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10,019,489 | 5 | 6 | 5. A computer-implemented method comprising: under control of a computing device executing specific computer-executable instructions, receiving, from a data capture device, data related to an item in a first configuration and a user; identifying the first configuration of the item; detecting, from the data related to the item in the first configuration and the user, indirect feedback of the user, wherein the indirect feedback is related to the item in the first configuration; identifying a second configuration of the item using the indirect feedback and the first configuration of the item, wherein the first configuration of the item is different than the second configuration of the item; and causing an image of the item in the second configuration to be presented on a display. | 5. A computer-implemented method comprising: under control of a computing device executing specific computer-executable instructions, receiving, from a data capture device, data related to an item in a first configuration and a user; identifying the first configuration of the item; detecting, from the data related to the item in the first configuration and the user, indirect feedback of the user, wherein the indirect feedback is related to the item in the first configuration; identifying a second configuration of the item using the indirect feedback and the first configuration of the item, wherein the first configuration of the item is different than the second configuration of the item; and causing an image of the item in the second configuration to be presented on a display. 6. The computer-implemented method of claim 5 , wherein the data capture device comprises a microphone and the data related to the item comprises audio data representing an utterance of the user. | 0.908793 |
8,438,007 | 29 | 31 | 29. A computer-readable storage device encoded with a computer program product for use in generating a second human language user interface for a software product having a first human language user interface, the product comprising instructions operable to cause data processing apparatus to perform operations comprising: opening a glossary database that includes a plurality of string sets at least some of which include a user interface string in a first human language and a corresponding user interface string in a second human language, wherein a string set comprises user interface strings having the same set identifier, a set identifier comprising context information about a previous use of a user interface string in a user interface of a software product including a name of the software product and an identifier specifying a type of user interface string and each user interface string comprises a string displayed in a user interface of a software product; selecting a user interface string in the first human language user interface; finding, using a processor, a string set in the glossary database having the selected user interface string and a user interface string in the second human language, wherein the user interface strings in the string set were previously used in a software product different from the software product for which the second human language user interface is being generated; and using the user interface string in the second human language in the second human language user interface, wherein finding a string set in the glossary database having the selected user interface string comprises: searching for one or more literal user interface strings in the glossary database that matches the selected user interface string, generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string, and deciding, based on the score, whether or not to select a string set. | 29. A computer-readable storage device encoded with a computer program product for use in generating a second human language user interface for a software product having a first human language user interface, the product comprising instructions operable to cause data processing apparatus to perform operations comprising: opening a glossary database that includes a plurality of string sets at least some of which include a user interface string in a first human language and a corresponding user interface string in a second human language, wherein a string set comprises user interface strings having the same set identifier, a set identifier comprising context information about a previous use of a user interface string in a user interface of a software product including a name of the software product and an identifier specifying a type of user interface string and each user interface string comprises a string displayed in a user interface of a software product; selecting a user interface string in the first human language user interface; finding, using a processor, a string set in the glossary database having the selected user interface string and a user interface string in the second human language, wherein the user interface strings in the string set were previously used in a software product different from the software product for which the second human language user interface is being generated; and using the user interface string in the second human language in the second human language user interface, wherein finding a string set in the glossary database having the selected user interface string comprises: searching for one or more literal user interface strings in the glossary database that matches the selected user interface string, generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string, and deciding, based on the score, whether or not to select a string set. 31. The product encoded on the computer-readable storage device of claim 29 , wherein if a single match is found, selecting a string set that includes the matching user interface string if the score for the matching user interface string equals or exceeds a specified minimum score value and if the score for the matching user interface string is less than the specified minimum score value, then not selecting the string set and delegating to a human translator the translation of the user interface string in the first human language into the second human language. | 0.608966 |
9,411,710 | 1 | 3 | 1. A method for testing a computer application, the method comprising: identifying, by a test server, components of a version of the application, said components including one or more components that are one of new and modified, wherein each of the one or more components corresponds to a keyword; generating, by the test server, a keyword matrix of the identified application components, the keyword matrix having a set of all identified application components as a first dimension and a set of the one or more components that are one of new and modified as a second dimension, wherein the keyword matrix comprises the keywords; performing, by the test server, a search in a test script repository with respect to components listed as at least one of the first and second dimensions, said test script repository including test scripts referencing at least some of the identified components, and determining a result of the search; populating, by the test server, the keyword matrix with test case identification numbers in the search result, the test case identification numbers corresponding to test scripts that refer to the at least some of the identified components of the application; and based on the populated keyword matrix, identifying, by the test server, one or more of (a) gaps in test case coverage for the version of the application, and (b) one or more test cases covering the version of the application. | 1. A method for testing a computer application, the method comprising: identifying, by a test server, components of a version of the application, said components including one or more components that are one of new and modified, wherein each of the one or more components corresponds to a keyword; generating, by the test server, a keyword matrix of the identified application components, the keyword matrix having a set of all identified application components as a first dimension and a set of the one or more components that are one of new and modified as a second dimension, wherein the keyword matrix comprises the keywords; performing, by the test server, a search in a test script repository with respect to components listed as at least one of the first and second dimensions, said test script repository including test scripts referencing at least some of the identified components, and determining a result of the search; populating, by the test server, the keyword matrix with test case identification numbers in the search result, the test case identification numbers corresponding to test scripts that refer to the at least some of the identified components of the application; and based on the populated keyword matrix, identifying, by the test server, one or more of (a) gaps in test case coverage for the version of the application, and (b) one or more test cases covering the version of the application. 3. The method of claim 1 further comprising receiving an input of test cases corresponding to the gaps in test coverage for the version of the application. | 0.799223 |
10,147,104 | 1 | 2 | 1. A method for improved demand forecasting utilizing searched attributes derived from a consumer's browsing activity including icon selection, navigation of a hierarchal structure presented as a website or app, and location, the method comprising: generating a virtual offer for one or more combinations of a category or sub-category, location, and price range; deriving a first portion of searched attributes from data that is received as input upon icon selection at a consumer facing user interface; accessing and pre-populating a second portion of the searched attributes upon receiving global positioning system (GPS) data indicative of a location from a consumer device; implicitly inferring a third portion of the searched attributes as a function of user browsing activity, the user browsing activity being navigation of a hierarchical data structure, the data structure organized by location and hyper-location or category and sub-category; storing, for each of one or more consumers, each of the first portion, the second portion, and third portion of the searched attributes; accessing, for each of one or more consumers, consumer data accessed from a consumer profile of the consumer, wherein the consumer data comprises searched attributes associated with the consumer, wherein each portion of the searched attributes derived from the data received as input upon icon selection is associated with at least one second portion indicative of a GPS location, and wherein each third portion of searched attributes implicitly inferred as a function of user browser activity also is associated with at least one second portion indicative of a GPS location; calculating a probability that a particular consumer would buy a particular offer in a particular time frame for at least a portion of the plurality of consumers and for each of the virtual offers; determining an estimated number of units to be sold for at least a portion of the one or more virtual offers as a function of at least the probability associated with each of the one or more virtual offers; generating promotions, each representative of an offer for sale of an actual product or service from an actual merchant, comprised of attributes configured to be matched to the searched attributes, from among the one or more virtual offers having an estimated number of units to be sold that meets a predetermined threshold; and causing display of a particular page layout on a user interface of a consumer device associated with the consumer, the particular page layout comprised of the promotions matching the searched attributes associated with the consumer and the consumer device, the particular page layout configured as a function of specifications of the consumer device, a detected specific location, and consumer preferences. | 1. A method for improved demand forecasting utilizing searched attributes derived from a consumer's browsing activity including icon selection, navigation of a hierarchal structure presented as a website or app, and location, the method comprising: generating a virtual offer for one or more combinations of a category or sub-category, location, and price range; deriving a first portion of searched attributes from data that is received as input upon icon selection at a consumer facing user interface; accessing and pre-populating a second portion of the searched attributes upon receiving global positioning system (GPS) data indicative of a location from a consumer device; implicitly inferring a third portion of the searched attributes as a function of user browsing activity, the user browsing activity being navigation of a hierarchical data structure, the data structure organized by location and hyper-location or category and sub-category; storing, for each of one or more consumers, each of the first portion, the second portion, and third portion of the searched attributes; accessing, for each of one or more consumers, consumer data accessed from a consumer profile of the consumer, wherein the consumer data comprises searched attributes associated with the consumer, wherein each portion of the searched attributes derived from the data received as input upon icon selection is associated with at least one second portion indicative of a GPS location, and wherein each third portion of searched attributes implicitly inferred as a function of user browser activity also is associated with at least one second portion indicative of a GPS location; calculating a probability that a particular consumer would buy a particular offer in a particular time frame for at least a portion of the plurality of consumers and for each of the virtual offers; determining an estimated number of units to be sold for at least a portion of the one or more virtual offers as a function of at least the probability associated with each of the one or more virtual offers; generating promotions, each representative of an offer for sale of an actual product or service from an actual merchant, comprised of attributes configured to be matched to the searched attributes, from among the one or more virtual offers having an estimated number of units to be sold that meets a predetermined threshold; and causing display of a particular page layout on a user interface of a consumer device associated with the consumer, the particular page layout comprised of the promotions matching the searched attributes associated with the consumer and the consumer device, the particular page layout configured as a function of specifications of the consumer device, a detected specific location, and consumer preferences. 2. The method of claim 1 , further comprising: receiving searched attributes associated with a particular location; adjusting the estimated number of units to be sold for at least a portion of the one or more virtual offers based on the searched attributes associated with the particular location. | 0.791139 |
7,801,912 | 77 | 78 | 77. The computer-accessible memory medium as recited in claim 73 , wherein each of the query nodes is configured to: receive a query request from a coordinator node; access the local query cache on the query node to determine if the query request can be satisfied from the local query cache; if the query request can be satisfied from the local query cache, return at least the entity identifiers from a set of one or more searchable data service objects from the local query cache that satisfy the query request to a client application that initiated the query request in accordance with the web service interface; if the query request cannot be satisfied from the local query cache, forward the query request to one or more of the storage nodes. | 77. The computer-accessible memory medium as recited in claim 73 , wherein each of the query nodes is configured to: receive a query request from a coordinator node; access the local query cache on the query node to determine if the query request can be satisfied from the local query cache; if the query request can be satisfied from the local query cache, return at least the entity identifiers from a set of one or more searchable data service objects from the local query cache that satisfy the query request to a client application that initiated the query request in accordance with the web service interface; if the query request cannot be satisfied from the local query cache, forward the query request to one or more of the storage nodes. 78. The computer-accessible memory medium as recited in claim 77 , wherein each of the one or more storage nodes is configured to: receive a query request from a query node; search a partition of a particular searchable index persistently stored by the storage node to locate a set of one or more searchable data service objects in the searchable index that satisfy the query request; and return at least the entity identifiers from the set of one or more searchable data service objects that satisfy the query request to a client application that initiated the query request in accordance with the web service interface. | 0.87217 |
7,571,485 | 20 | 22 | 20. A computer system for preventing unauthorized network activity, the computer system comprising: a software portion configured to detect an attempt by a computer to communicate with a remote site over a computer network; a software portion configured to query a database containing descriptions of known legitimate sites for an entry describing the remote site, wherein the database has hierarchical entries according to a schema, and a level of the hierarchy describes data gathered by a class of remote sites; a software portion configured to compare a data gathering profile for the site described by the database entry to a request for data made by the remote site; and a software portion configured to determine whether the remote site is to be treated as suspicious based at least on the results of the comparing step. | 20. A computer system for preventing unauthorized network activity, the computer system comprising: a software portion configured to detect an attempt by a computer to communicate with a remote site over a computer network; a software portion configured to query a database containing descriptions of known legitimate sites for an entry describing the remote site, wherein the database has hierarchical entries according to a schema, and a level of the hierarchy describes data gathered by a class of remote sites; a software portion configured to compare a data gathering profile for the site described by the database entry to a request for data made by the remote site; and a software portion configured to determine whether the remote site is to be treated as suspicious based at least on the results of the comparing step. 22. The computer system of claim 20 further comprising: a software portion configured to determine further whether data requested by the remote site complies with a privacy policy; a software portion configured to determine that the remote site is legitimate, responsive at least to determining that data requested by the remote site complies with the privacy policy; and a software portion configured to determine that the remote site is suspicious, responsive at least to determining that data requested by the remote site does not comply with the privacy policy. | 0.628778 |
8,600,930 | 2 | 3 | 2. The information processing device according to claim 1 , wherein each of said plurality of contents contains data for display of an associated one of said plurality of keywords and explanation data corresponding to the associated keyword, and said processing unit causes said output unit to output said data for display of the retrieved keyword and said explanation data of the retrieved keyword. | 2. The information processing device according to claim 1 , wherein each of said plurality of contents contains data for display of an associated one of said plurality of keywords and explanation data corresponding to the associated keyword, and said processing unit causes said output unit to output said data for display of the retrieved keyword and said explanation data of the retrieved keyword. 3. The information processing device according to claim 2 , wherein said data for display contains an expression of one of said plurality of keywords, and said data for display of each of two or more of said plurality of keywords having said expression in common further contains data for distinction specific to each of said two or more of said plurality of keywords. | 0.838879 |
8,840,695 | 1 | 11 | 1. A method of forming a shaped abrasive particle comprising: forming a mixture comprising a ceramic material into a sheet; sectioning at least a portion of the sheet using a mechanical object and forming at least one shaped abrasive particle from the sheet, wherein the at least one shaped abrasive particle comprises a two-dimensional shape as viewed in a plane defined by a length and a width of the shaped abrasive particle selected from the group consisting of polygons, ellipsoids, numerals, Greek alphabet characters, Latin alphabet characters, Russian alphabet characters, complex shapes having a combination of polygonal shapes, and a combination thereof, and wherein the at least one shaped abrasive particle comprises a body, wherein the body is essentially free of a binder. | 1. A method of forming a shaped abrasive particle comprising: forming a mixture comprising a ceramic material into a sheet; sectioning at least a portion of the sheet using a mechanical object and forming at least one shaped abrasive particle from the sheet, wherein the at least one shaped abrasive particle comprises a two-dimensional shape as viewed in a plane defined by a length and a width of the shaped abrasive particle selected from the group consisting of polygons, ellipsoids, numerals, Greek alphabet characters, Latin alphabet characters, Russian alphabet characters, complex shapes having a combination of polygonal shapes, and a combination thereof, and wherein the at least one shaped abrasive particle comprises a body, wherein the body is essentially free of a binder. 11. The method of claim 1 , wherein the mechanical object has a temperature significantly different than a temperature of the sheet. | 0.880651 |
8,848,088 | 17 | 19 | 17. A method, comprising: receiving, from an imaging device of an electronic device, a first image of a target object; analyzing, by one or more processors using an image recognition application, the first image to identify a first feature of the target object; accessing, by one or more of the processors, a model database to identify one or more models of objects that include the first feature; in response to identifying more than one model: identifying, by one or more of the processors, that one of the identified models includes a distinguishing point, determining, by one or more of the processors by analyzing a second image of the target object, that the target object comprises the distinguishing point, wherein determining that the target object comprises the distinguishing point comprises: identifying a location on the target object where the distinguishing point may appear; displaying the target object on a display of the electronic device; when an area that contains the location appears on the display, causing the display to indicate the location by displaying one or more boundary indicators; receiving the second image; and analyzing the second image to determine whether the second image includes the distinguishing point, and in response to determining that the target object comprises the distinguishing point, retrieving one or more document files that correspond to the identified model that contains the distinguishing point. | 17. A method, comprising: receiving, from an imaging device of an electronic device, a first image of a target object; analyzing, by one or more processors using an image recognition application, the first image to identify a first feature of the target object; accessing, by one or more of the processors, a model database to identify one or more models of objects that include the first feature; in response to identifying more than one model: identifying, by one or more of the processors, that one of the identified models includes a distinguishing point, determining, by one or more of the processors by analyzing a second image of the target object, that the target object comprises the distinguishing point, wherein determining that the target object comprises the distinguishing point comprises: identifying a location on the target object where the distinguishing point may appear; displaying the target object on a display of the electronic device; when an area that contains the location appears on the display, causing the display to indicate the location by displaying one or more boundary indicators; receiving the second image; and analyzing the second image to determine whether the second image includes the distinguishing point, and in response to determining that the target object comprises the distinguishing point, retrieving one or more document files that correspond to the identified model that contains the distinguishing point. 19. The method of claim 17 , wherein each model in the database is an appliance model. | 0.945223 |
5,499,108 | 32 | 42 | 32. A document-driven system comprising a document scanner, said scanner, in response to placement of a document by a user, scanning the document and generating image data representing the image of the document, wherein said placement alone is sufficient to initiate said scanning and generating, and a computer, said computer communicating with said document scanner, said computer displaying, in response to said placement, a plurality of user-selectable options for processing said image data. | 32. A document-driven system comprising a document scanner, said scanner, in response to placement of a document by a user, scanning the document and generating image data representing the image of the document, wherein said placement alone is sufficient to initiate said scanning and generating, and a computer, said computer communicating with said document scanner, said computer displaying, in response to said placement, a plurality of user-selectable options for processing said image data. 42. A system according to claim 32 wherein said scanner includes storage for said image data. | 0.908824 |
8,631,071 | 10 | 14 | 10. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to semantically search for available computing resources for a plurality of businesses conducting commerce in different industries, the available computing resources being searched using an industry model repository (IMR) architecture system comprising: (a) a first layer of abstraction comprising business specific model assets, (b) a second layer of abstraction comprising a plurality of topic maps, each of the topic maps comprising a set of topics of capturing characteristics and relationships among the business specific model assets and other topics, associations having a specific association type and association role played by a designated topic, and occurrences defining business specific instances of the business specific model assets, each of the occurrences having an occurrence type that links to a specific one of the topics and an occurrence locator indicating an accessible network location in a federated asset repository where a corresponding specific instance is stored; and (c) a third layer of abstraction comprising service oriented architecture (“SOA”) program services that utilize the topic maps of the second layer to semantically search for the business specific model assets, wherein one or more of the services of the third layer of abstraction and linkages between the topic maps of the second layer of abstraction change over time as indicated by different versions of the industry model repository (IMR) of the second layer, wherein the searching step searches the computing resources based on linkages specific to a particular one of the different versions of the industry model repository (IMR), wherein a plurality of different versions are concurrently active at runtime and are used by different ones of the plurality of different businesses to access the business specific model assets of the first layer using the SOA program services of the third layer; a first computing device executing a first SOA service available for the searching and use at a first time when a first version of the different versions of the industry model repository (IMR) is available to the first computing device and a second SOA available for the searching and use at a second, later time using a second version of the industry model repository but not available for the searching and use at the first time; a second computing device executing the second SOA service at approximately the first time when the first version of the industry model repository is available to the second computing device, the second computing device executing the second SOA service at approximately the second time; and at least one computing device of the industry model repository (IMR) enabling the first computing device to execute the first SOA service at the first time, enabling the first computing device to execute the second SOA at the second time, enabling the second computing device to execute the second SOA service at approximately the first and at approximately the second time, thereby permitting concurrent use of different versions of the industry model repository (IMR) by different devices without modification or redeployment of the industry model repository (IMR). | 10. A computer system comprising: one or more processors, one or more computer-readable memories and one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to semantically search for available computing resources for a plurality of businesses conducting commerce in different industries, the available computing resources being searched using an industry model repository (IMR) architecture system comprising: (a) a first layer of abstraction comprising business specific model assets, (b) a second layer of abstraction comprising a plurality of topic maps, each of the topic maps comprising a set of topics of capturing characteristics and relationships among the business specific model assets and other topics, associations having a specific association type and association role played by a designated topic, and occurrences defining business specific instances of the business specific model assets, each of the occurrences having an occurrence type that links to a specific one of the topics and an occurrence locator indicating an accessible network location in a federated asset repository where a corresponding specific instance is stored; and (c) a third layer of abstraction comprising service oriented architecture (“SOA”) program services that utilize the topic maps of the second layer to semantically search for the business specific model assets, wherein one or more of the services of the third layer of abstraction and linkages between the topic maps of the second layer of abstraction change over time as indicated by different versions of the industry model repository (IMR) of the second layer, wherein the searching step searches the computing resources based on linkages specific to a particular one of the different versions of the industry model repository (IMR), wherein a plurality of different versions are concurrently active at runtime and are used by different ones of the plurality of different businesses to access the business specific model assets of the first layer using the SOA program services of the third layer; a first computing device executing a first SOA service available for the searching and use at a first time when a first version of the different versions of the industry model repository (IMR) is available to the first computing device and a second SOA available for the searching and use at a second, later time using a second version of the industry model repository but not available for the searching and use at the first time; a second computing device executing the second SOA service at approximately the first time when the first version of the industry model repository is available to the second computing device, the second computing device executing the second SOA service at approximately the second time; and at least one computing device of the industry model repository (IMR) enabling the first computing device to execute the first SOA service at the first time, enabling the first computing device to execute the second SOA at the second time, enabling the second computing device to execute the second SOA service at approximately the first and at approximately the second time, thereby permitting concurrent use of different versions of the industry model repository (IMR) by different devices without modification or redeployment of the industry model repository (IMR). 14. The computer system of claim 10 , further comprising: program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to determine from stored differences between the first version and the second version of the industry model repository that parameters differ between a first business specific asset and a corresponding business specific asset, said corresponding business specific asset being updated for the second version of the industry model repository, said first business specific asset being for the first version of the industry model repository; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to, at the second layer of abstraction, receive a message from the third of second layer requesting the first business specific asset of the first layer, said message having parameters compliant with the first business specific asset and not for the corresponding business specific asset, at runtime, programs executing at the second layer of abstraction dynamically modifying the message to be compatible with the corresponding business specific asset using the stored differences; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to utilize the modified message to access the corresponding business specific asset. | 0.511425 |
