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8,572,024 | 14 | 19 | 14. The apparatus of claim 13 , further configured to collect a plurality of HTML structured documents from a merchant web site. | 14. The apparatus of claim 13 , further configured to collect a plurality of HTML structured documents from a merchant web site. 19. The apparatus of claim 14 , further configured to determine the co-occurring HTML structured documents that achieve a pre-determined threshold. | 0.69877 |
8,799,658 | 21 | 31 | 21. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, receiving, at a server, a request from a user to share a media item stored on a device of the user with one or more content rendering devices associated with one or more other users, wherein the request from the user does not include information identifying the one or more other users, or the one or more content rendering devices associated with the one or more other users, as intended recipients of the media item; in response to receiving the request at the server, associating a pass phrase with the request to share the media item; sending the pass phrase from the server to the device of the user; after sending the pass phrase, receiving, at the server, the media item stored on the device of the user; after receiving the media item at the server, storing the media item in association with the pass phrase, the pass phrase being usable for later access of the media item by the one or more other content rendering devices associated with the one or more other users; receiving, at the server, the pass phrase from individual content rendering devices of the one or more content rendering devices associated with the one or more other users; and sending at least a portion of the media item from the server to the individual content rendering devices associated with the one or more other users at least partly in response to the receiving of the pass phrase at the server. | 21. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, receiving, at a server, a request from a user to share a media item stored on a device of the user with one or more content rendering devices associated with one or more other users, wherein the request from the user does not include information identifying the one or more other users, or the one or more content rendering devices associated with the one or more other users, as intended recipients of the media item; in response to receiving the request at the server, associating a pass phrase with the request to share the media item; sending the pass phrase from the server to the device of the user; after sending the pass phrase, receiving, at the server, the media item stored on the device of the user; after receiving the media item at the server, storing the media item in association with the pass phrase, the pass phrase being usable for later access of the media item by the one or more other content rendering devices associated with the one or more other users; receiving, at the server, the pass phrase from individual content rendering devices of the one or more content rendering devices associated with the one or more other users; and sending at least a portion of the media item from the server to the individual content rendering devices associated with the one or more other users at least partly in response to the receiving of the pass phrase at the server. 31. The computer-implemented method as recited in claim 21 , further comprising receiving, at the server, a copy of the portion of the media item from the device of the user prior to sending the portion of the media item from the server to the individual content rendering devices. | 0.598571 |
9,397,830 | 4 | 5 | 4. The method of claim 3 , wherein the pattern indicators comprise encryption patterns to be used for generating the encrypted chunks. | 4. The method of claim 3 , wherein the pattern indicators comprise encryption patterns to be used for generating the encrypted chunks. 5. The method of claim 4 , wherein the randomly generating encryption parameters includes generating a key representing a symbol table transformation including a symbol table reversal. | 0.5 |
9,053,152 | 8 | 12 | 8. A computer-program product, comprising computer-readable instructions embodied on tangible, non-transitory media, the computer-readable instructions operable when executed to: identify a data artifact associated with each search result of at least one received search result; associate each identified data artifact with a module category of a plurality of module categories, the module category associated with a module associated with a module gallery displaying modules that may be associated with an enterprise workspace page associated with an enterprise workspace; inject the identified artifacts into a content gallery presenting available content associated with a module available to be selected and added to the enterprise workspace page and extending what is displayed in the module gallery to include non-identified artifacts; categorize the injected identified artifacts within the content gallery; present at least a subset of the injected identified artifacts on the enterprise workspace page; and construct a context associated with at least one of the enterprise workspace or the enterprise workspace page. | 8. A computer-program product, comprising computer-readable instructions embodied on tangible, non-transitory media, the computer-readable instructions operable when executed to: identify a data artifact associated with each search result of at least one received search result; associate each identified data artifact with a module category of a plurality of module categories, the module category associated with a module associated with a module gallery displaying modules that may be associated with an enterprise workspace page associated with an enterprise workspace; inject the identified artifacts into a content gallery presenting available content associated with a module available to be selected and added to the enterprise workspace page and extending what is displayed in the module gallery to include non-identified artifacts; categorize the injected identified artifacts within the content gallery; present at least a subset of the injected identified artifacts on the enterprise workspace page; and construct a context associated with at least one of the enterprise workspace or the enterprise workspace page. 12. The computer-program product of claim 8 , wherein injected identified artifacts are categorized within the content gallery according to a type and a source. | 0.73064 |
8,073,698 | 2 | 6 | 2. The method of claim 1 , wherein the managing comprises: if it is determined that the loaded multimodal web page is one of the plurality of multimodal web pages of the particular multimodal application, loading at least one global grammar in the loaded multimodal web page. | 2. The method of claim 1 , wherein the managing comprises: if it is determined that the loaded multimodal web page is one of the plurality of multimodal web pages of the particular multimodal application, loading at least one global grammar in the loaded multimodal web page. 6. The method of claim 2 , further comprising identifying the at least one global grammar based at least in part on markup in the loaded multimodal web page. | 0.5 |
8,250,145 | 7 | 8 | 7. The method of claim 1 , wherein the requested information received from the social networking system comprises a set of content items that relate to (1) one or more actions performed by one or more other users with whom the user has established a connection in the social networking system, and (2) at least one specified URL or domain. | 7. The method of claim 1 , wherein the requested information received from the social networking system comprises a set of content items that relate to (1) one or more actions performed by one or more other users with whom the user has established a connection in the social networking system, and (2) at least one specified URL or domain. 8. The method of claim 7 , wherein one or more of the specified URLs or domains are different from the requested web page. | 0.809375 |
8,200,661 | 1 | 5 | 1. A method for providing a recommendation, comprising: training a supervised-learning model based on portions of content in a support document that are accessed by one or more users during multiple separate sessions, wherein the support document comprises content for multiple support topics; configuring the supervised-learning model so that when the supervised-learning model is used to identify one or more support topics, the supervised-learning model assigns a larger weight to a first portion of the content that is accessed by a given user during a single session than a second portion of the content that is accessed by the given user during multiple separate sessions; monitoring user actions while a user interacts with the support document using a computer during a current session; based on the user actions, using the supervised-learning model to identify one or more support topics in the multiple support topics; and providing the recommendation, which includes the one or more identified support topics, to the user. | 1. A method for providing a recommendation, comprising: training a supervised-learning model based on portions of content in a support document that are accessed by one or more users during multiple separate sessions, wherein the support document comprises content for multiple support topics; configuring the supervised-learning model so that when the supervised-learning model is used to identify one or more support topics, the supervised-learning model assigns a larger weight to a first portion of the content that is accessed by a given user during a single session than a second portion of the content that is accessed by the given user during multiple separate sessions; monitoring user actions while a user interacts with the support document using a computer during a current session; based on the user actions, using the supervised-learning model to identify one or more support topics in the multiple support topics; and providing the recommendation, which includes the one or more identified support topics, to the user. 5. The method of claim 1 , wherein the support document includes a website or a web page. | 0.878082 |
8,768,960 | 9 | 15 | 9. One or more computer storage media having stored thereon computer-executable instructions that, when executed by a processor, causes the processor to perform operations comprising: identifying candidate phrases in a webpage based at least in part on an online encyclopedia phrases index; associating the candidate phrases with online encyclopedia entries; constructing a semantic bipartite graph between the candidate phrases and categories that include the online encyclopedia entries; and selecting one or more of the candidate phrases as keywords for advertisement targeting based at least in part on quantities of associations between a candidate phrase and the categories of the candidate phrases, the associations being derived from the semantic bipartite graph, in which the keywords for advertisement targeting are extracted by mining semantics provided by an online encyclopedia taxonomy. | 9. One or more computer storage media having stored thereon computer-executable instructions that, when executed by a processor, causes the processor to perform operations comprising: identifying candidate phrases in a webpage based at least in part on an online encyclopedia phrases index; associating the candidate phrases with online encyclopedia entries; constructing a semantic bipartite graph between the candidate phrases and categories that include the online encyclopedia entries; and selecting one or more of the candidate phrases as keywords for advertisement targeting based at least in part on quantities of associations between a candidate phrase and the categories of the candidate phrases, the associations being derived from the semantic bipartite graph, in which the keywords for advertisement targeting are extracted by mining semantics provided by an online encyclopedia taxonomy. 15. The one or more computer storage media of claim 9 , wherein the selecting includes utilizing a Hyperlink-Induced Topic Search (HITS) algorithm on the semantic bipartite graph to select a top N candidate phrases and categories as keywords and topics for the web page. | 0.649351 |
8,219,385 | 36 | 37 | 36. A computer-implemented method of conducting a search of electronically stored information, comprising: (a) providing a user with an interactive targeting rule editor to enable the user to formulate a targeting rule to identify desired search results, the targeting rule comprising a natural language text string, the interactive targeting rule editor allowing the user to change one or more designated editable portions of the natural language text string to one of a set of specified alternate portions, delete one or more designated removable portions of the natural language text string, and add one or more of a set of specified insertable portions to form a syntactically valid targeting rule in accordance with a targeting rule grammar; (b) receiving the text string or a representation thereof from the user; (c) translating the text string or a representation thereof into an executable query; and (d) executing the executable query against the electronically stored information to generate search results. | 36. A computer-implemented method of conducting a search of electronically stored information, comprising: (a) providing a user with an interactive targeting rule editor to enable the user to formulate a targeting rule to identify desired search results, the targeting rule comprising a natural language text string, the interactive targeting rule editor allowing the user to change one or more designated editable portions of the natural language text string to one of a set of specified alternate portions, delete one or more designated removable portions of the natural language text string, and add one or more of a set of specified insertable portions to form a syntactically valid targeting rule in accordance with a targeting rule grammar; (b) receiving the text string or a representation thereof from the user; (c) translating the text string or a representation thereof into an executable query; and (d) executing the executable query against the electronically stored information to generate search results. 37. The method of claim 36 wherein at least one of the specified alternate portions includes one or more further designated editable portions that can be changed by the user to one of a further set of specified alternate portions to form the syntactically valid targeting rule. | 0.5 |
7,840,460 | 1 | 13 | 1. A computerized method for evaluating a patent portfolio, comprising patent documents, by one or more experts, the method comprising: performing by a processor of a computing device the following steps: (a) determining a bias of each said expert by comparing results of evaluation of at least one test patent document performed by each said expert with a predetermined evaluation of said test patent document; and (b) evaluating the patent documents from the patent portfolio by said experts according to an evaluation method, including bias correcting the evaluation method for each said expert so that to compensate for the bias of each said expert; wherein: the step (b) further comprises evaluating a patent document from the patent portfolio according to an evaluation method, which processes a number of patent indices, characterizing different aspects of the patent document, into a Patent Quality index (PQ), characterizing value of the patent document, according to a non-linear function of said patent indices; the non-linear function is characterized by a parameter of non-linearity, corresponding to a bias of an expert and selected so that to compensate for the bias of the expert; the step (b) further comprises selecting the non-linear function, which is continuous, monotonously increasing or decreasing, bounded on the interval of variations of patent indices, and processes the patent indices into the PQ as follows: when a value of any patent index tends substantially to its minimal value, then the PQ also tends substantially to its minimal value for the increasing function, and to its maximal value for the decreasing function. | 1. A computerized method for evaluating a patent portfolio, comprising patent documents, by one or more experts, the method comprising: performing by a processor of a computing device the following steps: (a) determining a bias of each said expert by comparing results of evaluation of at least one test patent document performed by each said expert with a predetermined evaluation of said test patent document; and (b) evaluating the patent documents from the patent portfolio by said experts according to an evaluation method, including bias correcting the evaluation method for each said expert so that to compensate for the bias of each said expert; wherein: the step (b) further comprises evaluating a patent document from the patent portfolio according to an evaluation method, which processes a number of patent indices, characterizing different aspects of the patent document, into a Patent Quality index (PQ), characterizing value of the patent document, according to a non-linear function of said patent indices; the non-linear function is characterized by a parameter of non-linearity, corresponding to a bias of an expert and selected so that to compensate for the bias of the expert; the step (b) further comprises selecting the non-linear function, which is continuous, monotonously increasing or decreasing, bounded on the interval of variations of patent indices, and processes the patent indices into the PQ as follows: when a value of any patent index tends substantially to its minimal value, then the PQ also tends substantially to its minimal value for the increasing function, and to its maximal value for the decreasing function. 13. The method as described in claim 1 , wherein the non-linear transformation is as follows: PQ = 1 1 - b + b · ( K 1 x 1 + K 2 x 2 + … + K n x n ) , wherein b is the parameter of non-linearity, x 1 , x 2 , . . . , x n are patent indices, and K i , i=1, . . . n is a coefficient indicating relative contribution of the i-th patent index into the PQ, where K 1 =K 2 + . . . +K n =1. | 0.5 |
7,949,941 | 44 | 49 | 44. The non-transitory computer-readable storage medium of claim 32 , wherein the determining further comprises: based at least in part on the structural description that constrains the set of one or more XML documents to the hierarchy of nodes that may be present in the set of one or more XML documents, constructing a corresponding sample document that represents the structure of the set of one or more XML documents; submitting the sample document to an XSLT engine for transformation based at least in part on the XSLT stylesheet and for tracing execution paths associated with the transformation, wherein the execution paths indicate, for particular nodes contained in the sample document, which particular transformation template to use to transform the corresponding particular node. | 44. The non-transitory computer-readable storage medium of claim 32 , wherein the determining further comprises: based at least in part on the structural description that constrains the set of one or more XML documents to the hierarchy of nodes that may be present in the set of one or more XML documents, constructing a corresponding sample document that represents the structure of the set of one or more XML documents; submitting the sample document to an XSLT engine for transformation based at least in part on the XSLT stylesheet and for tracing execution paths associated with the transformation, wherein the execution paths indicate, for particular nodes contained in the sample document, which particular transformation template to use to transform the corresponding particular node. 49. The non-transitory computer-readable storage medium of claim 44 , wherein constructing the sample document includes constructing the sample document using a data guide to which the set of one or more XML documents structurally conforms. | 0.769231 |
9,047,337 | 4 | 5 | 4. The method of claim 1 , wherein the text string represents a partially completed database statement, and wherein providing the programming assistance comprises: predicting, based on the text string, one or more completed elements of the database statement; and displaying a list of the one or more completed elements in the editing pane. | 4. The method of claim 1 , wherein the text string represents a partially completed database statement, and wherein providing the programming assistance comprises: predicting, based on the text string, one or more completed elements of the database statement; and displaying a list of the one or more completed elements in the editing pane. 5. The method of claim 4 , wherein at least one of the one or more completed elements is a keyword of a database query language in which the database statement is being composed. | 0.5 |
10,073,794 | 14 | 18 | 14. A method comprising: receiving search input by the user, wherein the search input comprises at least one of a picture, visual product scan, service token scan or a brand logo scan; establishing a temporary application (APP) container; connecting to a web portal corresponding to a supplier related to the search input; downloading a website corresponding to the supplier from the web portal; displaying the website on the display screen of the mobile handheld communication device; retrieving search parameters from the search input; combining retrieved search parameters from the search input with locally saved customer preference data to generate a contextualized search criteria; combining the contextualized search criteria with location information of the user to identify a set of brand and product portals; connecting to the set of brand and product portals; requesting APPS that satisfy the contextualized search criteria to be downloaded from the set of brand and product portals into the temporary APP container location; presenting logos and tokens from the downloaded APPs to the user to enable an expanded search capability to the user that meets the search parameters; and collecting and compiling consumer preference data of the user. | 14. A method comprising: receiving search input by the user, wherein the search input comprises at least one of a picture, visual product scan, service token scan or a brand logo scan; establishing a temporary application (APP) container; connecting to a web portal corresponding to a supplier related to the search input; downloading a website corresponding to the supplier from the web portal; displaying the website on the display screen of the mobile handheld communication device; retrieving search parameters from the search input; combining retrieved search parameters from the search input with locally saved customer preference data to generate a contextualized search criteria; combining the contextualized search criteria with location information of the user to identify a set of brand and product portals; connecting to the set of brand and product portals; requesting APPS that satisfy the contextualized search criteria to be downloaded from the set of brand and product portals into the temporary APP container location; presenting logos and tokens from the downloaded APPs to the user to enable an expanded search capability to the user that meets the search parameters; and collecting and compiling consumer preference data of the user. 18. The method of claim 14 , further comprising storing the consumer preference data in memory. | 0.745989 |
8,671,280 | 6 | 8 | 6. An electronic document management method for managing document information relating to an electronic bond generated from electronic information and registered by a computer including a processor, the method comprising: acquiring, using the processor, a plurality of pieces of part identification information respectively identifiably expressing a plurality of parts of document information and a digital signature corresponding to the document information; acquiring, using the processor, a preparation type, a preparer's name and a time and date of preparation of the document information as tracing information of the document information, the preparation type indicating at least one of new issuance of an electronic bond, transfer of a whole electronic bond, issuance of divided electronic bonds, and transfer of one or more than one divided electronic bonds; managing the part identification information and the digital signature acquired in acquiring the plurality of pieces of part identification information and the digital signature and the tracing information acquired in acquiring the preparation type, the preparer's name and the time and date of preparation of the document information, in association with each other, managing, when the preparation type indicates the issuance of divided electronic bonds, the part identification information identifiably expressing amounts of the divided electronic bonds and attached with an electronic signature of the preparer's name of the issuance of divided electronic bonds; and presenting information relating to the tracing information to the user in response to a request from the user, and causing the acquiring of the plurality of pieces of part identification information and the digital signature and acquiring of the preparation type, the preparer's name and the time and date of preparation of the document information to be executed in response to a directive from the user:, wherein the acquiring the plurality of pieces of part identification information divides the document information into a plurality of parts, generates a piece of hash information according to the information of each part and acquires the generated plurality of pieces of hash information as the part identification information, and the hash information is generated by adding the time information to the information of each of the parts of the document information. | 6. An electronic document management method for managing document information relating to an electronic bond generated from electronic information and registered by a computer including a processor, the method comprising: acquiring, using the processor, a plurality of pieces of part identification information respectively identifiably expressing a plurality of parts of document information and a digital signature corresponding to the document information; acquiring, using the processor, a preparation type, a preparer's name and a time and date of preparation of the document information as tracing information of the document information, the preparation type indicating at least one of new issuance of an electronic bond, transfer of a whole electronic bond, issuance of divided electronic bonds, and transfer of one or more than one divided electronic bonds; managing the part identification information and the digital signature acquired in acquiring the plurality of pieces of part identification information and the digital signature and the tracing information acquired in acquiring the preparation type, the preparer's name and the time and date of preparation of the document information, in association with each other, managing, when the preparation type indicates the issuance of divided electronic bonds, the part identification information identifiably expressing amounts of the divided electronic bonds and attached with an electronic signature of the preparer's name of the issuance of divided electronic bonds; and presenting information relating to the tracing information to the user in response to a request from the user, and causing the acquiring of the plurality of pieces of part identification information and the digital signature and acquiring of the preparation type, the preparer's name and the time and date of preparation of the document information to be executed in response to a directive from the user:, wherein the acquiring the plurality of pieces of part identification information divides the document information into a plurality of parts, generates a piece of hash information according to the information of each part and acquires the generated plurality of pieces of hash information as the part identification information, and the hash information is generated by adding the time information to the information of each of the parts of the document information. 8. The electronic document management method according to claim 6 , wherein the acquiring of pieces of part identification information acquires the part identification information and the digital signature by transmitting a predetermined electronic form prepared by using electronic data from an electronic document management apparatus to a user terminal in response to a request from the user and receiving the data on the predetermined lines input from the user terminal, using the predetermined electronic form. | 0.5 |
