and the second score such that the third paraphrase is included in the second paraphrases and the fourth paraphrase is not included in the second paraphrases based on the first score being higher than the second score.
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15. A computer program product for generating paraphrases, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to: receive a plurality of bidirectional disjunctive logical forms, wherein the plurality of bidirectional disjunctive logical forms includes two directional disjunctions of differences between a first logical form of a first sentence and a second logical form of a second sentence; realize the plurality of bidirectional disjunctive logical forms to generate a first plurality of paraphrases of the first and second sentences; determine a first score for a third paraphrase of the first paraphrases; determine a second score for a fourth paraphrase of the first paraphrases, wherein the first score is higher than the second score based in part on a first syntactic variation between the third paraphrase and the first sentence and the second sentence being greater than a second syntactic variation between the fourth paraphrase and the first sentence and the second sentence; and prune the first paraphrases to generate second paraphrases, wherein the first paraphrases are pruned based on the first score and the second score such that the third paraphrase is included in the second paraphrases and the fourth paraphrase is not included in the second paraphrases based on the first score being higher than the second score. 16. The computer program product of claim 15 , wherein the differences include a first word that is an alternative to a second word and has a similar meaning to the second word, and wherein the two directional disjunctions include the first word combined with the second word.
| 0.766102 |
9,401,993 | 15 | 16 |
15. The computer-implemented method of claim 1 , wherein the received caller's language preference comprises more than one language.
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15. The computer-implemented method of claim 1 , wherein the received caller's language preference comprises more than one language. 16. The computer-implemented method of claim 15 , wherein providing the IVR menu tree comprises providing a first portion of the IVR menu tree in a first language and providing a second portion of the IVR menu tree in a second language.
| 0.5 |
6,101,461 | 3 | 5 |
3. A command inputting method used when inputting characters using software for Kana (Japanese character)-to-Chinese character conversion comprising the steps of: receiving a string comprising a plurality of characters through a keyboard; retrieving first Chinese character information or second Chinese character information corresponding to the character string by looking up the string in a Chinese character dictionary in which the first Chinese character information, comprising at least one Chinese character correlated to a character string, and the second Chinese character information, comprising a command and at least one Chinese character correlated to a character string, are previously stored; displaying the retrieved first Chinese character information or second Chinese character information as candidates for conversion in a list; receiving input for selecting a desired Chinese character or a command from the first Chinese character information or second Chinese character information displayed in a list; determining which of a Chinese character or a command has been selected or not according to a result of selection in said selecting step; replacing, when it is determined in said determining step that a Chinese character has been selected, the string with at least one corresponding Chinese character and displaying the at least one Chinese character; and executing the corresponding command when it is determined in said determining step that a command has been selected.
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3. A command inputting method used when inputting characters using software for Kana (Japanese character)-to-Chinese character conversion comprising the steps of: receiving a string comprising a plurality of characters through a keyboard; retrieving first Chinese character information or second Chinese character information corresponding to the character string by looking up the string in a Chinese character dictionary in which the first Chinese character information, comprising at least one Chinese character correlated to a character string, and the second Chinese character information, comprising a command and at least one Chinese character correlated to a character string, are previously stored; displaying the retrieved first Chinese character information or second Chinese character information as candidates for conversion in a list; receiving input for selecting a desired Chinese character or a command from the first Chinese character information or second Chinese character information displayed in a list; determining which of a Chinese character or a command has been selected or not according to a result of selection in said selecting step; replacing, when it is determined in said determining step that a Chinese character has been selected, the string with at least one corresponding Chinese character and displaying the at least one Chinese character; and executing the corresponding command when it is determined in said determining step that a command has been selected. 5. A command inputting method used when inputting characters using software for Kana-to-Chinese character conversion according to claim 3 further comprising a generating step of registering a command in the first Chinese character information in said Chinese character dictionary and generating second Chinese character information.
| 0.646055 |
8,055,608 | 1 | 2 |
1. A method, performed by computing hardware and programmable memory, for determining whether a first pinnacle concept is referenced by a first unit of natural language discourse, comprising: parsing the first unit of natural language discourse into a first parse structure that represents each sub-unit, of the first unit of natural language discourse, by a node; adding at least one concept-value pair, each of which indicates a reference to a same non-Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a first linguistic feature from a first set of linguistic features and the first set of linguistic features is approximately complete with respect to the non-Quantifier concept; adding at least one concept-value pair, each of which indicates a reference to a same Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a second linguistic feature from a second set of linguistic features and the second set of linguistic features is approximately complete with respect to the Quantifier concept; propagating the at least one concept-value pair for the Quantifier concept; identifying a first node of the first parse structure that has at least one concept-value pair for the non-Quantifier concept and at least one concept-value pair for the Quantifier concept; determining a first value to be scaled from the least one concept-value pair for the non-Quantifier concept; determining a first scaling value from the least one concept-value pair for the Quantifier concept; scaling the first value to be scaled with the first scaling value to produce a first scaled value; and propagating the at least one concept-value pair for the non-Quantifier concept.
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1. A method, performed by computing hardware and programmable memory, for determining whether a first pinnacle concept is referenced by a first unit of natural language discourse, comprising: parsing the first unit of natural language discourse into a first parse structure that represents each sub-unit, of the first unit of natural language discourse, by a node; adding at least one concept-value pair, each of which indicates a reference to a same non-Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a first linguistic feature from a first set of linguistic features and the first set of linguistic features is approximately complete with respect to the non-Quantifier concept; adding at least one concept-value pair, each of which indicates a reference to a same Quantifier concept, to at least one node of the first parse structure, wherein each reference is determined by identifying an occurrence of a second linguistic feature from a second set of linguistic features and the second set of linguistic features is approximately complete with respect to the Quantifier concept; propagating the at least one concept-value pair for the Quantifier concept; identifying a first node of the first parse structure that has at least one concept-value pair for the non-Quantifier concept and at least one concept-value pair for the Quantifier concept; determining a first value to be scaled from the least one concept-value pair for the non-Quantifier concept; determining a first scaling value from the least one concept-value pair for the Quantifier concept; scaling the first value to be scaled with the first scaling value to produce a first scaled value; and propagating the at least one concept-value pair for the non-Quantifier concept. 2. The method of claim 1 , wherein a sufficient approximation to completeness, for the first set of linguistic features, is determined empirically.
| 0.880098 |
5,587,903 | 1 | 6 |
1. A method for translating a sentence entered by a user into machine recognizable thought patterns, said method comprising: receiving the sentence entered by the user; translating the user's sentence to a universal language; parsing the translated sentence; deriving propositions from the parsed translated sentence of the user; sequentially storing the derived propositions into a knowledge database; and, generating a set of peripheral database linkages for the sets of derived propositions representing the user's sentence, wherein each peripheral database linkage includes a peripheral database representing a function of speech selectively linked to one or more of the other peripheral databases and the knowledge database.
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1. A method for translating a sentence entered by a user into machine recognizable thought patterns, said method comprising: receiving the sentence entered by the user; translating the user's sentence to a universal language; parsing the translated sentence; deriving propositions from the parsed translated sentence of the user; sequentially storing the derived propositions into a knowledge database; and, generating a set of peripheral database linkages for the sets of derived propositions representing the user's sentence, wherein each peripheral database linkage includes a peripheral database representing a function of speech selectively linked to one or more of the other peripheral databases and the knowledge database. 6. A method as claimed in claim 1, further comprising the steps of storing in an object database the identification of a pair of propositions, wherein a first proposition of the pair of propositions includes an object noun used as a subject noun in a second proposition of the pair of propositions.
| 0.765723 |
9,928,232 | 1 | 2 |
1. A method for generating a word candidate to assist a user providing an input to a computing device, comprising: receiving, at the computing device, the input containing a plurality of words, wherein the computing device performs the operations of: determining a conditional count; determining an unconditional count; determining an adjustment factor fora pair of words of the plurality of words based on the unconditional count and the conditional count; generating a data structure defining a plurality of word clusters, individual word clusters of the plurality of word clusters include at least one word of the plurality of words; reconstructing the adjustment factor of the pair of words based on a number of common clusters between individual words of the pair of words; determining a candidate probability associated with the word candidate based, at least in part, on the reconstructed adjustment factor, wherein the word candidate is selected from individual words associated with the plurality of word clusters; generating an output containing the word candidate based, at least in part, on the candidate probability; and displaying the word candidate on a display screen of the computing device.
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1. A method for generating a word candidate to assist a user providing an input to a computing device, comprising: receiving, at the computing device, the input containing a plurality of words, wherein the computing device performs the operations of: determining a conditional count; determining an unconditional count; determining an adjustment factor fora pair of words of the plurality of words based on the unconditional count and the conditional count; generating a data structure defining a plurality of word clusters, individual word clusters of the plurality of word clusters include at least one word of the plurality of words; reconstructing the adjustment factor of the pair of words based on a number of common clusters between individual words of the pair of words; determining a candidate probability associated with the word candidate based, at least in part, on the reconstructed adjustment factor, wherein the word candidate is selected from individual words associated with the plurality of word clusters; generating an output containing the word candidate based, at least in part, on the candidate probability; and displaying the word candidate on a display screen of the computing device. 2. The method of claim 1 , further comprising: obtaining an input indicating a word; and reconstructing a freshness value associated with one or more word clusters containing the word, the modification to the freshness value indicating that the one or more word clusters containing the word are more recent than other word clusters of the plurality of word clusters.
| 0.741525 |
9,569,504 | 15 | 16 |
15. The system of claim 14 , wherein using the first value or the second value to modify a quality score that is associated with the particular document comprises: associating the first value or the second value with a particular group of documents associated with the particular document.
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15. The system of claim 14 , wherein using the first value or the second value to modify a quality score that is associated with the particular document comprises: associating the first value or the second value with a particular group of documents associated with the particular document. 16. The system of claim 15 , wherein the particular group of documents and the particular document are associated with a same site.
| 0.5 |
5,471,560 | 1 | 3 |
1. A method for eliciting procedural knowledge from an expert for constructing an expert system said method being executable on a computer having an associated display device which results in the generation and display, in order, to the expert of a representation of an organized procedural information structure having properly ordered nodes, each of said nodes defining a goal, each said goal a parent goal to either a set of daughter goals which when completed effectuate said parent goal, or alternatively, a set of procedures for effectuating said parent goal, wherein each said procedure consists of instructions and questions to be put to said users in order to lead said user to achieve said goals, said method comprising the following steps wherein the requesting of said knowledge from said experts and his responses thereto are via said display device: A. requesting said expert to generally categorize said procedural knowledge to define a current reference goal which is initially a root goal which a user would want to achieve; B. requesting said expert to specify in a preferred order all goals which are daughters of the current reference goal, said daughter goals to be achieved before achieving their parent thereof, i.e., the current reference goal, which preferred order will determine the order to which said user may be displayed any of said goals or nodes, and also requesting said expert to specify the conditional relationships, if any, between any daughter goals and the current reference goal, each of said conditional relationships determining whether particular procedures will be displayed to the user, and each of said conditional relationships being designated by the expert as relative to information already made available to the expert system by said expert or by a user in response to procedures at run time, and in the absence of any said daughter goals proceeding to step D; C. designating on said display means and in accordance with said preferred order the new current reference goal and returning to step B; D. requesting said expert to specify procedures and to complete said current reference goal; E. designating on said display means the parent goal of said current reference goal as the current reference goal and, if there is at least a remaining one of said goals branching therefrom, then designating the next one of said remaining one of said goals in accordance with said preferred order as the current reference goal and returning to step B; F. stopping if said current reference goal is said root goal but otherwise returning to step E.
