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9,171,068 | 1 | 13 | 1. A method of providing personalized content recommendations using a computer comprising: providing a user interface on a computing device that monitors a user's information; generating a content signature that includes semantically salient content elements from the monitored user's information, a network address to the monitored user's information that the semantically salient content is based upon, and a plurality of densities of topics embodied in the salient content elements; storing a personal behavioral profile in a memory of the computing device, the memory stored with user's preferences based on a plurality of monitored past behaviors and a collaborative filtering; filtering items in an incoming information stream with the personal behavioral profile and the content signature and responsive to a document ranking based in part on a plurality of phrase inhibitors and a plurality of saturation topic phrases; and receiving only those items of the incoming information stream that match and is responsive to the document ranking and the personal behavioral profile for a certain information consumption mode of the user. | 1. A method of providing personalized content recommendations using a computer comprising: providing a user interface on a computing device that monitors a user's information; generating a content signature that includes semantically salient content elements from the monitored user's information, a network address to the monitored user's information that the semantically salient content is based upon, and a plurality of densities of topics embodied in the salient content elements; storing a personal behavioral profile in a memory of the computing device, the memory stored with user's preferences based on a plurality of monitored past behaviors and a collaborative filtering; filtering items in an incoming information stream with the personal behavioral profile and the content signature and responsive to a document ranking based in part on a plurality of phrase inhibitors and a plurality of saturation topic phrases; and receiving only those items of the incoming information stream that match and is responsive to the document ranking and the personal behavioral profile for a certain information consumption mode of the user. 13. The method of claim 1 further comprising automatically detecting a shift in the personal behavioral profile and applying a second personal behavioral profile in the filtering act. | 0.502717 |
9,619,465 | 8 | 10 | 8. A system comprising: a translation server operable to perform machine translation obtaining translation model data from a translation model for translation between a source language and a target language and language model data from a language model for the target language, the translation server further operable to translate text in the source language into the target language using the obtained translation model data and language model data, the translation server comprising: a request queue operable to store requests for language model data to be obtained for translating a segment in the source language, a segment translation server cache operable to store language model data obtained by the requests by the translation server; and a second segment translation server cache storing a selected portion of the language model, wherein the translation server is operable to: process the translation of the segment using language model data from a second language model for the target language to produce an initial translation of the segment before the requests for the language data in the language model in the request queue are sent out, update the requests for the language model data of the language model in the request queue based on the initial translation, send out the updated requests in the request queue to obtain language model data from the language model for processing the initial translation, and after the updated requests are served and the data for the updated requests are stored in the segment translation server cache, process the initial translation with the data for the updated requests to produce a final translation, after completing translation of the segment, delete data in the segment translation server cache and retain the selected portion of the language model in the second segment translation server cache. | 8. A system comprising: a translation server operable to perform machine translation obtaining translation model data from a translation model for translation between a source language and a target language and language model data from a language model for the target language, the translation server further operable to translate text in the source language into the target language using the obtained translation model data and language model data, the translation server comprising: a request queue operable to store requests for language model data to be obtained for translating a segment in the source language, a segment translation server cache operable to store language model data obtained by the requests by the translation server; and a second segment translation server cache storing a selected portion of the language model, wherein the translation server is operable to: process the translation of the segment using language model data from a second language model for the target language to produce an initial translation of the segment before the requests for the language data in the language model in the request queue are sent out, update the requests for the language model data of the language model in the request queue based on the initial translation, send out the updated requests in the request queue to obtain language model data from the language model for processing the initial translation, and after the updated requests are served and the data for the updated requests are stored in the segment translation server cache, process the initial translation with the data for the updated requests to produce a final translation, after completing translation of the segment, delete data in the segment translation server cache and retain the selected portion of the language model in the second segment translation server cache. 10. The system of claim 8 , wherein the translation model is divided into a plurality of translation model partitions, each translation model partition being less than the entire translation model and being stored on a different translation model server of a plurality of translation model servers, and the respective translation model partitions together constituting the entire translation model. | 0.672158 |
8,219,615 | 12 | 18 | 12. The computer program product of claim 1 , wherein the computer program product is operable such that first indicia is displayed with particular web content for use in connection with at least one aspect of the posting in association with the particular web content on the website in response to a selection thereof and an interface is displayed for allowing the user to type the new message, and further wherein the computer program product is operable such that second indicia is displayed with the particular web content for use in connection with at least one aspect of replying to a posted message that is posted with the particular web content on the website in response to a selection thereof, and further wherein the computer program product is operable such that the user is capable of posting the new message in association with the particular web content to both: the website associated with the particular web content and a different website that is not a source of the particular web content. | 12. The computer program product of claim 1 , wherein the computer program product is operable such that first indicia is displayed with particular web content for use in connection with at least one aspect of the posting in association with the particular web content on the website in response to a selection thereof and an interface is displayed for allowing the user to type the new message, and further wherein the computer program product is operable such that second indicia is displayed with the particular web content for use in connection with at least one aspect of replying to a posted message that is posted with the particular web content on the website in response to a selection thereof, and further wherein the computer program product is operable such that the user is capable of posting the new message in association with the particular web content to both: the website associated with the particular web content and a different website that is not a source of the particular web content. 18. The computer program product of claim 12 , wherein the computer program product is operable such that the new message is capable of being sorted as a function of time associated with the posting. | 0.880695 |
9,600,169 | 1 | 3 | 1. A computer-implemented method comprising: receiving, from a user via a user interface of a first device, mapping input that specifies a particular gesture, one or more first device actions to associate with the particular gesture, and a first device context to associate with the particular gesture and the one or more first device actions, wherein the first device context includes one or more devices, other than the first device, are in the presence of the first device, or the one or more devices have logged in to a particular user account; storing, in a non-transitory storage medium, a first mapping that specifies the particular gesture, the first device context, and the one or more first device actions, wherein the non-transitory storage medium further stores a second mapping that specifies the particular gesture, a second device context, and one or more second device actions; detecting, by the first device, performance of a given gesture; in response to detecting performance of the given gesture: determining that the given gesture matches the particular gesture that is specified in the first mapping and the second mapping; in response to determining that the given gesture matches the particular gesture specified in the first mapping and the second mapping, reading the first mapping to determine the first device context that is specified in the first mapping and reading the second mapping to determine the second device context that is specified in the second mapping; determining whether one or more conditions external to the first device, detected by the first device, match the first device context; responsive to determining that the one or more conditions external to the first device match the first device context, causing the first device to perform the one or more first device actions that are specified in the first mapping; determining whether the one or more conditions external to the first device, detected by the first device, match the second device context; and responsive to determining that the one or more conditions external to the first device match the second device context, causing the first device to perform the one or more second device actions that are specified in the second mapping. | 1. A computer-implemented method comprising: receiving, from a user via a user interface of a first device, mapping input that specifies a particular gesture, one or more first device actions to associate with the particular gesture, and a first device context to associate with the particular gesture and the one or more first device actions, wherein the first device context includes one or more devices, other than the first device, are in the presence of the first device, or the one or more devices have logged in to a particular user account; storing, in a non-transitory storage medium, a first mapping that specifies the particular gesture, the first device context, and the one or more first device actions, wherein the non-transitory storage medium further stores a second mapping that specifies the particular gesture, a second device context, and one or more second device actions; detecting, by the first device, performance of a given gesture; in response to detecting performance of the given gesture: determining that the given gesture matches the particular gesture that is specified in the first mapping and the second mapping; in response to determining that the given gesture matches the particular gesture specified in the first mapping and the second mapping, reading the first mapping to determine the first device context that is specified in the first mapping and reading the second mapping to determine the second device context that is specified in the second mapping; determining whether one or more conditions external to the first device, detected by the first device, match the first device context; responsive to determining that the one or more conditions external to the first device match the first device context, causing the first device to perform the one or more first device actions that are specified in the first mapping; determining whether the one or more conditions external to the first device, detected by the first device, match the second device context; and responsive to determining that the one or more conditions external to the first device match the second device context, causing the first device to perform the one or more second device actions that are specified in the second mapping. 3. The computer-implemented method of claim 1 , wherein: detecting, by the first device, performance of the given gesture includes detecting first input and the particular gesture is a first particular gesture; the computer-implemented method further comprises: receiving second input indicating that the first device detected a gesturing event that is one of the first particular gesture or a second particular gesture, and determining, based on the first device context, that the gesturing event corresponds to the first particular gesture. | 0.591252 |
8,818,910 | 5 | 7 | 5. The system of claim 4 , wherein at least one of the input variables comprises a social media network variable. | 5. The system of claim 4 , wherein at least one of the input variables comprises a social media network variable. 7. The system of claim 5 , wherein the social media network variable comprises an online social media influencer score for the candidates. | 0.566038 |
8,359,309 | 9 | 10 | 9. A system comprising: a storage device encoded with instructions; and data processing apparatus operable to execute the instructions to perform operations comprising: determining, for a plurality of search results responsive to a query, a respective count of times search results in the plurality of search results that refer to documents in a base corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the base corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the base corpus are for searches initiated by users in a plurality of different countries who employ a specific language; determining, for the plurality of search results responsive to the query, a respective count of times search results in the plurality of search results that refer to documents in a second corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the second corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the second corpus are for searches initiated by users in the plurality of different countries who employ the specific language; calculating a click through rate of the base corpus for the query based at least in part on the respective counts for the base corpus; calculating a click through rate of the second corpus for the query based at least in part on the respective counts for the second corpus; calculating a measure of relative relevance based at least in part on a ratio of the second corpus click through rate to the base corpus click through rate; and providing the measure of relative relevance to a ranking engine for ranking of search results for a search corresponding to the query; and wherein fewer search results of the plurality refer to documents in the second corpus than to documents in the base corpus. | 9. A system comprising: a storage device encoded with instructions; and data processing apparatus operable to execute the instructions to perform operations comprising: determining, for a plurality of search results responsive to a query, a respective count of times search results in the plurality of search results that refer to documents in a base corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the base corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the base corpus are for searches initiated by users in a plurality of different countries who employ a specific language; determining, for the plurality of search results responsive to the query, a respective count of times search results in the plurality of search results that refer to documents in a second corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the second corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the second corpus are for searches initiated by users in the plurality of different countries who employ the specific language; calculating a click through rate of the base corpus for the query based at least in part on the respective counts for the base corpus; calculating a click through rate of the second corpus for the query based at least in part on the respective counts for the second corpus; calculating a measure of relative relevance based at least in part on a ratio of the second corpus click through rate to the base corpus click through rate; and providing the measure of relative relevance to a ranking engine for ranking of search results for a search corresponding to the query; and wherein fewer search results of the plurality refer to documents in the second corpus than to documents in the base corpus. 10. The system of claim 9 wherein the respective counts for the base and second corpora are derived from language-specific data or country-specific data, and wherein calculating a click through rate for one of the corpora further comprises selecting which data to use for the respective counts based on a determination that the selected data will provide a reliable statistic. | 0.5 |
7,933,952 | 1 | 10 | 1. A non-transitory computer-readable medium including executable instructions which, when executed, collaborate information by: using a computer-implemented client to define an assembly workspace including associating one or more users as one or more participants of the assembly workspace, wherein the client is configured to interact with other clients as part of a collaborative authoring effort; associating an assembly document, including using a master assembly document to track and maintain user changes, with the assembly workspace including providing an in-memory manifestation of a state of the assembly document that includes data, metadata, content, and actions, and using an assembly document proxy to build the assembly document using stored information and an assembly document object to create a number of sections and a number of authored section content controls based in part on one or more of a first property associated with a begin editing operation, a second property associated with a completed section operation, a third property associated with a section status, a fourth property associated with an allow to reassign operation, and a fifth property associated with an allow to insert sections operation; applying a number of constraints to the assembly document, wherein the number of constraints determines which of the one or more participants is permitted to interact with the number of sections of the assembly document, the number of constraints defined in part by an editor role, an author role, and an observer role, wherein the editor role can be used to assign sections to authors including enabling an assigned author to reassign a section to other authors responsible for contributing content to one or more of the number of sections of the assembly document including editing root section metadata as part of assigning sections, updating section status, and restricting sections; and, generating a complete copy of the assembly document for each participant as part of a document assembly process using the assembly workspace and the assembly document proxy. | 1. A non-transitory computer-readable medium including executable instructions which, when executed, collaborate information by: using a computer-implemented client to define an assembly workspace including associating one or more users as one or more participants of the assembly workspace, wherein the client is configured to interact with other clients as part of a collaborative authoring effort; associating an assembly document, including using a master assembly document to track and maintain user changes, with the assembly workspace including providing an in-memory manifestation of a state of the assembly document that includes data, metadata, content, and actions, and using an assembly document proxy to build the assembly document using stored information and an assembly document object to create a number of sections and a number of authored section content controls based in part on one or more of a first property associated with a begin editing operation, a second property associated with a completed section operation, a third property associated with a section status, a fourth property associated with an allow to reassign operation, and a fifth property associated with an allow to insert sections operation; applying a number of constraints to the assembly document, wherein the number of constraints determines which of the one or more participants is permitted to interact with the number of sections of the assembly document, the number of constraints defined in part by an editor role, an author role, and an observer role, wherein the editor role can be used to assign sections to authors including enabling an assigned author to reassign a section to other authors responsible for contributing content to one or more of the number of sections of the assembly document including editing root section metadata as part of assigning sections, updating section status, and restricting sections; and, generating a complete copy of the assembly document for each participant as part of a document assembly process using the assembly workspace and the assembly document proxy. 10. The non-transitory computer-readable medium of claim 1 , wherein the instructions, when executed, collaborate information by using the metadata to define the number of constraints to determine which of the one or more participants is permitted to interact with one or more of the number of sections of the assembly document, wherein the number of authored section content controls can define when an author may begin editing a corresponding section, when the corresponding section should be completed, a section status of the corresponding section, an allow to reassign operation for the corresponding section, an allow to insert sections operation for the corresponding section, and a complete indication for the corresponding section. | 0.59695 |
4,751,740 | 32 | 33 | 32. In the document structure of claim 1 and wherein: the plurality of types includes a binary type specifying that the segment having the type contains codes representing binary values; the document structure includes at least one binary segment having the binary type; and the means for representing the contents of the binary segment includes codes representing binary values. | 32. In the document structure of claim 1 and wherein: the plurality of types includes a binary type specifying that the segment having the type contains codes representing binary values; the document structure includes at least one binary segment having the binary type; and the means for representing the contents of the binary segment includes codes representing binary values. 33. In the document structure of claim 32 and wherein: the codes representing binary values include a code specifying the number of codes representing binary values contained in the segment. | 0.837607 |
9,268,560 | 9 | 19 | 9. A non-transitory computer-readable storage medium comprising instructions for indicating a change to a dependent file, wherein the instructions, when executed, are for controlling a computer system to be configured for: receiving a first change to a program file; performing, via a computing device, a second change to code or program data in a first dependent file on the program file on the program file; wherein the second change is related to the first change; and displaying in a document editor a first identifier for the first dependent file in a first text style, if the first dependent file is changed based on the first change to the program file; displaying in the document editor a second identifier, in a second text style, for a second dependent file, wherein: code of the program file calls code or program data of the first dependent file and the second dependent file, the first text style indicates the first dependent file has been changed based on the first change to the program file, and the first text style and the second text style are different styles. | 9. A non-transitory computer-readable storage medium comprising instructions for indicating a change to a dependent file, wherein the instructions, when executed, are for controlling a computer system to be configured for: receiving a first change to a program file; performing, via a computing device, a second change to code or program data in a first dependent file on the program file on the program file; wherein the second change is related to the first change; and displaying in a document editor a first identifier for the first dependent file in a first text style, if the first dependent file is changed based on the first change to the program file; displaying in the document editor a second identifier, in a second text style, for a second dependent file, wherein: code of the program file calls code or program data of the first dependent file and the second dependent file, the first text style indicates the first dependent file has been changed based on the first change to the program file, and the first text style and the second text style are different styles. 19. The non-transitory computer-readable storage medium of claim 9 , wherein the first dependent file and the second dependent file are open in the document editor; and wherein the first identifier and the second identifier are displayed on different tabs of the document editor. | 0.565421 |
8,335,802 | 12 | 19 | 12. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods; wherein the invoking of the producer, converter, and distributor methods is triggered by at least one of the following: a schedule, a user input, and an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the schedule, the user input, or the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the schedule, the user input, or the event meets a predefined criterion. | 12. A computer-implemented method of distributing information retrieved from one or more data repositories, the method comprising: invoking, at a computer device separate from the one or more data repositories, a producer method to generate a document using data retrieved from one or more data repositories, the producer method selected, at a user interface, from a plurality of producer methods, wherein the plurality of producer methods are configured to generate different documents based on same data retrieved from the one or more data repositories; invoking, at the computer device separate from the one or more data repositories, a converter method to convert the generated document to an output format, the converter method selected, at the user interface, from a plurality of converter methods; and invoking, at the computer device separate from the one or more data repositories, a distributor method to distribute the converted document through a distribution channel, the distributor method selected, at the user interface, from a plurality of distributor methods; wherein the invoking of the producer, converter, and distributor methods is triggered by at least one of the following: a schedule, a user input, and an event, and wherein the producer, converter, and distributor methods are registered to be selected when the trigger is received; wherein the schedule, the user input, or the event is associated, at the user interface, with one or more settings defining the producer, converter, and distributor methods and at least one of the producer, converter, and distributor methods can be added to the one or more settings without affecting existing at least one of producer, converter, and distributor methods defined by the one or more settings, wherein the at least one of the added producer, converter, and distributor methods is configured to operate with the at least one of the invoked producer, converter, and distributor methods; wherein the one or more settings is processed based upon a condition that the schedule, the user input, or the event meets a predefined criterion. 19. The method of claim 12 , wherein the producer method generates several documents using the data, wherein the converter method converts the several documents, and wherein the distributor method distributes the several converted documents. | 0.634848 |
9,390,434 | 15 | 22 | 15. A system for providing advertising in one or more search results, the system comprising: a computing device comprising at least one database relating to at least one service provider, the at least one database being one of a plurality of databases, each database in the plurality of databases comprising a plurality of items for recognition, each database in the plurality of databases being for a corresponding vertical application; and a server coupled to the computing device via a network, the server being configured to execute instructions stored in memory to: receive the at least one database from the computing device via the network; process the at least one database based on the plurality of items for recognition; receive on the server over the network a sound data input comprising a query for the processed at least one database; determine one or more search results in the processed at least one database based on the query; identify one or more advertisement results in an advertisement database based on at least one of the query and the determined one or more search results, the advertisement database being communicatively coupled to the server; and transmit the one or more search results and the one or more advertisement results from the server to a remote computer system. | 15. A system for providing advertising in one or more search results, the system comprising: a computing device comprising at least one database relating to at least one service provider, the at least one database being one of a plurality of databases, each database in the plurality of databases comprising a plurality of items for recognition, each database in the plurality of databases being for a corresponding vertical application; and a server coupled to the computing device via a network, the server being configured to execute instructions stored in memory to: receive the at least one database from the computing device via the network; process the at least one database based on the plurality of items for recognition; receive on the server over the network a sound data input comprising a query for the processed at least one database; determine one or more search results in the processed at least one database based on the query; identify one or more advertisement results in an advertisement database based on at least one of the query and the determined one or more search results, the advertisement database being communicatively coupled to the server; and transmit the one or more search results and the one or more advertisement results from the server to a remote computer system. 22. The system of claim 15 , the instructions stored in memory to determine one or more search results in the processed at least one database comprising instructions stored in memory to match the query with one or more of the plurality of items for recognition within the at least one database. | 0.554545 |