8,583,434 | 21 | 22 | 21. An apparatus operable to analyze verbal communication, comprising: at least one computer processor programmed to implement: a recording controller operable to produce an electronic recording of a plurality of conversations, each of the plurality of conversations comprising a plurality of words spoken by one or more individuals; and an identification controller operable to process the electronic recording to identify a plurality of word alternatives for each of the spoken words, each of the plurality of word alternatives being identified by comparing a portion of the electronic recording to a lexicon, each of the plurality of word alternatives being assigned a corresponding probability of correctly identifying a spoken word; wherein the apparatus comprises an electronic file storage operable to store the word alternatives and the corresponding probabilities, at least two of the stored word alternatives being for a particular spoken word, a first word alternative of the at least two stored word alternatives being assigned a lower probability of correctly identifying the particular spoken word than another word alternative of the at least two stored word alternatives; and wherein the at least one computer processor is further programmed to implement an analysis controller operable to examine the word alternatives and the corresponding probabilities stored in the electronic file storage in the aggregate to determine at least one characteristic of the plurality of conversations other than a word alternative having a highest probability of correctly identifying a spoken word. | 21. An apparatus operable to analyze verbal communication, comprising: at least one computer processor programmed to implement: a recording controller operable to produce an electronic recording of a plurality of conversations, each of the plurality of conversations comprising a plurality of words spoken by one or more individuals; and an identification controller operable to process the electronic recording to identify a plurality of word alternatives for each of the spoken words, each of the plurality of word alternatives being identified by comparing a portion of the electronic recording to a lexicon, each of the plurality of word alternatives being assigned a corresponding probability of correctly identifying a spoken word; wherein the apparatus comprises an electronic file storage operable to store the word alternatives and the corresponding probabilities, at least two of the stored word alternatives being for a particular spoken word, a first word alternative of the at least two stored word alternatives being assigned a lower probability of correctly identifying the particular spoken word than another word alternative of the at least two stored word alternatives; and wherein the at least one computer processor is further programmed to implement an analysis controller operable to examine the word alternatives and the corresponding probabilities stored in the electronic file storage in the aggregate to determine at least one characteristic of the plurality of conversations other than a word alternative having a highest probability of correctly identifying a spoken word. 22. The apparatus of claim 21 , wherein the analysis controller is further operable to determine a frequency at which a particular word alternative occurs within the plurality of conversations. | 0.87336 |
6,029,159 | 11 | 19 | 11. A computer program embodied on a computer-readable medium that creates an accounting goal based multimedia business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal based educational environment, comprising: (a) a code segment that receives accesses the information in the spreadsheet object component of the rule-based expert system to retrieve information indicative of an accounting goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component that motivates accomplishment of the accounting goal; (c) a code segment that monitors answers to questions posed to evaluate the progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further motivates accomplishment of the accounting goal; and (d) a code segment that adjusts the feedback based on the student's progress toward the accounting goal. | 11. A computer program embodied on a computer-readable medium that creates an accounting goal based multimedia business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data, calculations required for the simulation and communication information to provide a goal based educational environment, comprising: (a) a code segment that receives accesses the information in the spreadsheet object component of the rule-based expert system to retrieve information indicative of an accounting goal; (b) a code segment that utilizes the information in the spreadsheet object component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component that motivates accomplishment of the accounting goal; (c) a code segment that monitors answers to questions posed to evaluate the progress toward the goal utilizing the spreadsheet object component of the rule-based expert system and provides goal-based remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further motivates accomplishment of the accounting goal; and (d) a code segment that adjusts the feedback based on the student's progress toward the accounting goal. 19. A computer program embodied on a computer-readable medium that creates an accounting goal based business simulation utilizing a rule-based expert system with a spreadsheet object component to provide an accounting goal based educational environment, as recited in claim 11, including the step of adjusting an example based on student progress. | 0.543421 |
8,521,675 | 13 | 18 | 13. A computer-implemented system of integrated automatic support and assistance, comprising: a user profile knowledge base in communication with an Al inference or semantic based engine, the user profile knowledge base storing a plurality of user information; a semantic enhanced search engine in communication with the Al inference or semantic based engine, the semantic enhanced search engine disposed to accept user queries from the Al or semantic based inference engine and to restructure the user queries into semantic components; wherein, the Al inference or semantic based engine is disposed to perform a method of integrated automatic support and assistance, the method comprising: identifying a user, wherein identifying the user includes retrieving models representing a system operated by the user; receiving a query or statement from the user through the Al inference or semantic based engine, the query or statement being related to a question about or a problem with at least one component on the system; determining a set of response time expectations based upon the received query or statement; relaying the set of response time expectations to the user; receiving feedback from the user based on the relaying; determining a user satisfaction value from the feedback; storing the user satisfaction value in the user profile for subsequent queries; determining if the received query or statement is a machine translatable query or statement; restructuring machine translatable terms of the received query or statement into semantic components based upon the retrieved models; determining a set of candidate knowledge bases both internal and external to the assistance providing system related to the semantic components; submitting the machine translatable query or statement to each knowledge base of the set of candidate knowledge bases; receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting; formatting the set of responses; submitting the formatted set of responses to the user through the Al inference or semantic based engine; determining if a response of the submitted formatted set of responses is accepted by the user; applying updated weights within the formatted set of responses; and storing the updated weights for future queries. | 13. A computer-implemented system of integrated automatic support and assistance, comprising: a user profile knowledge base in communication with an Al inference or semantic based engine, the user profile knowledge base storing a plurality of user information; a semantic enhanced search engine in communication with the Al inference or semantic based engine, the semantic enhanced search engine disposed to accept user queries from the Al or semantic based inference engine and to restructure the user queries into semantic components; wherein, the Al inference or semantic based engine is disposed to perform a method of integrated automatic support and assistance, the method comprising: identifying a user, wherein identifying the user includes retrieving models representing a system operated by the user; receiving a query or statement from the user through the Al inference or semantic based engine, the query or statement being related to a question about or a problem with at least one component on the system; determining a set of response time expectations based upon the received query or statement; relaying the set of response time expectations to the user; receiving feedback from the user based on the relaying; determining a user satisfaction value from the feedback; storing the user satisfaction value in the user profile for subsequent queries; determining if the received query or statement is a machine translatable query or statement; restructuring machine translatable terms of the received query or statement into semantic components based upon the retrieved models; determining a set of candidate knowledge bases both internal and external to the assistance providing system related to the semantic components; submitting the machine translatable query or statement to each knowledge base of the set of candidate knowledge bases; receiving a set of responses from each knowledge base of the set of knowledge bases in response to the submitting; formatting the set of responses; submitting the formatted set of responses to the user through the Al inference or semantic based engine; determining if a response of the submitted formatted set of responses is accepted by the user; applying updated weights within the formatted set of responses; and storing the updated weights for future queries. 18. The system of claim 13 , wherein determining a set of candidate knowledge bases includes submitting the semantic components to a meta knowledge database in communication with the Al inference or semantic based engine, applying a set of attribute matching algorithms or relationships to the semantic components with a plurality of attributes associated with a plurality of knowledge bases stored in the meta knowledge database, and determining the set of candidate knowledge bases based on matches between the plurality of attributes and the semantic components. | 0.500883 |
9,785,866 | 16 | 17 | 16. One or more computer storage media encoded with instructions that, when executed by a processor, configure a computer to perform acts comprising: accessing a corpus of multimedia data items, the corpus of multimedia data items including positive multimedia data items and negative multimedia data items, wherein: individual positive multimedia data items of the positive multimedia data items are associated with individual labels of a plurality of labels; and the negative multimedia data items are not associated with any label of the plurality of labels; extracting a first set of features from the individual positive multimedia data items; training a classifier based at least in part on the first set of features, the classifier including a plurality of model vectors each corresponding to one of the individual labels; based at least in part on applying the classifier to one or more of the individual positive multimedia data items, collecting statistics corresponding to each of the individual labels; extracting a second set of features from a new multimedia data item; applying the classifier to the second set of features to determine similarity values corresponding to each of the individual labels; determining that the new multimedia data item is one of the negative multimedia data items; based at least in part on determining that the new multimedia data item is one of the negative multimedia data items, comparing the statistics with the similarity values corresponding to each of the individual labels; and based at least in part on comparing the statistics with the similarity values, updating individual model vectors of the plurality of model vectors. | 16. One or more computer storage media encoded with instructions that, when executed by a processor, configure a computer to perform acts comprising: accessing a corpus of multimedia data items, the corpus of multimedia data items including positive multimedia data items and negative multimedia data items, wherein: individual positive multimedia data items of the positive multimedia data items are associated with individual labels of a plurality of labels; and the negative multimedia data items are not associated with any label of the plurality of labels; extracting a first set of features from the individual positive multimedia data items; training a classifier based at least in part on the first set of features, the classifier including a plurality of model vectors each corresponding to one of the individual labels; based at least in part on applying the classifier to one or more of the individual positive multimedia data items, collecting statistics corresponding to each of the individual labels; extracting a second set of features from a new multimedia data item; applying the classifier to the second set of features to determine similarity values corresponding to each of the individual labels; determining that the new multimedia data item is one of the negative multimedia data items; based at least in part on determining that the new multimedia data item is one of the negative multimedia data items, comparing the statistics with the similarity values corresponding to each of the individual labels; and based at least in part on comparing the statistics with the similarity values, updating individual model vectors of the plurality of model vectors. 17. One or more computer storage media as claim 16 recites, the acts further comprising: receiving a second new multimedia data item associated with a first label of the plurality of labels; extracting a third set of features from the second new multimedia data item; applying the classifier to the third set of features; based at least in part on applying the classifier to the third set of features, determining new similarity values corresponding to each of the individual labels; determining that the second new multimedia data item is one of the positive multimedia data items; determining that the classifier classified the second new multimedia data item as being associated with a second label of the plurality of labels, the second label being different from the first label; and adjusting at least two of the individual model vectors based at least in part on: scaling down a first individual model vector of the individual model vectors, the first individual model vector associated with the second label; and scaling up a second individual model vector of the individual model vectors, the second individual model vector associated with the first label. | 0.500429 |
9,794,356 | 13 | 14 | 13. The method of claim 10 , wherein the evaluating the policies using the dynamic data comprises determining if a number of sessions in which members of the group are participating is less than a maximum number in which members of the group are allowed to participate. | 13. The method of claim 10 , wherein the evaluating the policies using the dynamic data comprises determining if a number of sessions in which members of the group are participating is less than a maximum number in which members of the group are allowed to participate. 14. The method of claim 13 , wherein: if the number of sessions in which members of the group are participating is less than the maximum number, then: determining that the user is allowed to participate in a further session; and updating the number of sessions in which members of the group are participating; if the number of sessions in which members of the group are participating is not less than the maximum number, then determining that the user is not allowed to participate in a further session. | 0.862418 |
8,060,492 | 23 | 33 | 23. A Non-transitory computer-readable storage medium encoded with computer-executable instructions that when executed by a computing device, perform a method comprising: receiving a request over a network from a user for generation of at least one URL based context query, wherein the request comprises at least one query generation criteria; searching, via the network, for clusters of related data objects within a multidimensional dataspace having at least one spatial axis, at least one temporal axis, and at least one social axis using the at least one query generation criteria, wherein at least one cluster of data objects relating to the at least one query generation criteria is identified; checking permissions, via the network, relating to each data object in the at least one cluster of related data objects to determine if the user is permitted to access the data object, wherein if the user does not have permission to view the data object, the data object is removed from the cluster; generating, via the network, a URL having a context query comprising at least one context criteria, wherein the at least one context criteria is derived from the properties of the at least one cluster of data objects; and transmitting the URL having a context query to the end user. | 23. A Non-transitory computer-readable storage medium encoded with computer-executable instructions that when executed by a computing device, perform a method comprising: receiving a request over a network from a user for generation of at least one URL based context query, wherein the request comprises at least one query generation criteria; searching, via the network, for clusters of related data objects within a multidimensional dataspace having at least one spatial axis, at least one temporal axis, and at least one social axis using the at least one query generation criteria, wherein at least one cluster of data objects relating to the at least one query generation criteria is identified; checking permissions, via the network, relating to each data object in the at least one cluster of related data objects to determine if the user is permitted to access the data object, wherein if the user does not have permission to view the data object, the data object is removed from the cluster; generating, via the network, a URL having a context query comprising at least one context criteria, wherein the at least one context criteria is derived from the properties of the at least one cluster of data objects; and transmitting the URL having a context query to the end user. 33. The computer-readable storage medium of claim 23 wherein the at least one query generation criteria is an empirical query generation criteria, wherein the empirical query generation criteria specifies a method of generating the URL having a context query without reference to the at least one data cluster, comprising the additional step of: generating, via the network, a second URL having a second context query comprising at least one context criteria, wherein the at least one context criteria is derived using a method of generating the second URL having a second context query without reference to the at least one data cluster. | 0.78 |
8,370,156 | 8 | 10 | 8. One or more computer-readable storage media storing computer-executable instructions that when executed on a computer perform a method of modifying a system representation, the media storing one or more instructions for: simultaneously providing, using the computer: a first representation of a system, and a second representation of the system; receiving a user action associated with the first or second representation; analyzing: the first representation, and the second representation; automatically determining, using the computer, a first set of modifications for modifying one of the first or second representation, the first set of modifications determined: live based on the user action, and based on the analyzing; displaying, on a display device, the first set of modifications within the one of the first or second representation; and the first representation is one of: a graphical model of the system implemented in a graphical modeling environment, and code related to the system implemented in a text-based environment; and the second representation is the other of: the graphical model of the system, and the code related to the system. | 8. One or more computer-readable storage media storing computer-executable instructions that when executed on a computer perform a method of modifying a system representation, the media storing one or more instructions for: simultaneously providing, using the computer: a first representation of a system, and a second representation of the system; receiving a user action associated with the first or second representation; analyzing: the first representation, and the second representation; automatically determining, using the computer, a first set of modifications for modifying one of the first or second representation, the first set of modifications determined: live based on the user action, and based on the analyzing; displaying, on a display device, the first set of modifications within the one of the first or second representation; and the first representation is one of: a graphical model of the system implemented in a graphical modeling environment, and code related to the system implemented in a text-based environment; and the second representation is the other of: the graphical model of the system, and the code related to the system. 10. The computer-readable storage media of claim 8 , wherein the analyzing includes: analyzing components and/or configuration of the first representation. | 0.799223 |
8,438,494 | 1 | 5 | 1. An apparatus for formulating a computerized presentation of a sequence of scripts comprising audio files, the apparatus comprising: a content module for providing scripts to a user through an output device comprising fixed content; an interaction module for allowing users to selectively present the scripts to a contact during an electronic or live voice interaction between the user and the contact, and to freely interject agent content into the script presentation; a recording module for recording the presentation of scripts and agent content to the contact during the interaction; and an output module for outputting a script structure comprising a script sequence and script content, the script structure reflecting at least one choice made by the user during the presenting of scripts to a contact, as recorded by the recording module. | 1. An apparatus for formulating a computerized presentation of a sequence of scripts comprising audio files, the apparatus comprising: a content module for providing scripts to a user through an output device comprising fixed content; an interaction module for allowing users to selectively present the scripts to a contact during an electronic or live voice interaction between the user and the contact, and to freely interject agent content into the script presentation; a recording module for recording the presentation of scripts and agent content to the contact during the interaction; and an output module for outputting a script structure comprising a script sequence and script content, the script structure reflecting at least one choice made by the user during the presenting of scripts to a contact, as recorded by the recording module. 5. The apparatus of claim 1 , wherein the content module is configured to integrate agent content into the fixed content. | 0.849127 |
8,677,232 | 17 | 22 | 17. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display, cause the device to: display at least a portion of an electronic document at a first magnification level on the display; detect a first input indicating a first insertion point in the document, wherein the first insertion point is proximate to a first portion of text in the document; in response to detecting the first input: select a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the first portion of text at a default target text display size; and display a portion of the document at the second magnification level; detect a second input corresponding to a request to display a portion of the document at a third magnification level different from the second magnification level; in response to detecting the second input: display the portion of the document at the third magnification level; and store a user-adjusted target text display size corresponding to a text display size of the first portion of text at the third magnification level, wherein the user-adjusted target text display size is different from the default target text display size; and after storing the user-adjusted target text display size: detect a third input indicating a second insertion point in the document, wherein the second insertion point is proximate to a second portion of text in the document; and in response to detecting the third input, display the document at a respective magnification level such that the second portion of text is displayed at the user-adjusted target text display size. | 17. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display, cause the device to: display at least a portion of an electronic document at a first magnification level on the display; detect a first input indicating a first insertion point in the document, wherein the first insertion point is proximate to a first portion of text in the document; in response to detecting the first input: select a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the first portion of text at a default target text display size; and display a portion of the document at the second magnification level; detect a second input corresponding to a request to display a portion of the document at a third magnification level different from the second magnification level; in response to detecting the second input: display the portion of the document at the third magnification level; and store a user-adjusted target text display size corresponding to a text display size of the first portion of text at the third magnification level, wherein the user-adjusted target text display size is different from the default target text display size; and after storing the user-adjusted target text display size: detect a third input indicating a second insertion point in the document, wherein the second insertion point is proximate to a second portion of text in the document; and in response to detecting the third input, display the document at a respective magnification level such that the second portion of text is displayed at the user-adjusted target text display size. 22. The computer readable storage medium of claim 17 , wherein the respective magnification level is different from the third magnification level if the second portion of text has a different font size from a font size of the first portion of text. | 0.682864 |
7,788,578 | 1 | 6 | 1. A computer-implemented method for modifying appearance and behavior of a markup document having components, comprising: instantiating a web parts page; wherein the web parts page includes web part zones that include one or more web parts; instantiating a tool pane including tool parts for modifying the web parts page by adding code directly within code of the instantiated web parts page such that the instantiation of the tool pane changes a hierarchy of the web parts page; selecting tool parts that provide different functions to include within the tool pane for modifying the web parts page; wherein at least one of the different functions effect the layout of the web parts page; wherein at least another one of the different functions effect the appearance of the web parts page; wherein at least another one of the different functions changes a setting of a web part within the web parts page; and wherein at least another one of the different functions changes a number of web parts included in the web parts page; displaying the tool pane with the selected tool parts as part of the web parts page such that the tool pane is displayed within the web parts page that is modified using one of the provided tool parts; receiving an input to perform one of the functions that is associated with one of the tool parts that is included within the tool pane; wherein performing the function modifies the web parts page; and dynamically modifying the display of the web parts page and the tool pane in response to the modification of the web parts page such that different tool parts are included within the tool pane within the web parts page; wherein the same web parts page remains displayed. | 1. A computer-implemented method for modifying appearance and behavior of a markup document having components, comprising: instantiating a web parts page; wherein the web parts page includes web part zones that include one or more web parts; instantiating a tool pane including tool parts for modifying the web parts page by adding code directly within code of the instantiated web parts page such that the instantiation of the tool pane changes a hierarchy of the web parts page; selecting tool parts that provide different functions to include within the tool pane for modifying the web parts page; wherein at least one of the different functions effect the layout of the web parts page; wherein at least another one of the different functions effect the appearance of the web parts page; wherein at least another one of the different functions changes a setting of a web part within the web parts page; and wherein at least another one of the different functions changes a number of web parts included in the web parts page; displaying the tool pane with the selected tool parts as part of the web parts page such that the tool pane is displayed within the web parts page that is modified using one of the provided tool parts; receiving an input to perform one of the functions that is associated with one of the tool parts that is included within the tool pane; wherein performing the function modifies the web parts page; and dynamically modifying the display of the web parts page and the tool pane in response to the modification of the web parts page such that different tool parts are included within the tool pane within the web parts page; wherein the same web parts page remains displayed. 6. The computer-implemented method of claim 1 , further comprising wrapping the tool pane in a first cell of a table and the web parts in a second cell of the table. | 0.563492 |