9,183,308 | 13 | 14 | 13. A non-transitory computer-readable-storage medium comprising one or more processor-executable instructions that, when executed by at least one processor, causes the at least one processor to perform a method comprising: generating a topic model comprising a set of salient terms at least in part determined statistically from a comparison of an occurrence of a plurality of terms contained in selected items of real-time online information which a user has previously chosen to view with an occurrence of said terms in a body of real-time online information through a real-time information retrieval service, wherein the body of real-time online information comprises other items of real-time online information which the user has not previously chosen to view; retrieving, by the real time information retrieval service, additional items of online real-time information related to the topic model; automatically creating a search query derived from the set of salient terms in the topic model; using a search engine to search a body of non-real time information on the Internet, different than the body of real-time online information, for items of non-real time information responsive to the search query; and presenting to the user the additional items of online real-time information and the items of non-real time information responsive to the search query, as a result relevant to the user's interest. | 13. A non-transitory computer-readable-storage medium comprising one or more processor-executable instructions that, when executed by at least one processor, causes the at least one processor to perform a method comprising: generating a topic model comprising a set of salient terms at least in part determined statistically from a comparison of an occurrence of a plurality of terms contained in selected items of real-time online information which a user has previously chosen to view with an occurrence of said terms in a body of real-time online information through a real-time information retrieval service, wherein the body of real-time online information comprises other items of real-time online information which the user has not previously chosen to view; retrieving, by the real time information retrieval service, additional items of online real-time information related to the topic model; automatically creating a search query derived from the set of salient terms in the topic model; using a search engine to search a body of non-real time information on the Internet, different than the body of real-time online information, for items of non-real time information responsive to the search query; and presenting to the user the additional items of online real-time information and the items of non-real time information responsive to the search query, as a result relevant to the user's interest. 14. The computer-readable-storage medium of claim 13 further comprising accessing a plurality of information sources through a communication network to retrieve the non-real time information. | 0.5 |
7,818,197 | 7 | 13 | 7. A schedule management method for managing user's schedules and tasks, comprising: storing a context estimation rule for use in estimation of contexts of spare time blocks, wherein the context estimation rule is used to generate a context by applying the context estimation rule to the spare time blocks and the context estimation rule generates contexts corresponding to schedule types before spare time blocks whose contexts are estimated, and wherein the generated context varies based on dates and times of the spare time blocks and the generated context indicates conditions of the user; listing spare time blocks when there is no schedule set by the user; applying the context estimation rule to the listed spare time blocks, thereby estimating contexts of the spare time blocks; storing a task template that represents tasks and subtasks associated with the tasks, the task template including respective metadata of the subtasks; inputting a task; dividing the task into the associated subtasks based on the task template; storing a task recommendation rule for recommending tasks to do in accordance with the relation between contexts and metadata of tasks; applying, by a computer processor, the task recommendation rule to the listed spare time blocks, and recommending tasks to do in the spare time blocks on the basis of the contexts of the spare time blocks and the metadata of the subtasks; and managing the recommended tasks as schedules. | 7. A schedule management method for managing user's schedules and tasks, comprising: storing a context estimation rule for use in estimation of contexts of spare time blocks, wherein the context estimation rule is used to generate a context by applying the context estimation rule to the spare time blocks and the context estimation rule generates contexts corresponding to schedule types before spare time blocks whose contexts are estimated, and wherein the generated context varies based on dates and times of the spare time blocks and the generated context indicates conditions of the user; listing spare time blocks when there is no schedule set by the user; applying the context estimation rule to the listed spare time blocks, thereby estimating contexts of the spare time blocks; storing a task template that represents tasks and subtasks associated with the tasks, the task template including respective metadata of the subtasks; inputting a task; dividing the task into the associated subtasks based on the task template; storing a task recommendation rule for recommending tasks to do in accordance with the relation between contexts and metadata of tasks; applying, by a computer processor, the task recommendation rule to the listed spare time blocks, and recommending tasks to do in the spare time blocks on the basis of the contexts of the spare time blocks and the metadata of the subtasks; and managing the recommended tasks as schedules. 13. A schedule management method according to claim 7 , wherein the context estimation rule generates a context of a spare time following a specific schedule, wherein the context has a specific duration of time. | 0.511574 |
9,530,411 | 8 | 10 | 8. A voice server that supports multiple modes for interacting with a multimodal device, the voice server comprising: a computer processor; a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions configured to: receive a media file having a metadata container; retrieve, from the metadata container, a speech prompt related to content stored in the media file for inclusion in a multimodal application, wherein the speech prompt is an audio phrase played by the multimodal application; modify the grammar of the speech engine to include at least one of the grammar rule and the pronunciation rule; retrieve a speech artifact having an XML, document; and modify the multimodal application to include the speech prompt. | 8. A voice server that supports multiple modes for interacting with a multimodal device, the voice server comprising: a computer processor; a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions configured to: receive a media file having a metadata container; retrieve, from the metadata container, a speech prompt related to content stored in the media file for inclusion in a multimodal application, wherein the speech prompt is an audio phrase played by the multimodal application; modify the grammar of the speech engine to include at least one of the grammar rule and the pronunciation rule; retrieve a speech artifact having an XML, document; and modify the multimodal application to include the speech prompt. 10. The voice server of claim 8 wherein computer program instructions configured to retrieve, from the metadata container, a speech prompt related to content stored in the media file for inclusion in the multimodal application further comprise computer program instructions configured to retrieve an audio prompt to be played by a multimodal device. | 0.51257 |
9,268,857 | 1 | 12 | 1. A method comprising, by one or more processors associated with a social-networking system of an online social network: receiving, from a client device of a user, an indication of the user accessing a search tool at the client device of the user, the indication being received before the user inputs any search query or portion thereof to the search tool, wherein the user is a member of the online social network; in response to receiving the indication of the user accessing the search tool, compiling for presentation to the user a set of search results based on information known about the user stored by the social-networking system, the search results being compiled before the user inputs any search query or portion thereof to the search tool, each search result being associated with one or more call-to-action elements applicable to the search result, each call-to-action element being a user-interface element that prompts an action from the user to initiate a particular function or process related to the search result via the social-networking system; and sending, to the client device of the user, the set of search results with the call-to-action elements for presentation to the user, wherein the call-to-action elements are presented to the user in proximity to their corresponding search results. | 1. A method comprising, by one or more processors associated with a social-networking system of an online social network: receiving, from a client device of a user, an indication of the user accessing a search tool at the client device of the user, the indication being received before the user inputs any search query or portion thereof to the search tool, wherein the user is a member of the online social network; in response to receiving the indication of the user accessing the search tool, compiling for presentation to the user a set of search results based on information known about the user stored by the social-networking system, the search results being compiled before the user inputs any search query or portion thereof to the search tool, each search result being associated with one or more call-to-action elements applicable to the search result, each call-to-action element being a user-interface element that prompts an action from the user to initiate a particular function or process related to the search result via the social-networking system; and sending, to the client device of the user, the set of search results with the call-to-action elements for presentation to the user, wherein the call-to-action elements are presented to the user in proximity to their corresponding search results. 12. The method of claim 1 , further comprising: accessing a graph data structure comprising a plurality of nodes and a plurality of edges connecting the nodes, wherein the user corresponds to a first node of the plurality of nodes, and wherein the one or more search results correspond to one or more second nodes, respectively, of the plurality of nodes. | 0.717806 |
10,133,755 | 18 | 19 | 18. A method for applying legal analytics, the method comprising: accessing a source of legal information; retrieving legal data from the source of legal information; performing word recognition on the legal data; automatically normalizing inaccuracies discovered in the legal data; after normalizing the legal data, receiving input from an administrator to input supplemental legal data that adds a legal outcome for which no metadata element has been previously generated and modify the legal data; identifying, based on any recognized words, references to various legal entities in the legal data; identifying portions of the legal data that include at least one reference; associating each of the portions with a metadata element corresponding to the at least one legal entity referenced in each portion; and constructing a database that includes the legal data and metadata elements, wherein the database is searchable by legal entity; allowing a user to specify search parameters that are used to identify a segment of the legal data; applying legal analytics to the segment of the legal data; and presenting analytic results to the user. | 18. A method for applying legal analytics, the method comprising: accessing a source of legal information; retrieving legal data from the source of legal information; performing word recognition on the legal data; automatically normalizing inaccuracies discovered in the legal data; after normalizing the legal data, receiving input from an administrator to input supplemental legal data that adds a legal outcome for which no metadata element has been previously generated and modify the legal data; identifying, based on any recognized words, references to various legal entities in the legal data; identifying portions of the legal data that include at least one reference; associating each of the portions with a metadata element corresponding to the at least one legal entity referenced in each portion; and constructing a database that includes the legal data and metadata elements, wherein the database is searchable by legal entity; allowing a user to specify search parameters that are used to identify a segment of the legal data; applying legal analytics to the segment of the legal data; and presenting analytic results to the user. 19. The method of claim 18 , wherein the analytic results are presented to the user via a graphical user interface. | 0.753219 |
7,603,626 | 1 | 6 | 1. A computer-assisted method for having a plurality of participants author and submit segment candidates to create a collaborative work over a computer network comprising the steps of receiving over the computer network segment candidates prepared by at least some of the plurality of participants, distributing at least a subset of the submitted segment candidates to a voting audience over the computer network, receiving from the audience votes for a favored segment candidate, selecting a winning segment candidate from the submitted segment candidates for inclusion in the collaborative work based on the votes, and repeating the steps of submitting segment candidates, voting on the submitted segment candidates, and selecting a winning segment candidate to complete the collaborative work, wherein a promo, which is only authored by the author of the submitted segment, and which constitutes a subset of the content of the submitted segment, is submitted with each submitted segment candidate, said promo being indicative of the content of the submitted segment candidate, wherein said promo is designed to generate interest amongst members of the voting audience to view the submitted segment in full, wherein said promo comprises an image or graphic, and a title, summary, and excerpt, and wherein participation in said voting audience is open to the general public. | 1. A computer-assisted method for having a plurality of participants author and submit segment candidates to create a collaborative work over a computer network comprising the steps of receiving over the computer network segment candidates prepared by at least some of the plurality of participants, distributing at least a subset of the submitted segment candidates to a voting audience over the computer network, receiving from the audience votes for a favored segment candidate, selecting a winning segment candidate from the submitted segment candidates for inclusion in the collaborative work based on the votes, and repeating the steps of submitting segment candidates, voting on the submitted segment candidates, and selecting a winning segment candidate to complete the collaborative work, wherein a promo, which is only authored by the author of the submitted segment, and which constitutes a subset of the content of the submitted segment, is submitted with each submitted segment candidate, said promo being indicative of the content of the submitted segment candidate, wherein said promo is designed to generate interest amongst members of the voting audience to view the submitted segment in full, wherein said promo comprises an image or graphic, and a title, summary, and excerpt, and wherein participation in said voting audience is open to the general public. 6. The method according to claim 1 , wherein votes are received from the audience in a round, wherein a round comprises a time period for receiving segment candidates and a time period for voting on the submitted segment candidates. | 0.701031 |
9,563,625 | 5 | 6 | 5. The method of claim 1 , wherein the list of alternative translation possibilities comprises alternative portions associated with machine translation portions. | 5. The method of claim 1 , wherein the list of alternative translation possibilities comprises alternative portions associated with machine translation portions. 6. The method of claim 5 , wherein the machine translation portions comprise one of a line of machine code and a cluster of machine code lines. | 0.5 |
7,711,672 | 10 | 12 | 10. The method of claim 1 , wherein the processor is embedded in a device having voice recognition capability. | 10. The method of claim 1 , wherein the processor is embedded in a device having voice recognition capability. 12. The method of claim 10 , wherein the device is a hand-held device. | 0.75 |
9,836,469 | 10 | 13 | 10. One or more non-transitory computer-readable media storing a plugin to a digital asset editing program which, when executed by a computing device having at least one processor and memory, causes the computing device to perform the steps of: allowing filtering of a library of digital assets by custom metadata associated with the digital assets; obtaining custom metadata filtering criteria; responsive to using a digital asset index stored at the computing device to determine that one or more of the digital assets are associated with custom metadata satisfying the custom metadata filtering criteria, allowing selection of at least one filtering result, corresponding to one of the one or more digital assets, which, when selected, causes the corresponding digital asset to at least be loaded into the digital asset editing program for editing; responsive to a selection of the at least one filtering result, causing the corresponding digital asset to at least be loaded into the digital asset editing program for editing; wherein the causing the corresponding digital asset to at least be loaded into the digital asset editing program for editing comprises invoking an application programming interface offered by the digital asset editing program; wherein the application programming interface allows the plugin to at least load a specified digital asset into the digital asset editing program for editing; receiving notification of a change to a file in a file system of the computing device, the file containing a digital asset in the library; reading the file for custom metadata embedded in the digital asset; and updating the digital asset index to index the digital asset by the custom metadata read from the file. | 10. One or more non-transitory computer-readable media storing a plugin to a digital asset editing program which, when executed by a computing device having at least one processor and memory, causes the computing device to perform the steps of: allowing filtering of a library of digital assets by custom metadata associated with the digital assets; obtaining custom metadata filtering criteria; responsive to using a digital asset index stored at the computing device to determine that one or more of the digital assets are associated with custom metadata satisfying the custom metadata filtering criteria, allowing selection of at least one filtering result, corresponding to one of the one or more digital assets, which, when selected, causes the corresponding digital asset to at least be loaded into the digital asset editing program for editing; responsive to a selection of the at least one filtering result, causing the corresponding digital asset to at least be loaded into the digital asset editing program for editing; wherein the causing the corresponding digital asset to at least be loaded into the digital asset editing program for editing comprises invoking an application programming interface offered by the digital asset editing program; wherein the application programming interface allows the plugin to at least load a specified digital asset into the digital asset editing program for editing; receiving notification of a change to a file in a file system of the computing device, the file containing a digital asset in the library; reading the file for custom metadata embedded in the digital asset; and updating the digital asset index to index the digital asset by the custom metadata read from the file. 13. The one or more non-transitory computer-readable media of claim 10 , wherein the plugin, when executed by the computing device, further causes the computing device to perform the step of causing the corresponding digital asset to be positioned on an editing canvas at a position specified by custom metadata associated with the corresponding digital asset. | 0.638554 |
9,460,164 | 13 | 15 | 13. A method for viewing documents with legal categories via a computer having instructions stored in memory, the method comprising: executing instructions stored in memory by a processor to: provide example documents representative of specified legal criteria defining a legal category; categorize documents based on the specified legal criteria exemplified by the example documents; assign confidence levels to legal categorizations of at least one of the categorized documents; assign template buttons to the categorized documents, the template buttons having a pre-populated coding schema; load categorized documents consistent with the legal category into a queue; transmit to display a categorized document from the queue; and in response to a single input action, accept one or more classifications associated with the legal category of the categorized document and with the single input action invoke a subsequent categorized document from the queue for viewing. | 13. A method for viewing documents with legal categories via a computer having instructions stored in memory, the method comprising: executing instructions stored in memory by a processor to: provide example documents representative of specified legal criteria defining a legal category; categorize documents based on the specified legal criteria exemplified by the example documents; assign confidence levels to legal categorizations of at least one of the categorized documents; assign template buttons to the categorized documents, the template buttons having a pre-populated coding schema; load categorized documents consistent with the legal category into a queue; transmit to display a categorized document from the queue; and in response to a single input action, accept one or more classifications associated with the legal category of the categorized document and with the single input action invoke a subsequent categorized document from the queue for viewing. 15. The method of claim 13 , further comprising displaying highlighted document text associated with the confidence levels. | 0.842711 |
8,027,989 | 1 | 12 | 1. A computer-implemented method for providing a computer user with information related to electronic content, the method comprising: receiving a first request for information corresponding to first electronic content being rendered to a user submitting the first request when the first request is submitted; deriving context information associated with the first request based on the first electronic content being rendered to the user when the first request is submitted; in response to deriving the context information, storing the context information; receiving a second request, at a time subsequent to the first request, for information corresponding to second electronic content; in response to receiving the second request, determining whether the stored context information is relevant to the second request; in response to a determination that the stored context information is relevant to the second request: accessing, from electronic storage, the stored context information derived based on the first electronic content rendered during the first request; and causing presentation, to a user submitting the second request, of the accessed context information derived based on the first electronic content rendered during the first request along with information satisfying the second request. | 1. A computer-implemented method for providing a computer user with information related to electronic content, the method comprising: receiving a first request for information corresponding to first electronic content being rendered to a user submitting the first request when the first request is submitted; deriving context information associated with the first request based on the first electronic content being rendered to the user when the first request is submitted; in response to deriving the context information, storing the context information; receiving a second request, at a time subsequent to the first request, for information corresponding to second electronic content; in response to receiving the second request, determining whether the stored context information is relevant to the second request; in response to a determination that the stored context information is relevant to the second request: accessing, from electronic storage, the stored context information derived based on the first electronic content rendered during the first request; and causing presentation, to a user submitting the second request, of the accessed context information derived based on the first electronic content rendered during the first request along with information satisfying the second request. 12. The computer-implemented method of claim 1 wherein causing presentation comprises providing, to a terminal, the accessed context information derived based on the first electronic content rendered during the first request along with information satisfying the second request to enable the terminal to present the accessed context information derived based on the first electronic content rendered during the first request along with information satisfying the second request. | 0.519115 |