9,208,142 | 8 | 12 | 8. A computer program product for analyzing documents corresponding to demographics, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to determine whether demographic information associated with a first text analysis algorithm indicates that the first text analysis algorithm is intended to analyze a document based on demographic information associated with the document, wherein Natural Language Processing (NLP) utilizes text analysis algorithms to produce an analysis of the document and provide annotations; wherein the demographic information associated with the first text analysis algorithm is a demographic score that indicates a relationship to one or more demographic profiles, and the demographic information associated with the document is a demographic profile of an author of the document; responsive to determining that demographic information associated with the first text analysis algorithm does indicate that the first text analysis algorithm is intended to analyze the document, program instructions to analyze the document utilizing the first text analysis algorithm; and program instructions to generate a set of annotations for the document based on the analysis of the document utilizing the first text analysis algorithm. | 8. A computer program product for analyzing documents corresponding to demographics, the computer program product comprising: one or more computer-readable storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to determine whether demographic information associated with a first text analysis algorithm indicates that the first text analysis algorithm is intended to analyze a document based on demographic information associated with the document, wherein Natural Language Processing (NLP) utilizes text analysis algorithms to produce an analysis of the document and provide annotations; wherein the demographic information associated with the first text analysis algorithm is a demographic score that indicates a relationship to one or more demographic profiles, and the demographic information associated with the document is a demographic profile of an author of the document; responsive to determining that demographic information associated with the first text analysis algorithm does indicate that the first text analysis algorithm is intended to analyze the document, program instructions to analyze the document utilizing the first text analysis algorithm; and program instructions to generate a set of annotations for the document based on the analysis of the document utilizing the first text analysis algorithm. 12. The computer program product of claim 8 , wherein the demographic profile of an author of the document indicates information about the author of the document comprising one or more of: an age range of the author, a nationality of the author, a location of the author, and an education level of the author. | 0.694664 |
8,463,794 | 3 | 5 | 3. The computer-implemented system according to claim 1 , wherein: the first extraction unit uses the first text processing information to extract the noun word from the document data by performing a morphological analysis on the document data to extract noun words (Ki (i=1, 2 , . . . , n)); and the first extract unit further assigns, to each of the extracted noun words Ki, a weight corresponding to at least one of a position and a proportion of the noun word Ki in the document data. | 3. The computer-implemented system according to claim 1 , wherein: the first extraction unit uses the first text processing information to extract the noun word from the document data by performing a morphological analysis on the document data to extract noun words (Ki (i=1, 2 , . . . , n)); and the first extract unit further assigns, to each of the extracted noun words Ki, a weight corresponding to at least one of a position and a proportion of the noun word Ki in the document data. 5. The computer-implemented system according to claim 3 , wherein: when the position of the noun word Ki is not in a sentence, a determination is made as to whether or not the noun word Ki takes up the entire text segment; when the noun word Ki takes up the entire text segment, a score W is assigned to the noun word Ki; when the noun word Ki does not take up the entire text segment, a score Y is assigned to the noun word Ki; when the position of the noun word Ki is in a sentence, a determination is made as to whether or not the noun word Ki is in a parenthesis in the sentence and takes up the entire character string in the parenthesis; when the noun word Ki is in the parenthesis and takes up the entire character string in the parenthesis, a score X is assigned to the noun word Ki; and when the noun word Ki is not in a parenthesis or does not take up the entire character string, a score Z is assigned to the noun word Ki, wherein score W is greater than score X, score X is greater than score Y, and score Y is greater than score Z. | 0.5 |
8,615,442 | 9 | 10 | 9. The method of claim 7 , further comprising obtaining second content; analyzing language of the second content to identify lexical features of the second content; determining one or more topics of the second content based on the lexical features of the second content; and determining a similarity between the interests of the user as indicated by the interest graph and the one or more topics of the second content; wherein the content for the user is generated based on the determined similarity between the interests of the user and the one or more topics of the second content. | 9. The method of claim 7 , further comprising obtaining second content; analyzing language of the second content to identify lexical features of the second content; determining one or more topics of the second content based on the lexical features of the second content; and determining a similarity between the interests of the user as indicated by the interest graph and the one or more topics of the second content; wherein the content for the user is generated based on the determined similarity between the interests of the user and the one or more topics of the second content. 10. The method of claim 9 , wherein determining one or more topics of the second content comprises: comparing the lexical features of the second content to stored lexical features, wherein each of the stored lexical features is associated with one or more topics; and determining one or more topics of the second content based on the comparison. | 0.53504 |
8,078,598 | 1 | 8 | 1. A method comprising: receiving, by a processor, a structured query language query; determining, by the processor, at least one point data query and at least one relational data query based on the structured query language query; transmitting the at least one point data query to at least one point data server; transmitting the at least one relational data query to at least one relational data server; receiving, by the processor, point data and relational data in response to the point data query and the relational data query; and joining, by the processor, the received point data and the received relational data into a result rowset; wherein the receiving point data and relational data in response to the point data query and the relational data query comprises: receiving, from the at least one point data server in response to the at least one point data query that is based on the structured query language query, point data that has been collected from multiple heterogeneous sources based on components defined according to a class-based object model and encapsulated as object instantiations of the components; wherein the at least one point data server is to receive the object instantiations of the components defined according to the class-based object model; and wherein the point data is current, real-time or value data associated with one or more instruments, components, or portions of a manufacturing, industrial, commercial, or other system. | 1. A method comprising: receiving, by a processor, a structured query language query; determining, by the processor, at least one point data query and at least one relational data query based on the structured query language query; transmitting the at least one point data query to at least one point data server; transmitting the at least one relational data query to at least one relational data server; receiving, by the processor, point data and relational data in response to the point data query and the relational data query; and joining, by the processor, the received point data and the received relational data into a result rowset; wherein the receiving point data and relational data in response to the point data query and the relational data query comprises: receiving, from the at least one point data server in response to the at least one point data query that is based on the structured query language query, point data that has been collected from multiple heterogeneous sources based on components defined according to a class-based object model and encapsulated as object instantiations of the components; wherein the at least one point data server is to receive the object instantiations of the components defined according to the class-based object model; and wherein the point data is current, real-time or value data associated with one or more instruments, components, or portions of a manufacturing, industrial, commercial, or other system. 8. The method according to claim 1 , wherein joining the received point data and the received relational data into a result rowset comprises: synthesizing a first rowset based on the received point data; synthesizing a second rowset based on the received relational data; and combining the first rowset and the second rowset into the result rowset based on columns specified in the structured query language query. | 0.571429 |
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. | 0.880435 |
8,543,378 | 9 | 12 | 9. The computer readable-media as recited in claim 8 , wherein the filtering process comprises comparing a first and a last consonant in the misspelled entry with a first and a last consonant in a selected term. | 9. The computer readable-media as recited in claim 8 , wherein the filtering process comprises comparing a first and a last consonant in the misspelled entry with a first and a last consonant in a selected term. 12. The computer readable-media as recited in claim 9 , wherein the filtering process considers one or more consonants that are omittable from a start or end of the misspelled entry. | 0.56872 |
7,957,968 | 12 | 14 | 12. A computer based system for automatically generating a hierarchical grammar associated with a plurality of tasks comprising: creation means for creating a sub-grammar for each of the plurality of tasks, wherein the creation means comprises: receiving means for receiving data representing the task based from responses received from a distributed database; tagging means for automatically tagging the data into parts of speech to form tagged data; identification means for identifying filler words and core words from said tagged data by applying rules to differentiate between filler words and core words; modeling means for automatically modeling sentence structure based upon said tagged data using a set of modeling rules; synonym means for automatically identifying synonyms of said core words; and grammar means for automatically creating a sub-grammar using the modeled sentence structure, the tagged data, the identified synonyms, and the identified core words; and creation means for creating a high-level grammar by combining filler words identified in the creation of the sub-grammars. | 12. A computer based system for automatically generating a hierarchical grammar associated with a plurality of tasks comprising: creation means for creating a sub-grammar for each of the plurality of tasks, wherein the creation means comprises: receiving means for receiving data representing the task based from responses received from a distributed database; tagging means for automatically tagging the data into parts of speech to form tagged data; identification means for identifying filler words and core words from said tagged data by applying rules to differentiate between filler words and core words; modeling means for automatically modeling sentence structure based upon said tagged data using a set of modeling rules; synonym means for automatically identifying synonyms of said core words; and grammar means for automatically creating a sub-grammar using the modeled sentence structure, the tagged data, the identified synonyms, and the identified core words; and creation means for creating a high-level grammar by combining filler words identified in the creation of the sub-grammars. 14. The system of claim 12 , wherein said hierarchical grammar is combined with a statistical language model to recognize speech. | 0.5 |
9,785,948 | 1 | 7 | 1. A method for online task advising that assists a user to complete a task, the method comprising: receiving, from a user by a system comprising a hardware processor, a request to customize a task definition of a customizable script in a memory; updating, by the system, the task definition based on the request; receiving, from a user by the system, a selection of a task definition to be completed, the task definition to be completed being the updated task definition; creating, by the system, a task instance based, at least in part, on the selected task definition, the task instance comprising a step associated with completing the task, the step comprising a status indicator; receiving, by the system, a selection of the step from a user; determining, by the system, whether the selected step is associated with an action; responsive to the selected step being associated with the action, by the system: executing the action, and updating the status indicator of the selected step based on the executed action; responsive to the selected step not being associated with the action, by the system: presenting the user with the selected step for election whether to complete the selected step, receiving, from the user, an indication that the selected step is complete, and updating the status indicator of the selected step based on the indication from the user; and providing, by the system, the task instance for presentation on a display. | 1. A method for online task advising that assists a user to complete a task, the method comprising: receiving, from a user by a system comprising a hardware processor, a request to customize a task definition of a customizable script in a memory; updating, by the system, the task definition based on the request; receiving, from a user by the system, a selection of a task definition to be completed, the task definition to be completed being the updated task definition; creating, by the system, a task instance based, at least in part, on the selected task definition, the task instance comprising a step associated with completing the task, the step comprising a status indicator; receiving, by the system, a selection of the step from a user; determining, by the system, whether the selected step is associated with an action; responsive to the selected step being associated with the action, by the system: executing the action, and updating the status indicator of the selected step based on the executed action; responsive to the selected step not being associated with the action, by the system: presenting the user with the selected step for election whether to complete the selected step, receiving, from the user, an indication that the selected step is complete, and updating the status indicator of the selected step based on the indication from the user; and providing, by the system, the task instance for presentation on a display. 7. The method of claim 1 , wherein the task instance comprises a plurality of steps associated with completing the task, and wherein at least one step of the plurality of steps is a prerequisite step of at least one other step of the plurality of steps. | 0.705814 |
5,558,328 | 9 | 11 | 9. A method for arranging on a plurality of word game dice a plurality of letters of an alphabet appearing in a corpus of words, said dice having a total number of faces thereon, comprising the method of a) determining a relative frequency of appearance of each of said letters in said corpus of words; b) multiplying said relative frequency of appearance of each said letters by said total number of faces to receive a product for each of said letters; c) dividing said product for each of said letters by one hundred to receive an initial number for each of said letters; d) rounding said initial number for each of said letters to the nearest whole number to receive a final number for each of said letters, said final number for each of said letters representing the number of faces of said dice on which each of said letters will be displayed; and e) displaying said final number of each of said letters on said dice such that none of said letters am displayed more than once on any one of said dice and such that placement of common bigrams on any one die is minimized, said method of arranging resulting in an arrangement of letters on the dice that maximize the numbers of words that can be formed using said letters displayed on said dice. | 9. A method for arranging on a plurality of word game dice a plurality of letters of an alphabet appearing in a corpus of words, said dice having a total number of faces thereon, comprising the method of a) determining a relative frequency of appearance of each of said letters in said corpus of words; b) multiplying said relative frequency of appearance of each said letters by said total number of faces to receive a product for each of said letters; c) dividing said product for each of said letters by one hundred to receive an initial number for each of said letters; d) rounding said initial number for each of said letters to the nearest whole number to receive a final number for each of said letters, said final number for each of said letters representing the number of faces of said dice on which each of said letters will be displayed; and e) displaying said final number of each of said letters on said dice such that none of said letters am displayed more than once on any one of said dice and such that placement of common bigrams on any one die is minimized, said method of arranging resulting in an arrangement of letters on the dice that maximize the numbers of words that can be formed using said letters displayed on said dice. 11. The method of claim 9 wherein said plurality of letters includes vowel letters and wherein one die of said dice includes only vowel letters. | 0.626943 |
9,563,741 | 9 | 11 | 9. One or more tangible, non-transitory computer-readable media comprising: a custom knowledgebase comprising a plurality of assertions that have been automatically extracted from a plurality of publications, wherein each of the plurality of assertions encodes a relationship between a subject and an object; a sequence dataset comprising a plurality of called biological sequences, wherein each of the plurality of called biological sequences is associated with one or more of the plurality of assertions of the custom knowledgebase; and a client application configured to: compare a plurality of sample biological sequences to the plurality of called biological sequences of the sequence dataset; and determine, for at least one sample biological sequence that resembles a called biological sequence of the sequence dataset, one or more probable characteristics associated with that sample biological sequence using one or more assertions of the custom knowledgebase that are associated with the called biological sequence that resembles that sample biological sequence, wherein the at least one sample biological sequence is not in the sequence dataset. | 9. One or more tangible, non-transitory computer-readable media comprising: a custom knowledgebase comprising a plurality of assertions that have been automatically extracted from a plurality of publications, wherein each of the plurality of assertions encodes a relationship between a subject and an object; a sequence dataset comprising a plurality of called biological sequences, wherein each of the plurality of called biological sequences is associated with one or more of the plurality of assertions of the custom knowledgebase; and a client application configured to: compare a plurality of sample biological sequences to the plurality of called biological sequences of the sequence dataset; and determine, for at least one sample biological sequence that resembles a called biological sequence of the sequence dataset, one or more probable characteristics associated with that sample biological sequence using one or more assertions of the custom knowledgebase that are associated with the called biological sequence that resembles that sample biological sequence, wherein the at least one sample biological sequence is not in the sequence dataset. 11. The one or more tangible, non-transitory computer-readable media of claim 9 , wherein: the plurality of called biological sequences of the sequence dataset comprise at least one of called biological sequences that provide resistance to one or more antibiotics and called biological sequences that mediate regulation of antibiotic resistance; and the plurality of assertions of the custom knowledgebase comprise assertions that encode relationships between the called biological sequences of the sequence dataset and at least one of antibiotic resistance elements and regulatory elements. | 0.5 |
8,014,634 | 22 | 27 | 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. 27. The method of claim 22 , further comprising flagging the first graphical document if the first graphical document contains less than a minimum number of ratings, is rated with a rating indicative of content identified as objectionable or one or more broken links, or is associated with a particular class of advertising model. | 0.5 |
8,397,056 | 1 | 4 | 1. A computer system, comprising: a processor configured with: a mashup section that provides a mashup that performs an action on a resource included in the mashup; an attribute identification section that identifies an attribute of a user running the mashup to perform the action on the resource; and an access control section providing an access control, the mashup being associated to a permission artifact, the permission artifact specifying a principal and whether one of to permit and to prohibit the principal to take the action on the resource, wherein the access control is triggered only when the mashup attempts to perform the action on the resource, the access control (i) checks whether the attribute of the user running the mashup to perform the action is predefined as belonging to the principal specified in the permission artifact associated to the mashup, and then (ii) performs the one of to permit and to prohibit the action on the resource only when the attribute belongs to the principal, plural users that have a same single attribute belong to the principal when the same single attribute is defined as belonging to the principal, and the permission artifact further specifies: (i) the resource used by the mashup and (ii) the action on the resource for which permission is needed. | 1. A computer system, comprising: a processor configured with: a mashup section that provides a mashup that performs an action on a resource included in the mashup; an attribute identification section that identifies an attribute of a user running the mashup to perform the action on the resource; and an access control section providing an access control, the mashup being associated to a permission artifact, the permission artifact specifying a principal and whether one of to permit and to prohibit the principal to take the action on the resource, wherein the access control is triggered only when the mashup attempts to perform the action on the resource, the access control (i) checks whether the attribute of the user running the mashup to perform the action is predefined as belonging to the principal specified in the permission artifact associated to the mashup, and then (ii) performs the one of to permit and to prohibit the action on the resource only when the attribute belongs to the principal, plural users that have a same single attribute belong to the principal when the same single attribute is defined as belonging to the principal, and the permission artifact further specifies: (i) the resource used by the mashup and (ii) the action on the resource for which permission is needed. 4. The computer system of claim 1 , the mashup further comprising an extensible access control markup language (XACML) attribute-based artifact, the running of the mashup with the XACML attribute-based artifact results in a second access control. | 0.542751 |
7,689,033 | 53 | 62 | 53. An apparatus comprising: one or more processors; and memory having instructions including logic executable by the one or more processors to Perform a multiple stage face detection scheme to detect at least one human face within a digital image, the memory including: a boosting filter stage configured to process a set of initial candidate portions of digital image data using a boosting chain to produce a set of intermediate candidate portions, wherein the boosting chain includes a plurality of boosting chain nodes to identify candidate portions and a boot strap function following each of the plurality of boosting chain nodes, the boot strap function to use a weak learner of a previous boosting chain node in training another boosting chain node of the boosting chain, wherein the weak learner includes building a simple decision stump on a histogram of a Haar-like feature on a training set; and a post-filter stage configured to process the set of intermediate candidate portions to produce a set of final candidate portions, wherein at least one of the final candidate portions includes detected face image data. | 53. An apparatus comprising: one or more processors; and memory having instructions including logic executable by the one or more processors to Perform a multiple stage face detection scheme to detect at least one human face within a digital image, the memory including: a boosting filter stage configured to process a set of initial candidate portions of digital image data using a boosting chain to produce a set of intermediate candidate portions, wherein the boosting chain includes a plurality of boosting chain nodes to identify candidate portions and a boot strap function following each of the plurality of boosting chain nodes, the boot strap function to use a weak learner of a previous boosting chain node in training another boosting chain node of the boosting chain, wherein the weak learner includes building a simple decision stump on a histogram of a Haar-like feature on a training set; and a post-filter stage configured to process the set of intermediate candidate portions to produce a set of final candidate portions, wherein at least one of the final candidate portions includes detected face image data. 62. The apparatus as recited in claim 53 , wherein as part of the post-filter stage the logic is further configured to perform at least one process selected from a group of processes that includes a lighting correction process, a histogram equalization process a color filter process, and an SVM filter process. | 0.566852 |
10,114,873 | 8 | 12 | 8. A method comprising: processing a post shared by a user of an online social network in a feed of the online social network, the post comprising textual content and being identifiable through one or more objects stored in a database, the feed being displayable in a user interface on a display device, the processing of the post comprising: identifying a first keyword of the textual content of the post as being preceded by a first tag to define a first tagged keyword, identifying a first data source specified by the first tag, the first data source being external to a database system, identifying a second keyword of the textual content of the post as being preceded by the first tag or a second tag to define a second tagged keyword, and identifying a second data source specified by the first tag or the second tag, the second data source being different from the first data source and being external to the database system; requesting a first search of the first data source using the first keyword; requesting a second search of the second data source using the second keyword; and processing a plurality of content records identified by the searches, the processing of the content records comprising: selecting one or more of the content records as satisfying criteria specifying one or more of: a visibility of a content record, a relevance of a content record, a designated data source for a content record, a type of a content record, an action to perform in association with a content record, or a time range for an action to be performed in association with a content record, and responsive to selecting the one or more content records as satisfying the criteria, automatically generating and sharing in the feed a comment on the post, the comment comprising at least a portion of record content of the selected one or more content records; selecting a further content record in accordance with further criteria, the further criteria being configurable using a settings interface; automatically generating and sharing in the feed one or more further comments on the post, the one or more further comments comprising at least a portion of record content of the selected further content record; and automatically generating, using one or more heuristics, a feed tracked update associated with the selected further content record. | 8. A method comprising: processing a post shared by a user of an online social network in a feed of the online social network, the post comprising textual content and being identifiable through one or more objects stored in a database, the feed being displayable in a user interface on a display device, the processing of the post comprising: identifying a first keyword of the textual content of the post as being preceded by a first tag to define a first tagged keyword, identifying a first data source specified by the first tag, the first data source being external to a database system, identifying a second keyword of the textual content of the post as being preceded by the first tag or a second tag to define a second tagged keyword, and identifying a second data source specified by the first tag or the second tag, the second data source being different from the first data source and being external to the database system; requesting a first search of the first data source using the first keyword; requesting a second search of the second data source using the second keyword; and processing a plurality of content records identified by the searches, the processing of the content records comprising: selecting one or more of the content records as satisfying criteria specifying one or more of: a visibility of a content record, a relevance of a content record, a designated data source for a content record, a type of a content record, an action to perform in association with a content record, or a time range for an action to be performed in association with a content record, and responsive to selecting the one or more content records as satisfying the criteria, automatically generating and sharing in the feed a comment on the post, the comment comprising at least a portion of record content of the selected one or more content records; selecting a further content record in accordance with further criteria, the further criteria being configurable using a settings interface; automatically generating and sharing in the feed one or more further comments on the post, the one or more further comments comprising at least a portion of record content of the selected further content record; and automatically generating, using one or more heuristics, a feed tracked update associated with the selected further content record. 12. The method of claim 8 , wherein the comment further comprises a summary of the selected one or more content records. | 0.675676 |