8,548,796 | 11 | 14 | 11. A method machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-phrases, each of the bi-phrases including a text fragment from the first language and a text fragment from the second language, at least some of the bi-phrases comprising words tagged with restricted part of speech tags, at least one of the restricted part of speech tags configured for identifying a compoundable word from the second language as being one which also forms a part of a known closed compound word; retrieving text fragments in the second language from the library corresponding to text fragments in the source text; generating at least one target hypothesis, each of the target hypotheses comprising text fragments selected from the retrieved text fragments in the second language; and evaluating the target hypothesis based at least in part on combinations of restricted part of speech tags of corresponding compoundable words, comprising: for each of at least one specified combination of consecutive restricted part of speech tags of corresponding compoundable words from different bi-phrases, identifying occurrences of the specified combination in the hypothesis; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions taking into account the occurrences of the specified combination of the restricted part of speech tags of the corresponding compoundable words from different bi-phrases in the hypothesis; and based on the evaluation, outputting one of the at least one target hypothesis as the optimal hypothesis for forming the translation; and wherein at least one of the accessing, retrieving, evaluating and outputting is performed with a computer processor. | 11. A method machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-phrases, each of the bi-phrases including a text fragment from the first language and a text fragment from the second language, at least some of the bi-phrases comprising words tagged with restricted part of speech tags, at least one of the restricted part of speech tags configured for identifying a compoundable word from the second language as being one which also forms a part of a known closed compound word; retrieving text fragments in the second language from the library corresponding to text fragments in the source text; generating at least one target hypothesis, each of the target hypotheses comprising text fragments selected from the retrieved text fragments in the second language; and evaluating the target hypothesis based at least in part on combinations of restricted part of speech tags of corresponding compoundable words, comprising: for each of at least one specified combination of consecutive restricted part of speech tags of corresponding compoundable words from different bi-phrases, identifying occurrences of the specified combination in the hypothesis; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions taking into account the occurrences of the specified combination of the restricted part of speech tags of the corresponding compoundable words from different bi-phrases in the hypothesis; and based on the evaluation, outputting one of the at least one target hypothesis as the optimal hypothesis for forming the translation; and wherein at least one of the accessing, retrieving, evaluating and outputting is performed with a computer processor. 14. The method of claim 11 , wherein at least one feature function is a punish function which penalizes occurrences of at least one specified combination of consecutive restricted part of speech tags which limits generation of a closed compound. | 0.919725 |
7,944,448 | 43 | 45 | 43. The method according to claim 32 , wherein the emotion response message is output in emotion categories having differing validity time periods based on at least one of the social response message stored in the event buffer, one or more outputs from the predefined personality trait register, or one or more outputs from the emotional state register. | 43. The method according to claim 32 , wherein the emotion response message is output in emotion categories having differing validity time periods based on at least one of the social response message stored in the event buffer, one or more outputs from the predefined personality trait register, or one or more outputs from the emotional state register. 45. The method according to claim 43 , wherein the emotion response message generated for the lasting emotion category comprises one of a neutrality value, a happiness value, a sadness value or an anger value. | 0.927076 |
7,664,749 | 1 | 6 | 1. A method of creating a ranked join index for ordered data entries, comprising: determining, via a processor, a dominating set of said ordered data entries; mapping said dominating set of said ordered data entries according to rank attributes; determining a separating vector for each set of adjacent mapped data entries; and ordering said data entries according to a separating point associated with each of said separating vectors. | 1. A method of creating a ranked join index for ordered data entries, comprising: determining, via a processor, a dominating set of said ordered data entries; mapping said dominating set of said ordered data entries according to rank attributes; determining a separating vector for each set of adjacent mapped data entries; and ordering said data entries according to a separating point associated with each of said separating vectors. 6. The method of claim 1 , wherein said each set of adjacent mapped data entries comprises more than two mapped data points if data entries are collinear. | 0.895522 |
7,730,395 | 34 | 35 | 34. The system of claim 26 further comprising: means for monitoring the one or more virtual tags and the one or more transformation rules. | 34. The system of claim 26 further comprising: means for monitoring the one or more virtual tags and the one or more transformation rules. 35. The system of claim 34 wherein said means for monitoring provides microstatistics of the use of said one or more virtual tags and said one or more transformation rules. | 0.947625 |
7,577,651 | 63 | 64 | 63. The system of claim 62 wherein determining comprises classifying the search query based on the temporal profile of the search query. | 63. The system of claim 62 wherein determining comprises classifying the search query based on the temporal profile of the search query. 64. The system of claim 63 wherein determining comprises using a combination of features comprising: (a) divergence; (b) autocorrelation; (c) statistics of the rank order; or (d) burst model. | 0.940163 |
7,840,905 | 29 | 35 | 29. A system comprising: at least one processor; and a storage storing: a menu theme library comprising a menu theme template that includes a set of objects for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein properties for the set of objects are defined in a menu theme description file; a set of modules identified by a set of paths for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; and a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu. | 29. A system comprising: at least one processor; and a storage storing: a menu theme library comprising a menu theme template that includes a set of objects for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein properties for the set of objects are defined in a menu theme description file; a set of modules identified by a set of paths for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; and a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu. 35. The system of claim 29 , wherein the storage further stores: a menu theme bundle for storing (i) the menu theme description file and (ii) one or more content files. | 0.876471 |
7,769,769 | 9 | 16 | 9. A method for transforming in a computer system a metadata model for containing model objects, the method comprising: obtaining information from a model object in a lower layer of a metadata model stored in a storage device, wherein the metadata model includes the lower layer and a higher layer, wherein each of the lower layer and the higher layer includes one or more model objects, wherein the lower layer includes one or more model objects having a lower degree of abstraction than the model objects of the higher layer, wherein the lower layer provides access to a plurality of different data sources, and wherein the higher layer provides each of a plurality of different business intelligence tools with an interface by which to access each of the plurality of different data sources, and wherein each of the plurality of different business intelligence tools is designed to interface only with a corresponding subset of the plurality of different data sources; abstracting, with one or more computers of the computer system, the information by adding business rules for representing a business concept; creating, with the one or more computers, a new model object in the higher layer corresponding to the model object in the lower layer based on the information abstracted, wherein the new model object in the higher layer provides a representation of the business concept; and storing the metadata model having the lower layer and the higher layer in a storage device. | 9. A method for transforming in a computer system a metadata model for containing model objects, the method comprising: obtaining information from a model object in a lower layer of a metadata model stored in a storage device, wherein the metadata model includes the lower layer and a higher layer, wherein each of the lower layer and the higher layer includes one or more model objects, wherein the lower layer includes one or more model objects having a lower degree of abstraction than the model objects of the higher layer, wherein the lower layer provides access to a plurality of different data sources, and wherein the higher layer provides each of a plurality of different business intelligence tools with an interface by which to access each of the plurality of different data sources, and wherein each of the plurality of different business intelligence tools is designed to interface only with a corresponding subset of the plurality of different data sources; abstracting, with one or more computers of the computer system, the information by adding business rules for representing a business concept; creating, with the one or more computers, a new model object in the higher layer corresponding to the model object in the lower layer based on the information abstracted, wherein the new model object in the higher layer provides a representation of the business concept; and storing the metadata model having the lower layer and the higher layer in a storage device. 16. The method as claimed in claim 9 further comprising: selecting a subset of the model objects in the higher layer; and creating another new model object in the higher layer based on the selected subset of the model objects in the higher layer. | 0.727876 |
9,871,807 | 1 | 4 | 1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value. | 1. A system comprising: at least one processor; a memory; and an intrusion prevention mechanism stored in the memory and including instructions, which are executable by the at least one processor and include an analysis engine configured to tokenize an input stream of data into a plurality of parts including a first one or more parts and a second one or more parts, and select the first one or more parts for analysis, wherein the analysis engine includes one or more protocol parsers, and wherein the one or more protocol parsers analyze the first one or more parts, and a generic decoder configured to operate based on generic application-level protocol analysis language primitives, wherein the generic decoder is configured to assist the one or more protocol parsers of the analysis engine by analyzing the second one or more parts, having a same protocol as the first one or more parts and not analyzed by the analysis engine, for a signature, wherein the analyzing of the second one or more parts includes searching the second one or more parts for a first predetermined pattern, and generate an error signal in response to matching the first predetermined pattern in the second one or more parts, wherein the signature is detected in response to the pattern being matched in the second one or more parts, and wherein the primitives include at least one of a primitive configured for pattern matching, a primitive configured for skipping a first predetermined number of bytes to search for the first predetermined pattern, a primitive configured for specifying a window in which at least one pattern is to be searched, a primitive configured for using a regular expression for pattern matching, or a primitive configured for reading a value and moving within the first one or more parts based on that value. 4. The system of claim 1 , wherein the first one or more parts comprises file content within a file. | 0.939759 |
5,541,836 | 22 | 23 | 22. Apparatus for determining whether a sense for a word is lexically appropriate to a given position in a text, the apparatus comprising: means for obtaining a sequence of words in the text which includes the given position and is predominantly substantially longer than the average length of the sentences of the text; and means for analyzing the sequence to determine whether a sense specified in a word/sense pair for the word is a sense which is lexically appropriate to the given position. | 22. Apparatus for determining whether a sense for a word is lexically appropriate to a given position in a text, the apparatus comprising: means for obtaining a sequence of words in the text which includes the given position and is predominantly substantially longer than the average length of the sentences of the text; and means for analyzing the sequence to determine whether a sense specified in a word/sense pair for the word is a sense which is lexically appropriate to the given position. 23. The apparatus set forth in claim 22 wherein: the means for obtaining a sequence obtains a sequence whose length is approximately 100 words. | 0.923936 |
8,019,735 | 1 | 5 | 1. A system to provide query caching, comprising: one or more microprocessors; a query component, running on the one or more microprocessors, wherein the query component is deployed in a container and operates to issue a query to retrieve a query result from a database, wherein the query is associated with a transaction, and wherein the query result includes one or more instances of a class that is managed by the container, wherein the class represents one or more persisted data entries retrieved from the database and the one or more persisted data entries are associated with at least one row in a table in the database; a cache management component, running on the one or more microprocessors, to store the one or more instances of the class in a cache; a query registration component, running on the one or more microprocessors, to perform the steps of: maintaining the query in a query registry with one or more queries; looking up the query in the query registry; and allowing the cache management component to retrieve the stored one or more instances of the class for the query in the cache, when the query registration component determines that another query matches the query in the query registry; and wherein the cache management component further operates to allow the one or more instances of the class to be used concurrently by multiple users using an optimistic concurrency strategy, and wherein, under the optimistic concurrency strategy, the cache management component leaves the one or more instances of the class in the cached query result unlocked when the one or more instances of the class remain unchanged during the transaction; invalidate the one or more instances of the class in the cached query result that are used concurrently by multiple users during the transaction, when a row in the table in the database that is not used by the cached query result is updated or invalidated; and remove the query from the query registry and remove the cached query result with the one or more instances of the class from the cache. | 1. A system to provide query caching, comprising: one or more microprocessors; a query component, running on the one or more microprocessors, wherein the query component is deployed in a container and operates to issue a query to retrieve a query result from a database, wherein the query is associated with a transaction, and wherein the query result includes one or more instances of a class that is managed by the container, wherein the class represents one or more persisted data entries retrieved from the database and the one or more persisted data entries are associated with at least one row in a table in the database; a cache management component, running on the one or more microprocessors, to store the one or more instances of the class in a cache; a query registration component, running on the one or more microprocessors, to perform the steps of: maintaining the query in a query registry with one or more queries; looking up the query in the query registry; and allowing the cache management component to retrieve the stored one or more instances of the class for the query in the cache, when the query registration component determines that another query matches the query in the query registry; and wherein the cache management component further operates to allow the one or more instances of the class to be used concurrently by multiple users using an optimistic concurrency strategy, and wherein, under the optimistic concurrency strategy, the cache management component leaves the one or more instances of the class in the cached query result unlocked when the one or more instances of the class remain unchanged during the transaction; invalidate the one or more instances of the class in the cached query result that are used concurrently by multiple users during the transaction, when a row in the table in the database that is not used by the cached query result is updated or invalidated; and remove the query from the query registry and remove the cached query result with the one or more instances of the class from the cache. 5. The system according to claim 1 , wherein: the query registration component is configured to maintain the query registry by inserting or deleting a string of a query in the query registry. | 0.803498 |
9,355,485 | 11 | 13 | 11. A non-transitory computer readable storage medium storing an image data structure produced by a method of generating a visualization of a plurality of words inside a predefined shape, the method comprising: storing, in a computer readable medium, a plurality of values, each corresponding to one of the plurality of words; selecting, one or more processors, a maximum word size; computing, the one or more processors, a word size for each of the plurality of words based on the value corresponding to the word and the maximum word size; obtaining, the one or more processors, a word color for each of the plurality of words; and generating, the one or more processors, the image data structure for displaying on a display, the image data structure including an image having the plurality of words, each word having the corresponding word size and the corresponding word color; wherein selecting the maximum word size includes: generating, the one or more processors, a first set of maximum word sizes; for each maximum word size in the first set, arranging, using the one or more processors, the plurality of words such that a first word of the plurality of words has the maximum word size and remaining words of the plurality of words are not larger than the maximum word size, and determining, using the one or more processors, whether the arrangement of the plurality of words satisfies a first criterion, the first criterion being that none of the words in the arrangement are outside the predefined shape; selecting, the one or more processors, the largest maximum word size in the first set having an arrangement of the plurality of words that satisfies the first criterion. | 11. A non-transitory computer readable storage medium storing an image data structure produced by a method of generating a visualization of a plurality of words inside a predefined shape, the method comprising: storing, in a computer readable medium, a plurality of values, each corresponding to one of the plurality of words; selecting, one or more processors, a maximum word size; computing, the one or more processors, a word size for each of the plurality of words based on the value corresponding to the word and the maximum word size; obtaining, the one or more processors, a word color for each of the plurality of words; and generating, the one or more processors, the image data structure for displaying on a display, the image data structure including an image having the plurality of words, each word having the corresponding word size and the corresponding word color; wherein selecting the maximum word size includes: generating, the one or more processors, a first set of maximum word sizes; for each maximum word size in the first set, arranging, using the one or more processors, the plurality of words such that a first word of the plurality of words has the maximum word size and remaining words of the plurality of words are not larger than the maximum word size, and determining, using the one or more processors, whether the arrangement of the plurality of words satisfies a first criterion, the first criterion being that none of the words in the arrangement are outside the predefined shape; selecting, the one or more processors, the largest maximum word size in the first set having an arrangement of the plurality of words that satisfies the first criterion. 13. The non-transitory computer readable storage medium of claim 11 , wherein each of the plurality of values is a proportion, and computing the word size for each of the plurality of words includes multiplying the maximum word size by the proportion associated with the corresponding word. | 0.846885 |
9,880,693 | 1 | 9 | 1. A method, implemented at a computer system that includes one or more processors, for automatically editing storyboards based on a learned user-specific editing style, the method comprising: determining a first set of characteristics for a first plurality of media content items in a first storyboard, including: receiving first user input associating each of the first plurality of media content items with one or more of a first plurality of cells of a first storyboard; and analyzing each of the first plurality of media content items, including their associations with the first plurality of cells, to identify the first set of characteristics of the first plurality of media content items; determining a set of user-specific editing characteristics applied to the first plurality of media content items in the first story board, including: receiving second user input comprising a set of editing decisions, to create an edited first storyboard, the set of editing decisions including a plurality of editing decisions applied to the first plurality of cells to edit the first plurality of media content items in the first storyboard; and based on receiving the second user input, automatically defining a user-specific editing style, including comparing the first storyboard to the edited first storyboard to determine one or more user-specific editing style rules corresponding to the set of editing decisions that resulted in the differences between the first storyboard and the edited first storyboard, and defining metadata representing at least one of the plurality of editing decisions applied to the first plurality of cells; and automatically applying the user-specific editing style to a second plurality of media content items, including: receiving third user input associating each of the second plurality of media content items with one or more of a second plurality of cells of a second storyboard; analyzing each of the second plurality of media content items, including, their associations with the second plurality of cells, to identify a second set of characteristics of the second plurality of media content items; comparing the first set of characteristics of the first plurality of media content items with the second set of characteristics of the second plurality of media content items, to identify at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; automatically creating an edited second storyboard, by at least applying the user-specific editing style to the identified at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; and displaying the edited second storyboard. | 1. A method, implemented at a computer system that includes one or more processors, for automatically editing storyboards based on a learned user-specific editing style, the method comprising: determining a first set of characteristics for a first plurality of media content items in a first storyboard, including: receiving first user input associating each of the first plurality of media content items with one or more of a first plurality of cells of a first storyboard; and analyzing each of the first plurality of media content items, including their associations with the first plurality of cells, to identify the first set of characteristics of the first plurality of media content items; determining a set of user-specific editing characteristics applied to the first plurality of media content items in the first story board, including: receiving second user input comprising a set of editing decisions, to create an edited first storyboard, the set of editing decisions including a plurality of editing decisions applied to the first plurality of cells to edit the first plurality of media content items in the first storyboard; and based on receiving the second user input, automatically defining a user-specific editing style, including comparing the first storyboard to the edited first storyboard to determine one or more user-specific editing style rules corresponding to the set of editing decisions that resulted in the differences between the first storyboard and the edited first storyboard, and defining metadata representing at least one of the plurality of editing decisions applied to the first plurality of cells; and automatically applying the user-specific editing style to a second plurality of media content items, including: receiving third user input associating each of the second plurality of media content items with one or more of a second plurality of cells of a second storyboard; analyzing each of the second plurality of media content items, including, their associations with the second plurality of cells, to identify a second set of characteristics of the second plurality of media content items; comparing the first set of characteristics of the first plurality of media content items with the second set of characteristics of the second plurality of media content items, to identify at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; automatically creating an edited second storyboard, by at least applying the user-specific editing style to the identified at least one of the second plurality of media content items that has at least one characteristic that matches at least one characteristic of at least one of the first plurality of media content items; and displaying the edited second storyboard. 9. The method of claim 1 , wherein one or more computer-readable media have computer-executable instructions for performing the method of claim 1 . | 0.94938 |
8,731,929 | 24 | 27 | 24. The system according to claim 1 , further comprising an extension and modification facility configured to: enable behavior associated with the agent architecture to be configured via one or more speech interface commands or one or more inputs to a graphical user interface; and enable behavior associated with one or more of the plurality of domain agents to be configured via the one or more speech interface commands or the one or more inputs to the graphical user interface. | 24. The system according to claim 1 , further comprising an extension and modification facility configured to: enable behavior associated with the agent architecture to be configured via one or more speech interface commands or one or more inputs to a graphical user interface; and enable behavior associated with one or more of the plurality of domain agents to be configured via the one or more speech interface commands or the one or more inputs to the graphical user interface. 27. The system according to claim 24 , wherein the one or more speech interface commands or the one or more inputs to the graphical user interface can use a scripting language to configure the behavior associated with the agent architecture or the behavior associated with the one or more of the plurality of domain agents. | 0.928571 |
4,622,585 | 9 | 10 | 9. A compression device as claimed in claim 5, wherein there is provided a sequential logic element which has at least two states in order to activate the shift control (ISE) of said first and second shift register in a first state until a group of significant compression bits has been formed, to deactivate in reacation thereto said shift control in a second state, to activate said first output (IES) until said group of significant compression bits has been presented compltely on said first output, and to return in reaction thereto to said first state. | 9. A compression device as claimed in claim 5, wherein there is provided a sequential logic element which has at least two states in order to activate the shift control (ISE) of said first and second shift register in a first state until a group of significant compression bits has been formed, to deactivate in reacation thereto said shift control in a second state, to activate said first output (IES) until said group of significant compression bits has been presented compltely on said first output, and to return in reaction thereto to said first state. 10. A compression device as claimed in claim 9, wherein said second state has a substate in order to enable, together with the presentation of a last code bit of group of significant compression bits, the shift control of the next data bit. | 0.953935 |
8,700,555 | 8 | 13 | 8. A computer readable medium including processor executable instructions for sharing information between a semantic network and a knowledge sharing repository, including instructions to: retrieve from the semantic network, a set of data based on information included in the semantic network; access the knowledge sharing repository from a first computer system; and transfer, from the first computer system, the set of data to a computer system hosting the knowledge sharing repository for incorporation into the knowledge sharing repository. | 8. A computer readable medium including processor executable instructions for sharing information between a semantic network and a knowledge sharing repository, including instructions to: retrieve from the semantic network, a set of data based on information included in the semantic network; access the knowledge sharing repository from a first computer system; and transfer, from the first computer system, the set of data to a computer system hosting the knowledge sharing repository for incorporation into the knowledge sharing repository. 13. The computer readable medium of claim 8 wherein the instructions to retrieve the set of data include instructions to: access an infobox for a knowledge sharing repository page; and retrieve, as at least a portion of said data, at least a portion of the contents of the infobox. | 0.737383 |
7,933,762 | 17 | 19 | 17. The method of claim 16 in which the information about the performance comprises information about the performance of the validated model process applied to two independent data subsets, the independent data subsets being randomly selected from the historical data, and includes at least one of: a statistical report card, a link to a statistical report chart, a cumulative lift chart, a link to the cumulative lift chart, a non-cumulative lift chart, a link to the non-cumulative lift chart. | 17. The method of claim 16 in which the information about the performance comprises information about the performance of the validated model process applied to two independent data subsets, the independent data subsets being randomly selected from the historical data, and includes at least one of: a statistical report card, a link to a statistical report chart, a cumulative lift chart, a link to the cumulative lift chart, a non-cumulative lift chart, a link to the non-cumulative lift chart. 19. The method of claim 17 in which the final model and the model process validation results are stored persistently. | 0.965929 |
8,949,359 | 1 | 3 | 1. A method of hosting electronic conversations, comprising: at a computer system having one or more processors and memory storing programs for execution by the one or more processors, maintaining a plurality of conversations, each having an identified set of participants; maintaining for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; in response to receiving a search query from a first participant of a first conversation in the plurality of conversations: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and formatting all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. | 1. A method of hosting electronic conversations, comprising: at a computer system having one or more processors and memory storing programs for execution by the one or more processors, maintaining a plurality of conversations, each having an identified set of participants; maintaining for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; in response to receiving a search query from a first participant of a first conversation in the plurality of conversations: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and formatting all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. 3. The method of claim 1 , further comprising maintaining for a subscriber of the computer system a list of conversations in which the subscriber is a participant, updating a status of each such conversation in the list when a state of the respective conversation changes, and sending to the subscriber a list that comprises at least a portion of the list of conversations in which the subscriber is a participant, the list sent to the subscriber including status information for the listed conversations. | 0.592084 |