7,610,199 | 29 | 30 | 29. The computer readable storage medium of claim 27 , wherein said first speech endpoint is a speech starting point represented by a first frame of said audio signal and said second speech endpoint is a speech ending point represented by a second frame of said audio signal, said second frame occurring subsequent to said first frame. | 29. The computer readable storage medium of claim 27 , wherein said first speech endpoint is a speech starting point represented by a first frame of said audio signal and said second speech endpoint is a speech ending point represented by a second frame of said audio signal, said second frame occurring subsequent to said first frame. 30. The computer readable storage medium of claim 29 , further comprising the step of: backing up a pre-defined number of frames to a third frame of said audio signal that precedes said first frame; and performing speech recognition processing on at least a portion of said audio signal located between said third speech endpoint and said second speech endpoint. | 0.635815 |
8,121,967 | 1 | 7 | 1. A method for classifying structural input data, the method comprising a computer system performing steps of: constructing multiple classifiers, wherein each classifier is constructed on a subset of training data, using selected composite features from the subset of training data, the composite features being selected by iteratively applying a feature selection step wherein multiple disjoint feature sets are identified to represent the structural input data in different feature spaces, and the structural input data, when characterized by a skewed prior class distribution, being subjected to a sampling step to obtain a balanced class distribution; and computing a consensus among the multiple classifiers in accordance with a voting scheme such that at least a portion of the structural input data is assigned to a particular class in accordance with the computed consensus; wherein the computer system comprises a memory and a processor device operatively coupled to the memory. | 1. A method for classifying structural input data, the method comprising a computer system performing steps of: constructing multiple classifiers, wherein each classifier is constructed on a subset of training data, using selected composite features from the subset of training data, the composite features being selected by iteratively applying a feature selection step wherein multiple disjoint feature sets are identified to represent the structural input data in different feature spaces, and the structural input data, when characterized by a skewed prior class distribution, being subjected to a sampling step to obtain a balanced class distribution; and computing a consensus among the multiple classifiers in accordance with a voting scheme such that at least a portion of the structural input data is assigned to a particular class in accordance with the computed consensus; wherein the computer system comprises a memory and a processor device operatively coupled to the memory. 7. The method of claim 1 , wherein the structural data comprises skewed structural data. | 0.719745 |
7,805,159 | 15 | 16 | 15. The mobile device of claim 1 , further comprising: a processing subsystem, a memory subsystem, and a communication subsystem, the processing subsystem coupled to the memory subsystem and communication subsystem and operable to store and retrieve data in the memory subsystem, to execute instructions stored in the memory subsystem, and to cause the communication subsystem to transmit and receive data over a communication network. | 15. The mobile device of claim 1 , further comprising: a processing subsystem, a memory subsystem, and a communication subsystem, the processing subsystem coupled to the memory subsystem and communication subsystem and operable to store and retrieve data in the memory subsystem, to execute instructions stored in the memory subsystem, and to cause the communication subsystem to transmit and receive data over a communication network. 16. The mobile device of claim 15 , further comprising: executable predictive text program code stored in the memory subsystem and comprising instructions operable to cause the mobile device to predict a complete word or phrase from one or more text-entry characters input to the mobile device when the mobile device is in text-entry mode. | 0.5 |
9,158,556 | 16 | 17 | 16. The system of claim 15 , wherein the operations further comprise: determining a difference between at least one characteristic of the one or more particular portal objects and at least one of the rules or the customizable constraints; and preparing a notification of the determined difference for display through the GUI. | 16. The system of claim 15 , wherein the operations further comprise: determining a difference between at least one characteristic of the one or more particular portal objects and at least one of the rules or the customizable constraints; and preparing a notification of the determined difference for display through the GUI. 17. The system of claim 16 , wherein the operations further comprise initiating a block of publication of the portal content to a web portal based on the identified difference. | 0.732523 |
8,989,216 | 7 | 8 | 7. The tangible non-transitory storage device of claim 2 , wherein said context can be a major release or a minor release of said 3GPP standard. | 7. The tangible non-transitory storage device of claim 2 , wherein said context can be a major release or a minor release of said 3GPP standard. 8. The tangible non-transitory storage device of claim 7 , wherein said minor release of said 3GPP standard may be identified by either a specific version number or release date. | 0.5 |
9,898,459 | 13 | 21 | 13. A system for integrating domain information and semantic parsing to generate meaning representations from natural language input, the system comprising: a computer system comprising one or more physical processors programmed with computer program instructions to: receive a natural language input of a user comprising a natural language utterance in which at least a first input token has been uttered; provide the natural language input to a speech-to-text recognizer; obtain one or more words of the natural language input as an output of the speech-to-text recognizer, wherein the one or more words includes the first input token; obtain a semantic grammar that includes word combinations for intent processing and integrates a plurality of domain tokens relating to an information domain, wherein the semantic grammar integrates the plurality of domain tokens structured into a domain information Finite State Transducer (FST) parser that includes at least a first FST path comprising a first set of domain tokens and a second FST path comprising a second set of domain tokens; compare the plurality of domain tokens with the first input token; and generate a first score for the first FST path and a second score for the second FST path based on the comparison; select the first FST path based on the first score and the second score; determine a semantic structure of the one or more words based on the selected first FST path; generate a representation of an intention of the user based on the semantic structure, wherein the representation is used to execute a natural language based search request or a natural language based command. | 13. A system for integrating domain information and semantic parsing to generate meaning representations from natural language input, the system comprising: a computer system comprising one or more physical processors programmed with computer program instructions to: receive a natural language input of a user comprising a natural language utterance in which at least a first input token has been uttered; provide the natural language input to a speech-to-text recognizer; obtain one or more words of the natural language input as an output of the speech-to-text recognizer, wherein the one or more words includes the first input token; obtain a semantic grammar that includes word combinations for intent processing and integrates a plurality of domain tokens relating to an information domain, wherein the semantic grammar integrates the plurality of domain tokens structured into a domain information Finite State Transducer (FST) parser that includes at least a first FST path comprising a first set of domain tokens and a second FST path comprising a second set of domain tokens; compare the plurality of domain tokens with the first input token; and generate a first score for the first FST path and a second score for the second FST path based on the comparison; select the first FST path based on the first score and the second score; determine a semantic structure of the one or more words based on the selected first FST path; generate a representation of an intention of the user based on the semantic structure, wherein the representation is used to execute a natural language based search request or a natural language based command. 21. The system of claim 13 , wherein the computer system is further programmed to: obtain one or more dynamic data tokens from a dynamic data source; and integrate the one or more dynamic data tokens with the plurality of tokens from the information domain, wherein the meaning representation is determined based on the integrated dynamic data tokens. | 0.559045 |
5,577,241 | 5 | 6 | 5. A computer implemented method of creating search queries for a database comprising a plurality of documents, the method comprising: storing in a computer readable medium a plurality of query node creators, each query node creator capable of creating a query node that executes a search query to identify a next document in the database as a function of a search query operator upon at least one data element; storing in the computer readable medium a plurality of search operators, each search operator associated with a selected query node creator; receiving an input search query having a search query operator and at least one data element associated therewith; identifying each search query operator and associated data element in the search query; and for each search query operator in the search query: identifying the query node creator associated with the search query operator in the computer readable medium; and invoking the associated query node creator to create query node for the search query operator and the associated data element. | 5. A computer implemented method of creating search queries for a database comprising a plurality of documents, the method comprising: storing in a computer readable medium a plurality of query node creators, each query node creator capable of creating a query node that executes a search query to identify a next document in the database as a function of a search query operator upon at least one data element; storing in the computer readable medium a plurality of search operators, each search operator associated with a selected query node creator; receiving an input search query having a search query operator and at least one data element associated therewith; identifying each search query operator and associated data element in the search query; and for each search query operator in the search query: identifying the query node creator associated with the search query operator in the computer readable medium; and invoking the associated query node creator to create query node for the search query operator and the associated data element. 6. The method of claim 5, further comprising the step of: creating a hierarchical ordering of the created query nodes. | 0.824926 |
7,725,330 | 18 | 19 | 18. The method of claim 1 , further comprising: (a) automatically assessing the quality of the patient information of the medical record using the extracted billing information to obtain quality assessment results; and (b) storing the quality assessment results for the medical record. | 18. The method of claim 1 , further comprising: (a) automatically assessing the quality of the patient information of the medical record using the extracted billing information to obtain quality assessment results; and (b) storing the quality assessment results for the medical record. 19. The method of claim 18 , further comprising performing steps (a) and (b) for a plurality of medical records in an electronic database; and automatically generating quality assurance statistics based on the quality assessment results obtained for the plurality of medical records. | 0.5 |
9,741,142 | 2 | 3 | 2. The method of claim 1 , further comprising: detecting user input of a second new character at a second location in the scanned document; determining that the second new character is not among the synthesized characters of the synthesized digital font; and based on the determination that the second new character is not among the synthesized characters of the synthesized digital font, creating a similar-looking character for the second new character. | 2. The method of claim 1 , further comprising: detecting user input of a second new character at a second location in the scanned document; determining that the second new character is not among the synthesized characters of the synthesized digital font; and based on the determination that the second new character is not among the synthesized characters of the synthesized digital font, creating a similar-looking character for the second new character. 3. The method of claim 2 , further comprising adding the similar-looking character to the editable version of the scanned document at the second location. | 0.874183 |
7,627,536 | 16 | 17 | 16. A storage medium, readable by a computing device and comprising executable instructions that are executable by the computing device, in which when the executable instructions are executed, cause the computing device to: receive inputs defining a virtual world described by a state that may be influenced by a user; receive inputs defining one or more computer-controlled characters; receive inputs defining one or more language representations; receive inputs associating one or more of the language representations with one or more states of the virtual world, and one or more of the language representations with knowledgebases of one or more of the computer-controlled characters; combine one or more of the language representations associated with one or more of the states of the virtual world with one or more of the language representations associated with the knowledgebase of one of the computer-controlled characters, in response to an initiation of a user interaction, to dynamically generate one or more dialog elements based on both the combined language representations and inputs from the user; and provide the dialog elements in computer-controlled character dialog elements via one or more output devices. | 16. A storage medium, readable by a computing device and comprising executable instructions that are executable by the computing device, in which when the executable instructions are executed, cause the computing device to: receive inputs defining a virtual world described by a state that may be influenced by a user; receive inputs defining one or more computer-controlled characters; receive inputs defining one or more language representations; receive inputs associating one or more of the language representations with one or more states of the virtual world, and one or more of the language representations with knowledgebases of one or more of the computer-controlled characters; combine one or more of the language representations associated with one or more of the states of the virtual world with one or more of the language representations associated with the knowledgebase of one of the computer-controlled characters, in response to an initiation of a user interaction, to dynamically generate one or more dialog elements based on both the combined language representations and inputs from the user; and provide the dialog elements in computer-controlled character dialog elements via one or more output devices. 17. The medium of claim 16 , in which when the executable instructions are executed, further cause the computing device to receive the input as natural language inputs, and to translate the natural language inputs into the abstract language representations. | 0.574503 |
9,158,839 | 1 | 2 | 1. A method comprising: receiving, by a processing device, a data set, wherein the data set is annotated with at least a first annotation and at least a second annotation, wherein at least the first annotation and the second annotation represent characteristics within the data set; determining, by the processing device, a first identifier from the first annotation and a second identifier from the second annotation; associating, by the processing device, the first identifier to the second identifier to generate at least one joined identifier, wherein the at least one joined identifier is placed between the first annotation and the second annotation; computing, by the processing device, a feature weight and a transition weight for the annotated data set based on the first annotation, the second annotation, and the at least one joined identifier and a transition between each of the first annotation, the second annotation and the at least one joined identifier; receiving, by the processing device, a second data set, wherein the second data set is un-annotated; and classifying, by the processing device, the second data set based on the computed feature weight and the transition weight from the first data set. | 1. A method comprising: receiving, by a processing device, a data set, wherein the data set is annotated with at least a first annotation and at least a second annotation, wherein at least the first annotation and the second annotation represent characteristics within the data set; determining, by the processing device, a first identifier from the first annotation and a second identifier from the second annotation; associating, by the processing device, the first identifier to the second identifier to generate at least one joined identifier, wherein the at least one joined identifier is placed between the first annotation and the second annotation; computing, by the processing device, a feature weight and a transition weight for the annotated data set based on the first annotation, the second annotation, and the at least one joined identifier and a transition between each of the first annotation, the second annotation and the at least one joined identifier; receiving, by the processing device, a second data set, wherein the second data set is un-annotated; and classifying, by the processing device, the second data set based on the computed feature weight and the transition weight from the first data set. 2. The method of claim 1 further comprising providing the classified second data set to a user. | 0.75641 |
6,167,377 | 8 | 9 | 8. The method of claim 7, further comprising selecting a candidate by evaluating the candidates using the combined language model results and acoustic information associated with the candidates. | 8. The method of claim 7, further comprising selecting a candidate by evaluating the candidates using the combined language model results and acoustic information associated with the candidates. 9. The method of claim 8, wherein the evaluating uses a vocabulary of words, and wherein building the topic language model further comprises: prompting a user to identify a source of text; retrieving text from the source of text identified by the user; scanning the retrieved text to identify words from the text that are not included in the vocabulary of words; displaying the identified words to the user; prompting the user to select words to be included in the vocabulary; and adding words selected by the user to the vocabulary. | 0.5 |
8,620,918 | 19 | 25 | 19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. | 19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. 25. The computer storage medium of claim 19 , wherein the analysis includes treating a particular text string as a feature with a reduced clustering weight if the particular text string has been identified to be processed differently. | 0.533865 |
8,317,613 | 16 | 24 | 16. A processor-implemented method for social interactive content development of a plurality of art assets for an interactive video game, comprising: determining proximity relationships amongst the plurality of art assets, each of the art assets being defined for display during execution of the interactive video game; monitoring access to the plurality of art assets; initiating a communication in response to triggering a predefined access threshold set for a specific art asset based on a proximity relationship of the specific art asset to a proximate art asset; wherein the method is executed by a processor. | 16. A processor-implemented method for social interactive content development of a plurality of art assets for an interactive video game, comprising: determining proximity relationships amongst the plurality of art assets, each of the art assets being defined for display during execution of the interactive video game; monitoring access to the plurality of art assets; initiating a communication in response to triggering a predefined access threshold set for a specific art asset based on a proximity relationship of the specific art asset to a proximate art asset; wherein the method is executed by a processor. 24. The method of claim 16 , further comprising presenting value data regarding one or more of the plurality of content assets, the value data defining a relative level of importance, wherein the value data includes metrics derived from one or more of development time, play time, test time, cost, and revenue. | 0.735495 |
9,086,736 | 7 | 9 | 7. A method executed by a data processing system coupled to a digital device of a user, the method comprising: receiving a sequence of keypresses indicative of a user-intended textual object; for each keypress received, generating a combination of vocabulary entries based on multiple keypress interpretation strategies, each vocabulary entry predictive of a potential user-intended textual object as interpreted by an associated keypress interpretation strategy, wherein the multiple keypress interpretation strategies include a one-keypress-per-letter interpretation strategy and a multi-tap interpretation strategy; and presenting the combination of vocabulary entries, the presenting including updating at least one vocabulary entry of the combination of vocabulary entries based on any subsequent keypress received subsequent to an initial presentation of the combination, wherein the presenting further includes varying associated numbers of presented vocabulary entries arising from the one-keypress-per-letter interpretation strategy and the multi-tap interpretation strategy according to a user submitted ratio. | 7. A method executed by a data processing system coupled to a digital device of a user, the method comprising: receiving a sequence of keypresses indicative of a user-intended textual object; for each keypress received, generating a combination of vocabulary entries based on multiple keypress interpretation strategies, each vocabulary entry predictive of a potential user-intended textual object as interpreted by an associated keypress interpretation strategy, wherein the multiple keypress interpretation strategies include a one-keypress-per-letter interpretation strategy and a multi-tap interpretation strategy; and presenting the combination of vocabulary entries, the presenting including updating at least one vocabulary entry of the combination of vocabulary entries based on any subsequent keypress received subsequent to an initial presentation of the combination, wherein the presenting further includes varying associated numbers of presented vocabulary entries arising from the one-keypress-per-letter interpretation strategy and the multi-tap interpretation strategy according to a user submitted ratio. 9. The method of claim 7 , wherein the combination of vocabulary entries is selected from vocabulary entries arising from the multiple keypress interpretation strategies based on at least one of: frequency, recency of use, or context. | 0.7 |
7,613,953 | 20 | 21 | 20. The method as recited in claim 19 further comprising designating said command as a global command. | 20. The method as recited in claim 19 further comprising designating said command as a global command. 21. The method as recited in claim 20 further comprising reloading said command for making said command available in a public library. | 0.5 |