8,484,190 | 9 | 15 | 9. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause data processing apparatus to perform operations comprising: receiving, at a search interface, a first search query from a user; determining, based on a probability model of previous behavior of a collection of users, that the first search query is a trigger query, wherein the probability model is based on a probability of users of the collection of users selecting local search results in response to the first search query; in response to determining that the first search query is a trigger query, prompting the user for additional input, the prompting occurring prior to submission of the first search query to the search system; refining the first search query using the additional user input; and submitting the refined first search query to the search system. | 9. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause data processing apparatus to perform operations comprising: receiving, at a search interface, a first search query from a user; determining, based on a probability model of previous behavior of a collection of users, that the first search query is a trigger query, wherein the probability model is based on a probability of users of the collection of users selecting local search results in response to the first search query; in response to determining that the first search query is a trigger query, prompting the user for additional input, the prompting occurring prior to submission of the first search query to the search system; refining the first search query using the additional user input; and submitting the refined first search query to the search system. 15. The computer program product of claim 9 , where prompting the user for additional input includes modifying the search interface to include a suggestion of additional information. | 0.739255 |
8,335,780 | 6 | 7 | 6. A relational processor (RP) to create, maintain and query a relational database by assigning, storing and retrieving a unique associate for each instance of a relation for one or more relations and a plurality of instances of a relation, comprising (a) input means to receive data comprised of one or more relations, one or more relation instances, and one or more queries with additional means to (1) assign an integer i to a relation R making an Ri thereby allowing multiple relations each with its own number of domains k making relations of the form Ri (d 1 , d 2 , through dk) where a dk is the k th domain; (2) assign the integer j to the j th instance of said Ri making Rij; (3) make an associate aij comprising said i and said j; (4) output said Rij, said aij and said query; (b) an Associate Array Manager (AAM) with means to (1) receive said Rij, said aij and said query from the input means; (2) decompose said Rij into k single domain instances rij making rij (d 1 ), rij (d 2 ), through rij (dk); (3) make k single domain relation keys comprised of the relation index i and the domain value i|d 1 |, i|d 2 | through i|dk|; (4) make k single domain relation commands comprising retrieve (also called the search command) and store (also called the insert command); (5) output said domain keys i|d 1 |, i|d 2 | through i|dk| and said k commands to a specified Associate Processor for each of the k domains; (c) one or more Associate Processors (AP) each including memory means each with processing means to (1) receive the single domain keys i|d 1 |, i|d 2 | through i|dk|, the aij and the k single domain commands from the AAM; (2) store in said memory said associate aij using said single domain keys i|d 1 |, i|d 2 | through i|dk|, if said Rij does not exist in the database; (3) retrieve from said memory for each said single domain key the corresponding sets of associates denoted {aij} 1 , {aij} 2 , through {aij} k; (4) output said associate sets {aij} 1 , {aij} 2 , through {aij} k to one or more Set Processors (SP); (d) one or more Set Processors each comprising (1) input means to receive intra single domain commands comprising at least AND for each said single domain; (2) input means to receive said sets {aij} 1 , {aij} 2 , through {aij} k output by one or more said AP; (3) memory (also known as Set Memory) and processing means to store said associate sets implicitly using said indices i, j and k where implicitly comprises using the indices i and j to address a word in said Set Memory (also called the Set Memory Word) and the indices 1 , 2 , through k to set bit 0, bit 1, through bit k−1 in said Set Memory Word, for each aij that is in said associate sets {aij} 1 , {aij} 2 , through {aij} k; (4) logic processing means to perform the set intersection operation on said sets {aij} 1 , {aij} 2 , through {aij} k making the response set {aij} using said Set Memory words; (5) output means for outputting associates {aij} responsive to a query. | 6. A relational processor (RP) to create, maintain and query a relational database by assigning, storing and retrieving a unique associate for each instance of a relation for one or more relations and a plurality of instances of a relation, comprising (a) input means to receive data comprised of one or more relations, one or more relation instances, and one or more queries with additional means to (1) assign an integer i to a relation R making an Ri thereby allowing multiple relations each with its own number of domains k making relations of the form Ri (d 1 , d 2 , through dk) where a dk is the k th domain; (2) assign the integer j to the j th instance of said Ri making Rij; (3) make an associate aij comprising said i and said j; (4) output said Rij, said aij and said query; (b) an Associate Array Manager (AAM) with means to (1) receive said Rij, said aij and said query from the input means; (2) decompose said Rij into k single domain instances rij making rij (d 1 ), rij (d 2 ), through rij (dk); (3) make k single domain relation keys comprised of the relation index i and the domain value i|d 1 |, i|d 2 | through i|dk|; (4) make k single domain relation commands comprising retrieve (also called the search command) and store (also called the insert command); (5) output said domain keys i|d 1 |, i|d 2 | through i|dk| and said k commands to a specified Associate Processor for each of the k domains; (c) one or more Associate Processors (AP) each including memory means each with processing means to (1) receive the single domain keys i|d 1 |, i|d 2 | through i|dk|, the aij and the k single domain commands from the AAM; (2) store in said memory said associate aij using said single domain keys i|d 1 |, i|d 2 | through i|dk|, if said Rij does not exist in the database; (3) retrieve from said memory for each said single domain key the corresponding sets of associates denoted {aij} 1 , {aij} 2 , through {aij} k; (4) output said associate sets {aij} 1 , {aij} 2 , through {aij} k to one or more Set Processors (SP); (d) one or more Set Processors each comprising (1) input means to receive intra single domain commands comprising at least AND for each said single domain; (2) input means to receive said sets {aij} 1 , {aij} 2 , through {aij} k output by one or more said AP; (3) memory (also known as Set Memory) and processing means to store said associate sets implicitly using said indices i, j and k where implicitly comprises using the indices i and j to address a word in said Set Memory (also called the Set Memory Word) and the indices 1 , 2 , through k to set bit 0, bit 1, through bit k−1 in said Set Memory Word, for each aij that is in said associate sets {aij} 1 , {aij} 2 , through {aij} k; (4) logic processing means to perform the set intersection operation on said sets {aij} 1 , {aij} 2 , through {aij} k making the response set {aij} using said Set Memory words; (5) output means for outputting associates {aij} responsive to a query. 7. The SPs of claim 6 wherein each said SP has two or more said input means and one said output means and each said SP's output may be connected to the input of different SP whereby for said RP with three or more said APs said sets {aij} 1 , {aij} 2 , through {aij} k output by each AP produce one said response set {aij}. | 0.533333 |
9,966,077 | 10 | 11 | 10. The speech recognition device according to claim 9 , wherein when the speech continuation time is longer than a predetermined length, the determiner increases weights by which a second likelihood, indicating a likelihood of the second speech recognition result information, and a third likelihood, indicating a likelihood of the third speech recognition result information, are multiplied, compared to weights, by which a first likelihood, indicating a likelihood of the first speech recognition result information, and a fourth likelihood, indicating a likelihood of the fourth speech recognition result information, are multiplied. | 10. The speech recognition device according to claim 9 , wherein when the speech continuation time is longer than a predetermined length, the determiner increases weights by which a second likelihood, indicating a likelihood of the second speech recognition result information, and a third likelihood, indicating a likelihood of the third speech recognition result information, are multiplied, compared to weights, by which a first likelihood, indicating a likelihood of the first speech recognition result information, and a fourth likelihood, indicating a likelihood of the fourth speech recognition result information, are multiplied. 11. The speech recognition device according to claim 10 , wherein when the speech continuation time is longer than the predetermined length, the determiner increases the weight by which the second likelihood is multiplied compared to the weight by which the third likelihood is multiplied. | 0.5 |
9,116,984 | 1 | 10 | 1. A method of automatically summarizing an electronic conversation thread, the method being implemented by a processor executing executable instructions on a memory storage, comprising: receiving a conversation thread comprised of electronic communications; processing the electronic communications of the received conversation thread to identify text components, the text components including phrases in the electronic communications; selecting at least two of the electronic communications for use in generating a conversation thread summary; discarding, from the selected electronic communications, electronic communications being duplicates of other selected electronic communications; ranking the selected electronic communications based on ranking criteria including importance, weight or relevance of various features and properties associated with each of the selected electronic communications; processing the text components to identify key words based on the ranking of the selected electronic communications; and generating the conversation thread summary comprising a portion of the key words and the text components, wherein the key words and the text components are selected based on the ranking of the selected electronic communications. | 1. A method of automatically summarizing an electronic conversation thread, the method being implemented by a processor executing executable instructions on a memory storage, comprising: receiving a conversation thread comprised of electronic communications; processing the electronic communications of the received conversation thread to identify text components, the text components including phrases in the electronic communications; selecting at least two of the electronic communications for use in generating a conversation thread summary; discarding, from the selected electronic communications, electronic communications being duplicates of other selected electronic communications; ranking the selected electronic communications based on ranking criteria including importance, weight or relevance of various features and properties associated with each of the selected electronic communications; processing the text components to identify key words based on the ranking of the selected electronic communications; and generating the conversation thread summary comprising a portion of the key words and the text components, wherein the key words and the text components are selected based on the ranking of the selected electronic communications. 10. The method of claim 1 , wherein ranking the selected electronic communications based on one or more ranking criteria further comprises ranking the selected electronic communications based on a date and time associated with each of the selected electronic communications. | 0.619444 |
7,797,384 | 6 | 8 | 6. A non-transitory machine readable storage having stored thereon a computer program for dynamically restructuring a named collaborative context, the computer program comprising a routine set of instructions which when executed by a machine causes the machine to perform the steps of: composing a first arrangement of collaborators, roles, tools and resources in a named collaborative space; rendering said first arrangement in a user interface to permit collaborator interactions with said tools and resources; monitoring said named collaborative space for changes in state; and, responsive to a change in state in said named collaborative space, composing a second arrangement of collaborators, roles, tools and resources and rendering said second arrangement in place of said first arrangement. | 6. A non-transitory machine readable storage having stored thereon a computer program for dynamically restructuring a named collaborative context, the computer program comprising a routine set of instructions which when executed by a machine causes the machine to perform the steps of: composing a first arrangement of collaborators, roles, tools and resources in a named collaborative space; rendering said first arrangement in a user interface to permit collaborator interactions with said tools and resources; monitoring said named collaborative space for changes in state; and, responsive to a change in state in said named collaborative space, composing a second arrangement of collaborators, roles, tools and resources and rendering said second arrangement in place of said first arrangement. 8. The non-transitory machine readable storage of claim 6 , wherein said rendering step comprises the step of aggregating a portal view according to said first arrangement, and wherein said re-rendering step comprises the step of aggregating a different portal view according to said second arrangement. | 0.5 |
8,473,299 | 1 | 15 | 1. A method comprising: selecting a top level flow controller that is a recursive transition network flow controller and a finite state model, to yield a selected top level flow controller; selecting available reusable subdialogs for each application part below the top level flow controller, to yield selected reusable subdialogs; developing a subdialog for each application part not having an available subdialog, to yield developed subdialogs; and testing and deploying a spoken dialog service using the selected top level flow controller, the selected reusable subdialogs and the developed subdialogs. | 1. A method comprising: selecting a top level flow controller that is a recursive transition network flow controller and a finite state model, to yield a selected top level flow controller; selecting available reusable subdialogs for each application part below the top level flow controller, to yield selected reusable subdialogs; developing a subdialog for each application part not having an available subdialog, to yield developed subdialogs; and testing and deploying a spoken dialog service using the selected top level flow controller, the selected reusable subdialogs and the developed subdialogs. 15. The method of claim 1 , wherein the available reusable subdialogs are one of a billing subdialog and a credit rule-based flow controllers. | 0.712551 |
10,109,270 | 11 | 14 | 11. A system comprising: one or more computers; and a non-transitory computer-readable medium coupled to the one or more computers having instructions stored thereon, which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving context data from a client device of a user; selecting a user context corresponding to the context data from the client device, the user context being selected from among a plurality of user contexts, and the user context indicating a level of complexity of speech that the user is likely able to comprehend at a given time when the context data was received; selecting, from among a plurality of candidate text segments that correspond to different levels of complexity of speech, the text segment for text-to-speech synthesis by a text-to-speech module that best matches the selected user context; generating audio data comprising a synthesized utterance of the selected text segment using the text-to-speech module; and providing, to the client device, the audio data comprising the synthesized utterance of the selected text segment. | 11. A system comprising: one or more computers; and a non-transitory computer-readable medium coupled to the one or more computers having instructions stored thereon, which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving context data from a client device of a user; selecting a user context corresponding to the context data from the client device, the user context being selected from among a plurality of user contexts, and the user context indicating a level of complexity of speech that the user is likely able to comprehend at a given time when the context data was received; selecting, from among a plurality of candidate text segments that correspond to different levels of complexity of speech, the text segment for text-to-speech synthesis by a text-to-speech module that best matches the selected user context; generating audio data comprising a synthesized utterance of the selected text segment using the text-to-speech module; and providing, to the client device, the audio data comprising the synthesized utterance of the selected text segment. 14. The system of claim 11 , wherein: receiving the context data comprises receiving data indicating a location, speed, or movement pattern of the client device; and selecting the user context comprises selecting the user context based on the location, speed, or movement pattern of the client device indicated by the context data. | 0.697441 |
9,602,310 | 1 | 6 | 1. A message correlation system comprising: a message manager and processor that determine whether there are two or more outstanding queries to which a response from a user to any of the outstanding queries that includes no context would render the response uncorrelatable to one of the outstanding queries; and a keyword management module that correlates a keyword associated with a response to an outstanding query, wherein, when there is a conflict where the keyword is used in at least two of the two or more outstanding queries or the keyword is not used in the two or more outstanding queries, a supplemental query is sent to the user requesting clarification. | 1. A message correlation system comprising: a message manager and processor that determine whether there are two or more outstanding queries to which a response from a user to any of the outstanding queries that includes no context would render the response uncorrelatable to one of the outstanding queries; and a keyword management module that correlates a keyword associated with a response to an outstanding query, wherein, when there is a conflict where the keyword is used in at least two of the two or more outstanding queries or the keyword is not used in the two or more outstanding queries, a supplemental query is sent to the user requesting clarification. 6. The system of claim 1 , wherein one or more of an end user, an end user device and the keyword management module select the keyword. | 0.693182 |
7,650,276 | 4 | 5 | 4. The method of claim 1 wherein: the first data source identifies one of: 1) an object field; 2) an object property; and 3) an Extensible Markup Language document element. | 4. The method of claim 1 wherein: the first data source identifies one of: 1) an object field; 2) an object property; and 3) an Extensible Markup Language document element. 5. The method of claim 4 wherein: an object is a JavaBean. | 0.5 |
8,145,654 | 1 | 7 | 1. A computer-implemented method for keyword searching, the method comprising: generating, by a server, tokens for a plurality of keywords in a document collection, wherein the generating further comprises determining a keyword position of a keyword in a document of the document collection, and determining a number of noisy keywords preceding the keyword in the document; merging the tokens to create an index; receiving a search query, wherein the search query includes at least one search phrase; receiving, for the at least one search phrase, an indication from a user specifying to perform one of a noisy phrase search or a noiseless phrase search; searching the index for the at least one search phrase based on the indication received from the user; and when the indication from the user specifies a noiseless phrase search, performing the noiseless phrase search at least in part by subtracting a value of the keyword position by the number of noisy keywords preceding the keyword. | 1. A computer-implemented method for keyword searching, the method comprising: generating, by a server, tokens for a plurality of keywords in a document collection, wherein the generating further comprises determining a keyword position of a keyword in a document of the document collection, and determining a number of noisy keywords preceding the keyword in the document; merging the tokens to create an index; receiving a search query, wherein the search query includes at least one search phrase; receiving, for the at least one search phrase, an indication from a user specifying to perform one of a noisy phrase search or a noiseless phrase search; searching the index for the at least one search phrase based on the indication received from the user; and when the indication from the user specifies a noiseless phrase search, performing the noiseless phrase search at least in part by subtracting a value of the keyword position by the number of noisy keywords preceding the keyword. 7. The computer-implemented method of claim 1 , wherein the search query includes both noisy search phrases and noiseless search phrases. | 0.864087 |
7,890,465 | 13 | 14 | 13. The method of claim 1 further including: digitally signing said encrypted file using a digital signature. | 13. The method of claim 1 further including: digitally signing said encrypted file using a digital signature. 14. The method of claim 13 wherein said digital signature is a PKI based digital signature. | 0.5 |
9,984,161 | 7 | 9 | 7. A blog search engine data processing system comprising: a host server comprising memory and at least one processor and configured for coupling to different client computing devices over a computer communications network; a blog search engine executing in the memory of the host server and configured to query blog content according to different query terms; and, an authorship sensitive relevance module coupled to the blog search engine, the authorship sensitive relevance module comprising program code enabled upon execution in the memory of the host server to extract authorship criteria from a search engine query provided in a form completed by a user specifying both query terms to query World Wide Web (“Web”) content (“blog content”) and also authorship criteria for authors of blog content, to evaluate the authorship criteria for each blog author of corresponding blog content returned by the search engine query based upon a degree to which the blog author of the corresponding blog content is deemed both authoritative and trustworthy, blog authors of corresponding blog content determined to be more authoritative and trustworthy having a higher ranking than blog authors of the corresponding blog content determined to be less authoritative and trustworthy, to compute a relevance for each entry in a results set based upon the evaluated authorship criteria, wherein entries for blog authors of higher ranking are computed to have a higher relevance and entries for blog authors of lower ranking are computed to have a lower relevance, to sort the results set from an entry in the results set of highest relevance to an entry in the results set of lowest relevance and to present in order of relevance a listing of blog content corresponding to the results set, wherein the authorship criteria includes an indication of a degree to which a blog author of blog content in the results set is deemed both authoritative and trustworthy, wherein authoritativeness is computed by determining a number of others whom have subscribed to blog content authored by the blog author, and wherein trustworthiness is computed by at least one of determining whether the blog author is known to a querying end user through inclusion in a list of contacts for the end user and frequent communications exchanged by the end user with the blog author, the blog author being a writer of blog content; and, wherein the program code of the module further extracts from the search engine query provided in the form completed by the user, content criteria for the blog content in the respective entries of the results set returned by the search engine query, evaluates the content criteria for blog content returned by the search engine query, and computes the relevance for each entry in the results set based both upon the evaluated authorship criteria and also the evaluated content criteria. | 7. A blog search engine data processing system comprising: a host server comprising memory and at least one processor and configured for coupling to different client computing devices over a computer communications network; a blog search engine executing in the memory of the host server and configured to query blog content according to different query terms; and, an authorship sensitive relevance module coupled to the blog search engine, the authorship sensitive relevance module comprising program code enabled upon execution in the memory of the host server to extract authorship criteria from a search engine query provided in a form completed by a user specifying both query terms to query World Wide Web (“Web”) content (“blog content”) and also authorship criteria for authors of blog content, to evaluate the authorship criteria for each blog author of corresponding blog content returned by the search engine query based upon a degree to which the blog author of the corresponding blog content is deemed both authoritative and trustworthy, blog authors of corresponding blog content determined to be more authoritative and trustworthy having a higher ranking than blog authors of the corresponding blog content determined to be less authoritative and trustworthy, to compute a relevance for each entry in a results set based upon the evaluated authorship criteria, wherein entries for blog authors of higher ranking are computed to have a higher relevance and entries for blog authors of lower ranking are computed to have a lower relevance, to sort the results set from an entry in the results set of highest relevance to an entry in the results set of lowest relevance and to present in order of relevance a listing of blog content corresponding to the results set, wherein the authorship criteria includes an indication of a degree to which a blog author of blog content in the results set is deemed both authoritative and trustworthy, wherein authoritativeness is computed by determining a number of others whom have subscribed to blog content authored by the blog author, and wherein trustworthiness is computed by at least one of determining whether the blog author is known to a querying end user through inclusion in a list of contacts for the end user and frequent communications exchanged by the end user with the blog author, the blog author being a writer of blog content; and, wherein the program code of the module further extracts from the search engine query provided in the form completed by the user, content criteria for the blog content in the respective entries of the results set returned by the search engine query, evaluates the content criteria for blog content returned by the search engine query, and computes the relevance for each entry in the results set based both upon the evaluated authorship criteria and also the evaluated content criteria. 9. The system of claim 7 , wherein the authorship criteria comprises an extent to which the blog author of corresponding blog content is deemed authoritative. | 0.55618 |
9,055,147 | 1 | 14 | 1. A method comprising: initiating, at one or more computing devices, a finite state machine; receiving, at the one or more computing devices, a voice input; interpreting, at the one or more computing devices, the received voice input, comprising: transitioning to a domain state functionality of the finite state machine, selecting a generic prompt corresponding to the domain state functionality, and selecting a specific prompt corresponding to the generic prompt, wherein the specific prompt comprises a variant of the generic prompt and also corresponds to the domain state functionality; and transmitting, at the one or more computing devices, the specific prompt in a response. | 1. A method comprising: initiating, at one or more computing devices, a finite state machine; receiving, at the one or more computing devices, a voice input; interpreting, at the one or more computing devices, the received voice input, comprising: transitioning to a domain state functionality of the finite state machine, selecting a generic prompt corresponding to the domain state functionality, and selecting a specific prompt corresponding to the generic prompt, wherein the specific prompt comprises a variant of the generic prompt and also corresponds to the domain state functionality; and transmitting, at the one or more computing devices, the specific prompt in a response. 14. The method of claim 1 , wherein the specific prompt is selected based on a configuration parameter. | 0.733161 |