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1. A method for eliciting procedural knowledge from an expert for constructing an expert system said method being executable on a computer having an associated display device which results in the generation and display, in order, to the expert of a representation of an organized procedural information structure having properly ordered nodes, each of said nodes defining a goal, each said goal a parent goal to either a set of daughter goals which when completed effectuate said parent goal, or alternatively, a set of procedures for effectuating said parent goal, wherein each said procedure consists of instructions and questions to be put to said users in order to lead said user to achieve said goals, said method comprising the following steps wherein the requesting of said knowledge from said experts and his responses thereto are via said display device: A. requesting said expert to generally categorize said procedural knowledge to define a current reference goal which is initially a root goal which a user would want to achieve; B. requesting said expert to specify in a preferred order all goals which are daughters of the current reference goal, said daughter goals to be achieved before achieving their parent thereof, i.e., the current reference goal, which preferred order will determine the order to which said user may be displayed any of said goals or nodes, and also requesting said expert to specify the conditional relationships, if any, between any daughter goals and the current reference goal, each of said conditional relationships determining whether particular procedures will be displayed to the user, and each of said conditional relationships being designated by the expert as relative to information already made available to the expert system by said expert or by a user in response to procedures at run time, and in the absence of any said daughter goals proceeding to step D; C. designating on said display means and in accordance with said preferred order the new current reference goal and returning to step B; D. requesting said expert to specify procedures and to complete said current reference goal; E. designating on said display means the parent goal of said current reference goal as the current reference goal and, if there is at least a remaining one of said goals branching therefrom, then designating the next one of said remaining one of said goals in accordance with said preferred order as the current reference goal and returning to step B; F. stopping if said current reference goal is said root goal but otherwise returning to step E. 3. A method according to claim 1 wherein in said step D involves giving or getting information to or from the end user in a predetermined order as specified in said step B thereof.
| 0.632653 |
9,130,882 | 3 | 4 |
3. The computer-implemented method of claim 2 , comprising determining content of the particular web page based on at least one context value of the plurality of context values associated with the request.
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3. The computer-implemented method of claim 2 , comprising determining content of the particular web page based on at least one context value of the plurality of context values associated with the request. 4. The computer-implemented method of claim 3 , comprising determining the content of the particular web page at least in part by determining a display order of items in the particular web page based on the at least one context value.
| 0.5 |
8,972,873 | 2 | 3 |
2. The device of claim 1 wherein the instructions further instruct the processor to instantiate a widget assembly application, the widget assembly application having drop down menu displays identifying widget content or widget template type for selection by a user of the widget assembly application.
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2. The device of claim 1 wherein the instructions further instruct the processor to instantiate a widget assembly application, the widget assembly application having drop down menu displays identifying widget content or widget template type for selection by a user of the widget assembly application. 3. The device of claim 2 wherein the widget assembly application includes a widget preview display or wherein the widget environment is specific to one or more of the following: an operating system, a browser platform, a client-based application, a server-based application, a mash-up canvas, or a device.
| 0.5 |
6,018,708 | 11 | 12 |
11. A speech recognition system as defined in claim 1, comprising a plurality of standard text lexicons.
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11. A speech recognition system as defined in claim 1, comprising a plurality of standard text lexicons. 12. A speech recognition system as defined in claim 11, comprising selection means for selecting one of said plurality of standard text lexicons for use as a source by said insertion unit in inserting at least one orthography from the selected one of said plurality of standard text lexicons into said list.
| 0.5 |
7,644,062 | 11 | 17 |
11. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause to perform: transforming a base query to generate a transformed query; wherein the base query includes a union between each base branch of a plurality of base branches; wherein each of two or more base branches of said plurality of base branches joins a set of tables; wherein the sets of tables of the two or more base branches of the plurality of base branches include a common table set shared by all the sets of tables, said common table set including a common table; wherein each of the two or more base branches of the plurality of base branches include a respective set of tables that does not include said common table set; wherein the step of transforming the base query includes replacing the plurality of base branches with a first group branch that joins the common table and an inline view, the inline view comprising a union between a plurality of respective branches, wherein the plurality of respective branches includes, for each base branch of said plurality of base branches, a FROM list that: references the respective set of tables, and does not reference the common table.
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11. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause to perform: transforming a base query to generate a transformed query; wherein the base query includes a union between each base branch of a plurality of base branches; wherein each of two or more base branches of said plurality of base branches joins a set of tables; wherein the sets of tables of the two or more base branches of the plurality of base branches include a common table set shared by all the sets of tables, said common table set including a common table; wherein each of the two or more base branches of the plurality of base branches include a respective set of tables that does not include said common table set; wherein the step of transforming the base query includes replacing the plurality of base branches with a first group branch that joins the common table and an inline view, the inline view comprising a union between a plurality of respective branches, wherein the plurality of respective branches includes, for each base branch of said plurality of base branches, a FROM list that: references the respective set of tables, and does not reference the common table. 17. The computer-readable storage medium of claim 11 , wherein: the base query includes a union between a set of base branches that include said plurality of base branches and a second plurality of base branches; each base branch of said second plurality of base branches joins a set of tables; the sets of tables of the second plurality of base branches includes a second common table; and the step of transforming the base query includes replacing the second plurality of base branches with a second group branch that joins the second common table and second inline view.
| 0.5 |
9,354,709 | 12 | 20 |
12. A method comprising: determining an identity of a user of the device; receiving a first rotation signal representing a first rotation of the device in a first direction about a first axis of the device; comparing the first rotation to a first threshold, wherein the first threshold is based on the identity; determining completion of a first stage of a tilt gesture based at least in part on the comparing of the first rotation to the first threshold; receiving a second rotation signal representing a second rotation of the device in a second direction about the first axis, the second direction being opposite the first direction; comparing the second rotation to a second threshold, wherein the first threshold is based on the identity; and determining completion of the tilt gesture based at least in part on the comparing of the second rotation to the second threshold.
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12. A method comprising: determining an identity of a user of the device; receiving a first rotation signal representing a first rotation of the device in a first direction about a first axis of the device; comparing the first rotation to a first threshold, wherein the first threshold is based on the identity; determining completion of a first stage of a tilt gesture based at least in part on the comparing of the first rotation to the first threshold; receiving a second rotation signal representing a second rotation of the device in a second direction about the first axis, the second direction being opposite the first direction; comparing the second rotation to a second threshold, wherein the first threshold is based on the identity; and determining completion of the tilt gesture based at least in part on the comparing of the second rotation to the second threshold. 20. The method of claim 12 , wherein the first rotation occurs at a first time and the second rotation occurs at a second time, the second time being after the first time.
| 0.765753 |
9,838,259 | 9 | 13 |
9. A non-transitory computer readable medium having stored thereon instructions managing client defined response requirements in a domain name system query comprising machine executable code which when executed by at least one processor, causes the processor to: determine when a DNS request to resolve a hostname comprises a domain name with a value indicating a type of internet protocol version; truncate the internet protocol version value from the DNS request when the domain name and the internet protocol version value is present and prior to querying at least one of a plurality of servers for an internet protocol address associated with the DNS request; receive the internet protocol address from the at least one of a plurality of servers; determine when a format of the received internet protocol address conforms to one or more policies; and perform one or more actions based on the determination of the conformance of the received internet protocol address.
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9. A non-transitory computer readable medium having stored thereon instructions managing client defined response requirements in a domain name system query comprising machine executable code which when executed by at least one processor, causes the processor to: determine when a DNS request to resolve a hostname comprises a domain name with a value indicating a type of internet protocol version; truncate the internet protocol version value from the DNS request when the domain name and the internet protocol version value is present and prior to querying at least one of a plurality of servers for an internet protocol address associated with the DNS request; receive the internet protocol address from the at least one of a plurality of servers; determine when a format of the received internet protocol address conforms to one or more policies; and perform one or more actions based on the determination of the conformance of the received internet protocol address. 13. The medium as set forth in claim 9 wherein the determining if the format of the received internet protocol address further comprises provide the received internet protocol address to the querying client computing device without taking any of the one or more actions when the format of the received internet protocol address is determined to be conforming to the one or more policies.
| 0.614542 |
9,632,985 | 38 | 40 |
38. The method of claim 28 , wherein generating a digital specification comprises generating instructions, which when executed by the execution environment, causes the electronic reading device to present a manipulable image object.
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38. The method of claim 28 , wherein generating a digital specification comprises generating instructions, which when executed by the execution environment, causes the electronic reading device to present a manipulable image object. 40. The method of claim 38 , wherein generating a digital specification comprises generating instructions, which when executed by the execution environment, causes the electronic reading device to allow a user to zoom a manipulable image object.
| 0.651989 |
7,725,418 | 2 | 3 |
2. The method of claim 1 , wherein the step of receiving data further comprises receiving said data from multiple users or from multiple locations.
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2. The method of claim 1 , wherein the step of receiving data further comprises receiving said data from multiple users or from multiple locations. 3. The method of claim 2 , wherein said distributed capture technique comprises the step of prompting a plurality of users to supply one or more words in response to a query.
| 0.5 |
7,603,349 | 12 | 17 |
12. The computer-readable storage medium of claim 11 , wherein the at least a portion of content is selectable by the user.
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12. The computer-readable storage medium of claim 11 , wherein the at least a portion of content is selectable by the user. 17. The computer-readable medium of claim 12 , further comprising code which, when executed by one or more processors at the client, causes the client to, in response to the user selecting the at least a portion of content, generate the context vector to send to the first server.
| 0.608939 |
8,386,912 | 10 | 21 |
10. The method of claim 1 further comprising determining a predefined set of preferences; and storing the versions of the documents in accordance with the determined preferences.
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10. The method of claim 1 further comprising determining a predefined set of preferences; and storing the versions of the documents in accordance with the determined preferences. 21. The method of claim 10 wherein the set of preferences includes a preference for compressing a document.
| 0.774262 |
7,631,278 | 1 | 2 |
1. A computer system for focus navigation of a user interface, comprising: a computing processor; a discrete, directional input device, the discrete, directional input device comprising an input device other than a mouse; and one or more computer-readable media storing computer executable components comprising: a directional focus navigation engine for changing an input focus from a current user interface object in the user interface, the input focus being changed in response to receiving a single, discrete, directional input from the discrete, directional input device; a target candidate selector operably coupled to the directional focus navigation engine for selecting target candidates that are in a traversal direction indicated by the single, discrete, directional input, the target candidates being selected from among one or more user interface objects for receiving the input focus, and the target candidate selector operating to: define a selection region including at least an edge of the current user interface object in the direction of the single, discrete directional input through a parallel edge of a display area; define a baseline region within the selection region and which is a subset of the selection region; and select target candidates that overlap the selection region in the direction of the single, discrete, directional input and only when an edge opposite to the direction of the single, discrete, directional input overlaps the selection region; and a target candidate scorer operably coupled to the directional focus navigation engine for scoring the target candidates selected for receiving the input focus, whereby the scoring of each target candidate is used to select a user interface object to receive input focus in response to the single, discrete, directional input, and wherein scoring the target candidates includes: for all selected target candidates that at least partially overlap the baseline region, scoring them according to their perpendicular distance from an edge of the current user interface object, in a direction parallel to the direction of the single, discrete, directional input; and for all selected target candidates that do not overlap the baseline region, scoring them according to their radial distance from a point on a line partially defining one edge of the baseline region.