7,562,286 | 35 | 41 | 35. A computer program product embodied in a computer readable medium and directly loadable into an internal memory of a computer, comprising computer program instructions which when executed by the computer performs a document managing operation of designating a desired document in a series of documents managed under a Document Management Alliance document object model and making a connection to a desired node in a hierarchical tree-structure of the desired document, the document managing operation comprising the steps of: accepting a document call request for the desired document, that is made by a client apparatus by presenting a document ID including two character strings in the form of one of a URL syntax or a sentence construction, the first character string being a route node designating the document object and the second character string specifying at least one of a version, a rendition, or a content of the document object; separating said document ID into character strings for identifying at least one of said version, said rendition or said content of the document object; executing operations in accordance with said character strings separated by said separating step; providing a default value for at least one of said version, said rendition or said content of the document object; making connections to nodes in the hierarchical tree-structure of the desired document, that are designated by the document ID, sequentially from an upper level one to a lower level one; and returning, when a connection to the desired node specified by the document ID has been made in the connections making step, prescribed information related to the desired node. | 35. A computer program product embodied in a computer readable medium and directly loadable into an internal memory of a computer, comprising computer program instructions which when executed by the computer performs a document managing operation of designating a desired document in a series of documents managed under a Document Management Alliance document object model and making a connection to a desired node in a hierarchical tree-structure of the desired document, the document managing operation comprising the steps of: accepting a document call request for the desired document, that is made by a client apparatus by presenting a document ID including two character strings in the form of one of a URL syntax or a sentence construction, the first character string being a route node designating the document object and the second character string specifying at least one of a version, a rendition, or a content of the document object; separating said document ID into character strings for identifying at least one of said version, said rendition or said content of the document object; executing operations in accordance with said character strings separated by said separating step; providing a default value for at least one of said version, said rendition or said content of the document object; making connections to nodes in the hierarchical tree-structure of the desired document, that are designated by the document ID, sequentially from an upper level one to a lower level one; and returning, when a connection to the desired node specified by the document ID has been made in the connections making step, prescribed information related to the desired node. 41. The computer program product according to claim 35 , wherein in the connections making step, a connection to a primary rendition at a lower level of a version of the desired document, that is designated by the document ID, is made when the document ID accepted in the document call request accepting step omits designation of a rendition in the hierarchical tree-structure of the desired document. | 0.601392 |
9,652,541 | 5 | 16 | 5. A computer-implemented method of refining a search query, comprising: receiving a search request from a client device, the search request including at least a first query term and at least a first search refinement value; providing a first set of search results corresponding to the first query term and the first search refinement value to be displayed on the client device; providing an editable search refinement specification including a plurality of editable elements to be displayed along with the first set of search results, the plurality of editable elements including at least a first editable element corresponding to the first query term and at least a second editable element corresponding to the first search refinement value, each of the plurality of editable elements being associated with text and a respective text input box element, each of the plurality of editable elements enabling a user to adjust the text of at least one editable element of the plurality of editable elements of the editable search refinement specification via the respective text input box element while maintaining the text of at least one other editable element of the plurality of editable elements of the editable search refinement specification; providing a displayable option element utilized to modify a currently selected editable element of the plurality of editable elements and to be displayed along with the plurality of editable elements, the displayable option element including two or more of a set of selectable operation icons including an edit operation icon, a remove operation icon, an undo operation icon, a save operation icon, a share operation icon, an auto-complete operation icon, a help operation icon, and a suggestion operation icon; receiving a submission including at least a second query term and at least a second search refinement value taken from the editable search refinement specification after adjustment of the text of at least one editable element of the editable search refinement specification via the respective text input box element; and providing a second set of search results matching the second query term and the second search refinement value in the editable search refinement specification after the adjustment to be displayed on the client device. | 5. A computer-implemented method of refining a search query, comprising: receiving a search request from a client device, the search request including at least a first query term and at least a first search refinement value; providing a first set of search results corresponding to the first query term and the first search refinement value to be displayed on the client device; providing an editable search refinement specification including a plurality of editable elements to be displayed along with the first set of search results, the plurality of editable elements including at least a first editable element corresponding to the first query term and at least a second editable element corresponding to the first search refinement value, each of the plurality of editable elements being associated with text and a respective text input box element, each of the plurality of editable elements enabling a user to adjust the text of at least one editable element of the plurality of editable elements of the editable search refinement specification via the respective text input box element while maintaining the text of at least one other editable element of the plurality of editable elements of the editable search refinement specification; providing a displayable option element utilized to modify a currently selected editable element of the plurality of editable elements and to be displayed along with the plurality of editable elements, the displayable option element including two or more of a set of selectable operation icons including an edit operation icon, a remove operation icon, an undo operation icon, a save operation icon, a share operation icon, an auto-complete operation icon, a help operation icon, and a suggestion operation icon; receiving a submission including at least a second query term and at least a second search refinement value taken from the editable search refinement specification after adjustment of the text of at least one editable element of the editable search refinement specification via the respective text input box element; and providing a second set of search results matching the second query term and the second search refinement value in the editable search refinement specification after the adjustment to be displayed on the client device. 16. The computer-implemented method of claim 5 , further comprising: in response to the adjustment of the text of the at least one editable element of the editable search refinement specification and before providing for display the second set of search results, automatically modifying at least another editable element of the editable search refinement specification based at least in part upon an aspect of the adjustment. | 0.5 |
8,996,357 | 3 | 4 | 3. The computer-readable, non-transitory medium according to claim 2 , wherein the displaying displays two or more diagrams of different kinds by determining which kind of diagram is relevant to which relationship link dataset, according to the types of relationships represented by relationship links derived from the relationship datasets, and including the relationship links, together with graphical symbols connected by the relationship links, in the diagram that is determined to be relevant. | 3. The computer-readable, non-transitory medium according to claim 2 , wherein the displaying displays two or more diagrams of different kinds by determining which kind of diagram is relevant to which relationship link dataset, according to the types of relationships represented by relationship links derived from the relationship datasets, and including the relationship links, together with graphical symbols connected by the relationship links, in the diagram that is determined to be relevant. 4. The computer-readable, non-transitory medium according to claim 3 , wherein the displaying of two or more diagrams includes: including the relationship links, together with graphical symbols connected by the relationship links, in an activity diagram when the relationship links represent relationships between activities; and including the relationship links, together with graphical symbols connected by the relationship links, in a class diagram when the relationship links represent relationships between classes to be used. | 0.5 |
8,302,010 | 1 | 6 | 1. In a computer-based system, a method of editing a time-based media program that includes recorded speech, the method comprising: receiving an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, editing the transcript text of the augmented transcript, wherein the editing comprises reordering the transcript text by moving a selected span of the transcript text from a first position within the transcript text to a second position within the transcript text, wherein the association of the tinting information with each of the plurality of words within the transcript is preserved during the editing, and wherein the editing of the augmented transcript does not involve playback of the time-based media; and outputting the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a reordered temporal sequence that corresponds to the reordered transcript text of the edited augmented transcript. | 1. In a computer-based system, a method of editing a time-based media program that includes recorded speech, the method comprising: receiving an augmented transcript of the recorded speech in a mark-up language format, wherein the augmented transcript includes text of a transcript of the recorded speech and timing information that, for each of a plurality of words of the text within the transcript, associates that text word with a temporal location of recorded speech within the time-based media program that corresponds to that text word; in a user interface displaying a transcript text view of the augmented transcript, editing the transcript text of the augmented transcript, wherein the editing comprises reordering the transcript text by moving a selected span of the transcript text from a first position within the transcript text to a second position within the transcript text, wherein the association of the tinting information with each of the plurality of words within the transcript is preserved during the editing, and wherein the editing of the augmented transcript does not involve playback of the time-based media; and outputting the edited augmented transcript, wherein the edited augmented transcript, when received and processed by a time-based media editing system, is capable of causing the time-based media editing system to generate an edited version of the time-based media program that includes time-based media in a reordered temporal sequence that corresponds to the reordered transcript text of the edited augmented transcript. 6. The method of claim 1 , wherein the time-based media program is not accessible by the computer-based system during the editing step. | 0.782958 |
8,014,591 | 3 | 4 | 3. A pattern recognition method as in claim 1 , further comprising: obtaining a set of training data for training said classifier module; obtaining a particular training sample for said classifier module and an associated label for said training sample; creating a first model for said classifier module by training said classifier module on said set of training data not including said particular training sample; creating a second model for said classifier module by training said classifier module on said set of training data including said particular training sample; creating said linkage of said plurality of models in which said plurality of models includes at least said first model and said second model. | 3. A pattern recognition method as in claim 1 , further comprising: obtaining a set of training data for training said classifier module; obtaining a particular training sample for said classifier module and an associated label for said training sample; creating a first model for said classifier module by training said classifier module on said set of training data not including said particular training sample; creating a second model for said classifier module by training said classifier module on said set of training data including said particular training sample; creating said linkage of said plurality of models in which said plurality of models includes at least said first model and said second model. 4. A pattern recognition method as in claim 3 , further comprising: annotating said particular training sample with the information obtained from said accumulating of evidence to accept or reject said null hypothesis. | 0.5 |
7,849,144 | 24 | 25 | 24. The medium of claim 23 , further comprising instructions for detecting a presence of each of the sending party and the destination party for transfer of instant messages based on a corresponding registration with the server, the determining including determining the language preference for the destination party in response to detecting the corresponding presence. | 24. The medium of claim 23 , further comprising instructions for detecting a presence of each of the sending party and the destination party for transfer of instant messages based on a corresponding registration with the server, the determining including determining the language preference for the destination party in response to detecting the corresponding presence. 25. The medium of claim 24 , further comprising instructions for detecting that the instant message is expressed in the first language based on determining the corresponding language preference for the sending party specifies the first language, the translating based on a determined difference between the language preference for the sending party in the language preference for the destination party. | 0.5 |
9,223,529 | 10 | 11 | 10. The apparatus of claim 9 , wherein the at least one job specific resource comprises at least one of a printer type, an available printer and a printer's output format. | 10. The apparatus of claim 9 , wherein the at least one job specific resource comprises at least one of a printer type, an available printer and a printer's output format. 11. The apparatus of claim 10 , wherein the printer type comprises a laser printer, a color printer, an ink jet printer, or a color laser printer. | 0.699588 |
8,806,304 | 15 | 17 | 15. A device comprising: one or more components to: receive a word, of a block of words within traffic, on which to perform forward error correction, each word of the block of words including respective encoded bits and respective sets of reliability bits for identifying a respective level of reliability of each one of the respective encoded bits, identify, within the word, least reliable positions that correspond to a subset of encoded bits associated with one or more lowest levels of reliability, generate a set of candidate words based on different combinations in which the subset of encoded bits can be inverted, identify a first pair of words of the set of candidate words, the first pair including a first candidate word and a second candidate word, the first candidate word including a most reliable bit, of the subset of encoded bits associated with the first candidate word, that is not inverted, identify a quantity of errors associated with the first candidate word, determine whether the quantity of errors corresponds to an odd value, invert a parity bit associated with the first candidate word when the quantity of errors corresponds to the odd value, select the second candidate word when the parity bit, associated with the first candidate word is inverted, and perform forward error correction, on the word using the second candidate word based on selection of the second candidate word. | 15. A device comprising: one or more components to: receive a word, of a block of words within traffic, on which to perform forward error correction, each word of the block of words including respective encoded bits and respective sets of reliability bits for identifying a respective level of reliability of each one of the respective encoded bits, identify, within the word, least reliable positions that correspond to a subset of encoded bits associated with one or more lowest levels of reliability, generate a set of candidate words based on different combinations in which the subset of encoded bits can be inverted, identify a first pair of words of the set of candidate words, the first pair including a first candidate word and a second candidate word, the first candidate word including a most reliable bit, of the subset of encoded bits associated with the first candidate word, that is not inverted, identify a quantity of errors associated with the first candidate word, determine whether the quantity of errors corresponds to an odd value, invert a parity bit associated with the first candidate word when the quantity of errors corresponds to the odd value, select the second candidate word when the parity bit, associated with the first candidate word is inverted, and perform forward error correction, on the word using the second candidate word based on selection of the second candidate word. 17. The device of claim 15 , where the one or more components are further to: determine a quantity of errors associated with the second candidate word, discard the second candidate word based on a determination that the quantity of errors, associated with the second candidate word, is greater than a threshold, and perform forward error correction on the word, using the first candidate word, when the second candidate word is discarded. | 0.682148 |
10,140,333 | 1 | 11 | 1. A method for performing queries on a search engine, based on input from a user, the method comprising: retrieving database entries from one or more relational databases; flattening the one or more relational databases with a plurality of the database entries; indexing the plurality of flattened database entries to form a full-text search engine index; prompting the user to enter an input; continuously monitoring the user input; each time an input is entered by the user, processing the user input by: computing a set of non-null partial queries in response to the input entered by the user, the non-null partial queries each being both valid on the one or more relational databases and having matching, instantiated records on the one or more relational databases thereby always resulting in non-null responses; associating a structured item to each non-null partial query; allowing the user to select one of the structured items; if the user selects one of the structured items, replacing the user input by the nonnull partial query associated to the selected structured item; when the user validates the input, executing the input as a query; and providing documents to the user corresponding to the executed query. | 1. A method for performing queries on a search engine, based on input from a user, the method comprising: retrieving database entries from one or more relational databases; flattening the one or more relational databases with a plurality of the database entries; indexing the plurality of flattened database entries to form a full-text search engine index; prompting the user to enter an input; continuously monitoring the user input; each time an input is entered by the user, processing the user input by: computing a set of non-null partial queries in response to the input entered by the user, the non-null partial queries each being both valid on the one or more relational databases and having matching, instantiated records on the one or more relational databases thereby always resulting in non-null responses; associating a structured item to each non-null partial query; allowing the user to select one of the structured items; if the user selects one of the structured items, replacing the user input by the nonnull partial query associated to the selected structured item; when the user validates the input, executing the input as a query; and providing documents to the user corresponding to the executed query. 11. The method according to claim 1 , wherein computing a set of non-null partial queries in response to the input entered by the user includes auto-completion suggestions. | 0.765027 |
7,607,018 | 2 | 7 | 2. The method of collecting and authenticating electronic signatures and documents recited in claim 1 further comprising the step of storing a representation of a third handwritten signature and an associated third authenticated electronic signature of a third signatory in said database. | 2. The method of collecting and authenticating electronic signatures and documents recited in claim 1 further comprising the step of storing a representation of a third handwritten signature and an associated third authenticated electronic signature of a third signatory in said database. 7. The method of collecting and authenticating electronic signatures and documents recited in claim 2 wherein said third electronic signature is biometrically authenticated. | 0.847979 |
7,529,676 | 2 | 5 | 2. The audio device control device according to claim 1 , further comprising: environmental information acquisition means which acquires environmental data indicating environmental circumstances in which an external audio device is employed; and wherein the audio device control means specifies music reproduced by the audio device based on the environmental data acquired by the environmental information acquisition means. | 2. The audio device control device according to claim 1 , further comprising: environmental information acquisition means which acquires environmental data indicating environmental circumstances in which an external audio device is employed; and wherein the audio device control means specifies music reproduced by the audio device based on the environmental data acquired by the environmental information acquisition means. 5. The audio device control device according to claim 2 , further comprising: time acquisition means for acquiring the current time; and wherein the music discrimination information storing means stores discrimination information for discrimination the music and time characteristics with corresponding to with respect to one another; and the audio device control means acquires the environmental data indicating time characteristics including the current time, and specifies music indicated by specification information corresponding to the acquired time characteristics as music reproduced by the audio device. | 0.599476 |
9,251,221 | 1 | 17 | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. 17. The method of claim 1 , further comprising: causing display of object scores for a plurality of objects in a descending order of score. | 0.892581 |
8,161,369 | 7 | 8 | 7. The computer-implemented method of claim 1 , further comprising selecting the reference. | 7. The computer-implemented method of claim 1 , further comprising selecting the reference. 8. The computer-implemented method of claim 7 , wherein upon selecting the reference, the interpreter visually formats the relevant multimedia portion and displays the visually formatted multimedia portion within the presenter module. | 0.5 |
9,684,718 | 1 | 4 | 1. A system for searching for a web document, comprising: a central processing unit (CPU) circuit; a receiver executed by the CPU circuit and configured to receive a user's search request; a search engine configured to search for a web document related to the search request based on a web document index, and to determine a move path for accessing the web document based on a move path index of the web document; a sender configured to send the move path for accessing the web document to the user; a web browser configured to display the web document and the move path for accessing the web document; and a web document obtainer configured to obtain the web document by simulating clicking of the web browser based on the move path. | 1. A system for searching for a web document, comprising: a central processing unit (CPU) circuit; a receiver executed by the CPU circuit and configured to receive a user's search request; a search engine configured to search for a web document related to the search request based on a web document index, and to determine a move path for accessing the web document based on a move path index of the web document; a sender configured to send the move path for accessing the web document to the user; a web browser configured to display the web document and the move path for accessing the web document; and a web document obtainer configured to obtain the web document by simulating clicking of the web browser based on the move path. 4. The system of claim 1 , further comprising: a move path obtainer configured to obtain the move path for accessing the web document; and a move path index creator configured to create the move path index of the web document. | 0.710997 |
4,096,934 | 16 | 19 | 16. A method for selecting and printing desired ideographs from a list of available ideographs comprising coding the available ideographs by at least a portion of the phonetic spelling of their commonly used names, coding the available ideographs by a descriptive characteristic of each available ideograph, storing the codes as coded information representing the available ideographs, inputing information representing at least a portion of the phonetic spelling of a desired ideograph, inputing information representing the descriptive characteristic of the desired ideograph, comparing the inputed information representing the phonetic spelling and descriptive characteristic of the desired ideograph with the stored coded information of the available ideographs, selecting the desired ideograph based on the stored coded information and the input information and visually reproducing the selected indeograph thereby permitting the use of a conventional keyboard by a person without special training to uniquely identify and print each desired ideograph. | 16. A method for selecting and printing desired ideographs from a list of available ideographs comprising coding the available ideographs by at least a portion of the phonetic spelling of their commonly used names, coding the available ideographs by a descriptive characteristic of each available ideograph, storing the codes as coded information representing the available ideographs, inputing information representing at least a portion of the phonetic spelling of a desired ideograph, inputing information representing the descriptive characteristic of the desired ideograph, comparing the inputed information representing the phonetic spelling and descriptive characteristic of the desired ideograph with the stored coded information of the available ideographs, selecting the desired ideograph based on the stored coded information and the input information and visually reproducing the selected indeograph thereby permitting the use of a conventional keyboard by a person without special training to uniquely identify and print each desired ideograph. 19. The method of claim 16 wherein the descriptive characteristic includes the names of parts of the ideographs. | 0.861728 |