9,846,901 | 6 | 7 | 6. The method of claim 1 , wherein the characteristic specified in the request is a first characteristic, wherein identifying the first product for recommendation comprises determining, based at least in part on analysis of a first natural language product review, that the first product also matches a second characteristic specified in the request. | 6. The method of claim 1 , wherein the characteristic specified in the request is a first characteristic, wherein identifying the first product for recommendation comprises determining, based at least in part on analysis of a first natural language product review, that the first product also matches a second characteristic specified in the request. 7. The method of claim 6 , further comprising updating the ontology to include a relationship between the first product and the second characteristic determined to match the first product based on the first natural language product review, and to include a link to the first natural language product review in association with the relationship between the first product and the second characteristic. | 0.5 |
7,668,791 | 11 | 14 | 11. A computer readable storage medium containing executable program instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving a search term comprising a noun; finding relevant electronic resources that match the search term; displaying a list of relevant electronic resources and snippets of the relevant electronic resources in the list that comprise words matching the search term; parsing a plurality of relevant electronic documents to discover factual descriptions of sentences that comprise the noun of the search term and one or more verbs matching words of a fact-word table constructed to include a list of verbs determined to be indicative of fact expressions; eliminating portions of the relevant electronic documents from fact extraction processing that comprise words not matching the search term and words of the fact-word table; examining the discovered factual descriptions to identify the linguistic constituents of the factual descriptions after eliminating portions of the electronic documents; determining whether to present a factual description as a fact relevant to the search term based on the identified linguistic constituent by applying excluding rules to candidate factual descriptions in relation to the linguistic constituents, scoring candidate factual descriptions based on certainty of a matching fact-word and on individual weights of subject and object noun phrases, and eliminating candidate factual descriptions from consideration according to the excluding rules and scoring of the factual descriptions; and presenting at least a portion of a sentence that contains the search term and a factual description determined to be a fact relevant to the search term. | 11. A computer readable storage medium containing executable program instructions that, when executed by a processor, cause the processor to perform acts comprising: receiving a search term comprising a noun; finding relevant electronic resources that match the search term; displaying a list of relevant electronic resources and snippets of the relevant electronic resources in the list that comprise words matching the search term; parsing a plurality of relevant electronic documents to discover factual descriptions of sentences that comprise the noun of the search term and one or more verbs matching words of a fact-word table constructed to include a list of verbs determined to be indicative of fact expressions; eliminating portions of the relevant electronic documents from fact extraction processing that comprise words not matching the search term and words of the fact-word table; examining the discovered factual descriptions to identify the linguistic constituents of the factual descriptions after eliminating portions of the electronic documents; determining whether to present a factual description as a fact relevant to the search term based on the identified linguistic constituent by applying excluding rules to candidate factual descriptions in relation to the linguistic constituents, scoring candidate factual descriptions based on certainty of a matching fact-word and on individual weights of subject and object noun phrases, and eliminating candidate factual descriptions from consideration according to the excluding rules and scoring of the factual descriptions; and presenting at least a portion of a sentence that contains the search term and a factual description determined to be a fact relevant to the search term. 14. The computer readable storage medium of claim 11 , wherein the acts further comprise: comparing the score of each factual description remaining for consideration to a threshold; and for each factual description that is taken from an electronic document that contains the search term and that has a score that exceeds the threshold, presenting at least a portion of the sentence containing the factual description as a fact relevant to the search term. | 0.5 |
7,502,770 | 3 | 4 | 3. The system of claim 2 , wherein collecting a simple poll via an optional voting scheme indicates whether a user liked an explanation; wherein an encryption scheme hides a user's identity, and wherein it is guaranteed that a user votes only once. | 3. The system of claim 2 , wherein collecting a simple poll via an optional voting scheme indicates whether a user liked an explanation; wherein an encryption scheme hides a user's identity, and wherein it is guaranteed that a user votes only once. 4. The system of claim 3 , wherein said simple poll comprises a voting scheme comprising a user operated forward and back selection mechanism. | 0.5 |
7,478,048 | 14 | 15 | 14. The program storage device according to claim 13 , wherein said receiving user selection input to add one or more hyperlinks comprises adding the hyperlinks to a content stream comprising a TTS voice XML file by the steps of the user editing the TTS voice XML file in the edit area of said graphic user interface, marking or entering the parts to be added with the hyperlinks, invoking the corresponding icons and entering the corresponding hyperlink addresses. | 14. The program storage device according to claim 13 , wherein said receiving user selection input to add one or more hyperlinks comprises adding the hyperlinks to a content stream comprising a TTS voice XML file by the steps of the user editing the TTS voice XML file in the edit area of said graphic user interface, marking or entering the parts to be added with the hyperlinks, invoking the corresponding icons and entering the corresponding hyperlink addresses. 15. The program storage device according to claim 14 , characterized in that when the user marks or enters the same parts to be added with the hyperlinks in the edit area of the graphic user interface for many times and invokes the same hyperlink attributes, the hyperlinks for the whole TTS voice XML stream are batch-added. | 0.5 |
7,979,452 | 5 | 6 | 5. A method for retrieving task information as set forth in claim 4 , wherein the acts of acquiring associating, indexing, correlating, and forming are done over a computer network. | 5. A method for retrieving task information as set forth in claim 4 , wherein the acts of acquiring associating, indexing, correlating, and forming are done over a computer network. 6. A method for retrieving task information as set forth in claim 5 , further comprising an act of updating the task-based index as new documents are available. | 0.5 |
8,099,662 | 8 | 11 | 8. An apparatus comprising: one or more processors and a memory; an input module adapted to receive, from a user interface, an annotation associated with a background image; a control module adapted to add the annotation to a queue of pending annotations; an output module adapted to transmit the annotation from the apparatus to a server; wherein the control module removes the annotation from the queue of pending annotations, and adds the annotation to a list of acknowledged annotations, when an acknowledgment of the annotation is received by the apparatus from the server; wherein the output module generates a display image comprising the background image, annotations in the list of acknowledged annotations, and annotations in the queue of pending annotations; and wherein the one or more processors and the memory cooperate to implement at least in part the input, output and control modules. | 8. An apparatus comprising: one or more processors and a memory; an input module adapted to receive, from a user interface, an annotation associated with a background image; a control module adapted to add the annotation to a queue of pending annotations; an output module adapted to transmit the annotation from the apparatus to a server; wherein the control module removes the annotation from the queue of pending annotations, and adds the annotation to a list of acknowledged annotations, when an acknowledgment of the annotation is received by the apparatus from the server; wherein the output module generates a display image comprising the background image, annotations in the list of acknowledged annotations, and annotations in the queue of pending annotations; and wherein the one or more processors and the memory cooperate to implement at least in part the input, output and control modules. 11. The apparatus of claim 8 : wherein the acknowledgment of the annotation indicates a Z-order for the annotation; and wherein the output module generates the display image according to the Z-orders of the annotations. | 0.688034 |
8,965,915 | 17 | 18 | 17. The non-transitory medium of claim 16 , comprising instructions compatible with: the set of characteristics including metadata of the initial query comprising at least one of: a number of attributes in the initial result set, a data type of each of the attributes, a frequency of usage per user, a uniqueness constraint on the attributes, anullability of individual attributes, and a functional dependency between the attributes. | 17. The non-transitory medium of claim 16 , comprising instructions compatible with: the set of characteristics including metadata of the initial query comprising at least one of: a number of attributes in the initial result set, a data type of each of the attributes, a frequency of usage per user, a uniqueness constraint on the attributes, anullability of individual attributes, and a functional dependency between the attributes. 18. The non-transitory medium of claim 17 , comprising instructions compatible with: the set of characteristics including aggregate statistical characteristics comprising at least one of generic aggregate statistics and scenario aggregate statistics, the generic aggregate statistics being calculated in a manner that is independent of a set of semantics of the attributes, and the scenario aggregate statistics being defined through a domain expert and being relevant in a particular scenario to enable incorporation of a domain-specific interpretation of the semantics of the each attribute and each set of data of the at least one of the initial result set and the subsequent result set. | 0.5 |
7,870,161 | 1 | 13 | 1. A method for string signature scanning, comprising: processing one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each a variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; receiving a particular string field comprising a string of data values; identifying any signatures included in the particular string field including scanning the particular string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size and searching the particular string field for the one or more signatures associated with one or more identified fingerprints using the one or more follow-on search data structures at the locations where the one or more identified fingerprints are found; and outputting any identified signatures in the particular string field. | 1. A method for string signature scanning, comprising: processing one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each a variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; receiving a particular string field comprising a string of data values; identifying any signatures included in the particular string field including scanning the particular string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size and searching the particular string field for the one or more signatures associated with one or more identified fingerprints using the one or more follow-on search data structures at the locations where the one or more identified fingerprints are found; and outputting any identified signatures in the particular string field. 13. The method of claim 1 , where the one or more search data structures for the one or more fingerprints associated with the one or more signatures includes one or more search data structures stored in one or more content addressable memories (CAM) and scanning the particular string field for the one or more fingerprints associated with the one or more signatures includes using the one or more content addressable memories (CAM). | 0.672961 |
8,473,897 | 1 | 2 | 1. A method for defining declarative code in an intermediate machine readable representation, including: specifying a plurality of programming constructs of a declarative programming language including specifying each type associated with the plurality of programming constructs as a function of at least one constraint on type, wherein values associated with the plurality of programming constructs are conformable to a plurality of types such that a particular value is conformable with each of the plurality of types in which the particular value does not violate a constraint codified in a type declaration, and wherein the specifying includes specifying additional state information about at least one programming construct of the plurality of programming constructs; and based on the plurality of programming constructs, generating in memory of a computing device at least one abstract syntax tree structure in a machine readable intermediate language representation of the declarative programming language, wherein the generating includes representing the additional state information in the at least one abstract syntax tree structure as at least one attached property. | 1. A method for defining declarative code in an intermediate machine readable representation, including: specifying a plurality of programming constructs of a declarative programming language including specifying each type associated with the plurality of programming constructs as a function of at least one constraint on type, wherein values associated with the plurality of programming constructs are conformable to a plurality of types such that a particular value is conformable with each of the plurality of types in which the particular value does not violate a constraint codified in a type declaration, and wherein the specifying includes specifying additional state information about at least one programming construct of the plurality of programming constructs; and based on the plurality of programming constructs, generating in memory of a computing device at least one abstract syntax tree structure in a machine readable intermediate language representation of the declarative programming language, wherein the generating includes representing the additional state information in the at least one abstract syntax tree structure as at least one attached property. 2. The method of claim 1 , wherein the generating includes representing type checking data in the at least one abstract syntax tree structure as at least one attached property. | 0.59633 |
10,120,861 | 15 | 16 | 15. A domain classification system for domain based natural language processing, comprising: memory storing: query models each for a domain of a set of domains and comprising at least an ontology having a set of semantic tokens organized in hierarchical levels, and a set of domain-specific semantic constructions each including one or more of the semantic tokens linked by one of a set of predefined grammatical relations; trigram corpora, each corpus for a domain of the set of domains and each having entries comprising: trigrams obtained based on the query model of the domain, each trigram having a first, second and third semantic token; and corresponding trigram probabilities each representing a relative probability that the third semantic token appearing in the trigrams given the first and the second sematic tokens; and computer executable instructions; and a processor in communication with the memory, and when executing the instructions, configured to implement software components comprising: a receiving component configured to receive an input text from a remote device via a network connection; a set of domain relevance analyzer components corresponding to the set of domains configured to determine relevance scores for the input text with respect to the set of domains based on tokenized sequences of the input text corresponding to the set of domains, the query models, and the trigram corpora; a classifier component configured to classify the input text among the set of domains based on the relevance scores with respect to the set of domains for the input text; and a component configured to transmit, to the remote device, a communication comprising the input text based upon the classifying. | 15. A domain classification system for domain based natural language processing, comprising: memory storing: query models each for a domain of a set of domains and comprising at least an ontology having a set of semantic tokens organized in hierarchical levels, and a set of domain-specific semantic constructions each including one or more of the semantic tokens linked by one of a set of predefined grammatical relations; trigram corpora, each corpus for a domain of the set of domains and each having entries comprising: trigrams obtained based on the query model of the domain, each trigram having a first, second and third semantic token; and corresponding trigram probabilities each representing a relative probability that the third semantic token appearing in the trigrams given the first and the second sematic tokens; and computer executable instructions; and a processor in communication with the memory, and when executing the instructions, configured to implement software components comprising: a receiving component configured to receive an input text from a remote device via a network connection; a set of domain relevance analyzer components corresponding to the set of domains configured to determine relevance scores for the input text with respect to the set of domains based on tokenized sequences of the input text corresponding to the set of domains, the query models, and the trigram corpora; a classifier component configured to classify the input text among the set of domains based on the relevance scores with respect to the set of domains for the input text; and a component configured to transmit, to the remote device, a communication comprising the input text based upon the classifying. 16. The domain classification system of claim 15 , wherein the processor, when executing the instructions, is further configured to implement software components comprising: a semantic construction expander component configured to obtain one expanded set of semantic constructions as semantic corpus for each domain by replacing at least one of the semantic tokens of at least one of the semantic constructions of the query model of the domain with corresponding semantic tokens at a lower hierarchical level in the ontology of the query model of the domain; and a trigram generator component configured to generate the trigram corpora by: generating the trigrams for each domain based on the expanded set of semantic constructions for the domain; and obtaining the trigram probabilities corresponding to the trigrams for each domain. | 0.5 |
8,627,442 | 2 | 4 | 2. The method of claim 1 , wherein building said plurality of HTTP message models further comprises developing said plurality of security rules. | 2. The method of claim 1 , wherein building said plurality of HTTP message models further comprises developing said plurality of security rules. 4. The method of claim 2 , wherein said building and developing further comprise chaining at least two given ones of said plurality of security rules together based on at least said given condition being common to both of said at least two given ones of said plurality of security rules. | 0.835624 |
9,053,500 | 34 | 36 | 34. A non-transitory computer readable medium bearing instructions for providing data to a web browser, said instructions being arranged to cause one or more processors upon execution thereof to perform the steps of: generating the data which includes a display region with associated content; determining if a pre-selected locale is mandatory; if the pre-selected locale is mandatory; formatting at least a portion of the associated content according to the pre-selected locale when generating the data; if the pre-selected locale is not mandatory: identifying a user-selected locale, and formatting at least a portion of the associated content according to the user-selected locale when generating the data; and transmitting the data to the web browser. | 34. A non-transitory computer readable medium bearing instructions for providing data to a web browser, said instructions being arranged to cause one or more processors upon execution thereof to perform the steps of: generating the data which includes a display region with associated content; determining if a pre-selected locale is mandatory; if the pre-selected locale is mandatory; formatting at least a portion of the associated content according to the pre-selected locale when generating the data; if the pre-selected locale is not mandatory: identifying a user-selected locale, and formatting at least a portion of the associated content according to the user-selected locale when generating the data; and transmitting the data to the web browser. 36. The non-transitory computer readable medium of claim 34 , wherein the request includes the user-specified locale. | 0.5 |
9,524,175 | 9 | 10 | 9. A non-transitory computer-readable storage medium storing program instructions executable by on one or more processors to implement a tool configured to: determine, for an overloaded operation invocation identified in source code of a computer program, whether the source code includes, as an argument to the invocation, an expression whose type is context-dependent; and in response to a determination that the source code includes, as an argument to the invocation, an expression whose type is context-dependent, determine, at an overload resolver to which the expression is provided as input, (a) whether each argument of the invocation, including the expression, is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations identified from the source code, and (b) whether a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria; in response to a determination that (a) each argument of the invocation is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations in the source code, and (b) a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate executable instructions for the invocation in accordance with the particular invocable operation declaration; and in response to a determination that none of the plurality of invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate an error indication; wherein the error is generated even though each argument of the invocation is compatible with a type of a corresponding parameter indicated in a plurality of invocable operation declarations in the source code. | 9. A non-transitory computer-readable storage medium storing program instructions executable by on one or more processors to implement a tool configured to: determine, for an overloaded operation invocation identified in source code of a computer program, whether the source code includes, as an argument to the invocation, an expression whose type is context-dependent; and in response to a determination that the source code includes, as an argument to the invocation, an expression whose type is context-dependent, determine, at an overload resolver to which the expression is provided as input, (a) whether each argument of the invocation, including the expression, is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations identified from the source code, and (b) whether a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria; in response to a determination that (a) each argument of the invocation is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations in the source code, and (b) a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate executable instructions for the invocation in accordance with the particular invocable operation declaration; and in response to a determination that none of the plurality of invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate an error indication; wherein the error is generated even though each argument of the invocation is compatible with a type of a corresponding parameter indicated in a plurality of invocable operation declarations in the source code. 10. The non-transitory computer-readable storage medium as recited in claim 9 , wherein the overloaded operation invocation comprises one of: a method invocation, or a constructor invocation. | 0.929259 |
9,256,694 | 15 | 16 | 15. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining that, among a set of search results that are each identified as at least potentially relevant by a search engine in response to a search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query; and in response to determining that, among the set of search results that are each identified as at least potentially relevant by the search engine in response to the search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query: providing a search results page that (i) includes a subset of the search results, including the one or more search results that are each classified by the search engine as very relevant to the search query, and one or more search results that are identified as at least potentially relevant by the search engine but that are not each classified by the search engine as very relevant to the search query, and (ii) includes a respective image in association with only those search results of the subset that are each classified by the search engine as very relevant to the search query, and (iii) does not include a respective image in association with those search results of the subset that are not each classified by the search engine as very relevant to the search query. | 15. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: determining that, among a set of search results that are each identified as at least potentially relevant by a search engine in response to a search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query; and in response to determining that, among the set of search results that are each identified as at least potentially relevant by the search engine in response to the search query submitted to the search engine, one or more of the search results are each classified by the search engine as very relevant to the search query: providing a search results page that (i) includes a subset of the search results, including the one or more search results that are each classified by the search engine as very relevant to the search query, and one or more search results that are identified as at least potentially relevant by the search engine but that are not each classified by the search engine as very relevant to the search query, and (ii) includes a respective image in association with only those search results of the subset that are each classified by the search engine as very relevant to the search query, and (iii) does not include a respective image in association with those search results of the subset that are not each classified by the search engine as very relevant to the search query. 16. The system of claim 15 , wherein the operations comprise: classifying a specific search result as very relevant to the search query based on an observed historical click through rate associated with the specific search result, the specific search result being one of the one or more search results that are each classified as very relevant to the search query. | 0.5 |
10,013,679 | 1 | 15 | 1. A method comprising: identifying, by a processor, first vehicle service data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the processor, wherein a first identifier uniquely identifies the first vehicle service data; associating, by the processor, a meaning with the first vehicle service data based on the terms of the natural human language represented by the first vehicle service data that match the one or more taxonomy terms; generating, by the processor, first metadata that represents the meaning associated with the first vehicle service data; generating vehicle service content based at least in part on the first metadata; generating, by the processor, second metadata that represents a meaning with at least a portion of second vehicle service data; aggregating, by the processor, at least the first metadata and the second metadata to produce aggregated metadata; associating, by the processor, the first identifier with the first metadata; receiving a request for the vehicle service content, wherein the request includes the first identifier and/or the first metadata, and in response to the request for the vehicle service content, sending the vehicle service content to be displayed by a service tool. | 1. A method comprising: identifying, by a processor, first vehicle service data represents terms of a natural human language that match one or more taxonomy terms within a defined taxonomy searchable by the processor, wherein a first identifier uniquely identifies the first vehicle service data; associating, by the processor, a meaning with the first vehicle service data based on the terms of the natural human language represented by the first vehicle service data that match the one or more taxonomy terms; generating, by the processor, first metadata that represents the meaning associated with the first vehicle service data; generating vehicle service content based at least in part on the first metadata; generating, by the processor, second metadata that represents a meaning with at least a portion of second vehicle service data; aggregating, by the processor, at least the first metadata and the second metadata to produce aggregated metadata; associating, by the processor, the first identifier with the first metadata; receiving a request for the vehicle service content, wherein the request includes the first identifier and/or the first metadata, and in response to the request for the vehicle service content, sending the vehicle service content to be displayed by a service tool. 15. The method of claim 1 , wherein the first identifier includes at least one repair order number. | 0.907821 |
10,068,132 | 10 | 17 | 10. A method comprising: accessing an image comprising a depiction of a page region; determining portions of the image depicting text within the page region: identifying a line segment depicted in the image, the line segment having a first part within one or more of the portions of the image depicting text and a second part outside of the portions of the image depicting text; identifying a color of the line segment, based on the second part of the line segment depicted in the image outside of the portions of the image depicting text; determining a difference value between the color of the line segment and a color of each element of the portions of the image depicting; and identifying, by one or more processors of a machine, the text by performing optical character recognition on the portions of the image depicting text while ignoring elements within the portions of the image depicting text that have the color of the line segment. | 10. A method comprising: accessing an image comprising a depiction of a page region; determining portions of the image depicting text within the page region: identifying a line segment depicted in the image, the line segment having a first part within one or more of the portions of the image depicting text and a second part outside of the portions of the image depicting text; identifying a color of the line segment, based on the second part of the line segment depicted in the image outside of the portions of the image depicting text; determining a difference value between the color of the line segment and a color of each element of the portions of the image depicting; and identifying, by one or more processors of a machine, the text by performing optical character recognition on the portions of the image depicting text while ignoring elements within the portions of the image depicting text that have the color of the line segment. 17. The method of claim 10 , further comprising: populating an item listing in an online marketplace using the text. | 0.866359 |