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1. A computer system for focus navigation of a user interface, comprising: a computing processor; a discrete, directional input device, the discrete, directional input device comprising an input device other than a mouse; and one or more computer-readable media storing computer executable components comprising: a directional focus navigation engine for changing an input focus from a current user interface object in the user interface, the input focus being changed in response to receiving a single, discrete, directional input from the discrete, directional input device; a target candidate selector operably coupled to the directional focus navigation engine for selecting target candidates that are in a traversal direction indicated by the single, discrete, directional input, the target candidates being selected from among one or more user interface objects for receiving the input focus, and the target candidate selector operating to: define a selection region including at least an edge of the current user interface object in the direction of the single, discrete directional input through a parallel edge of a display area; define a baseline region within the selection region and which is a subset of the selection region; and select target candidates that overlap the selection region in the direction of the single, discrete, directional input and only when an edge opposite to the direction of the single, discrete, directional input overlaps the selection region; and a target candidate scorer operably coupled to the directional focus navigation engine for scoring the target candidates selected for receiving the input focus, whereby the scoring of each target candidate is used to select a user interface object to receive input focus in response to the single, discrete, directional input, and wherein scoring the target candidates includes: for all selected target candidates that at least partially overlap the baseline region, scoring them according to their perpendicular distance from an edge of the current user interface object, in a direction parallel to the direction of the single, discrete, directional input; and for all selected target candidates that do not overlap the baseline region, scoring them according to their radial distance from a point on a line partially defining one edge of the baseline region. 2. The system of claim 1 further comprising an application operably coupled to the directional focus navigation engine, the application having one or more user interface objects receiving a single, discrete directional input from the discrete, directional input device.
| 0.5 |
8,131,538 | 1 | 12 |
1. A phoneme decoding system, comprising: a non-transitory medium; one or more sentences disposed on the medium, each sentence comprising one or more words, each of the words comprising at least one letter string representative of at least one of a single-source phoneme, a silent phoneme, and a multi-source phoneme; and a symbol key defining a unique mnemonic pictogram for every multi-source phoneme of the system; wherein at least one word comprises a multi-source phoneme letter string with a unique pictogram positioned thereabove or therebelow that represents the phoneme for the given usage of the underlying letter string in the word and in the sentence, and that is the only pictogram for all letter strings associated with said phoneme; all of the letter strings disposed on said medium form all or part of said one or more words disposed on said medium; and all of the pictograms are positioned above or below the letter strings they represent.
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1. A phoneme decoding system, comprising: a non-transitory medium; one or more sentences disposed on the medium, each sentence comprising one or more words, each of the words comprising at least one letter string representative of at least one of a single-source phoneme, a silent phoneme, and a multi-source phoneme; and a symbol key defining a unique mnemonic pictogram for every multi-source phoneme of the system; wherein at least one word comprises a multi-source phoneme letter string with a unique pictogram positioned thereabove or therebelow that represents the phoneme for the given usage of the underlying letter string in the word and in the sentence, and that is the only pictogram for all letter strings associated with said phoneme; all of the letter strings disposed on said medium form all or part of said one or more words disposed on said medium; and all of the pictograms are positioned above or below the letter strings they represent. 12. The phoneme decoding system of claim 1 , comprising computer executable code for, in accordance with an alteration to the symbol key, automatically redefining the exclusive relationships and altering the disposition of the pictograms accordingly.
| 0.5 |
8,380,651 | 60 | 61 |
60. The system of claim 23 in which generating the function includes converting each of a plurality of rule cases in the rule specification to a logical expression to form a plurality of logical expressions, and compiling the plurality of logical expressions into computer-executable code.
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60. The system of claim 23 in which generating the function includes converting each of a plurality of rule cases in the rule specification to a logical expression to form a plurality of logical expressions, and compiling the plurality of logical expressions into computer-executable code. 61. The system of claim 60 in which compiling the plurality of logical expressions includes one or more of combining expressions, optimizing individual expressions, and optimizing groups of expressions.
| 0.5 |
8,515,762 | 6 | 8 |
6. A system for utilizing a plurality of recognizers to process an utterance based on a markup language document, the system comprising a client computing device, the client computing device comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative: to receive the markup language document; to receive the utterance; to select at least one of the plurality of recognizers for returning a results set for the utterance based on markup language in the markup language document, the at least one of the plurality of recognizers for returning the results set for the utterance being selected based on markup language in the markup language document, the selection based on the markup language comprising: recognizing a grammar used in the utterance; parsing the markup language document for at least one markup language tag identifying at least one of the plurality of recognizers for returning the results set for the utterance based on the grammar; and selecting, by an event handler, the at least one of the plurality of recognizers identified by the at least one markup language tag, the selected at least one of the plurality of recognizers comprising a local recognizer embedded on a client computing device, when the grammar includes data stored on the client computing device, the selected at least one of the plurality of recognizers comprising a network recognizer on a network server, when the grammar includes data which is retrieved via a query from the network server to a remote search engine; to receive the results set from the selected at least one of the plurality of recognizers in a format determined by a processing method specified in the markup language document; and to execute an event in response to receiving the results set, the event comprising determining actions in response to receiving the results set, the actions being based on at least an assigned confidence score indicating an accuracy of a speech recognition for the utterance, the actions comprising ignoring the results set when the results sets comprises unprocessed results for the utterance and the confidence score is below a predetermined threshold, the actions further comprising preventing the results set from being displayed to a user.
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6. A system for utilizing a plurality of recognizers to process an utterance based on a markup language document, the system comprising a client computing device, the client computing device comprising: a memory for storing executable program code; and a processor, functionally coupled to the memory, the processor being responsive to computer-executable instructions contained in the program code and operative: to receive the markup language document; to receive the utterance; to select at least one of the plurality of recognizers for returning a results set for the utterance based on markup language in the markup language document, the at least one of the plurality of recognizers for returning the results set for the utterance being selected based on markup language in the markup language document, the selection based on the markup language comprising: recognizing a grammar used in the utterance; parsing the markup language document for at least one markup language tag identifying at least one of the plurality of recognizers for returning the results set for the utterance based on the grammar; and selecting, by an event handler, the at least one of the plurality of recognizers identified by the at least one markup language tag, the selected at least one of the plurality of recognizers comprising a local recognizer embedded on a client computing device, when the grammar includes data stored on the client computing device, the selected at least one of the plurality of recognizers comprising a network recognizer on a network server, when the grammar includes data which is retrieved via a query from the network server to a remote search engine; to receive the results set from the selected at least one of the plurality of recognizers in a format determined by a processing method specified in the markup language document; and to execute an event in response to receiving the results set, the event comprising determining actions in response to receiving the results set, the actions being based on at least an assigned confidence score indicating an accuracy of a speech recognition for the utterance, the actions comprising ignoring the results set when the results sets comprises unprocessed results for the utterance and the confidence score is below a predetermined threshold, the actions further comprising preventing the results set from being displayed to a user. 8. The system of claim 6 , wherein the markup language document comprises at least one of a locally stored markup language document on the client computing device and a remotely stored markup language document on the network server.
| 0.793594 |
8,364,686 | 1 | 7 |
1. A method performed by one or more computer devices, the method comprising: generating, by at least one of the one or more computer devices, a fingerprint for an input document, where generating the fingerprint includes: sampling the input document to obtain a plurality of sampled blocks, generating a set of checksum values from the plurality of sampled blocks, where each checksum value, in the set of checksum values, corresponds to an address of a respective one of a plurality of bits of the fingerprint, and generating the fingerprint by flipping a particular bit, of the plurality of bits of the fingerprint, a quantity of times based on a quantity of checksum values, in the set of checksum values, that corresponds to the address of the particular bit; and storing, by at least one of the one or more computing devices, the fingerprint in a memory.
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1. A method performed by one or more computer devices, the method comprising: generating, by at least one of the one or more computer devices, a fingerprint for an input document, where generating the fingerprint includes: sampling the input document to obtain a plurality of sampled blocks, generating a set of checksum values from the plurality of sampled blocks, where each checksum value, in the set of checksum values, corresponds to an address of a respective one of a plurality of bits of the fingerprint, and generating the fingerprint by flipping a particular bit, of the plurality of bits of the fingerprint, a quantity of times based on a quantity of checksum values, in the set of checksum values, that corresponds to the address of the particular bit; and storing, by at least one of the one or more computing devices, the fingerprint in a memory. 7. The method of claim 1 , further comprising: reducing a length of a checksum value, in the set of checksum values, to a particular length, where the checksum value, of the particular length, corresponds to an address of one of the plurality of bits of the fingerprint based on the checksum value matching the address of the one of the plurality of bits of the fingerprint.
| 0.5 |
7,702,601 | 1 | 4 |
1. A method, executed on a computing device, for using an expert system to recommend a customized solution for a customer, the method comprising: providing in the expert system a set of scenarios each of which includes default facts and is associated with a detailed rule base that when applied in isolation to the default facts fully determines a prototype solution; selecting a particular scenario from the set of scenarios based at least on user input, wherein the selecting comprises: posing at least one specific question to a user who is a representative of the customer and obtaining supplied facts from answers to the questions; in a context of the supplied facts, inferring facts from parseable input supplied to the expert system; determining a subset of the scenarios from the inferred facts and the supplied facts; and enabling the user to select a particular scenario from the subset of the scenarios; generating a customized solution by applying the detailed rule base associated with the particular scenario to a set of candidate facts that comprises the inferred facts, the supplied facts, and assumed facts, where the assumed facts are any default facts of the particular scenario that complement and do not conflict with the inferred facts and the supplied facts iteratively refining the customized solution; and presenting the user with the customized solution and with a log of the parseable input supplied to the expert system; and indicating to the user which of the candidate facts are most significant in determining the customized solution.
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1. A method, executed on a computing device, for using an expert system to recommend a customized solution for a customer, the method comprising: providing in the expert system a set of scenarios each of which includes default facts and is associated with a detailed rule base that when applied in isolation to the default facts fully determines a prototype solution; selecting a particular scenario from the set of scenarios based at least on user input, wherein the selecting comprises: posing at least one specific question to a user who is a representative of the customer and obtaining supplied facts from answers to the questions; in a context of the supplied facts, inferring facts from parseable input supplied to the expert system; determining a subset of the scenarios from the inferred facts and the supplied facts; and enabling the user to select a particular scenario from the subset of the scenarios; generating a customized solution by applying the detailed rule base associated with the particular scenario to a set of candidate facts that comprises the inferred facts, the supplied facts, and assumed facts, where the assumed facts are any default facts of the particular scenario that complement and do not conflict with the inferred facts and the supplied facts iteratively refining the customized solution; and presenting the user with the customized solution and with a log of the parseable input supplied to the expert system; and indicating to the user which of the candidate facts are most significant in determining the customized solution. 4. The method of claim 1 , wherein iteratively refining the customized solution comprises: enabling the user to edit the log; updating the inferred facts and the assumed facts of the candidate facts in the context of the supplied facts and the edited log; and refining the customized solution by applying the detailed rule base associated with the particular scenario to the updated candidate facts.
| 0.540323 |
9,141,867 | 8 | 9 |
8. A method comprising: under control of one or more processors configured with executable instructions, identifying a plurality of segments of content in a content item; determining that a segment boundary hint is associated with the content item; adjusting a segment of the plurality of segments based on the segment boundary hint; and presenting the content of the content item based at least in part on the plurality of segments.