8,744,847 | 35 | 36 | 35. The method of claim 33 , wherein the phone categories include individual phones. | 35. The method of claim 33 , wherein the phone categories include individual phones. 36. The method of claim 35 , wherein the individual phones include the AA phone and the AE phone. | 0.5 |
7,908,234 | 16 | 28 | 16. A non-transitory computer-readable medium storing computer-executable program code comprising code to configure at least one processor to: train a usefulness prediction model to generate a usefulness prediction in connection with a given universal resource locator (URL), the training of the usefulness prediction model comprising: inputting a training set of URLs, determining the quantity of negative URLs and positive URLs identified by the training set, extracting one or more features from the URLs in the training set, counting the number of times each feature occurs in said positive URLs, counting the number of times each feature occurs in said negative URLs, and using the quantities of positive and negative URLs, the number of times the features occurred in said positive and negative URLs, the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL. | 16. A non-transitory computer-readable medium storing computer-executable program code comprising code to configure at least one processor to: train a usefulness prediction model to generate a usefulness prediction in connection with a given universal resource locator (URL), the training of the usefulness prediction model comprising: inputting a training set of URLs, determining the quantity of negative URLs and positive URLs identified by the training set, extracting one or more features from the URLs in the training set, counting the number of times each feature occurs in said positive URLs, counting the number of times each feature occurs in said negative URLs, and using the quantities of positive and negative URLs, the number of times the features occurred in said positive and negative URLs, the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL. 28. The computer-readable medium of claim 16 , the given URL being a part of a set of search results, the program code further comprising program code to configure the one or more processors to: request the usefulness prediction in connection with the given URL; determine whether or not to remove the given URL from the set of search results using the usefulness prediction generated in connection with the given URL. | 0.75977 |
8,285,542 | 10 | 16 | 10. A system for generating a language model used to estimate a desired directory assistance listing based on a listing request input, the system comprising: a processor: a corpus of directory assistance listings; and a language model generation component configured to: access the corpus of directory assistance listings; for each word in each listing in the corpus, determine, based on one or more characteristics of the word in the listing, whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word; generate language model counts attributable to the word using the processor, wherein the language model counts are generated based on whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word, and based on a characteristic indicative of how well the word operates to distinguish the listing that contains the word from other listings in the corpus; and store the language model with the language model counts. | 10. A system for generating a language model used to estimate a desired directory assistance listing based on a listing request input, the system comprising: a processor: a corpus of directory assistance listings; and a language model generation component configured to: access the corpus of directory assistance listings; for each word in each listing in the corpus, determine, based on one or more characteristics of the word in the listing, whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word; generate language model counts attributable to the word using the processor, wherein the language model counts are generated based on whether the word is likely to be omitted from the listing request input when the desired directory assistance listing is a listing that contains the word, and based on a characteristic indicative of how well the word operates to distinguish the listing that contains the word from other listings in the corpus; and store the language model with the language model counts. 16. The system of claim 10 , wherein the corpus of directory assistance listings is divided into categories, and the one or more characteristics comprise an importance measure based on a frequency of occurrence of the word in the category to which the listing, that contains the word, belongs. | 0.596419 |
8,289,281 | 6 | 9 | 6. A method of controlling a portable computer which operates by an operating system (OS) corresponding to a predetermined language, the method comprising: automatically identifying the predetermined language of the currently operating OS; assigning an input key value to each of a plurality of input keys, each input key having at least one character printed thereon to input the printed character, by referring to a key array corresponding to the identified predetermined language of the currently operating OS; assigning a non-alphanumeric function to at least one of the input keys having the printed character in response to determining the predetermined language of the currently operating OS is change to a different language; and operating the portable computer according to the non-alphanumeric function assigned to the changed input key value of a selected input key. | 6. A method of controlling a portable computer which operates by an operating system (OS) corresponding to a predetermined language, the method comprising: automatically identifying the predetermined language of the currently operating OS; assigning an input key value to each of a plurality of input keys, each input key having at least one character printed thereon to input the printed character, by referring to a key array corresponding to the identified predetermined language of the currently operating OS; assigning a non-alphanumeric function to at least one of the input keys having the printed character in response to determining the predetermined language of the currently operating OS is change to a different language; and operating the portable computer according to the non-alphanumeric function assigned to the changed input key value of a selected input key. 9. The method of claim 6 , further comprising: generating a message to notify a user of the portable computer that the predetermined language to which the OS operates has a plurality of characters different than characters printed on the input keys. | 0.5 |
9,104,700 | 1 | 4 | 1. A computer-implemented method for searching for information, comprising: under control of one or more computer systems configured with executable instructions, receiving a request to perform a search based at least in part on an image captured by a digital camera of a mobile device, the request including the image; determining that at least one portion of the image includes text information; analyzing the at least one portion of the image to recognize one or more words in the text information; searching one or more databases to identify one or more products related to the one or more words, the one or more databases selected based at least in part by: performing an N-gram match between the text information and field entries in the one or more databases; and providing pricing information relating to at least a selected portion of the one or more products to the user in response to the request. | 1. A computer-implemented method for searching for information, comprising: under control of one or more computer systems configured with executable instructions, receiving a request to perform a search based at least in part on an image captured by a digital camera of a mobile device, the request including the image; determining that at least one portion of the image includes text information; analyzing the at least one portion of the image to recognize one or more words in the text information; searching one or more databases to identify one or more products related to the one or more words, the one or more databases selected based at least in part by: performing an N-gram match between the text information and field entries in the one or more databases; and providing pricing information relating to at least a selected portion of the one or more products to the user in response to the request. 4. The computer-implemented method of claim 1 , further comprising processing the at least one portion of the image to improve a quality of the at least one portion. | 0.7 |
8,307,073 | 11 | 12 | 11. The method of claim 1 , further comprising sanitizing the URL before processing the URL in order to exclude at least one character from processing. | 11. The method of claim 1 , further comprising sanitizing the URL before processing the URL in order to exclude at least one character from processing. 12. The method of claim 11 , wherein sanitizing the URL comprises removing “<” or “>” characters in the URL. | 0.5 |
8,756,561 | 1 | 7 | 1. A method of configuring a general purpose computer comprising: deriving a meta-model, the meta-model being independent of a particular software application, the derivation comprising identifying a subset of common structures and functions from a plurality of enterprise resource planning applications; deriving a plurality of software models from a specific enterprise resource planning application by executing at least one query on a repository associated with the specific enterprise resource planning application, wherein each of the plurality of software models is compliant with the meta-model by sharing the subset of common structures and functions; and deriving a customer specific software application from the specific enterprise resource planning application and the plurality of software models to enable interacting with the specific enterprise resource planning application using the plurality of software models. | 1. A method of configuring a general purpose computer comprising: deriving a meta-model, the meta-model being independent of a particular software application, the derivation comprising identifying a subset of common structures and functions from a plurality of enterprise resource planning applications; deriving a plurality of software models from a specific enterprise resource planning application by executing at least one query on a repository associated with the specific enterprise resource planning application, wherein each of the plurality of software models is compliant with the meta-model by sharing the subset of common structures and functions; and deriving a customer specific software application from the specific enterprise resource planning application and the plurality of software models to enable interacting with the specific enterprise resource planning application using the plurality of software models. 7. The method of claim 1 , wherein at least one of the plurality of software models is selected from a group consisting of: a binding model, a Structured Query Language (SQL) model, an object model, and an application model. | 0.697297 |
8,407,580 | 17 | 21 | 17. A method for presenting information, the method comprising the acts of: presenting an input cell on a workspace associated with a computational software application, the input cell including an input expression; presenting on the workspace an output cell including a result that is an evaluation of the input expression by the computational software application, while presenting on the workspace the input cell; presenting on the workspace a first user interface mechanism associated with the input cell, while presenting on the workspace the output cell; hiding on the workspace the input cell, while presenting on the workspace the output cell, in response to an activation of the first user interface mechanism, wherein hiding the input cell reduces the size of the workspace as compared to when both the input cell and the output cell are presented on the workspace; presenting on the workspace a second user interface mechanism associated with the input cell; and presenting on the workspace the input cell in response to an activation of the second user interface mechanism, while presenting on the workspace the output cell. | 17. A method for presenting information, the method comprising the acts of: presenting an input cell on a workspace associated with a computational software application, the input cell including an input expression; presenting on the workspace an output cell including a result that is an evaluation of the input expression by the computational software application, while presenting on the workspace the input cell; presenting on the workspace a first user interface mechanism associated with the input cell, while presenting on the workspace the output cell; hiding on the workspace the input cell, while presenting on the workspace the output cell, in response to an activation of the first user interface mechanism, wherein hiding the input cell reduces the size of the workspace as compared to when both the input cell and the output cell are presented on the workspace; presenting on the workspace a second user interface mechanism associated with the input cell; and presenting on the workspace the input cell in response to an activation of the second user interface mechanism, while presenting on the workspace the output cell. 21. The method according to claim 17 , wherein the first user interface mechanism and the second user interface mechanism are a first state and a second state, respectively, of a single user interface mechanism; wherein the method further comprises: changing the state of the single user interface mechanism from the first state to the second state in response to the activation of the first user interface mechanism; changing the state of the single user interface mechanism from the second state to the first state in response to the activation of the second user interface mechanism. | 0.5 |
9,977,920 | 1 | 16 | 1. A method for providing data privacy in a computer network, the method comprising: performing, by a security inference control processor of a network device in the computer network, operations comprising: receiving a query from a user device that is associated with a user through a network interface circuit; generating, in response to the query, a query result data set based on information in a database stored in a memory comprising a non-volatile data storage device; determining a Personally Identifiable Information (PII) exposure risk associated with the query result data by: evaluating a combination of the query result data set with an exposure storage log comprising query result data sets from past queries associated with the use; determining an exposure type of the query result data set, wherein the exposure type comprises one of exposure complete type, exposure element type, or exposure unprotected type, wherein the exposure complete type indicates protected information, wherein the exposure element type indicates information that is protected when considered collectively with other information, and wherein the exposure unprotected type indicates unprotected information; and determining the PII exposure risk based on the exposure type; and selectively providing, based on the PII exposure risk, the query result data set to the user in response to the query, so as to refrain from providing the query result data set if the PII exposure risk is greater than a risk threshold. | 1. A method for providing data privacy in a computer network, the method comprising: performing, by a security inference control processor of a network device in the computer network, operations comprising: receiving a query from a user device that is associated with a user through a network interface circuit; generating, in response to the query, a query result data set based on information in a database stored in a memory comprising a non-volatile data storage device; determining a Personally Identifiable Information (PII) exposure risk associated with the query result data by: evaluating a combination of the query result data set with an exposure storage log comprising query result data sets from past queries associated with the use; determining an exposure type of the query result data set, wherein the exposure type comprises one of exposure complete type, exposure element type, or exposure unprotected type, wherein the exposure complete type indicates protected information, wherein the exposure element type indicates information that is protected when considered collectively with other information, and wherein the exposure unprotected type indicates unprotected information; and determining the PII exposure risk based on the exposure type; and selectively providing, based on the PII exposure risk, the query result data set to the user in response to the query, so as to refrain from providing the query result data set if the PII exposure risk is greater than a risk threshold. 16. The method of claim 1 , wherein the database comprises an immutable database comprising data in the immutable database that is marked as deleted, wherein the selectively providing the query result data set to the user comprises: determining that the query result data set includes at least one data element that is marked as deleted in the immutable database; and selectively providing the query result data set to the user if the user is authorized to access the at least one data element that is marked as deleted in the immutable database and based on the PII exposure risk. | 0.59931 |
8,799,512 | 1 | 6 | 1. A system for providing cross-platform support for a variety of media types, the system comprising: a plurality of servers, including at least one server providing content of one or more different media types and at least one server providing one or more services, the plurality of servers comprising an Internet Protocol television (“IPTV”) server and a billing server; a plurality of managers, each manager communicatively coupled with one or more of the servers and translating content or services of the servers with which the manager is connected from the media types of the servers to one or more of a plurality of common language messages each of the plurality of common language messages related to one of the services of one of the servers with which the manager is connected; a communications bus communicatively coupled with each of the managers and receiving and transporting the one or more common language messages from the managers; and a plurality of end devices of different types, each end device communicatively coupled with the bus and receiving and translating the common language messages to a format specific to the end device based on the type; and a system audit tool communicatively coupled with the bus and monitoring common language messages on the bus, the system audit tool comprising: an audit tool database that maintains one or more logs of bus messages; a bus message logger, communicatively coupled with the bus and the audit tool database, that records messages from the bus in the audit tool database; and a heartbeat logger communicatively coupled with the bus and the audit tool database and recording heartbeat messages sent periodically on the bus from the one or more end devices and the one or more managers to indicate a normal status of the one or more end devices and the one or more managers; wherein the plurality of managers comprises a first manager coupled with a first server and correlating a user's request message to the first server with one or more missed heartbeats from the first server to identify a problem with the first server. | 1. A system for providing cross-platform support for a variety of media types, the system comprising: a plurality of servers, including at least one server providing content of one or more different media types and at least one server providing one or more services, the plurality of servers comprising an Internet Protocol television (“IPTV”) server and a billing server; a plurality of managers, each manager communicatively coupled with one or more of the servers and translating content or services of the servers with which the manager is connected from the media types of the servers to one or more of a plurality of common language messages each of the plurality of common language messages related to one of the services of one of the servers with which the manager is connected; a communications bus communicatively coupled with each of the managers and receiving and transporting the one or more common language messages from the managers; and a plurality of end devices of different types, each end device communicatively coupled with the bus and receiving and translating the common language messages to a format specific to the end device based on the type; and a system audit tool communicatively coupled with the bus and monitoring common language messages on the bus, the system audit tool comprising: an audit tool database that maintains one or more logs of bus messages; a bus message logger, communicatively coupled with the bus and the audit tool database, that records messages from the bus in the audit tool database; and a heartbeat logger communicatively coupled with the bus and the audit tool database and recording heartbeat messages sent periodically on the bus from the one or more end devices and the one or more managers to indicate a normal status of the one or more end devices and the one or more managers; wherein the plurality of managers comprises a first manager coupled with a first server and correlating a user's request message to the first server with one or more missed heartbeats from the first server to identify a problem with the first server. 6. The system of claim 1 , further comprising a user profile database communicatively coupled with the bus and maintaining records of a set of user preferences for one or more of the end devices of the interface level. | 0.5 |
8,806,204 | 1 | 3 | 1. A method of eliminating token collision in a multiple domain environment, said method comprising the computer-implemented steps of: establishing a first data vault located at a first domain; establishing a plurality of second data vaults, each located at one of a plurality of second domains; receiving at said first domain a sensitive data string for tokenization; generating a new token according to a token generation algorithm wherein said new token is independent of at least a portion of the data in said sensitive data string, and wherein said token generation algorithm is configured to embed within said new token a domain designator corresponding to said first domain; storing said token in said first data vault; creating a replica of said first data vault at each of said plurality of second domains; and creating a replica of each of a said plurality of second data vaults at said first domain. | 1. A method of eliminating token collision in a multiple domain environment, said method comprising the computer-implemented steps of: establishing a first data vault located at a first domain; establishing a plurality of second data vaults, each located at one of a plurality of second domains; receiving at said first domain a sensitive data string for tokenization; generating a new token according to a token generation algorithm wherein said new token is independent of at least a portion of the data in said sensitive data string, and wherein said token generation algorithm is configured to embed within said new token a domain designator corresponding to said first domain; storing said token in said first data vault; creating a replica of said first data vault at each of said plurality of second domains; and creating a replica of each of a said plurality of second data vaults at said first domain. 3. The method of claim 1 , wherein said domain designator comprises a single digit selected from the ten numerals, zero through nine. | 0.889351 |
9,460,155 | 5 | 6 | 5. The contextual user engagement system of claim 1 , wherein a value occurs within a negated context, the confidence value is defined as: C N ( v ) = ⅇ ( 1 N - 1 ) C ( v ) . | 5. The contextual user engagement system of claim 1 , wherein a value occurs within a negated context, the confidence value is defined as: C N ( v ) = ⅇ ( 1 N - 1 ) C ( v ) . 6. The contextual user engagement system of claim 5 , where the information extraction engine receives domain-specific rules and patterns from a user. | 0.5 |