8,224,650 | 25 | 45 | 25. A computer readable storage medium having instructions, which when executed on a computer generate client side markup for a client in a client/server system, the instructions comprising: a first set of visual controls defined on an authoring page for a website having attributes related to a first modality of interaction with a user of the client that being visual renderings on the client device, and the attributes including at least one of location for visual rendering, font, background color, and foreground color, and the first set of controls being related to client side markup executable by a client browser; a second set of controls defined on the authoring page for defining desired operation on the client device having attributes related to a second modality of interaction with the user of the client that being at least one of recognition and audible prompting, the second set of controls being selectively associated with the first set of controls, and the second set of controls being related to client side markup executable by a client browser, the second set of controls comprising: a question control for generating markup related to audible prompting of a question; and an answer control for generating markup related to a grammar for recognition, the question and answer controls being associated with a semantic map comprising one or more semantic items that form a layer between individually associated visual domain primary controls and a non-visual recognition domain of the question and answer controls, the associated visual domain primary controls comprising markup; and a module operable on a computer, the module being configured to receive the authoring page, wherein the module is further configured to process the controls of the first set in the authoring page to generate client side markup by incorporating the attributes in the controls that is executable by the client browser on the client in the server/client system in accordance with the controls of the first set and the attributes of the controls of the first set to perform both visual rendering, and wherein the module is further configured to process the controls of the second set to generate client side markup by incorporating the attributes in the controls that is executable by the client browser on the client in the server/client system in accordance with the controls of the second set and the attributes of the controls of the second set in the authoring page. | 25. A computer readable storage medium having instructions, which when executed on a computer generate client side markup for a client in a client/server system, the instructions comprising: a first set of visual controls defined on an authoring page for a website having attributes related to a first modality of interaction with a user of the client that being visual renderings on the client device, and the attributes including at least one of location for visual rendering, font, background color, and foreground color, and the first set of controls being related to client side markup executable by a client browser; a second set of controls defined on the authoring page for defining desired operation on the client device having attributes related to a second modality of interaction with the user of the client that being at least one of recognition and audible prompting, the second set of controls being selectively associated with the first set of controls, and the second set of controls being related to client side markup executable by a client browser, the second set of controls comprising: a question control for generating markup related to audible prompting of a question; and an answer control for generating markup related to a grammar for recognition, the question and answer controls being associated with a semantic map comprising one or more semantic items that form a layer between individually associated visual domain primary controls and a non-visual recognition domain of the question and answer controls, the associated visual domain primary controls comprising markup; and a module operable on a computer, the module being configured to receive the authoring page, wherein the module is further configured to process the controls of the first set in the authoring page to generate client side markup by incorporating the attributes in the controls that is executable by the client browser on the client in the server/client system in accordance with the controls of the first set and the attributes of the controls of the first set to perform both visual rendering, and wherein the module is further configured to process the controls of the second set to generate client side markup by incorporating the attributes in the controls that is executable by the client browser on the client in the server/client system in accordance with the controls of the second set and the attributes of the controls of the second set in the authoring page. 45. The computer readable storage medium of claim 25 wherein the second set of controls further includes means defining a command for generating markup related to a grammar for one of navigation in the markup, help with a task, and repeating an audible prompt. | 0.772329 |
9,085,303 | 23 | 28 | 23. A vehicle personal assistant embodied in one or more non-transitory machine readable storage media, the vehicle personal assistant executable by a computing system to: receive a human-generated spoken natural language phrase; execute a semantic interpretation process on the human-generated spoken natural language phrase to derive, from the human-generated spoken natural language phrase, a trigger condition, a search action, and a search parameter to be used in executing the search action if the trigger condition is met, the trigger condition comprising a data value; monitor one or more vehicle-related real-time sensor inputs; compare a first vehicle-related real-time sensor input to the data value to determine whether the vehicle-related trigger condition has occurred; and in response to determining that the trigger condition has occurred: determine a current value of a second real-time input associated with the occurrence of the trigger condition; and execute the search action using (i) the current value of the second real-time input and (ii) the search parameter derived from the human-generated spoken natural language phrase. | 23. A vehicle personal assistant embodied in one or more non-transitory machine readable storage media, the vehicle personal assistant executable by a computing system to: receive a human-generated spoken natural language phrase; execute a semantic interpretation process on the human-generated spoken natural language phrase to derive, from the human-generated spoken natural language phrase, a trigger condition, a search action, and a search parameter to be used in executing the search action if the trigger condition is met, the trigger condition comprising a data value; monitor one or more vehicle-related real-time sensor inputs; compare a first vehicle-related real-time sensor input to the data value to determine whether the vehicle-related trigger condition has occurred; and in response to determining that the trigger condition has occurred: determine a current value of a second real-time input associated with the occurrence of the trigger condition; and execute the search action using (i) the current value of the second real-time input and (ii) the search parameter derived from the human-generated spoken natural language phrase. 28. The vehicle personal assistant of claim 23 , executable by the computing system to receive the vehicle-related real-time sensor inputs from a vehicle network of the vehicle. | 0.738938 |
7,529,753 | 28 | 39 | 28. A computer accessible storage hardware having stored thereon computer-executable instructions for providing application layer functionality between one or more database clients and one or more database servers, the computer executable instructions operable to: at a decoding layer above a network layer at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; extract query-language statements from the database messages; at a decoding layer above a network layer at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations: receiving database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decoding the database messages; and extracting query-language statements from the database messages; at an application layer above the decoding layer, a caching application operable for: receiving query-language statements extracted at the decoders comprising queries; receiving query-language statements extracted at the decoders comprising query results corresponding to the queries; and recording the queries and the query results corresponding to the queries in a cache residing at the first network location wherein the queries are associated with a corresponding query result; and a monitoring application operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders, wherein at least one observation is associated with a query result stored in the cache and communicate one or more observations associated with the queries to one or more computing systems at a fourth network location according to the needs of the one or more computer systems, wherein at least one of the computer systems maintains a web cache and is operable to modify the web cache based upon the communicated observations wherein observations on the database messages based at least in part on the query-language statement extracted at the decoders comprise the following: subject database instances of the query-language statements; network protocols and versions of the network protocols used to communicate the database messages; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; devices hosting the clients; and a number of queries communicated from each of the clients to each of one or more database instances; and at an application layer above the decoding layer at the first network location, process the query-language statements extracted at the decoding layer. | 28. A computer accessible storage hardware having stored thereon computer-executable instructions for providing application layer functionality between one or more database clients and one or more database servers, the computer executable instructions operable to: at a decoding layer above a network layer at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations: receive database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decode the database messages; extract query-language statements from the database messages; at a decoding layer above a network layer at a first network location between one or more database clients residing at one or more second network locations and one or more database servers residing at one or more third network locations: receiving database messages communicated from the database clients and intended for the database servers and database messages communicated from the database servers and intended for the database clients; decoding the database messages; and extracting query-language statements from the database messages; at an application layer above the decoding layer, a caching application operable for: receiving query-language statements extracted at the decoders comprising queries; receiving query-language statements extracted at the decoders comprising query results corresponding to the queries; and recording the queries and the query results corresponding to the queries in a cache residing at the first network location wherein the queries are associated with a corresponding query result; and a monitoring application operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders, wherein at least one observation is associated with a query result stored in the cache and communicate one or more observations associated with the queries to one or more computing systems at a fourth network location according to the needs of the one or more computer systems, wherein at least one of the computer systems maintains a web cache and is operable to modify the web cache based upon the communicated observations wherein observations on the database messages based at least in part on the query-language statement extracted at the decoders comprise the following: subject database instances of the query-language statements; network protocols and versions of the network protocols used to communicate the database messages; devices hosting the subject database instances of the query-language statements; hostnames, Internet Protocol (IP) addresses, Media Access Control (MAC) addresses, and network ports of the database servers; operating systems (OSs), versions of the OSs, and attributes of the OSs of devices hosting the subject database instances; devices hosting the clients; and a number of queries communicated from each of the clients to each of one or more database instances; and at an application layer above the decoding layer at the first network location, process the query-language statements extracted at the decoding layer. 39. The computer accessible storage hardware of claim 28 , wherein the instructions are further operable, at a query-language layer above the decoding layer at the first network location, to receive query-language statements extracted at the decoding layer and, before the application layer receives the query-language statements, parse the query-language statements for processing at the application layer. | 0.588889 |
6,167,411 | 13 | 15 | 13. A method in accordance with claim 11, wherein said method further comprises the steps of: receiving a user selection of a pre-existing character to be edited in the handwriting capture widget; and editing the received user selected pre-existing character to be edited, wherein said receiving and editing steps are performed prior to said receiving of the at least one character in the handwriting capture widget. | 13. A method in accordance with claim 11, wherein said method further comprises the steps of: receiving a user selection of a pre-existing character to be edited in the handwriting capture widget; and editing the received user selected pre-existing character to be edited, wherein said receiving and editing steps are performed prior to said receiving of the at least one character in the handwriting capture widget. 15. A method in accordance with claim 13, wherein said editing step comprises: displaying a correction menu with a plurality of editing options; receiving a user selection of one of the editing options from the correction menu; and editing the received user selected pre-existing character to be edited in the handwriting capture widget based on the received user selected editing option from the correction menu. | 0.5 |
9,056,256 | 12 | 13 | 12. The method of claim 1 further comprising automatically selecting a particular option, from a set of currently-available options, based at least in part on the play personality. | 12. The method of claim 1 further comprising automatically selecting a particular option, from a set of currently-available options, based at least in part on the play personality. 13. The method of claim 12 wherein the step of automatically selecting the particular option includes: assigning play-type weights to each option in the set of currently-available options; determining a score for each option in the set of currently-available options based on a comparison between the play personality of the user, and the play-type weights assigned to each option in the set of currently-available options; and selecting the particular option based on the scores assigned to each option in the set of currently-available options. | 0.5 |
9,323,741 | 8 | 10 | 8. The method of claim 7 , wherein said determining said function match further comprises analyzing the function to determine one or more determinative features; and accepting said function match only if said function in said one or more documents comprises said one or more determinative features. | 8. The method of claim 7 , wherein said determining said function match further comprises analyzing the function to determine one or more determinative features; and accepting said function match only if said function in said one or more documents comprises said one or more determinative features. 10. The method of claim 8 , wherein said searching through one or more documents comprises analyzing structured and unstructured data in said documents. | 0.749175 |
8,626,054 | 1 | 3 | 1. A computer-implemented method for annotating an essay, comprising: identifying by a processing system a sentence of the essay; identifying by the processing system a plurality of features associated with said sentence; determining by the processing system a probability of said sentence being a discourse element by a statistical evaluation that includes mapping the plurality of features to a model, said model having been generated by a machine learning application trained based on at least one annotated essay, wherein said mapping comprises extracting a pattern from the sentence based on the plurality of features and based on the training of the machine learning application; and annotating by the processing system said essay based on said probability, wherein said discourse element is at least one of: a title, a background, a thesis statement, a main point, support, and conclusion. | 1. A computer-implemented method for annotating an essay, comprising: identifying by a processing system a sentence of the essay; identifying by the processing system a plurality of features associated with said sentence; determining by the processing system a probability of said sentence being a discourse element by a statistical evaluation that includes mapping the plurality of features to a model, said model having been generated by a machine learning application trained based on at least one annotated essay, wherein said mapping comprises extracting a pattern from the sentence based on the plurality of features and based on the training of the machine learning application; and annotating by the processing system said essay based on said probability, wherein said discourse element is at least one of: a title, a background, a thesis statement, a main point, support, and conclusion. 3. The method of claim 1 , further comprising: receiving the essay. | 0.912304 |
7,814,092 | 5 | 6 | 5. The computer-implemented method of claim 1 wherein receiving named entity recognition client results comprises receiving named entity recognition client results identifying named entities known to the one or more client machines, but not known to the server. | 5. The computer-implemented method of claim 1 wherein receiving named entity recognition client results comprises receiving named entity recognition client results identifying named entities known to the one or more client machines, but not known to the server. 6. The computer-implemented method of claim 5 wherein performing named entity recognition on the server comprises identifying named entities known to the server, but not known to the one or more client machines. | 0.5 |
7,500,189 | 17 | 18 | 17. A computer storage medium encoding a computer program of instructions for executing a computer implemented method for creating a color template for a document, the method comprising: receiving at least one color for the document; constraining at least one document parameter to the at least one color, to generate at least one constrained color parameter; comparing the at least one constrained color parameter to one or more attributes of one or more example color templates in a template example library; automatically selecting one or more example color templates based on the comparison; receiving a selection of one of the one or more example color templates; automatically applying the selected example color template to the constrained color parameters to extrapolate one or more other colors for unset document parameters; and providing the selected example color template based on the received colors and the extrapolated colors. | 17. A computer storage medium encoding a computer program of instructions for executing a computer implemented method for creating a color template for a document, the method comprising: receiving at least one color for the document; constraining at least one document parameter to the at least one color, to generate at least one constrained color parameter; comparing the at least one constrained color parameter to one or more attributes of one or more example color templates in a template example library; automatically selecting one or more example color templates based on the comparison; receiving a selection of one of the one or more example color templates; automatically applying the selected example color template to the constrained color parameters to extrapolate one or more other colors for unset document parameters; and providing the selected example color template based on the received colors and the extrapolated colors. 18. A computer storage medium defined in claim 17 , wherein the constrained color parameter is one of a color setting or a relationship between two color settings. | 0.5 |
7,814,127 | 28 | 29 | 28. The computer-readable medium of claim 24 , wherein the data abstraction model further comprises a reference to at least a portion of the translation information. | 28. The computer-readable medium of claim 24 , wherein the data abstraction model further comprises a reference to at least a portion of the translation information. 29. The computer-readable medium of claim 28 , wherein the referenced portion is a default file. | 0.5 |
10,152,757 | 8 | 14 | 8. A computer-implemented data processing method of providing one or more activities to subsequent viewers of a piece of multimedia in a time-shifted manner according to an activity map, comprising: identifying, by one or more activity management servers, a plurality of segments that make up a piece of multimedia; receiving, by the one or more activity management servers, a plurality of activities from one or more users prior to a first time, each particular activity of the plurality of activities being associated with a respective particular segment of the plurality of segments; generating, by the one or more activity management servers, an activity map for the piece of multimedia based at least in part on the plurality of segments, the activity map indicating: the association between each particular activity of the plurality of activities and the respective particular segment of the plurality of segments; and one or more associations between one or more particular activities of the plurality of activities and one or more other activities of the plurality of activities; receiving, by the one or more activity management servers, from a client device, a first request to display one or more activities associated with the piece of multimedia; in response to the first request, generating a graphical display of the one or more activities associated with the piece multimedia based at least in part on the activity map, the graphical display comprising a word cloud generated based at least in part on a graphic density of one or more particular words that appear in the one or more activities; and causing the client device to display the graphical display. | 8. A computer-implemented data processing method of providing one or more activities to subsequent viewers of a piece of multimedia in a time-shifted manner according to an activity map, comprising: identifying, by one or more activity management servers, a plurality of segments that make up a piece of multimedia; receiving, by the one or more activity management servers, a plurality of activities from one or more users prior to a first time, each particular activity of the plurality of activities being associated with a respective particular segment of the plurality of segments; generating, by the one or more activity management servers, an activity map for the piece of multimedia based at least in part on the plurality of segments, the activity map indicating: the association between each particular activity of the plurality of activities and the respective particular segment of the plurality of segments; and one or more associations between one or more particular activities of the plurality of activities and one or more other activities of the plurality of activities; receiving, by the one or more activity management servers, from a client device, a first request to display one or more activities associated with the piece of multimedia; in response to the first request, generating a graphical display of the one or more activities associated with the piece multimedia based at least in part on the activity map, the graphical display comprising a word cloud generated based at least in part on a graphic density of one or more particular words that appear in the one or more activities; and causing the client device to display the graphical display. 14. The computer-implemented data processing method of claim 8 , further comprising generating the word cloud based on the one or more words that appear in the one or more activities. | 0.881014 |
8,515,731 | 10 | 11 | 10. The method of claim 8 , where generating the term group of text strings and the synonym group of text strings further includes: normalizing each term phrase and each synonym phrase; identifying a group of normalized term phrases as the term group of text strings; and identifying a group of normalized synonym phrases as the synonym group of text strings. | 10. The method of claim 8 , where generating the term group of text strings and the synonym group of text strings further includes: normalizing each term phrase and each synonym phrase; identifying a group of normalized term phrases as the term group of text strings; and identifying a group of normalized synonym phrases as the synonym group of text strings. 11. The method of claim 10 , where normalizing each term phrase and each synonym phrase includes normalizing a case of each letter in each term phrase and each letter in each synonym phrase and removing any stop words from each term phrase and each synonym phrase. | 0.5 |
8,781,811 | 15 | 18 | 15. A system, comprising: a server comprising a first computer readable medium and a first processor configured to: obtain a plurality of language preferences from a first device; and store the plurality of language preferences to the first computer readable medium; the first device comprising a second computer readable medium and a second processor configured to: receive the plurality of language preferences from the server over a first network connection; store the plurality of language preferences to the second computer readable medium; execute a first application that is unable to access the plurality of language preferences associated with the server; access plurality of language preferences stored on the second computer readable medium; and resolve the first application according to the plurality of language preferences stored on the second computer readable medium; and a second device comprising a third computer readable medium and a third processor configured to: receive the plurality of language preferences from the server over a second network connection; store the plurality of language preferences to the third computer readable medium; execute a second application that is unable to access the plurality of language preferences associated with the server; access the plurality of language preferences stored on the third computer readable medium; and resolve the second application according to the plurality of language preferences stored on the third computer readable medium. | 15. A system, comprising: a server comprising a first computer readable medium and a first processor configured to: obtain a plurality of language preferences from a first device; and store the plurality of language preferences to the first computer readable medium; the first device comprising a second computer readable medium and a second processor configured to: receive the plurality of language preferences from the server over a first network connection; store the plurality of language preferences to the second computer readable medium; execute a first application that is unable to access the plurality of language preferences associated with the server; access plurality of language preferences stored on the second computer readable medium; and resolve the first application according to the plurality of language preferences stored on the second computer readable medium; and a second device comprising a third computer readable medium and a third processor configured to: receive the plurality of language preferences from the server over a second network connection; store the plurality of language preferences to the third computer readable medium; execute a second application that is unable to access the plurality of language preferences associated with the server; access the plurality of language preferences stored on the third computer readable medium; and resolve the second application according to the plurality of language preferences stored on the third computer readable medium. 18. The system of claim 15 , wherein the first computer readable medium comprises a database. | 0.915301 |
