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7,657,458 | 1 | 5 | 1. An apparatus, comprising: a database that contains reviews and reviews information, locator code information, subject information, and user information; and a computer system configured to instantiate a review engine server that provides a first information to a user and receives a second information from said user and stores at least some of the second information in the database, wherein said first information includes at least a review form, and said second information includes at least a locator code, and further wherein said locator code references a unique transaction. | 1. An apparatus, comprising: a database that contains reviews and reviews information, locator code information, subject information, and user information; and a computer system configured to instantiate a review engine server that provides a first information to a user and receives a second information from said user and stores at least some of the second information in the database, wherein said first information includes at least a review form, and said second information includes at least a locator code, and further wherein said locator code references a unique transaction. 5. An apparatus as recited in claim 1 wherein said review engine server further includes a social network engine, a locator lookup module, and a subject lookup module. | 0.724422 |
9,436,777 | 1 | 2 | 1. A method comprising: receiving, by a server computer over a network from a computing device, a first request for search suggestions related to a first search query that has been input into a search term entry area displayed by a web browser executing on the computing device; transmitting in response to the first request, by the server computer over the network to the computing device, instructions for the computing device to display a plurality of search suggestions related to the first search query, each of plurality of the search suggestions representing content from a respective search results web page; setting, by the server computer, a cookie with a time stamp for the displaying of the plurality of the search suggestions related to the first search query; transmitting, by the server computer over the network, instructions to the computing device to receive an identified web page component that is part of at least one respective search results web page prior to an initial display of the respective search results web page by the computing device; transmitting, by the server computer over the network to the computing device, during the transmission of instructions to initially display the plurality of search suggestions related to the first search query, storage instructions that further cause the computing device to store in a memory of the computing device the web page component that is part of the at least one respective search results web page prior to initially displaying the respective search results web page; transmitting, by the server computer over the network instructions to the computing device, to visibly display the plurality of search suggestions related to the first search query transmitted by the server computer without visibly displaying the stored web page component during display of the plurality of search suggestions related to the first search query; receiving, by the server computer over the network, a second request for a second search suggestion related to a second search query; determining, by the server computer, that the time period associated with the timestamp of the cookie related to the first search query has not elapsed; and transmitting, by the server computer over the network, upon determination that the time period related to the first search query has not elapsed, instructions to the computing device to display a search suggestion related to the second search query prior to initially displaying the respective search results web page and further causing the computing device to store a web page component associated with a search results web page corresponding to the search suggestion related to the second search query. | 1. A method comprising: receiving, by a server computer over a network from a computing device, a first request for search suggestions related to a first search query that has been input into a search term entry area displayed by a web browser executing on the computing device; transmitting in response to the first request, by the server computer over the network to the computing device, instructions for the computing device to display a plurality of search suggestions related to the first search query, each of plurality of the search suggestions representing content from a respective search results web page; setting, by the server computer, a cookie with a time stamp for the displaying of the plurality of the search suggestions related to the first search query; transmitting, by the server computer over the network, instructions to the computing device to receive an identified web page component that is part of at least one respective search results web page prior to an initial display of the respective search results web page by the computing device; transmitting, by the server computer over the network to the computing device, during the transmission of instructions to initially display the plurality of search suggestions related to the first search query, storage instructions that further cause the computing device to store in a memory of the computing device the web page component that is part of the at least one respective search results web page prior to initially displaying the respective search results web page; transmitting, by the server computer over the network instructions to the computing device, to visibly display the plurality of search suggestions related to the first search query transmitted by the server computer without visibly displaying the stored web page component during display of the plurality of search suggestions related to the first search query; receiving, by the server computer over the network, a second request for a second search suggestion related to a second search query; determining, by the server computer, that the time period associated with the timestamp of the cookie related to the first search query has not elapsed; and transmitting, by the server computer over the network, upon determination that the time period related to the first search query has not elapsed, instructions to the computing device to display a search suggestion related to the second search query prior to initially displaying the respective search results web page and further causing the computing device to store a web page component associated with a search results web page corresponding to the search suggestion related to the second search query. 2. The method of claim 1 wherein the web page component comprises a selected web page asset identified as part of the respective search results web page. | 0.870777 |
9,158,794 | 7 | 8 | 7. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for creating an association between each of a plurality of media objects and temporal, spatial, social network and topical data including deriving relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data and interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media matching each criteria of multiple criteria included in a combined context, the combined context defined by social criteria, location criteria, topical criteria, and temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the location criteria describing a location or type of location associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for; locating a user profile associated with the user including one or more designations of favorite media of the user; logic executed by the processor for determining media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying a location associated with the request and determining media associated with the location based on the association; logic executed by the processor for identifying topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match each criteria included in the combined context based on the located user profile, determined media associated with the one or more people or types of people, media associated with the location, media associated with the identified topics, and media associated with the identified time; logic executed by the processor for assembling via the network a playlist containing a reference to the plurality of media files; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. | 7. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for creating an association between each of a plurality of media objects and temporal, spatial, social network and topical data including deriving relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data and interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media matching each criteria of multiple criteria included in a combined context, the combined context defined by social criteria, location criteria, topical criteria, and temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the location criteria describing a location or type of location associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for; locating a user profile associated with the user including one or more designations of favorite media of the user; logic executed by the processor for determining media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying a location associated with the request and determining media associated with the location based on the association; logic executed by the processor for identifying topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match each criteria included in the combined context based on the located user profile, determined media associated with the one or more people or types of people, media associated with the location, media associated with the identified topics, and media associated with the identified time; logic executed by the processor for assembling via the network a playlist containing a reference to the plurality of media files; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. 8. The system of claim 7 wherein the social criteria comprise criteria that match a plurality of users within a social network, and the preferences of the plurality of users are used when determining media associated with the one or more people or types of people defined by the social criteria. | 0.866031 |
9,235,917 | 9 | 12 | 9. A method comprising, at a processor: automatically detecting video compression information in at least a portion of at least one image frame of video content; associating metadata corresponding to the detected video compression information with the image frame by embedding the metadata with the at least one image frame to tightly couple the metadata to the at least one image frame to provide for metadata-to-content synchronization that is independent of playback performance, playback timing, and user interaction, wherein the metadata associates at least one multimedia element with the detected video compression information, and wherein upon rendering of the image frame, the multimedia element is to be overlaid on the at least a portion of the image frame based on the metadata. | 9. A method comprising, at a processor: automatically detecting video compression information in at least a portion of at least one image frame of video content; associating metadata corresponding to the detected video compression information with the image frame by embedding the metadata with the at least one image frame to tightly couple the metadata to the at least one image frame to provide for metadata-to-content synchronization that is independent of playback performance, playback timing, and user interaction, wherein the metadata associates at least one multimedia element with the detected video compression information, and wherein upon rendering of the image frame, the multimedia element is to be overlaid on the at least a portion of the image frame based on the metadata. 12. The method of claim 9 , wherein to automatically detect video compression information comprises to automatically detect at least one of scene change information and scene complexity information. | 0.772414 |
8,825,614 | 7 | 9 | 7. The method of claim 6 , further comprising searching for XBRL concepts matching search conditions within at least one searched entity selected from the group consisting of the received XBRL document and the first and second versions of the XBRL taxonomy. | 7. The method of claim 6 , further comprising searching for XBRL concepts matching search conditions within at least one searched entity selected from the group consisting of the received XBRL document and the first and second versions of the XBRL taxonomy. 9. The method of claim 7 , wherein the search conditions comprise searching for a deprecated XBRL concept in the second version of the XBRL taxonomy. | 0.964991 |
10,002,182 | 12 | 15 | 12. A system for computerized identification and presentation of semantic themes occurring in a set of electronic documents, the system comprising: one or more processors; and memory coupled to the one or more processors, the memory storing computer-executable instructions that, when executed, cause the one or more processors to: generate one or more topics by performing topic modeling on the set of electronic documents; output, using the topic modeling, a plurality of ordered lists of words, individual ones of the plurality of ordered lists of words corresponding to individual ones of the one or more topics, the ordered lists of words being arranged from top to bottom corresponding to highest to lowest probability in relation to the one or more topics; determine a first unused theme name from a first list of the plurality of ordered lists of words, wherein the first unused theme name is determined based at least in part on a first iterative process identifying a first unused word that is not on an already-used list starting from a top of the first list and moving toward a bottom of the first list; add the first unused theme name to the already-used list; determine a second unused theme name from a second list of the plurality of ordered lists of words, wherein the second unused theme name is determined based at least in part on a second iterative process identifying a second unused word that is not on the already-used list starting from a top of moving toward a bottom of the second list; add the second unused theme name to the already-used list; remove, for the individual ones of the plurality of ordered lists of words, one or more words at a bottom of an ordered list of words thereby providing a plurality of ordered lists of top keywords corresponding to individual ones of the one or more topics, wherein individual ones of the plurality of ordered lists of top keywords have up to a predetermined number of top keywords; and apply a matching algorithm to the plurality of ordered lists of top keywords to produce a plurality of reduced lists of keywords, individual ones of the plurality of reduced lists of keywords including a subset of keywords of the individual ones of the plurality of ordered lists of top keywords, the individual ones of the plurality of reduced lists of keywords corresponding to individual ones of the plurality of ordered lists of top keywords, such that a keyword from the plurality of ordered lists of top keywords appears in no more than a predetermined number of reduced lists of keywords of the plurality of reduced lists of keywords. | 12. A system for computerized identification and presentation of semantic themes occurring in a set of electronic documents, the system comprising: one or more processors; and memory coupled to the one or more processors, the memory storing computer-executable instructions that, when executed, cause the one or more processors to: generate one or more topics by performing topic modeling on the set of electronic documents; output, using the topic modeling, a plurality of ordered lists of words, individual ones of the plurality of ordered lists of words corresponding to individual ones of the one or more topics, the ordered lists of words being arranged from top to bottom corresponding to highest to lowest probability in relation to the one or more topics; determine a first unused theme name from a first list of the plurality of ordered lists of words, wherein the first unused theme name is determined based at least in part on a first iterative process identifying a first unused word that is not on an already-used list starting from a top of the first list and moving toward a bottom of the first list; add the first unused theme name to the already-used list; determine a second unused theme name from a second list of the plurality of ordered lists of words, wherein the second unused theme name is determined based at least in part on a second iterative process identifying a second unused word that is not on the already-used list starting from a top of moving toward a bottom of the second list; add the second unused theme name to the already-used list; remove, for the individual ones of the plurality of ordered lists of words, one or more words at a bottom of an ordered list of words thereby providing a plurality of ordered lists of top keywords corresponding to individual ones of the one or more topics, wherein individual ones of the plurality of ordered lists of top keywords have up to a predetermined number of top keywords; and apply a matching algorithm to the plurality of ordered lists of top keywords to produce a plurality of reduced lists of keywords, individual ones of the plurality of reduced lists of keywords including a subset of keywords of the individual ones of the plurality of ordered lists of top keywords, the individual ones of the plurality of reduced lists of keywords corresponding to individual ones of the plurality of ordered lists of top keywords, such that a keyword from the plurality of ordered lists of top keywords appears in no more than a predetermined number of reduced lists of keywords of the plurality of reduced lists of keywords. 15. The system according to claim 12 wherein the predetermined number of reduced lists of keywords is one. | 0.780083 |
9,741,336 | 2 | 4 | 2. The method of claim 1 , further comprising generating the audible response based on the set of dialog actions and via a machine learning algorithm. | 2. The method of claim 1 , further comprising generating the audible response based on the set of dialog actions and via a machine learning algorithm. 4. The method of claim 2 , wherein the machine learning algorithm augmented by the reinforcement learning is based on the partially observable Markov decision process. | 0.889404 |
9,141,383 | 3 | 16 | 3. The method of claim 1 , wherein the parent process includes a business process, and further including employing a BPEL extension activity to facilitate accessing the definition of the subprocess. | 3. The method of claim 1 , wherein the parent process includes a business process, and further including employing a BPEL extension activity to facilitate accessing the definition of the subprocess. 16. The method of claim 3 , wherein the definition of the subprocess is adapted to enable a portion of the subprocess to call the subprocess itself, thereby facilitating recursion. | 0.961407 |
7,664,767 | 11 | 14 | 11. A computer-implemented method comprising: accessing, over a network, content associated wit an electronic document made available on the network by a content provider; programmatically deriving, using at least one processor, business category information related to the electronic document from the accessed content associated wit the electronic document; storing information identifying the electronic document in an electronic data store in association with business category data corresponding to the derived business category information, thereby enabling subsequent business category-based searching to yield the electronic document; receiving a business category-based query from a user, the business category-based query being associated with a particular business category; determining, using at least one processor, whether the particular business category is related to the business category data corresponding to the derived business category information; and conditioned on the determining that the particular business category is related to the business category data corresponding to the derived business category information, returning a search result for the electronic document based on the information identifying the electronic document. | 11. A computer-implemented method comprising: accessing, over a network, content associated wit an electronic document made available on the network by a content provider; programmatically deriving, using at least one processor, business category information related to the electronic document from the accessed content associated wit the electronic document; storing information identifying the electronic document in an electronic data store in association with business category data corresponding to the derived business category information, thereby enabling subsequent business category-based searching to yield the electronic document; receiving a business category-based query from a user, the business category-based query being associated with a particular business category; determining, using at least one processor, whether the particular business category is related to the business category data corresponding to the derived business category information; and conditioned on the determining that the particular business category is related to the business category data corresponding to the derived business category information, returning a search result for the electronic document based on the information identifying the electronic document. 14. The method of claim 11 wherein accessing, over the network, content associated with the electronic document made available on the network by the content provider comprises automatically, without human intervention, accessing, over the network, the content associated with the electronic document using a hyperlink that is included in a different electronic document and that links to the electronic document. | 0.862207 |
7,818,678 | 11 | 12 | 11. The method of claim 10 , wherein each of said plurality of reviewers is uniquely identifiable by said network, and wherein the master data file includes information specifying review privileges for at least one of said plurality of reviewers. | 11. The method of claim 10 , wherein each of said plurality of reviewers is uniquely identifiable by said network, and wherein the master data file includes information specifying review privileges for at least one of said plurality of reviewers. 12. The method of claim 11 further comprising: displaying a subset of the edits in the secondary data file associated with a given reviewer. | 0.94701 |
9,798,724 | 9 | 15 | 9. A system for document discovery, comprising: a data repository storing a plurality of electronic documents, wherein each of the plurality of electronic documents comprises searchable metadata; a computer processor connected to the data repository that: receives a scan of a physical copy of a document comprising a non-text object; determines a first tag for the non-text object by comparing the non-text object with a plurality of templates comprising a plurality of tags, wherein the first tag defines a portion of the non-text object in an original file and specifies a type of the non-text object and a formatting attribute of the non-text object; generates, based on the first tag, non-text object metadata comprising composition information comprising the type and the formatting attribute for the non-text object; searches the plurality of electronic documents stored in the data repository with a search query comprising the non-text object metadata; compares the non-text object metadata with the searchable metadata; and provides a location of the original file to a user when the non-text object metadata in the search query matches the searchable metadata of the original file. | 9. A system for document discovery, comprising: a data repository storing a plurality of electronic documents, wherein each of the plurality of electronic documents comprises searchable metadata; a computer processor connected to the data repository that: receives a scan of a physical copy of a document comprising a non-text object; determines a first tag for the non-text object by comparing the non-text object with a plurality of templates comprising a plurality of tags, wherein the first tag defines a portion of the non-text object in an original file and specifies a type of the non-text object and a formatting attribute of the non-text object; generates, based on the first tag, non-text object metadata comprising composition information comprising the type and the formatting attribute for the non-text object; searches the plurality of electronic documents stored in the data repository with a search query comprising the non-text object metadata; compares the non-text object metadata with the searchable metadata; and provides a location of the original file to a user when the non-text object metadata in the search query matches the searchable metadata of the original file. 15. The system of claim 9 , wherein the data repository is part of an enterprise content management (ECM) system. | 0.88834 |
9,659,109 | 9 | 10 | 9. The method of claim 7 , wherein: determining the highest solution node comprises: storing a reference to a next-highest-branch query node of the query nodes, wherein the next-highest-branch query node is a query node of the query nodes in the ending-character subtree, the next-highest-branch query node is a child node of one of the query nodes traversed when determining the highest solution node, and the subtree score of the next-highest-branch query node is a next-highest score than the score of the highest solution node; and determining the subset of the solution nodes comprises: determining a next-highest solution node of the solution nodes from among a next-highest-branch subtree that is rooted at the next-highest-branch query node. | 9. The method of claim 7 , wherein: determining the highest solution node comprises: storing a reference to a next-highest-branch query node of the query nodes, wherein the next-highest-branch query node is a query node of the query nodes in the ending-character subtree, the next-highest-branch query node is a child node of one of the query nodes traversed when determining the highest solution node, and the subtree score of the next-highest-branch query node is a next-highest score than the score of the highest solution node; and determining the subset of the solution nodes comprises: determining a next-highest solution node of the solution nodes from among a next-highest-branch subtree that is rooted at the next-highest-branch query node. 10. The method of claim 9 , wherein: determining the next-highest solution node comprises: traversing the next-highest-branch subtree from the next-highest-branch query node to the next-highest solution node by repeatedly branching from a parent query node of the query nodes to a top child query node of the query nodes, wherein the subtree score of the top child query node is equal to the subtree score of the next-highest-branch query node. | 0.876598 |