9,977,955 | 15 | 21 | 15. A system for identifying books located on a bookshelf, the system comprising: a mobile device configured to capture one or more photographic images of the bookshelf; a computer server configured to receive the captured one or more photographic images and to: segment the photographic images into regions, each of the regions corresponding to a respective book spine; analyze at least one of the regions to identify a book corresponding thereto, wherein the computer server is further configured, in furtherance of analyzing the at least one of the regions, to: extract one or more visual features descriptive of the at least one of the regions, the one or more visual features including machine-recognized text and a location of the machine-recognized text contained within the at least one of the regions, wherein the machine-recognized text and the location of the machine-recognized text are used as analogues of visual features; perform a matching operation based on the one or more visual features, the matching operation performed against stored data associating plural book identities with corresponding visual features; when the matching operation returns one of the book identities sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing said one of the book identities; when the matching operation fails to return one of the book identities sufficiently closely matched with the one or more visual features, initiate a further analysis of the at least one of the regions to identify the book corresponding thereto; and when the further analysis returns a further book identity sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing the further book identity; and browse another user's bookshelf, wherein browsing another user's bookshelf comprises: comparing a first book title list of a first bookshelf belonging to a first user with a second book title list of a second bookshelf belonging to a second user, wherein the first book title list and the second book title list include book titles identified as a result of analyzing the at least one of the regions; and enabling the first user to access the second book title list of the second bookshelf when there is at least a predetermined amount of overlap between the book titles of the first user's bookshelf and the book titles of the second user's bookshelf. | 15. A system for identifying books located on a bookshelf, the system comprising: a mobile device configured to capture one or more photographic images of the bookshelf; a computer server configured to receive the captured one or more photographic images and to: segment the photographic images into regions, each of the regions corresponding to a respective book spine; analyze at least one of the regions to identify a book corresponding thereto, wherein the computer server is further configured, in furtherance of analyzing the at least one of the regions, to: extract one or more visual features descriptive of the at least one of the regions, the one or more visual features including machine-recognized text and a location of the machine-recognized text contained within the at least one of the regions, wherein the machine-recognized text and the location of the machine-recognized text are used as analogues of visual features; perform a matching operation based on the one or more visual features, the matching operation performed against stored data associating plural book identities with corresponding visual features; when the matching operation returns one of the book identities sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing said one of the book identities; when the matching operation fails to return one of the book identities sufficiently closely matched with the one or more visual features, initiate a further analysis of the at least one of the regions to identify the book corresponding thereto; and when the further analysis returns a further book identity sufficiently closely matched with the one or more visual features, identify the at least one of the regions as representing the further book identity; and browse another user's bookshelf, wherein browsing another user's bookshelf comprises: comparing a first book title list of a first bookshelf belonging to a first user with a second book title list of a second bookshelf belonging to a second user, wherein the first book title list and the second book title list include book titles identified as a result of analyzing the at least one of the regions; and enabling the first user to access the second book title list of the second bookshelf when there is at least a predetermined amount of overlap between the book titles of the first user's bookshelf and the book titles of the second user's bookshelf. 21. The system of claim 15 , wherein the stored data comprises models stored in a training set. | 0.877261 |
8,363,950 | 12 | 13 | 12. The method of claim 11 where a first sigmoid function is applied to the first score and a second sigmoid function is applied to the second score. | 12. The method of claim 11 where a first sigmoid function is applied to the first score and a second sigmoid function is applied to the second score. 13. The method of claim 12 where an output of the output layer is based on a linear combination result of an output of the at least one hidden layer. | 0.5 |
8,645,395 | 18 | 19 | 18. The method of claim 17 , further comprising recognizing a polarizer in the opinion word before calculating the opinion score. | 18. The method of claim 17 , further comprising recognizing a polarizer in the opinion word before calculating the opinion score. 19. The method of claim 18 , further comprising instructing the sentiment rating engine to override the opinion score, thereby making the polarizer the opinion score. | 0.5 |
8,121,432 | 1 | 5 | 1. A method for partitioning a video sequence, comprising: dividing a video sequence into a plurality of segments; generating a transcript of speech content of the video sequence, wherein the transcript comprises a plurality of words and identifies temporal locations of the words in the video sequence; selecting a plurality of keywords from the plurality of words in the transcript; selecting a set of keywords from the plurality of keywords, wherein the keywords in the set of keywords are related to each other by meanings of the keywords; determining a distribution of occurrences across the plurality of segments of the keywords in the set of keywords; selecting a group of segments from the plurality of segments using the distribution, wherein the segments in the group of segments are temporally adjacent and the group of segments corresponds to a peak of the occurrences across the plurality of segments of the keywords in the set of keywords; and forming a partition of the video sequence from the group of segments; wherein generating the transcript of speech content of the video sequence comprises generating the transcript from audio content of the video sequence using automatic speech recognition, determining whether the transcript generated from the audio content is satisfactory, responsive to a determination that the transcript generated from the audio content is not satisfactory, determining whether the video sequence has closed caption, and responsive to a determination that the video sequence has closed caption, generating the transcript from the closed caption. | 1. A method for partitioning a video sequence, comprising: dividing a video sequence into a plurality of segments; generating a transcript of speech content of the video sequence, wherein the transcript comprises a plurality of words and identifies temporal locations of the words in the video sequence; selecting a plurality of keywords from the plurality of words in the transcript; selecting a set of keywords from the plurality of keywords, wherein the keywords in the set of keywords are related to each other by meanings of the keywords; determining a distribution of occurrences across the plurality of segments of the keywords in the set of keywords; selecting a group of segments from the plurality of segments using the distribution, wherein the segments in the group of segments are temporally adjacent and the group of segments corresponds to a peak of the occurrences across the plurality of segments of the keywords in the set of keywords; and forming a partition of the video sequence from the group of segments; wherein generating the transcript of speech content of the video sequence comprises generating the transcript from audio content of the video sequence using automatic speech recognition, determining whether the transcript generated from the audio content is satisfactory, responsive to a determination that the transcript generated from the audio content is not satisfactory, determining whether the video sequence has closed caption, and responsive to a determination that the video sequence has closed caption, generating the transcript from the closed caption. 5. The method of claim 1 , further comprising: generating a sound label for each of the plurality of segments, wherein the sound label indicates a class of sound in audio content of a corresponding segment; generating a visual label for each of the plurality of segments, wherein the visual label indicates a class of visual content of the corresponding segment; and selecting a one of the plurality of segments as a boundary for the partition using a one of the sound label or the visual label for the selected one of the plurality of segments. | 0.5 |
9,418,124 | 7 | 11 | 7. A system for processing a set of data records having time conflicts, the data records representing respective versions of an entity for which there can be only one preferred value at any given point in time, wherein each of the data records has an n-dimensional time record, the system comprising: one or more processors; and a memory comprising instructions which, when executed by the one or more processors, cause the one or more processors to: define a policy from among a plurality of candidate policies, said defined policy designed to resolve time conflicts between those data records having time conflicts; compare all data records in a cumulative, pair-wise fashion; identify time-based conflicts between pairs of records and identify time-conflicted pairs; determine which record in every time-conflicted pair of records is to be adjusted in accordance with said defined policy; adjust the time interval of every said determined record to be adjusted in accordance with said defined policy; and output a modified set of data records having said adjusted time intervals, wherein (i) said modified set of data records contains no time conflicts and (ii) said adjusted time intervals in the modified set of data records do not depend on the order in which the data records are processed by said computer-implemented method. | 7. A system for processing a set of data records having time conflicts, the data records representing respective versions of an entity for which there can be only one preferred value at any given point in time, wherein each of the data records has an n-dimensional time record, the system comprising: one or more processors; and a memory comprising instructions which, when executed by the one or more processors, cause the one or more processors to: define a policy from among a plurality of candidate policies, said defined policy designed to resolve time conflicts between those data records having time conflicts; compare all data records in a cumulative, pair-wise fashion; identify time-based conflicts between pairs of records and identify time-conflicted pairs; determine which record in every time-conflicted pair of records is to be adjusted in accordance with said defined policy; adjust the time interval of every said determined record to be adjusted in accordance with said defined policy; and output a modified set of data records having said adjusted time intervals, wherein (i) said modified set of data records contains no time conflicts and (ii) said adjusted time intervals in the modified set of data records do not depend on the order in which the data records are processed by said computer-implemented method. 11. The system of claim 7 , wherein said outputted modified set of records comprise a concise and complete temporal history of all data records such that a history of said entity is retrievable via a standard XML manipulation language. | 0.5 |
9,244,893 | 9 | 10 | 9. The printer processing method described in claim 8 , wherein: wherein the conversion unit has: a first conversion unit for converting the first mark-up language document to a converted mark-up language document that conforms to output format information relating to a document format for documents output to the printer, and a second conversion unit for converting the converted mark-up language document to the binary data based on the model-dependent information. | 9. The printer processing method described in claim 8 , wherein: wherein the conversion unit has: a first conversion unit for converting the first mark-up language document to a converted mark-up language document that conforms to output format information relating to a document format for documents output to the printer, and a second conversion unit for converting the converted mark-up language document to the binary data based on the model-dependent information. 10. The computer described in claim 9 , wherein: the output format information is user-defined: and the first conversion unit converts the first mark-up language document to an output format based on the output format information. | 0.5 |
7,503,060 | 3 | 4 | 3. A safety verification device of an electronic reactive system, which is a cipher communication system or control system for a nuclear reactor or aircraft, represented by a set of function symbols, a set of rewriting rules, a set of axioms, a set of first terms, and a second term to be verified, said set of axioms being a set consisting only a commutative law and an associative law, and said safety verification device of a reactive system comprising a processing unit, a recording unit, a translation unit, a simulation unit and a set operation unit, wherein; said set of function symbols, said set of rewriting rules, said set of axioms, said set of first terms, and said second term to be verified are recorded in said recording unit; said translation unit is controlled by said processing unit to read out said set of axioms and said set of first terms from said recording unit and to generate, under said set of axioms, a first equational tree automaton which accepts said set of first terms; said simulation unit is controlled by said processing unit to read out said set of rewriting rules, said set of axioms and said set of first terms from said recording unit and to generate, under said set of rewriting rules and said set of axioms and using said first equational tree automaton as initial data, a second equational tree automaton which accepts said set of first terms and a set that comprises terms derived from said set of first terms; said set operation unit is controlled by said processing unit to determine whether or not said second equational tree automaton accepts said second term to be verified; said second equational tree automaton is generated through first and second repetition processes; wherein said first repetition process comprises: (A) setting said first equational tree automaton to initial data; (B) selecting an element p from a first group which consists of position information in a tree-structure when left sides of equations, each of said equations corresponding to a rewriting rule in said set of rewriting rules, are described in tree-structure, wherein said element p is positioned at the end of said tree-structure; (C) determining a set of third terms by rewriting all terms which are included in a third equational tree automaton obtained in a last process performed according to the rewriting rule ƒ(c p.l tl , . . . , c p.n tn )-->c p l|p , wherein a function symbol of said element p is described as ƒ, argument terms are described as t l , . . . , t n , and a term l|p corresponding to said element p is described as ƒ(t l , . . . , t n ); (D) obtaining a fourth equational tree automaton by performing repeatedly said (B) selecting and (C) determining processes regarding all elements p positioned at the ends of said tree-structure of said first group; and wherein said second repetition process comprises: (E) setting said fourth equational tree automaton to initial data; (F) selecting an element q from a second group which consists of position information in a tree-structure when right sides of equations, each of said equations corresponding to a rewriting rule in said set of rewriting rules, are described in tree-structure, wherein said element q is positioned at the end of said tree-structure; (G) determining a set of fourth terms by rewriting all terms which are included in a fifth equational tree automaton obtained in a last process performed according to the rewriting rule ƒ(d q.l tl , . . . , d q.n tn )->d q r|q , wherein a function symbol of said element q is described as ƒ, argument terms are described as t l , . . . , t n , and a term r|q corresponding to said element q is described as f(t l , . . . , t n ); and (H) obtaining said second equational tree automaton by performing repeatedly said (F) selecting and (G) determining processes regarding all elements q positioned at the ends of said tree-structure of said second group. | 3. A safety verification device of an electronic reactive system, which is a cipher communication system or control system for a nuclear reactor or aircraft, represented by a set of function symbols, a set of rewriting rules, a set of axioms, a set of first terms, and a second term to be verified, said set of axioms being a set consisting only a commutative law and an associative law, and said safety verification device of a reactive system comprising a processing unit, a recording unit, a translation unit, a simulation unit and a set operation unit, wherein; said set of function symbols, said set of rewriting rules, said set of axioms, said set of first terms, and said second term to be verified are recorded in said recording unit; said translation unit is controlled by said processing unit to read out said set of axioms and said set of first terms from said recording unit and to generate, under said set of axioms, a first equational tree automaton which accepts said set of first terms; said simulation unit is controlled by said processing unit to read out said set of rewriting rules, said set of axioms and said set of first terms from said recording unit and to generate, under said set of rewriting rules and said set of axioms and using said first equational tree automaton as initial data, a second equational tree automaton which accepts said set of first terms and a set that comprises terms derived from said set of first terms; said set operation unit is controlled by said processing unit to determine whether or not said second equational tree automaton accepts said second term to be verified; said second equational tree automaton is generated through first and second repetition processes; wherein said first repetition process comprises: (A) setting said first equational tree automaton to initial data; (B) selecting an element p from a first group which consists of position information in a tree-structure when left sides of equations, each of said equations corresponding to a rewriting rule in said set of rewriting rules, are described in tree-structure, wherein said element p is positioned at the end of said tree-structure; (C) determining a set of third terms by rewriting all terms which are included in a third equational tree automaton obtained in a last process performed according to the rewriting rule ƒ(c p.l tl , . . . , c p.n tn )-->c p l|p , wherein a function symbol of said element p is described as ƒ, argument terms are described as t l , . . . , t n , and a term l|p corresponding to said element p is described as ƒ(t l , . . . , t n ); (D) obtaining a fourth equational tree automaton by performing repeatedly said (B) selecting and (C) determining processes regarding all elements p positioned at the ends of said tree-structure of said first group; and wherein said second repetition process comprises: (E) setting said fourth equational tree automaton to initial data; (F) selecting an element q from a second group which consists of position information in a tree-structure when right sides of equations, each of said equations corresponding to a rewriting rule in said set of rewriting rules, are described in tree-structure, wherein said element q is positioned at the end of said tree-structure; (G) determining a set of fourth terms by rewriting all terms which are included in a fifth equational tree automaton obtained in a last process performed according to the rewriting rule ƒ(d q.l tl , . . . , d q.n tn )->d q r|q , wherein a function symbol of said element q is described as ƒ, argument terms are described as t l , . . . , t n , and a term r|q corresponding to said element q is described as f(t l , . . . , t n ); and (H) obtaining said second equational tree automaton by performing repeatedly said (F) selecting and (G) determining processes regarding all elements q positioned at the ends of said tree-structure of said second group. 4. A safety verification device of a reactive system according to claim 3 , wherein said set of function symbols is a set comprising function symbols representing encryption, decryption and communication processing as elements, said set of rewriting rules is a set comprising as an element a rule representing that encrypted information is returned to plaintext by decryption, said second term to be verified is confidential information, and said set of first terms is a set of knowledge of each of subjects that exchange confidential information, and a set of knowledge of a subject that monitors the information exchanged between said subjects. | 0.5 |
9,619,702 | 1 | 10 | 1. A method for creating digitized text for a record from an image of the record, comprising: obtaining a digital image of a record; evaluating the record image in order to locate each of multiple word images; for each located word image, identifying multiple word features of that word image; assigning each of the multiple word images that have similar word features to one of a plurality of word clusters; selecting a representative word image in each of the word clusters as a centroid; reviewing, by an analyst, the centroid in each of the word clusters, and entering digitized text for the centroid; and assigning the digitized text for the centroid to all other word images in the same word cluster as the centroid. | 1. A method for creating digitized text for a record from an image of the record, comprising: obtaining a digital image of a record; evaluating the record image in order to locate each of multiple word images; for each located word image, identifying multiple word features of that word image; assigning each of the multiple word images that have similar word features to one of a plurality of word clusters; selecting a representative word image in each of the word clusters as a centroid; reviewing, by an analyst, the centroid in each of the word clusters, and entering digitized text for the centroid; and assigning the digitized text for the centroid to all other word images in the same word cluster as the centroid. 10. The method of claim 1 , wherein the multiple word features are selected from a group comprising: top line profile, bottom-line profile, left line profile, right line profile, vertical projection profile, horizontal projection profile, peaks, valleys, watershed cup areas, watershed cap areas, loops and holes, intersections and crossings, stroke orientation, word aspect ratio, and convex whole. | 0.669702 |
9,830,146 | 1 | 2 | 1. A method for performing version control for Application Programming Interfaces (APIs) of an operating system, said operating system configured to be revised by version and by platform, said method comprising: for a given API, creating metadata associated with a plurality of constructs of said API, said metadata comprising version indication data, wherein said metadata comprises a version attribute, said version attribute further comprising a version introduction value, said version introduction value indicating each one of the plurality of constructs of said APl being introduced to a version of the operating system, and wherein said version indication data comprises a version value and a platform value, said version value denoting the version of the operating system in which the associated construct was revised, said platform value denoting the operating system platform associated with the version value, and wherein said metadata is created automatically from API description files; associating the version indication data for said each one of the plurality of constructs of said API, said version indication indicating when said respective one of the plurality of constructs of said API is to be revised into a given version of an operating system; defining versioning rules for said each one of the plurality of constructs of said API according to said metadata, wherein said each one of the plurality of constructs comprises at least one of a structure, an enum, an interface, and a composable class and wherein the versioning rules are dependent upon a given construct's version indication data; and based on construction of a new version of said operating system and said metadata associated with the plurality of constructs of said API, enforcing said versioning rules for each of the respective ones of said plurality of constructs of said API. | 1. A method for performing version control for Application Programming Interfaces (APIs) of an operating system, said operating system configured to be revised by version and by platform, said method comprising: for a given API, creating metadata associated with a plurality of constructs of said API, said metadata comprising version indication data, wherein said metadata comprises a version attribute, said version attribute further comprising a version introduction value, said version introduction value indicating each one of the plurality of constructs of said APl being introduced to a version of the operating system, and wherein said version indication data comprises a version value and a platform value, said version value denoting the version of the operating system in which the associated construct was revised, said platform value denoting the operating system platform associated with the version value, and wherein said metadata is created automatically from API description files; associating the version indication data for said each one of the plurality of constructs of said API, said version indication indicating when said respective one of the plurality of constructs of said API is to be revised into a given version of an operating system; defining versioning rules for said each one of the plurality of constructs of said API according to said metadata, wherein said each one of the plurality of constructs comprises at least one of a structure, an enum, an interface, and a composable class and wherein the versioning rules are dependent upon a given construct's version indication data; and based on construction of a new version of said operating system and said metadata associated with the plurality of constructs of said API, enforcing said versioning rules for each of the respective ones of said plurality of constructs of said API. 2. The method of claim 1 , wherein said metadata comprises a deprecatable version attribute, said deprecatable version attribute further comprising a version deprecation value, said version deprecation value associating said construct being removed in a version of an operating system. | 0.5 |