8,818,801 | 7 | 8 | 7. The dialogue speech recognition system according to claim 1 , further comprising: a turn information generation unit, implemented by the at least one CPU, that generates turn information based on start time and end time of a speech signal of each speaker. | 7. The dialogue speech recognition system according to claim 1 , further comprising: a turn information generation unit, implemented by the at least one CPU, that generates turn information based on start time and end time of a speech signal of each speaker. 8. The dialogue speech recognition system according to claim 7 , wherein the turn information generation unit generates turn information indicating that a certain speaker has the turn to speak during a period from time when a speech signal of the speaker becomes sounded from a state where speech signals of all speakers are soundless to time when the speech signal of the speaker becomes soundless, and, provided that a speech signal of another speaker has become sounded at the time when the speech signal of the speaker set to have the turn to speak becomes soundless, generates turn information indicating that said another speaker has the turn to speak during a period from the time to time when the speech signal of said another speaker becomes soundless. | 0.817506 |
9,436,440 | 1 | 3 | 1. A computer program product embodied on a non-transitory computer readable medium, comprising computer code for: identifying an object-oriented information model including JAVA™ code associated with JAVA™ programming language to be converted to a document-oriented model described in Extensible Markup Language (XML); automatically identifying a plurality of objects associated with the object-oriented information model that are each associated with a plurality of instances, including identifying a plurality of objects that each include a plurality of different object definitions for that object; optimizing the object-oriented information model by, for each of the plurality of objects each associated with the plurality of instances, storing the plurality of different object definitions in a defined data container outside of the object-oriented information model and replacing each of the plurality of different object definitions with a reference to the different object definitions in the defined data container outside of the object-oriented information model; annotating the optimized object-oriented information model, in response to performing the storing and the replacing; and automatically validating the optimized object-oriented information model by verifying the reference to the plurality of different object definitions in the defined data container outside of the optimized object-oriented information model is associated with at least one object identifier. | 1. A computer program product embodied on a non-transitory computer readable medium, comprising computer code for: identifying an object-oriented information model including JAVA™ code associated with JAVA™ programming language to be converted to a document-oriented model described in Extensible Markup Language (XML); automatically identifying a plurality of objects associated with the object-oriented information model that are each associated with a plurality of instances, including identifying a plurality of objects that each include a plurality of different object definitions for that object; optimizing the object-oriented information model by, for each of the plurality of objects each associated with the plurality of instances, storing the plurality of different object definitions in a defined data container outside of the object-oriented information model and replacing each of the plurality of different object definitions with a reference to the different object definitions in the defined data container outside of the object-oriented information model; annotating the optimized object-oriented information model, in response to performing the storing and the replacing; and automatically validating the optimized object-oriented information model by verifying the reference to the plurality of different object definitions in the defined data container outside of the optimized object-oriented information model is associated with at least one object identifier. 3. The computer program product of claim 1 , wherein storing the plurality of different object definitions in the location other than the object-oriented information model includes storing the plurality of different object definitions in a defined container that is outside of the object-oriented information model. | 0.527027 |
8,903,799 | 14 | 15 | 14. A method for finding data objects corresponding to a user query, comprising: receiving a selected object type at a computer having a search formation engine, the selected object type being selected by a user; the search formation engine presenting a user interface on a device associated with the user, the user interface comprising query options for the user to formulate a query on the selected object type, the query options comprising a structured query constraint and an unstructured query constraint; the search formation engine forming the query for an information retrieval engine, the query combining the structured query constraint and the unstructured query constraint; and the information retrieval engine processing the query and returning data objects that correspond to the query, the data objects being from a set of data objects, each data object in the set of data objects comprising unstructured data and a metadata structure as ascribed by an object type definition for an object type, wherein the object type definition specifies a set of attributes representing metadata for data objects instantiated according to the object type, the user interface based on a particular object type definition for the selected object type. | 14. A method for finding data objects corresponding to a user query, comprising: receiving a selected object type at a computer having a search formation engine, the selected object type being selected by a user; the search formation engine presenting a user interface on a device associated with the user, the user interface comprising query options for the user to formulate a query on the selected object type, the query options comprising a structured query constraint and an unstructured query constraint; the search formation engine forming the query for an information retrieval engine, the query combining the structured query constraint and the unstructured query constraint; and the information retrieval engine processing the query and returning data objects that correspond to the query, the data objects being from a set of data objects, each data object in the set of data objects comprising unstructured data and a metadata structure as ascribed by an object type definition for an object type, wherein the object type definition specifies a set of attributes representing metadata for data objects instantiated according to the object type, the user interface based on a particular object type definition for the selected object type. 15. The method of claim 14 , further comprising indexing the set of data objects in an index for search by the information retrieval engine. | 0.785276 |
8,650,207 | 5 | 6 | 5. A computer-implemented process for performing string transformations involving at least two different operations, comprising: using a computer to perform the following process actions: accessing a first expression language associated with string transformations that involve a first operation, said first expression language comprising a first set of grammar rules defining expressions therein; accessing a second expression language associated with string transformations that involve at least one operation that is different from said first operation, said second expression language comprising a second set of grammar rules defining expressions therein; combining the first expression language and the second expression language to establish a combined expression language; generating a synthesis procedure which learns a set of expressions in the combined expression language that produces a prescribed output from one or more input string variables using said at least two different operations based on a set of one or more input-output examples each comprising one or more input string variables and said prescribed output; and receiving one or more input string variables of a same type found in the set of one or more input-output examples, and producing the prescribed output using the synthesis procedure. | 5. A computer-implemented process for performing string transformations involving at least two different operations, comprising: using a computer to perform the following process actions: accessing a first expression language associated with string transformations that involve a first operation, said first expression language comprising a first set of grammar rules defining expressions therein; accessing a second expression language associated with string transformations that involve at least one operation that is different from said first operation, said second expression language comprising a second set of grammar rules defining expressions therein; combining the first expression language and the second expression language to establish a combined expression language; generating a synthesis procedure which learns a set of expressions in the combined expression language that produces a prescribed output from one or more input string variables using said at least two different operations based on a set of one or more input-output examples each comprising one or more input string variables and said prescribed output; and receiving one or more input string variables of a same type found in the set of one or more input-output examples, and producing the prescribed output using the synthesis procedure. 6. The process of claim 5 , wherein the process action of combining the first expression language and the second expression language to establish a combined expression language, comprises the actions of: combining the first and second sets of grammar rules without repeating any of the rules; and whenever an expression in the first expression language additionally involves at least one operation that is different from said first operation, including a second expression language expression corresponding to the at least one operation that is different from said first operation in the first language expression; and whenever an expression in the second expression language additionally involves said first operation, including a first expression language expression corresponding to said first operation in the second language expression. | 0.800994 |
9,569,413 | 1 | 15 | 1. A method comprising: receiving a document having a plurality of lines with text, the document comprising text associated with at least one topic of interest and text not associated with the at least one topic of interest; determining, for each line in the document, a length of the line and a number of off-topic indicators, the off-topic indicators characterizing portions of the document as likely being not being associated with the at least one topic of interest; determining a density for each line based on the determined line length and the determined number of off-topic indicators, the density for each line being proportional to the determined line length and inversely proportional to an exponential base greater than one of the number of off-topic indicators; identifying, using the determined densities for each line, portions of the document likely associated with the at least one topic of interest; and providing data characterizing the identified portions of the document. | 1. A method comprising: receiving a document having a plurality of lines with text, the document comprising text associated with at least one topic of interest and text not associated with the at least one topic of interest; determining, for each line in the document, a length of the line and a number of off-topic indicators, the off-topic indicators characterizing portions of the document as likely being not being associated with the at least one topic of interest; determining a density for each line based on the determined line length and the determined number of off-topic indicators, the density for each line being proportional to the determined line length and inversely proportional to an exponential base greater than one of the number of off-topic indicators; identifying, using the determined densities for each line, portions of the document likely associated with the at least one topic of interest; and providing data characterizing the identified portions of the document. 15. A method as in claim 1 , wherein providing data comprises generating a cleaned document file removing the portions of the document not likely associated with the at least one topic of interest. | 0.855994 |
7,783,626 | 8 | 9 | 8. An article of manufacture comprising a tangible computer readable storage medium storing a program for building an index, wherein the program, when executed by a processor of a computer, causes operations to be performed, the operations comprising: storing a current version of a store having a tokenized version of each document in a corpus of documents, a delta store accumulating changes to the current version of the store, and previously generated global analysis computations, wherein the previously generated global analysis computations include an anchor text table, a rank table, and a duplicates table; building a new version of the index and outputting a raw anchor text table and a raw duplicates table by accessing the current version of the store store i , the delta store, and the previously generated global analysis computations; and generating new global analysis computations by accessing the raw anchor text table, the raw duplicates table, and the previously generated global analysis computations, wherein the new global analysis computations include a new anchor text table, a new rank table, and a new duplicates table. | 8. An article of manufacture comprising a tangible computer readable storage medium storing a program for building an index, wherein the program, when executed by a processor of a computer, causes operations to be performed, the operations comprising: storing a current version of a store having a tokenized version of each document in a corpus of documents, a delta store accumulating changes to the current version of the store, and previously generated global analysis computations, wherein the previously generated global analysis computations include an anchor text table, a rank table, and a duplicates table; building a new version of the index and outputting a raw anchor text table and a raw duplicates table by accessing the current version of the store store i , the delta store, and the previously generated global analysis computations; and generating new global analysis computations by accessing the raw anchor text table, the raw duplicates table, and the previously generated global analysis computations, wherein the new global analysis computations include a new anchor text table, a new rank table, and a new duplicates table. 9. The article of manufacture of claim 8 , wherein the operations for index creation further comprise: building a new version of a delta store using the previously generated global analysis computations, a current version of a delta store, and newly crawled documents. | 0.501859 |
8,386,260 | 1 | 8 | 1. A method performed by an application server, the method comprising the steps of: receiving, over an application server/voice server control path between the application server and a voice server, an indication from the voice server that speech has been recognized based on uplink audio data sent from a client device to the voice server over an audio data path between the client device and the voice server, wherein the uplink audio data represents a user utterance received through a voice modality of the client device, and wherein the voice server is distinct from the application server; and sending, over an application server/client control path between the application server and the client device that is distinct from the audio data path, a message to the client device that includes a recognition result for the speech and that causes the client device to update a visual display to reflect the recognition result. | 1. A method performed by an application server, the method comprising the steps of: receiving, over an application server/voice server control path between the application server and a voice server, an indication from the voice server that speech has been recognized based on uplink audio data sent from a client device to the voice server over an audio data path between the client device and the voice server, wherein the uplink audio data represents a user utterance received through a voice modality of the client device, and wherein the voice server is distinct from the application server; and sending, over an application server/client control path between the application server and the client device that is distinct from the audio data path, a message to the client device that includes a recognition result for the speech and that causes the client device to update a visual display to reflect the recognition result. 8. The method of claim 1 , further comprising the steps of: receiving an indication from the client device, over the application server/client control path, that a current focus within the visual display rendered on the client device has changed to a different focus, wherein the different focus indicates a display element of the visual display for which input data currently is receivable by the client device though a visual modality and a voice modality; and sending a message to the voice server, over the application server/voice server control path, which includes information that will cause the voice server to execute machine code corresponding to the different focus. | 0.715604 |
9,230,041 | 10 | 15 | 10. A system comprising: one or more server computers comprising a main memory storing an in-memory database, wherein the one or more server computers having one or more processors coupled to the main memory and executing computer readable instructions for a plurality of computer modules including: an entity extraction module configured to receive a user input of partial search query parameters from a user interface, wherein the partial search query parameters having at least one incomplete search query parameter, wherein the user interface is presented on a user computer, wherein the entity extraction module being further configured to: extract one or more first entities, in real-time, as search query data is requested by the user computer, from the partial search query parameters by comparing the partial search query parameters with an entity co-occurrence database having instances of co-occurrence of the one or more first entities in an electronic data corpus and identifying at least one entity type corresponding to the one or more first entities in the partial search query parameters, wherein the in-memory database comprises the entity co-occurrence database, wherein a score is assigned to each extracted feature, wherein the score indicates a level of certainty of the each extracted feature being correctly extracted with a correct attribute; and a fuzzy-score matching module configured to select in real-time, as the search query data is requested by the user computer, a fuzzy matching algorithm for searching the entity co-occurrence database to identify one or more records associated with the partial search query parameters, wherein the fuzzy matching algorithm corresponds to the at least one identified entity type, the fuzzy-score matching module being further configured to: search, in real-time, as the search query data is requested by the user computer, the entity co-occurrence database using the selected fuzzy matching algorithm and form one or more first suggested search query parameters from the one or more records based on the search, and present the one or more first suggested search query parameters to the user interface; wherein the entity extraction module is further configured to: receive a user selection of the one or more first suggested search query parameters from the user interface so as to form completed search query parameters, extract one or more second entities from the completed search query parameters, search the entity co-occurrence database to identify one or more entities related to the one or more second entities so as to form one or more second suggested search query parameters, and present the one or more second suggested search query parameters to the user interface. | 10. A system comprising: one or more server computers comprising a main memory storing an in-memory database, wherein the one or more server computers having one or more processors coupled to the main memory and executing computer readable instructions for a plurality of computer modules including: an entity extraction module configured to receive a user input of partial search query parameters from a user interface, wherein the partial search query parameters having at least one incomplete search query parameter, wherein the user interface is presented on a user computer, wherein the entity extraction module being further configured to: extract one or more first entities, in real-time, as search query data is requested by the user computer, from the partial search query parameters by comparing the partial search query parameters with an entity co-occurrence database having instances of co-occurrence of the one or more first entities in an electronic data corpus and identifying at least one entity type corresponding to the one or more first entities in the partial search query parameters, wherein the in-memory database comprises the entity co-occurrence database, wherein a score is assigned to each extracted feature, wherein the score indicates a level of certainty of the each extracted feature being correctly extracted with a correct attribute; and a fuzzy-score matching module configured to select in real-time, as the search query data is requested by the user computer, a fuzzy matching algorithm for searching the entity co-occurrence database to identify one or more records associated with the partial search query parameters, wherein the fuzzy matching algorithm corresponds to the at least one identified entity type, the fuzzy-score matching module being further configured to: search, in real-time, as the search query data is requested by the user computer, the entity co-occurrence database using the selected fuzzy matching algorithm and form one or more first suggested search query parameters from the one or more records based on the search, and present the one or more first suggested search query parameters to the user interface; wherein the entity extraction module is further configured to: receive a user selection of the one or more first suggested search query parameters from the user interface so as to form completed search query parameters, extract one or more second entities from the completed search query parameters, search the entity co-occurrence database to identify one or more entities related to the one or more second entities so as to form one or more second suggested search query parameters, and present the one or more second suggested search query parameters to the user interface. 15. The system of claim 10 wherein the entity co-occurrence database is indexed. | 0.896104 |
7,855,799 | 8 | 13 | 8. A method of printing electronic documents implemented at least in part on a computing system, comprising: identifying a plurality of pages comprised in an electronic document; receiving an input identifying a first subset of the plurality of pages; receiving an input identifying a printing option to be performed on the first subset of the plurality of pages; storing information identifying the printing option to be performed on the first subset of the plurality of pages; and creating instructions for printing the electronic document, said instructions comprising instructions for implementing the selected printing option in connection with the first subset of the plurality of pages; wherein receiving an input identifying a printing option to be performed on the first subset of the plurality of pages comprises receiving an input identifying a printing option relating to at least one of the following: grouping documents; splitting documents into subsets; controlling the sequence of printing of documents; selecting a normal media; selecting an exception media; identifying page level override of the normal media; identifying finishing parameters for a document; identifying finishing parameters for a subset; identifying finishing parameters for a group; selecting simplex printing for a document; selecting simplex printing for a subset; selecting simplex printing for a group; inserting tabs between pages; inserting tabs between documents; printing on tabs; inserting sheets between pages; inserting sheets between documents; and inserting covers. | 8. A method of printing electronic documents implemented at least in part on a computing system, comprising: identifying a plurality of pages comprised in an electronic document; receiving an input identifying a first subset of the plurality of pages; receiving an input identifying a printing option to be performed on the first subset of the plurality of pages; storing information identifying the printing option to be performed on the first subset of the plurality of pages; and creating instructions for printing the electronic document, said instructions comprising instructions for implementing the selected printing option in connection with the first subset of the plurality of pages; wherein receiving an input identifying a printing option to be performed on the first subset of the plurality of pages comprises receiving an input identifying a printing option relating to at least one of the following: grouping documents; splitting documents into subsets; controlling the sequence of printing of documents; selecting a normal media; selecting an exception media; identifying page level override of the normal media; identifying finishing parameters for a document; identifying finishing parameters for a subset; identifying finishing parameters for a group; selecting simplex printing for a document; selecting simplex printing for a subset; selecting simplex printing for a group; inserting tabs between pages; inserting tabs between documents; printing on tabs; inserting sheets between pages; inserting sheets between documents; and inserting covers. 13. The method of claim 8 , wherein receiving an input identifying a printing option to be performed on the first subset comprises receiving an input identifying inserting a separation sheet between the subset of the plurality of pages and adjacent pages in the electronic document. | 0.881711 |
7,672,922 | 2 | 8 | 2. The pointer-oriented object acquisition method according to claim 1 , characterized in that a third pointer on the vocabulary of the computer system in which the RAM (Random Access Memory) address (of memory area in which each word of the vocabulary of the computer system of Artificial Intelligence of a cyborg or an android is mapped, or rather is stored) of each parsed word of the associative object, or rather of the association, is stored together with the RAM address of the word that contains the abstract information of the parsed word in the context to the entire associative object is substantiated and treated tangibly in the one natural language by the pointer-oriented object acquisition method at run-time as an abstract object (as a corresponding thought of this computer system of Artificial Intelligence of a cyborg or an android), in a way of the thinking paradigm of the programming language C++, as in instancing an object on the Heap (the freely available memory storage area by dynamic memory allocation). | 2. The pointer-oriented object acquisition method according to claim 1 , characterized in that a third pointer on the vocabulary of the computer system in which the RAM (Random Access Memory) address (of memory area in which each word of the vocabulary of the computer system of Artificial Intelligence of a cyborg or an android is mapped, or rather is stored) of each parsed word of the associative object, or rather of the association, is stored together with the RAM address of the word that contains the abstract information of the parsed word in the context to the entire associative object is substantiated and treated tangibly in the one natural language by the pointer-oriented object acquisition method at run-time as an abstract object (as a corresponding thought of this computer system of Artificial Intelligence of a cyborg or an android), in a way of the thinking paradigm of the programming language C++, as in instancing an object on the Heap (the freely available memory storage area by dynamic memory allocation). 8. The pointer-oriented object acquisition method according to claim 2 , characterized in that the diverse parts of a sentence, for example the object, the subject, the predicate, the attributes, the adverbial modifiers, the local modifier, the temporal modifier etc., which consist of several words, are initialized by the computer system of Artificial Intelligence of a cyborg or an android in interpreting with the other variables defined previously and provided with a value. | 0.835282 |
8,503,797 | 35 | 45 | 35. The system of claim 34 , wherein the processing system extracts the physical attributes of the scanned document by cropping and/or rotating the scanned document as needed to create a processed scanned document for feature extraction. | 35. The system of claim 34 , wherein the processing system extracts the physical attributes of the scanned document by cropping and/or rotating the scanned document as needed to create a processed scanned document for feature extraction. 45. The system of claim 35 , wherein the processing system extracts physical attributes of the scanned document by computing a text/nontext ratio of the scanned document. | 0.955544 |
9,047,488 | 24 | 25 | 24. The apparatus of claim 23 , wherein the one or more key attributes are textual terms, and wherein determining, for the relational context corresponding to the selected group, based on personal information data corresponding to the selected persons in the selected group, one or more key attributes in the personal information data, comprises: identifying one or more key terms based on a terms listing data structure specific to the relational context; determining a relative rarity measure for each key term in the one or more key terms based on a relative number of occurrences of the key term within the corpus of personal information data; generating the relative rarity matrix data structure based on the relative rarity measures of the one or more key terms; generating a combinatorial rarity matrix based on the relative rarity matrix, wherein the combinatorial rarity matrix identifies combinations of rare key terms in the one or more key terms and a probability measure of each combination of rare key terms occurring; determining a rarity function based on the combinatorial rarity matrix, wherein the rarity function defines a border between rare combinations of terms and common combinations of terms within the relational context; and selecting the selected key attributes for anonymization based on the rarity function. | 24. The apparatus of claim 23 , wherein the one or more key attributes are textual terms, and wherein determining, for the relational context corresponding to the selected group, based on personal information data corresponding to the selected persons in the selected group, one or more key attributes in the personal information data, comprises: identifying one or more key terms based on a terms listing data structure specific to the relational context; determining a relative rarity measure for each key term in the one or more key terms based on a relative number of occurrences of the key term within the corpus of personal information data; generating the relative rarity matrix data structure based on the relative rarity measures of the one or more key terms; generating a combinatorial rarity matrix based on the relative rarity matrix, wherein the combinatorial rarity matrix identifies combinations of rare key terms in the one or more key terms and a probability measure of each combination of rare key terms occurring; determining a rarity function based on the combinatorial rarity matrix, wherein the rarity function defines a border between rare combinations of terms and common combinations of terms within the relational context; and selecting the selected key attributes for anonymization based on the rarity function. 25. The apparatus of claim 24 , wherein the instructions cause the processor to determine a rarity function at least by: performing a linear regression operation on the combinatorial rarity matrix to generate a linear regression graph in which data points correspond to terms or combinations of terms in the combinatorial rarity matrix; generating a linear predictor function based on the linear regression graph and a cost function; and shifting the linear predictor function to better fit data points having a higher rarity weight in the linear regression graph while maintaining a cost value of the cost function equal to or below a maximum cost value, to thereby generate the rarity function. | 0.500717 |