7,487,190 | 1 | 3 | 1. An automatic method of indicating changes in a structured document implemented via a computer, the method comprising: determining that a unit of content in an updated version of a structured document and a related unit of content in a previous version of the structured documents are associated with the same entry, wherein determining comprises: accessing a base topic set having a single topic identifier associated with each unit of content in the previous version of the structured document; accessing an undated topic set having a single topic identifier associated with each unit of content in the updated version of the structured document; identifying a particular topic identifier in the updated topic set that corresponds to the same particular topic identifier in the base topic set comparing the unit of content associated with the particular topic identifier in the updated version of the structured document with the related unit of content associated with the particular topic identifier in the previous version of the structured document to determine whether the unit of content in the updated version of the structure document has been modified with respect to the related unit of content in the previous version of the structure document; generating a table of contents associated with the updated version of the structured document, the table of contents having one entry associated with each unit of content in the updated version of the structured document; and marking a first entry in the table of contents if the unit of content associated with the first entry has been modified a predetermined degree from a previous version of the content, wherein the predetermined degree is represented by a difference metric as determined by a content comparator, such that: in an event that the difference is counted as a modification, the difference metric represents each change in words, tags, and formatting, wherein the changes comprise changes in font, color, size, inserted content, and deleted content between the respective units of content in the updated version of the structured document and the previous version of the structured document; and in an event that not all differences are counted as modifications, changes are classified by type such that changes of meaning are classified in a different type than changes in form, wherein changes in form include rephrasing that does not change the meaning of the content, and the difference metric represents the number of changes of meaning within each unit of content. | 1. An automatic method of indicating changes in a structured document implemented via a computer, the method comprising: determining that a unit of content in an updated version of a structured document and a related unit of content in a previous version of the structured documents are associated with the same entry, wherein determining comprises: accessing a base topic set having a single topic identifier associated with each unit of content in the previous version of the structured document; accessing an undated topic set having a single topic identifier associated with each unit of content in the updated version of the structured document; identifying a particular topic identifier in the updated topic set that corresponds to the same particular topic identifier in the base topic set comparing the unit of content associated with the particular topic identifier in the updated version of the structured document with the related unit of content associated with the particular topic identifier in the previous version of the structured document to determine whether the unit of content in the updated version of the structure document has been modified with respect to the related unit of content in the previous version of the structure document; generating a table of contents associated with the updated version of the structured document, the table of contents having one entry associated with each unit of content in the updated version of the structured document; and marking a first entry in the table of contents if the unit of content associated with the first entry has been modified a predetermined degree from a previous version of the content, wherein the predetermined degree is represented by a difference metric as determined by a content comparator, such that: in an event that the difference is counted as a modification, the difference metric represents each change in words, tags, and formatting, wherein the changes comprise changes in font, color, size, inserted content, and deleted content between the respective units of content in the updated version of the structured document and the previous version of the structured document; and in an event that not all differences are counted as modifications, changes are classified by type such that changes of meaning are classified in a different type than changes in form, wherein changes in form include rephrasing that does not change the meaning of the content, and the difference metric represents the number of changes of meaning within each unit of content. 3. A method as recited in claim 1 further comprising classifying one or more modifications in a unit of content associated with a marked entry by a modification type. | 0.889481 |
9,824,404 | 8 | 13 | 8. The method of claim 7 wherein the social commerce connection further includes a social media index value. | 8. The method of claim 7 wherein the social commerce connection further includes a social media index value. 13. The method of claim 8 further comprising: re-calculating automatically from the first cloud application a social media index value associated with the social commerce connection for the selected social media merchant; and storing from the first cloud application the re-calculated social media index value in the pre-determined search index structure in the stored cloud storage objects for the selected social media merchant. | 0.976261 |
10,146,865 | 6 | 10 | 6. A method for processing non-semantic visual input data to organize the non-semantic visual input data so that the non-semantic visual input data is readily accessible by both a human and a computing device, by describing the non-semantic visual input data semantically, comprising: (a) enabling a user to select and access portions of the non-semantic visual input data that have not yet been tagged with asserts, for tagging with asserts according to defined criteria; (b) selecting elements in the portions of the non-semantic visual input data that have been tagged with asserts, for further processing, wherein one type selected from a plurality of different types is assigned to each selected element, each type that is assigned being associated with a corresponding assert; (c) generating additional asserts that connect the asserts associated with each type of element, to properties of said element; and (d) for one or more types assigned to the selected elements, enabling one or more additional properties having their own tagonomy to be associated with the selected elements, wherein the asserts and properties associated with the non-semantic visual input data are in a form that enables the non-semantic visual input data to be readily accessed and queried by both a human and a computing device. | 6. A method for processing non-semantic visual input data to organize the non-semantic visual input data so that the non-semantic visual input data is readily accessible by both a human and a computing device, by describing the non-semantic visual input data semantically, comprising: (a) enabling a user to select and access portions of the non-semantic visual input data that have not yet been tagged with asserts, for tagging with asserts according to defined criteria; (b) selecting elements in the portions of the non-semantic visual input data that have been tagged with asserts, for further processing, wherein one type selected from a plurality of different types is assigned to each selected element, each type that is assigned being associated with a corresponding assert; (c) generating additional asserts that connect the asserts associated with each type of element, to properties of said element; and (d) for one or more types assigned to the selected elements, enabling one or more additional properties having their own tagonomy to be associated with the selected elements, wherein the asserts and properties associated with the non-semantic visual input data are in a form that enables the non-semantic visual input data to be readily accessed and queried by both a human and a computing device. 10. The method of claim 6 , further comprising using a tagonomy editor to specify a tagonomy node for an element selected in the non-semantic visual input data and to associate one or more ontologies with the tagonomy node. | 0.863692 |
8,224,832 | 20 | 21 | 20. The system of claim 19 , wherein the identifying of one or more differences occurs at specified intervals. | 20. The system of claim 19 , wherein the identifying of one or more differences occurs at specified intervals. 21. The system of claim 20 , wherein providing notification comprises providing notification for display on one or more electronic display devices. | 0.953774 |
4,685,135 | 20 | 21 | 20. The system of claim 19 wherein said pitch parameter-designating means includes means for designating a delta pitch parameter for limiting the amplitude of the primary or secondary stress. | 20. The system of claim 19 wherein said pitch parameter-designating means includes means for designating a delta pitch parameter for limiting the amplitude of the primary or secondary stress. 21. The system of claim 20 wherein each frame comprises a signal indicating whether or not the frame is the end of the allophone. | 0.969212 |
7,537,170 | 19 | 20 | 19. A method comprising: using a printing device: i) providing a first set of print structures on a surface with first ink, and ii) providing a second set of print structures on the surface with optical variable ink, the second set of print structures comprises breaks in one or more lines, with the second set of print structures conveying a machine-readable plural-bit auxiliary signal, the second set of print structure are provided to cooperate with the first set of print structures so that at a first observation angle the first set of print structures and the second set of print structures appear to provide a first visibly perceptible feature, and at a second observation angle the second set of print structures appear less observable so that the first set of print structures and the second set of print structures provide a second visibly perceptible feature. | 19. A method comprising: using a printing device: i) providing a first set of print structures on a surface with first ink, and ii) providing a second set of print structures on the surface with optical variable ink, the second set of print structures comprises breaks in one or more lines, with the second set of print structures conveying a machine-readable plural-bit auxiliary signal, the second set of print structure are provided to cooperate with the first set of print structures so that at a first observation angle the first set of print structures and the second set of print structures appear to provide a first visibly perceptible feature, and at a second observation angle the second set of print structures appear less observable so that the first set of print structures and the second set of print structures provide a second visibly perceptible feature. 20. The method of claim 19 where the first set of print structures and the second set of print structures comprise lines at the first observation angle. | 0.58011 |
8,290,924 | 1 | 10 | 1. A method to answer a query, comprising: saving, in a first database, website classifications of websites based on contents; receiving keywords in the query; determining query specifications from the keywords, the query specifications being website classifications of websites that may contain an answer to the query; determining a group of websites based on the query specifications and the website classifications saved in the first database; selecting a website from the group based on credibility of the websites saved in a second database; searching web pages of the website for the answer; selecting the answer from the web pages; and transmitting the answer. | 1. A method to answer a query, comprising: saving, in a first database, website classifications of websites based on contents; receiving keywords in the query; determining query specifications from the keywords, the query specifications being website classifications of websites that may contain an answer to the query; determining a group of websites based on the query specifications and the website classifications saved in the first database; selecting a website from the group based on credibility of the websites saved in a second database; searching web pages of the website for the answer; selecting the answer from the web pages; and transmitting the answer. 10. The method of claim 1 , further comprising prompting and receiving feedback on answer accuracy, wherein the credibility of the websites saved in the second database is based on the feedback on answer accuracy. | 0.839608 |
8,490,003 | 8 | 12 | 8. A system for proximity based text exchange comprising: one or more processors; at least one memory storing program instructions executable by the one or more processors; a message handler, comprising at least a portion of the program instructions, able to receive a text exchange associated with a distance value, wherein the text exchange is conveyed by an text exchange application, wherein the text exchange application is linked to a group session comprising of a plurality of participants, wherein the text exchange is a real-time text based communication between the plurality of participants utilizing a plurality of computing devices; and a proximity engine, comprising at least a portion of the program instructions, configured to identify a distance value associated with the text exchange and determine at least one recipient of the received text exchange based on the distance value associated with the proximity exchange and the proximity value associated with the at least one recipient; and an engine, comprising at least a portion of the program instructions, configured to communicate the proximity exchange to a computing device utilized by the determined at least one recipient when the proximity value of the at east one recipient is equivalent to the distance value of the proximity exchange. | 8. A system for proximity based text exchange comprising: one or more processors; at least one memory storing program instructions executable by the one or more processors; a message handler, comprising at least a portion of the program instructions, able to receive a text exchange associated with a distance value, wherein the text exchange is conveyed by an text exchange application, wherein the text exchange application is linked to a group session comprising of a plurality of participants, wherein the text exchange is a real-time text based communication between the plurality of participants utilizing a plurality of computing devices; and a proximity engine, comprising at least a portion of the program instructions, configured to identify a distance value associated with the text exchange and determine at least one recipient of the received text exchange based on the distance value associated with the proximity exchange and the proximity value associated with the at least one recipient; and an engine, comprising at least a portion of the program instructions, configured to communicate the proximity exchange to a computing device utilized by the determined at least one recipient when the proximity value of the at east one recipient is equivalent to the distance value of the proximity exchange. 12. The system of claim 8 , wherein the system is a middleware software associated with an IBM LOTUS SAMETIME. | 0.898524 |
8,381,299 | 33 | 35 | 33. The medium of claim 32 , the method further comprising: defining a second window in the input dataset; identifying second matching n-grams by determining whether the first input n-grams in the second window correspond to one of the first plurality of distinct training n-grams; and computing a second anomaly detection score for the input dataset using the second matching n-grams and first plurality of appearance frequencies. | 33. The medium of claim 32 , the method further comprising: defining a second window in the input dataset; identifying second matching n-grams by determining whether the first input n-grams in the second window correspond to one of the first plurality of distinct training n-grams; and computing a second anomaly detection score for the input dataset using the second matching n-grams and first plurality of appearance frequencies. 35. The medium of claim 33 , wherein the plurality of n-grams in the training dataset also includes a second plurality of distinct training n-grams that are each a second size, and the input dataset also includes second input n-grams that are each the second size, and wherein the method further comprises: computing a second plurality of appearance frequencies, wherein each of the second plurality of appearance frequencies corresponds to one of the second plurality of distinct training n-grams; identifying third matching n-grams by determining whether the second input n-grams in the first window correspond to one of the second plurality of distinct training n-grams; computing a third anomaly detection score for the input dataset using the third matching n-grams and the second plurality of appearance frequencies; and determining based upon the third anomaly detection score whether the input dataset contains an anomaly. | 0.871476 |
7,590,933 | 1 | 11 | 1. A computer-executed method of displaying changes to a data file comprising: associating an annotation with a programming module of a baseline file on a computer; displaying on a display of the computer in an unsegmented window of a graphical user interface the baseline file as a tree structure having a plurality of nodes, each node representing a programming module of the baseline file; and displaying the annotation, on the display of the computer in the unsegmented window of the graphical user interface, proximate to the node that represents the programming module with which the annotation is associated, the annotation including a plurality of selectable messages displayed proximate to each other in order to facilitate visual comparison, each selectable message describing a modification made to the baseline file by a different contributor, the annotation indicating that the modifications produce a conflict, the conflict being resolvable within the unsegmented window by a selection of one of the selectable messages. | 1. A computer-executed method of displaying changes to a data file comprising: associating an annotation with a programming module of a baseline file on a computer; displaying on a display of the computer in an unsegmented window of a graphical user interface the baseline file as a tree structure having a plurality of nodes, each node representing a programming module of the baseline file; and displaying the annotation, on the display of the computer in the unsegmented window of the graphical user interface, proximate to the node that represents the programming module with which the annotation is associated, the annotation including a plurality of selectable messages displayed proximate to each other in order to facilitate visual comparison, each selectable message describing a modification made to the baseline file by a different contributor, the annotation indicating that the modifications produce a conflict, the conflict being resolvable within the unsegmented window by a selection of one of the selectable messages. 11. The computer-executed method of claim 1 , further comprising generating an annotation file by: generating a copy of the baseline file; comparing contributor files with the copy of the baseline file to identify one or more modifications by each contributor to the baseline file; incorporating each identified modification as an annotation in the copy of the baseline file; storing the copy of the baseline file with the annotations as the annotation file. | 0.501089 |
8,495,680 | 25 | 26 | 25. The non-transitory computer-readable storage medium according to claim 18 , further comprising instructions for parameterizing the viewer's monitor behavior with a pseudo hidden Markov process. | 25. The non-transitory computer-readable storage medium according to claim 18 , further comprising instructions for parameterizing the viewer's monitor behavior with a pseudo hidden Markov process. 26. The non-transitory computer-readable storage medium according to claim 25 , wherein the pseudo hidden Markov process is a double random process. | 0.963384 |
10,127,901 | 11 | 19 | 11. A computer storage device, having computer-executable instructions that, when executed by at least one processor, perform a method for converting text-to-speech, the method comprising: receiving text input into a plurality of first level recurrent neural networks; determining, by a first recurrent neural network in the plurality of first level recurrent neural networks, one or more properties of the text input from the group consisting of: part-of-speech properties, phonemes, linguistic prosody properties, contextual properties, and semantic properties; determining, by a second recurrent neural network in the plurality of first level recurrent neural networks, one or more properties of the text input from the group consisting of: part-of-speech properties, phonemes, linguistic prosody properties, contextual properties, and semantic properties, wherein the determined one or properties by the second recurrent neural network is different from the determined one or more properties by the first recurrent neural network; receiving, by a recurrent neural network in a second level, the determined properties from the first recurrent neural network in the plurality of first level recurrent neural networks and the second recurrent neural networks in the plurality of first level recurrent neural networks; determining by the recurrent neural network in the second level, phonetic properties for the text input based on the properties received from the first recurrent neural network in the plurality of first level recurrent neural networks and the second neural network in the plurality of first level recurrent neural networks, wherein the recurrent neural network in the second level is different from the first recurrent neural network in the plurality of first level recurrent neural networks and the second recurrent neural network in the plurality of first level recurrent neural networks; and based on the determined phonetic properties, generating a generation sequence for synthetization by an audio synthesizer. | 11. A computer storage device, having computer-executable instructions that, when executed by at least one processor, perform a method for converting text-to-speech, the method comprising: receiving text input into a plurality of first level recurrent neural networks; determining, by a first recurrent neural network in the plurality of first level recurrent neural networks, one or more properties of the text input from the group consisting of: part-of-speech properties, phonemes, linguistic prosody properties, contextual properties, and semantic properties; determining, by a second recurrent neural network in the plurality of first level recurrent neural networks, one or more properties of the text input from the group consisting of: part-of-speech properties, phonemes, linguistic prosody properties, contextual properties, and semantic properties, wherein the determined one or properties by the second recurrent neural network is different from the determined one or more properties by the first recurrent neural network; receiving, by a recurrent neural network in a second level, the determined properties from the first recurrent neural network in the plurality of first level recurrent neural networks and the second recurrent neural networks in the plurality of first level recurrent neural networks; determining by the recurrent neural network in the second level, phonetic properties for the text input based on the properties received from the first recurrent neural network in the plurality of first level recurrent neural networks and the second neural network in the plurality of first level recurrent neural networks, wherein the recurrent neural network in the second level is different from the first recurrent neural network in the plurality of first level recurrent neural networks and the second recurrent neural network in the plurality of first level recurrent neural networks; and based on the determined phonetic properties, generating a generation sequence for synthetization by an audio synthesizer. 19. The computer storage device of claim 11 , wherein the one or more properties are received by a hidden layer and an output layer of the recurrent neural network in the second level. | 0.502703 |
8,635,223 | 9 | 14 | 9. A method for providing a classification suggestion for electronically stored information, comprising the steps of: maintaining a corpus of electronically stored information (ESI) comprising reference ESI items each associated with a classification and uncoded ESI items; providing a cluster of uncoded ESI items and reference ESI items; determining a neighborhood of reference ESI items in the cluster for at least one of the uncoded ESI items; determining a classification of the neighborhood using a classifier; suggesting the classification of the neighborhood as a suggested classification code for the at least one uncoded ESI item; assigning a further classification code to the at least one uncoded ESI item based on instructions from a user; identifying a difference between the assigned classification code and the suggested classification code; and displaying the difference between the assigned classification code and the suggested classification code, wherein the steps are performed by a suitably programmed computer. | 9. A method for providing a classification suggestion for electronically stored information, comprising the steps of: maintaining a corpus of electronically stored information (ESI) comprising reference ESI items each associated with a classification and uncoded ESI items; providing a cluster of uncoded ESI items and reference ESI items; determining a neighborhood of reference ESI items in the cluster for at least one of the uncoded ESI items; determining a classification of the neighborhood using a classifier; suggesting the classification of the neighborhood as a suggested classification code for the at least one uncoded ESI item; assigning a further classification code to the at least one uncoded ESI item based on instructions from a user; identifying a difference between the assigned classification code and the suggested classification code; and displaying the difference between the assigned classification code and the suggested classification code, wherein the steps are performed by a suitably programmed computer. 14. The method according to claim 9 , further comprising: determining a distance metric based on the similarity of each reference ESI item in the neighborhood to the at least one uncoded ESI item; summing the distance metrics of the reference ESI items associated with the same classification; averaging the sums of the distance metrics in each classification; and assigning the classification of the reference ESI items in the neighborhood with the closest average distance metric as the classification of the neighborhood. | 0.612999 |
10,027,346 | 15 | 20 | 15. The method of claim 14 , said maintaining the sorted list comprises: (a) incrementing a first frequency of a first symbol associated with a token of the stream received from the first hardware engine; and (b) repeatedly swapping locations of the first symbol and a second symbol just above the first symbol in the sorted list while the first frequency is greater than a second frequency of the second symbol. | 15. The method of claim 14 , said maintaining the sorted list comprises: (a) incrementing a first frequency of a first symbol associated with a token of the stream received from the first hardware engine; and (b) repeatedly swapping locations of the first symbol and a second symbol just above the first symbol in the sorted list while the first frequency is greater than a second frequency of the second symbol. 20. The method of claim 15 , further comprising: maintaining a frequency table having an entry for each symbol, the frequency table is indexed by symbol value, each entry of the frequency table holds the frequency of occurrence of the symbol; each entry of the sorted list holds the value of the symbol; and each entry of the frequency table also holds an index into the entry of the sorted list holding the symbol value that indexes into the frequency table. | 0.664964 |