9,743,357 | 1 | 5 | 1. An energy harvesting communication device configured with means for boosting signal reception, the communication device comprising: a. at least a cell platform; b. at least a charging circuit apparatus; c. at least a control apparatus; d. at least a communication apparatus communicatively coupled to said charging circuit apparatus and in association with the control apparatus; and e. said cell platform further disposed with sensors embedded in silicon substrate to provide at least one of a communication medium, a detection platform, a communication clarity, a detection selectivity, and a detection sensitivity. | 1. An energy harvesting communication device configured with means for boosting signal reception, the communication device comprising: a. at least a cell platform; b. at least a charging circuit apparatus; c. at least a control apparatus; d. at least a communication apparatus communicatively coupled to said charging circuit apparatus and in association with the control apparatus; and e. said cell platform further disposed with sensors embedded in silicon substrate to provide at least one of a communication medium, a detection platform, a communication clarity, a detection selectivity, and a detection sensitivity. 5. The energy harvesting communication device of claim 1 , wherein said charging circuit apparatus further comprising at least one of: a communication circuit board; means for charging a battery; means for managing energy; means for controlling energy to a storage medium; means for loading energy to a storage medium; and wherein said charging circuit apparatus in communication with at least one of said cell platform; said control apparatus; a cell associated with a housing member being affixed with a shapeable miniaturized ferrous structure; a shapeable light reflective plate; a display device configured with at least a supporting structure; an energy harvesting case, an energy harvesting case being disposed with embedded sensors; an energy harvesting case in association with embedded multiple antennas on chip; an energy harvesting case configured for at least one of communication, signal booster, data content display. | 0.791312 |
9,437,027 | 4 | 5 | 4. The method of claim 1 , wherein transforming the query image and the one or more objects using the one or more objects to produce the synthesized image further comprises combining an image feature distribution for the at least one inserted object with other object models in the depth layer. | 4. The method of claim 1 , wherein transforming the query image and the one or more objects using the one or more objects to produce the synthesized image further comprises combining an image feature distribution for the at least one inserted object with other object models in the depth layer. 5. The method of claim 4 further comprising updating the scene representation to correspond to a semantic structure of the synthesized image. | 0.5 |
7,996,793 | 1 | 7 | 1. A method for providing recognition of gestures made by a user using a filter representing a gesture, the filter comprising base information about the gesture, comprising: receiving data captured by a camera, the data corresponding to a first application; applying the filter to the data and determining an output from the base information about the gesture; sending the first application the output; receiving second data captured by the camera, the data corresponding to a second application; applying the filter to the second data and determining a second output from the base information about the gesture; and sending the second application the second output. | 1. A method for providing recognition of gestures made by a user using a filter representing a gesture, the filter comprising base information about the gesture, comprising: receiving data captured by a camera, the data corresponding to a first application; applying the filter to the data and determining an output from the base information about the gesture; sending the first application the output; receiving second data captured by the camera, the data corresponding to a second application; applying the filter to the second data and determining a second output from the base information about the gesture; and sending the second application the second output. 7. The method of claim 1 , wherein the output comprises a confidence level that the data is indicative of the gesture being performed. | 0.92369 |
7,656,861 | 9 | 14 | 9. A network processing device, comprising: a processor configured to: convert media signaling into Internet Protocol (IP) media packets; receive text signaling comprising different analog audio tones representing different alpha-numeric characters; identify the alpha-numeric characters represented by the analog audio tones and generate digital values that represent the same identified alpha-numeric characters; formatting the digital values into IP text packets absent analog signaling characteristics describing the audio tones; and sending the IP media packets and the IP text packets in interleaved manner over an IP network using the same real-time IP transport session. | 9. A network processing device, comprising: a processor configured to: convert media signaling into Internet Protocol (IP) media packets; receive text signaling comprising different analog audio tones representing different alpha-numeric characters; identify the alpha-numeric characters represented by the analog audio tones and generate digital values that represent the same identified alpha-numeric characters; formatting the digital values into IP text packets absent analog signaling characteristics describing the audio tones; and sending the IP media packets and the IP text packets in interleaved manner over an IP network using the same real-time IP transport session. 14. The network processing device according to claim 9 wherein the processor specifies, in a media-signaling session prior to sending the text packets, a character rate that controls a maximum transfer rate for transferring characters in the IP text packets during the real-time IP media transport session as a preventative against dropping of text packets. | 0.5 |
9,348,815 | 1 | 2 | 1. A computer-implemented method, comprising: reading text data corresponding to one or more messages, wherein the text data comprises natural language content; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data, and wherein the language patterns comprise at least one of part-of-speech, syntactic role, and sentiment associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training; wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error in the created one or more semantic annotations, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. | 1. A computer-implemented method, comprising: reading text data corresponding to one or more messages, wherein the text data comprises natural language content; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data, and wherein the language patterns comprise at least one of part-of-speech, syntactic role, and sentiment associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training; wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error in the created one or more semantic annotations, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. 2. The method of claim 1 , wherein identifying the annotation error from the knowledge graph representation and updating the respective annotation comprises receiving an annotation correction from at least one user via a user interface. | 0.598639 |
9,756,081 | 1 | 4 | 1. A method comprising: receiving, by a first stage of a context-aware pattern matching and parsing (CPMP) hardware accelerator of a network security device, a packet stream; identifying, by the first stage, a plurality of candidate packets within the packet stream that each satisfy one or more pre-match conditions relating to a set of Intrusion Prevention System (IPS) or Application Delivery Controller (ADC) rules by performing a pre-matching process on packets within the packet stream; emitting, by the first stage, information indicative of a candidate rule from the set of IPS or ADC rules for which a full-match process is to be performed with respect to a candidate packet of the plurality of candidate packets selected based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching tokens within the candidate packet; performing, by a second stage of the CPMP hardware accelerator including a plurality of CPMP processors, the full-match process on the candidate packet to determine whether the candidate packet satisfies the candidate rule by fetching and executing special purpose CPMP instructions to perform one or more of (i) context-aware pattern matching on one or more packet field values of the candidate packet, (ii) context-aware string matching on packet data of the candidate packet and (iii) regular expression matching on the packet data based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network security device. | 1. A method comprising: receiving, by a first stage of a context-aware pattern matching and parsing (CPMP) hardware accelerator of a network security device, a packet stream; identifying, by the first stage, a plurality of candidate packets within the packet stream that each satisfy one or more pre-match conditions relating to a set of Intrusion Prevention System (IPS) or Application Delivery Controller (ADC) rules by performing a pre-matching process on packets within the packet stream; emitting, by the first stage, information indicative of a candidate rule from the set of IPS or ADC rules for which a full-match process is to be performed with respect to a candidate packet of the plurality of candidate packets selected based on a correlation of results of the pre-matching process; tokenizing, by the first stage, packet data of the candidate packet to produce matching tokens and corresponding locations of the matching tokens within the candidate packet; performing, by a second stage of the CPMP hardware accelerator including a plurality of CPMP processors, the full-match process on the candidate packet to determine whether the candidate packet satisfies the candidate rule by fetching and executing special purpose CPMP instructions to perform one or more of (i) context-aware pattern matching on one or more packet field values of the candidate packet, (ii) context-aware string matching on packet data of the candidate packet and (iii) regular expression matching on the packet data based on a plurality of predefined conditions associated with the candidate rule, corresponding contextual information provided by the candidate rule, the matching tokens and the corresponding locations; and providing, by the second stage, results of the full-match process to a general purpose processor of the network security device. 4. The method of claim 1 , further comprising when the candidate packet is determined to satisfy the candidate rule, then causing the candidate packet and the information indicative of the candidate rule to be made available to the general purpose processor. | 0.734021 |
7,548,912 | 13 | 14 | 13. The method of claim 12 , wherein the request packet comprises a query text element for specifying a query string for the keyword query. | 13. The method of claim 12 , wherein the request packet comprises a query text element for specifying a query string for the keyword query. 14. The method of claim 13 , wherein the request packet further comprises a properties element for specifying the properties to be returned from a query. | 0.5 |
5,566,330 | 31 | 32 | 31. A stored program computer, comprising: a central processor and a memory; and in said memory, a computer-executable interface program for providing a graphical user interface to a computer database manager program, the interface program comprising: a graphic painter being programmed to allow an applications programmer to tailor associations between columns of a database table managed by said database manager program and associated editing styles, without access to source code of said interface program; each editing style specifying a display format and screen display position for data of the associated column, said graphic painter being programmed to allow said applications programmer to manipulate graphical figures on a display screen of a computer and thereby specify said column/style associations in correspondence to said graphical figures; the editing styles tailorable by said applications programmer further comprising extended column definitions of display characteristics for data of corresponding columns of said database table beyond those characteristics inherent in a data dictionary of said database table; a graphical user interface component programmed to provide said graphical user interface and allow a user to manipulate data of said database table, the behavior and appearance of said graphical user interface being determined by said column/style associations with said extended column definitions, said graphical user interface component being programmed to generate and issue commands to said database manager program to direct said database manager program to read data from and write data to said database table, said commands being determined in accordance with said column/style associations and in response to requests entered to said graphical user interface component by said user. | 31. A stored program computer, comprising: a central processor and a memory; and in said memory, a computer-executable interface program for providing a graphical user interface to a computer database manager program, the interface program comprising: a graphic painter being programmed to allow an applications programmer to tailor associations between columns of a database table managed by said database manager program and associated editing styles, without access to source code of said interface program; each editing style specifying a display format and screen display position for data of the associated column, said graphic painter being programmed to allow said applications programmer to manipulate graphical figures on a display screen of a computer and thereby specify said column/style associations in correspondence to said graphical figures; the editing styles tailorable by said applications programmer further comprising extended column definitions of display characteristics for data of corresponding columns of said database table beyond those characteristics inherent in a data dictionary of said database table; a graphical user interface component programmed to provide said graphical user interface and allow a user to manipulate data of said database table, the behavior and appearance of said graphical user interface being determined by said column/style associations with said extended column definitions, said graphical user interface component being programmed to generate and issue commands to said database manager program to direct said database manager program to read data from and write data to said database table, said commands being determined in accordance with said column/style associations and in response to requests entered to said graphical user interface component by said user. 32. The stored program computer of claim 31 wherein: said extended column definitions comprise a label for labelling the display of data of a column of said database table, said label being different than the column name maintained by said database manager program. | 0.706208 |
9,466,068 | 11 | 18 | 11. A system for determining pupillary response to a multimedia data element (MMDE) viewed through a user computing device, comprising: a processor; and a memory connected to the processor, the memory contains instructions that when executed by the processor, the system is configured to: receive a first image of a viewer's pupil captured prior to display of the MMDE over the user computing device; receive a second image of a viewer's pupil captured after the display of the MMDE over the user computing device; determine, using the first image and the second image, if the viewer's pupil has been dilated; when identifying of a pupil dilation, query a deep-content-classification (DCC) system to find a match between at least one concept structure and the at least second image of the user's pupil; upon identification of at least one matching concept, receive a first set of metadata related to the at least one matching concept structure; determine the viewer's attention to the displayed MMDE respective of the first set of metadata; and associate the at least one MMDE with the determined user attention. | 11. A system for determining pupillary response to a multimedia data element (MMDE) viewed through a user computing device, comprising: a processor; and a memory connected to the processor, the memory contains instructions that when executed by the processor, the system is configured to: receive a first image of a viewer's pupil captured prior to display of the MMDE over the user computing device; receive a second image of a viewer's pupil captured after the display of the MMDE over the user computing device; determine, using the first image and the second image, if the viewer's pupil has been dilated; when identifying of a pupil dilation, query a deep-content-classification (DCC) system to find a match between at least one concept structure and the at least second image of the user's pupil; upon identification of at least one matching concept, receive a first set of metadata related to the at least one matching concept structure; determine the viewer's attention to the displayed MMDE respective of the first set of metadata; and associate the at least one MMDE with the determined user attention. 18. The system of claim 11 , wherein the DCC system comprises: an attention processor (AP) for generating a plurality of items from the received sensory signal and determining which of the generated items are of interest for signature generation; a signature generator (SG) for generating at least one signature responsive to at least one item of interest of the sensory signal; and a concept generator (CG) for matching between the at least one signature generated responsive to at least one item of interest of the sensory signal and a plurality of signature reduced clusters associated with a plurality of cluster structures to identify at least the first set of metadata. | 0.5 |
10,146,770 | 8 | 13 | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a cognitive system for capturing referential information, wherein the computer readable program causes the computing device to: receive, by a message aggregator executing within the cognitive system, a first indication that a group text messaging conversation is in a muted state for a first user, detect, by a cognitive agent executing within the cognitive system, a first use of a referential phrase in the group text messaging conversation during a first time period when the group text messaging conversation is in the muted state wherein detecting the first use of the referential phrase comprises: parsing, by a parser executing within the cognitive agent, one or more conversation message within the group text messaging conversation to perform parsing and semantic analysis to annotate the one or more conversation messages; extracting, by a feature extraction component executing within the cognitive agent, a set of features from the one or more conversation message describing the one or more conversation message; and processing by a natural language classifier component executing within the cognitive agent, the set of features to identify that the one or more conversation messages contain the first use of the referential phrase using a machine learning model that determines a category for each term or phrase based on the set of features and calculates a confidence for each category; receive, by the message aggregator, a second indication that the group text messaging conversation is in a non-muted state for the first user; detect, by the cognitive agent, a second use of the referential phrase in the group text messaging conversation during a second time period when the group text messaging conversation is in the non-muted state, wherein the second time period is subsequent to the first time period; alter, by the cognitive agent, a message containing the second use of the referential phrase within the group text messaging conversation within a multi-user chat display; determine, by the cognitive system, a first probability that the first user understands the referential phrase; and provide, by the cognitive system, first information to the first user within the multi-user chat display when the first probability is below a threshold, wherein the first information pertains to the referential phrase. | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a cognitive system for capturing referential information, wherein the computer readable program causes the computing device to: receive, by a message aggregator executing within the cognitive system, a first indication that a group text messaging conversation is in a muted state for a first user, detect, by a cognitive agent executing within the cognitive system, a first use of a referential phrase in the group text messaging conversation during a first time period when the group text messaging conversation is in the muted state wherein detecting the first use of the referential phrase comprises: parsing, by a parser executing within the cognitive agent, one or more conversation message within the group text messaging conversation to perform parsing and semantic analysis to annotate the one or more conversation messages; extracting, by a feature extraction component executing within the cognitive agent, a set of features from the one or more conversation message describing the one or more conversation message; and processing by a natural language classifier component executing within the cognitive agent, the set of features to identify that the one or more conversation messages contain the first use of the referential phrase using a machine learning model that determines a category for each term or phrase based on the set of features and calculates a confidence for each category; receive, by the message aggregator, a second indication that the group text messaging conversation is in a non-muted state for the first user; detect, by the cognitive agent, a second use of the referential phrase in the group text messaging conversation during a second time period when the group text messaging conversation is in the non-muted state, wherein the second time period is subsequent to the first time period; alter, by the cognitive agent, a message containing the second use of the referential phrase within the group text messaging conversation within a multi-user chat display; determine, by the cognitive system, a first probability that the first user understands the referential phrase; and provide, by the cognitive system, first information to the first user within the multi-user chat display when the first probability is below a threshold, wherein the first information pertains to the referential phrase. 13. The computer program product of claim 8 , wherein detecting the first use of the referential phrase comprises recording the first use of the referential phrase with identification of a type of referential phrase, and a confidence value. | 0.704433 |
9,146,673 | 14 | 17 | 14. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display and a touch-sensitive surface, cause the device to: display a first keyboard on the display, the first keyboard comprising a first plurality of keys; detect a key activation gesture at a first time at a location on the touch-sensitive surface that corresponds to a location of a first key in the first keyboard; in response to detecting the key activation gesture at the first time, activate the first key; detect one or more contacts on the touch-sensitive surface at a second time after the first time, the one or more contacts corresponding to a keyboard selection gesture; and, in response to detecting the one or more contacts that correspond to the keyboard selection gesture at the second time after the first time: replace the first keyboard with a second keyboard when the second time exceeds a predefined period of time after the first time; and maintain display of the first keyboard when the second time is less than the predefined period of time after the first time. | 14. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display and a touch-sensitive surface, cause the device to: display a first keyboard on the display, the first keyboard comprising a first plurality of keys; detect a key activation gesture at a first time at a location on the touch-sensitive surface that corresponds to a location of a first key in the first keyboard; in response to detecting the key activation gesture at the first time, activate the first key; detect one or more contacts on the touch-sensitive surface at a second time after the first time, the one or more contacts corresponding to a keyboard selection gesture; and, in response to detecting the one or more contacts that correspond to the keyboard selection gesture at the second time after the first time: replace the first keyboard with a second keyboard when the second time exceeds a predefined period of time after the first time; and maintain display of the first keyboard when the second time is less than the predefined period of time after the first time. 17. The computer readable storage medium of claim 14 , wherein the display is a touch-sensitive display that includes the touch-sensitive surface. | 0.733577 |
7,822,498 | 3 | 5 | 3. The method of claim 2 , further comprising: inputting the combined audio file into a speech recognition engine. | 3. The method of claim 2 , further comprising: inputting the combined audio file into a speech recognition engine. 5. The method of claim 3 , wherein the speech containing audio file is one of a plurality of speech containing audio files able to be selectively combined with the audio file that contains background sounds. | 0.789634 |
8,762,289 | 15 | 22 | 15. The computer-implemented method of claim 3 , wherein a search result includes selection of an advertisement from a plurality of advertisements. | 15. The computer-implemented method of claim 3 , wherein a search result includes selection of an advertisement from a plurality of advertisements. 22. The computer-implemented method of claim 15 , further comprising comparing the advertisement to a stored advertisement designated for the query. | 0.5 |