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8. A method comprising: under control of one or more processors configured with executable instructions, identifying a plurality of segments of content in a content item; determining that a segment boundary hint is associated with the content item; adjusting a segment of the plurality of segments based on the segment boundary hint; and presenting the content of the content item based at least in part on the plurality of segments. 9. The method as recited in claim 8 , further comprising: determining that the segment boundary hint is associated with the content item; and partially segmenting the content item based at least in part on the segment boundary hint before the identifying the plurality of segments.
| 0.5 |
9,678,950 | 1 | 7 |
1. A method for translating a message sent from a first user in a rich communication service (RCS) to a second user in a non-RCS, the method comprising the steps of: identifying a language of the message received from the first user at a server in the RCS; storing the identified language into a language history table with an entry of the first user; identifying whether a preferred language of the second user is present in the language history table; obtaining the preferred language from the language history table, when the preferred language is present in the language history table; obtaining the preferred language from a language history of the second user and storing the preferred language in the language history table with an entry of the second user, when the preferred language is not present in the language history table; and translating the message into the preferred language at a translator, wherein the language history of the second user is obtained by using at least one of an application programming interface (API) and a network to network interface (NNI).
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1. A method for translating a message sent from a first user in a rich communication service (RCS) to a second user in a non-RCS, the method comprising the steps of: identifying a language of the message received from the first user at a server in the RCS; storing the identified language into a language history table with an entry of the first user; identifying whether a preferred language of the second user is present in the language history table; obtaining the preferred language from the language history table, when the preferred language is present in the language history table; obtaining the preferred language from a language history of the second user and storing the preferred language in the language history table with an entry of the second user, when the preferred language is not present in the language history table; and translating the message into the preferred language at a translator, wherein the language history of the second user is obtained by using at least one of an application programming interface (API) and a network to network interface (NNI). 7. The method, as claimed in claim 1 , wherein the server determines whether the identified language and the preferred language match, sends the message from the server to the second user when the identified language and the preferred language match, sends the message from the server to the translator when the identified language and the preferred language do not match and sends the message, the identified language and the preferred language to the translator.
| 0.5 |
9,846,844 | 1 | 8 |
1. A computer-implemented method of evaluating information confidence based on cognitive behavior indicators of a user, the method comprising: determining, by a processor, a system generated answer to a question in an active learning question and answer system, wherein the system generated answer includes a first answer confidence score for the system generated answer; querying a user for an answer to the question in the active learning question and answer system based on the first answer confidence score; receiving, by the processor, information from the user as an answer to the question in the active learning question and answer system; monitoring, by the processor, the user for one or more cognitive behavior indicators when the user is providing the information, wherein the one or more cognitive behavior indicators comprise one or more biometric measurements of the user at a time the information is provided by the user and measures of an influence of an external stimuli on the user at the time the information is provided by the user; determining, by the processor, a second answer confidence score for the information received from the user based on the one or more biometric measurements of the user and the measures of the influence of an external stimuli on the user; annotating, by the processor, the information with the cognitive behavior indicators, a user profile associated with the user, and the second answer confidence score; and updating the first answer confidence score based at least in part on the second answer confidence score.
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1. A computer-implemented method of evaluating information confidence based on cognitive behavior indicators of a user, the method comprising: determining, by a processor, a system generated answer to a question in an active learning question and answer system, wherein the system generated answer includes a first answer confidence score for the system generated answer; querying a user for an answer to the question in the active learning question and answer system based on the first answer confidence score; receiving, by the processor, information from the user as an answer to the question in the active learning question and answer system; monitoring, by the processor, the user for one or more cognitive behavior indicators when the user is providing the information, wherein the one or more cognitive behavior indicators comprise one or more biometric measurements of the user at a time the information is provided by the user and measures of an influence of an external stimuli on the user at the time the information is provided by the user; determining, by the processor, a second answer confidence score for the information received from the user based on the one or more biometric measurements of the user and the measures of the influence of an external stimuli on the user; annotating, by the processor, the information with the cognitive behavior indicators, a user profile associated with the user, and the second answer confidence score; and updating the first answer confidence score based at least in part on the second answer confidence score. 8. The computer-implemented method of claim 1 , further comprising annotating the information with user characteristics stored in a user profile.
| 0.81738 |
8,407,253 | 2 | 9 |
2. The method of claim 1 , further comprising: eliminating, based on the relation weighted values and a preset restriction condition on semantic relation types, a semantic relation with error from the knowledge graph.
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2. The method of claim 1 , further comprising: eliminating, based on the relation weighted values and a preset restriction condition on semantic relation types, a semantic relation with error from the knowledge graph. 9. The method of claim 2 , wherein the eliminating of the semantic relation with error comprises removing the semantic relation with error from the knowledge graph based on the relation weighted values and entity cardinality of the semantic relation type.
| 0.575 |
7,831,836 | 1 | 9 |
1. One or more computer-readable media usable to determine a password, the computer-readable media comprising instructions, executable by a processor, for: generating words, one after another, the words each having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from a character string for the respective character position, each character string: being stored in memory; comprising a plurality of permissible characters that may be used in the password, the order of the characters in the character string being individually selected for each character position of the word based on a frequency that each character occurs at the respective character position in words in a database, such that the characters in each character string are ordered from most frequent occurrence at the respective character position to least frequent occurrence at the respective character position and each character string begins with a permissible character most frequently used in the words in the database at the respective position and ends with a permissible character least frequently used in the words in the database at the respective position; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined.
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1. One or more computer-readable media usable to determine a password, the computer-readable media comprising instructions, executable by a processor, for: generating words, one after another, the words each having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from a character string for the respective character position, each character string: being stored in memory; comprising a plurality of permissible characters that may be used in the password, the order of the characters in the character string being individually selected for each character position of the word based on a frequency that each character occurs at the respective character position in words in a database, such that the characters in each character string are ordered from most frequent occurrence at the respective character position to least frequent occurrence at the respective character position and each character string begins with a permissible character most frequently used in the words in the database at the respective position and ends with a permissible character least frequently used in the words in the database at the respective position; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. 9. The one or more computer-readable media of claim 1 , wherein the character string for the first position of the words comprises letters and numbers arranged in the order: s, c, p, a, b, t, m, d, r, h, f, g, u, e, l, i, o, n, w, v, k, j, q, y, z, 0, x, 3, 1, 2, 4, 6, 5, 7, 8, 9.
| 0.5 |
8,775,349 | 1 | 7 |
1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions.
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1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions. 7. The method according to claim 1 , which comprises using a dictionary during the analysis which stores similar and/or synonymous descriptors in order to analyze similar and synonymous names.
| 0.825455 |
5,559,926 | 19 | 32 |
19. A method for training a speech recognition system to recognize a user's utterance, comprising the steps of: providing an utterance to the speech recognition system while in a training mode; monitoring a bio-signal derived from the user, said bio-signal being related to autonomic activity; and using said bio-signal to identify said utterance for retraining.
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19. A method for training a speech recognition system to recognize a user's utterance, comprising the steps of: providing an utterance to the speech recognition system while in a training mode; monitoring a bio-signal derived from the user, said bio-signal being related to autonomic activity; and using said bio-signal to identify said utterance for retraining. 32. The method of claim 19, wherein said bio-signal is related to electrical activity.
| 0.751445 |
9,898,255 | 15 | 18 |
15. A computer program product embodied in a non-transitory computer-readable storage medium and comprising instructions for execution by at least one processor, wherein the instructions instruct the at least one processor to: present a user interface (UI) layout of a particular application UI for a first context in a primary display and at least one miniature UI layout of the same particular application UI for a plurality of contexts including the first context in a secondary display area adjacent to the primary display, each UI layout including a plurality of UI elements, at least a portion of the UI elements included in the first context included in the plurality of contexts in the secondary display area; receive from a user, a selection of a particular UI layout from the at least one miniature UI layouts presented in the secondary display area, the particular UI layout associated with a second context different from the first context; present the particular UI layout for the selected second context in the primary display in response to the received selection from the user; identify a modification to at least one UI element in the context presented in the primary display; determine at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area, including the first context, based on the modification of the at least one UI element in the second context in the primary display, wherein the determined at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area is based on a set of responsive UI design rules specific to each of the at least one contexts other than the context presented in the primary display, and wherein the at least one modification includes a first modification to at least one context other than to the context presented in the primary display different than the identified modification to the at least one UI element in the context presented in the primary display; automatically perform the at least one determined modification to the UI layout in at least one of the plural contexts in the secondary display area; and present an updated UI layout of the particular application UI for the context in the primary display and an updated miniature UI layout of the particular application UI for the at least one of the plural contexts in the secondary display area.
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15. A computer program product embodied in a non-transitory computer-readable storage medium and comprising instructions for execution by at least one processor, wherein the instructions instruct the at least one processor to: present a user interface (UI) layout of a particular application UI for a first context in a primary display and at least one miniature UI layout of the same particular application UI for a plurality of contexts including the first context in a secondary display area adjacent to the primary display, each UI layout including a plurality of UI elements, at least a portion of the UI elements included in the first context included in the plurality of contexts in the secondary display area; receive from a user, a selection of a particular UI layout from the at least one miniature UI layouts presented in the secondary display area, the particular UI layout associated with a second context different from the first context; present the particular UI layout for the selected second context in the primary display in response to the received selection from the user; identify a modification to at least one UI element in the context presented in the primary display; determine at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area, including the first context, based on the modification of the at least one UI element in the second context in the primary display, wherein the determined at least one modification to the at least one miniature UI layout in at least one of the contexts in the secondary display area is based on a set of responsive UI design rules specific to each of the at least one contexts other than the context presented in the primary display, and wherein the at least one modification includes a first modification to at least one context other than to the context presented in the primary display different than the identified modification to the at least one UI element in the context presented in the primary display; automatically perform the at least one determined modification to the UI layout in at least one of the plural contexts in the secondary display area; and present an updated UI layout of the particular application UI for the context in the primary display and an updated miniature UI layout of the particular application UI for the at least one of the plural contexts in the secondary display area. 18. The computer program product of claim 15 , wherein the secondary display area comprises a preview area providing a miniature representation of the UI layouts for the plural contexts as compared to the UI layout in the context presented in the primary display.
| 0.5 |
8,549,397 | 7 | 8 |
7. The system as recited in claim 5 , wherein the binary format video content is presented at the predetermined client in a manner that preserves the layout, rendering, UI interaction, and dynamic aspects of the original markup language video content.
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7. The system as recited in claim 5 , wherein the binary format video content is presented at the predetermined client in a manner that preserves the layout, rendering, UI interaction, and dynamic aspects of the original markup language video content. 8. The system as recited in claim 7 , wherein the binary format video content is presented at the predetermined client using a form element, scrolling, navigation, and event handling as recited in the original markup language video content.
| 0.5 |
9,171,180 | 10 | 11 |
10. The system of claim 8 , wherein the digital conversation is a public conversation accessible to other users within the enterprise level information networking system.