9,798,776 | 8 | 9 | 8. A computer system for parsing a search query, comprising: a memory device that stores a set of instructions; and at least one processor to execute the set of instructions to: identify a sequence of character substrings in a character string; generate context objects for performing a search, the context objects including associations between search categories and character sub strings; store, in a first context object, an association between a first search category and a first character substring in the sequence of character sub strings; compare a second character substring in the sequence of character substrings and a second search category; determine that the first character substring in the sequence of character substrings corresponds to a third search category; store, in a second context object, an association between the third search category and the first character substring; and search indexed information using at least the second context object. | 8. A computer system for parsing a search query, comprising: a memory device that stores a set of instructions; and at least one processor to execute the set of instructions to: identify a sequence of character substrings in a character string; generate context objects for performing a search, the context objects including associations between search categories and character sub strings; store, in a first context object, an association between a first search category and a first character substring in the sequence of character sub strings; compare a second character substring in the sequence of character substrings and a second search category; determine that the first character substring in the sequence of character substrings corresponds to a third search category; store, in a second context object, an association between the third search category and the first character substring; and search indexed information using at least the second context object. 9. The computer system of claim 8 , wherein the third search category represents part of a geographical address. | 0.903945 |
7,788,248 | 54 | 55 | 54. The apparatus of claim 52 , wherein the returned web page includes results returned from the query submitted to the search engine. | 54. The apparatus of claim 52 , wherein the returned web page includes results returned from the query submitted to the search engine. 55. The apparatus of claim 54 , further comprising: means for receiving a selection of a first result from the returned web page, the first result associated with a first uniform resource locator (URL); means for displaying a first web page associated with the first URL; means for preventing the first web page from controlling the focus; and means for permitting the first web page to control the focus if no additional input is received within the search field within a predetermined period of time. | 0.85407 |
8,265,778 | 12 | 14 | 12. An apparatus comprising: a monitor arranged to monitor a stream of events occurring at the apparatus and, for each event, to detect a plurality of features describing the event, at least some of which are related in a hierarchical manner; a memory storing a tree-based graphical data structure comprising layers of parent and child variable nodes connected by edges, wherein weights associated with the features describing the event are represented by variable nodes and the variable nodes are connected such that sequences of connected variable nodes represent the hierarchical relations between features; a processor arranged to store at each variable node of the graphical data structure, statistics describing a probability distribution representing a latent event score; a training engine arranged to update the statistics on the basis of the monitored event by using a Bayesian machine learning process and also such that latent event score information is propagated along the sequences of variable nodes which represent the hierarchical relations; a prediction engine arranged to predict an event using the graphical data structure; and a controller arranged to use the predicted event to control the apparatus. | 12. An apparatus comprising: a monitor arranged to monitor a stream of events occurring at the apparatus and, for each event, to detect a plurality of features describing the event, at least some of which are related in a hierarchical manner; a memory storing a tree-based graphical data structure comprising layers of parent and child variable nodes connected by edges, wherein weights associated with the features describing the event are represented by variable nodes and the variable nodes are connected such that sequences of connected variable nodes represent the hierarchical relations between features; a processor arranged to store at each variable node of the graphical data structure, statistics describing a probability distribution representing a latent event score; a training engine arranged to update the statistics on the basis of the monitored event by using a Bayesian machine learning process and also such that latent event score information is propagated along the sequences of variable nodes which represent the hierarchical relations; a prediction engine arranged to predict an event using the graphical data structure; and a controller arranged to use the predicted event to control the apparatus. 14. An apparatus as claimed in claim 12 wherein the graphical data structure comprises a level noise variable node at each layer of variable nodes. | 0.853 |
9,462,110 | 1 | 6 | 1. A method comprising: a mobile station making a first determination that the mobile station is moving at greater than a threshold rate; the mobile station making a second determination that, while the mobile station is moving at greater than the threshold rate, outgoing text messaging from the mobile station reflects more than a threshold degradation in typing proficiency; and in response to making the first and second determinations, the mobile station performing at least one action selected from the group consisting of (i) disabling visible presentation of received text messages and (ii) disabling manual keying of text messages. | 1. A method comprising: a mobile station making a first determination that the mobile station is moving at greater than a threshold rate; the mobile station making a second determination that, while the mobile station is moving at greater than the threshold rate, outgoing text messaging from the mobile station reflects more than a threshold degradation in typing proficiency; and in response to making the first and second determinations, the mobile station performing at least one action selected from the group consisting of (i) disabling visible presentation of received text messages and (ii) disabling manual keying of text messages. 6. The method of claim 1 , wherein the mobile station making the first determination comprises the mobile station using a positioning technology. | 0.846723 |
7,945,888 | 1 | 11 | 1. A method for verification of a hardware system-under-test including at least one processor, the method comprising: building an executable image of a hardware exerciser, wherein the hardware exerciser is adapted to control a test cycle of the hardware system-under-test, wherein the test cycle comprises at least generation and execution of a test; said building comprises embedding in the executable image data corresponding to: architectural knowledge of the system-under-test, testing knowledge of the system-under-test, and a test template for the system-under-test, wherein said test template is defined in a formal language and includes biasing directives to control one or more parameters of a randomly generated test of said system-under-test; wherein said building further comprises storing the executable image in a non-transitory computer readable medium; and wherein said executable image of the hardware exerciser is configured to be executed by the hardware system-under-test. | 1. A method for verification of a hardware system-under-test including at least one processor, the method comprising: building an executable image of a hardware exerciser, wherein the hardware exerciser is adapted to control a test cycle of the hardware system-under-test, wherein the test cycle comprises at least generation and execution of a test; said building comprises embedding in the executable image data corresponding to: architectural knowledge of the system-under-test, testing knowledge of the system-under-test, and a test template for the system-under-test, wherein said test template is defined in a formal language and includes biasing directives to control one or more parameters of a randomly generated test of said system-under-test; wherein said building further comprises storing the executable image in a non-transitory computer readable medium; and wherein said executable image of the hardware exerciser is configured to be executed by the hardware system-under-test. 11. The method of claim 1 , wherein the hardware exerciser is a bare-metal tool. | 0.957265 |
9,165,055 | 1 | 8 | 1. A computer implemented method for processing data, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term, wherein at least a portion of the identified content is stored in the database; and associating the at least one term with the identified content; wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers and are used to link the identified content with the at least one term. | 1. A computer implemented method for processing data, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more documents to identify at least one term based on at least one rule; identifying content for the at least one term, wherein at least a portion of the identified content is stored in the database; and associating the at least one term with the identified content; wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers and are used to link the identified content with the at least one term. 8. The method of claim 1 , wherein the content comprises one or more of text, image, sound, video and mixed media. | 0.768293 |
8,566,154 | 31 | 32 | 31. The system according to claim 30 , wherein a re-targeted advertisement is created for the user if the user made more than one recent visit to the Web site to review a product, but did not purchase the product. | 31. The system according to claim 30 , wherein a re-targeted advertisement is created for the user if the user made more than one recent visit to the Web site to review a product, but did not purchase the product. 32. The system according to claim 31 , wherein the re-targeted advertisement created for the user is a coupon to purchase the product at the Web site. | 0.950364 |
7,904,876 | 20 | 26 | 20. The medium of claim 19 wherein the interactive graphics language format is an interactive vector graphics language format. | 20. The medium of claim 19 wherein the interactive graphics language format is an interactive vector graphics language format. 26. The medium of claim 20 , wherein the view of graphical block diagram model is displayed in the interactive graphics language format using an interactive graphics viewer. | 0.911464 |
9,153,233 | 1 | 6 | 1. A voice-controlled data system, comprising: a storage medium for storing media files, the media files comprising audio files and including associated file identification data for allowing the identification of the media files, where the file identification data associated with each audio file includes first phonetic information that corresponds to first phonetic rules for pronouncing an artist and a song title associated with the audio file and second phonetic information that corresponds to second phonetic rules for pronouncing the artist and the song title associated with the audio file, where the first phonetic information and the second phonetic information included in the file identification data are part of the audio file; a static vocabulary list including phonetic transcriptions of corresponding user commands; a phonetic data extraction unit for extracting the first phonetic information and the second phonetic information from the file identification data; a speech recognition unit for receiving voice data from a user, the voice data including a static vocabulary and a variable vocabulary, the static vocabulary including a user command and the variable vocabulary including the artist and the song title associated with a desired media file, where the speech recognition unit is configured to generate a control command based on comparing the received voice data to the phonetic transcriptions of the static vocabulary list and the first phonetic information and the second phonetic information extracted by the phonetic data extraction unit; and a media player for playing the media files, the media player configured to select a media file based on the control command received from the speech recognition unit. | 1. A voice-controlled data system, comprising: a storage medium for storing media files, the media files comprising audio files and including associated file identification data for allowing the identification of the media files, where the file identification data associated with each audio file includes first phonetic information that corresponds to first phonetic rules for pronouncing an artist and a song title associated with the audio file and second phonetic information that corresponds to second phonetic rules for pronouncing the artist and the song title associated with the audio file, where the first phonetic information and the second phonetic information included in the file identification data are part of the audio file; a static vocabulary list including phonetic transcriptions of corresponding user commands; a phonetic data extraction unit for extracting the first phonetic information and the second phonetic information from the file identification data; a speech recognition unit for receiving voice data from a user, the voice data including a static vocabulary and a variable vocabulary, the static vocabulary including a user command and the variable vocabulary including the artist and the song title associated with a desired media file, where the speech recognition unit is configured to generate a control command based on comparing the received voice data to the phonetic transcriptions of the static vocabulary list and the first phonetic information and the second phonetic information extracted by the phonetic data extraction unit; and a media player for playing the media files, the media player configured to select a media file based on the control command received from the speech recognition unit. 6. The data system of claim 1 , where the first phonetic rules correspond to a first language and the second phonetic rules correspond to a second language. | 0.856089 |
10,114,612 | 2 | 3 | 2. The method of claim 1 , wherein the media interconnection graph links information comprising actors, directors, composers, titles, and locations. | 2. The method of claim 1 , wherein the media interconnection graph links information comprising actors, directors, composers, titles, and locations. 3. The method of claim 2 , wherein the constructing of the media interconnection graph is further based on common information in two media. | 0.927149 |
9,092,405 | 22 | 26 | 22. A computer-implemented method for presenting versions of network resources, the method comprising: under the control of a network computing component executing on one or more physical computing components of a network computing provider, the physical computing components configured to execute specific instructions, retrieving, from an electronic data store, a plurality of historical representations of a network resource as previously obtained from a content provider, the plurality of historical representations obtained from the content provider in response to a plurality of browse session requests for the network resource received from a particular client computing device at one or more previous times, wherein the content provider is separate from the network computing component; determining at least one difference between at least two of the plurality of historical representations; and generating a user interface comprising an interactive timeline and at least two objects, each object of the at least two objects comprising a visual representation of a corresponding one of the at least two historical representations, wherein a first object of the at least two objects comprises a visual indicator of the at least one difference, wherein a second object of the at least two objects is at least partially obscured by display of the first object, and wherein display of the first object is at least partially replaced by display of the second object in response to a user interaction with the interactive timeline. | 22. A computer-implemented method for presenting versions of network resources, the method comprising: under the control of a network computing component executing on one or more physical computing components of a network computing provider, the physical computing components configured to execute specific instructions, retrieving, from an electronic data store, a plurality of historical representations of a network resource as previously obtained from a content provider, the plurality of historical representations obtained from the content provider in response to a plurality of browse session requests for the network resource received from a particular client computing device at one or more previous times, wherein the content provider is separate from the network computing component; determining at least one difference between at least two of the plurality of historical representations; and generating a user interface comprising an interactive timeline and at least two objects, each object of the at least two objects comprising a visual representation of a corresponding one of the at least two historical representations, wherein a first object of the at least two objects comprises a visual indicator of the at least one difference, wherein a second object of the at least two objects is at least partially obscured by display of the first object, and wherein display of the first object is at least partially replaced by display of the second object in response to a user interaction with the interactive timeline. 26. The computer-implemented method of claim 22 , wherein generating the visual indicator comprises altering a historical representation to include the visual indicator when displayed. | 0.764103 |
7,966,172 | 1 | 3 | 1. A method for creating an expression to specify a subset of data, comprising: receiving a selection of a command; in response to receiving the selection of the command, displaying a natural language expression that includes the command and at least a first changeable field embedded in the displayed natural language expression; receiving a indication of first data for the first changeable embedded field from a direct interaction with the displayed natural language expression; modifying the natural language expression in response to the first data and displaying the modified natural language expression; displaying an add field indicator; receiving a selection of the add field indicator from a direct interaction with the displayed natural language expression; in response to the selection of the add field indicator, adding a second changeable field embedded in the natural language expression and displaying the natural language expression with the second changeable field embedded in the displayed natural language expression; receiving an indication of second data for the second changeable embedded field from a direct interaction with the displayed natural language expression; and modifying the natural language expression in response to the second data and displaying the modified natural language expression. | 1. A method for creating an expression to specify a subset of data, comprising: receiving a selection of a command; in response to receiving the selection of the command, displaying a natural language expression that includes the command and at least a first changeable field embedded in the displayed natural language expression; receiving a indication of first data for the first changeable embedded field from a direct interaction with the displayed natural language expression; modifying the natural language expression in response to the first data and displaying the modified natural language expression; displaying an add field indicator; receiving a selection of the add field indicator from a direct interaction with the displayed natural language expression; in response to the selection of the add field indicator, adding a second changeable field embedded in the natural language expression and displaying the natural language expression with the second changeable field embedded in the displayed natural language expression; receiving an indication of second data for the second changeable embedded field from a direct interaction with the displayed natural language expression; and modifying the natural language expression in response to the second data and displaying the modified natural language expression. 3. The method of claim 1 , further comprising: displaying a first remove field indicator, the first remove field indicator is associated with a first changeable embedded field displayed in the natural language expression; displaying a second remove field indicator, the second remove field indicator is associated with a set of multiple changeable embedded fields displayed in the natural language expression, the set of multiple changeable embedded fields includes the first changeable embedded field; modifying the natural language expression by removing the first changeable embedded field from the natural language expression and displaying the modified natural language expression, if a selection of the first remove field indicator is received; and modifying the natural language expression by removing the set of multiple changeable embedded fields from the natural language expression and displaying the modified natural language expression, if a selection of the second remove field indicator is received. | 0.635252 |
8,605,039 | 1 | 10 | 1. An apparatus comprising a controller, arranged to: receive input identifying a touch point at a first position wherein said input is a touch input identifying a virtual key and wherein said touch point is the point of touch for the touch input; display a first set of candidates comprising at least one candidate at a second position offset from said touch point, said first position and said second position both being in a common display area, and to interpret subsequent touch input originating from the touch point as having an offset position at a projected touch point originating at the second position wherein the offset of the projected touch point and an offset of the subsequent touch input are related, the candidates comprising candidate wordstems wherein at least one of the wordstems comprises a word; receive input referring to a first candidate being comprised in said first set; receive a select command of said first candidate; and input said selected candidate as text. | 1. An apparatus comprising a controller, arranged to: receive input identifying a touch point at a first position wherein said input is a touch input identifying a virtual key and wherein said touch point is the point of touch for the touch input; display a first set of candidates comprising at least one candidate at a second position offset from said touch point, said first position and said second position both being in a common display area, and to interpret subsequent touch input originating from the touch point as having an offset position at a projected touch point originating at the second position wherein the offset of the projected touch point and an offset of the subsequent touch input are related, the candidates comprising candidate wordstems wherein at least one of the wordstems comprises a word; receive input referring to a first candidate being comprised in said first set; receive a select command of said first candidate; and input said selected candidate as text. 10. The apparatus according to claim 1 , wherein said first set of candidates comprises a candidate that is associated with a word completion. | 0.833724 |
8,380,511 | 1 | 6 | 1. A method comprising: a) creating a set of text descriptions, wherein the set of text descriptions comprises, for each category in a category set, a corresponding text description for the category; b) accepting the set of text descriptions; c) identifying each word from a lexical data source which is related to a word in the set of text descriptions by less than a threshold number of semantic relations; d) creating a build time set of word pairs, each word pair from the build time set of word pairs comprising a word from the identified words from the lexical data source and a word from the set of text descriptions; e) using, without human intervention, a processor to assign lexical chaining confidence scores to each word pair from the build time set of word pairs; f) accepting a text statement from an input source; g) creating a run time set of word pairs, each word pair from the run time set of word pairs comprising a word from the accepted text statement, and a word from the set of text descriptions; and h) determining at least one category corresponding to the accepted text statement based, at least in part, on said assigned lexical chaining confidence scores for word pairs from the build time set of word pairs corresponding to word pairs from the run time set of word pairs. | 1. A method comprising: a) creating a set of text descriptions, wherein the set of text descriptions comprises, for each category in a category set, a corresponding text description for the category; b) accepting the set of text descriptions; c) identifying each word from a lexical data source which is related to a word in the set of text descriptions by less than a threshold number of semantic relations; d) creating a build time set of word pairs, each word pair from the build time set of word pairs comprising a word from the identified words from the lexical data source and a word from the set of text descriptions; e) using, without human intervention, a processor to assign lexical chaining confidence scores to each word pair from the build time set of word pairs; f) accepting a text statement from an input source; g) creating a run time set of word pairs, each word pair from the run time set of word pairs comprising a word from the accepted text statement, and a word from the set of text descriptions; and h) determining at least one category corresponding to the accepted text statement based, at least in part, on said assigned lexical chaining confidence scores for word pairs from the build time set of word pairs corresponding to word pairs from the run time set of word pairs. 6. The method of claim 1 wherein said text statement is derived from an audio response using automatically generated statistical language models (SLMs). | 0.971663 |