8,793,119 | 13 | 16 | 13. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: at each turn in a dialog, nominating via a processor, using a partially observable Markov decision process in parallel with a conventional dialog process, a set of allowed dialog actions and a set of contextual features; outputting allowed dialog actions from the conventional dialog process to the partially observable Markov decision process; selecting an optimal action from the set of allowed dialog actions using a machine learning algorithm to yield a selected optimal action; generating a response based on the selected optimal action at each turn in the dialog. | 13. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: at each turn in a dialog, nominating via a processor, using a partially observable Markov decision process in parallel with a conventional dialog process, a set of allowed dialog actions and a set of contextual features; outputting allowed dialog actions from the conventional dialog process to the partially observable Markov decision process; selecting an optimal action from the set of allowed dialog actions using a machine learning algorithm to yield a selected optimal action; generating a response based on the selected optimal action at each turn in the dialog. 16. The computer-readable storage device of claim 13 , wherein the set of manually nominated allowed dialog actions incorporates a set of business rules. | 0.552632 |
7,577,643 | 9 | 10 | 9. The media of claim 8 , wherein normalizing the score includes determining a maximum number of search results provided by a search engine that receives the key phrase as a search term. | 9. The media of claim 8 , wherein normalizing the score includes determining a maximum number of search results provided by a search engine that receives the key phrase as a search term. 10. The media of claim 9 , further comprising augmenting the score based on a search engine rank assigned to webpage results associated with the key phrase. | 0.939441 |
9,734,193 | 18 | 21 | 18. A system comprising: an electronic device having: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a textual representation of user speech; identifying a candidate named entity from the textual representation of user speech, wherein the candidate named entity is associated with a plurality of saliency scores, each saliency score of the plurality of saliency scores representing a relationship strength between the candidate named entity and a respective domain of a plurality of domains; determining possible parts of speech of the candidate named entity; determining whether the possible parts of speech of the candidate named entity comprises one or more of a predetermined set of parts of speech; in response to determining that the possible parts of speech of the candidate named entity do not comprise one or more of the predetermined set of parts of speech, lowering a saliency score of the plurality of saliency scores associated with the candidate named entity; identifying a domain of the plurality of domains for processing the textual representation of user speech based at least in part on the lowered saliency score associated with the candidate named entity; and performing, by a virtual assistant on the electronic device, one or more tasks based on the identified domain to present an output. | 18. A system comprising: an electronic device having: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a textual representation of user speech; identifying a candidate named entity from the textual representation of user speech, wherein the candidate named entity is associated with a plurality of saliency scores, each saliency score of the plurality of saliency scores representing a relationship strength between the candidate named entity and a respective domain of a plurality of domains; determining possible parts of speech of the candidate named entity; determining whether the possible parts of speech of the candidate named entity comprises one or more of a predetermined set of parts of speech; in response to determining that the possible parts of speech of the candidate named entity do not comprise one or more of the predetermined set of parts of speech, lowering a saliency score of the plurality of saliency scores associated with the candidate named entity; identifying a domain of the plurality of domains for processing the textual representation of user speech based at least in part on the lowered saliency score associated with the candidate named entity; and performing, by a virtual assistant on the electronic device, one or more tasks based on the identified domain to present an output. 21. The system of claim 18 , wherein the candidate named entity comprises a string of two or more words, and wherein determining possible parts of speech of the candidate named entity comprises determining possible parts of speech of a last word of the string of two or more words. | 0.733397 |
8,767,825 | 16 | 23 | 16. A method for providing an adaptive video transcoding framework for a video hosting service, the method comprising: estimating video coding complexity of a source video, the source video having a plurality of coding parameters and a first resolution; training one or more rate-distortion models and scaling models from a plurality of different encoded videos of a video corpus; transcoding the source video based on the estimated video coding complexity of the source video and a target bitrate estimated by rate-distortion models and scaling models trained by a video rate-distortion modeling engine; and determining an optimal resolution for the source video based on the estimated video coding complexity of the source video, and to transcode the source video with the first resolution into an output video with the optimal resolution. | 16. A method for providing an adaptive video transcoding framework for a video hosting service, the method comprising: estimating video coding complexity of a source video, the source video having a plurality of coding parameters and a first resolution; training one or more rate-distortion models and scaling models from a plurality of different encoded videos of a video corpus; transcoding the source video based on the estimated video coding complexity of the source video and a target bitrate estimated by rate-distortion models and scaling models trained by a video rate-distortion modeling engine; and determining an optimal resolution for the source video based on the estimated video coding complexity of the source video, and to transcode the source video with the first resolution into an output video with the optimal resolution. 23. The method of claim 16 , wherein determining an optimal resolution for the source video comprises: receiving the source video having a first video format and a first resolution; obtaining a video coding complexity score of the source video; determining a second resolution of the source video based on the video coding complexity; and encoding the source video into an output video having the second resolution and a predetermined video output format. | 0.860258 |
8,818,100 | 34 | 37 | 34. The system of claim 32 wherein: the subsets module determines the initial subset of rows for each column having more than one character block aligned in that column in the text rows of the at least one document image, each initial subset of rows comprising one or more of the text rows of the at least one document image having at least one alignment of at least one character block in a selected column, each initial subset of rows having a set of columns comprising the selected column and other columns in the one or more text rows of a corresponding initial subset of rows in which the selected column is present; in the optimum set module, each optimum set comprises a most representative set of columns selected from the set of columns of the corresponding initial subset of rows; and in the division module: each final subset of rows comprises at least one of the one or more text rows of the corresponding initial subset of rows having a corresponding physical structure that is most similar to the most representative set of columns of the corresponding optimum set when compared to physical structures of all of the one or more text rows of the corresponding initial subset of rows; each confidence factor measures a similarity of corresponding physical structures of the at least one of the one or more text rows in one corresponding final subset of rows to each other; and each particular text row has at least one confidence factor corresponding to at least one final subset of rows in which the particular text row is an element. | 34. The system of claim 32 wherein: the subsets module determines the initial subset of rows for each column having more than one character block aligned in that column in the text rows of the at least one document image, each initial subset of rows comprising one or more of the text rows of the at least one document image having at least one alignment of at least one character block in a selected column, each initial subset of rows having a set of columns comprising the selected column and other columns in the one or more text rows of a corresponding initial subset of rows in which the selected column is present; in the optimum set module, each optimum set comprises a most representative set of columns selected from the set of columns of the corresponding initial subset of rows; and in the division module: each final subset of rows comprises at least one of the one or more text rows of the corresponding initial subset of rows having a corresponding physical structure that is most similar to the most representative set of columns of the corresponding optimum set when compared to physical structures of all of the one or more text rows of the corresponding initial subset of rows; each confidence factor measures a similarity of corresponding physical structures of the at least one of the one or more text rows in one corresponding final subset of rows to each other; and each particular text row has at least one confidence factor corresponding to at least one final subset of rows in which the particular text row is an element. 37. The system of claim 34 wherein: each corresponding optimum set is represented by a corresponding master row having the set of columns from the corresponding initial subset of rows, each corresponding master row comprising a first indicator in particular columns in the set of columns for the corresponding initial subset of rows that are elements of the corresponding optimum set and a second indicator in other particular columns in the set of columns for the corresponding initial subset of rows that are not elements of the corresponding optimum set; and the division module: splits the one or more text rows in each corresponding initial subset of rows into at least a first group of text rows and a second group of text rows, the first group of text rows comprising the at least one of the one or more text rows, the at least one of the one or more text rows having a smallest distance and a highest matches to the corresponding master row when compared to distances and matches of all of the one or more text rows in the corresponding initial subset of rows, the second group of text rows comprising either no text rows or at least one other text row having a larger distance and a smaller matches to the corresponding master row when compared to the smallest distance and highest matches of the at least one of the one or more text rows; and selects the first group of text rows to be in the final subset of rows. | 0.779839 |
7,711,565 | 46 | 49 | 46. Apparatus adapted to provide information to one or more of a plurality of passengers of a transport apparatus, comprising: first computerized apparatus configured to sample the conversational speech between at least two of said passengers; second computerized apparatus configured to retrieve stored information based on said sampled speech, said stored information being contextually related to at least portions of said sampled speech; and display generation apparatus configured to generate signals relating to at least a portion of said stored information for use on a display device. | 46. Apparatus adapted to provide information to one or more of a plurality of passengers of a transport apparatus, comprising: first computerized apparatus configured to sample the conversational speech between at least two of said passengers; second computerized apparatus configured to retrieve stored information based on said sampled speech, said stored information being contextually related to at least portions of said sampled speech; and display generation apparatus configured to generate signals relating to at least a portion of said stored information for use on a display device. 49. The apparatus of claim 46 , wherein said display device comprises a display device disposed on a personal electronic device (PED) in data communication with said display generation apparatus. | 0.830139 |
9,875,087 | 8 | 9 | 8. A system for staged compilation of a declarative program comprising: a declarative language compiler configured to receive a declarative program as input, and comprising: a parse and semantic check module configured to parse and semantically check the declarative program; a graph generation module configured to compute a strongly connected component graph; a relational algebra machine (RAM) generation module configured to translate the declarative program into a relational algebra machine (RAM) using a modified semi-naïve algorithm, wherein the modified semi-naïve algorithm is a semi-naïve algorithm with modifications comprising unrolling two iterations of a fixed-point loop; and a code generation module configured to: perform a translation of the RAM into code of an imperative programming language to obtain a translated RAM; generate specialized extractor code in the imperative programming language, wherein the specialized extractor code comprises a reduced set of relations extracted from the declarative program; generate query API code in the imperative programming language; compile the translated RAM, the specialized extractor code, and the query API code to obtain a program analysis module; receive a program for analysis; provide the program as input to the program analysis module; extract a plurality of input relations from the program; and perform, using the plurality of input relations, a static program analysis on the program. | 8. A system for staged compilation of a declarative program comprising: a declarative language compiler configured to receive a declarative program as input, and comprising: a parse and semantic check module configured to parse and semantically check the declarative program; a graph generation module configured to compute a strongly connected component graph; a relational algebra machine (RAM) generation module configured to translate the declarative program into a relational algebra machine (RAM) using a modified semi-naïve algorithm, wherein the modified semi-naïve algorithm is a semi-naïve algorithm with modifications comprising unrolling two iterations of a fixed-point loop; and a code generation module configured to: perform a translation of the RAM into code of an imperative programming language to obtain a translated RAM; generate specialized extractor code in the imperative programming language, wherein the specialized extractor code comprises a reduced set of relations extracted from the declarative program; generate query API code in the imperative programming language; compile the translated RAM, the specialized extractor code, and the query API code to obtain a program analysis module; receive a program for analysis; provide the program as input to the program analysis module; extract a plurality of input relations from the program; and perform, using the plurality of input relations, a static program analysis on the program. 9. The system of claim 8 , wherein, after compilation, the program analysis module comprises a program analysis engine, a specialized extractor, and a query API. | 0.943706 |
9,092,723 | 2 | 6 | 2. The method of claim 1 , wherein training of the dynamic string analysis handler in the instructional environment further comprises: receiving a query request from the client application, wherein said query request comprises the string query of the subset and the plurality of contextual metadata associated with the string query of the subset; selecting a string analysis algorithm from a plurality of string analysis algorithms available for use by the string analysis module that best addresses the received query request, wherein said selection utilizes a heuristic strategy; executing the selected string analysis algorithm upon the string query of the subset; conveying results of the execution of the selected string analysis algorithm to the client application; receiving selection feedback having a selection score from the client application for the results of the executed string analysis algorithm, wherein said selection score quantitatively expresses the effectiveness of the selected string analysis algorithm; and when the received selection feedback indicates an unsatisfactory selection of the string analysis algorithm, automatically modifying the heuristic strategy with respect to at least one of the string query of the subset, the plurality of contextual metadata associated with the string query of the subset, and a plurality of selection rules that influence the heuristic strategy. | 2. The method of claim 1 , wherein training of the dynamic string analysis handler in the instructional environment further comprises: receiving a query request from the client application, wherein said query request comprises the string query of the subset and the plurality of contextual metadata associated with the string query of the subset; selecting a string analysis algorithm from a plurality of string analysis algorithms available for use by the string analysis module that best addresses the received query request, wherein said selection utilizes a heuristic strategy; executing the selected string analysis algorithm upon the string query of the subset; conveying results of the execution of the selected string analysis algorithm to the client application; receiving selection feedback having a selection score from the client application for the results of the executed string analysis algorithm, wherein said selection score quantitatively expresses the effectiveness of the selected string analysis algorithm; and when the received selection feedback indicates an unsatisfactory selection of the string analysis algorithm, automatically modifying the heuristic strategy with respect to at least one of the string query of the subset, the plurality of contextual metadata associated with the string query of the subset, and a plurality of selection rules that influence the heuristic strategy. 6. The method of claim 2 , wherein the selection score is calculated using a predefined equation that expresses a culmination of a plurality of metrics used to evaluate the effectiveness of the selected string analysis algorithm. | 0.928033 |
9,153,233 | 8 | 10 | 8. A method for a voice-controlled selection of a media file stored on a data storage unit including a plurality of media files, the media files comprising audio files and including media data and associated file identification data, where the file identification data associated with each audio file includes first phonetic information that corresponds to first phonetic rules for pronouncing an artist and a song title associated with the audio file and second phonetic information that corresponds to second phonetic rules for pronouncing the artist and the song title associated with the audio file, where the first phonetic information and the second phonetic information included in the file identification data are part of the audio file, the method comprising: inputting voice data for selecting one of the media files, the voice data including a static vocabulary and a variable vocabulary, the static vocabulary including a user command and the variable vocabulary including the artist and the song title associated with a desired media file; supplying the voice data to a speech recognition unit; providing a static vocabulary list including phonetic transcriptions of corresponding user commands; extracting the first phonetic information and the second phonetic information from the file identification data; supplying the phonetic transcriptions from the static vocabulary list and the first phonetic information and the second phonetic information extracted from the file identification data to the speech recognition unit as recognition vocabulary; generating a control command by comparing the input voice data to the phonetic transcriptions and the extracted phonetic information; using a media file player to select a media file from the data storage unit in accordance with the generated control command; and executing a user command on the media file in accordance with the generated control command. | 8. A method for a voice-controlled selection of a media file stored on a data storage unit including a plurality of media files, the media files comprising audio files and including media data and associated file identification data, where the file identification data associated with each audio file includes first phonetic information that corresponds to first phonetic rules for pronouncing an artist and a song title associated with the audio file and second phonetic information that corresponds to second phonetic rules for pronouncing the artist and the song title associated with the audio file, where the first phonetic information and the second phonetic information included in the file identification data are part of the audio file, the method comprising: inputting voice data for selecting one of the media files, the voice data including a static vocabulary and a variable vocabulary, the static vocabulary including a user command and the variable vocabulary including the artist and the song title associated with a desired media file; supplying the voice data to a speech recognition unit; providing a static vocabulary list including phonetic transcriptions of corresponding user commands; extracting the first phonetic information and the second phonetic information from the file identification data; supplying the phonetic transcriptions from the static vocabulary list and the first phonetic information and the second phonetic information extracted from the file identification data to the speech recognition unit as recognition vocabulary; generating a control command by comparing the input voice data to the phonetic transcriptions and the extracted phonetic information; using a media file player to select a media file from the data storage unit in accordance with the generated control command; and executing a user command on the media file in accordance with the generated control command. 10. The method of claim 8 , where the step of generating a control command includes the step of comparing a phoneme sequence in the voice data to determine a candidate list of best matching media files and further determining the most likely entry in the candidate list by matching acoustic representations of the entries in the candidate list to the voice data. | 0.501377 |
7,899,846 | 12 | 13 | 12. At a computer system, a method for editing one or more characteristics of a model using a declarative model editor, the method comprising: an act of receiving user input indicating a declarative entry to be applied to a model, the declarative entry comprising one or more user-configurable model editor characteristics configurable by a user for application to one or more models based on a selected native schema, the models being instances of the native schema, the model editor characteristics including one or more characteristics that are not specified by the native underlying schema and that customize the model editor for editing a selected model; an act of generating a declarative model editor based on the declarative entry; an act of receiving a model, the model being editable by the generated declarative model editor; and an act of editing one or more user-configurable characteristics of the model, wherein the model characteristics conform to the constraints in the native underlying schema. | 12. At a computer system, a method for editing one or more characteristics of a model using a declarative model editor, the method comprising: an act of receiving user input indicating a declarative entry to be applied to a model, the declarative entry comprising one or more user-configurable model editor characteristics configurable by a user for application to one or more models based on a selected native schema, the models being instances of the native schema, the model editor characteristics including one or more characteristics that are not specified by the native underlying schema and that customize the model editor for editing a selected model; an act of generating a declarative model editor based on the declarative entry; an act of receiving a model, the model being editable by the generated declarative model editor; and an act of editing one or more user-configurable characteristics of the model, wherein the model characteristics conform to the constraints in the native underlying schema. 13. The method of claim 12 , wherein the editing comprises selecting declarative functions configured to be applied to the model. | 0.893035 |
7,568,171 | 28 | 29 | 28. The computer program product of claim 25 , wherein moving the element comprises: determining a set of candidate positions for which a projection of the axis onto screen space is located on the screen space from the starting point to the ending point of the stroke; and selecting a candidate position from the set based at least in part on the direction of the stroke. | 28. The computer program product of claim 25 , wherein moving the element comprises: determining a set of candidate positions for which a projection of the axis onto screen space is located on the screen space from the starting point to the ending point of the stroke; and selecting a candidate position from the set based at least in part on the direction of the stroke. 29. The computer program product of claim 28 , wherein the position of the element in scene space is further definable by an orientation about the axis, and positioning the element further comprises: determining the orientation of the element based at least in part on the curvature of the stroke. | 0.897018 |
9,507,832 | 1 | 2 | 1. A method of identifying content items ordered based on microgenres of desired content items, the method comprising: receiving, at a server, from a client device of a user, through the user interfacing with a video consumption application that is executed at the client device, an input identifying a desired content item of a plurality of content items, wherein each content item of the plurality of content items is associated with: a respective genre that broadly characterizes the respective content item, a respective microgenre that, with respect to the respective genre, narrowly characterizes the respective content item, and a respective relevance value that indicates how relevant the respective content item is to the user; causing to be stored, at a database, an entry associated with a microgenre of the desired content item in a data structure associated with a profile of the user; identifying, based on the profile of the user, a subset of the plurality of content items, wherein the respective microgenre associated with each content item of the subset comprises the microgenre of the desired content item; increasing the respective relevance value associated with each content item of the subset; ranking each content item of the plurality of content items in an order reflecting the respective relevance value associated with each content item of the plurality of content items; and causing the client device to, using the video consumption application, generate a display based on the order. | 1. A method of identifying content items ordered based on microgenres of desired content items, the method comprising: receiving, at a server, from a client device of a user, through the user interfacing with a video consumption application that is executed at the client device, an input identifying a desired content item of a plurality of content items, wherein each content item of the plurality of content items is associated with: a respective genre that broadly characterizes the respective content item, a respective microgenre that, with respect to the respective genre, narrowly characterizes the respective content item, and a respective relevance value that indicates how relevant the respective content item is to the user; causing to be stored, at a database, an entry associated with a microgenre of the desired content item in a data structure associated with a profile of the user; identifying, based on the profile of the user, a subset of the plurality of content items, wherein the respective microgenre associated with each content item of the subset comprises the microgenre of the desired content item; increasing the respective relevance value associated with each content item of the subset; ranking each content item of the plurality of content items in an order reflecting the respective relevance value associated with each content item of the plurality of content items; and causing the client device to, using the video consumption application, generate a display based on the order. 2. The method of claim 1 , wherein the input is a first input, wherein the desired content item is a first desired content item, wherein the entry is a first entry, and wherein the method further comprises: receiving, at the server, from the client device, a second input identifying a second desired content item of the plurality of content items; and causing to be stored, at the database, a second entry associated with a microgenre of the second desired content item in the data structure associated with the profile of the user, wherein the data structure includes data relating to historically desired content items of the user. | 0.557263 |