7,610,190 | 1 | 4 | 1. A method of determining a hybrid text summary by a hybrid summarization system having a processor, a relevance score determination module, a structural representation of the discourse determination module and a percolation module, the method comprising: determining discourse constituents for a text by the processor; determining a structural representation of discourse for the text by the structural representation of the discourse determination module; determining relevance scores for discourse constituents based on at least one non-structural measure of relevance by the relevance score determination module; percolating relevance scores based on the structural representation of discourse by the percolation module; and determining a hybrid text summary, by the processor, based on discourse constituents with relevance scores compared to a threshold relevance score, wherein percolating the relevance scores comprises: for each child discourse constituent node in the structural representation, assigning the relevance score of the child discourse constituent node to the parent discourse constituent node if the child discourse constituent node is more relevant; for any subordinating nodes, assigning the relevance scores of the subordinated discourse constituent to the subordinating discourse constituent if the subordinated discourse constituent is more relevant; and for any coordination nodes, assigning the relevance score of the most relevant child to other child discourse constituent nodes. | 1. A method of determining a hybrid text summary by a hybrid summarization system having a processor, a relevance score determination module, a structural representation of the discourse determination module and a percolation module, the method comprising: determining discourse constituents for a text by the processor; determining a structural representation of discourse for the text by the structural representation of the discourse determination module; determining relevance scores for discourse constituents based on at least one non-structural measure of relevance by the relevance score determination module; percolating relevance scores based on the structural representation of discourse by the percolation module; and determining a hybrid text summary, by the processor, based on discourse constituents with relevance scores compared to a threshold relevance score, wherein percolating the relevance scores comprises: for each child discourse constituent node in the structural representation, assigning the relevance score of the child discourse constituent node to the parent discourse constituent node if the child discourse constituent node is more relevant; for any subordinating nodes, assigning the relevance scores of the subordinated discourse constituent to the subordinating discourse constituent if the subordinated discourse constituent is more relevant; and for any coordination nodes, assigning the relevance score of the most relevant child to other child discourse constituent nodes. 4. The method of claim 1 , wherein non-structural measures of relevance are determined based on at least one of statistics, keywords, knowledge bases. | 0.84787 |
9,686,587 | 2 | 3 | 2. The playback method according to claim 1 , wherein the first playback data is in a first image data format. | 2. The playback method according to claim 1 , wherein the first playback data is in a first image data format. 3. The playback method according to claim 2 , wherein the step of converting the first character information in the first playback data to the first speech data comprises: performing optical character recognition on the first playback data to obtain the first character information; and converting the first character information into the first speech data. | 0.5 |
8,275,623 | 28 | 29 | 28. A set-top box comprising: a memory storing computer instructions; and a controller coupled with the memory, wherein the controller, responsive to executing the computer instructions, performs operations comprising: detecting a plurality of users engaging in a voice conference to discuss a presentation of a media program supplied by an interactive television network; and identifying for the plurality of users at least one of advertisement content or marketable media content from textual dialog derived from the voice conference. | 28. A set-top box comprising: a memory storing computer instructions; and a controller coupled with the memory, wherein the controller, responsive to executing the computer instructions, performs operations comprising: detecting a plurality of users engaging in a voice conference to discuss a presentation of a media program supplied by an interactive television network; and identifying for the plurality of users at least one of advertisement content or marketable media content from textual dialog derived from the voice conference. 29. The set-top box of claim 28 , wherein the controller is operative to: monitor the media program; identify a behavioral profile of at least one user; identify a media program profile from the monitored media program; and identify for the plurality of users the at least one of advertisement content or marketable media content according to the behavioral profile of the at least one user and the media program profile. | 0.5 |
9,984,127 | 1 | 2 | 1. An automated method for improving search results in consideration of emphasized content comprising: prior to delivery to a user, intercepting natural language results from a search performed using a natural language query; detecting, by one or more processors, a natural language in which the results are expressed; retrieving according to the detected natural language, by the one or more processors, from a database, a cultural rule indicating how emphasis of words and sub-phrases is made using a shift from a default text typestyle to an emphasized text typestyle, wherein the shift occurs for one or more words in a phrase and the phrase is otherwise encoded in the default text typestyle, and wherein the emphasized text typestyle is selected from the group consisting of bolding, underlining, strikethrough, color and italicization; finding, by the one or more processors, using the cultural rule, one or more emphasized words in the results; assigning, the one or more processors, confidence scores to each result according to occurrences of found emphasized words relevant to the query; re-ranking, by the one or more processors, the results according to an initial relevance and according to the confidence scores; and producing, by the one or more processors, to the user, the re-ranked results. | 1. An automated method for improving search results in consideration of emphasized content comprising: prior to delivery to a user, intercepting natural language results from a search performed using a natural language query; detecting, by one or more processors, a natural language in which the results are expressed; retrieving according to the detected natural language, by the one or more processors, from a database, a cultural rule indicating how emphasis of words and sub-phrases is made using a shift from a default text typestyle to an emphasized text typestyle, wherein the shift occurs for one or more words in a phrase and the phrase is otherwise encoded in the default text typestyle, and wherein the emphasized text typestyle is selected from the group consisting of bolding, underlining, strikethrough, color and italicization; finding, by the one or more processors, using the cultural rule, one or more emphasized words in the results; assigning, the one or more processors, confidence scores to each result according to occurrences of found emphasized words relevant to the query; re-ranking, by the one or more processors, the results according to an initial relevance and according to the confidence scores; and producing, by the one or more processors, to the user, the re-ranked results. 2. The method as set forth in claim 1 wherein the producing of the results further comprises annotation of the results to reflect the detected emphasized one or more words. | 0.752161 |
4,099,230 | 1 | 10 | 1. In a programmed digital computer, apparatus for loading a program into a memory in a manner to be location independent so that each segment of the program may be selectively accessed for modification or debugging without affecting the balance of the program, wherein each given program segment is identified by a program segment label comprised of a group of coded digital signals which precedes a plurality of instructions that follow said label and that comprise a program segment, comprising a program memory, a source of a plurality of program segments each including a program segment label followed by a plurality of instructions, means for sequentially transferring said plurality of program segments into and out of said program memory, a program counter means for counting storage addresses used in providing to said program memory the addresses for storage and for read out of program labels and instructions from said program memory, a label memory means, wherein each label memory address is represented by a program segment label, label detecting means for detecting when a program segment label has been transferred by said means for transferring said plurality of program segments, control means, responsive to a label being detected by said label detecting means, for loading in said program counter the address at which the first instruction after said detected program label is stored in said program memory, and for addressing said label memory means with the detected program segment label, and means responsive to said label detecting means and said control means for storing said loaded address in said label memory means at an address represented by said detected program segment label, whereby a program segment can be selectively read out for modification or debugging by addressing said label memory means with a programmed segment label to obtain the address in said program memory of the first instruction of the program segment. | 1. In a programmed digital computer, apparatus for loading a program into a memory in a manner to be location independent so that each segment of the program may be selectively accessed for modification or debugging without affecting the balance of the program, wherein each given program segment is identified by a program segment label comprised of a group of coded digital signals which precedes a plurality of instructions that follow said label and that comprise a program segment, comprising a program memory, a source of a plurality of program segments each including a program segment label followed by a plurality of instructions, means for sequentially transferring said plurality of program segments into and out of said program memory, a program counter means for counting storage addresses used in providing to said program memory the addresses for storage and for read out of program labels and instructions from said program memory, a label memory means, wherein each label memory address is represented by a program segment label, label detecting means for detecting when a program segment label has been transferred by said means for transferring said plurality of program segments, control means, responsive to a label being detected by said label detecting means, for loading in said program counter the address at which the first instruction after said detected program label is stored in said program memory, and for addressing said label memory means with the detected program segment label, and means responsive to said label detecting means and said control means for storing said loaded address in said label memory means at an address represented by said detected program segment label, whereby a program segment can be selectively read out for modification or debugging by addressing said label memory means with a programmed segment label to obtain the address in said program memory of the first instruction of the program segment. 10. Apparatus for implementing the program structure of a computer as recited in claim 1 wherein there is included a source of data representative of human language identifiers of the plurality of program segments, text memory means for storing therein data representative of human language identifiers of the plurality of program segments stored in said program memory, text counter means for generating addresses for storing and for read out of said data from said text memory means, means for transferring said data to said text memory while loading said plurality of program segments into said program memory from said source of data. means for detecting a label, and text table means responsive to the detection of a label, for storing, at locations identified by the label for each program segment, the address generated by said text counter means, in said text table means, of the first character of said human language identifier of the program segment, identified by said label. | 0.870845 |
9,535,895 | 9 | 12 | 9. A computer-implemented method, comprising: under control of a device comprising one or more processors configured with executable instructions, receiving at a graphical user interface of the device user selection of a sample electronic text; identifying multiple sample n-grams of the sample electronic text; for a first language: calculating a first probability based at least in part on a frequency of occurrence, in the first language, of a first sample n-gram of the multiple n-grams; calculating a second probability based at least in part on a frequency of occurrence, in the first language, of a second sample n-gram of the multiple n-grams; generating a first average based at least in part on the first probability and the second probability; for a second language: calculating a third probability based at least in part on a frequency of occurrence, in the second language, of the first sample n-gram of the multiple sample n-grams; calculating a fourth probability based at least in part on a frequency of occurrence, in the second language, of the second sample n-gram of the multiple n-grams; generating a second average based at least in part on the third probability and the fourth probability; determining a language of the sample electronic text based at least in part on comparing at least the first average and the second average; displaying, via the graphical user interface, an indication of the language; performing, via the device, a language-dependent operation based at least in part on the language of the sample electronic text; and displaying, via the graphical user interface, information associated with the language-dependent operation. | 9. A computer-implemented method, comprising: under control of a device comprising one or more processors configured with executable instructions, receiving at a graphical user interface of the device user selection of a sample electronic text; identifying multiple sample n-grams of the sample electronic text; for a first language: calculating a first probability based at least in part on a frequency of occurrence, in the first language, of a first sample n-gram of the multiple n-grams; calculating a second probability based at least in part on a frequency of occurrence, in the first language, of a second sample n-gram of the multiple n-grams; generating a first average based at least in part on the first probability and the second probability; for a second language: calculating a third probability based at least in part on a frequency of occurrence, in the second language, of the first sample n-gram of the multiple sample n-grams; calculating a fourth probability based at least in part on a frequency of occurrence, in the second language, of the second sample n-gram of the multiple n-grams; generating a second average based at least in part on the third probability and the fourth probability; determining a language of the sample electronic text based at least in part on comparing at least the first average and the second average; displaying, via the graphical user interface, an indication of the language; performing, via the device, a language-dependent operation based at least in part on the language of the sample electronic text; and displaying, via the graphical user interface, information associated with the language-dependent operation. 12. The computer-implemented method of claim 9 , wherein calculating the first probability is based at least in part on relative occurrence frequencies of the first sample n-gram within reference texts of different languages. | 0.836483 |
8,543,400 | 1 | 4 | 1. A voice processing method, comprising: receiving an utterance; comparing the utterance with a corresponding utterance in teaching materials according to at least one matching algorithm to obtain a plurality of matching values corresponding to a plurality of voice units of the utterance; scoring the respective voice units in at least one first scoring item according to the matching values corresponding to the respective voice units; scoring the utterance in at least one second scoring item according to the scores of the respective voice units in the first scoring item; and scoring the utterance in the second scoring item according to the scores of the respective voice units in the first scoring item and at least one personified voice scoring algorithm for the second scoring item, wherein the method for generating the personified voice scoring algorithm for the second scoring item comprises the steps of: receiving training utterances corresponding to at least one training sentence in a phonetic-balanced sentence set produced by a plurality of learners and at least one real teacher; comparing the training utterances of the learners and that of the real teacher according to at least one matching algorithm to obtain a plurality of matching values corresponding to a plurality of voice units of the training utterances; receiving scores corresponding to the respective voice units of the training utterances of the learners in the first scoring item provided by the real teacher; receiving scores corresponding to the training utterances of the learners in the second scoring item provided by the real teacher; and determining the personified voice scoring algorithm for the second scoring item according to the scores corresponding to the respective voice units of the training utterances in the first scoring item and the scores corresponding to the training utterances in the second scoring item. | 1. A voice processing method, comprising: receiving an utterance; comparing the utterance with a corresponding utterance in teaching materials according to at least one matching algorithm to obtain a plurality of matching values corresponding to a plurality of voice units of the utterance; scoring the respective voice units in at least one first scoring item according to the matching values corresponding to the respective voice units; scoring the utterance in at least one second scoring item according to the scores of the respective voice units in the first scoring item; and scoring the utterance in the second scoring item according to the scores of the respective voice units in the first scoring item and at least one personified voice scoring algorithm for the second scoring item, wherein the method for generating the personified voice scoring algorithm for the second scoring item comprises the steps of: receiving training utterances corresponding to at least one training sentence in a phonetic-balanced sentence set produced by a plurality of learners and at least one real teacher; comparing the training utterances of the learners and that of the real teacher according to at least one matching algorithm to obtain a plurality of matching values corresponding to a plurality of voice units of the training utterances; receiving scores corresponding to the respective voice units of the training utterances of the learners in the first scoring item provided by the real teacher; receiving scores corresponding to the training utterances of the learners in the second scoring item provided by the real teacher; and determining the personified voice scoring algorithm for the second scoring item according to the scores corresponding to the respective voice units of the training utterances in the first scoring item and the scores corresponding to the training utterances in the second scoring item. 4. The method of claim 1 , wherein the first scoring item comprises the phoneme correctness, the pitch correctness, or the phoneme-length correctness for the respective voice units. | 0.917577 |
9,245,233 | 1 | 2 | 1. A computer-implemented method comprising: obtaining training data, the training data comprising a plurality of graphs, each defined by nodes and edges connecting between the nodes, wherein at least some of the nodes are labeled; determining, by a processor, a statistical model of a graph in accordance with the training data, the statistical model takes into account at least one structured and labeled feature of the graph, wherein the structured and labeled feature of the graph is defined based on a connection between a plurality of nodes and based on at least a portion of the labels of the plurality of nodes; based on the training data, building a consensus graph retaining information relating to the values of the structured and labeled feature in the plurality of graphs in the training data; obtaining an examined graph; and determining, by the processor, a score of the examined graph indicative of a similarity between the examined graph and the training data, wherein the score is based on a value of the structured and labeled feature in the examined graph, wherein said determining the score is performed by traversing the consensus graph and the examined graph to compare the values of the structured and labeled feature. | 1. A computer-implemented method comprising: obtaining training data, the training data comprising a plurality of graphs, each defined by nodes and edges connecting between the nodes, wherein at least some of the nodes are labeled; determining, by a processor, a statistical model of a graph in accordance with the training data, the statistical model takes into account at least one structured and labeled feature of the graph, wherein the structured and labeled feature of the graph is defined based on a connection between a plurality of nodes and based on at least a portion of the labels of the plurality of nodes; based on the training data, building a consensus graph retaining information relating to the values of the structured and labeled feature in the plurality of graphs in the training data; obtaining an examined graph; and determining, by the processor, a score of the examined graph indicative of a similarity between the examined graph and the training data, wherein the score is based on a value of the structured and labeled feature in the examined graph, wherein said determining the score is performed by traversing the consensus graph and the examined graph to compare the values of the structured and labeled feature. 2. The computer-implemented method of claim 1 , wherein the structured and labeled feature is one of the following features: a binary feature indicating existence of a labeled path in the graph; a binary feature indicating existence of a labeled, non-path, sub-tree topology; and a feature relating to a terminal value of a labeled path in the graph. | 0.5 |
9,607,058 | 1 | 3 | 1. A method of managing documents associated with one or more patent applications, the method comprising: associating a first database record and a second database record with a patent family identifier, wherein the first database record corresponds to a first patent application and the second database record corresponds to a second patent application; retrieving a reference from a patent data resource using a crawler service based on one or more of the patent family identifier, the first patent application, and the second patent application; based on a determination that automatic text extraction is applicable to the reference, generating an optical character recognition (OCR) version of the reference, wherein generating the OCR version of the reference comprises converting the reference from a native file format to a format that facilitates automatic data extraction; based on a determination that the OCR version of the reference meets or exceeds a confidence level threshold, matching the OCR version of the reference to at least one of a plurality of reference templates, wherein matching the OCR version of the reference to at least one of the plurality of reference templates comprises comparing at least a portion of the extractable data in the OCR version of the reference to one or more of the plurality of reference templates to identify a match; extracting a select data from the OCR version of the reference based on the at least one of the plurality of reference templates identified as a match; validating the extracted data, wherein the validating the extracted data comprises determining that the extracted data is not already associated with one or more of the first database record and the second database record; populating a plurality of input fields of an information disclosure statement (IDS) form using at least the validated extracted data, wherein at least one of the plurality of input fields includes descriptive data corresponding to the reference; presenting an IDS generating interface to a generating user, the IDS generating interface comprising a representation of the populated IDS form and a reference flow rule option configured to allow the generating user to modify a reference flow rule associated with the patent family identifier, wherein the reference flow rule is configured to control a cross citation of the reference between database records; receiving a selection of the reference flow rule option via the IDS generating interface; presenting an IDS review interface to a reviewing user, the IDS review interface comprising a representation of a review version of the populated IDS form and a representation of the reference; presenting a set of selectable options to the reviewing user, wherein the set of selectable options includes an approve option and a do not file option; receiving, via the IDS review interface, a selection of the approve option; and notifying the generating user that the IDS form is ready to be filed. | 1. A method of managing documents associated with one or more patent applications, the method comprising: associating a first database record and a second database record with a patent family identifier, wherein the first database record corresponds to a first patent application and the second database record corresponds to a second patent application; retrieving a reference from a patent data resource using a crawler service based on one or more of the patent family identifier, the first patent application, and the second patent application; based on a determination that automatic text extraction is applicable to the reference, generating an optical character recognition (OCR) version of the reference, wherein generating the OCR version of the reference comprises converting the reference from a native file format to a format that facilitates automatic data extraction; based on a determination that the OCR version of the reference meets or exceeds a confidence level threshold, matching the OCR version of the reference to at least one of a plurality of reference templates, wherein matching the OCR version of the reference to at least one of the plurality of reference templates comprises comparing at least a portion of the extractable data in the OCR version of the reference to one or more of the plurality of reference templates to identify a match; extracting a select data from the OCR version of the reference based on the at least one of the plurality of reference templates identified as a match; validating the extracted data, wherein the validating the extracted data comprises determining that the extracted data is not already associated with one or more of the first database record and the second database record; populating a plurality of input fields of an information disclosure statement (IDS) form using at least the validated extracted data, wherein at least one of the plurality of input fields includes descriptive data corresponding to the reference; presenting an IDS generating interface to a generating user, the IDS generating interface comprising a representation of the populated IDS form and a reference flow rule option configured to allow the generating user to modify a reference flow rule associated with the patent family identifier, wherein the reference flow rule is configured to control a cross citation of the reference between database records; receiving a selection of the reference flow rule option via the IDS generating interface; presenting an IDS review interface to a reviewing user, the IDS review interface comprising a representation of a review version of the populated IDS form and a representation of the reference; presenting a set of selectable options to the reviewing user, wherein the set of selectable options includes an approve option and a do not file option; receiving, via the IDS review interface, a selection of the approve option; and notifying the generating user that the IDS form is ready to be filed. 3. The method of claim 1 , wherein the reference flow rule option comprises the patent family identifier, a count of family members, a count of records related by subject matter, and an action. | 0.75 |
9,218,421 | 16 | 17 | 16. An apparatus as defined in claim 8 , wherein the virality determiner is to calculate times between the adjacent ones of the inbound links by: determining posting times of the posts that are relevant to the topic; comparing a first list including the posting times to a second list including the inbound links to determine a third list including posting times of the inbound links; and determining the times between the adjacent ones of the inbound links in the third list. | 16. An apparatus as defined in claim 8 , wherein the virality determiner is to calculate times between the adjacent ones of the inbound links by: determining posting times of the posts that are relevant to the topic; comparing a first list including the posting times to a second list including the inbound links to determine a third list including posting times of the inbound links; and determining the times between the adjacent ones of the inbound links in the third list. 17. An apparatus as defined in claim 16 , wherein the virality determiner is further to arrange the third list chronologically. | 0.807576 |
7,475,010 | 16 | 30 | 16. An apparatus for use in a natural language processing system for resolving natural language ambiguities within text documents, comprising: a trainer that trains probabilistic classifiers from annotated training data containing a sense tag for each polysemous word; a part-of-speech processor that processes said text documents into tokens and determines their part-of-speech tags; a classifier module that computes a measure of confidence using said probabilistic classifiers for each known sense of said tokens defined within a semantic lexicon based on contextual features and assigns a default sense for tokens absent from said semantic lexicon based on their part-of-speech tags; a word sense disambiguator that determines assignment of word senses for each said token in said sentence such that the combined probability across said sentence is maximized; and a context integrator that integrates additional contextual features as generated by one or more of the following natural language processing apparatuses into said probabilistic classifiers whereby said measure of confidence is improved: using a chunking apparatus that identifies multi-word phrases and the associated measure of confidence for each phrase; using a named-entity recognition apparatus that identifies named entities and the associated measure of confidence for each entity; using a syntactic parsing apparatus that constructs sentential parse trees and the associated measure of confidence for each tree; using an anaphora resolution apparatus that identifies anaphor references and the associated measure of confidence for each reference; using a discourse categorization apparatus that determines document categories and the associated measure of confidence for each category; using a discourse structure analysis apparatus that determines discourse structures and the associated measure of confidence for each structure. | 16. An apparatus for use in a natural language processing system for resolving natural language ambiguities within text documents, comprising: a trainer that trains probabilistic classifiers from annotated training data containing a sense tag for each polysemous word; a part-of-speech processor that processes said text documents into tokens and determines their part-of-speech tags; a classifier module that computes a measure of confidence using said probabilistic classifiers for each known sense of said tokens defined within a semantic lexicon based on contextual features and assigns a default sense for tokens absent from said semantic lexicon based on their part-of-speech tags; a word sense disambiguator that determines assignment of word senses for each said token in said sentence such that the combined probability across said sentence is maximized; and a context integrator that integrates additional contextual features as generated by one or more of the following natural language processing apparatuses into said probabilistic classifiers whereby said measure of confidence is improved: using a chunking apparatus that identifies multi-word phrases and the associated measure of confidence for each phrase; using a named-entity recognition apparatus that identifies named entities and the associated measure of confidence for each entity; using a syntactic parsing apparatus that constructs sentential parse trees and the associated measure of confidence for each tree; using an anaphora resolution apparatus that identifies anaphor references and the associated measure of confidence for each reference; using a discourse categorization apparatus that determines document categories and the associated measure of confidence for each category; using a discourse structure analysis apparatus that determines discourse structures and the associated measure of confidence for each structure. 30. The apparatus for use in a natural language processing system of claim 16 , wherein said semantic lexicon is organized as an ontology. | 0.961388 |