8,583,988 | 1 | 2 | 1. A computer program product for performing an input/output (I/O) processing operation at a host computer system configured for communication with a control unit, the computer program product comprising: a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: obtaining information relating to an I/O operation at a channel subsystem in the host computer system, the channel subsystem including at least one channel having a channel processor and a local channel memory, the channel subsystem in communication with a network interface configured to transmit data between the channel subsystem and the control unit during the I/O operation; generating at least one address control word (ACW) specifying at least one host memory location for transfer of the data between the host computer system and the control unit, and storing the at least one ACW in the local channel memory, the at least one ACW including at least one of a data check word generation field and a data check word save field; generating an address control structure for each data transfer specified by the I/O operation and forwarding each address control structure from the at least one channel to the network interface, each address control structure specifying a location in the local channel memory of a corresponding ACW; forwarding an I/O command message to the at least one I/O device via the network interface; responsive to the I/O command message, receiving a data transfer request from the network interface that includes the address control structure; responsive to the data transfer request including input data to be stored in the host memory and at least one received data check word, storing the at least one received data check word in the data check word save field and performing a check of the input data to determine whether the input data has been corrupted, and routing the input data to one of the at least one host memory location specified by the corresponding ACW responsive to determining that the input data has not been corrupted; and responsive to the data transfer request including a request for output data to be retrieved from the host memory, retrieving the output data from the one or another of the at least one host memory location specified by the corresponding ACW, generating at least one data check word based on the data check word generation field, appending the at least one generated data check word to the output data, and routing the output data and the at least one generated data check word to the network interface. | 1. A computer program product for performing an input/output (I/O) processing operation at a host computer system configured for communication with a control unit, the computer program product comprising: a non-transitory tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: obtaining information relating to an I/O operation at a channel subsystem in the host computer system, the channel subsystem including at least one channel having a channel processor and a local channel memory, the channel subsystem in communication with a network interface configured to transmit data between the channel subsystem and the control unit during the I/O operation; generating at least one address control word (ACW) specifying at least one host memory location for transfer of the data between the host computer system and the control unit, and storing the at least one ACW in the local channel memory, the at least one ACW including at least one of a data check word generation field and a data check word save field; generating an address control structure for each data transfer specified by the I/O operation and forwarding each address control structure from the at least one channel to the network interface, each address control structure specifying a location in the local channel memory of a corresponding ACW; forwarding an I/O command message to the at least one I/O device via the network interface; responsive to the I/O command message, receiving a data transfer request from the network interface that includes the address control structure; responsive to the data transfer request including input data to be stored in the host memory and at least one received data check word, storing the at least one received data check word in the data check word save field and performing a check of the input data to determine whether the input data has been corrupted, and routing the input data to one of the at least one host memory location specified by the corresponding ACW responsive to determining that the input data has not been corrupted; and responsive to the data transfer request including a request for output data to be retrieved from the host memory, retrieving the output data from the one or another of the at least one host memory location specified by the corresponding ACW, generating at least one data check word based on the data check word generation field, appending the at least one generated data check word to the output data, and routing the output data and the at least one generated data check word to the network interface. 2. The computer program product of claim 1 , wherein the at least one received data check word and the at least one generated data check word are selected from a longitudinal redundancy check word (LRC), a cyclical redundancy check word (CRC) and a Check Sum. | 0.622449 |
8,185,606 | 1 | 7 | 1. A computer implemented method for email change tracking, the computer implemented method comprising: receiving an email having a change tracking annotation defining an annotated portion within the email to form a received email, wherein the received email includes a set of tags comprising start and end tags defining an annotated portion, wherein the tags of the annotated portion comprise tags from a set of comment tags; parsing the received email with a first parser, the first parser ignoring the annotated portion to form a parsed first portion and wherein the tags of the annotated portion are ignored by the first parser; parsing the annotated portion of the received email with a second parser capable of parsing the annotated portion to form a parsed annotated portion, wherein the tags of the annotated portion are parsed by the second parser; and displaying the received email, comprising the parsed first portion and the parsed annotated portion, wherein the parsed annotated portion includes email change tracking indicating changes in a text that occurred at each location of each text change to a user. | 1. A computer implemented method for email change tracking, the computer implemented method comprising: receiving an email having a change tracking annotation defining an annotated portion within the email to form a received email, wherein the received email includes a set of tags comprising start and end tags defining an annotated portion, wherein the tags of the annotated portion comprise tags from a set of comment tags; parsing the received email with a first parser, the first parser ignoring the annotated portion to form a parsed first portion and wherein the tags of the annotated portion are ignored by the first parser; parsing the annotated portion of the received email with a second parser capable of parsing the annotated portion to form a parsed annotated portion, wherein the tags of the annotated portion are parsed by the second parser; and displaying the received email, comprising the parsed first portion and the parsed annotated portion, wherein the parsed annotated portion includes email change tracking indicating changes in a text that occurred at each location of each text change to a user. 7. The computer implemented method of claim 1 wherein the tags of the comment tags further comprise an add tag in a first http comment tag and an enclosing add tag in a second http comment tag in which the add tag and the enclosing add tag indicate that text between the http comment tags of the add tag and the enclosing add tag is text that was added to a block of text. | 0.821326 |
9,454,706 | 1 | 8 | 1. A method for Arabic like alphanumeric character recognition, comprising: receiving a handwritten Arabic like alphanumeric character, from an alphanumeric input device; storing, in a memory, fuzzy models of a plurality of Arabic like alphanumeric characters; preprocessing, by processing circuitry, the handwritten Arabic like alphanumeric character; extracting, by the processing circuitry, features from the preprocessed Arabic like alphanumeric character; computing, by the processing circuitry, a similarity value based on fuzzy comparisons between points of the preprocessed Arabic like alphanumeric character and the stored fuzzy models; classifying, by the processing circuitry, the handwritten Arabic like alphanumeric character based at least in part on the similarity value; and outputting a classified alphanumeric character, wherein the similarity value between a preprocessed Arabic like alphanumeric character S and a fuzzy model M is calculated based on a membership value calculated by applying sim ( S , M ) = 1 N ∑ i = 1 N M v ( S ( i ) , M ( i ) ) wherein the membership value is expressed as: M v ( S ( i ) , M ( i ) ) = { 0 , d > α 1 or d < α 2 1 , β 1 ≤ d ≤ β 2 α 1 - d α 1 - β , β 1 < d ≤ α 1 d - α 2 β 2 - α 2 , α 2 ≤ d < β 2 where N is a number of points, d is a directional feature of the preprocessed Arabic like alphanumeric character S at point i, β 1 and β 2 are a first tolerance and α 1 and α 2 are a second tolerance. | 1. A method for Arabic like alphanumeric character recognition, comprising: receiving a handwritten Arabic like alphanumeric character, from an alphanumeric input device; storing, in a memory, fuzzy models of a plurality of Arabic like alphanumeric characters; preprocessing, by processing circuitry, the handwritten Arabic like alphanumeric character; extracting, by the processing circuitry, features from the preprocessed Arabic like alphanumeric character; computing, by the processing circuitry, a similarity value based on fuzzy comparisons between points of the preprocessed Arabic like alphanumeric character and the stored fuzzy models; classifying, by the processing circuitry, the handwritten Arabic like alphanumeric character based at least in part on the similarity value; and outputting a classified alphanumeric character, wherein the similarity value between a preprocessed Arabic like alphanumeric character S and a fuzzy model M is calculated based on a membership value calculated by applying sim ( S , M ) = 1 N ∑ i = 1 N M v ( S ( i ) , M ( i ) ) wherein the membership value is expressed as: M v ( S ( i ) , M ( i ) ) = { 0 , d > α 1 or d < α 2 1 , β 1 ≤ d ≤ β 2 α 1 - d α 1 - β , β 1 < d ≤ α 1 d - α 2 β 2 - α 2 , α 2 ≤ d < β 2 where N is a number of points, d is a directional feature of the preprocessed Arabic like alphanumeric character S at point i, β 1 and β 2 are a first tolerance and α 1 and α 2 are a second tolerance. 8. The method of claim 1 , wherein the first tolerance and the second tolerance of a fuzzy model are based on a standard deviation obtained from directional features. | 0.548913 |
8,332,439 | 1 | 9 | 1. A method comprising: accessing a corpus stored in one or more tangible media, the corpus comprising a plurality of terms; performing the following for each term of one or more terms of the plurality of terms to yield a plurality of parent-child relationships: identifying one or more parent terms of the each term according to directional affinity, the plurality of terms comprising the one or more parent terms, the directional affinity being the number of co-occurrence contexts that include two terms, over the number of co-occurrence contexts that include one term; and establishing one or more parent-child relationships from the one or more parent terms and the each term; and automatically generating a hierarchical graph from the plurality of parent-child relationships, wherein the automatically generating the hierarchical graph from the plurality of parent-child relationships comprises reducing the hierarchical graph by: identifying a parent-child relationship and a redundant parent-child relationship of the hierarchical graph; and removing the redundant parent-child relationship from the hierarchical graph. | 1. A method comprising: accessing a corpus stored in one or more tangible media, the corpus comprising a plurality of terms; performing the following for each term of one or more terms of the plurality of terms to yield a plurality of parent-child relationships: identifying one or more parent terms of the each term according to directional affinity, the plurality of terms comprising the one or more parent terms, the directional affinity being the number of co-occurrence contexts that include two terms, over the number of co-occurrence contexts that include one term; and establishing one or more parent-child relationships from the one or more parent terms and the each term; and automatically generating a hierarchical graph from the plurality of parent-child relationships, wherein the automatically generating the hierarchical graph from the plurality of parent-child relationships comprises reducing the hierarchical graph by: identifying a parent-child relationship and a redundant parent-child relationship of the hierarchical graph; and removing the redundant parent-child relationship from the hierarchical graph. 9. The method of claim 1 : the corpus comprising a plurality of documents, the plurality of documents comprising the plurality of terms; and further comprising: associating each graph term of the hierarchical graph with a document that includes the each graph term; receiving a search query comprising a parent term; and retrieving one or more documents associated with a child of the parent term. | 0.694615 |
9,280,906 | 1 | 4 | 1. A system comprising: an electronic data store configured to store: an audiobook; and an electronic book that is a companion to the audiobook; and a computing device, comprising a physical processor, that is in communication with the electronic data store, the computing device configured to: identify a plurality of words that correspond between the audiobook and the electronic book, wherein each of said plurality of words occurs in both the audiobook and the electronic book in identical order; select a word, from the plurality of words, for modified presentation; cause textual presentation of the plurality of words; during the textual presentation of the plurality of words, cause audible presentation of one or more words, from the plurality of words, that precede the word selected for modified presentation without causing audible presentation of the word selected for modified presentation; prompt a user to speak the word selected for modified presentation; obtain a spoken response as audio input; determine that the spoken response includes the word selected for modified presentation; and subsequent to determining that the spoken response includes the word selected for modified presentation, cause audible presentation of one or more words, from the plurality of words, that follow the word selected for modified presentation. | 1. A system comprising: an electronic data store configured to store: an audiobook; and an electronic book that is a companion to the audiobook; and a computing device, comprising a physical processor, that is in communication with the electronic data store, the computing device configured to: identify a plurality of words that correspond between the audiobook and the electronic book, wherein each of said plurality of words occurs in both the audiobook and the electronic book in identical order; select a word, from the plurality of words, for modified presentation; cause textual presentation of the plurality of words; during the textual presentation of the plurality of words, cause audible presentation of one or more words, from the plurality of words, that precede the word selected for modified presentation without causing audible presentation of the word selected for modified presentation; prompt a user to speak the word selected for modified presentation; obtain a spoken response as audio input; determine that the spoken response includes the word selected for modified presentation; and subsequent to determining that the spoken response includes the word selected for modified presentation, cause audible presentation of one or more words, from the plurality of words, that follow the word selected for modified presentation. 4. The system of claim 1 , wherein the word selected for modified presentation is selected from the plurality of words based at least in part on user input. | 0.833333 |
9,584,991 | 1 | 7 | 1. A system comprising of: a first mobile device configured to display messages on a display of the mobile device; at least one processor in communication with the mobile device; a communication module in communication with the mobile device, wherein the communication module is configured for: enabling communication between all of the system modules; enabling communication between the mobile device and a second mobile device; and activating privacy controls for intercepting electronic transmissions for controlling the display of the electronic transmissions on the mobile device; a determination module in communication with the at least one processor, wherein the determination module is configured for determining presence of an indicator tag for incoming and/or outgoing decoded messages identifying messages for which there is a corresponding cryptic text; and for converting the at least one decoded message into cryptic text for displaying on the display; and an interactive module in communication with the at least one processor wherein the interactive module is configured to enable user interaction with the cryptic texts via at least one icon, which are embedded with code configured to enable different user interactions with the cryptic text, wherein the embedded code may be executed by dragging the at least one icon to a code execution area of the display. | 1. A system comprising of: a first mobile device configured to display messages on a display of the mobile device; at least one processor in communication with the mobile device; a communication module in communication with the mobile device, wherein the communication module is configured for: enabling communication between all of the system modules; enabling communication between the mobile device and a second mobile device; and activating privacy controls for intercepting electronic transmissions for controlling the display of the electronic transmissions on the mobile device; a determination module in communication with the at least one processor, wherein the determination module is configured for determining presence of an indicator tag for incoming and/or outgoing decoded messages identifying messages for which there is a corresponding cryptic text; and for converting the at least one decoded message into cryptic text for displaying on the display; and an interactive module in communication with the at least one processor wherein the interactive module is configured to enable user interaction with the cryptic texts via at least one icon, which are embedded with code configured to enable different user interactions with the cryptic text, wherein the embedded code may be executed by dragging the at least one icon to a code execution area of the display. 7. The system of claim 1 , further comprising calendaring a response to the cryptic text. | 0.875698 |
7,593,846 | 28 | 31 | 28. The computer-readable storage medium of claim 27 wherein the ranking is based on the hierarchical structure. | 28. The computer-readable storage medium of claim 27 wherein the ranking is based on the hierarchical structure. 31. The computer-readable storage medium of claim 28 wherein the ranking is based on an extent of depth of the hierarchical structure in each semantic solution. | 0.946702 |
8,694,888 | 5 | 6 | 5. The non-transitory computer readable medium of claim 4 , the computer program further comprising a set of instructions for modifying the plurality of received frames. | 5. The non-transitory computer readable medium of claim 4 , the computer program further comprising a set of instructions for modifying the plurality of received frames. 6. The non-transitory computer readable medium of claim 5 , wherein the set of instructions for modifying the plurality of received frames comprises a set of instructions for modifying how each particular received frame depicts a representation of the character. | 0.906562 |
9,830,319 | 1 | 11 | 1. A method for mapping one or more key-value pairs associated with a document into one or more tabular structures, the one or more key-value pairs each having a key name and a value, and each of the one or more tabular structures having one or more rows and columns for storing the values, the method comprising: reading the document, by a document reader, to identify the one or more key-value pairs associated with the input document; determining whether a value associated with a given one of the one or more key-value pairs is a scalar value or a composite value; in the event that the value associated with the key-value pair is a scalar value: extracting the key name of the key-value pair, storing the value of the key-value pair in a row of the tabular structure, or in the event that the value associated with the key-value pair is a composite value: extracting the key name of the key-value pair; generating a sub-tabular structure associated with the extracted key name of the key-value pair. | 1. A method for mapping one or more key-value pairs associated with a document into one or more tabular structures, the one or more key-value pairs each having a key name and a value, and each of the one or more tabular structures having one or more rows and columns for storing the values, the method comprising: reading the document, by a document reader, to identify the one or more key-value pairs associated with the input document; determining whether a value associated with a given one of the one or more key-value pairs is a scalar value or a composite value; in the event that the value associated with the key-value pair is a scalar value: extracting the key name of the key-value pair, storing the value of the key-value pair in a row of the tabular structure, or in the event that the value associated with the key-value pair is a composite value: extracting the key name of the key-value pair; generating a sub-tabular structure associated with the extracted key name of the key-value pair. 11. The method of claim 1 , wherein the document is input from a data source. | 0.942537 |
8,190,424 | 11 | 20 | 11. A computer-implemented method for prospecting digital information through online social communities, comprising: maintaining a home evergreen index for a home community and a plurality of frontier evergreen indexes for respective frontier communities, the home evergreen index and the frontier evergreen indexes covering topically-limited subject areas, each of the subject areas comprising electronically-stored digital information, the home evergreen index and each frontier evergreen index comprising: defining a hierarchy of stored topics; and matching a stored topic model to each of the topics in the topic hierarchy, each of the topic models comprising a pattern evaluable against the digital information, wherein the pattern identifies such digital information matching the topic model's topic; identifying at least one frontier evergreen index that comprises stored topics that are at least partially distinct from the stored topics comprised in the home evergreen index; obtaining vetted assessments as provided by the frontier community of the at least one frontier evergreen index for articles of the digital information identified by the patterns that comprise the topic models of the at least one frontier evergreen index; selecting the articles of the digital information corresponding to the vetted assessments that are favorable and matching the patterns that comprise the topic models of the home evergreen index against the selected articles of the digital information; and providing the selected articles of the digital information that were matched on a display. | 11. A computer-implemented method for prospecting digital information through online social communities, comprising: maintaining a home evergreen index for a home community and a plurality of frontier evergreen indexes for respective frontier communities, the home evergreen index and the frontier evergreen indexes covering topically-limited subject areas, each of the subject areas comprising electronically-stored digital information, the home evergreen index and each frontier evergreen index comprising: defining a hierarchy of stored topics; and matching a stored topic model to each of the topics in the topic hierarchy, each of the topic models comprising a pattern evaluable against the digital information, wherein the pattern identifies such digital information matching the topic model's topic; identifying at least one frontier evergreen index that comprises stored topics that are at least partially distinct from the stored topics comprised in the home evergreen index; obtaining vetted assessments as provided by the frontier community of the at least one frontier evergreen index for articles of the digital information identified by the patterns that comprise the topic models of the at least one frontier evergreen index; selecting the articles of the digital information corresponding to the vetted assessments that are favorable and matching the patterns that comprise the topic models of the home evergreen index against the selected articles of the digital information; and providing the selected articles of the digital information that were matched on a display. 20. A method according to claim 11 , wherein the digital information comprises one or more of printed documents, Web pages, and material written in a digital media. | 0.923364 |
9,251,182 | 1 | 7 | 1. A computer-implemented method of supplementing structured information within a data system for entities based on unstructured data comprising: analyzing documents with unstructured data specifying two or more entities of the structured information and interactions between those two or more entities; identifying from the interactions within the unstructured data of the documents one or more relationships between entities of the structured information; extracting attribute values from the unstructured data for one or more entities of the structured information base on a comparison of the unstructured data with one or more dictionaries each including values for a corresponding attribute of an entity within the data system, wherein extracting attribute values from the unstructured data includes: generating tokens from the unstructured data and comparing the tokens to the values within the one or more dictionaries, wherein at least one value within a dictionary includes a plurality of tokens; retrieving entity records with structured information form the data system based on the extracted attribute values; constructing entity references for corresponding one or more entities of the data system based on a comparison of the retrieved entity records and the extracted attribute values; linking the entity references to the corresponding one or more entities within the data system to supplement the structured information for the corresponding one or more entities with information extracted from the unstructured data, wherein the entity references include extracted attributes from the unstructured data for corresponding linked entities; and linking entities of the structured information to each other within the structured information to indicate related entities based on the one or more relationships between those entities identified form the interactions specified within the unstructured data of the documents. | 1. A computer-implemented method of supplementing structured information within a data system for entities based on unstructured data comprising: analyzing documents with unstructured data specifying two or more entities of the structured information and interactions between those two or more entities; identifying from the interactions within the unstructured data of the documents one or more relationships between entities of the structured information; extracting attribute values from the unstructured data for one or more entities of the structured information base on a comparison of the unstructured data with one or more dictionaries each including values for a corresponding attribute of an entity within the data system, wherein extracting attribute values from the unstructured data includes: generating tokens from the unstructured data and comparing the tokens to the values within the one or more dictionaries, wherein at least one value within a dictionary includes a plurality of tokens; retrieving entity records with structured information form the data system based on the extracted attribute values; constructing entity references for corresponding one or more entities of the data system based on a comparison of the retrieved entity records and the extracted attribute values; linking the entity references to the corresponding one or more entities within the data system to supplement the structured information for the corresponding one or more entities with information extracted from the unstructured data, wherein the entity references include extracted attributes from the unstructured data for corresponding linked entities; and linking entities of the structured information to each other within the structured information to indicate related entities based on the one or more relationships between those entities identified form the interactions specified within the unstructured data of the documents. 7. The computer-implemented method of claim 1 , wherein linking the entity references includes: inserting the entity references into one of the data system and an external data source based on a comparison of matching scores for the entity references with corresponding thresholds. | 0.603107 |
8,400,944 | 11 | 13 | 11. A method for displaying message-related relationships, comprising: analyzing messages, comprising: identifying entities associated with each message, wherein the entities comprise senders and recipients of the messages; and accumulating a number of messages communicated between each sender and each recipient; creating a social network by connecting one or more of the senders and recipients via a link based on the number of messages communicated between that sender and that recipient; generating a semantic network comprising concepts of the messages; and simultaneously displaying the social network and the semantic network. | 11. A method for displaying message-related relationships, comprising: analyzing messages, comprising: identifying entities associated with each message, wherein the entities comprise senders and recipients of the messages; and accumulating a number of messages communicated between each sender and each recipient; creating a social network by connecting one or more of the senders and recipients via a link based on the number of messages communicated between that sender and that recipient; generating a semantic network comprising concepts of the messages; and simultaneously displaying the social network and the semantic network. 13. A method according to claim 11 , wherein each entity comprises one of an individual and a corporation. | 0.892495 |