7,580,903 | 1 | 8 | 1. A means for creating optimized elements of a device, comprising: (a) selecting an equation or set equations that models the behavior of the elements of a device; (b) selecting a range for each input variable in said equation or set of equations; (c) selecting the number of trials; (d) selecting the logical distribution function of each of the said input variables; (e) selecting at least two fuzzy level boundaries for each of the said phenomenon; (f) generating values for all of said input variables of all of said trials, within said input variable's said range and within said logical distribution, using Monte Carlo simulations; (g) solving said equation or equations to produce outputs to produce a Meta Model; (h) increasing or decreasing the generated values of one of said input variables by fixed increments for each of said trials; (i) solving said equation or equations using the incremented or decremented values of one of said input values; (j) identifying the fuzzy level placement within said fuzzy level boundary for each of said outputs generated using said incremented or decremented input values for each of said trials; (k) calculating the probability of said fuzzy level placement for one of said outputs by dividing the number of said outputs at each of the said fuzzy levels by the number of said trials; (l) categorizing said fuzzy level placements for said output as indicating a positive or negative correlation; (m) categorizing the magnitude of said fuzzy level placement when there are more than two of the said fuzzy level boundaries; (n) repeating the process steps h through m for each of the remaining input variables; (o) mapping said correlations and said probabilities of the relationships between said input variables and phenomena in the form of a fuzzy cognitive map; and (p) adjusting the characteristics of said elements of said device, in accordance with said fuzzy cognitive map. | 1. A means for creating optimized elements of a device, comprising: (a) selecting an equation or set equations that models the behavior of the elements of a device; (b) selecting a range for each input variable in said equation or set of equations; (c) selecting the number of trials; (d) selecting the logical distribution function of each of the said input variables; (e) selecting at least two fuzzy level boundaries for each of the said phenomenon; (f) generating values for all of said input variables of all of said trials, within said input variable's said range and within said logical distribution, using Monte Carlo simulations; (g) solving said equation or equations to produce outputs to produce a Meta Model; (h) increasing or decreasing the generated values of one of said input variables by fixed increments for each of said trials; (i) solving said equation or equations using the incremented or decremented values of one of said input values; (j) identifying the fuzzy level placement within said fuzzy level boundary for each of said outputs generated using said incremented or decremented input values for each of said trials; (k) calculating the probability of said fuzzy level placement for one of said outputs by dividing the number of said outputs at each of the said fuzzy levels by the number of said trials; (l) categorizing said fuzzy level placements for said output as indicating a positive or negative correlation; (m) categorizing the magnitude of said fuzzy level placement when there are more than two of the said fuzzy level boundaries; (n) repeating the process steps h through m for each of the remaining input variables; (o) mapping said correlations and said probabilities of the relationships between said input variables and phenomena in the form of a fuzzy cognitive map; and (p) adjusting the characteristics of said elements of said device, in accordance with said fuzzy cognitive map. 8. A means for creating optimized elements of a device as in claim 1 , wherein adjusting the characteristics of said elements of said device, in accordance with said fuzzy cognitive map, is done by changing the dimensions of a part of a device. | 0.504065 |
9,129,227 | 9 | 10 | 9. A system for recommending content items, the system comprising: a hardware processor that: determines a plurality of accessed content items associated with a user, wherein each of a plurality of content items is associated with a plurality of topics; determines the plurality of topics associated with each of the plurality of accessed content items; generates a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics and wherein the model of user interests is generated by: retrieving a user interest profile that includes the plurality of topics associated with the plurality of content items accessed by the user and a plurality of other user interest profiles; generating a decision tree, wherein a portion of the decision tree identifies which of the plurality of other user interest profiles are similar to the user interest profile; determining a subset of the plurality of topics corresponding to the user interest profile and the similar user interest profiles in the portion of the decision tree; and determining a conjunction that models interaction between the subset of the plurality of topics and the plurality of content items; applies the model to determine, for the plurality of content items, a probability that the user watches a content item of the plurality of content items; ranks the plurality of content items based on the determined probability; and selects a subset of the plurality of content items to recommend to the user based on the ranked plurality of content items. | 9. A system for recommending content items, the system comprising: a hardware processor that: determines a plurality of accessed content items associated with a user, wherein each of a plurality of content items is associated with a plurality of topics; determines the plurality of topics associated with each of the plurality of accessed content items; generates a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics and wherein the model of user interests is generated by: retrieving a user interest profile that includes the plurality of topics associated with the plurality of content items accessed by the user and a plurality of other user interest profiles; generating a decision tree, wherein a portion of the decision tree identifies which of the plurality of other user interest profiles are similar to the user interest profile; determining a subset of the plurality of topics corresponding to the user interest profile and the similar user interest profiles in the portion of the decision tree; and determining a conjunction that models interaction between the subset of the plurality of topics and the plurality of content items; applies the model to determine, for the plurality of content items, a probability that the user watches a content item of the plurality of content items; ranks the plurality of content items based on the determined probability; and selects a subset of the plurality of content items to recommend to the user based on the ranked plurality of content items. 10. The system of claim 9 , wherein the plurality of content items includes one of: a plurality of video content items and a channel that provides the plurality of video content items. | 0.868195 |
9,195,642 | 3 | 4 | 3. A system for spell checking URLs in a resource, the system comprising a computer processor and a computer memory operatively coupled to the computer processor, the computer memory including computer program instructions that, when executed by the computer processor, cause the system to carry out the steps of: identifying, within a resource, a URL; determining whether the URL is valid, including determining whether a domain name contained in the URL resolves to an Internet Protocol (‘IP’) address; and if the URL is invalid, marking the URL as misspelled to generate a marked URL; suggesting an alternative spelling for the URL and displaying the marked URL; and if the domain name contained in the URL resolves to an Internet Protocol (‘IP’) address, determining whether to suggest an alternative URL, wherein determining whether to suggest an alternative URL further comprise: downloading a resource from a network address identified by URL; and comparing the downloaded resource with the resource containing the URL. | 3. A system for spell checking URLs in a resource, the system comprising a computer processor and a computer memory operatively coupled to the computer processor, the computer memory including computer program instructions that, when executed by the computer processor, cause the system to carry out the steps of: identifying, within a resource, a URL; determining whether the URL is valid, including determining whether a domain name contained in the URL resolves to an Internet Protocol (‘IP’) address; and if the URL is invalid, marking the URL as misspelled to generate a marked URL; suggesting an alternative spelling for the URL and displaying the marked URL; and if the domain name contained in the URL resolves to an Internet Protocol (‘IP’) address, determining whether to suggest an alternative URL, wherein determining whether to suggest an alternative URL further comprise: downloading a resource from a network address identified by URL; and comparing the downloaded resource with the resource containing the URL. 4. The system of claim 3 , wherein the computer program instructions that, when executed by the computer processor, cause the system to carry out the step of suggesting an alternative spelling for the URL further comprise: computer program instructions that, when executed by the computer processor, cause the system to carry out the step of identifying a keyword in the resource; computer program instructions that, when executed by the computer processor, cause the system to carry out the step of querying a search engine with the identified keyword; and computer program instructions that, when executed by the computer processor, cause the system to carry out the step of selecting a URL in dependence upon search results returned by the search engine. | 0.50066 |
9,288,523 | 1 | 4 | 1. A method for one or more computer servers that are communicatively coupled to the Internet and that provide a website for enabling uploading of media content, sorting the media content, and downloading the media content, the method comprising: executing computer program instructions stored in one or more memories with one or more processors associated with the one or more computer servers to perform at least the following: enabling users and producers to set up user accounts on the website; receiving and storing user preference information or user profile information from the users that influences access, at least in part, to media content associated with the website by respective client devices; searching media content on the Internet in order to identify topics; identifying the topics, the topics indicative of relevant news or events, the topics indicative of types of the media content that will be requested for uploading from the producers; determining respective profiles for the producers; selecting a topic for a respective producer based at least in part upon a respective producer profile and the user preference information or the user profile information; publishing the topic to the respective producer; receiving and storing the media content uploaded from the producer that relates to the topic in the one or more memories; and enabling the users to select and download the media content over the Internet from the respective client devices. | 1. A method for one or more computer servers that are communicatively coupled to the Internet and that provide a website for enabling uploading of media content, sorting the media content, and downloading the media content, the method comprising: executing computer program instructions stored in one or more memories with one or more processors associated with the one or more computer servers to perform at least the following: enabling users and producers to set up user accounts on the website; receiving and storing user preference information or user profile information from the users that influences access, at least in part, to media content associated with the website by respective client devices; searching media content on the Internet in order to identify topics; identifying the topics, the topics indicative of relevant news or events, the topics indicative of types of the media content that will be requested for uploading from the producers; determining respective profiles for the producers; selecting a topic for a respective producer based at least in part upon a respective producer profile and the user preference information or the user profile information; publishing the topic to the respective producer; receiving and storing the media content uploaded from the producer that relates to the topic in the one or more memories; and enabling the users to select and download the media content over the Internet from the respective client devices. 4. The method of claim 1 , wherein the executing further performs: communicating an advertisement to a user with the media content. | 0.777211 |
8,612,373 | 1 | 8 | 1. A method for evolving an annotating model for classifying a document or a data item therein, comprising: composing a first concept evolution model as a training set comprised of a first set of selectively determinable class labels of element instances within the document that are detectable within the document to produce a result of predicting class labels to be assigned to unlabeled element instances and the first concept evolution model; training a learning algorithm with the training set and the concept evolution model to generate a trained model wherein the learning algorithm comprises a global approach to reshape a list of the classes and adjusts the set of features, or wherein the learning algorithm comprises a local approach that creates a local model of one or few events, the definition set of classes remains unchanged, and the training set can be extended with new examples; using the trained model to predict class labels for unlabeled element instances within the document; computing a confidence factor for a predicted class label is accurately predicted for unlabeled elements; identifying an unlabeled element instance within the document with a corresponding suggested annotation having a confidence factor less than zero; and adjusting the classifying of the unlabeled element instance wherein a second concept evolution model is composed for more accurate classifying of the document, and wherein the composing and applying are executed by a designer of the annotating model and the computing is machine implemented. | 1. A method for evolving an annotating model for classifying a document or a data item therein, comprising: composing a first concept evolution model as a training set comprised of a first set of selectively determinable class labels of element instances within the document that are detectable within the document to produce a result of predicting class labels to be assigned to unlabeled element instances and the first concept evolution model; training a learning algorithm with the training set and the concept evolution model to generate a trained model wherein the learning algorithm comprises a global approach to reshape a list of the classes and adjusts the set of features, or wherein the learning algorithm comprises a local approach that creates a local model of one or few events, the definition set of classes remains unchanged, and the training set can be extended with new examples; using the trained model to predict class labels for unlabeled element instances within the document; computing a confidence factor for a predicted class label is accurately predicted for unlabeled elements; identifying an unlabeled element instance within the document with a corresponding suggested annotation having a confidence factor less than zero; and adjusting the classifying of the unlabeled element instance wherein a second concept evolution model is composed for more accurate classifying of the document, and wherein the composing and applying are executed by a designer of the annotating model and the computing is machine implemented. 8. The method according to claim 1 , wherein the confidence factor is calculated using the formula: conf me ( x ) = ∑ i P ( y i | x ) log P ( y i | x ) . | 0.551075 |
7,814,109 | 10 | 16 | 10. A system for automated classification of events, said system comprising: at least one database for storing a plurality of keywords and categories associated with said keywords and for storing a set of statistical parameters, based on past analysis of events, for keywords and said categories associated with said keywords, wherein said statistical parameters comprise ambiguity parameter values of said keywords and statistical probabilities that said keywords and said categories dominate one or more other of said keywords and said categories; and an event categorization platform, comprising processor and memory, to receive at least one event, wherein said event comprises on-line activity between said user and said entity and to determine a plurality of event units from said event, said event categorization platform comprising: a token analysis module coupled to said database, said token analysis module to retrieve a plurality of keywords from said database, each retrieved keyword matching a corresponding event unit, to identify a category associated with each of said keywords retrieved, to select a dominant keyword from said keywords retrieved based on said statistical parameters by using said at least one keyword category and an ambiguity parameter value calculated for said each keyword as a factor of a conditional probability that said at least one keyword category is associated with said dominant keyword and to categorize said event based on a category associated with said dominant keyword, wherein said category for said event identifies primary subject matter for said event, wherein said token analysis module is further configured to selecting said dominant keyword based on said at least one keyword category and an ambiguity parameter value; and an ambiguity processing module coupled to said token analysis module, said ambiguity processing module to calculate said ambiguity parameter value for said each keyword as a factor of a conditional probability that said at least one keyword category is associated with said dominant keyword. | 10. A system for automated classification of events, said system comprising: at least one database for storing a plurality of keywords and categories associated with said keywords and for storing a set of statistical parameters, based on past analysis of events, for keywords and said categories associated with said keywords, wherein said statistical parameters comprise ambiguity parameter values of said keywords and statistical probabilities that said keywords and said categories dominate one or more other of said keywords and said categories; and an event categorization platform, comprising processor and memory, to receive at least one event, wherein said event comprises on-line activity between said user and said entity and to determine a plurality of event units from said event, said event categorization platform comprising: a token analysis module coupled to said database, said token analysis module to retrieve a plurality of keywords from said database, each retrieved keyword matching a corresponding event unit, to identify a category associated with each of said keywords retrieved, to select a dominant keyword from said keywords retrieved based on said statistical parameters by using said at least one keyword category and an ambiguity parameter value calculated for said each keyword as a factor of a conditional probability that said at least one keyword category is associated with said dominant keyword and to categorize said event based on a category associated with said dominant keyword, wherein said category for said event identifies primary subject matter for said event, wherein said token analysis module is further configured to selecting said dominant keyword based on said at least one keyword category and an ambiguity parameter value; and an ambiguity processing module coupled to said token analysis module, said ambiguity processing module to calculate said ambiguity parameter value for said each keyword as a factor of a conditional probability that said at least one keyword category is associated with said dominant keyword. 16. The system according to claim 10 , wherein said token analysis module further selects a keyword of a pair of retrieved keywords, said selection based on an output value calculated for said each keyword of said pair of keywords, said selected keyword having a highest-ranked output value, repeats said selecting for at least one subsequent pair of retrieved keywords including said selected keyword to obtain said dominant keyword, and retrieves said at least one category associated with said dominant keyword from said keyword database. | 0.500923 |
9,858,343 | 5 | 6 | 5. The computer-readable data storage device of claim 1 , wherein the agent action comprises performing a task within an application. | 5. The computer-readable data storage device of claim 1 , wherein the agent action comprises performing a task within an application. 6. The computer-readable data storage device of claim 5 , wherein the at least one of the plurality of semantic concepts associated with the ontology comprises a shortcut synonym associated with performing the task within the application. | 0.96028 |
7,496,837 | 22 | 24 | 22. The computer readable medium as defined in claim 21 , wherein: the structured markup language document has a plurality of data entry fields each corresponding to one said markup language node; and each data entry field is used when data is added to or deleted from the structured markup language document using a corresponding said portion of the single maximal information fragment to perform the data entry with the data entry field. | 22. The computer readable medium as defined in claim 21 , wherein: the structured markup language document has a plurality of data entry fields each corresponding to one said markup language node; and each data entry field is used when data is added to or deleted from the structured markup language document using a corresponding said portion of the single maximal information fragment to perform the data entry with the data entry field. 24. The computer readable medium as defined in claim 22 , wherein the method further comprises a step of entering the data from the data entry into a structured markup language file that corresponds to the structured markup language document, wherein each said data entry field has a corresponding field in the structured markup language file. | 0.941825 |
9,691,291 | 1 | 5 | 1. A system for generating student group assignments based on student attributes and student-variable-related criteria and conducting group learning over a network based on the student group assignments, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, program the one or more physical processors to obtain student information about students registered to take a course, wherein, for each student, the student information comprises attributes of the student that correspond to variables of the student; obtain group criteria information associated with the course, wherein the group criteria information comprises first criteria indicating that the students are to be grouped in a manner that they achieve a target level of diversity with respect to a first variable and second criteria indicating that the students are to be grouped in a manner that they achieve a level of similarity with respect to a second variable; assign, based on the attributes, the first criteria, and the second criteria, a first set of the students to a first student group, wherein the first set of the students in the first student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; assign, based on the attributes, the first criteria, and the second criteria, a second set of the students to a second student group, wherein the second set of the students in the second student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; generate an instructor user interface display; provide, through the instructor user interface display, a first display option associated with the first student group, the first display option, when selected, specifies that a first message interface should be displayed on the instructor user interface display, wherein the first message interface display includes one or more first messages exchanged via a first communication channel accessible by the first student group; provide, through the instructor user interface display, a second display option associated with the second student group, the second display option, when selected, specifies that a second message interface should be displayed on the instructor user interface display instead of the first message interface, wherein the second message interface display includes one or more second messages exchanged via a second communication channel accessible by the second student group; receive a selection of the first display option, and cause the first message interface to be displayed on the instructor user interface display in response to the selection of the first display option; and receive a selection of the second display option, and cause the second message interface to be displayed on the instructor user interface display instead of the first message interface display in response to the selection of the second display option. | 1. A system for generating student group assignments based on student attributes and student-variable-related criteria and conducting group learning over a network based on the student group assignments, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, program the one or more physical processors to obtain student information about students registered to take a course, wherein, for each student, the student information comprises attributes of the student that correspond to variables of the student; obtain group criteria information associated with the course, wherein the group criteria information comprises first criteria indicating that the students are to be grouped in a manner that they achieve a target level of diversity with respect to a first variable and second criteria indicating that the students are to be grouped in a manner that they achieve a level of similarity with respect to a second variable; assign, based on the attributes, the first criteria, and the second criteria, a first set of the students to a first student group, wherein the first set of the students in the first student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; assign, based on the attributes, the first criteria, and the second criteria, a second set of the students to a second student group, wherein the second set of the students in the second student group, as a whole, are grouped together to be diverse with respect to the first variable based on the target level of diversity and are grouped together to be similar with respect to the second variable based on the target level of similarity; generate an instructor user interface display; provide, through the instructor user interface display, a first display option associated with the first student group, the first display option, when selected, specifies that a first message interface should be displayed on the instructor user interface display, wherein the first message interface display includes one or more first messages exchanged via a first communication channel accessible by the first student group; provide, through the instructor user interface display, a second display option associated with the second student group, the second display option, when selected, specifies that a second message interface should be displayed on the instructor user interface display instead of the first message interface, wherein the second message interface display includes one or more second messages exchanged via a second communication channel accessible by the second student group; receive a selection of the first display option, and cause the first message interface to be displayed on the instructor user interface display in response to the selection of the first display option; and receive a selection of the second display option, and cause the second message interface to be displayed on the instructor user interface display instead of the first message interface display in response to the selection of the second display option. 5. The system of claim 1 , wherein the first criteria indicates a first preferred number of students having a first attribute corresponding to the first variable and a second preferred number of students having a second attribute corresponding to the first variable. | 0.873574 |
8,612,469 | 1 | 4 | 1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user. | 1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user. 4. The computer-implemented method of claim 1 wherein the storing the first suggestion and position information on the first suggestion in a suggestions database at the server comprises: receiving a first position selected by the first user in a first paragraph; and receiving a second position selected by the first user in the first paragraph. | 0.828869 |
9,444,793 | 32 | 33 | 32. A system for securing data transmitted between a client device and a server comprising: a memory; and a controller configured to: obtain input text sent from the client device to the server; process said input text to obtain processed text, wherein said controller is configured to process said input text by: when the input text is not to be searchable by the server, transforming the input text non-deterministically or a combination of deterministically and non-deterministically, using at least one key, to obtain processed text; and when the input text is to be searchable by the server, transforming said input text deterministically, using at least one key to obtain processed text, and including a statistically significant feature in the processed text, the feature including a rarely used character or group of characters; and transmit the processed text to the server. | 32. A system for securing data transmitted between a client device and a server comprising: a memory; and a controller configured to: obtain input text sent from the client device to the server; process said input text to obtain processed text, wherein said controller is configured to process said input text by: when the input text is not to be searchable by the server, transforming the input text non-deterministically or a combination of deterministically and non-deterministically, using at least one key, to obtain processed text; and when the input text is to be searchable by the server, transforming said input text deterministically, using at least one key to obtain processed text, and including a statistically significant feature in the processed text, the feature including a rarely used character or group of characters; and transmit the processed text to the server. 33. The system of claim 32 , wherein said controller is further configured to determine not to transform at least a portion of the input text. | 0.895126 |
8,098,273 | 11 | 12 | 11. The apparatus of claim 10 , wherein the logic when executed is further operable to: associate the at least one portion of the service call with the indication of the mood of the caller; and store the at least one portion of the service call with the indication of the mood determined for the at least one portion. | 11. The apparatus of claim 10 , wherein the logic when executed is further operable to: associate the at least one portion of the service call with the indication of the mood of the caller; and store the at least one portion of the service call with the indication of the mood determined for the at least one portion. 12. The apparatus of claim 11 , wherein the logic when executed is further operable to: associate a plurality of portions of the service call with a plurality of indications of moods; and analyze the plurality of portions and the indication of the mood associated with each of the plurality of portions to determine which aspects of the plurality of portions of the service call invoked a positive mood or a negative mood. | 0.867379 |
8,014,634 | 22 | 24 | 22. A computer-implemented method comprising: storing a first graphical document; comparing graphical content of the first graphical document to graphical content of a second graphical document by a processor; flagging the first graphical document based on the comparison; providing the flagged first graphical document to one or more evaluator terminals for rating information; and approving or disapproving the flagged first graphical document based on the rating information received from the one or more evaluator terminals by the processor. | 22. A computer-implemented method comprising: storing a first graphical document; comparing graphical content of the first graphical document to graphical content of a second graphical document by a processor; flagging the first graphical document based on the comparison; providing the flagged first graphical document to one or more evaluator terminals for rating information; and approving or disapproving the flagged first graphical document based on the rating information received from the one or more evaluator terminals by the processor. 24. The method of claim 22 , further comprising flagging the first graphical document if the comparison indicates that the first graphical document contains material identified as objectionable. | 0.889396 |