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10. The system of claim 8 , wherein the digital conversation is a public conversation accessible to other users within the enterprise level information networking system. 11. The system of claim 10 , wherein the at least one user and the second user are allowed to contribute to the public conversation and the other users are allowed to view the public conversation.
| 0.5 |
8,879,854 | 7 | 10 |
7. An apparatus for recognizing an emotion of an individual using Action Units (AUs), the apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory includes instructions stored therein, that when executed by the processor, cause the processor to: receive an input AU string including one or more AUs that represents a facial expression of the individual; match the input AU string with each of a plurality of AU strings, each of the plurality of AU strings comprising a set of a same number of AUs that are most discriminative of a respective one of a plurality of emotions; identify an AU string from the plurality of AU strings that best matches the input AU string; and output an emotion label corresponding to the best matching AU string that indicates the emotion of the individual.
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7. An apparatus for recognizing an emotion of an individual using Action Units (AUs), the apparatus comprising: a processor; and a memory coupled to the processor, wherein the memory includes instructions stored therein, that when executed by the processor, cause the processor to: receive an input AU string including one or more AUs that represents a facial expression of the individual; match the input AU string with each of a plurality of AU strings, each of the plurality of AU strings comprising a set of a same number of AUs that are most discriminative of a respective one of a plurality of emotions; identify an AU string from the plurality of AU strings that best matches the input AU string; and output an emotion label corresponding to the best matching AU string that indicates the emotion of the individual. 10. The apparatus of claim 7 , wherein the processor: determines a discriminative power for each of a plurality of AUs based on statistical data; selects a set of AUs representing each of a plurality of emotion labels, based on the discriminative power for each of the plurality of AUs; and stores the selected set of AUs associated with each of the plurality of emotion labels as AU strings.
| 0.604839 |
9,454,240 | 1 | 15 |
1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of a gesture detected at a presence-sensitive input device; determining, by the computing device, based at least in part on the indication of the gesture, a spatial model probability associated with one or more keys from the plurality of keys; adjusting, by the computing device, based on at least one characteristic of the gesture, the spatial model probability associated with the one or more keys from the plurality of keys, wherein the at least one characteristic of the gesture includes a speed of a portion of the gesture; determining, by the computing device, based on the adjusted spatial model probability associated with the one or more keys from the plurality of keys, a character string; and responsive to determining that the character string is not included in a lexicon and that the adjusted spatial model probability associated with the one or more keys from the plurality of keys exceeds a probability threshold, outputting, by the computing device and for display, the character string.
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1. A method comprising: outputting, by a computing device and for display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of a gesture detected at a presence-sensitive input device; determining, by the computing device, based at least in part on the indication of the gesture, a spatial model probability associated with one or more keys from the plurality of keys; adjusting, by the computing device, based on at least one characteristic of the gesture, the spatial model probability associated with the one or more keys from the plurality of keys, wherein the at least one characteristic of the gesture includes a speed of a portion of the gesture; determining, by the computing device, based on the adjusted spatial model probability associated with the one or more keys from the plurality of keys, a character string; and responsive to determining that the character string is not included in a lexicon and that the adjusted spatial model probability associated with the one or more keys from the plurality of keys exceeds a probability threshold, outputting, by the computing device and for display, the character string. 15. The method of claim 1 , wherein the presence-sensitive input device comprises a presence-sensitive screen, wherein the character string is output for display at the presence-sensitive screen.
| 0.867527 |
9,898,335 | 3 | 4 |
3. The method of claim 2 , further comprising: prior to determining that every stack in a plurality of stacks is in a blocked state or completed state, identifying expressions for batch evaluation in one or more stacks of the plurality of stacks that is in an unblocked state; transitioning a state of each stack of the plurality of stacks that is in an unblocked state to a blocked state.
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3. The method of claim 2 , further comprising: prior to determining that every stack in a plurality of stacks is in a blocked state or completed state, identifying expressions for batch evaluation in one or more stacks of the plurality of stacks that is in an unblocked state; transitioning a state of each stack of the plurality of stacks that is in an unblocked state to a blocked state. 4. The method of claim 3 , wherein identifying expressions for batch evaluation comprises determining whether the expressions have a particular characteristic that is included in a pre-determined list of characteristics that are associated with expressions that should be batch evaluated.
| 0.5 |
7,783,668 | 18 | 19 |
18. The method of claim 13 , wherein the formally represented knowledge further comprises one or more entity lists wherein each entity list contains a list of one or more entities associated with other entities contained in the entity list, and wherein assigning the index further comprises extracting an entity contained in an entity list from a particular piece of content in the corpus and associating a particular entity list to the particular piece of content.
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18. The method of claim 13 , wherein the formally represented knowledge further comprises one or more entity lists wherein each entity list contains a list of one or more entities associated with other entities contained in the entity list, and wherein assigning the index further comprises extracting an entity contained in an entity list from a particular piece of content in the corpus and associating a particular entity list to the particular piece of content. 19. The method of claim 18 , wherein assigning an index further comprises assigning a particular facet to a particular piece of content when a term in the piece of content is contained in the synsets of the facet.
| 0.5 |
6,073,096 | 19 | 22 |
19. A method of speech recognition comprising the steps of: providing a speaker dependent system for each of a plurality of training speakers; providing an acoustic space for each of the training speakers, each acoustic space being characterized by a set of acoustic features; grouping the speaker dependent systems with the acoustic spaces to build acoustic spaces with common features from all the speaker dependent systems; clustering the grouped acoustic spaces to form cluster systems based on a common acoustic characteristic; selecting from a group of cluster systems, a subset of cluster systems closest to adaptation data from a speaker; transforming the subset of cluster systems to bring the subset of cluster systems closer to the speaker based on the adaptation data to form adapted cluster systems; and combining the adapted cluster systems to create a speaker adapted system for decoding speech from the speaker.
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19. A method of speech recognition comprising the steps of: providing a speaker dependent system for each of a plurality of training speakers; providing an acoustic space for each of the training speakers, each acoustic space being characterized by a set of acoustic features; grouping the speaker dependent systems with the acoustic spaces to build acoustic spaces with common features from all the speaker dependent systems; clustering the grouped acoustic spaces to form cluster systems based on a common acoustic characteristic; selecting from a group of cluster systems, a subset of cluster systems closest to adaptation data from a speaker; transforming the subset of cluster systems to bring the subset of cluster systems closer to the speaker based on the adaptation data to form adapted cluster systems; and combining the adapted cluster systems to create a speaker adapted system for decoding speech from the speaker. 22. The method of speech recognition as recited in claim 19, wherein each cluster system of the group of cluster systems includes a Hidden Markov Model system.
| 0.829032 |
9,282,289 | 1 | 7 |
1. A method for generating a summary document of an online meeting, the method comprising: storing, in computer memory, at least a portion of screen data representing a previously presented portion of an ongoing online meeting; capturing a plurality of screenshots in response to trigger events, each screenshot i) being based at least in part on the stored screen data and ii) being representable as an image thumbnail, wherein capturing each screenshot of the screen data includes associating a timestamp with the screenshot, the timestamp indicating a point in time in the previously presented portion of the meeting; combining the plurality of screenshots, thereby dynamically generating a summary document summarizing the ongoing online meeting, wherein the image thumbnails representing the plurality of screenshots are for facilitating navigating through the summary document while the ongoing online meeting is still ongoing; and signaling for presenting, at a viewer computing device attending the meeting, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to one of the plurality of screenshots in the summary document, wherein the second screen data includes stored screen data from a previously presented portion of the ongoing online meeting, and wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data, wherein signaling for presenting the first screen data corresponding to the currently presented portion of the ongoing online meeting includes presenting live screen and audio data of the ongoing online meeting, and wherein signaling for presenting the second screen data corresponding to the screenshot includes displaying screen data from the previously presented portion of the online meeting corresponding to the point in time in the previously presented portion of the meeting indicated by the timestamp associated with the one of the plurality of screenshots in the summary document.
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1. A method for generating a summary document of an online meeting, the method comprising: storing, in computer memory, at least a portion of screen data representing a previously presented portion of an ongoing online meeting; capturing a plurality of screenshots in response to trigger events, each screenshot i) being based at least in part on the stored screen data and ii) being representable as an image thumbnail, wherein capturing each screenshot of the screen data includes associating a timestamp with the screenshot, the timestamp indicating a point in time in the previously presented portion of the meeting; combining the plurality of screenshots, thereby dynamically generating a summary document summarizing the ongoing online meeting, wherein the image thumbnails representing the plurality of screenshots are for facilitating navigating through the summary document while the ongoing online meeting is still ongoing; and signaling for presenting, at a viewer computing device attending the meeting, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to one of the plurality of screenshots in the summary document, wherein the second screen data includes stored screen data from a previously presented portion of the ongoing online meeting, and wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data, wherein signaling for presenting the first screen data corresponding to the currently presented portion of the ongoing online meeting includes presenting live screen and audio data of the ongoing online meeting, and wherein signaling for presenting the second screen data corresponding to the screenshot includes displaying screen data from the previously presented portion of the online meeting corresponding to the point in time in the previously presented portion of the meeting indicated by the timestamp associated with the one of the plurality of screenshots in the summary document. 7. The method of claim 1 , wherein the summary document is generated by the viewer computing device.
| 0.855072 |
4,695,977 | 4 | 5 |
4. The method of claim 3 further comprises the steps of deactivating said second one of said scripts by said computer system's execution of a fourth one of said scripts; generating a deactivate signal by said computer system after the execution of the step of deactivating said second one of said scripts; storing a signal by said computer system indicating that said second one of said scripts is to be deactivated in another one of said process states; and stopping said computer system from further processing of said deactivate signal by execution of other groups of instructions of said second one of said scripts in response to said deactivate signal thereby inhibiting the deactivation of the execution of said second one of said scripts.
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4. The method of claim 3 further comprises the steps of deactivating said second one of said scripts by said computer system's execution of a fourth one of said scripts; generating a deactivate signal by said computer system after the execution of the step of deactivating said second one of said scripts; storing a signal by said computer system indicating that said second one of said scripts is to be deactivated in another one of said process states; and stopping said computer system from further processing of said deactivate signal by execution of other groups of instructions of said second one of said scripts in response to said deactivate signal thereby inhibiting the deactivation of the execution of said second one of said scripts. 5. The method of claim 4 wherein said step of deactivating the execution of said second one of said scripts further comprises the step of purging said second one of said scripts by said computer system's execution of another group of instructions of said second one of said scripts in response to said stored signal and said process entering said other state.
| 0.5 |
8,918,389 | 10 | 13 |
10. A method for displaying suggested queries for web searching, comprising the operations of: displaying a plurality of search results in a graphical user interface for a search engine; capturing positive feedback and negative feedback as to the plurality of search results from a user; determining a collective aboutness signature for the plurality of search results associated with the positive feedback; determining a collective aboutness signature for the plurality of search results associated with the negative feedback; obtaining a score of similarity to each of the collective aboutness signatures for a representation of each query suggestion in a plurality of query suggestions; separating the scored query suggestions into two or more groups, based at least in part on the similarity scores; displaying one or more query suggestions from one or more groups in a graphical user interface for a search engine, wherein aboutness in each collective aboutness signature depends on a lexicon, wherein each collective aboutness signature is a union or summation of an aboutness signature for each search result in the plurality of search results, and wherein each operation of the method is executed by one or more processors.