8,065,315 | 1 | 6 | 1. A system comprising: a search middleware configured to receive a search request for a solution to a software incident from at least one consumer search user interface (UI), via a search interface, and to conduct a search of at least two solution repositories of a plurality of solution repositories for a possible solution to the incident, based on the search request, and further configured to return a combined solution search result to the consumer UI, wherein each of the plurality of solution repositories contains documents of a solution type and is associated with an index configured to store attributes associated with at least some of the documents, and to store at least one attribute value associated with each attribute; a native search interface configured to search the index based on the attributes and thereby obtain at least some of the documents containing at least one of the attributes and attribute value, and a repository search interface configured to map the search request between the search interface and the native search interface, including mapping at least one attribute or attribute value specified by the search request into a format for searching using the index, wherein the search middleware includes a search source manager configured to select the at least two solution repositories from the plurality of solution repositories, based on the search request, an attribute manager configured to associate the attributes commonly between each of the plurality of repositories, and to associate these attributes with the index of each repository; a search dispatcher configured to receive the search request expressed using the attributes and provide the search request to repository interfaces of the at least two solution repositories for translation for input to respective native interfaces thereof for conducting a search for the attributes using the indices of each of the at least two repositories to obtain the documents, and to receive the search result from each repository, and a search compiler configured to receive the documents and compile the documents into the solution search result for providing to the consumer search UI including an identification of a source solution repository of each document in the search result. | 1. A system comprising: a search middleware configured to receive a search request for a solution to a software incident from at least one consumer search user interface (UI), via a search interface, and to conduct a search of at least two solution repositories of a plurality of solution repositories for a possible solution to the incident, based on the search request, and further configured to return a combined solution search result to the consumer UI, wherein each of the plurality of solution repositories contains documents of a solution type and is associated with an index configured to store attributes associated with at least some of the documents, and to store at least one attribute value associated with each attribute; a native search interface configured to search the index based on the attributes and thereby obtain at least some of the documents containing at least one of the attributes and attribute value, and a repository search interface configured to map the search request between the search interface and the native search interface, including mapping at least one attribute or attribute value specified by the search request into a format for searching using the index, wherein the search middleware includes a search source manager configured to select the at least two solution repositories from the plurality of solution repositories, based on the search request, an attribute manager configured to associate the attributes commonly between each of the plurality of repositories, and to associate these attributes with the index of each repository; a search dispatcher configured to receive the search request expressed using the attributes and provide the search request to repository interfaces of the at least two solution repositories for translation for input to respective native interfaces thereof for conducting a search for the attributes using the indices of each of the at least two repositories to obtain the documents, and to receive the search result from each repository, and a search compiler configured to receive the documents and compile the documents into the solution search result for providing to the consumer search UI including an identification of a source solution repository of each document in the search result. 6. The system of claim 1 wherein the repository search interface includes a web service. | 0.885714 |
8,041,918 | 15 | 17 | 15. A system for performing garbage collection, comprising: a block address identifying a block of memory; and a first thread configured to: obtain a first reference bitmap comprising the block address and a plurality of mark bits; obtain a first reference; identify a mark bit of the plurality of mark bits based on the first reference; compare an address associated with the mark bit and the first reference to generate a comparison; select an existing word from a global bit map based on the block address and the comparison; calculate a new word based on the plurality of mark bits and the existing word; replace the existing word in the global bit map with the new word; reclaim the block of memory for reuse based on the global bit map after replacing the existing word; perform a bitwise negation operation on the existing word to generate a negated existing word; perform a bitwise AND operation on the negated existing word and the plurality of mark bits to generate a result; and identify a second reference based on the result, wherein the second reference is reachable. | 15. A system for performing garbage collection, comprising: a block address identifying a block of memory; and a first thread configured to: obtain a first reference bitmap comprising the block address and a plurality of mark bits; obtain a first reference; identify a mark bit of the plurality of mark bits based on the first reference; compare an address associated with the mark bit and the first reference to generate a comparison; select an existing word from a global bit map based on the block address and the comparison; calculate a new word based on the plurality of mark bits and the existing word; replace the existing word in the global bit map with the new word; reclaim the block of memory for reuse based on the global bit map after replacing the existing word; perform a bitwise negation operation on the existing word to generate a negated existing word; perform a bitwise AND operation on the negated existing word and the plurality of mark bits to generate a result; and identify a second reference based on the result, wherein the second reference is reachable. 17. The system of claim 15 , wherein the first thread is further configured to push the second reference on a first mark stack. | 0.762172 |
8,060,931 | 2 | 3 | 2. The system as recited in claim 1 , wherein the associated authorization query comprises an associated authorization query template having one or more predetermined empty slots. | 2. The system as recited in claim 1 , wherein the associated authorization query comprises an associated authorization query template having one or more predetermined empty slots. 3. The system as recited in claim 2 , wherein the security scheme converts the authorization query template into the authorization query by substituting a requesting principal or a requested resource that relates to the resource-specific operation into the one or more predetermined empty slots. | 0.9081 |
9,031,243 | 1 | 9 | 1. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for multi-stage audio signal analysis, the method comprising: performing a first-stage processing operation on an audio signal, the first stage processing operation including a windowed signal analysis to calculate from the audio signal statistical descriptor features that are stored in a raw feature vector; performing a second stage statistical processing operation on the raw feature vector to derive a reduced feature vector; performing a third stage processing operation on the reduced feature vector to derive at least one sound object label that refers to the original audio signal; and mapping the at least one sound object label into a stream of control events sent to a sound-object-driven, multimedia-aware software application, wherein the sound-object-driven multimedia-aware software application is responsive to the stream of control events to configure processing for the audio signal, and wherein any of the processing operations of the first through third stages are configurable. | 1. A non-transitory computer-readable storage medium having embodied thereon a program, the program being executable by a processor to perform a method for multi-stage audio signal analysis, the method comprising: performing a first-stage processing operation on an audio signal, the first stage processing operation including a windowed signal analysis to calculate from the audio signal statistical descriptor features that are stored in a raw feature vector; performing a second stage statistical processing operation on the raw feature vector to derive a reduced feature vector; performing a third stage processing operation on the reduced feature vector to derive at least one sound object label that refers to the original audio signal; and mapping the at least one sound object label into a stream of control events sent to a sound-object-driven, multimedia-aware software application, wherein the sound-object-driven multimedia-aware software application is responsive to the stream of control events to configure processing for the audio signal, and wherein any of the processing operations of the first through third stages are configurable. 9. The non-transitory computer-readable storage medium of claim 1 , wherein the first through fourth stages are all processed in real-time for use in an on-the-fly analytical operation. | 0.797149 |
9,996,637 | 1 | 17 | 1. A method for formally verifying a hardware/software co-design, the method comprising: providing in a co-design, a first model, and a second model, wherein the first model is one of a hardware model, and the second model is one of a software model, or vice versa; performing an abstraction on the first model, wherein the abstraction comprises refining the first model to a lower abstraction level; specifying a safety property comprising one or more conditions to be satisfied by a composed hardware/software model; combining the abstraction of the first model and the safety property to obtain an abstracted first model; translating the abstracted first model and a corresponding interface model into a Property Specification Language, wherein the Property Specification Language is capable of describing a model environment for the second model; based on the described model environment, composing, by a model checker, the abstracted first model and the second model to obtain the composed hardware/software model, wherein the model checker automatically composes the abstracted first model and the second model using a construct in the Property Specification Language; verifying whether the composed hardware/software model satisfies the safety property; in response to the composed hardware/software model not satisfying the safety property, projecting, by the model checker, a counterexample on the first model, wherein the counterexample is projected on variables of the abstracted first model, the interface model, and the second model such that a sequence of model states is obtained as a consequence of projecting the counterexample; verifying whether the counterexample projected on the first model comprises a real error trace in the first model; based on the counterexample being a real error trace, signaling that the hardware/software co-design violates the safety property; and based on the counterexample not being a real error trace, refining the abstraction of the first model to eliminate the error trace. | 1. A method for formally verifying a hardware/software co-design, the method comprising: providing in a co-design, a first model, and a second model, wherein the first model is one of a hardware model, and the second model is one of a software model, or vice versa; performing an abstraction on the first model, wherein the abstraction comprises refining the first model to a lower abstraction level; specifying a safety property comprising one or more conditions to be satisfied by a composed hardware/software model; combining the abstraction of the first model and the safety property to obtain an abstracted first model; translating the abstracted first model and a corresponding interface model into a Property Specification Language, wherein the Property Specification Language is capable of describing a model environment for the second model; based on the described model environment, composing, by a model checker, the abstracted first model and the second model to obtain the composed hardware/software model, wherein the model checker automatically composes the abstracted first model and the second model using a construct in the Property Specification Language; verifying whether the composed hardware/software model satisfies the safety property; in response to the composed hardware/software model not satisfying the safety property, projecting, by the model checker, a counterexample on the first model, wherein the counterexample is projected on variables of the abstracted first model, the interface model, and the second model such that a sequence of model states is obtained as a consequence of projecting the counterexample; verifying whether the counterexample projected on the first model comprises a real error trace in the first model; based on the counterexample being a real error trace, signaling that the hardware/software co-design violates the safety property; and based on the counterexample not being a real error trace, refining the abstraction of the first model to eliminate the error trace. 17. The method according to claim 1 , wherein the model checker comprises conventional model checkers to compose the model environment described by the Property Specification Language and check the safety property. | 0.833593 |
8,196,053 | 3 | 4 | 3. The method of claim 2 , wherein: the converting further comprises: reducing a number of the treatment types by aggregating at least two of the treatment types together; and reformatting the information into the metadata; and the generating further comprises parsing the metadata. | 3. The method of claim 2 , wherein: the converting further comprises: reducing a number of the treatment types by aggregating at least two of the treatment types together; and reformatting the information into the metadata; and the generating further comprises parsing the metadata. 4. The method of claim 3 , wherein the reduced treatment types comprise at least one of: positive, negative, mildly negative, questioned, others, or cited. | 0.924757 |
8,452,794 | 1 | 2 | 1. A method comprising: receiving, at a first computing device, a search request from a second computing device of a user, the search request for images associated with a textual query; determining, by the first computing device and based at least in part on the received textual query, multiple images that are associated with the received textual query; determining, by the first computing device, a first keyword that is associated with a first set of the multiple images and determining, by the first computing device, a second keyword that is associated with a second set of the multiple images; clustering, by the first computing device, the first set of the multiple images into two or more clusters and clustering, by the first computing device, the second set of the multiple images into two or more clusters; determining, by the first computing device: (i) an image from the first cluster of the first set of the multiple images that is representative of the first cluster of the first set of the multiple images; (ii) an image from the second cluster of the first set of the multiple images that is representative of the second cluster of the first set of the multiple images; (iii) an image from the first cluster of the second set of the multiple images that is representative of the first cluster of the second set of the multiple images, and (iv) an image from the second cluster of the second set of the multiple images that is representative of the second cluster of the second set of the multiple images; providing the first keyword and the second keyword and the respective representative images of the first and the second clusters of the first set and the respective representative images of the first and the second clusters of the second set, to the second computing device of the user, in a suggestion to refine the search request based at least on the first keyword or the second keyword and based at least on one of the respective representative images; and responsive to receiving a selection of one of the first keyword or the second keyword and a selection of one of the respective representative images, refining the search request based at least on the selected keyword and based at least on the selected representative image. | 1. A method comprising: receiving, at a first computing device, a search request from a second computing device of a user, the search request for images associated with a textual query; determining, by the first computing device and based at least in part on the received textual query, multiple images that are associated with the received textual query; determining, by the first computing device, a first keyword that is associated with a first set of the multiple images and determining, by the first computing device, a second keyword that is associated with a second set of the multiple images; clustering, by the first computing device, the first set of the multiple images into two or more clusters and clustering, by the first computing device, the second set of the multiple images into two or more clusters; determining, by the first computing device: (i) an image from the first cluster of the first set of the multiple images that is representative of the first cluster of the first set of the multiple images; (ii) an image from the second cluster of the first set of the multiple images that is representative of the second cluster of the first set of the multiple images; (iii) an image from the first cluster of the second set of the multiple images that is representative of the first cluster of the second set of the multiple images, and (iv) an image from the second cluster of the second set of the multiple images that is representative of the second cluster of the second set of the multiple images; providing the first keyword and the second keyword and the respective representative images of the first and the second clusters of the first set and the respective representative images of the first and the second clusters of the second set, to the second computing device of the user, in a suggestion to refine the search request based at least on the first keyword or the second keyword and based at least on one of the respective representative images; and responsive to receiving a selection of one of the first keyword or the second keyword and a selection of one of the respective representative images, refining the search request based at least on the selected keyword and based at least on the selected representative image. 2. The method as recited in claim 1 , the refining of the search request comprises: ranking images that are associated with the received textual query based at least on a similarity of each of the images to: (i) the selected keyword, and (ii) the selected representative image; and outputting one or more of the images based at least in part on the ranking. | 0.692771 |
8,195,555 | 14 | 15 | 14. The system of claim 11 , wherein the one or more processors are further configured to receive an input to a calendar function associated with the electronic collaboration forum, wherein the input schedules an event associated with the collaboration team, wherein the scheduled event relates to one or more advisor services to be provided to the client by the collaboration team, and wherein the one or more processors are further configured to schedule the event in the calendar function associated with the electronic collaboration forum in response to the received input. | 14. The system of claim 11 , wherein the one or more processors are further configured to receive an input to a calendar function associated with the electronic collaboration forum, wherein the input schedules an event associated with the collaboration team, wherein the scheduled event relates to one or more advisor services to be provided to the client by the collaboration team, and wherein the one or more processors are further configured to schedule the event in the calendar function associated with the electronic collaboration forum in response to the received input. 15. The system of claim 14 , wherein the one or more processors are further configured to receive additional inputs to the calendar function of the electronic collaboration forum, the additional interactions involving the client and/or advisors from the collaboration team, the additional interactions being related to the one or more advisor services to be provided to the client that are related to the scheduled event, and wherein the one or more processors are still further configured to schedule the additional interactions in the calendar function in response to the additional inputs. | 0.816605 |
8,205,263 | 17 | 18 | 17. The computer system of claim 15 , wherein the monitoring module is further configured to identify one or more library strings included in each of the multiple executable files. | 17. The computer system of claim 15 , wherein the monitoring module is further configured to identify one or more library strings included in each of the multiple executable files. 18. The computer system of claim 17 , wherein the monitoring module is further configured to generate the list of pre-verified library strings that comprises the one or more library strings included in each of the multiple executable files. | 0.90172 |
6,032,116 | 15 | 16 | 15. The speech recognition system as in claim 14 wherein the distance measure, d(.function.,.function.), between the speech input signal, .function., and the reference speech signal, .function., is defined by: ##EQU28## wherein .function..sub.i and .function..sub.i are the ith line spectral pair frequencies in the speech input signal and the reference speech signal, respectively, the constants .alpha..sub.1, .alpha..sub.2, .beta..sub.1 and .beta..sub.2 are set to substantially minimize quantization error, and e.sub.i is the error power spectrum of the speech input signal and a predicted speech input signal at the ith line spectral pair frequency of the speech input signal. | 15. The speech recognition system as in claim 14 wherein the distance measure, d(.function.,.function.), between the speech input signal, .function., and the reference speech signal, .function., is defined by: ##EQU28## wherein .function..sub.i and .function..sub.i are the ith line spectral pair frequencies in the speech input signal and the reference speech signal, respectively, the constants .alpha..sub.1, .alpha..sub.2, .beta..sub.1 and .beta..sub.2 are set to substantially minimize quantization error, and e.sub.i is the error power spectrum of the speech input signal and a predicted speech input signal at the ith line spectral pair frequency of the speech input signal. 16. The speech recognition system of claim 15 wherein the i=1 to N.sub.1 line spectral pair frequencies are in the 0 to 400 Hz range. | 0.93971 |
8,068,092 | 1 | 2 | 1. A method of disambiguating an input into a handheld electronic device that comprises an input apparatus, an output apparatus, and a memory having stored therein a plurality of objects including a plurality of word objects, the input apparatus comprising a plurality of input members, at least some of the input members each having a plurality of characters assigned thereto, the method comprising: detecting an ambiguous input comprising a number of actuations of a number of the input members; outputting a number of first character permutations of the ambiguous input that each correspond with a word object in the memory; and determining that the first character permutations are fewer in quantity than a predetermined number and, responsive thereto, outputting a number of second character permutations of the ambiguous input that do not correspond with a word object in the memory. | 1. A method of disambiguating an input into a handheld electronic device that comprises an input apparatus, an output apparatus, and a memory having stored therein a plurality of objects including a plurality of word objects, the input apparatus comprising a plurality of input members, at least some of the input members each having a plurality of characters assigned thereto, the method comprising: detecting an ambiguous input comprising a number of actuations of a number of the input members; outputting a number of first character permutations of the ambiguous input that each correspond with a word object in the memory; and determining that the first character permutations are fewer in quantity than a predetermined number and, responsive thereto, outputting a number of second character permutations of the ambiguous input that do not correspond with a word object in the memory. 2. The method of claim 1 , further comprising outputting the first character permutations at a higher priority than the second character permutations. | 0.861878 |
4,066,998 | 7 | 9 | 7. The apparatus according to claim 6 further comprising: means for temporarily storing position data of said left-most and right-most grid locations for each examined row; means for providing and storing a no-hole indication when the interrogated grid locations of an examined row contain only character portions; and logic means for comparing the stored position data and stored no-hole indications to provide an indication when said left-most grid location of an examined row having no hole is further left than said left-most grid location of another examined row having no hold on the same character. | 7. The apparatus according to claim 6 further comprising: means for temporarily storing position data of said left-most and right-most grid locations for each examined row; means for providing and storing a no-hole indication when the interrogated grid locations of an examined row contain only character portions; and logic means for comparing the stored position data and stored no-hole indications to provide an indication when said left-most grid location of an examined row having no hole is further left than said left-most grid location of another examined row having no hold on the same character. 9. The apparatus according to claim 7 further comprising: additional logic means for providing an additional indication when said right-most grid location of an examined row having no hole is further right than said right-most grid location of another examined row having no hole in the same character. | 0.893362 |
8,201,103 | 18 | 20 | 18. A system for accessing an out-space user interface for a program, the instructions comprising: a processor; a display; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured to: display an in-space user interface having an out-space actuator associated with the in-space user interface, wherein the in-space user interface includes an information display area and an in-space feature selection surface that includes a display of authoring features of the document including editing; receive a selection of the out-space actuator; and in response to receiving the selection of the out-space actuator, display an out-space user interface, wherein the out-space user interface includes an in-space image and an out-space feature selection surface that comprises non-authoring features that has a larger area than the in-space feature selection surface, wherein selecting the in-space image redisplays the in-space user interface. | 18. A system for accessing an out-space user interface for a program, the instructions comprising: a processor; a display; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured to: display an in-space user interface having an out-space actuator associated with the in-space user interface, wherein the in-space user interface includes an information display area and an in-space feature selection surface that includes a display of authoring features of the document including editing; receive a selection of the out-space actuator; and in response to receiving the selection of the out-space actuator, display an out-space user interface, wherein the out-space user interface includes an in-space image and an out-space feature selection surface that comprises non-authoring features that has a larger area than the in-space feature selection surface, wherein selecting the in-space image redisplays the in-space user interface. 20. The computer-implemented method of claim 18 , wherein the out-space user interface does not include authoring features. | 0.809006 |