8,812,540 | 1 | 7 | 1. A method comprising: based on first content that has been opened within a content presentation application executing on a client device, the client device automatically selecting context information to submit to a server; responsive to automatically selecting the context information for submission to the server, the client device automatically sending the context information from the client device to the server; responsive to sending the context information to the server, the client device receiving a first search result from the server; responsive to activation input activating a search interface, displaying the search interface; after receiving the activation input, and prior to receiving any user input of a query term via the activated search interface, displaying the first search result within a preview section of the search interface; subsequent to displaying the first search result in the preview section, receiving user input entering one or more query terms via the search interface, the one or more query terms including at least one term that is not found in the context information; sending the one or more query terms to the server; responsive to sending the one or more query terms to the server, the client device receiving a second search result from the server; displaying the second search result in the search interface at the client device. | 1. A method comprising: based on first content that has been opened within a content presentation application executing on a client device, the client device automatically selecting context information to submit to a server; responsive to automatically selecting the context information for submission to the server, the client device automatically sending the context information from the client device to the server; responsive to sending the context information to the server, the client device receiving a first search result from the server; responsive to activation input activating a search interface, displaying the search interface; after receiving the activation input, and prior to receiving any user input of a query term via the activated search interface, displaying the first search result within a preview section of the search interface; subsequent to displaying the first search result in the preview section, receiving user input entering one or more query terms via the search interface, the one or more query terms including at least one term that is not found in the context information; sending the one or more query terms to the server; responsive to sending the one or more query terms to the server, the client device receiving a second search result from the server; displaying the second search result in the search interface at the client device. 7. The method of claim 1 , wherein the client device is a handheld device, the method further comprising: displaying the first content in the content presentation application; providing a particular input key designated for initiating a queryless search based on the first content; wherein the first search result is displayed responsive to receiving input via the particular input key. | 0.694136 |
9,852,731 | 15 | 19 | 15. One or more non-transitory computer-readable storage media storing computer-executable instructions for causing a computing device to: while the computing device is in a low-power state: receive audio input from a user at the computing device; and determine that the audio input comprises a wake phrase; transition the computing device from the low-power state to an active state if the audio input comprises the wake phrase; while the computing device is in the low-power state or the active state: attempt to verify the user based at least in part on a first portion of the audio input comprising the wake phrase; and while the computing device is in the active state: interpret a second portion of the audio input not comprising the wake phrase as a command to launch an application on the computing device; and launch the application at the computing device when the command is a user agnostic command or not launch the application when the command is not a user agnostic command, wherein a user agnostic command comprises a command that does not require identifying information or personal data of the user. | 15. One or more non-transitory computer-readable storage media storing computer-executable instructions for causing a computing device to: while the computing device is in a low-power state: receive audio input from a user at the computing device; and determine that the audio input comprises a wake phrase; transition the computing device from the low-power state to an active state if the audio input comprises the wake phrase; while the computing device is in the low-power state or the active state: attempt to verify the user based at least in part on a first portion of the audio input comprising the wake phrase; and while the computing device is in the active state: interpret a second portion of the audio input not comprising the wake phrase as a command to launch an application on the computing device; and launch the application at the computing device when the command is a user agnostic command or not launch the application when the command is not a user agnostic command, wherein a user agnostic command comprises a command that does not require identifying information or personal data of the user. 19. The one or more computer-readable storage media of claim 15 , further comprising computer-executable instructions for causing the computing device to: interpret a second audio input comprising the wake phrase as a second command to be executed by the computing device; and perform the second command at the computing device. | 0.689981 |
9,740,928 | 14 | 15 | 14. A system for creating digitized text for a record from an image of the record, comprising: one or more processors; and a memory, the memory storing instructions that are executable by the one or more processors and configure the system to: receive multiple word images from one or more records; for each received word image, identify multiple word features of that word image; assign one or more values to each of the multiple word features for each word image in order to create a feature vector associated with that word image; and assign each word image to a word cluster based on its feature vector, wherein each word image is assigned to a word cluster based on its feature vector by: calculating a distance between each one of the multiple word images and every other one of the multiple word images, based on feature vectors associated with those word images; selecting, from among the multiple word images, two of the word images that are closest in distance to each other; and assigning the two of the word images to the word cluster. | 14. A system for creating digitized text for a record from an image of the record, comprising: one or more processors; and a memory, the memory storing instructions that are executable by the one or more processors and configure the system to: receive multiple word images from one or more records; for each received word image, identify multiple word features of that word image; assign one or more values to each of the multiple word features for each word image in order to create a feature vector associated with that word image; and assign each word image to a word cluster based on its feature vector, wherein each word image is assigned to a word cluster based on its feature vector by: calculating a distance between each one of the multiple word images and every other one of the multiple word images, based on feature vectors associated with those word images; selecting, from among the multiple word images, two of the word images that are closest in distance to each other; and assigning the two of the word images to the word cluster. 15. The system of claim 14 , wherein the stored instructions further configure the system to: select a representative word image in the word cluster; select digitized text for the representative word image; and assign the selected digitized text to each of the word images in the word cluster. | 0.652844 |
7,929,772 | 1 | 14 | 1. A method for generating typographical line adapted to generating a plurality of typographical lines of a line of printing words in an image, wherein the line of printing words comprises a plurality of printing characters, the method comprising: using an optical character recognition device to perform the steps of (a) obtaining the image comprising the printing words; (b) scanning the line of printing words and labeling a first edge and a second edge of each printing character in the line of printing words; (c) extracting a first edge reference point of the first edge and a second edge reference point of the second edge of each of the printing characters, respectively; (d) using a least square method to obtain a first straight line asymptotic to the first edge reference points; (e) using the first straight line as a first base line to calculate a vertical distance between each of the second edge reference points and the first base line; (f) using a group converging algorithm to divide the second edge reference points into a first group and a second group according to the vertical distances; (g) using the least square method to obtain a second straight line and a third straight line asymptotic to the first group and the second group of the second edge reference points, respectively; (h) using the second straight line or the third straight line obtained from corresponding first group or second group that has the most reference points as a second base line to calculate a vertical distance between each of the first edge reference point and the second base line; (i) using the group converging algorithm to divide the first edge reference points into a third group and a fourth group according to the vertical distances; (j) using the least square method to obtain a fourth straight line and a fifth straight line asymptotic to the first edge reference points of the third group and the fourth group, respectively; and (k) using the second straight line, the third straight line, the fourth straight line and the fifth straight line as the typographical lines of the printing word line. | 1. A method for generating typographical line adapted to generating a plurality of typographical lines of a line of printing words in an image, wherein the line of printing words comprises a plurality of printing characters, the method comprising: using an optical character recognition device to perform the steps of (a) obtaining the image comprising the printing words; (b) scanning the line of printing words and labeling a first edge and a second edge of each printing character in the line of printing words; (c) extracting a first edge reference point of the first edge and a second edge reference point of the second edge of each of the printing characters, respectively; (d) using a least square method to obtain a first straight line asymptotic to the first edge reference points; (e) using the first straight line as a first base line to calculate a vertical distance between each of the second edge reference points and the first base line; (f) using a group converging algorithm to divide the second edge reference points into a first group and a second group according to the vertical distances; (g) using the least square method to obtain a second straight line and a third straight line asymptotic to the first group and the second group of the second edge reference points, respectively; (h) using the second straight line or the third straight line obtained from corresponding first group or second group that has the most reference points as a second base line to calculate a vertical distance between each of the first edge reference point and the second base line; (i) using the group converging algorithm to divide the first edge reference points into a third group and a fourth group according to the vertical distances; (j) using the least square method to obtain a fourth straight line and a fifth straight line asymptotic to the first edge reference points of the third group and the fourth group, respectively; and (k) using the second straight line, the third straight line, the fourth straight line and the fifth straight line as the typographical lines of the printing word line. 14. The method of generating typographical line according to claim 1 , wherein the first edge reference point and the second edge reference point of each of the printing characters comprise either the center point or end point of the first edge and the second edge of each of the printing characters. | 0.805447 |
4,879,648 | 4 | 6 | 4. A method of selectively desired data sets as claimed in claim 1 wherein one categorical list-and the associated group of data sets represents a control list and each data set therein represents a control command. | 4. A method of selectively desired data sets as claimed in claim 1 wherein one categorical list-and the associated group of data sets represents a control list and each data set therein represents a control command. 6. A method of selectively desired data sets as claimed in claim 4 wherein one control command is a modify selection command and the method further includes changing a displayed and selected data set of one category to a new data set based upon the application of said select control when the data set representing said modify selection command is displayed and selected via said scrolling control and said select control and based upon the application of said select control and said scrolling control to display and select said new data set from said one category. | 0.875877 |
8,554,564 | 12 | 15 | 12. A speech end-pointing method, comprising: receiving an audio stream; analyzing energy and noise characteristics of a frame of the audio stream by a computer processor to determine whether the frame has energy above a background noise level; incrementing an energy counter by a length of the frame in response to a determination by the computer processor that the frame has energy above the background noise level; incrementing a lack of energy counter by the length of the frame in response to a determination by the computer processor that the frame does not have energy above the background noise level; and applying a plurality of rules by the computer processor to detect a beginning and an end of a speech segment of the audio stream based on the energy counter and the lack of energy counter. | 12. A speech end-pointing method, comprising: receiving an audio stream; analyzing energy and noise characteristics of a frame of the audio stream by a computer processor to determine whether the frame has energy above a background noise level; incrementing an energy counter by a length of the frame in response to a determination by the computer processor that the frame has energy above the background noise level; incrementing a lack of energy counter by the length of the frame in response to a determination by the computer processor that the frame does not have energy above the background noise level; and applying a plurality of rules by the computer processor to detect a beginning and an end of a speech segment of the audio stream based on the energy counter and the lack of energy counter. 15. The method of claim 12 , where the step of applying the plurality of rules comprises setting the beginning of the speech segment or the end of the speech segment in response to a determination that the frame has energy above the background noise level and the energy counter is above a continuous non-voiced energy threshold. | 0.777402 |
8,996,622 | 16 | 17 | 16. An apparatus, comprising: a processor; and a memory, at least one of the processor or the memory being adapted for: generating one or more graphs using data obtained from a query log, the one or more graphs including an anticlick graph, wherein the anticlick graph represents a search query and information pertaining to documents in corresponding search results that, according to the data obtained from the query log, have not been clicked by a user that submitted the search query, wherein the anticlick graph does not represent information pertaining to documents in the corresponding search results that, according to the data obtained from the query log, have been clicked by the user that submitted the search query, wherein the anticlick graph includes one or more edges, the one or more edges being between a query and the corresponding search results that, according to the data obtained from the query log, have not been clicked by the user that submitted the query; ascertaining values of one or more syntactic features of the one or more graphs; propagating categories from a web directory among nodes in each of the one or more graphs; determining values of one or more semantic features of the one or more graphs; and detecting spam hosts using the values of the syntactic features and the semantic features; wherein the anti-click graph includes a host-based graph or a document-based graph, wherein the nodes of the host-based graph includes one or more host nodes representing hosts corresponding to the documents that, according to the data obtained from the query log, have not been clicked by the user that submitted the corresponding search query, and wherein the nodes of the document-based graph includes one or more document nodes representing the documents that, according to the data obtained from the query log, have not been clicked by the user that submitted the corresponding search query. | 16. An apparatus, comprising: a processor; and a memory, at least one of the processor or the memory being adapted for: generating one or more graphs using data obtained from a query log, the one or more graphs including an anticlick graph, wherein the anticlick graph represents a search query and information pertaining to documents in corresponding search results that, according to the data obtained from the query log, have not been clicked by a user that submitted the search query, wherein the anticlick graph does not represent information pertaining to documents in the corresponding search results that, according to the data obtained from the query log, have been clicked by the user that submitted the search query, wherein the anticlick graph includes one or more edges, the one or more edges being between a query and the corresponding search results that, according to the data obtained from the query log, have not been clicked by the user that submitted the query; ascertaining values of one or more syntactic features of the one or more graphs; propagating categories from a web directory among nodes in each of the one or more graphs; determining values of one or more semantic features of the one or more graphs; and detecting spam hosts using the values of the syntactic features and the semantic features; wherein the anti-click graph includes a host-based graph or a document-based graph, wherein the nodes of the host-based graph includes one or more host nodes representing hosts corresponding to the documents that, according to the data obtained from the query log, have not been clicked by the user that submitted the corresponding search query, and wherein the nodes of the document-based graph includes one or more document nodes representing the documents that, according to the data obtained from the query log, have not been clicked by the user that submitted the corresponding search query. 17. The apparatus as recited in claim 16 , wherein the one or more semantic features comprise one or more measures of dispersion of each document node or host node in the one or more graphs. | 0.84375 |
9,317,513 | 6 | 10 | 6. A system for producing a content database, the system comprising: a processor; a content manager engine for execution by the processor, the content manager engine configured to: extract content from a first document by removing metadata and formatting of the first document; divide the extracted content into at least first and second content fragments; store the first content fragment as a first entry and the second content fragment as a second entry in the content database; produce a first document mapping that maps to the first and second entries in the content database; store the first document mapping to a document mapping data structure; insert, in response to a first request, the first and second content fragments into a new document based on the first document mapping; receive a modification to the new document, wherein the modification to the new document includes a modified first content fragment received over a computer network, the modified first content fragment having at least one image or character of text that differs from the first content fragment; storing the modified first content fragment as the first entry in the content database; and inserting, in response to a second request, the modified first content fragment and the second content fragment into a modified document based on the first document mapping. | 6. A system for producing a content database, the system comprising: a processor; a content manager engine for execution by the processor, the content manager engine configured to: extract content from a first document by removing metadata and formatting of the first document; divide the extracted content into at least first and second content fragments; store the first content fragment as a first entry and the second content fragment as a second entry in the content database; produce a first document mapping that maps to the first and second entries in the content database; store the first document mapping to a document mapping data structure; insert, in response to a first request, the first and second content fragments into a new document based on the first document mapping; receive a modification to the new document, wherein the modification to the new document includes a modified first content fragment received over a computer network, the modified first content fragment having at least one image or character of text that differs from the first content fragment; storing the modified first content fragment as the first entry in the content database; and inserting, in response to a second request, the modified first content fragment and the second content fragment into a modified document based on the first document mapping. 10. The system of claim 6 , wherein each content fragment comprises a predetermined amount of data. | 0.8213 |
8,140,549 | 21 | 23 | 21. A computer program product for performing operations via a spreadsheet, the computer program product comprising: program instructions, stored on at least one of the one or more storage devices, to create in the spreadsheet a named array object of three or more dimensions; program instructions, stored on at least one of the one or more storage devices, to access elements of the named array object of three or more dimensions, wherein: the multidimensional array object comprise a set of values, one value for each distinct list of coordinates of the multidimensional array object, the list of coordinates comprising a coordinate for each dimension of the multidimensional array object; and the accessing comprises: displaying the elements of the array object as cells of the spreadsheet; and referencing the array object by name in an expression entered into a text-based interface of the spreadsheet, the expression including the name of the array object; and program instructions, stored on at least one of the one or more storage devices, to modify elements of the array object via modifying the contents of the cells of the spreadsheet. | 21. A computer program product for performing operations via a spreadsheet, the computer program product comprising: program instructions, stored on at least one of the one or more storage devices, to create in the spreadsheet a named array object of three or more dimensions; program instructions, stored on at least one of the one or more storage devices, to access elements of the named array object of three or more dimensions, wherein: the multidimensional array object comprise a set of values, one value for each distinct list of coordinates of the multidimensional array object, the list of coordinates comprising a coordinate for each dimension of the multidimensional array object; and the accessing comprises: displaying the elements of the array object as cells of the spreadsheet; and referencing the array object by name in an expression entered into a text-based interface of the spreadsheet, the expression including the name of the array object; and program instructions, stored on at least one of the one or more storage devices, to modify elements of the array object via modifying the contents of the cells of the spreadsheet. 23. The computer program product of claim 21 , wherein the program instructions to create comprise program instructions to create a workbook, the workbook comprising the named array object of three or more dimensions and one or more other array elements, wherein one or more cells of the workbook contain values of objects other than the named array object and the one or more other array elements. | 0.750627 |
5,579,416 | 13 | 14 | 13. An apparatus according to claim 8, further comprising means for instructing said display means to display one of the inputted characters and the graphic patterns corresponding to the character patterns at one time. | 13. An apparatus according to claim 8, further comprising means for instructing said display means to display one of the inputted characters and the graphic patterns corresponding to the character patterns at one time. 14. An apparatus according to claim 13, wherein the parameters comprise information for modifying inputted characters. | 0.962131 |
8,449,451 | 2 | 3 | 2. The method of claim 1 , wherein the pleasuring device is signaled using one of wired communications and wireless communications. | 2. The method of claim 1 , wherein the pleasuring device is signaled using one of wired communications and wireless communications. 3. The method of claim 2 , wherein the wireless communications are transmitted using Bluetooth technology. | 0.959634 |
9,268,880 | 1 | 14 | 1. A computer implemented method, comprising: identifying an association of a user to a provided media file, wherein the provided media file is available to the user for consumption; identifying an aspect of the provided media file, wherein the aspect is a specific attribute of the provided media file; identifying a search query entered by the user; identifying a plurality of query suggestions, wherein the query suggestions are based on the search query; determining, based on identifying the association of the user to the provided media file, a similarity between one or more of the query suggestions and the aspect of the provided media file; and selecting one or more of the query suggestions to provide to the user, wherein a given query suggestion of the query suggestions is selected based on the similarity between the given query suggestion and the aspect; wherein selecting the given query suggestion to provide to the user is further based on a difference between a time interval and a threshold time period, wherein the time interval is based on the time between the user being provided the media file or consuming the media file and the user entering the search query, and wherein the threshold time period is dependent on a type of media of the provided media file. | 1. A computer implemented method, comprising: identifying an association of a user to a provided media file, wherein the provided media file is available to the user for consumption; identifying an aspect of the provided media file, wherein the aspect is a specific attribute of the provided media file; identifying a search query entered by the user; identifying a plurality of query suggestions, wherein the query suggestions are based on the search query; determining, based on identifying the association of the user to the provided media file, a similarity between one or more of the query suggestions and the aspect of the provided media file; and selecting one or more of the query suggestions to provide to the user, wherein a given query suggestion of the query suggestions is selected based on the similarity between the given query suggestion and the aspect; wherein selecting the given query suggestion to provide to the user is further based on a difference between a time interval and a threshold time period, wherein the time interval is based on the time between the user being provided the media file or consuming the media file and the user entering the search query, and wherein the threshold time period is dependent on a type of media of the provided media file. 14. The method of claim 1 , wherein selecting the given query suggestion to provide to the user is further based on an overall popularity of the media file. | 0.924638 |
8,799,265 | 1 | 13 | 1. A text index, comprising a data structure stored in a memory for access by at least one application program being executed on a data processing system, for use in the preparation of semantically associated text searches of electronic documents in a search engine, said text index comprising: one or more content records corresponding to an electronic document, the content records identifying one or more text terms present within the electronic document; one or more term association records associating a text term present within the electronic document identified by a content record with a pre-determined semantic definition of the text term; one or more content association records linking a term association record of the one or more term association records with a content record of the one or more content records; wherein a user is enabled to provide one or more user-defined text search terms desired to be located within the text index; wherein, for user-defined text search terms having term association records within the search index, the user is iteratively presented a list of one or more pre-determined semantic definitions associated with each of the one or more user-defined text search terms, enabling the user to select a pre-determined semantic definition of those one or more user-defined text search terms; wherein the one or more content association records contained within the text index are searched using the user-defined text search terms to locate electronic documents previously catalogued as containing the one or more user-defined text search terms in association with the selected pre-determined semantic definitions, to form a semantically relevant results set; wherein new term association records are updated or created during the use of the text index by enabling a user to select pre-determined semantic definitions for association with user-defined text search terms; and wherein new content association records are updated or created during the use of the text index in a search, by associating a particular electronic document with the use-defined text search terms, and selected pre-determined semantic definitions of the user-defined text search terms, used to locate the particular electronic document. | 1. A text index, comprising a data structure stored in a memory for access by at least one application program being executed on a data processing system, for use in the preparation of semantically associated text searches of electronic documents in a search engine, said text index comprising: one or more content records corresponding to an electronic document, the content records identifying one or more text terms present within the electronic document; one or more term association records associating a text term present within the electronic document identified by a content record with a pre-determined semantic definition of the text term; one or more content association records linking a term association record of the one or more term association records with a content record of the one or more content records; wherein a user is enabled to provide one or more user-defined text search terms desired to be located within the text index; wherein, for user-defined text search terms having term association records within the search index, the user is iteratively presented a list of one or more pre-determined semantic definitions associated with each of the one or more user-defined text search terms, enabling the user to select a pre-determined semantic definition of those one or more user-defined text search terms; wherein the one or more content association records contained within the text index are searched using the user-defined text search terms to locate electronic documents previously catalogued as containing the one or more user-defined text search terms in association with the selected pre-determined semantic definitions, to form a semantically relevant results set; wherein new term association records are updated or created during the use of the text index by enabling a user to select pre-determined semantic definitions for association with user-defined text search terms; and wherein new content association records are updated or created during the use of the text index in a search, by associating a particular electronic document with the use-defined text search terms, and selected pre-determined semantic definitions of the user-defined text search terms, used to locate the particular electronic document. 13. A method of serving of semantically refined advertising content in websites, wherein a text index in accordance with claim 1 is used to identify semantically relevant advertising content, wherein the advertising content pieces are selected from the electronic documents indexed within the text index, and the text search terms used to identify semantically relevant advertising material are captured from user input or behavior on each respective website. | 0.721481 |