9,583,106 | 1 | 2 | 1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device. | 1. A method for presenting interactive audio content, the method comprising: receiving, using a computing device that includes a hardware processor, an audio input device, and an audio output device, an interactive audiobook having narrative content that includes a plurality of action points, wherein each of the plurality of action points provides a plurality of user actions and a narrative portion corresponding to each of the plurality of user actions; receiving, using the hardware processor of the computing device, a selection of a user engagement density from a user, wherein the selection determines a number of the plurality of action points in the narrative content of the interactive audiobook, and wherein a higher-selected user engagement density increases the number of the plurality of action points and a lower-selected user engagement density decreases the number of action points in the narrative content; causing, using the hardware processor of the computing device, the narrative content with the determined number of the plurality of action points to be presented via the audio output device to the user based on the selected user engagement density; determining, using the hardware processor of the computing device, that a speech input has been received by the audio input device at one of the plurality of action points during the playback of the narrative content of the interactive audiobook; converting, using the hardware processor of the computing device, the speech input to a text input; determining, using the hardware processor of the computing device, whether the user action associated with the text input corresponds to one of the plurality of user actions; selecting, using the hardware processor of the computing device, the narrative portion corresponding to the text input in response to determining that the user action corresponds to one of the plurality of user actions; converting, using the hardware processor of the computing device, the selected narrative portion to an audio output; modifying, using the hardware processor of the computing device, the narrative content of the interactive audiobook with the converted audio output of the selected narrative portion; and causing, using the hardware processor of the computing device, the narrative content with the converted audio output of the selected narrative portion to be presented to the user via the audio output device. 2. The method of claim 1 , wherein receiving the narrative content further comprises transmitting a user selection of the interactive audiobook from a plurality of interactive audiobooks and receiving the selected interactive audiobook. | 0.551331 |
7,743,103 | 19 | 20 | 19. A method of journalsing electronic mail in a shared multiple user environment, in which the users' incoming electronic mail are sent and received from extenal correspondents, said system includes a common mail server with a central storage wherein electronic mail items of the users are stored and may be retrieved, said method comprising: monitoring the flow of in- and outbound electronic mails on the mail server to and from the server users, and intercepting at least a selection of the in- and outbound e-mails, creating a notification record of a set of e-mail information data for each intercepted electronic mail and providing that the users can decide if intercepted electronic mails are to be available for a search query, whereby electronic mails are journalized and shared between a multiple of users; storing said notification records and the associated electronic mails in an electronic mail manager database (EMM-DB) so that the notification records and the associated electronic mails are archived and made accessible for the users in the multiple users environment by a search query; creating predefined and ad-hoc search queries by a query builder (EQB), said search queries can be applied/submitted to the EMM-DB and wherein a search query is selecting a user-defined series of information data from the notification records in the electronic mail management database irrespective of recipients or senders of said electronic mails; storing said predefined and ad-hoc search queries in a query database (QUERY-DB); providing all users access to queries in the QUERY-DB and electronic mails in the EMM-DB. whereby the electronic mails are searchable independent of senders and recipients; and defining user access rights to queries in the QUERY-DB and electronic mails in the EMM-DB by access control means (EAC). | 19. A method of journalsing electronic mail in a shared multiple user environment, in which the users' incoming electronic mail are sent and received from extenal correspondents, said system includes a common mail server with a central storage wherein electronic mail items of the users are stored and may be retrieved, said method comprising: monitoring the flow of in- and outbound electronic mails on the mail server to and from the server users, and intercepting at least a selection of the in- and outbound e-mails, creating a notification record of a set of e-mail information data for each intercepted electronic mail and providing that the users can decide if intercepted electronic mails are to be available for a search query, whereby electronic mails are journalized and shared between a multiple of users; storing said notification records and the associated electronic mails in an electronic mail manager database (EMM-DB) so that the notification records and the associated electronic mails are archived and made accessible for the users in the multiple users environment by a search query; creating predefined and ad-hoc search queries by a query builder (EQB), said search queries can be applied/submitted to the EMM-DB and wherein a search query is selecting a user-defined series of information data from the notification records in the electronic mail management database irrespective of recipients or senders of said electronic mails; storing said predefined and ad-hoc search queries in a query database (QUERY-DB); providing all users access to queries in the QUERY-DB and electronic mails in the EMM-DB. whereby the electronic mails are searchable independent of senders and recipients; and defining user access rights to queries in the QUERY-DB and electronic mails in the EMM-DB by access control means (EAC). 20. The method according to claim 19 , including formatting each intercepted electronic mail. | 0.792411 |
8,924,398 | 2 | 3 | 2. The method of claim 1 , wherein obtaining the plurality of relevant database log entries comprises: obtaining a database log entry directed to a database catalog entity; determining the database log entry is directed to a unit of recovery; determining the database log entry was generated as a consequence of a targeted database action; and repeating the acts of obtaining and determining for one or more additional database log entries. | 2. The method of claim 1 , wherein obtaining the plurality of relevant database log entries comprises: obtaining a database log entry directed to a database catalog entity; determining the database log entry is directed to a unit of recovery; determining the database log entry was generated as a consequence of a targeted database action; and repeating the acts of obtaining and determining for one or more additional database log entries. 3. The method of claim 2 , wherein the act of determining the first portion of database log entries comprises determining the database log entry is a first log entry in the common unit of recovery. | 0.673841 |
8,645,248 | 31 | 42 | 31. A computer implemented method of providing integrated customer communications, comprising: generating documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from at least one component of the account opening system, and static content for the templates received from a content repository, wherein said generating comprises: receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; managing documents associated with the communications; and maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; transmitting the communications via one or more transmission channels; managing the templates and the content; and storing, retrieving, and managing storage of the documents, wherein he managing the templates comprises creating, previewing, editing, maintaining and deleting communication templates for different channels, defining what data items are included in the communication, inserting dynamic variables that vary by at least one of channel and communication type, defining a source of the dynamic data for the communication, and making deployments to various environments for validation. | 31. A computer implemented method of providing integrated customer communications, comprising: generating documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from at least one component of the account opening system, and static content for the templates received from a content repository, wherein said generating comprises: receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; managing documents associated with the communications; and maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; transmitting the communications via one or more transmission channels; managing the templates and the content; and storing, retrieving, and managing storage of the documents, wherein he managing the templates comprises creating, previewing, editing, maintaining and deleting communication templates for different channels, defining what data items are included in the communication, inserting dynamic variables that vary by at least one of channel and communication type, defining a source of the dynamic data for the communication, and making deployments to various environments for validation. 42. The computer implemented method of providing customer communications of claim 31 , further comprising requesting the communications, wherein said requesting the communications comprises: selecting the template comprising at least one of header, footer, marketing, body, and web links; selecting a milestone comprising at least one of validate identity, decisioning, product configuration, funding, and boarding/fulfillment; selecting at least one of a message type, a brand, a line of business description, a language, a layout, and a channel; and entering the content and select images to be included in the document. | 0.5 |
7,716,576 | 1 | 6 | 1. A method of processing Extensible Markup Language (XML) documents, said method comprising: parsing an XML document comprising content in an XML format; converting said content into pcodes according to a conversion key, wherein said conversion key comprises a lookup table (LUT) comprising a plurality of XML tags, said XML tags each having a corresponding pcode, wherein an XML tag is converted into a pcode according to said conversion key and wherein said content converted into pcodes is convertible back to XML using said conversion key; representing a recurring sequence of different XML source code segments comprising multiple XML tags as a single same pcode, wherein said LUT further comprises an entry comprising said recurring sequence and said single pcode; generating a pcode file comprising said XML document parsed and converted into pcode, wherein said pcode file comprises said single pcode in lieu of each occurrence of said recurring sequence of XML tags; and forwarding said conversion key with said pcode file from one computer system to another computer system. | 1. A method of processing Extensible Markup Language (XML) documents, said method comprising: parsing an XML document comprising content in an XML format; converting said content into pcodes according to a conversion key, wherein said conversion key comprises a lookup table (LUT) comprising a plurality of XML tags, said XML tags each having a corresponding pcode, wherein an XML tag is converted into a pcode according to said conversion key and wherein said content converted into pcodes is convertible back to XML using said conversion key; representing a recurring sequence of different XML source code segments comprising multiple XML tags as a single same pcode, wherein said LUT further comprises an entry comprising said recurring sequence and said single pcode; generating a pcode file comprising said XML document parsed and converted into pcode, wherein said pcode file comprises said single pcode in lieu of each occurrence of said recurring sequence of XML tags; and forwarding said conversion key with said pcode file from one computer system to another computer system. 6. The method of claim 1 , further comprising processing said pcode file without converting said pcode file back to XML. | 0.775281 |
8,096,713 | 1 | 2 | 1. A hand-propelled printer, comprising: a scanner configured to scan a first copy of a project document including updates and configured to generate update data from the project document, wherein the update data is used to update a stored version of the project document in a database; a position module to determine position data of the hand-propelled printer in response to movement of the hand-propelled printer on a second copy of the project document, wherein the position data includes a location and an orientation of the hand-propelled printer relative to an origin and an initial orientation; and a processor configured to receive the update data corresponding to the updates made to the first copy of the project document and accessed from the database and configured to communicate print data to a print mechanism to selectively print the updates at correct locations on the second copy of the project document according to the position data. | 1. A hand-propelled printer, comprising: a scanner configured to scan a first copy of a project document including updates and configured to generate update data from the project document, wherein the update data is used to update a stored version of the project document in a database; a position module to determine position data of the hand-propelled printer in response to movement of the hand-propelled printer on a second copy of the project document, wherein the position data includes a location and an orientation of the hand-propelled printer relative to an origin and an initial orientation; and a processor configured to receive the update data corresponding to the updates made to the first copy of the project document and accessed from the database and configured to communicate print data to a print mechanism to selectively print the updates at correct locations on the second copy of the project document according to the position data. 2. The hand-propelled printer of claim 1 wherein the updates include revisions to elements in the project document. | 0.896583 |
9,633,116 | 1 | 9 | 1. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving, by a server comprising one or more computers, first endorsement information characterizing a first member's rating of a first local product or service provider, wherein the first member is in a member network and is provided with a financial incentive to endorse the first local product or service provider; receiving, by the server from a second member in the member network, a local search query comprising information identifying one or more items to be found and a geographic locale to be searched; identifying, using a member network engine available to the server, that there is an association between the first member and the second member, wherein the association comprises an explicit relationship between the first member and the second member or a common membership of the first member and the second member in a community of the member network, wherein the first member is explicitly related to at least one other member in the member network; ranking items responsive to the local search query based on a type of the association between the second member and the first member in the member network; and responding, by the server, to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items. | 1. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving, by a server comprising one or more computers, first endorsement information characterizing a first member's rating of a first local product or service provider, wherein the first member is in a member network and is provided with a financial incentive to endorse the first local product or service provider; receiving, by the server from a second member in the member network, a local search query comprising information identifying one or more items to be found and a geographic locale to be searched; identifying, using a member network engine available to the server, that there is an association between the first member and the second member, wherein the association comprises an explicit relationship between the first member and the second member or a common membership of the first member and the second member in a community of the member network, wherein the first member is explicitly related to at least one other member in the member network; ranking items responsive to the local search query based on a type of the association between the second member and the first member in the member network; and responding, by the server, to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items. 9. The computer storage medium of claim 1 , the operations comprising: receiving endorsement information characterizing a third member's rating of a second local product or service provider, wherein the third member is associated with the first member in the member network, and the association comprises an explicit relationship between the first member and the third member or a common membership of the first member and the third member in a community of the member network; and determining the items responsive to the local search query including the second local product or service provider, wherein the information describing the result set responsive to the local search query includes at least one identifier personally identifying the third member and indicating that endorsement information characterizing the third member's rating of the second local product or service provider has been received. | 0.5 |
8,311,967 | 19 | 20 | 19. A computer-readable storage device encoded with a computer program product, the computer program product comprising instructions that when executed on one or more computers cause the one or more computers to perform operations comprising: receiving a request from a client-subscriber computing system for access to a trained predictive model from a repository of trained predictive models, which trained predictive model can generate a predictive output in response to receiving input data having one or more input types, wherein the one or more input types can be determined from the request; determining from information that describes each of the trained predictive models in the predictive model repository that one or more models included in the predictive model repository match the request from the client-subscriber computing system, wherein determining a match is based at least in part on a comparison of the one or more input types determined from the request to input types included in the information that describes the trained predictive models; and providing access to at least one of the one or more models to the client-subscriber computing system; wherein the one or more models that match the request are models that were trained using training data provided by a computing system other than the client-subscriber computing system. | 19. A computer-readable storage device encoded with a computer program product, the computer program product comprising instructions that when executed on one or more computers cause the one or more computers to perform operations comprising: receiving a request from a client-subscriber computing system for access to a trained predictive model from a repository of trained predictive models, which trained predictive model can generate a predictive output in response to receiving input data having one or more input types, wherein the one or more input types can be determined from the request; determining from information that describes each of the trained predictive models in the predictive model repository that one or more models included in the predictive model repository match the request from the client-subscriber computing system, wherein determining a match is based at least in part on a comparison of the one or more input types determined from the request to input types included in the information that describes the trained predictive models; and providing access to at least one of the one or more models to the client-subscriber computing system; wherein the one or more models that match the request are models that were trained using training data provided by a computing system other than the client-subscriber computing system. 20. The computer-readable storage device of claim 19 , the operations further comprising: determining an output type for predictive output for the client-subscriber computing system, wherein: if the output type is included in the request, then determining the output type comprises receiving the output type in the request; and if the output type is not included in the request, then determining the output type comprises determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository are compatible with the one or more input types determined from the request to input types and that the one or more models can generate output of one or more output types, and selecting the output type from the one or more output types. | 0.5 |
9,141,690 | 13 | 15 | 13. An article of manufacture comprising a computer readable storage medium having content stored thereon, which when executed, cause a machine to perform operations including: receiving a query at a multitenant database system (MTS), wherein the MTS stores data for multiple client organizations each identified by a tenant identifier (ID) and one or more users are associated with the tenant ID, wherein the one or more users of each client organization access data identified by the tenant ID associated with the respective client organization, and wherein the multitenant database is hosted by an entity separate from the client organization; categorizing the semantic terms of the query into one or more categories based on a multidimensional categorization scheme stored in the MTS, the multidimensional categorization scheme associated with a tenant ID of a user that originated the query; accessing relationship metadata of records in the MTS previously categorized into one or more of the same categories as the query, including accessing first and second relationship types, wherein: the first relationship type metadata indicate a record relationship between one record in the MTS to another record in the MTS, and the second relationship type metadata indicate a category relationship between one of the categories of the one record in the MTS and other available categories of the multidimensional categorization scheme associated with the user's tenant ID, the category relationship based on a previously determined statistical similarity of the categories; retrieving records from the MTS: previously categorized into one or more of the same categories as the query, having record relationships with any of the already retrieved records, and previously categorized in a category having category relationships with one or more categories of any of the already retrieved records; computing a statistical likelihood that each retrieved record is a desired solution to the query meriting inclusion in a result set for the query, the statistical likelihood computed based on usage statistics accumulated for each retrieved record, including usage statistics accumulate for the record relationships and category relationships to other retrieved records; monitoring usage of the result set, including whether and for how long a record included in the result set is used, with greater usage associated with solutions of greater desirability and lesser usage associated with solutions of lesser desirability; and updating usage statistics indicating statistical similarity of records based on usage of the result set, including weighting more heavily records, record relationships and category relationships identified as being a desired solution to the query. | 13. An article of manufacture comprising a computer readable storage medium having content stored thereon, which when executed, cause a machine to perform operations including: receiving a query at a multitenant database system (MTS), wherein the MTS stores data for multiple client organizations each identified by a tenant identifier (ID) and one or more users are associated with the tenant ID, wherein the one or more users of each client organization access data identified by the tenant ID associated with the respective client organization, and wherein the multitenant database is hosted by an entity separate from the client organization; categorizing the semantic terms of the query into one or more categories based on a multidimensional categorization scheme stored in the MTS, the multidimensional categorization scheme associated with a tenant ID of a user that originated the query; accessing relationship metadata of records in the MTS previously categorized into one or more of the same categories as the query, including accessing first and second relationship types, wherein: the first relationship type metadata indicate a record relationship between one record in the MTS to another record in the MTS, and the second relationship type metadata indicate a category relationship between one of the categories of the one record in the MTS and other available categories of the multidimensional categorization scheme associated with the user's tenant ID, the category relationship based on a previously determined statistical similarity of the categories; retrieving records from the MTS: previously categorized into one or more of the same categories as the query, having record relationships with any of the already retrieved records, and previously categorized in a category having category relationships with one or more categories of any of the already retrieved records; computing a statistical likelihood that each retrieved record is a desired solution to the query meriting inclusion in a result set for the query, the statistical likelihood computed based on usage statistics accumulated for each retrieved record, including usage statistics accumulate for the record relationships and category relationships to other retrieved records; monitoring usage of the result set, including whether and for how long a record included in the result set is used, with greater usage associated with solutions of greater desirability and lesser usage associated with solutions of lesser desirability; and updating usage statistics indicating statistical similarity of records based on usage of the result set, including weighting more heavily records, record relationships and category relationships identified as being a desired solution to the query. 15. The article of manufacture of claim 13 , further comprising content to provide instructions for storing the query as a new record in the MTS, based on the stored multidimensional categorization scheme associated with the user's tenant ID. | 0.662953 |
9,734,410 | 5 | 6 | 5. The method of claim 1 , further comprising: providing a message representing the attentiveness data to the host device. | 5. The method of claim 1 , further comprising: providing a message representing the attentiveness data to the host device. 6. The method of claim 5 , wherein the message comprises at least one of: happy, confused, focused, bored, attentive, and understood. | 0.5 |
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