9,779,083 | 16 | 17 | 16. A system for converting a natural language sentence into a computer-readable primitive sentence, the system comprising: a processing device; and a non-transitory, processor-readable storage medium comprising one or more programming instructions that, when executed, cause the processing device to: identify a verbal block in the natural language sentence; split the natural language sentence into one or more logical clauses; determine a type for each of the one or more logical clauses, wherein the type indicates whether each of the one or more logical clauses contains an ambiguous verbal block; disambiguate the ambiguous verbal block within each of the one or more logical clauses, wherein each verbal block is considered independently of a noun phrase; and construct the computer-readable primitive sentence for each ambiguous verbal block by duplicating a shared noun phrase of the ambiguous verbal block, wherein the computer-readable primitive sentence improves a functioning of a computing device by not requiring voluminous storage space in allowing the computing device to process the natural language sentence to obtain information from the natural language sentence. | 16. A system for converting a natural language sentence into a computer-readable primitive sentence, the system comprising: a processing device; and a non-transitory, processor-readable storage medium comprising one or more programming instructions that, when executed, cause the processing device to: identify a verbal block in the natural language sentence; split the natural language sentence into one or more logical clauses; determine a type for each of the one or more logical clauses, wherein the type indicates whether each of the one or more logical clauses contains an ambiguous verbal block; disambiguate the ambiguous verbal block within each of the one or more logical clauses, wherein each verbal block is considered independently of a noun phrase; and construct the computer-readable primitive sentence for each ambiguous verbal block by duplicating a shared noun phrase of the ambiguous verbal block, wherein the computer-readable primitive sentence improves a functioning of a computing device by not requiring voluminous storage space in allowing the computing device to process the natural language sentence to obtain information from the natural language sentence. 17. The system of claim 16 , wherein the non-transitory, processor-readable storage medium further comprises one or more programming instructions that, when executed, cause the processing device to: extract the information from the computer-readable primitive sentence. | 0.583591 |
9,871,714 | 1 | 18 | 1. A method comprising, by a computing device: accessing, by the computing device, a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them; receiving, at the computing device from a client device of a first user, a first structured query comprising references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges; determining, by the computing device, a search bias of the first user with respect to the first structured query, the search bias being determined based at least in part on: (1) an explicit bias of the first user based on an analysis of the nodes and edges referenced in the first structured query; and (2) an implicit bias of the first user determined based on an analysis of a first node corresponding to the first user and a plurality of user nodes corresponding to a plurality of second users, respectively, sharing one or more user attributes with the first user; identifying, by the computing device, one or more nodes of a plurality of second nodes, wherein the identified nodes correspond to the structured query, and identifying the one or more nodes is based at least in part on the search bias of the first user; generating, by the computing device, one or more search results corresponding to one or more of the identified one or more nodes, respectively, each search result comprising a reference to the corresponding identified node; and sending, from the computing device to the client device, responsive to the first structured query, one or more search results for display to the first user. | 1. A method comprising, by a computing device: accessing, by the computing device, a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them; receiving, at the computing device from a client device of a first user, a first structured query comprising references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges; determining, by the computing device, a search bias of the first user with respect to the first structured query, the search bias being determined based at least in part on: (1) an explicit bias of the first user based on an analysis of the nodes and edges referenced in the first structured query; and (2) an implicit bias of the first user determined based on an analysis of a first node corresponding to the first user and a plurality of user nodes corresponding to a plurality of second users, respectively, sharing one or more user attributes with the first user; identifying, by the computing device, one or more nodes of a plurality of second nodes, wherein the identified nodes correspond to the structured query, and identifying the one or more nodes is based at least in part on the search bias of the first user; generating, by the computing device, one or more search results corresponding to one or more of the identified one or more nodes, respectively, each search result comprising a reference to the corresponding identified node; and sending, from the computing device to the client device, responsive to the first structured query, one or more search results for display to the first user. 18. The method of claim 1 , wherein the analysis of the first node corresponding to the first user and the plurality of user nodes corresponding to the plurality of second users, respectively, comprises: calculating a score for each of the identified nodes, wherein the score is calculated using a probabilistic ranking model that scores each identified node based at least in part on a number of edges connecting the identified node to one or more nodes within the first set of user nodes, the first set of user nodes comprising the first node and a plurality of user nodes corresponding to the plurality of second users, respectively, sharing one or more user attributes with the first user. | 0.5 |
8,201,095 | 18 | 19 | 18. The program product of claim 15 wherein the one or more thread keywords are identified by at least one of a thread creator and a forum moderator. | 18. The program product of claim 15 wherein the one or more thread keywords are identified by at least one of a thread creator and a forum moderator. 19. The program product of claim 18 wherein the program product further comprises program instructions to automatically determine the one or more relevancy scores based upon at least one of a keyword frequency and a keyword proximity to an original post. | 0.5 |
10,037,383 | 17 | 19 | 17. The method of claim 16 , wherein the particular template further comprises query specification data that is used by a query formulator to generate a structured query comprising a first clause that specifies how the corresponding particular input is compared to the one or more data structures when conducting a search. | 17. The method of claim 16 , wherein the particular template further comprises query specification data that is used by a query formulator to generate a structured query comprising a first clause that specifies how the corresponding particular input is compared to the one or more data structures when conducting a search. 19. The method of claim 17 , wherein the structured query further comprises: a particular search filter with a required value indicated by the query specification data. | 0.5 |
8,117,225 | 15 | 27 | 15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. | 15. A computer program product embodied on a non-transitory computer-readable medium, comprising: code for registering a global unique user login information capable of being used to access a plurality of different online applications associated with an online application system including a first online application that provides access to a first one or more files associated with the first online application, a second online application that provides access to a second one or more files associated with the second online application, a third online application that provides access to a third one or more files associated with the third online application, and a fourth online application that provides access to a fourth one or more files associated with the fourth online application; code for receiving the global unique user login information in connection with a login; code for receiving an indication to add access to the first online application, utilizing at least one first online application identifier associated with the first online application; code for receiving an indication to add access to the second online application, utilizing at least one second online application identifier associated with the second online application; code for receiving an indication to add access to the third online application, utilizing at least one third online application identifier associated with the third online application; code for receiving an indication to add access to the fourth online application, utilizing at least one fourth online application identifier associated with the fourth online application; code for allowing registration of the first online application; code for allowing registration of the second online application; code for allowing registration of the third online application; code for allowing registration of the fourth online application; code for displaying the at least one first online application identifier associated with the first online application for access purposes; code for displaying the at least one second online application identifier associated with the second online application for access purposes; code for displaying the at least one third online application identifier associated with the third online application for access purposes; code for displaying the at least one fourth online application identifier associated with the fourth online application for access purposes; code for receiving a selection of the at least one first online application identifier associated with the first online application for access purposes; code for receiving a selection of the at least one second online application identifier associated with the second online application for access purposes; code for receiving a selection of the at least one third online application identifier associated with the third online application for access purposes; code for receiving a selection of the at least one fourth online application identifier associated with the fourth online application for access purposes; code for, in response to the selection of the at least one first online application identifier associated with the first online application for access purposes, allowing access to the first online application; code for, in response to the selection of the at least one second online application identifier associated with the second online application for access purposes, allowing access to the second online application; code for, in response to the selection of the at least one third online application identifier associated with the third online application for access purposes, allowing access to the third online application; code for, in response to the selection of the at least one fourth online application identifier associated with the fourth online application for access purposes, allowing access to the fourth online application; code for identifying at least one profile, the at least one profile including: at least one user profile of an accessing user, the at least one user profile including: registration information determined when the accessing user registered, and automatically determined information that is determined automatically based on user selections of the accessing user; and at least one group profile; code for displaying a search interface in connection with the online application system, the search interface being displayed simultaneously with an advertisement that is selected based on the registration information and the automatically determined information of the at least one user profile, and the at least one group profile; code for performing a search in connection with the online application system utilizing the search interface; and code for displaying search results of the search, where the search results involve a plurality of the different online applications associated with the online application system. 27. The computer program product of claim 15 , wherein the first one or more files includes a picture. | 0.933071 |
9,800,618 | 6 | 9 | 6. A method, comprising: a user agent providing at least one privacy preference relative to at least one user identity; the user agent receiving user selections indicating at least one privacy preference-related input pertaining to the user identity wherein the user identity is represented by at least one information card used in completing an online transaction with a relying party; the user agent generating at least one privacy preference, using the user selections; the user agent furnishing the at least one generated privacy preference; the user agent evaluating at least one privacy preference against a privacy policy associated with an online transaction and obtained from the relying party, the evaluating using the at least one privacy preference of any category referencing at least one required attribute; and a host computer providing the at least one information card representing the user identity to the relying party. | 6. A method, comprising: a user agent providing at least one privacy preference relative to at least one user identity; the user agent receiving user selections indicating at least one privacy preference-related input pertaining to the user identity wherein the user identity is represented by at least one information card used in completing an online transaction with a relying party; the user agent generating at least one privacy preference, using the user selections; the user agent furnishing the at least one generated privacy preference; the user agent evaluating at least one privacy preference against a privacy policy associated with an online transaction and obtained from the relying party, the evaluating using the at least one privacy preference of any category referencing at least one required attribute; and a host computer providing the at least one information card representing the user identity to the relying party. 9. The method of claim 6 , further comprises the user agent conducting a process to receive from an identity manager at least one indication of the at least one information card each representative of a user identity, and to determine a privacy preference for the at least one information card. | 0.598361 |
7,974,835 | 1 | 2 | 1. A natural language, mixed-initiative system comprising: a main menu detector for receiving a user input, said main menu detector configured to distinguish a user input specifying a requested action from a user input specifying a token for performing an action, wherein if the user input specifies a requested action, said main menu detector routes the user input to an action interpreter, and wherein if the user input specifies a token, said main menu detector routes the user input to an action router; a classifier configured to distinguish user inputs specifying context dependent data from user inputs specifying context independent data, wherein said classifier routes user inputs specifying context dependent data to said main menu detector and user inputs specifying context independent data to an action interpreter; an action interpreter configured to determine an action from the user input; an action router configured to route the user input to one of a plurality of token interpreters determined by the action router to be suited for interpreting the user input if the user input specifies a token; and at least one token interpreter configured to determine a token from a user input to be used in performing an action. | 1. A natural language, mixed-initiative system comprising: a main menu detector for receiving a user input, said main menu detector configured to distinguish a user input specifying a requested action from a user input specifying a token for performing an action, wherein if the user input specifies a requested action, said main menu detector routes the user input to an action interpreter, and wherein if the user input specifies a token, said main menu detector routes the user input to an action router; a classifier configured to distinguish user inputs specifying context dependent data from user inputs specifying context independent data, wherein said classifier routes user inputs specifying context dependent data to said main menu detector and user inputs specifying context independent data to an action interpreter; an action interpreter configured to determine an action from the user input; an action router configured to route the user input to one of a plurality of token interpreters determined by the action router to be suited for interpreting the user input if the user input specifies a token; and at least one token interpreter configured to determine a token from a user input to be used in performing an action. 2. The system of claim 1 , wherein said action interpreter further determines a token from the user input provided to said action interpreter. | 0.5 |
10,068,617 | 13 | 14 | 13. A system comprising: one or more processors; one or more storage media carrying instructions which, when executed by the one or more processors, cause: storing comment data that indicates a plurality of comments that are associated with a media item; wherein two comments in the plurality of comments are from different users of a plurality of users; wherein each comment in the plurality of comments is associated with a time within the media item; receiving first input that indicates a particular time; wherein the particular time is one of: a selection time indicating when a comment was first or last selected by a user, or a view time indicating when a comment was first or last viewed by a user in response to receiving the first input: performing a search of the plurality of comments based on the particular time, identifying, as a result of performing the search, one or more comments of the plurality of comments that are associated with the particular time; in response to identifying the one or more comments as the result of performing the search, causing, to be displayed on a screen of a computing device, the one or more comments of the plurality of comments; receiving second input that indications user selection of a first comment in the one or more comments; in response to receiving the second input: identifying a first time that is associated with the first comment, identifying, within the media item, a location that corresponds to the first time, causing a playback position of a media player to move to the location. | 13. A system comprising: one or more processors; one or more storage media carrying instructions which, when executed by the one or more processors, cause: storing comment data that indicates a plurality of comments that are associated with a media item; wherein two comments in the plurality of comments are from different users of a plurality of users; wherein each comment in the plurality of comments is associated with a time within the media item; receiving first input that indicates a particular time; wherein the particular time is one of: a selection time indicating when a comment was first or last selected by a user, or a view time indicating when a comment was first or last viewed by a user in response to receiving the first input: performing a search of the plurality of comments based on the particular time, identifying, as a result of performing the search, one or more comments of the plurality of comments that are associated with the particular time; in response to identifying the one or more comments as the result of performing the search, causing, to be displayed on a screen of a computing device, the one or more comments of the plurality of comments; receiving second input that indications user selection of a first comment in the one or more comments; in response to receiving the second input: identifying a first time that is associated with the first comment, identifying, within the media item, a location that corresponds to the first time, causing a playback position of a media player to move to the location. 14. The system of claim 13 , wherein the instructions, when executed by the one or more processors, further cause, in response to receiving the second input, causing the media item to play beginning at the location. | 0.865793 |
10,095,786 | 25 | 26 | 25. A computer readable non-transitory storage medium for tangibly storing thereon computer readable instructions that when executed by a digital content summarization system server perform a method comprising: obtaining, for a first media content item having associated descriptive information, a plurality of second media content items as auxiliary data, the obtaining using the descriptive information associated with the first media content item, the first media content item comprising a plurality of units; generating a media content item feature space comprising a first number of feature vectors comprising feature descriptor values representing the first media content item, the generating further comprising generating an auxiliary data feature space comprising a second number of feature vectors comprising feature descriptor values representing the plurality of second media content items as auxiliary data, obtained using the descriptive information; identifying a plurality of segments of the first media content item, each segment comprising at least one unit of the first media content item's plurality of units; scoring each segment of the plurality of segments of the first media content item, scoring a segment of the plurality of segments comprising determining a distance between the auxiliary data feature and at least one feature vector of the first number of feature vectors, the at least one feature vector representing the segment, each segment's score representing a measure of similarity of the segment to the descriptive information represented by the auxiliary data feature space; identifying at least one segment of the plurality of segments of the first media content item as more similar to the descriptive information, based on its determined distance to the auxiliary data feature space representing the descriptive information relative to others of the plurality of segments using the scoring of the plurality of segments; and generating a summary of the first media content item, the summary comprising the at least one segment of the plurality of segments of the first media content item, identified as being more similar to the descriptive information. | 25. A computer readable non-transitory storage medium for tangibly storing thereon computer readable instructions that when executed by a digital content summarization system server perform a method comprising: obtaining, for a first media content item having associated descriptive information, a plurality of second media content items as auxiliary data, the obtaining using the descriptive information associated with the first media content item, the first media content item comprising a plurality of units; generating a media content item feature space comprising a first number of feature vectors comprising feature descriptor values representing the first media content item, the generating further comprising generating an auxiliary data feature space comprising a second number of feature vectors comprising feature descriptor values representing the plurality of second media content items as auxiliary data, obtained using the descriptive information; identifying a plurality of segments of the first media content item, each segment comprising at least one unit of the first media content item's plurality of units; scoring each segment of the plurality of segments of the first media content item, scoring a segment of the plurality of segments comprising determining a distance between the auxiliary data feature and at least one feature vector of the first number of feature vectors, the at least one feature vector representing the segment, each segment's score representing a measure of similarity of the segment to the descriptive information represented by the auxiliary data feature space; identifying at least one segment of the plurality of segments of the first media content item as more similar to the descriptive information, based on its determined distance to the auxiliary data feature space representing the descriptive information relative to others of the plurality of segments using the scoring of the plurality of segments; and generating a summary of the first media content item, the summary comprising the at least one segment of the plurality of segments of the first media content item, identified as being more similar to the descriptive information. 26. The computer readable non-transitory storage medium of claim 25 , the descriptive information comprising a title of the first media content item. | 0.918668 |
8,825,473 | 1 | 3 | 1. A computer-implemented method of analyzing messages in a computer system to allow workflows constituted by the messages to be identified, the method comprising: analyzing a sequence of messages in a computer system in order to classify the messages, thereby producing a corresponding sequence of classifications of the messages; and, applying sequence induction to the sequence of classifications of the messages to produce (i) a set of sub-sequences of the classifications of the messages and (ii) a sequence grammar for the sub-sequences, from which a workflow constituted by the sequence of messages can be identified, wherein the set of sub-sequences of the classifications of the messages and the sequence grammar for the sub-sequences are obtained by building rules that describe bigrams formed between classifications of the messages in the sequence of classifications of the messages; and wherein a choice to build a new rule is based on all the bigrams that can be formed given the most recent classification in the input sequence of classifications of the messages and each of the classifications in the sequence of classifications of the messages falling within a window. | 1. A computer-implemented method of analyzing messages in a computer system to allow workflows constituted by the messages to be identified, the method comprising: analyzing a sequence of messages in a computer system in order to classify the messages, thereby producing a corresponding sequence of classifications of the messages; and, applying sequence induction to the sequence of classifications of the messages to produce (i) a set of sub-sequences of the classifications of the messages and (ii) a sequence grammar for the sub-sequences, from which a workflow constituted by the sequence of messages can be identified, wherein the set of sub-sequences of the classifications of the messages and the sequence grammar for the sub-sequences are obtained by building rules that describe bigrams formed between classifications of the messages in the sequence of classifications of the messages; and wherein a choice to build a new rule is based on all the bigrams that can be formed given the most recent classification in the input sequence of classifications of the messages and each of the classifications in the sequence of classifications of the messages falling within a window. 3. A method according to claim 1 wherein the sequence of messages is analyzed and the messages are classified by clustering the messages according to similarity of the messages. | 0.675824 |
8,019,754 | 31 | 34 | 31. A method of re-ranking a list of documents obtained from a search wherein a ranking of a document in the list is determined by a relevance of the document to a search text, the method performed by a computer processor, having a scalable time complexity of O(N x ) where 0<=X<=1.0, and comprising: classifying the list of documents so that each document in the list has a fingerprint, said fingerprint comprising a list of weights associated with particular topic categories in a classification system, each of the weights representing a degree to which the document relates to the particular topic category that the weight is associated with, the weights obtained automatically from a computer program, providing a user fingerprint, the user fingerprint comprising a list of cumulative weights associated with particular topic categories in the classification system, each of the cumulative weights representing a degree to which text or texts in a link recently accessed by a user relates to the particular topic category that the cumulative weight is associated with, the cumulative weights obtained from weights that in turn were obtained automatically from a computer program, searching the list of documents by comparing the user fingerprint with the fingerprint for each document in the list of documents, and re-ranking the list of documents based on a degree to which a fingerprint of the document in the list has a mathematical overlap with the user fingerprint, the method configured to re-rank the list of documents based on relevance to the search text whether the list of documents includes text written in one language or in more than one language. | 31. A method of re-ranking a list of documents obtained from a search wherein a ranking of a document in the list is determined by a relevance of the document to a search text, the method performed by a computer processor, having a scalable time complexity of O(N x ) where 0<=X<=1.0, and comprising: classifying the list of documents so that each document in the list has a fingerprint, said fingerprint comprising a list of weights associated with particular topic categories in a classification system, each of the weights representing a degree to which the document relates to the particular topic category that the weight is associated with, the weights obtained automatically from a computer program, providing a user fingerprint, the user fingerprint comprising a list of cumulative weights associated with particular topic categories in the classification system, each of the cumulative weights representing a degree to which text or texts in a link recently accessed by a user relates to the particular topic category that the cumulative weight is associated with, the cumulative weights obtained from weights that in turn were obtained automatically from a computer program, searching the list of documents by comparing the user fingerprint with the fingerprint for each document in the list of documents, and re-ranking the list of documents based on a degree to which a fingerprint of the document in the list has a mathematical overlap with the user fingerprint, the method configured to re-rank the list of documents based on relevance to the search text whether the list of documents includes text written in one language or in more than one language. 34. The method of claim 31 , wherein a selected number of weights is between 1 and 75 and the classification system is the Dewey Decimal System. | 0.516779 |