8,112,412 | 18 | 19 | 18. At least one non-transitory computer readable medium containing a computer program product for receiving and processing suggestions concerning reputable executable files to download, the computer program product comprising: program code for examining, by a computer, web pages browsed by a user; program code for extracting, by a computer, terms describing downloadable executable files from visited web pages, such that the terms indicate categories of executable file types for specific executable files; program code for detecting, by a computer, attempts by the user to download executable files; program code for, responsive to each detected attempt, transmitting, by a computer, at least an identifier of the corresponding executable file and indications of recently extracted terms to a categorization component; and program code for, responsive to at least one transmission to the categorization component, receiving, by a computer, a recommendation of at least one alternative executable file with an acceptable reputation to download. | 18. At least one non-transitory computer readable medium containing a computer program product for receiving and processing suggestions concerning reputable executable files to download, the computer program product comprising: program code for examining, by a computer, web pages browsed by a user; program code for extracting, by a computer, terms describing downloadable executable files from visited web pages, such that the terms indicate categories of executable file types for specific executable files; program code for detecting, by a computer, attempts by the user to download executable files; program code for, responsive to each detected attempt, transmitting, by a computer, at least an identifier of the corresponding executable file and indications of recently extracted terms to a categorization component; and program code for, responsive to at least one transmission to the categorization component, receiving, by a computer, a recommendation of at least one alternative executable file with an acceptable reputation to download. 19. The at least one non-transitory computer readable medium of claim 18 wherein the program code for transmitting at least an identifier of the corresponding executable file and indications of recently extracted terms to a categorization component further comprises: program code for obtaining a reputational score of the executable file; and program code for transmitting the identifier of the executable file, the reputational score of the executable file and the recently extracted terms to the categorization component. | 0.801815 |
7,982,737 | 23 | 24 | 23. The medium of claim 20 , wherein to resolve the particular character with the particular glyph the program instructions are executable to determine that the particular glyph matches the particular character. | 23. The medium of claim 20 , wherein to resolve the particular character with the particular glyph the program instructions are executable to determine that the particular glyph matches the particular character. 24. The medium of claim 23 , wherein to determine that the particular glyph matches the particular character the program instructions are executable to determine that a character code of said particular character is mapped to an index of said particular glyph as specified by an encoding table that maps character codes to glyph indices. | 0.867531 |
8,706,732 | 1 | 4 | 1. A method for managing information about entities, the method comprising: receiving an observation, by one or more computers, the observation including an updated piece of information about an entity having a geographic location and a context, wherein the context includes at least one value of an attribute describing the entity to which the updated piece of information relates; storing, by the one or more computers, the received observation as an immutable observation that includes the updated piece of information about the entity having the geographic location and the context, wherein the immutable observation is not modifiable after storage of the immutable observation; matching, by the one or more computers, the immutable observation with a first cluster of observations representing the entity using the context; the matching comprising: generating a query derived from one or more values of attributes included in the context; identifying, by the one or more computers, one or more candidate clusters of observations responsive to the generated query; generating, by the one or more computers, a respective score for the one or more candidate clusters, wherein the respective score is based on a comparison of one or more attribute values from the context and a corresponding one or more attribute values of the one or more candidate clusters; and matching, by the one or more computers, the immutable observation with a select candidate cluster having the highest respective score; and associating, by the one or more computers, the immutable observation with the first cluster of observations. | 1. A method for managing information about entities, the method comprising: receiving an observation, by one or more computers, the observation including an updated piece of information about an entity having a geographic location and a context, wherein the context includes at least one value of an attribute describing the entity to which the updated piece of information relates; storing, by the one or more computers, the received observation as an immutable observation that includes the updated piece of information about the entity having the geographic location and the context, wherein the immutable observation is not modifiable after storage of the immutable observation; matching, by the one or more computers, the immutable observation with a first cluster of observations representing the entity using the context; the matching comprising: generating a query derived from one or more values of attributes included in the context; identifying, by the one or more computers, one or more candidate clusters of observations responsive to the generated query; generating, by the one or more computers, a respective score for the one or more candidate clusters, wherein the respective score is based on a comparison of one or more attribute values from the context and a corresponding one or more attribute values of the one or more candidate clusters; and matching, by the one or more computers, the immutable observation with a select candidate cluster having the highest respective score; and associating, by the one or more computers, the immutable observation with the first cluster of observations. 4. The method of claim 1 , wherein the received observation does not include a system-generated identifier for the entity. | 0.791809 |
9,355,092 | 1 | 3 | 1. A method of emulating human-like responses, the method comprising: storing a library comprising one or more different subject matter data structures, each data structure comprising a plurality of output instructions related to the subject matter of the data structure, each output instruction producing a human-like response and being associated with a received input stimulus, wherein the received input stimuli comprise human inputs and system inputs, the system inputs received via at least one sensor; associating each event with a tag; using the tag to determine whether an event corresponds to an important event or a non-important event; looking up output instructions in each data structure that are associated with the received input stimulus; outputting, via a human output API, one or more responses to the received stimulus according to a found output instruction when the event corresponds to an important event, wherein the one or more responses are ordered according to a priority rating; placing non-important events in an event queue; applying logical rules to the non-important events to determine whether a plurality of non-important events are collectively indicative of an important event; and outputting, via a human output API, one or more responses when the logical rules determine that the plurality of non-important events are collectively indicative of an important event, wherein the one or more responses are ordered according to a priority rating; wherein the one or more different subject matter data structures are arranged such that the output instructions which produce the human-like response are grouped hierarchically according to their respective associated stimuli. | 1. A method of emulating human-like responses, the method comprising: storing a library comprising one or more different subject matter data structures, each data structure comprising a plurality of output instructions related to the subject matter of the data structure, each output instruction producing a human-like response and being associated with a received input stimulus, wherein the received input stimuli comprise human inputs and system inputs, the system inputs received via at least one sensor; associating each event with a tag; using the tag to determine whether an event corresponds to an important event or a non-important event; looking up output instructions in each data structure that are associated with the received input stimulus; outputting, via a human output API, one or more responses to the received stimulus according to a found output instruction when the event corresponds to an important event, wherein the one or more responses are ordered according to a priority rating; placing non-important events in an event queue; applying logical rules to the non-important events to determine whether a plurality of non-important events are collectively indicative of an important event; and outputting, via a human output API, one or more responses when the logical rules determine that the plurality of non-important events are collectively indicative of an important event, wherein the one or more responses are ordered according to a priority rating; wherein the one or more different subject matter data structures are arranged such that the output instructions which produce the human-like response are grouped hierarchically according to their respective associated stimuli. 3. A method as claimed in claim 1 , wherein the output instructions produce the response in the form of one or more of the following: language, an animated graphical display, voice characteristics, and/or control signals. | 0.704545 |
6,122,666 | 7 | 10 | 7. In a network comprising a plurality of source servers, each associated with sales information, a plurality of clients each making requests for said sales information, wherein each client request corresponds to one of a plurality of users and a plurality of proxies which receive said requests for sales information from said clients, a method of satisfying said requests for sales information, comprising: dividing said plurality of proxies into a plurality of sets of one or more proxies wherein each of the plurality of sets of one or more proxies performs a respectively different translation based on a preassignment; directing a first translation request to a first set of one or more proxies based on said preassignment; directing a second translation request to a second set of one or more proxies based on said preassignment; performing said first translation at said first set of one or more proxies after receiving said sales information from one of said source servers; performing said second translation at said second set of one or more proxies after receiving said sales information from one or another of said source servers; and providing said first and second translations. | 7. In a network comprising a plurality of source servers, each associated with sales information, a plurality of clients each making requests for said sales information, wherein each client request corresponds to one of a plurality of users and a plurality of proxies which receive said requests for sales information from said clients, a method of satisfying said requests for sales information, comprising: dividing said plurality of proxies into a plurality of sets of one or more proxies wherein each of the plurality of sets of one or more proxies performs a respectively different translation based on a preassignment; directing a first translation request to a first set of one or more proxies based on said preassignment; directing a second translation request to a second set of one or more proxies based on said preassignment; performing said first translation at said first set of one or more proxies after receiving said sales information from one of said source servers; performing said second translation at said second set of one or more proxies after receiving said sales information from one or another of said source servers; and providing said first and second translations. 10. A method of satisfying said requests for sales information according to claim 7, wherein said translation includes a tax calculation. | 0.610795 |
7,555,718 | 13 | 14 | 13. The method of claim 1 , wherein the keyframes are cropped. | 13. The method of claim 1 , wherein the keyframes are cropped. 14. The method of claim 13 , wherein the keyframes are cropped according to an aspect ratio. | 0.952675 |
9,196,255 | 19 | 20 | 19. The apparatus according to claim 12 , further caused to, in said identify of said one or more target vectors with respect to an input vector, check for at least several candidate vectors of said plurality of candidate vectors, and wherein in each said check, the same reference vector is used, and wherein the apparatus is further caused to retrieve said distance between said candidate vector and said reference vector from a memory that comprises distances between said reference vector and all candidate vectors of said plurality of candidate vectors. | 19. The apparatus according to claim 12 , further caused to, in said identify of said one or more target vectors with respect to an input vector, check for at least several candidate vectors of said plurality of candidate vectors, and wherein in each said check, the same reference vector is used, and wherein the apparatus is further caused to retrieve said distance between said candidate vector and said reference vector from a memory that comprises distances between said reference vector and all candidate vectors of said plurality of candidate vectors. 20. The apparatus according to claim 19 , further caused to compute, in said identify of said one or more target vectors with respect to an input vector, said distance between said reference vector and said at least sorted representation of said input vector only once. | 0.934262 |
9,230,009 | 2 | 3 | 2. The method of claim 1 , wherein identifying a matching cluster comprises: determining, for each previously generated cluster in the one or more previously generated clusters, a distance of the input question from a center of the previously generated cluster; and selecting a matching cluster, from the one or more previously generated clusters, based on the determined distances. | 2. The method of claim 1 , wherein identifying a matching cluster comprises: determining, for each previously generated cluster in the one or more previously generated clusters, a distance of the input question from a center of the previously generated cluster; and selecting a matching cluster, from the one or more previously generated clusters, based on the determined distances. 3. The method of claim 2 , wherein selecting a matching cluster comprises: comparing the distances to one or more threshold distance values; and selecting a matching cluster based on whether or not a corresponding distance of the matching cluster has a predetermined relationship with the one or more threshold distance values. | 0.882627 |
9,037,993 | 13 | 14 | 13. A non-transitory processor-readable medium having stored thereon processor-executable instructions configured to cause a personal computing device processor to perform operations comprising: displaying on a display of a device at least one pallet illustrating associations between a series of unique non-descriptive graphical figures and corresponding unique text-based characters, wherein each text-based character corresponds to one of a plurality of keys comprising an input mechanism of the device and wherein each unique non-descriptive graphical figure is associated with a corresponding text-based character, wherein the series of unique non-descriptive graphical figures comprises a series of unique background colors and a series of unique pen colors; receiving input of a text-based character corresponding to a unique non-descriptive graphical figure and displaying the non-descriptive graphical figure in a predetermined display location in accordance with a defined sequence scheme comprising rules for the order of entry of a sequence, and repeating receiving input of a text-based character corresponding to a next non-descriptive graphical figure and displaying the next non-descriptive graphical figure in a next predetermined display location in accordance with the defined sequence scheme until receipt of the sequence is complete; and processing the input text-based characters as a user password. | 13. A non-transitory processor-readable medium having stored thereon processor-executable instructions configured to cause a personal computing device processor to perform operations comprising: displaying on a display of a device at least one pallet illustrating associations between a series of unique non-descriptive graphical figures and corresponding unique text-based characters, wherein each text-based character corresponds to one of a plurality of keys comprising an input mechanism of the device and wherein each unique non-descriptive graphical figure is associated with a corresponding text-based character, wherein the series of unique non-descriptive graphical figures comprises a series of unique background colors and a series of unique pen colors; receiving input of a text-based character corresponding to a unique non-descriptive graphical figure and displaying the non-descriptive graphical figure in a predetermined display location in accordance with a defined sequence scheme comprising rules for the order of entry of a sequence, and repeating receiving input of a text-based character corresponding to a next non-descriptive graphical figure and displaying the next non-descriptive graphical figure in a next predetermined display location in accordance with the defined sequence scheme until receipt of the sequence is complete; and processing the input text-based characters as a user password. 14. The non-transitory processor-readable medium of claim 13 , wherein the stored processor-executable instructions are configured to cause a personal computing device processor to perform operations further comprising: displaying on the display of the device at least one pallet illustrating associations between a series of unique color features and corresponding unique text-based characters, wherein each text-based character corresponds to one of the plurality of keys comprising the input mechanism of the device and wherein each color feature is associated with a corresponding text-based character; and receiving input of a text-based character corresponding to a particular color feature. | 0.552632 |
9,116,990 | 7 | 8 | 7. The memory device of claim 6 , wherein the method further comprises calculating the publication time for the document based on when the document was first indexed by a search engine and a previous time the document's location was visited by the search engine, and wherein the document was not available at the previous time. | 7. The memory device of claim 6 , wherein the method further comprises calculating the publication time for the document based on when the document was first indexed by a search engine and a previous time the document's location was visited by the search engine, and wherein the document was not available at the previous time. 8. The memory device of claim 7 , wherein the publication time is calculated without parsing the document for text indicating when the document was published. | 0.962595 |
9,910,829 | 12 | 19 | 12. In a computer-based system, a method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques; obtaining the plurality of images; automatically categorizing a plurality of subdocument images into a plurality of predetermined categories based on analyzing textual infoiniation and/or image characteristics of each of the plurality of document images using the classification rules, wherein said step of automatically categorizing comprises: producing an output score for each subdocument image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for said plurality of subdocument images based on said output scores; automatically generating at least one identifier for identifying which of said plurality of subdocument images belongs to which of said plurality of predetermined categories; and separating subdocuments within the plurality of subdocument images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of subdocument images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or inserting one or more computer-generated separation pages between at least some of the plurality of subdocument images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of subdocument images and inserting the one or more computer-generated separation pages between at least some of the plurality of subdocument images. | 12. In a computer-based system, a method for automatically separating documents represented within a plurality of images by delineating document boundaries and identifying document types in accordance with classification rules, the method comprising: automatically generating classification rules that predict a document type or subdocument type for each of the plurality of images based on textual information and/or graphical information represented in each respective one of the plurality of images, wherein the classification rules are generated based on analyzing textual information and/or graphical information of a plurality of training images using one or more of: a probabilistic network; relational algebra; and machine learning techniques; obtaining the plurality of images; automatically categorizing a plurality of subdocument images into a plurality of predetermined categories based on analyzing textual infoiniation and/or image characteristics of each of the plurality of document images using the classification rules, wherein said step of automatically categorizing comprises: producing an output score for each subdocument image based on the analysis thereof using the classification rules, wherein each output score represents an estimated document type probability or a subdocument type probability; and using a graph search algorithm to determine an optimum categorization sequence from a plurality of possible categorization sequences for said plurality of subdocument images based on said output scores; automatically generating at least one identifier for identifying which of said plurality of subdocument images belongs to which of said plurality of predetermined categories; and separating subdocuments within the plurality of subdocument images from one another by either: electronically associating at least one computer-generated label with at least some of the plurality of subdocument images, each label corresponding to a different one of the plurality of categories and comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or inserting one or more computer-generated separation pages between at least some of the plurality of subdocument images to delineate images belonging to different ones of the plurality of categories, each separation page comprising one of the one or more identifiers generated for identifying which of the plurality of subdocument images belongs to which of the plurality of predetermined categories; or both electronically associating the at least one computer-generated label with at least some of the plurality of subdocument images and inserting the one or more computer-generated separation pages between at least some of the plurality of subdocument images. 19. The method of claim 12 , wherein said output scores represent a probability that each subdocument image belongs to at least one respective category from said plurality of predetermined categories. | 0.723757 |
4,171,816 | 1 | 5 | 1. A game apparatus, comprising: a plurality of strips having two faces, one of said faces being a front face having thereon a word or combination of words exemplifying a language category, the other face being a rear face having a word or words identifying the language category exemplified on said front face; a game board having a plurality of spaces oriented in a plurality of rows and a plurality of columns for receiving and accumulating said strips according to each of said language categories, certain preselected ones of said spaces on the game board having a designation therein for rewarding bonus points; an indicator means for random selection of any one of said language categories; and dice, each of which has words or syllables on its face for determining by change an amount of bonus points to be rewarded upon receiving and accumulating one of said strips upon one of said certain preselected spaces of said game board. | 1. A game apparatus, comprising: a plurality of strips having two faces, one of said faces being a front face having thereon a word or combination of words exemplifying a language category, the other face being a rear face having a word or words identifying the language category exemplified on said front face; a game board having a plurality of spaces oriented in a plurality of rows and a plurality of columns for receiving and accumulating said strips according to each of said language categories, certain preselected ones of said spaces on the game board having a designation therein for rewarding bonus points; an indicator means for random selection of any one of said language categories; and dice, each of which has words or syllables on its face for determining by change an amount of bonus points to be rewarded upon receiving and accumulating one of said strips upon one of said certain preselected spaces of said game board. 5. The apparatus of claim 1, wherein each of said dice have a syllable on two faces and have a different language category word on the remaining faces. | 0.741438 |
5,513,311 | 1 | 3 | 1. A method in a data processing system for efficiently creating a logical connection between a new graphic object and at least one of a plurality of existing graphic objects, wherein a number of diverse types of logical connections may be created between graphic objects, said method comprising: in response to a placement of a new graphic object in a location, identifying each existing graphic object within said plurality of existing graphic objects located within a predetermined distance from said new graphic object; and automatically creating a particular logical connection between said new graphic object and each identified existing graphic object based upon a position of each identified existing graphic object with respect to said new graphic object, wherein logical connections between graphic objects are efficiently created. | 1. A method in a data processing system for efficiently creating a logical connection between a new graphic object and at least one of a plurality of existing graphic objects, wherein a number of diverse types of logical connections may be created between graphic objects, said method comprising: in response to a placement of a new graphic object in a location, identifying each existing graphic object within said plurality of existing graphic objects located within a predetermined distance from said new graphic object; and automatically creating a particular logical connection between said new graphic object and each identified existing graphic object based upon a position of each identified existing graphic object with respect to said new graphic object, wherein logical connections between graphic objects are efficiently created. 3. The method of claim 1, wherein said new object and said plurality of objects are located in a display having a x-axis and a y-axis and wherein said step of automatically creating a particular logical connection includes creating an OR connection in response to said new graphic object and an identified existing graphic object being located along a line parallel to a y-axis. | 0.620482 |