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10. A method for displaying suggested queries for web searching, comprising the operations of: displaying a plurality of search results in a graphical user interface for a search engine; capturing positive feedback and negative feedback as to the plurality of search results from a user; determining a collective aboutness signature for the plurality of search results associated with the positive feedback; determining a collective aboutness signature for the plurality of search results associated with the negative feedback; obtaining a score of similarity to each of the collective aboutness signatures for a representation of each query suggestion in a plurality of query suggestions; separating the scored query suggestions into two or more groups, based at least in part on the similarity scores; displaying one or more query suggestions from one or more groups in a graphical user interface for a search engine, wherein aboutness in each collective aboutness signature depends on a lexicon, wherein each collective aboutness signature is a union or summation of an aboutness signature for each search result in the plurality of search results, and wherein each operation of the method is executed by one or more processors. 13. The method of claim 10 , wherein the negative feedback includes skipping a search result in a displayed list of search results.
| 0.5 |
9,886,424 | 9 | 11 |
9. A web application framework system, comprising: a computer system comprising: non-transitory memory; and a context analyzer layer comprising: a request context module configured to be operable at the computer system and receive a web request context; and a context parser module; wherein the context parser module is configured to: be operable at the computer system; receive the web request context, wherein the web request context comprises a coded expression; determine if the coded expression contains a property name of multiple property names; if the coded expression contains the property name of the multiple property names, update the web request context by replacing the coded expression with a value of the property name of the multiple property names; if the coded expression does not contain any property name of the multiple property names, update the web request context by replacing at least a part of the coded expression by at least one of: determining that the coded expression starts with a request parameter attribute, and replacing the at least the part of the coded expression with a value of a parameter name at the context analyzer layer; determining that the coded expression starts with a request cookie attribute and replacing the at least the part of the coded expression with a value of a cookie name at the context analyzer layer; determining that the coded expression starts with a request attribute and replacing the at least the part of the coded expression with a value of an attribute name at the context analyzer layer; or determining that the coded expression starts with a request header attribute and replacing the at least the part of the coded expression with a value of a header name at the context analyzer layer; determine that if a value of the at least the part of the coded expression is null after replacing the at least the part of the coded expression; determine if the value of the at least the part of the coded expression is marked as required; if the value of the at least the part of the coded expression is (1) determined to be null and (2) not marked as required, then ignore the value of the at least the part of the coded expression; if the value of the at least the part of the coded expression is (1) determined to be null and (2) marked as required, then generate a warning in a log based at least in part on the value of the at least the part of the coded expression is null after replacing the at least the part of the coded expression; determine that the coded expression starts with a context attribute, and attempt to identify a context analyzer name class and replace the at least the part of the coded expression with a value of a context key of the context analyzer name class at the context analyzer layer; and determine that the context analyzer name class is not identified or that the value of the context key is not specified, and then throw an invalid configuration exception.
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9. A web application framework system, comprising: a computer system comprising: non-transitory memory; and a context analyzer layer comprising: a request context module configured to be operable at the computer system and receive a web request context; and a context parser module; wherein the context parser module is configured to: be operable at the computer system; receive the web request context, wherein the web request context comprises a coded expression; determine if the coded expression contains a property name of multiple property names; if the coded expression contains the property name of the multiple property names, update the web request context by replacing the coded expression with a value of the property name of the multiple property names; if the coded expression does not contain any property name of the multiple property names, update the web request context by replacing at least a part of the coded expression by at least one of: determining that the coded expression starts with a request parameter attribute, and replacing the at least the part of the coded expression with a value of a parameter name at the context analyzer layer; determining that the coded expression starts with a request cookie attribute and replacing the at least the part of the coded expression with a value of a cookie name at the context analyzer layer; determining that the coded expression starts with a request attribute and replacing the at least the part of the coded expression with a value of an attribute name at the context analyzer layer; or determining that the coded expression starts with a request header attribute and replacing the at least the part of the coded expression with a value of a header name at the context analyzer layer; determine that if a value of the at least the part of the coded expression is null after replacing the at least the part of the coded expression; determine if the value of the at least the part of the coded expression is marked as required; if the value of the at least the part of the coded expression is (1) determined to be null and (2) not marked as required, then ignore the value of the at least the part of the coded expression; if the value of the at least the part of the coded expression is (1) determined to be null and (2) marked as required, then generate a warning in a log based at least in part on the value of the at least the part of the coded expression is null after replacing the at least the part of the coded expression; determine that the coded expression starts with a context attribute, and attempt to identify a context analyzer name class and replace the at least the part of the coded expression with a value of a context key of the context analyzer name class at the context analyzer layer; and determine that the context analyzer name class is not identified or that the value of the context key is not specified, and then throw an invalid configuration exception. 11. The web application framework system of claim 9 , further comprising a data collector layer comprising: a data analyzer module configured to: be operable at the computer system; process a requested decision; parse a web page definition containing a plurality of modules in a tree structure; extract at least one of data sources or references from the plurality of modules in the tree structure; skip parsing of one or more sub-tree modules of the plurality of modules in the tree structure if the one or more sub-tree modules comprise a data analyzer representing a decision function; invoke a call to the at least one of the data sources or the references of the plurality of modules in the tree structure for the data analyzer of the one or more sub-tree modules; execute the data analyzer of the one or more sub-tree modules after receiving data from the at least one of the data sources or the references; and make a decision for the one or more sub-tree modules; and a data collector module configured to be operable at the computer system.
| 0.5 |
8,756,236 | 10 | 18 |
10. A computer-implemented system for indexing documents, comprising: an index that includes references to each of a plurality of previously indexed documents; and one or more computing devices operable to: receive a first set of one or more topics relating to a text of a document and a weight for each topic in the first set, where the weight represents how strongly the topic is associated with the document; and generate a first update to the index by inserting a reference to the document for each of the one or more topics in the first set; receive a second set of one or more topics relating to the text of the document and a weight for each topic in the second set; and generate a second update to the index by inserting the reference to the document for topics in the second set that are not in the first set and removing the reference to the document for topics in the first set that are not in the second set, wherein the second set is generated in response to a triggering event.
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10. A computer-implemented system for indexing documents, comprising: an index that includes references to each of a plurality of previously indexed documents; and one or more computing devices operable to: receive a first set of one or more topics relating to a text of a document and a weight for each topic in the first set, where the weight represents how strongly the topic is associated with the document; and generate a first update to the index by inserting a reference to the document for each of the one or more topics in the first set; receive a second set of one or more topics relating to the text of the document and a weight for each topic in the second set; and generate a second update to the index by inserting the reference to the document for topics in the second set that are not in the first set and removing the reference to the document for topics in the first set that are not in the second set, wherein the second set is generated in response to a triggering event. 18. The system of claim 10 , wherein the index contains references to a predetermined set of related documents.
| 0.609155 |
7,721,200 | 16 | 20 |
16. A storage medium containing instructions for generating of a customized document about a product, which when executed by a processor, causes the processor to perform operations comprising: a) providing a user with a document manager input interface, the input interface including a definition manager module, a electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module, wherein the document definition comprises at least one of (i) organization of sections of the customized document, (ii) maintenance codes specific to the product, and (iii) page formatting information; c) creating the customized document from the document definition using the definition manager module; d) storing the customized document in a relational database; e) editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) establishing effectivity associations, using the effectivity interface module, for a given component of the product, and thereby defining a manner in which a change to the given component is propagated throughout the customized document; i) in response to the user making the change to the given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, (iv) the customized data provided by the electronic library manager module, and (v) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document.
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16. A storage medium containing instructions for generating of a customized document about a product, which when executed by a processor, causes the processor to perform operations comprising: a) providing a user with a document manager input interface, the input interface including a definition manager module, a electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module, wherein the document definition comprises at least one of (i) organization of sections of the customized document, (ii) maintenance codes specific to the product, and (iii) page formatting information; c) creating the customized document from the document definition using the definition manager module; d) storing the customized document in a relational database; e) editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) establishing effectivity associations, using the effectivity interface module, for a given component of the product, and thereby defining a manner in which a change to the given component is propagated throughout the customized document; i) in response to the user making the change to the given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, (iv) the customized data provided by the electronic library manager module, and (v) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document. 20. The storage medium of claim 16 , further comprising instructions which when executed by a processor, causes the processor to perform operations comprising: translating the customized document from an extensible markup language file to an output format selected using an extensible style sheet language transform.
| 0.5 |
8,606,728 | 17 | 23 |
17. A computer-readable storage device having stored thereon instructions, which, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: calculating one or more types of suggestion scores for each of a plurality of training examples, wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples.
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17. A computer-readable storage device having stored thereon instructions, which, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: calculating one or more types of suggestion scores for each of a plurality of training examples, wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples. 23. The storage device of claim 17 , wherein the operations further comprise: obtaining a user-defined utility for each of one or more predicted categories, wherein utility is a measure of importance for the category, wherein calculating one or more types of suggestion scores for a particular training example comprises calculating each of the one or more types of suggestion scores weighted by the user-defined utility of a predicted category of the particular training example.
| 0.600666 |
9,350,863 | 15 | 16 |
15. The method of claim 11 , wherein, after said anchor is built, said chat data is categorized into said team/department names using said filters.
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15. The method of claim 11 , wherein, after said anchor is built, said chat data is categorized into said team/department names using said filters. 16. The method of claim 15 , wherein specific filters are applied for voice categorization.
| 0.872905 |
9,864,356 | 1 | 9 |
1. Identification method of nonlinear parameter varying models (NPV), the method based on nonlinear model identification system, said system comprises four parts including input module, identified object, output module, and system identification module, the input module applies the excitation signal to the identified object, the output signal of the identified object is sent to the system identification module by using the output module, the operating conditions of the identified object are described with one or more operating point variables, said method comprises the following steps: Step (1), local nonlinear model tests: the term “local” refers to that the value of the operating point variable remains constant; firstly, set the value of the operating point variable; on the premise of that the operating point variable remains constant, set the values of the manipulating variables in their working intervals; then, traverse all the values of the manipulating variables (MV) in their working intervals by using the input module, and obtain the steady-state output data with respect to one controlled variable (CV) from the output module; if the number of the manipulating variables (MV) is more than one, when traversing all the values of one manipulating variable in its working interval by using the input module, other manipulating variables remain constant; finally, the excitation signal is applied to all the manipulating variables (MV) of the identified object by using the input module, and obtain the dynamic output data with respect to said controlled variable (CV) from the output module; Step (2), identify local nonlinear models: the system identification module automatically carries out the local nonlinear model identification based on the steady output data and dynamic output data obtained in step (1) by using the nonlinear identification method to estimate the parameters of the local nonlinear models, and then obtains the local nonlinear models at the set value of the operating point variable in step (1); Step (3), repeat the above step (1) and step (2) for automatically completing the identification of all required local nonlinear models with respect to all set operating point variable values, and obtain all required local nonlinear models of all set operating point variable values; said all set operating point variable values include the upper bound and the lower bound of the operating range of the operating point variable; and then check whether the local nonlinear models can meet the required accuracy threshold; if it is not satisfied, adjust the values of the manipulating variables in their working intervals and/or adjust the excitation signal, then return to step (1); otherwise, continue; Step (4), operating point variable transition tests: said operating point variable transition tests are to transit the identified object from one operating point variable value to another operating point variable value by using the input module; in the operating point variable transition tests, change the operating point variable value, and apply the excitation signal to all the manipulating variables (MV) of the identified object by using the input module, and then obtain the operating point variable transition dynamic output data with respect to said controlled variable (CV) from the output module; Step (5), identify the multi-input single-output nonlinear parameter varying model: all required local nonlinear models are utilized to convert the local nonlinear models to the multi-input single-output nonlinear parameter varying model (NPV) by using the interpolation philosophy, the weighting functions used in the interpolation philosophy are determined by the parameter estimation method based on the total testing data which include the local nonlinear model test data and the operating point variable transition test data; Step (6), check whether the multi-input single-output nonlinear parameter varying model (NPV) obtained in Step (5) can meet the required accuracy threshold; if it is not satisfied, increase the number of the local nonlinear models and turn to step (3), or increase the operating point variable transition test data and turn to step (4); if satisfied, continue; Step (7), repeat the above steps from step (1) to step (6) for identifying all the multi-input single-output nonlinear parameter varying models (NPV) with respect to all the controlled variables (CV), and then complete the identification of the multi-input multi-output nonlinear parameter varying models (NPV) by putting together all the multi-input single-output nonlinear parameter varying models (NPV) with respect to all the controlled variables (CV).