8,095,538 | 6 | 7 | 6. A method as claimed in claim 1 further comprising: inputting a user search query; utilizing the snippet index to determine documents relevant to said query. | 6. A method as claimed in claim 1 further comprising: inputting a user search query; utilizing the snippet index to determine documents relevant to said query. 7. A method as claimed in claim 6 wherein said similarity function includes a Jaccard function on the words within the query and annotation. | 0.545455 |
8,984,098 | 11 | 14 | 11. A system comprising: a processor; a model generation engine stored on a memory and executed by the processor, the model generation engine for generating a model for a user comprising an interest of the user and prior interaction of the user with heterogeneous data sources; a scoring engine stored on the memory and executed by the processor, the scoring engine coupled to the model generation engine for obtaining a group of candidate content items for one or more streams of content from the heterogeneous data sources, computing an interestingness score for each candidate content item in the group by combining properties of each candidate content item over single-attribute properties using the model and based upon interestingness of each candidate content item to the user and an extent to which the candidate content item's popularity has changed within a geographic area associated with the user and comparing the interestingness score for each candidate content item with a threshold for a first interest type and a second interest type to determine which candidate content items have an interestingness score that exceeds the threshold for the first interest type or the second interest type; and a user interface engine coupled to the scoring engine, the user interface engine for organizing a first content item and a second content item in a first stream of content based on candidate content items that have an interestingness score that exceeds the threshold for the first interest type or the second interest type, providing the first stream of content for presentation in a first direction to the user, generating a user interface for configuring the one or more streams of content, the user interface comprising the first content item, the second content item and a marker, the marker associated with the second content item for the user to request a third content item related to the second content item, and responsive to receiving a selection of the marker associated with the second content item from the user, organizing the second and third content items in a second stream of content, providing the second stream of content for presentation in a second direction to the user, and updating the user interface to include the second stream of content. | 11. A system comprising: a processor; a model generation engine stored on a memory and executed by the processor, the model generation engine for generating a model for a user comprising an interest of the user and prior interaction of the user with heterogeneous data sources; a scoring engine stored on the memory and executed by the processor, the scoring engine coupled to the model generation engine for obtaining a group of candidate content items for one or more streams of content from the heterogeneous data sources, computing an interestingness score for each candidate content item in the group by combining properties of each candidate content item over single-attribute properties using the model and based upon interestingness of each candidate content item to the user and an extent to which the candidate content item's popularity has changed within a geographic area associated with the user and comparing the interestingness score for each candidate content item with a threshold for a first interest type and a second interest type to determine which candidate content items have an interestingness score that exceeds the threshold for the first interest type or the second interest type; and a user interface engine coupled to the scoring engine, the user interface engine for organizing a first content item and a second content item in a first stream of content based on candidate content items that have an interestingness score that exceeds the threshold for the first interest type or the second interest type, providing the first stream of content for presentation in a first direction to the user, generating a user interface for configuring the one or more streams of content, the user interface comprising the first content item, the second content item and a marker, the marker associated with the second content item for the user to request a third content item related to the second content item, and responsive to receiving a selection of the marker associated with the second content item from the user, organizing the second and third content items in a second stream of content, providing the second stream of content for presentation in a second direction to the user, and updating the user interface to include the second stream of content. 14. The system of claim 11 , wherein responsive to receiving selections of the marker from the user, the user interface engine displays new content items that move in the second direction. | 0.716012 |
9,613,161 | 4 | 6 | 4. The system of claim 1 , wherein the plurality of search results are displayed in a scrollable interface; and the operations further comprise, responsive to an amount of scrolling of the scrollable interface past a threshold, displaying refinement data in a non-scrollable element, the refinement data including one or more refinement options, the displaying of the non-scrollable element being performed in conjunction with the displaying of the plurality of search results. | 4. The system of claim 1 , wherein the plurality of search results are displayed in a scrollable interface; and the operations further comprise, responsive to an amount of scrolling of the scrollable interface past a threshold, displaying refinement data in a non-scrollable element, the refinement data including one or more refinement options, the displaying of the non-scrollable element being performed in conjunction with the displaying of the plurality of search results. 6. The system of claim 4 , wherein the threshold is based on a determination that a first refinement option of the one or more refinement options has scrolled off of the display device. | 0.785383 |
8,861,856 | 8 | 14 | 8. A method for determining a logical structure of a document, the method comprising: acquiring an image of the document; identifying one or more blocks in the image of the document; generating at least two document hypotheses for the image of the document, wherein said generating includes referencing a plurality of document models, wherein each document model describes one or more possible logical structures, and wherein each document model includes information about blocks of said respective document model; after generating said at least two document hypotheses, generating at least one block hypothesis corresponding to at least one of said identified one or more blocks in the image of the document; for each document hypothesis, selecting programmatically as a best document hypothesis the document hypothesis that has a best degree of correspondence with one or more block hypotheses for the document; and forming a representation of the document based on the best document hypothesis. | 8. A method for determining a logical structure of a document, the method comprising: acquiring an image of the document; identifying one or more blocks in the image of the document; generating at least two document hypotheses for the image of the document, wherein said generating includes referencing a plurality of document models, wherein each document model describes one or more possible logical structures, and wherein each document model includes information about blocks of said respective document model; after generating said at least two document hypotheses, generating at least one block hypothesis corresponding to at least one of said identified one or more blocks in the image of the document; for each document hypothesis, selecting programmatically as a best document hypothesis the document hypothesis that has a best degree of correspondence with one or more block hypotheses for the document; and forming a representation of the document based on the best document hypothesis. 14. The method of claim 8 , wherein identifying said one or more blocks in the image of the document includes selecting a best block hypothesis for each block by comparing each block hypothesis with information about blocks of said respective document model. | 0.5 |
8,204,182 | 2 | 39 | 2. The method of claim 1 , wherein a user of the text exchange client is permitted to modify entries of the translation table. | 2. The method of claim 1 , wherein a user of the text exchange client is permitted to modify entries of the translation table. 39. The method of claim 2 , wherein the text exchange client is an off-the-shelf unmodified client, and wherein the speech enabled application is an unmodified application configured to execute in a VoiceXML server. | 0.70788 |
8,875,013 | 1 | 7 | 1. A method for validating XML documents comprising: determining a set of preprocessing parameters from an XML document, wherein responsive to any missing preprocessing parameter in the set of preprocessing parameters, determining the XML document to be invalid, wherein a result of determining that the XML document is invalid causes a ceasing of activities related to validation, wherein the preprocessing parameters represent at least one of data tags and values within the XML document, and wherein the preprocessing parameters represent at least one of data tags and values within the XML document; upon determining the set of preprocessing parameters, identifying a validation sequence from a plurality of validation sequences for the XML document based on the set of preprocessing parameters, wherein each of the validation sequence comprises a unique order of execution for series of validation passes to validate the XML document, wherein said validation sequence comprises a plurality of validation elements, wherein each validation pass corresponds to one of the validation elements, wherein each of the validation element represents a type of governance for validating the XML document, wherein each validation pass is configured to validate the XML document for at least one condition defined by the validation element; and perform a multi-pass validation associated with the validation sequence on the XML document; and producing a validation element result for each performed validation pass. | 1. A method for validating XML documents comprising: determining a set of preprocessing parameters from an XML document, wherein responsive to any missing preprocessing parameter in the set of preprocessing parameters, determining the XML document to be invalid, wherein a result of determining that the XML document is invalid causes a ceasing of activities related to validation, wherein the preprocessing parameters represent at least one of data tags and values within the XML document, and wherein the preprocessing parameters represent at least one of data tags and values within the XML document; upon determining the set of preprocessing parameters, identifying a validation sequence from a plurality of validation sequences for the XML document based on the set of preprocessing parameters, wherein each of the validation sequence comprises a unique order of execution for series of validation passes to validate the XML document, wherein said validation sequence comprises a plurality of validation elements, wherein each validation pass corresponds to one of the validation elements, wherein each of the validation element represents a type of governance for validating the XML document, wherein each validation pass is configured to validate the XML document for at least one condition defined by the validation element; and perform a multi-pass validation associated with the validation sequence on the XML document; and producing a validation element result for each performed validation pass. 7. The method of claim 1 , further comprising: analyzing the XML document using a text parser; and determining said validation sequence from a plurality of previously defined validation sequences based upon results of analyzing the XML document using the text parser. | 0.841825 |
8,584,226 | 1 | 9 | 1. A method for a geographic country of origin filter of information transmitting on a network: a) a network object on which the method is embodied, which extracts a network address from Internet traffic routed or collected by said network object; and performs at least one data lookup operation to obtain country of origin geographic information pertaining to said Internet network address; b) configuring said geographic country of origin filter by: Sending or receiving information used to generate a set of persistent geographic country of origin associations comprising a plurality of Internet address blocks; Performing at least one data processing operating to associate a geographic country of origin location pertaining to each block; and Generating at least one geographic country of origin security assertion wherein a device action is defined for at least one geographic country of origin association wherein the device action is triggered for any Internet address belonging to a defined network address block having an estimated country of origin geographic location, wherein the device action either: Allows Internet traffic to be sent or received from said Internet address to the desired destination; Disallows Internet traffic to be sent or received from said Internet address to the desired destination; or Mows Internet traffic to be sent or received from said Internet address to an undesired destination determined by said geographic filter; c) Optimizing said geographic country of origin information pertaining to Internet network addresses in accordance with at least one algorithm, wherein an algorithm is applied to the plurality of geographic country of origin associations between IP address blocks and geographic country of origin locations. | 1. A method for a geographic country of origin filter of information transmitting on a network: a) a network object on which the method is embodied, which extracts a network address from Internet traffic routed or collected by said network object; and performs at least one data lookup operation to obtain country of origin geographic information pertaining to said Internet network address; b) configuring said geographic country of origin filter by: Sending or receiving information used to generate a set of persistent geographic country of origin associations comprising a plurality of Internet address blocks; Performing at least one data processing operating to associate a geographic country of origin location pertaining to each block; and Generating at least one geographic country of origin security assertion wherein a device action is defined for at least one geographic country of origin association wherein the device action is triggered for any Internet address belonging to a defined network address block having an estimated country of origin geographic location, wherein the device action either: Allows Internet traffic to be sent or received from said Internet address to the desired destination; Disallows Internet traffic to be sent or received from said Internet address to the desired destination; or Mows Internet traffic to be sent or received from said Internet address to an undesired destination determined by said geographic filter; c) Optimizing said geographic country of origin information pertaining to Internet network addresses in accordance with at least one algorithm, wherein an algorithm is applied to the plurality of geographic country of origin associations between IP address blocks and geographic country of origin locations. 9. The method of claim 1 , wherein a geographic security assertion is at least one Resource Identifier and a Device Action. | 0.818584 |
8,180,804 | 12 | 17 | 12. The system of claim 11 , wherein the data store of information is indexed into one or more indexes to facilitate the determining of the first and second data sets. | 12. The system of claim 11 , wherein the data store of information is indexed into one or more indexes to facilitate the determining of the first and second data sets. 17. The system of claim 12 , wherein: to determine the first data set, the logic, when executed by the one or more processors, is operable to send a first nested query to an indexing process that searches the one or more indexes; and to determine the second data set, the logic, when executed by the one or more processors, is operable to send a second nested query to the indexing process that searches the one or more indexes. | 0.5 |
7,937,465 | 1 | 10 | 1. A computationally-implemented system, comprising: circuitry for acquiring subjective user state data including data indicating at least one subjective user state associated with a user; circuitry for acquiring objective occurrence data including data indicating at least one objective occurrence associated with the user; and circuitry for correlating the subjective user state data with the objective occurrence data based, at least in part, on a determination of at least one sequential pattern associated with the at least one subjective user state and the at least one objective occurrence. | 1. A computationally-implemented system, comprising: circuitry for acquiring subjective user state data including data indicating at least one subjective user state associated with a user; circuitry for acquiring objective occurrence data including data indicating at least one objective occurrence associated with the user; and circuitry for correlating the subjective user state data with the objective occurrence data based, at least in part, on a determination of at least one sequential pattern associated with the at least one subjective user state and the at least one objective occurrence. 10. The computationally-implemented system of claim 1 , wherein said circuitry for acquiring subjective user state data including data indicating at least one subjective user state associated with a user comprises: circuitry for acquiring a time stamp associated with the at least one subjective user state. | 0.763482 |
9,880,997 | 14 | 15 | 14. A method, comprising: obtaining, by a device, information identifying type classifications via an interface or from a memory, the interface including one or more of a communication interface or a user interface, each type classification, of the type classifications, indicating that terms classified under the type classification are expressed by a particular type of value of a plurality of types of values, the plurality of types of values including character strings and numeric values; obtaining, by the device and via the interface, text to be processed to infer one or more type classifications associated with unique terms, the text being included in a file associated with development of a computer program for a computer system, and each respective term, of the terms, being associated with a plurality of different possible values of a same type classification of the one or more type classifications; standardizing, by the device, the text to prepare the text for processing by adjusting at least one character in the text of the file; processing, by the device, the text that has been standardized to identify terms in the text based on delimiting characters in the text; associating, by the device, at least one tag with the identified terms in the text, the at least one tag being one or more of a part-of-speech tag, an entity tag, or a term tag; extracting, by the device and based on the at least one tag associated with the terms, one or more terms, of the terms identified in the text, as unique terms for which to infer the one or more type classifications, a quantity of the unique terms being fewer than a quantity of the terms identified in the text; generating a data structure that stores the unique terms; inferring, by the device, a type relationship between a particular term, of the unique terms stored in the data structure, and a particular type classification, of the one or more type classifications, by performing one or more type classification techniques, the one or more type classification techniques including at least one of: a name-based analysis that compares the particular term to a set of name-based type indicators associated with the particular type classification, a context-based analysis that compares a modifier, that modifies the particular term, to a set of context-based type indicators associated with the particular type classification, a synonym-based analysis that compares a synonym, of the particular term, to the set of name-based type indicators associated with the particular type classification, or a value-based analysis that compares a value, that appears within a threshold proximity of the particular term, to a set of value-based type indicators or a set of value-based type patterns associated with the particular type classification; classifying, by the device, the unique terms by assigning the one or more type classifications to the unique terms based on performing the one or more type classification techniques; providing, for display via the interface and by the device, information associated with development of the computer program, the information associated with development of the computer program identifying the type relationship, between the particular term and the particular type classification, based on inferring the type relationship and further based on performing the one or more type classification techniques; receiving, via the interface and by the device, a set of test data rules from a user or from another device; generating, by the device, test data based on the set of test data rules, the test data including the unique terms to be classified, type classifications under which the unique terms are to be classified, and values for the unique terms; applying, by the device, the test data to the computer program, the computer program being designed based on the text that was processed to infer one or more type classifications for the unique terms extracted from the text, and the applying of the test data to the computer program includes input of the test data to the computer program and executing the computer program to: classify the test data to obtain a confidence score associated with the classifying a unique term, of the unique terms, under each of the type classifications determined to be associated with the unique term; and providing, by the device and for display to the user or to another device, the test data, the one or more type classifications generated from the test data, and the confidence score associated with the one or more type classifications. | 14. A method, comprising: obtaining, by a device, information identifying type classifications via an interface or from a memory, the interface including one or more of a communication interface or a user interface, each type classification, of the type classifications, indicating that terms classified under the type classification are expressed by a particular type of value of a plurality of types of values, the plurality of types of values including character strings and numeric values; obtaining, by the device and via the interface, text to be processed to infer one or more type classifications associated with unique terms, the text being included in a file associated with development of a computer program for a computer system, and each respective term, of the terms, being associated with a plurality of different possible values of a same type classification of the one or more type classifications; standardizing, by the device, the text to prepare the text for processing by adjusting at least one character in the text of the file; processing, by the device, the text that has been standardized to identify terms in the text based on delimiting characters in the text; associating, by the device, at least one tag with the identified terms in the text, the at least one tag being one or more of a part-of-speech tag, an entity tag, or a term tag; extracting, by the device and based on the at least one tag associated with the terms, one or more terms, of the terms identified in the text, as unique terms for which to infer the one or more type classifications, a quantity of the unique terms being fewer than a quantity of the terms identified in the text; generating a data structure that stores the unique terms; inferring, by the device, a type relationship between a particular term, of the unique terms stored in the data structure, and a particular type classification, of the one or more type classifications, by performing one or more type classification techniques, the one or more type classification techniques including at least one of: a name-based analysis that compares the particular term to a set of name-based type indicators associated with the particular type classification, a context-based analysis that compares a modifier, that modifies the particular term, to a set of context-based type indicators associated with the particular type classification, a synonym-based analysis that compares a synonym, of the particular term, to the set of name-based type indicators associated with the particular type classification, or a value-based analysis that compares a value, that appears within a threshold proximity of the particular term, to a set of value-based type indicators or a set of value-based type patterns associated with the particular type classification; classifying, by the device, the unique terms by assigning the one or more type classifications to the unique terms based on performing the one or more type classification techniques; providing, for display via the interface and by the device, information associated with development of the computer program, the information associated with development of the computer program identifying the type relationship, between the particular term and the particular type classification, based on inferring the type relationship and further based on performing the one or more type classification techniques; receiving, via the interface and by the device, a set of test data rules from a user or from another device; generating, by the device, test data based on the set of test data rules, the test data including the unique terms to be classified, type classifications under which the unique terms are to be classified, and values for the unique terms; applying, by the device, the test data to the computer program, the computer program being designed based on the text that was processed to infer one or more type classifications for the unique terms extracted from the text, and the applying of the test data to the computer program includes input of the test data to the computer program and executing the computer program to: classify the test data to obtain a confidence score associated with the classifying a unique term, of the unique terms, under each of the type classifications determined to be associated with the unique term; and providing, by the device and for display to the user or to another device, the test data, the one or more type classifications generated from the test data, and the confidence score associated with the one or more type classifications. 15. The method of claim 14 , where inferring the type relationship by performing the one or more type classification techniques comprises: performing the name-based analysis; determining, based on performing the name-based analysis, that the particular term includes a first word that matches a second word included in the set of name-based type indicators; and inferring the type relationship based on determining that the particular term includes the first word that matches the second word. | 0.57279 |
8,140,980 | 1 | 7 | 1. A method for providing multi-media conferencing, the method comprising: receiving textual information for display during a conference session among a plurality of participants; retrieving configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; augmenting the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the augmenting of the textual information includes determining whether the textual information is contained in a predetermined list of terms and associated supplemental information, wherein the supplemental information includes definitions of the corresponding terms, and marking the textual information to notify the one participant that the supplemental information is available for selective display if the textual information is in the list; and forwarding the textual information having the marking to the one participant for display during the conference session without replacement of the textual information. | 1. A method for providing multi-media conferencing, the method comprising: receiving textual information for display during a conference session among a plurality of participants; retrieving configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; augmenting the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the augmenting of the textual information includes determining whether the textual information is contained in a predetermined list of terms and associated supplemental information, wherein the supplemental information includes definitions of the corresponding terms, and marking the textual information to notify the one participant that the supplemental information is available for selective display if the textual information is in the list; and forwarding the textual information having the marking to the one participant for display during the conference session without replacement of the textual information. 7. A method according to claim 1 , the method further comprising: recording the conference session; marking the recorded conference session; and selectively providing marking information to one or more of the participants. | 0.610526 |
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