10,013,492 | 7 | 28 | 7. The computer-implemented method of claim 1 , further comprising: causing display of at least one additional question that is associated with assessing a reading level of the electronic book. | 7. The computer-implemented method of claim 1 , further comprising: causing display of at least one additional question that is associated with assessing a reading level of the electronic book. 28. The computer-implemented method of claim 7 , further comprising: assessing the reading level of the electronic book based at least in part on the response; and causing display of a recommendation of additional electronic content items based at least in part on the reading level. | 0.92634 |
6,050,825 | 1 | 8 | 1. A cover for a partial section of a keyboard having a frame and multiple alpha-numeric, function and format keys, the cover comprising: a resiliently flexible non-transparent body which is configured to only overlie a predetermined number of non-format and non-function keys totaling less than all of the keys of the keyboard; a wall extending downwardly from a perimeter of the body; and grooves within the body and configured so that the body individually form-fits the predetermined number of keys, whereby the cover is adapted for use on a variety of keyboards. | 1. A cover for a partial section of a keyboard having a frame and multiple alpha-numeric, function and format keys, the cover comprising: a resiliently flexible non-transparent body which is configured to only overlie a predetermined number of non-format and non-function keys totaling less than all of the keys of the keyboard; a wall extending downwardly from a perimeter of the body; and grooves within the body and configured so that the body individually form-fits the predetermined number of keys, whereby the cover is adapted for use on a variety of keyboards. 8. The cover of claim 1, including a mid-line marking which defines a separation line for adapting the cover to an ergonomic keyboard having a separation between two sets of keys. | 0.756793 |
8,302,010 | 12 | 13 | 12. A computer program product, comprising: a non-transitory computer-readable medium with computer program instructions encoded thereon, wherein the computer program instructions, when processed by a computer, instruct the computer to perform a method for enabling a user to edit a time-based media program that includes recorded speech, the method comprising: causing the computer to receive 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, enabling the user to edit 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 timing information with each of the plurality of words within the transcript is preserved during the editing, and wherein editing the augmented transcript does not involve playback of the time-based media; and causing the computer to output 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. | 12. A computer program product, comprising: a non-transitory computer-readable medium with computer program instructions encoded thereon, wherein the computer program instructions, when processed by a computer, instruct the computer to perform a method for enabling a user to edit a time-based media program that includes recorded speech, the method comprising: causing the computer to receive 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, enabling the user to edit 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 timing information with each of the plurality of words within the transcript is preserved during the editing, and wherein editing the augmented transcript does not involve playback of the time-based media; and causing the computer to output 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. 13. The computer program product of claim 12 , wherein the time-based media program includes a video component synchronized with the recorded speech. | 0.775602 |
7,844,607 | 1 | 2 | 1. A system for sharing information useful in building queries, comprising: an annotation database for storing annotations; a query building interface allowing users to build queries by specifying query components, wherein the query components are stored and are accessible to the query building interface; and an annotation system allowing users to create and display annotations associated with query components used in building queries, wherein the annotation system provides an annotation creating interface allowing a user to create an annotation for a query component selected from the query building interface, wherein the indication is an annotation icon; and wherein the annotation system is configured to: display an annotation associated with a query component, in response to a user selecting the annotation icon, display, to the user, a suggested substitution for the query component associated with the annotation, and replace the query component associated with the annotation with the suggested substitution, in response to the user accepting the suggested substitution. | 1. A system for sharing information useful in building queries, comprising: an annotation database for storing annotations; a query building interface allowing users to build queries by specifying query components, wherein the query components are stored and are accessible to the query building interface; and an annotation system allowing users to create and display annotations associated with query components used in building queries, wherein the annotation system provides an annotation creating interface allowing a user to create an annotation for a query component selected from the query building interface, wherein the indication is an annotation icon; and wherein the annotation system is configured to: display an annotation associated with a query component, in response to a user selecting the annotation icon, display, to the user, a suggested substitution for the query component associated with the annotation, and replace the query component associated with the annotation with the suggested substitution, in response to the user accepting the suggested substitution. 2. The system of claim 1 , wherein the annotation system provides an annotation creating interface allowing a user to create an annotation for a query component selected from the query building interface. | 0.502439 |
9,110,904 | 11 | 15 | 11. A device comprising: a communication interface; one or more memories, wherein the one or more memories store instructions; and one or more processors, wherein the one or more processors execute the instructions to: obtain metadata pertaining to programs originating from metadata sources; compare metadata of a first type from one of the metadata sources with one or more metadata of the first type from one or more others of the metadata sources; determine whether compared metadata of the first type from the one of the metadata sources matches the one or more metadata of the first type from the one or more others of the metadata sources based on a comparison; transform the compared metadata based on one or more transformation rules when the compared metadata does not match; store transformed metadata, wherein the transformed metadata of the first type from the one of the metadata sources matches at least one of the one or more metadata of the first type from at least one other of the metadata sources; identify when metadata of a same metadata type is obtained from the one of the metadata sources and the at least one other of the metadata sources, wherein the metadata of the same metadata type is other than the first type; determine which metadata of the same metadata type to aggregate based on a quality metric that indicates a quality of each metadata; and select metadata of the same metadata type from the one of the metadata sources or the at least one other of the metadata sources based on a determination of which metadata of the same metadata type to aggregate, wherein, when making the determination of which metadata of the same metadata type to aggregate based on the quality metric, the one or more processors further execute the instructions to: count a number of words in the metadata of the same metadata type from the one of the metadata sources; count a number of words in the metadata of the same metadata type from the at least one other of the metadata sources; and determine whether the number of words in the metadata of the same metadata type from the one of the metadata sources is greater than the number of words in the metadata of the same metadata type from the at least one other of the metadata sources, and wherein, when making a selection of metadata of the same metadata type, the one or more processors further execute the instructions to: select the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources in response to a determination that the number of words in the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources is greater. | 11. A device comprising: a communication interface; one or more memories, wherein the one or more memories store instructions; and one or more processors, wherein the one or more processors execute the instructions to: obtain metadata pertaining to programs originating from metadata sources; compare metadata of a first type from one of the metadata sources with one or more metadata of the first type from one or more others of the metadata sources; determine whether compared metadata of the first type from the one of the metadata sources matches the one or more metadata of the first type from the one or more others of the metadata sources based on a comparison; transform the compared metadata based on one or more transformation rules when the compared metadata does not match; store transformed metadata, wherein the transformed metadata of the first type from the one of the metadata sources matches at least one of the one or more metadata of the first type from at least one other of the metadata sources; identify when metadata of a same metadata type is obtained from the one of the metadata sources and the at least one other of the metadata sources, wherein the metadata of the same metadata type is other than the first type; determine which metadata of the same metadata type to aggregate based on a quality metric that indicates a quality of each metadata; and select metadata of the same metadata type from the one of the metadata sources or the at least one other of the metadata sources based on a determination of which metadata of the same metadata type to aggregate, wherein, when making the determination of which metadata of the same metadata type to aggregate based on the quality metric, the one or more processors further execute the instructions to: count a number of words in the metadata of the same metadata type from the one of the metadata sources; count a number of words in the metadata of the same metadata type from the at least one other of the metadata sources; and determine whether the number of words in the metadata of the same metadata type from the one of the metadata sources is greater than the number of words in the metadata of the same metadata type from the at least one other of the metadata sources, and wherein, when making a selection of metadata of the same metadata type, the one or more processors further execute the instructions to: select the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources in response to a determination that the number of words in the metadata of the same metadata type from the one of the metadata sources or from the at least one other of the metadata sources is greater. 15. The device of claim 11 , wherein the one or more processors further execute the instructions to: identify when metadata of the same metadata type is obtained from the one of the metadata sources and the at least one other of the metadata sources, wherein the same metadata type is other than title metadata; identify differences between metadata associated the same metadata type; and generate metadata based on a combining of metadata associated with the same metadata type. | 0.779466 |
8,401,855 | 13 | 14 | 13. A non-volatile computer readable medium containing a plurality of program instructions, which when executed by a processor, cause the processor to perform the steps of: processing the rules of a defined set of grammar rules for various objects within an application executed by the dialog system; labeling each grammar rule of the set of grammar rules with semantic or syntactic characteristics by annotating each grammar rule with a specific item of information regarding each element of the respective grammar rule to produce labeled grammar rules; generating labeled sentences from the set of labeled grammar rules to preclude the need to label sentences after they are generated; and using the labeled sentences to train one or more statistical models to be used by a spoken language unit of the dialog system. | 13. A non-volatile computer readable medium containing a plurality of program instructions, which when executed by a processor, cause the processor to perform the steps of: processing the rules of a defined set of grammar rules for various objects within an application executed by the dialog system; labeling each grammar rule of the set of grammar rules with semantic or syntactic characteristics by annotating each grammar rule with a specific item of information regarding each element of the respective grammar rule to produce labeled grammar rules; generating labeled sentences from the set of labeled grammar rules to preclude the need to label sentences after they are generated; and using the labeled sentences to train one or more statistical models to be used by a spoken language unit of the dialog system. 14. The medium of claim 13 wherein each grammar rule of the set of grammar rules comprises a context-free grammar rule. | 0.791958 |
7,984,004 | 11 | 12 | 11. A method that facilitates determining an indication of usefulness of a query suggestion with respect to a query, comprising the following computer-executable acts: receiving the query from a user; generating a plurality of query suggestions based at least in part upon the received query; causing a processor to create multiple groups of query suggestions from the plurality of generated query suggestions, wherein each of the multiple groups of query suggestions includes a plurality of query suggestions; using a logistic regression model that has been trained from data that is indicative of user interaction with respect to query suggestions to output an indication of usefulness for each group of queries in the multiple groups of query suggestions based at least in part upon the received query, wherein query suggestions in a group of query suggestions with a highest indication of usefulness assigned thereto are presented to the user, wherein the data that is indicative of user interaction with respect to query suggestions comprises queries provided to a search engine by users, search results returned to the users subsequent to the search engine performing searches using the queries, search results selected by the users subsequent to the search results being returned to the users, query suggestions provided to the users responsive to the queries being provided to the search engine by the users, query suggestions selected by the users upon the users being provided with the query suggestions, and search results selected by the users subsequent to the users selecting the query suggestions. | 11. A method that facilitates determining an indication of usefulness of a query suggestion with respect to a query, comprising the following computer-executable acts: receiving the query from a user; generating a plurality of query suggestions based at least in part upon the received query; causing a processor to create multiple groups of query suggestions from the plurality of generated query suggestions, wherein each of the multiple groups of query suggestions includes a plurality of query suggestions; using a logistic regression model that has been trained from data that is indicative of user interaction with respect to query suggestions to output an indication of usefulness for each group of queries in the multiple groups of query suggestions based at least in part upon the received query, wherein query suggestions in a group of query suggestions with a highest indication of usefulness assigned thereto are presented to the user, wherein the data that is indicative of user interaction with respect to query suggestions comprises queries provided to a search engine by users, search results returned to the users subsequent to the search engine performing searches using the queries, search results selected by the users subsequent to the search results being returned to the users, query suggestions provided to the users responsive to the queries being provided to the search engine by the users, query suggestions selected by the users upon the users being provided with the query suggestions, and search results selected by the users subsequent to the users selecting the query suggestions. 12. The method of claim 11 , further comprising: using the logistic regression model to individually compute an indication of usefulness for each of the plurality of query suggestions; and displaying query suggestions in an order that corresponds to indications of usefulness corresponding thereto. | 0.778603 |
7,478,170 | 42 | 44 | 42. The tangible, computer-accessible storage medium as recited in claim 39 , wherein the program instructions are further computer-executable to implement plugging a different pluggable converter module into the framework, wherein the different converter module is configured to convert office documents in a different office document format to and from small device documents in a different small device format. | 42. The tangible, computer-accessible storage medium as recited in claim 39 , wherein the program instructions are further computer-executable to implement plugging a different pluggable converter module into the framework, wherein the different converter module is configured to convert office documents in a different office document format to and from small device documents in a different small device format. 44. The tangible, computer-accessible storage medium as recited in claim 42 , wherein the program instructions are further computer-executable to implement plugging a pluggable merger module into the framework, wherein the merger module is configured to merge modified versions of small device documents in the different small device format with corresponding office documents in the different office document format to generate synchronized versions of the office documents. | 0.874802 |
9,454,615 | 11 | 16 | 11. A system for predicting user behaviors based on term taxonomies, comprising: a processing unit; and a memory, the memory containing instructions that, when executed by the processing unit, configure the system to: generate phrases respective of user generated content, wherein each phrase is a sentiment phrase or a non-sentiment phrase, each sentiment phrase including at least one word describing a sentiment; identify at least one connection between at least two of the generated phrases, wherein each connection is a direct connection or a hidden connection; generate at least one term taxonomy based on the identified at least one connection, wherein each term taxonomy is an association between a non-sentiment phrase and at least one of a plurality of sentiment phrases; periodically analyze the at least one term taxonomy to determine at least one trend of each non-sentiment phrase respective of the associated plurality of sentiment phrases; and generate a prediction of future behavior of the at least one trend with respect to the at least one term taxonomy. | 11. A system for predicting user behaviors based on term taxonomies, comprising: a processing unit; and a memory, the memory containing instructions that, when executed by the processing unit, configure the system to: generate phrases respective of user generated content, wherein each phrase is a sentiment phrase or a non-sentiment phrase, each sentiment phrase including at least one word describing a sentiment; identify at least one connection between at least two of the generated phrases, wherein each connection is a direct connection or a hidden connection; generate at least one term taxonomy based on the identified at least one connection, wherein each term taxonomy is an association between a non-sentiment phrase and at least one of a plurality of sentiment phrases; periodically analyze the at least one term taxonomy to determine at least one trend of each non-sentiment phrase respective of the associated plurality of sentiment phrases; and generate a prediction of future behavior of the at least one trend with respect to the at least one term taxonomy. 16. The system of claim 11 , wherein the system is further configured to: determine a probability that at least a first phrase and at least a second phrase of the generated phrases appear together. | 0.719373 |
9,641,631 | 10 | 11 | 10. A computer-implemented personalized content recommendation and management method comprising: creating, storing and managing user profile information in the user profile repository; utilizing an algorithm to generate targeted personalized content recommendations for a user based on said user's profile information; seamlessly propagating a user's profile across multiple third-party websites and applications; building social instructions based on said user's profile; aggregating content across multiple third-party websites and applications to be presented to said user based on the generated personalized content recommendations, and organizing said aggregated content; storing information about said personalized content to be utilized by said system in the generation of said user's personalized content recommendations; providing a developer portal dashboard wherein the developer portal dashboard prompts a publisher to add a system generated button to the publisher's websites and/or applications in order to connect the websites and/or applications with a network of the system; accessing a user's system account by a system log in and/or by a user's social network login thereby authorizing the system to access said user's personal data; and generating analytics from a specified time period to measure a system generated button's effect on access to particular third party websites and applications. | 10. A computer-implemented personalized content recommendation and management method comprising: creating, storing and managing user profile information in the user profile repository; utilizing an algorithm to generate targeted personalized content recommendations for a user based on said user's profile information; seamlessly propagating a user's profile across multiple third-party websites and applications; building social instructions based on said user's profile; aggregating content across multiple third-party websites and applications to be presented to said user based on the generated personalized content recommendations, and organizing said aggregated content; storing information about said personalized content to be utilized by said system in the generation of said user's personalized content recommendations; providing a developer portal dashboard wherein the developer portal dashboard prompts a publisher to add a system generated button to the publisher's websites and/or applications in order to connect the websites and/or applications with a network of the system; accessing a user's system account by a system log in and/or by a user's social network login thereby authorizing the system to access said user's personal data; and generating analytics from a specified time period to measure a system generated button's effect on access to particular third party websites and applications. 11. The computer-implemented personalized content recommendation and management method of claim 10 wherein the user's system log in comprises a user's email address. | 0.92268 |
8,666,757 | 1 | 22 | 1. A computer-implemented method for generating fraud indication within a prospective payment system (PPS), the method being implemented by one or more data processors forming part of at least one computer and comprising: generating, by at least one data processor, profiles of service provider activities rendered for payment by a facility, the profiles being dynamically derived from transactional level data associated with service provider activities; calculating, by at least one data processor, summary variables from the profiles input into an unsupervised predictive model for at least one particular metric, the at least one metric at any desired level of and associated with the PPS comprising one of: an indicator of total costs claimed by the facility at that level; an indicator of the facility's average patient length of stay at that level; and an indicator of total claims made by the facility at that level; determining, by at least one data processor, a deviation measure based on comparing the summary variables with industry-wide peer data for the particular metric, wherein comparing the summary variable with industry-wide peer data comprises: determining, by at least one data processor, a first distribution based on the summary variables; determining, by at least one data processor, a second distribution based on the industry-wide peer data; and detecting, by at least one data processor, aberrations between the first distribution and the second distribution; integrating, by at least one data processor, the aberrations detected to produce normalized variables; and deriving, by at least one data processor, an indicator from the deviation measure, the indicator representing the fraud indication based on aberrations associated with the deviation measure; wherein a profile is generated by: generating a profile of a first entity, generating a profile of at least one second entity that interacts with the first entity through transactions with the first entity, generating a profile of at least one third entity comprising a combination of the profiles of the interacting first and second entities, and enhancing the profile of the first entity with the profile of the at least one third entity, wherein an interacting pair of entities is itself an entity. | 1. A computer-implemented method for generating fraud indication within a prospective payment system (PPS), the method being implemented by one or more data processors forming part of at least one computer and comprising: generating, by at least one data processor, profiles of service provider activities rendered for payment by a facility, the profiles being dynamically derived from transactional level data associated with service provider activities; calculating, by at least one data processor, summary variables from the profiles input into an unsupervised predictive model for at least one particular metric, the at least one metric at any desired level of and associated with the PPS comprising one of: an indicator of total costs claimed by the facility at that level; an indicator of the facility's average patient length of stay at that level; and an indicator of total claims made by the facility at that level; determining, by at least one data processor, a deviation measure based on comparing the summary variables with industry-wide peer data for the particular metric, wherein comparing the summary variable with industry-wide peer data comprises: determining, by at least one data processor, a first distribution based on the summary variables; determining, by at least one data processor, a second distribution based on the industry-wide peer data; and detecting, by at least one data processor, aberrations between the first distribution and the second distribution; integrating, by at least one data processor, the aberrations detected to produce normalized variables; and deriving, by at least one data processor, an indicator from the deviation measure, the indicator representing the fraud indication based on aberrations associated with the deviation measure; wherein a profile is generated by: generating a profile of a first entity, generating a profile of at least one second entity that interacts with the first entity through transactions with the first entity, generating a profile of at least one third entity comprising a combination of the profiles of the interacting first and second entities, and enhancing the profile of the first entity with the profile of the at least one third entity, wherein an interacting pair of entities is itself an entity. 22. The computer-implemented method according to claim 1 , wherein the facility is selected from a group of entities comprising healthcare related facilities, healthcare providers, patients, beneficiaries, healthcare claims processors, and skilled nursing facilities. | 0.784677 |