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1. Identification method of nonlinear parameter varying models (NPV), the method based on nonlinear model identification system, said system comprises four parts including input module, identified object, output module, and system identification module, the input module applies the excitation signal to the identified object, the output signal of the identified object is sent to the system identification module by using the output module, the operating conditions of the identified object are described with one or more operating point variables, said method comprises the following steps: Step (1), local nonlinear model tests: the term “local” refers to that the value of the operating point variable remains constant; firstly, set the value of the operating point variable; on the premise of that the operating point variable remains constant, set the values of the manipulating variables in their working intervals; then, traverse all the values of the manipulating variables (MV) in their working intervals by using the input module, and obtain the steady-state output data with respect to one controlled variable (CV) from the output module; if the number of the manipulating variables (MV) is more than one, when traversing all the values of one manipulating variable in its working interval by using the input module, other manipulating variables remain constant; finally, the excitation signal is applied to all the manipulating variables (MV) of the identified object by using the input module, and obtain the dynamic output data with respect to said controlled variable (CV) from the output module; Step (2), identify local nonlinear models: the system identification module automatically carries out the local nonlinear model identification based on the steady output data and dynamic output data obtained in step (1) by using the nonlinear identification method to estimate the parameters of the local nonlinear models, and then obtains the local nonlinear models at the set value of the operating point variable in step (1); Step (3), repeat the above step (1) and step (2) for automatically completing the identification of all required local nonlinear models with respect to all set operating point variable values, and obtain all required local nonlinear models of all set operating point variable values; said all set operating point variable values include the upper bound and the lower bound of the operating range of the operating point variable; and then check whether the local nonlinear models can meet the required accuracy threshold; if it is not satisfied, adjust the values of the manipulating variables in their working intervals and/or adjust the excitation signal, then return to step (1); otherwise, continue; Step (4), operating point variable transition tests: said operating point variable transition tests are to transit the identified object from one operating point variable value to another operating point variable value by using the input module; in the operating point variable transition tests, change the operating point variable value, and apply the excitation signal to all the manipulating variables (MV) of the identified object by using the input module, and then obtain the operating point variable transition dynamic output data with respect to said controlled variable (CV) from the output module; Step (5), identify the multi-input single-output nonlinear parameter varying model: all required local nonlinear models are utilized to convert the local nonlinear models to the multi-input single-output nonlinear parameter varying model (NPV) by using the interpolation philosophy, the weighting functions used in the interpolation philosophy are determined by the parameter estimation method based on the total testing data which include the local nonlinear model test data and the operating point variable transition test data; Step (6), check whether the multi-input single-output nonlinear parameter varying model (NPV) obtained in Step (5) can meet the required accuracy threshold; if it is not satisfied, increase the number of the local nonlinear models and turn to step (3), or increase the operating point variable transition test data and turn to step (4); if satisfied, continue; Step (7), repeat the above steps from step (1) to step (6) for identifying all the multi-input single-output nonlinear parameter varying models (NPV) with respect to all the controlled variables (CV), and then complete the identification of the multi-input multi-output nonlinear parameter varying models (NPV) by putting together all the multi-input single-output nonlinear parameter varying models (NPV) with respect to all the controlled variables (CV). 9. Identification method of nonlinear parameter varying models (NPV) as claimed in claim 1 wherein the parameter estimation method of the weighting functions in said step (5) adopts the least square method or the maximum likelihood estimation method.
| 0.615385 |
7,949,539 | 16 | 23 |
16. A method of generating a document migration report identifying those documents in a group of documents that may be candidates for use in at least one of a plurality of migration categories, comprising the steps of: providing migration data metrics, said migration data metrics including a range of characteristic document data for each of a plurality of characteristics for at least one of a plurality of migration categories; for each document in a group of documents, assigning characteristic document data for each of said plurality of characteristics; comparing characteristic document data for each document in said group of documents to said migration data metrics to determine which of those documents having characteristic document data that fall within a range specified by said migration data metrics for said one of the plurality of migration categories; saving the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories; and generating a migration report listing the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories.
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16. A method of generating a document migration report identifying those documents in a group of documents that may be candidates for use in at least one of a plurality of migration categories, comprising the steps of: providing migration data metrics, said migration data metrics including a range of characteristic document data for each of a plurality of characteristics for at least one of a plurality of migration categories; for each document in a group of documents, assigning characteristic document data for each of said plurality of characteristics; comparing characteristic document data for each document in said group of documents to said migration data metrics to determine which of those documents having characteristic document data that fall within a range specified by said migration data metrics for said one of the plurality of migration categories; saving the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories; and generating a migration report listing the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories. 23. The method as claimed in claim 16 , wherein said generating step comprises generating said migration report as a display on a computer display screen.
| 0.576923 |
9,916,063 | 2 | 8 |
2. The method according to claim 1 , further comprising: moving the text box down from the original position as the pull-down gesture lengthens.
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2. The method according to claim 1 , further comprising: moving the text box down from the original position as the pull-down gesture lengthens. 8. The method according to claim 2 , wherein: the position of the user prompt icon is in an upper portion of the display area of the text box.
| 0.706612 |
7,689,580 | 14 | 19 |
14. The method of claim 1 comprising: providing a user interface on a display screen, wherein the display screen comprises a search area and a results area, wherein the query having a first format and not understandable by the search engine is entered and displayed in the search area; receiving the query having the second format to perform a search, wherein performing the search includes utilizing the index store containing information associated with the first and second transactional application; displaying in the results area a list of results after the search is performed; when a result is associated with the first transactional application, displaying the results for the first transactional application and a first associated action button; when a result is associated with the second transactional application, displaying the results for the second transactional application and a second associated action button; invoking a third transactional application associated with the first transactional application when the first associated action button is selected; and invoking a fourth transactional application associated with the second transactional application when the second associated action button is selected.
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14. The method of claim 1 comprising: providing a user interface on a display screen, wherein the display screen comprises a search area and a results area, wherein the query having a first format and not understandable by the search engine is entered and displayed in the search area; receiving the query having the second format to perform a search, wherein performing the search includes utilizing the index store containing information associated with the first and second transactional application; displaying in the results area a list of results after the search is performed; when a result is associated with the first transactional application, displaying the results for the first transactional application and a first associated action button; when a result is associated with the second transactional application, displaying the results for the second transactional application and a second associated action button; invoking a third transactional application associated with the first transactional application when the first associated action button is selected; and invoking a fourth transactional application associated with the second transactional application when the second associated action button is selected. 19. The method of claim 14 wherein the query having a first format is entered using pull-down or pop-up menus.
| 0.692737 |
8,606,010 | 6 | 12 |
6. The method of claim 4 , wherein in step (3), the construction of said character classifier block including the following steps: (i) constructing a separate weak classifier for each image feature characteristic statistic, wherein each weak classifier classifies an image region as a printable-character region or as a non-character regions based on the computed results of its corresponding image feature characteristic statistic; (ii) constructing said level 1 classifier sub-block by combining a first plurality of weak classifiers corresponding to image feature characteristic statistics in categories not higher than in a first category in said sequence of increasing computational cost; (iii) constructing said level 2 classifier sub-block by combining a second plurality of weak classifier corresponding to image features characteristic statistics in categories not higher than a second category in said sequence of increasing computational cost, said second category being higher than said first category in said sequence of increasing computational cost; (iv) constructing said level 3 classifier sub-block by combining a third plurality of weak classifier corresponding to image features characteristic statistics in categories not higher than a third category in said sequence of increasing computational cost, said third category being higher than said second category in said sequence of increasing computational cost.
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6. The method of claim 4 , wherein in step (3), the construction of said character classifier block including the following steps: (i) constructing a separate weak classifier for each image feature characteristic statistic, wherein each weak classifier classifies an image region as a printable-character region or as a non-character regions based on the computed results of its corresponding image feature characteristic statistic; (ii) constructing said level 1 classifier sub-block by combining a first plurality of weak classifiers corresponding to image feature characteristic statistics in categories not higher than in a first category in said sequence of increasing computational cost; (iii) constructing said level 2 classifier sub-block by combining a second plurality of weak classifier corresponding to image features characteristic statistics in categories not higher than a second category in said sequence of increasing computational cost, said second category being higher than said first category in said sequence of increasing computational cost; (iv) constructing said level 3 classifier sub-block by combining a third plurality of weak classifier corresponding to image features characteristic statistics in categories not higher than a third category in said sequence of increasing computational cost, said third category being higher than said second category in said sequence of increasing computational cost. 12. The method of claim 6 , wherein in each of steps (ii), (iii) and (iv), IF in the construction of each of the level 1, level 2 and level 3 classifier sub-blocks: the number of weak classifiers used in its construction is designated F, each weak classifier h f in its construction corresponds to a respective image feature characteristic statistic f where f=1 to F, and the total number of training sample pairs is designated P, THEN the constructing of each of the level 1, level 2 and level 3 classifier sub-blocks includes the following steps: (I) Computing an initial weight w p for each of the P training sample pairs as follows, w p = area of training sample air p sum of the areas of all P training sample pairs (II) initializing an iteration counter t=0; (III) computing classification error ε t, f within current iteration t for each weak classifier h f for the all P training sample pairs, where w t,p denotes the weight of training sample pair p within current iteration t. ɛ t , f = ∑ p = 1 P w t , p ( h f ( x p ) - y p ) where a classification of printable-character region is assigned a value of 1 and a classification of non-character region is assigned a value of −1, h f (x p ) indicates that weak classifier h f assigned a classification label x p to training sample pair p so that h f f (x p ) is the computed classification value of training p sample p computed using weak classifier h f constructed for feature f, and y p is the true classification value of training sample p; (IV) letting ĥ t,f denote the best weak classifier among all F weak classifiers h 1 to h F within current iteration t, ĥ t,f is defined as the weak classifier h f (x p ) that rendered the smallest classification error ε t,f in step (III) as follows
ĥ t,f =the [h f ( x p )]that rendered the minimum(ε t,f ); (V) updating the weights w t,p for each of the P training sample pairs as follows w t , p = w t , p × β t ( 1 - e p ) e p = { 0 , h ^ t , f ( x p ) = y p 1 , otherwise where β t = ɛ t 1 - ɛ t , and ε t is the average of all ɛ t , f ∴ ɛ t = ∑ f = 1 F ɛ t , f F ; (VI) skipping to step (IX) if t=F; (VII) incrementing t by 1; (VIII) normalizing updated sample weights as follows w t , p = w [ ( t - 1 ) , p ] ∑ p = 1 P w [ ( t - 1 ) , p ] and returning to step (III); (IX) defining the current classifier ĥ(x) by combing select weak classifiers from among the best weak classifiers ĥ t, f of the past F iterations as follows: h ^ ( x ) = { + 1 , ∑ t = 1 F α t h ^ t ( x ) ≥ ( 1 2 ) ∑ t = 1 F α t , α t = log ( 1 β t ) - 1 , otherwise .
| 0.5 |
10,068,490 | 10 | 11 |
10. The method of claim 7 , wherein determining the cognitive state of the student includes determining the student's cognitive load or fatigue.