8,555,182 | 12 | 13 | 12. The method recited in claim 8 , wherein said step (f) of positioning the results in ranked order on the graphical user interface comprises the step of reordering the results displayed in the priority positions upon a repositioning of a search term relative to the reference position. | 12. The method recited in claim 8 , wherein said step (f) of positioning the results in ranked order on the graphical user interface comprises the step of reordering the results displayed in the priority positions upon a repositioning of a search term relative to the reference position. 13. The method recited in claim 12 , wherein said step of reordering the results displayed in the priority positions upon a repositioning of a search term relative to the reference position occurs without performing a new search of the database. | 0.934667 |
9,367,605 | 10 | 20 | 10. The one or more tangible computer-readable storage media of claim 9 , wherein the identifying the plurality of portions within the respective document comprises: traversing, by the computing device, at least one word in the forward index of the respective document; recording, by the computing device, the at least one traversed word and a location of the at least one traversed word in a first data structure by using the location of the traversed word as an index of the first data structure; and when the at least one traversed word matches one of the keywords, recording, by the computing device, the at least one traversed word and the location of the at least one traversed word in a second data structure by using the at least one traversed word as an index of the second data structure. | 10. The one or more tangible computer-readable storage media of claim 9 , wherein the identifying the plurality of portions within the respective document comprises: traversing, by the computing device, at least one word in the forward index of the respective document; recording, by the computing device, the at least one traversed word and a location of the at least one traversed word in a first data structure by using the location of the traversed word as an index of the first data structure; and when the at least one traversed word matches one of the keywords, recording, by the computing device, the at least one traversed word and the location of the at least one traversed word in a second data structure by using the at least one traversed word as an index of the second data structure. 20. The one or more tangible computer-readable storage media of claim 10 , wherein the finding the portion among the plurality of portions comprises: determining, by the computing device, the beginning position of the portion and the ending position of the portion according to the first data structure, the second data structure, and the length limit, the determining including: in response to determining that a total length of traversed words in the first data structure is less than the length limit, setting the beginning position to a location of a first traversed word in the first data structure and setting the ending position to a location of a last traversed word in the first data structure; or in response to determining that the total length of traversed words in the first data structure is not less than the length limit, utilizing the second data structure to determine one or more portions of the respective document that have lengths less than the length limit, to determine the portion of the one or more portions that has the highest number of the one or more keywords, and to set the beginning position and ending position of the portion based on the locations of a first traversed word and a last traversed word, respectively, in the portion. | 0.775948 |
7,962,490 | 5 | 12 | 5. The method of claim 1 , further comprising determining if the plurality of contexts includes at least one duplicate context. | 5. The method of claim 1 , further comprising determining if the plurality of contexts includes at least one duplicate context. 12. The method of claim 5 , further comprising removing the at least one duplicate context from the plurality of contexts prior to the storing of the plurality of contexts, if it is determined that the plurality of contexts includes the at least one duplicate context. | 0.933762 |
10,042,880 | 4 | 12 | 4. A computing system comprising: at least one processor; and a memory including instructions operable to be executed by the at least one processor to configure the computing system to: process a first electronic document to determine a first block and a second block, each block constituting a logical entity within the first electronic document; categorize portions of the first block to identify a first title portion and a first body-text portion; determine a first plurality of features from the first block, wherein the first plurality of features relate, at least in part, to the first body-text portion; provide the first plurality of features from the first block to a first classifier, the first classifier to identify whether the first block is likely to be where a hypothetical person would begin reading the first electronic document; determine, based on a first score output by the first classifier in response to the first plurality of features, that the first block is not likely to be where the hypothetical person would begin reading the electronic document; categorize portions of the second block to identify a second title, a second title portion and a second body-text portion; determine a second plurality of features from a second block, wherein the second plurality of features relate, at least in part, to the second body-text portion; provide the second plurality of features to the first classifier; determine, based on a second score output by the first classifier in response to the second plurality of features, that the second block is likely to be where the hypothetical person would begin reading the first electronic document; and generate data for the first electronic document to indicate a start-of-reading location to a document output device, used to access the first electronic document, to output the second block upon initially opening the first electronic document. | 4. A computing system comprising: at least one processor; and a memory including instructions operable to be executed by the at least one processor to configure the computing system to: process a first electronic document to determine a first block and a second block, each block constituting a logical entity within the first electronic document; categorize portions of the first block to identify a first title portion and a first body-text portion; determine a first plurality of features from the first block, wherein the first plurality of features relate, at least in part, to the first body-text portion; provide the first plurality of features from the first block to a first classifier, the first classifier to identify whether the first block is likely to be where a hypothetical person would begin reading the first electronic document; determine, based on a first score output by the first classifier in response to the first plurality of features, that the first block is not likely to be where the hypothetical person would begin reading the electronic document; categorize portions of the second block to identify a second title, a second title portion and a second body-text portion; determine a second plurality of features from a second block, wherein the second plurality of features relate, at least in part, to the second body-text portion; provide the second plurality of features to the first classifier; determine, based on a second score output by the first classifier in response to the second plurality of features, that the second block is likely to be where the hypothetical person would begin reading the first electronic document; and generate data for the first electronic document to indicate a start-of-reading location to a document output device, used to access the first electronic document, to output the second block upon initially opening the first electronic document. 12. The computing system of claim 4 , the memory further comprises instructions that further configure the computing system to: provide the second plurality of features from the second block to a second classifier, the first classifier and the second classifier using different classifier models, wherein the instructions to determine that the second block is likely to be where the hypothetical person would begin reading the first electronic document further base the determination on a third score output by the second classifier in response to the second plurality of features. | 0.708918 |
7,676,851 | 1 | 17 | 1. A headwear piece comprising: a crown defining an opening into which a wearer's head can be directed; and a brim/bill projecting away from the crown, the crown having an inside surface for engaging a wearer's head directed into the opening to thereby maintain the headwear piece in an operative position upon the wearer's head, the crown and brim/bill further having an exposed outside surface to which ornamentation is applied, the ornamentation comprising bullion wire that is applied to the exposed outside surface so as to define at least a part of a viewable component that comprises at least one of: a) a scene; b) a logo; c) a design; d) a word; e) a letter; and f) a depiction of a: i) person; ii) place; and/or iii) thing, wherein the ornamentation comprises a discrete shape with an area bounded by a border, and the ornamentation comprises: a) wire that is at least one of bullion wire and non-bullion wire applied in a first pattern comprising substantially straight, substantially parallel, adjacent lengths of the at least one of bullion wire and non-bullion wire within the area bounded by the border that collectively contiguously cover a substantial portion of the area bounded by the border; and b) bullion wire applied in a second pattern comprising substantially straight, substantially parallel, adjacent lengths of bullion wire within the area bounded by the border and overlying the first pattern, wherein the lengths of bullion wire in the second pattern are transverse to the lengths of wire in the first pattern and collectively contiguously cover a substantial portion of the area bounded by the border, a plurality of the lengths of the bullion wire in the second pattern each spanning across a plurality of the lengths of the wire in the first pattern without being interwoven with the spanned plurality of lengths of wire in the first pattern. | 1. A headwear piece comprising: a crown defining an opening into which a wearer's head can be directed; and a brim/bill projecting away from the crown, the crown having an inside surface for engaging a wearer's head directed into the opening to thereby maintain the headwear piece in an operative position upon the wearer's head, the crown and brim/bill further having an exposed outside surface to which ornamentation is applied, the ornamentation comprising bullion wire that is applied to the exposed outside surface so as to define at least a part of a viewable component that comprises at least one of: a) a scene; b) a logo; c) a design; d) a word; e) a letter; and f) a depiction of a: i) person; ii) place; and/or iii) thing, wherein the ornamentation comprises a discrete shape with an area bounded by a border, and the ornamentation comprises: a) wire that is at least one of bullion wire and non-bullion wire applied in a first pattern comprising substantially straight, substantially parallel, adjacent lengths of the at least one of bullion wire and non-bullion wire within the area bounded by the border that collectively contiguously cover a substantial portion of the area bounded by the border; and b) bullion wire applied in a second pattern comprising substantially straight, substantially parallel, adjacent lengths of bullion wire within the area bounded by the border and overlying the first pattern, wherein the lengths of bullion wire in the second pattern are transverse to the lengths of wire in the first pattern and collectively contiguously cover a substantial portion of the area bounded by the border, a plurality of the lengths of the bullion wire in the second pattern each spanning across a plurality of the lengths of the wire in the first pattern without being interwoven with the spanned plurality of lengths of wire in the first pattern. 17. The headwear piece according to claim 1 wherein the ornamentation is pre-formed as a patch that is applied to the exposed, outside surface. | 0.771565 |
9,851,950 | 13 | 14 | 13. A method according to claim 12 , further comprising: after simultaneously displaying at least the portion of the second user input in the imprecise syntax and the second instruction in the precise syntax on the workspace document, hiding at least the portion of the second user input in the imprecise syntax on the workspace document in response to activation of a first user interface mechanism such that at least the portion of the second user input in the imprecise syntax is not displayed on the display device. | 13. A method according to claim 12 , further comprising: after simultaneously displaying at least the portion of the second user input in the imprecise syntax and the second instruction in the precise syntax on the workspace document, hiding at least the portion of the second user input in the imprecise syntax on the workspace document in response to activation of a first user interface mechanism such that at least the portion of the second user input in the imprecise syntax is not displayed on the display device. 14. A method according to claim 13 , further comprising: after hiding at least the portion of the second user input in the imprecise syntax on the workspace document in response to activation of the first user interface mechanism, re-displaying at least the portion of the second user input in the imprecise syntax on the workspace document in response to activation of a second user interface mechanism such that at least the portion of the second user input in the imprecise syntax is displayed again on the display device. | 0.942761 |
8,027,957 | 9 | 18 | 9. One or more computer-storage media embodying computer-useable instructions that, when employed by a computing device, cause the computing device to perform a method comprising: receiving a grammar usable by a search engine to route search queries to corresponding domains of information to find and return information for the search queries, the grammar comprising a plurality of rules, each rule comprising a sequence of token classes used to describe search queries, each token class comprising a logical grouping of tokens, each token comprising a string of one or more characters; parsing the grammar to identify the plurality of rules and token classes; eliminating, from the grammar, any duplicate rules identified from parsing the grammar; assigning a score to each rule indicative of an importance of each rule to the grammar, wherein the score for each rule is based at least in part on the frequency with which each rule corresponds with search queries contained in query logs; identifying one or more rules as important rules based on the one or more rules having a high score indicative of a high importance to the grammar; removing the one or more important rules from consideration for compression; identifying, from the token classes, two or more unimportant token classes that are eligible for compression and at least one important token class that is not eligible for compression; breaking at least one rule into a plurality of sub-rules based on important token classes, wherein each sub-rule includes a portion of the token classes from the at least one rule and each sub-rule begins and ends with an important token class and wherein a beginning token class and ending token class in each rule is treated as an important token class for purposes of breaking each rule into the plurality of sub-rules; identifying one or more sub-rules containing only important token classes; removing the one or more sub-rules containing only important token classes from consideration for compression; eliminating, from the grammar, any duplicate sub-rules identified; analyzing the plurality of sub-rules to identify at least one set of sub-rules as compression candidates; analyzing the unimportant token classes in the at least one set of sub-rules to identify two or more unimportant token classes for compression; merging the two or more unimportant token classes from the at least one set of sub-rules to generate a merged token class; substituting the merged token class in the grammar for the two or more unimportant token classes that were merged to generate the merged token class, wherein substituting the merged token class in the grammar for the two or more unimportant token classes that were merged to generate the merged token class comprises substituting the merged token class for all instances within the grammar of the two or more unimportant token classes that were merged to generate the merged token class; and eliminating any duplicate sub-rules and any duplicate rules after substituting the merged token classes in the grammar to generate a compressed grammar. | 9. One or more computer-storage media embodying computer-useable instructions that, when employed by a computing device, cause the computing device to perform a method comprising: receiving a grammar usable by a search engine to route search queries to corresponding domains of information to find and return information for the search queries, the grammar comprising a plurality of rules, each rule comprising a sequence of token classes used to describe search queries, each token class comprising a logical grouping of tokens, each token comprising a string of one or more characters; parsing the grammar to identify the plurality of rules and token classes; eliminating, from the grammar, any duplicate rules identified from parsing the grammar; assigning a score to each rule indicative of an importance of each rule to the grammar, wherein the score for each rule is based at least in part on the frequency with which each rule corresponds with search queries contained in query logs; identifying one or more rules as important rules based on the one or more rules having a high score indicative of a high importance to the grammar; removing the one or more important rules from consideration for compression; identifying, from the token classes, two or more unimportant token classes that are eligible for compression and at least one important token class that is not eligible for compression; breaking at least one rule into a plurality of sub-rules based on important token classes, wherein each sub-rule includes a portion of the token classes from the at least one rule and each sub-rule begins and ends with an important token class and wherein a beginning token class and ending token class in each rule is treated as an important token class for purposes of breaking each rule into the plurality of sub-rules; identifying one or more sub-rules containing only important token classes; removing the one or more sub-rules containing only important token classes from consideration for compression; eliminating, from the grammar, any duplicate sub-rules identified; analyzing the plurality of sub-rules to identify at least one set of sub-rules as compression candidates; analyzing the unimportant token classes in the at least one set of sub-rules to identify two or more unimportant token classes for compression; merging the two or more unimportant token classes from the at least one set of sub-rules to generate a merged token class; substituting the merged token class in the grammar for the two or more unimportant token classes that were merged to generate the merged token class, wherein substituting the merged token class in the grammar for the two or more unimportant token classes that were merged to generate the merged token class comprises substituting the merged token class for all instances within the grammar of the two or more unimportant token classes that were merged to generate the merged token class; and eliminating any duplicate sub-rules and any duplicate rules after substituting the merged token classes in the grammar to generate a compressed grammar. 18. The one or more computer-storage media of claim 9 , wherein merging the two or more unimportant token classes from the at least one set of sub-rules to generate a merged token class comprises generating a duplicate-free union of tokens included in each of the two or more unimportant token classes from the at least one set of sub-rules. | 0.621111 |
8,875,016 | 1 | 7 | 1. An image analysis and conversion method comprising: receiving a digital ink image having defined perceptually salient structures by an electronic device configured to perform the receiving; converting the digital ink image into multiple structured object representations of the digital ink image by the electronic device the multiple structured object representations correlating to ones of the defined perceptually salient structures of the digital ink image; and altering at least one of the structured object representations into multiple simultaneously existing structured alternative interpretations of the at least one structured object representations of the digital ink image by the electronic device, each of the alternative interpretations being viewable by a user and being plausible intended outputs of the user. | 1. An image analysis and conversion method comprising: receiving a digital ink image having defined perceptually salient structures by an electronic device configured to perform the receiving; converting the digital ink image into multiple structured object representations of the digital ink image by the electronic device the multiple structured object representations correlating to ones of the defined perceptually salient structures of the digital ink image; and altering at least one of the structured object representations into multiple simultaneously existing structured alternative interpretations of the at least one structured object representations of the digital ink image by the electronic device, each of the alternative interpretations being viewable by a user and being plausible intended outputs of the user. 7. The method according to claim 1 , wherein the digital ink image is converted into the multiple structured object representations of the digital ink image through the use of an Alternative Graph. | 0.945998 |
9,710,468 | 16 | 27 | 16. A system for creating a topic profile comprising: a database for storing a plurality of social media content items; a processor communicatively coupled to the database, the processor configured to: receive a first query; identify, in the database, a first plurality of social media content items associated with the first query, wherein the first plurality of social media content items are a result of executing the first query; identify, from among the first plurality of social media content items, a first set of one or more related keywords, wherein each keyword in the first set is referenced in at least one social media content item from among the plurality of social media content items; generate a topic profile based on the first query, wherein the topic profile comprises the first query, the first plurality of social media content items, and the first set of one or more related keywords; display, on a client computing device, a user interface comprising: a word cloud based on the topic profile, wherein the word cloud comprises the first query and the first set of one or more related keywords, and at least a portion of the first plurality of social media content items; receive, via the user interface, a selection of a first related keyword from among the first set of one or more related keywords displayed in the word cloud; generate a second query based on the first query and the first related keyword; execute the second query; and update the topic profile based upon a result of executing the second query. | 16. A system for creating a topic profile comprising: a database for storing a plurality of social media content items; a processor communicatively coupled to the database, the processor configured to: receive a first query; identify, in the database, a first plurality of social media content items associated with the first query, wherein the first plurality of social media content items are a result of executing the first query; identify, from among the first plurality of social media content items, a first set of one or more related keywords, wherein each keyword in the first set is referenced in at least one social media content item from among the plurality of social media content items; generate a topic profile based on the first query, wherein the topic profile comprises the first query, the first plurality of social media content items, and the first set of one or more related keywords; display, on a client computing device, a user interface comprising: a word cloud based on the topic profile, wherein the word cloud comprises the first query and the first set of one or more related keywords, and at least a portion of the first plurality of social media content items; receive, via the user interface, a selection of a first related keyword from among the first set of one or more related keywords displayed in the word cloud; generate a second query based on the first query and the first related keyword; execute the second query; and update the topic profile based upon a result of executing the second query. 27. The system of claim 16 , the processor further configured to automatically group similar social media content items among the first plurality of content items using text clustering, and wherein displaying at least a portion of the first plurality of content items comprises displaying a representative content item from each group of similar content items, wherein the representative content item represents a group of similar content items. | 0.633443 |
4,520,501 | 46 | 47 | 46. Apparatus for presenting speech information comprising means for producing a sequence of signals representative of speech; first and second multiple point grid matrix arrays of tactile stimulators adapted to be positioned at spaced locations on a human limb for providing coordinated tactile stimulation thereto; and means responsive to the signals for simultaneously activating the tactile stimulators of each array in respective first and second sequences of patterns that correspond to signals of the sequence, the first pattern being a code which represents a speech sound and the second pattern being another code which represents a mouth shape that produces the speech sound, in order to provide a coded tactile presentation of the speech. | 46. Apparatus for presenting speech information comprising means for producing a sequence of signals representative of speech; first and second multiple point grid matrix arrays of tactile stimulators adapted to be positioned at spaced locations on a human limb for providing coordinated tactile stimulation thereto; and means responsive to the signals for simultaneously activating the tactile stimulators of each array in respective first and second sequences of patterns that correspond to signals of the sequence, the first pattern being a code which represents a speech sound and the second pattern being another code which represents a mouth shape that produces the speech sound, in order to provide a coded tactile presentation of the speech. 47. The apparatus of claim 46, wherein the first and second arrays are adapted to be positioned in opposing relationship on opposite sides of the limb. | 0.664444 |
9,503,686 | 1 | 23 | 1. A system for providing a discussion topic reviewing tool, the system comprising: a video conferencing apparatus including a processor, a memory, a first display in communication with the processor, a video camera in communication with the processor, a speaker in communication with the processor, and a microphone in communication with the processor; and a video conferencing module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: initiate presentation on the first display a review bucket configured to receive from a customer a plurality of discussion topics for use in a video conference communication session between the customer and a business agent that represents a particular entity; receive from the customer, within the review bucket, an identifier associated with a first discussion topic that the customer is interested in discussing during the video conference communication session; initiate transmission of the first discussion topic to the business agent via an agent-implemented apparatus, the agent-implemented apparatus comprising a second display; initiate a video conference communication session between the customer and the business agent to discuss the first discussion topic transmitted to the business agent; present the review bucket on the first display, wherein the review bucket is configured to be dynamically positioned about the first display in one or more non-fixed orientations by the customer, wherein the review bucket is configured to allow both the customer and the business agent to view, edit, reorder and remove discussion topics within the review bucket in real time; present a replication of the review bucket on the second display; receive from the customer during the video conference communication session, within the review bucket, one or more identifiers associated with one or more second discussion topics from the plurality of discussion topics; and place the one or more identifiers associated with the one or more second discussion topics in a video conference communication queue based on at least an order in which the one or more second discussion topics are received, wherein the order is determined by the customer. | 1. A system for providing a discussion topic reviewing tool, the system comprising: a video conferencing apparatus including a processor, a memory, a first display in communication with the processor, a video camera in communication with the processor, a speaker in communication with the processor, and a microphone in communication with the processor; and a video conferencing module stored in the memory, comprising executable instructions that when executed by the processor cause the processor to: initiate presentation on the first display a review bucket configured to receive from a customer a plurality of discussion topics for use in a video conference communication session between the customer and a business agent that represents a particular entity; receive from the customer, within the review bucket, an identifier associated with a first discussion topic that the customer is interested in discussing during the video conference communication session; initiate transmission of the first discussion topic to the business agent via an agent-implemented apparatus, the agent-implemented apparatus comprising a second display; initiate a video conference communication session between the customer and the business agent to discuss the first discussion topic transmitted to the business agent; present the review bucket on the first display, wherein the review bucket is configured to be dynamically positioned about the first display in one or more non-fixed orientations by the customer, wherein the review bucket is configured to allow both the customer and the business agent to view, edit, reorder and remove discussion topics within the review bucket in real time; present a replication of the review bucket on the second display; receive from the customer during the video conference communication session, within the review bucket, one or more identifiers associated with one or more second discussion topics from the plurality of discussion topics; and place the one or more identifiers associated with the one or more second discussion topics in a video conference communication queue based on at least an order in which the one or more second discussion topics are received, wherein the order is determined by the customer. 23. The system of claim 1 , wherein the one or more second discussion topics comprise the first discussion topic. | 0.928571 |
8,407,162 | 24 | 25 | 24. A method according to claim 23 , comprising the step of: storing said first formal model, said second formal model and said annotated formal model in ontology holding means. | 24. A method according to claim 23 , comprising the step of: storing said first formal model, said second formal model and said annotated formal model in ontology holding means. 25. A method according to claim 24 , wherein the algorithm elaboration step comprises: applying inference or derivation rules of the inference capabilities on the annotated formal model to elaborate an algorithm for building or generating the formal probabilistic graph structure model. | 0.876404 |
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