9,183,294 | 10 | 14 | 10. A system, comprising: a memory device for storing a program; a processor in communication with the memory device, the processor operative with the program to: define a meta-ontology, wherein the meta-ontology includes high-level properties and their mappings to specific properties defined in a plurality of different ontologies; receive a question, wherein the question is associated with a high-level property; and provide an answer to the question, wherein the answer is determined by referring only to the meta-ontology to retrieve required information, and in answering a question about a concept, synonyms of the concept's name used in the question are retrieved, and then, the synonyms are used to retrieve corresponding uniform resource identifiers, wherein a synonym is a high-level property included in a resource description framework description of each of the ontologies, wherein the resource description framework description of a first ontology of the ontologies describes how a first synonym corresponds to a first property from the first ontology and how the first synonym is queried such that the first synonym can be retrieved from the first ontology. | 10. A system, comprising: a memory device for storing a program; a processor in communication with the memory device, the processor operative with the program to: define a meta-ontology, wherein the meta-ontology includes high-level properties and their mappings to specific properties defined in a plurality of different ontologies; receive a question, wherein the question is associated with a high-level property; and provide an answer to the question, wherein the answer is determined by referring only to the meta-ontology to retrieve required information, and in answering a question about a concept, synonyms of the concept's name used in the question are retrieved, and then, the synonyms are used to retrieve corresponding uniform resource identifiers, wherein a synonym is a high-level property included in a resource description framework description of each of the ontologies, wherein the resource description framework description of a first ontology of the ontologies describes how a first synonym corresponds to a first property from the first ontology and how the first synonym is queried such that the first synonym can be retrieved from the first ontology. 14. The system of claim 10 , wherein the meta-ontology includes information about how to generate queries that are used to retrieve information associated with the high-level properties from the ontologies. | 0.729659 |
9,965,484 | 1 | 9 | 1. A method, comprising: identifying a source file opened within a source application; determining a copy point within the source file, the determining the copy point within the source file comprises determining a location within the source file associated with a row of data and determining the copy point based on the location within the source file; acquiring a set of data strings corresponding with a set of data fields from the source file based on the copy point, the set of data fields corresponds with the row of data located within a first worksheet and hierarchical data located within a second worksheet different from the first worksheet that is linked to the row of data via one or more links, the set of data strings comprises a hidden string that was not displayed within the source file when the copy point was determined, the acquiring the set of data strings includes acquiring a copy template based on the copy point, the copy template includes a link of the one or more links to the hidden string, the acquiring the set of data strings includes extracting the row of data from the first worksheet and extracting the hidden string that was not displayed within the source file when the copy point was determined from the second worksheet different from the first worksheet using the link; detecting a paste triggering event; identifying a target file opened in a target application different from the source application in response to detecting the paste triggering event; identifying a paste template based on the target application, the paste template comprises mappings for a subset of the set of data fields less than all fields of the set of data fields into locations within the target file; writing a subset of the set of data strings less than all data strings of the set of data strings corresponding with the subset of the set of data fields to the locations within the target file using the paste template, the subset of the set of data strings includes the hidden string; and displaying at least a portion of the target file comprising the subset of the set of data strings, the displaying the at least a portion of the target file includes displaying the hidden string within the target file. | 1. A method, comprising: identifying a source file opened within a source application; determining a copy point within the source file, the determining the copy point within the source file comprises determining a location within the source file associated with a row of data and determining the copy point based on the location within the source file; acquiring a set of data strings corresponding with a set of data fields from the source file based on the copy point, the set of data fields corresponds with the row of data located within a first worksheet and hierarchical data located within a second worksheet different from the first worksheet that is linked to the row of data via one or more links, the set of data strings comprises a hidden string that was not displayed within the source file when the copy point was determined, the acquiring the set of data strings includes acquiring a copy template based on the copy point, the copy template includes a link of the one or more links to the hidden string, the acquiring the set of data strings includes extracting the row of data from the first worksheet and extracting the hidden string that was not displayed within the source file when the copy point was determined from the second worksheet different from the first worksheet using the link; detecting a paste triggering event; identifying a target file opened in a target application different from the source application in response to detecting the paste triggering event; identifying a paste template based on the target application, the paste template comprises mappings for a subset of the set of data fields less than all fields of the set of data fields into locations within the target file; writing a subset of the set of data strings less than all data strings of the set of data strings corresponding with the subset of the set of data fields to the locations within the target file using the paste template, the subset of the set of data strings includes the hidden string; and displaying at least a portion of the target file comprising the subset of the set of data strings, the displaying the at least a portion of the target file includes displaying the hidden string within the target file. 9. The method of claim 1 , wherein: the identifying a paste template based on the target application includes identifying the paste template from a plurality of paste templates based on the target application, a first paste template of the plurality of paste templates includes a first set of data field mappings into the target file, a second paste template of the plurality of paste templates includes a second set of data field mappings into the target file that are different from the first set of data field mappings into the target file. | 0.562802 |
9,468,848 | 1 | 3 | 1. A method for assigning a gesture dictionary, comprising: determining a characteristic of a user that is independent of a motion or pose made by the user; correlating the characteristic of the user to a first gesture dictionary of a plurality of gesture dictionaries, each gesture dictionary of the plurality of gesture dictionaries identifying a set of input commands to a computer that may be invoked by a performance of a corresponding gesture; assigning the first gesture dictionary to the user, the first gesture dictionary corresponding to the characteristic; and processing captured data with the first gesture dictionary to identify whether a second motion or pose by the user in the captured data invokes an input command to the computer. | 1. A method for assigning a gesture dictionary, comprising: determining a characteristic of a user that is independent of a motion or pose made by the user; correlating the characteristic of the user to a first gesture dictionary of a plurality of gesture dictionaries, each gesture dictionary of the plurality of gesture dictionaries identifying a set of input commands to a computer that may be invoked by a performance of a corresponding gesture; assigning the first gesture dictionary to the user, the first gesture dictionary corresponding to the characteristic; and processing captured data with the first gesture dictionary to identify whether a second motion or pose by the user in the captured data invokes an input command to the computer. 3. The method of claim 1 , wherein the user is a first user and correlating the characteristic of the user to the first gesture dictionary comprises: correlating the characteristic of the first user to a characteristic of a second user, and assigning a gesture dictionary assigned to the second user to the first user. | 0.695985 |
8,312,440 | 11 | 12 | 11. The computer program product of claim 10 further comprising applying at least one template to the source code of the program to obtain one or more abstract coding styles. | 11. The computer program product of claim 10 further comprising applying at least one template to the source code of the program to obtain one or more abstract coding styles. 12. The computer program product of claim 11 further comprising: (1) parsing the source code and extracting program elements; and (2) computing an abstract coding style of each program element by applying a corresponding coding style template. | 0.922562 |
7,805,441 | 1 | 5 | 1. A method comprising: parsing, in a computer, an original search query received from a user over a network through a query web page to obtain at least one query term; retrieving a plurality of keywords from a database related contextually to a category of said query web page and said at least one query term; generating, in a computer, a set of modified queries, each modified query comprising said at least one query term and at least one keyword of said plurality of keywords; retrieving, in a computer, a plurality of advertising offers for each modified query and for said original query; removing, in a computer, any advertising offer that is not related contextually to said category of said query web page; and ranking, in a computer, the advertising offers not removed based on at least one predetermined parameter. | 1. A method comprising: parsing, in a computer, an original search query received from a user over a network through a query web page to obtain at least one query term; retrieving a plurality of keywords from a database related contextually to a category of said query web page and said at least one query term; generating, in a computer, a set of modified queries, each modified query comprising said at least one query term and at least one keyword of said plurality of keywords; retrieving, in a computer, a plurality of advertising offers for each modified query and for said original query; removing, in a computer, any advertising offer that is not related contextually to said category of said query web page; and ranking, in a computer, the advertising offers not removed based on at least one predetermined parameter. 5. The method according to claim 1 , wherein: said at least one predetermined parameter further comprises a combination between a “pay-per-click” (PPC) categorization parameter and a “click-through-rate” (CTR) categorization parameter. | 0.759714 |
10,032,191 | 12 | 16 | 12. The method of claim 1 , wherein the client device and the networked media device reside on networks that are incommunicable with each other comprising at least one of a firewall separation, a different network separation, a physical separation, and an unreachable connection separation, and wherein the sandboxed application of the security sandbox of the client device and the sandbox reachable service of the networked media device communicate with each other through a relay service employed by a pairing server having a discovery module and a relay module to facilitate a trusted communication between the sandboxed application and the sandbox reachable service. | 12. The method of claim 1 , wherein the client device and the networked media device reside on networks that are incommunicable with each other comprising at least one of a firewall separation, a different network separation, a physical separation, and an unreachable connection separation, and wherein the sandboxed application of the security sandbox of the client device and the sandbox reachable service of the networked media device communicate with each other through a relay service employed by a pairing server having a discovery module and a relay module to facilitate a trusted communication between the sandboxed application and the sandbox reachable service. 16. The method of claim 12 , further comprising: initiating the relay service through at least one of a series of web pages where information is communicated using hyperlinks that point at the pairing server, and a form having a confirmation dialog that is submitted back to the pairing server, and wherein a global unique identifier is masked through the pairing server when the confirmation dialog is served from the pairing server. | 0.965045 |
10,097,785 | 11 | 15 | 11. A method of selectively supplementing main program video content with a sign language video content, comprising: at a video receiver device, receiving data representing audio and at least one frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content having a plurality of locations to accept the sign language video content; at the video receiver device, receiving a signal indicative of a selection of a first location of the plurality of locations for display of the sign language video content; and responsive to receiving the signal indicative of the selection of the first location, at a content circuit within the video receiver device, presenting in the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; responsive to a signal to view the sign language video content, disabling a video scaler; and responsive to a signal not to view the sign language video content, enabling the video scaler. | 11. A method of selectively supplementing main program video content with a sign language video content, comprising: at a video receiver device, receiving data representing audio and at least one frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content having a plurality of locations to accept the sign language video content; at the video receiver device, receiving a signal indicative of a selection of a first location of the plurality of locations for display of the sign language video content; and responsive to receiving the signal indicative of the selection of the first location, at a content circuit within the video receiver device, presenting in the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; responsive to a signal to view the sign language video content, disabling a video scaler; and responsive to a signal not to view the sign language video content, enabling the video scaler. 15. The method according to claim 11 , where the content circuit comprises a hardware content replacement state machine. | 0.926918 |
9,171,141 | 3 | 15 | 3. A method, comprising: determining an active point of a contact patch when a touchscreen of a handheld electronic device is touched by a user as a first keystroke, the active point being a point at which the touch of the user is determined to have been intended; determining the active point is near a hot spot for each of multiple keys on a virtual keyboard on the touchscreen, the hot spot for a key being a spot that the device considers to be a center of the key; selecting a particular key from among the multiple keys as a key intended by the user for the first keystroke; including a particular character represented by the particular key as a character in an ongoing stream of text input by the user; determining whether spelling and context considerations are finished for the first keystroke; if spelling and context considerations for the first keystroke are not finished, processing one or more additional keystrokes, and determining after each additional keystrokes whether spelling and context considerations are finished for the first keystroke; and upon determining that the spelling and context considerations for the first keystroke are finished, determining based on the spelling and context considerations for the first keystroke whether to change the selection of the particular key as the key intended by the user for the first keystroke. | 3. A method, comprising: determining an active point of a contact patch when a touchscreen of a handheld electronic device is touched by a user as a first keystroke, the active point being a point at which the touch of the user is determined to have been intended; determining the active point is near a hot spot for each of multiple keys on a virtual keyboard on the touchscreen, the hot spot for a key being a spot that the device considers to be a center of the key; selecting a particular key from among the multiple keys as a key intended by the user for the first keystroke; including a particular character represented by the particular key as a character in an ongoing stream of text input by the user; determining whether spelling and context considerations are finished for the first keystroke; if spelling and context considerations for the first keystroke are not finished, processing one or more additional keystrokes, and determining after each additional keystrokes whether spelling and context considerations are finished for the first keystroke; and upon determining that the spelling and context considerations for the first keystroke are finished, determining based on the spelling and context considerations for the first keystroke whether to change the selection of the particular key as the key intended by the user for the first keystroke. 15. The method of claim 3 , wherein the context considerations include examining the context of a sentence to select which of multiple words was intended by the user if more than one possible character for the first keystroke forms a real word in a sentence. | 0.772487 |
9,558,170 | 10 | 11 | 10. A system comprising: one or more processors; a table generator stored on a memory and executable by the one or more processors, the table generator configured to generate a table from form images and store the table in a database as a collection of the form images, a first cell of the table including image data and symbolic data corresponding to first information, a second cell of the table including image data corresponding to second information; a state recorder stored on the memory and executable by the one or more processors, the state recorder configured to receive an operation for modifying a first view of the collection from a first user; a view creation module stored on a memory and executable by the one or more processors, the view creation module configured to create a second view of the collection based on the operation; and a communication unit stored on a memory and executable by the one or more processors, the communication unit configured to provide the first view of the collection to the first user by displaying the image data corresponding to the first information in the first cell and displaying the image data corresponding to the second information in the second cell, wherein the first cell, including both the image data and the symbolic data corresponding to the first information, is highlighted to indicate that symbolic data is available for the first cell and to be visually different from the second cell including only the image data corresponding to the second information, and provide the second view of the collection to the first user by displaying the symbolic data corresponding to the first information in the first cell and displaying the image data corresponding to the second information in the second cell. | 10. A system comprising: one or more processors; a table generator stored on a memory and executable by the one or more processors, the table generator configured to generate a table from form images and store the table in a database as a collection of the form images, a first cell of the table including image data and symbolic data corresponding to first information, a second cell of the table including image data corresponding to second information; a state recorder stored on the memory and executable by the one or more processors, the state recorder configured to receive an operation for modifying a first view of the collection from a first user; a view creation module stored on a memory and executable by the one or more processors, the view creation module configured to create a second view of the collection based on the operation; and a communication unit stored on a memory and executable by the one or more processors, the communication unit configured to provide the first view of the collection to the first user by displaying the image data corresponding to the first information in the first cell and displaying the image data corresponding to the second information in the second cell, wherein the first cell, including both the image data and the symbolic data corresponding to the first information, is highlighted to indicate that symbolic data is available for the first cell and to be visually different from the second cell including only the image data corresponding to the second information, and provide the second view of the collection to the first user by displaying the symbolic data corresponding to the first information in the first cell and displaying the image data corresponding to the second information in the second cell. 11. The system of claim 10 , wherein the communication unit is further configured to provide a list of views of the collection including the first view of the collection to a second user, the second user having access to the collection, wherein the state recorder is configured to receive a selection of the first view of the collection from the second user, and further comprising: a query engine configured to run a query associated with the first view of the collection; and wherein the communication unit is further configured to provide the first view of the collection to the second user. | 0.50084 |
9,645,656 | 1 | 10 | 1. A method for text input of ambiguous input sequences entered by a device user, the method comprising: a primary process of receiving a user input on an input device having a plurality of selectable input items, each input item being associated with at least one character, an input sequence being generated in dependence of selection of input items, wherein the generated input sequence corresponds to the sequence of input items that have been selected, and wherein the generated input sequence has a textual interpretation of the characters associated with the input sequence, wherein the textual interpretation is ambiguous, and displaying on a display the textual interpretation; and a secondary process, initiated upon receiving an input associated with a delete-character command and comprising deleting a character of the textual interpretation, at a position thereof, wherein the deleted character corresponds to a first input item, and returning to the primary process where textual interpretations associated with the deleted character for said position are excluded, and displaying an updated textual interpretation, wherein the updated textual interpretation, at a position corresponding to the deleted character of the textual interpretation, has another character being associated with a second input item of the input device, wherein the second input item is in vicinity of the first input item; wherein the primary and secondary processes are performed until a user input associated with a confirm-text command is received. | 1. A method for text input of ambiguous input sequences entered by a device user, the method comprising: a primary process of receiving a user input on an input device having a plurality of selectable input items, each input item being associated with at least one character, an input sequence being generated in dependence of selection of input items, wherein the generated input sequence corresponds to the sequence of input items that have been selected, and wherein the generated input sequence has a textual interpretation of the characters associated with the input sequence, wherein the textual interpretation is ambiguous, and displaying on a display the textual interpretation; and a secondary process, initiated upon receiving an input associated with a delete-character command and comprising deleting a character of the textual interpretation, at a position thereof, wherein the deleted character corresponds to a first input item, and returning to the primary process where textual interpretations associated with the deleted character for said position are excluded, and displaying an updated textual interpretation, wherein the updated textual interpretation, at a position corresponding to the deleted character of the textual interpretation, has another character being associated with a second input item of the input device, wherein the second input item is in vicinity of the first input item; wherein the primary and secondary processes are performed until a user input associated with a confirm-text command is received. 10. The method of claim 1 , wherein textual interpretation is ambiguous because the selected input item is associated with a plurality of characters. | 0.921331 |
9,940,016 | 12 | 15 | 12. A method performed by a computing device, the method comprising: obtaining input data from a keyboard that accepts shape-writing and radial entry, the input data indicating that a current stroke performed on the keyboard moved in a specific direction; identifying a shape-writing input and a radial entry input that can both be entered to the keyboard via strokes that move in the specific direction; based at least on a characteristic of the current stroke, disambiguating the current stroke to determine whether the current stroke is the shape-writing input or the radial entry input; in a first instance when the current stroke is disambiguated as the shape-writing input, entering a word on the computing device, the word being identified by the shape-writing input; and in a second instance when the current stroke is disambiguated as the radial entry input, enter a character on the computing device. | 12. A method performed by a computing device, the method comprising: obtaining input data from a keyboard that accepts shape-writing and radial entry, the input data indicating that a current stroke performed on the keyboard moved in a specific direction; identifying a shape-writing input and a radial entry input that can both be entered to the keyboard via strokes that move in the specific direction; based at least on a characteristic of the current stroke, disambiguating the current stroke to determine whether the current stroke is the shape-writing input or the radial entry input; in a first instance when the current stroke is disambiguated as the shape-writing input, entering a word on the computing device, the word being identified by the shape-writing input; and in a second instance when the current stroke is disambiguated as the radial entry input, enter a character on the computing device. 15. The method of claim 12 , the characteristic being a pressure applied during the current stroke. | 0.945183 |
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