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10. The method of claim 7 , wherein determining the cognitive state of the student includes determining the student's cognitive load or fatigue. 11. The method of claim 10 , wherein determining the cognitive state of the student includes determining the student's fatigue.
| 0.5 |
8,041,729 | 1 | 10 |
1. A computer-implemented method comprising: one or more computing devices associating a category to a set of nodes of a graph by: the one or more computing devices determining a first node that represents a first term that is in the category; the one or more computing devices locating a second node associated with the first node based at least in part on a first degree of cross-reference between the first node and the second node, the second node representing a second term, wherein the first degree of cross-reference is based at least in part on a frequency by which the first term appears in a set of documents with the second term; the one or more computing devices locating a third node associated with the second node based at least in part on a second degree of cross-reference between the second node and the third node, the third node representing a third term, wherein the second degree of cross-reference is based at least in part on a frequency by which the second term appears in a set of documents with the third term; based at least in part on both (a) the first degree of cross-reference between the first node and the second node, and (b) the second degree of cross-reference between the second node and the third node, determining whether or not the third term is in the category; in response to determining that the third term is in the category, storing information that indicates the third term is in the category.
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1. A computer-implemented method comprising: one or more computing devices associating a category to a set of nodes of a graph by: the one or more computing devices determining a first node that represents a first term that is in the category; the one or more computing devices locating a second node associated with the first node based at least in part on a first degree of cross-reference between the first node and the second node, the second node representing a second term, wherein the first degree of cross-reference is based at least in part on a frequency by which the first term appears in a set of documents with the second term; the one or more computing devices locating a third node associated with the second node based at least in part on a second degree of cross-reference between the second node and the third node, the third node representing a third term, wherein the second degree of cross-reference is based at least in part on a frequency by which the second term appears in a set of documents with the third term; based at least in part on both (a) the first degree of cross-reference between the first node and the second node, and (b) the second degree of cross-reference between the second node and the third node, determining whether or not the third term is in the category; in response to determining that the third term is in the category, storing information that indicates the third term is in the category. 10. The computer-implemented method of claim 1 , wherein the category is associated with a set of related nodes, the method further comprising: determining a set of related terms, each term of the set of related terms associated with a node of the set of related nodes; determining that a query is associated with at least one term of the set of related terms; in response to determining that the query is related to the at least one term of the set of related terms, storing a second information that indicates the query is associated with at least one other term of the set of related terms.
| 0.629838 |
9,652,997 | 5 | 8 |
5. An apparatus for building information on an emotion lexeme comprising: a database including emotion expression lexemes and emotion basis lexemes corresponding to the emotion expression lexemes; an emotion basis lexeme derivation unit retrieving documents on the web on a basis of an original emotion expression lexeme from a sentence which is input, and deriving emotion basis lexemes of the original emotion expression lexeme from sentences of the documents including the original emotion expression lexeme; a new emotion basis lexeme determination unit storing a new emotion basis lexeme determined among the emotion basis lexemes according to a predefined new lexeme criterion, in the database; an emotion expression lexeme derivation unit retrieving a document on the web on a basis of the new emotion basis lexeme and deriving emotion expression lexemes related to the emotion basis lexeme from sentences of the document including the new emotion basis lexeme; and a new emotion expression lexeme determination unit storing a new emotion expression lexeme determined among the emotion expression lexemes according to a predefined new lexeme criterion, in the database, wherein the new emotion expression lexeme determination unit assigns an emotion strength to the new emotion expression lexeme and then stores the emotion strength of the new emotion expression lexeme in the database, and wherein the emotion strength is calculated by multiplying an emotion strength value of the new emotion expression lexeme by a sum of weights of a plurality of modifiers.
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5. An apparatus for building information on an emotion lexeme comprising: a database including emotion expression lexemes and emotion basis lexemes corresponding to the emotion expression lexemes; an emotion basis lexeme derivation unit retrieving documents on the web on a basis of an original emotion expression lexeme from a sentence which is input, and deriving emotion basis lexemes of the original emotion expression lexeme from sentences of the documents including the original emotion expression lexeme; a new emotion basis lexeme determination unit storing a new emotion basis lexeme determined among the emotion basis lexemes according to a predefined new lexeme criterion, in the database; an emotion expression lexeme derivation unit retrieving a document on the web on a basis of the new emotion basis lexeme and deriving emotion expression lexemes related to the emotion basis lexeme from sentences of the document including the new emotion basis lexeme; and a new emotion expression lexeme determination unit storing a new emotion expression lexeme determined among the emotion expression lexemes according to a predefined new lexeme criterion, in the database, wherein the new emotion expression lexeme determination unit assigns an emotion strength to the new emotion expression lexeme and then stores the emotion strength of the new emotion expression lexeme in the database, and wherein the emotion strength is calculated by multiplying an emotion strength value of the new emotion expression lexeme by a sum of weights of a plurality of modifiers. 8. The apparatus of claim 5 , wherein each predefined new lexeme criterion comprises at least one of a number of sentences including a lexeme, a number of documents including the lexeme, a popularity of a document containing a sentence including the lexeme, and a recognition of a website containing the sentence including the lexeme.
| 0.727569 |
9,043,367 | 1 | 24 |
1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form.
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1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form. 24. The method as set forth in claim 1 , wherein said establishing a statistical probability involves, for a given alternative candidate term, determining a frequency of occurrence of said given alternative candidate term in a set of sample data.
| 0.532319 |
8,086,643 | 13 | 17 |
13. A non-transitory computer-readable medium embodied with software for translating between schemas, the software when executed using one or more computers is configured to: receive source schema data and target schema data, the source schema data and the target schemas each comprising a taxonomy comprising a hierarchy of classes into which products may be categorized, wherein the target schema data comprises a different taxonomy then the taxonomy of the source schema data, at least the source schema data further comprising a product ontology associated with one or more of the classes, each product ontology comprising one or more product attributes, at least the source schema data further comprising one or more pointers identifying one or more seller databases and associated with at least one source class, the one or more seller databases including product data associated with one or more products categorized in the source class; generate a graphical representation of the taxonomies of the source schema data and the target schema data, the graphical representation allowing at least one of the plurality of buyer computers to graphically associate classes of the source schema data with classes of the target schema data; communicate the graphical representation to at least one of the plurality of buyer computers; associate one or more source classes of the source schema data with one or more target classes of the target schema data; and generate a product ontology for each of the target classes wherein at least one of the target classes is a parent class and the product ontology for each target class is based on the product ontologies of the associated source classes by determining an intersection of the product attributes included in the product ontologies of the target classes.
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13. A non-transitory computer-readable medium embodied with software for translating between schemas, the software when executed using one or more computers is configured to: receive source schema data and target schema data, the source schema data and the target schemas each comprising a taxonomy comprising a hierarchy of classes into which products may be categorized, wherein the target schema data comprises a different taxonomy then the taxonomy of the source schema data, at least the source schema data further comprising a product ontology associated with one or more of the classes, each product ontology comprising one or more product attributes, at least the source schema data further comprising one or more pointers identifying one or more seller databases and associated with at least one source class, the one or more seller databases including product data associated with one or more products categorized in the source class; generate a graphical representation of the taxonomies of the source schema data and the target schema data, the graphical representation allowing at least one of the plurality of buyer computers to graphically associate classes of the source schema data with classes of the target schema data; communicate the graphical representation to at least one of the plurality of buyer computers; associate one or more source classes of the source schema data with one or more target classes of the target schema data; and generate a product ontology for each of the target classes wherein at least one of the target classes is a parent class and the product ontology for each target class is based on the product ontologies of the associated source classes by determining an intersection of the product attributes included in the product ontologies of the target classes. 17. The computer-readable medium of claim 13 , wherein: at least the source schema data further comprises a seller ontology associated with one or more of the classes, each seller ontology comprising one or more attributes associated with one or more sellers of a product; and the software is further configured to generate a seller ontology for each of the target classes based on the seller ontologies of the associated source classes.
| 0.5 |
8,341,081 | 1 | 13 |
1. A computer-implemented method for identifying an on-line bank account utilized for business purposes, the method comprising: a computer receiving or determining a name of an on-line bank account entered by an account holder; the computer parsing the name into a plurality of name segments; the computer applying a first set of rules to each of the plurality of name segments individually, and a second set of rules to groups of multiple name segments; and the computer determining whether the on-line bank account is utilized for business purposes based at least in part upon respective scores generated by applying the first and second sets of rules.
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1. A computer-implemented method for identifying an on-line bank account utilized for business purposes, the method comprising: a computer receiving or determining a name of an on-line bank account entered by an account holder; the computer parsing the name into a plurality of name segments; the computer applying a first set of rules to each of the plurality of name segments individually, and a second set of rules to groups of multiple name segments; and the computer determining whether the on-line bank account is utilized for business purposes based at least in part upon respective scores generated by applying the first and second sets of rules. 13. The method of claim 1 , the first set of rules comprising rule that assigns a score to a name segment based on whether a name segment is included in a business name database.
| 0.85873 |
9,377,948 | 10 | 16 |
10. An information handling device, comprising: a display; an input surface; one or more processors; a memory device storing instructions accessible to the one or more processors, the instructions being executable by the one or more processors to: accept, at the input surface, one or more inputs, the one or more inputs comprising handwriting inputs including a special handwriting input pre-associated with a request for assistance; determine, using the one or more processors, a candidate list of inputs based on the handwriting inputs and the special handwriting input; and provide, using the one or more processors, a display of the candidate list on the display.
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10. An information handling device, comprising: a display; an input surface; one or more processors; a memory device storing instructions accessible to the one or more processors, the instructions being executable by the one or more processors to: accept, at the input surface, one or more inputs, the one or more inputs comprising handwriting inputs including a special handwriting input pre-associated with a request for assistance; determine, using the one or more processors, a candidate list of inputs based on the handwriting inputs and the special handwriting input; and provide, using the one or more processors, a display of the candidate list on the display. 16. The information handling device of claim 10 , wherein the instructions are further executable by the one or more processors to ascertain, using the one or more processors, user input selecting one of the candidate list of inputs; and input, using the one or more processors, a candidate input selected in place of initial handwriting input.
| 0.5 |
7,814,040 | 9 | 10 |
9. The method according to claim 8 , in which the number of concepts, K, is chosen to maximize log ( P ( F , V ) ) - m K 2 log ( MN ) where m K is the number of free parameters needed for a model with K mixture components.
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9. The method according to claim 8 , in which the number of concepts, K, is chosen to maximize log ( P ( F , V ) ) - m K 2 log ( MN ) where m K is the number of free parameters needed for a model with K mixture components. 10. The method according to claim 9 , in which
m K =( K− 1)+ K ( M− 1)+ K ( N− 1)+ L 2 =K ( M+N− 1)+ L 2 −1.
| 0.5 |
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