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7,548,913 | 21 | 23 | 21. A method, performed on one or more processing devices, for generating a report from multiple sources, the method comprising: (I) obtaining a topic based on input queries relating to the topic; (II) obtaining information about the topic from the multiple sources, the information comprising excerpts from the multiple sources that meet one or more criteria; and (III) generating the report using the excerpts, wherein generating the report comprises: (i) obtaining subtopics for the excerpts; (ii) organizing the excerpts based on the subtopics; and (iii) editing text in the excerpts; (IV) wherein obtaining information about the topic comprises: (i) assigning the topic to one or more categories; (ii) determining whether the topic is ambiguous based on the one or more categories to which the topic is assigned; (iii) wherein, if the topic is determined to be ambiguous, the method comprises: disambiguating the topic by combining names of the one or more categories with the topic, thereby producing a disambiguated topic; and formulating a search query based on the disambiguated topic; (iv) wherein, if the topic is determined not to be ambiguous, the method comprises: formulating the search query based on the topic; (v) searching the multiple sources using the search query; (vi) receiving search results as a result of searching the multiple sources, the search results comprising documents corresponding to the search query; (vii) selecting a subset of the documents from which to extract the excerpts, the subset of the documents being selected based on intrinsic metrics and extrinsic metrics, the intrinsic metrics comprising data from the documents and the extrinsic metrics comprising data relating to the documents but not from the documents; and (viii) extracting the excerpts from the subset the documents, wherein the excerpts are extracted from the subset of documents based on the one or more criteria, the excerpts comprising text and non-text. | 21. A method, performed on one or more processing devices, for generating a report from multiple sources, the method comprising: (I) obtaining a topic based on input queries relating to the topic; (II) obtaining information about the topic from the multiple sources, the information comprising excerpts from the multiple sources that meet one or more criteria; and (III) generating the report using the excerpts, wherein generating the report comprises: (i) obtaining subtopics for the excerpts; (ii) organizing the excerpts based on the subtopics; and (iii) editing text in the excerpts; (IV) wherein obtaining information about the topic comprises: (i) assigning the topic to one or more categories; (ii) determining whether the topic is ambiguous based on the one or more categories to which the topic is assigned; (iii) wherein, if the topic is determined to be ambiguous, the method comprises: disambiguating the topic by combining names of the one or more categories with the topic, thereby producing a disambiguated topic; and formulating a search query based on the disambiguated topic; (iv) wherein, if the topic is determined not to be ambiguous, the method comprises: formulating the search query based on the topic; (v) searching the multiple sources using the search query; (vi) receiving search results as a result of searching the multiple sources, the search results comprising documents corresponding to the search query; (vii) selecting a subset of the documents from which to extract the excerpts, the subset of the documents being selected based on intrinsic metrics and extrinsic metrics, the intrinsic metrics comprising data from the documents and the extrinsic metrics comprising data relating to the documents but not from the documents; and (viii) extracting the excerpts from the subset the documents, wherein the excerpts are extracted from the subset of documents based on the one or more criteria, the excerpts comprising text and non-text. 23. The method of claim 21 , wherein the multiple sources comprise Web sites and the report comprises a Web page. | 0.940085 |
6,145,003 | 2 | 3 | 2. The method of claim 1, wherein the primary document address specification includes the first protocol and a first network address, and the secondary document address specification includes the second protocol and a second network address, and wherein the first protocol is different from the second protocol. | 2. The method of claim 1, wherein the primary document address specification includes the first protocol and a first network address, and the secondary document address specification includes the second protocol and a second network address, and wherein the first protocol is different from the second protocol. 3. The method of claim 2, wherein the first protocol is HTTP and the second protocol is FILE. | 0.969942 |
10,146,751 | 1 | 3 | 1. A computer-implemented method for detecting hidden information in an unstructured data source, and generating a new data object representing the detected information, comprising: defining a first attribute for identifying a target term in a text content, wherein the first attribute comprises a semantic or syntactic attribute, wherein the semantic attribute includes being or representing a name of an object or a property associated with an object; defining a target term as a term that is associated with the first attribute; identifying a second attribute as an additional attribute associated with the target term, wherein the second attribute comprises a semantic or syntactic attribute; receiving a text content comprising a plurality of terms each comprising a word or a phrase; identifying a first term in the text content; identifying a second term in the context of the first term, wherein the context includes a term having a syntactic or semantic relation with the first term; identifying whether the second term refers to or represents the second attribute; if the second term is identified as referring to or representing the second attribute, then determining that the first term is the target term; generating a first data object comprising a first label associated with the first term, wherein the first label is not an element extracted from the text content, wherein the first attribute and the second attribute are not explicitly indicated in the text content; associating the first term to a search engine or a database; and when the first term is associated to a search engine, using the first term as an automatically-generated query to perform a search and determine a relevance for a search result, and displaying the search result in a user interface, wherein the first term is displayed in the user interface for an enhanced user interface functionality of highlighting a key information item that is automatically discovered from an unstructured data source and used for determining the relevance of the search result, wherein the search engine comprises an enterprise search engine, a job-seeking search engine, a recruitment search engine, a text analytics tool, and a data mining search engine; when the first term is associated to a database, compiling a data source comprising the first term, wherein the data source indicates that the first term is associated with the first label representing the first attribute that is hidden in the raw unstructured data source. | 1. A computer-implemented method for detecting hidden information in an unstructured data source, and generating a new data object representing the detected information, comprising: defining a first attribute for identifying a target term in a text content, wherein the first attribute comprises a semantic or syntactic attribute, wherein the semantic attribute includes being or representing a name of an object or a property associated with an object; defining a target term as a term that is associated with the first attribute; identifying a second attribute as an additional attribute associated with the target term, wherein the second attribute comprises a semantic or syntactic attribute; receiving a text content comprising a plurality of terms each comprising a word or a phrase; identifying a first term in the text content; identifying a second term in the context of the first term, wherein the context includes a term having a syntactic or semantic relation with the first term; identifying whether the second term refers to or represents the second attribute; if the second term is identified as referring to or representing the second attribute, then determining that the first term is the target term; generating a first data object comprising a first label associated with the first term, wherein the first label is not an element extracted from the text content, wherein the first attribute and the second attribute are not explicitly indicated in the text content; associating the first term to a search engine or a database; and when the first term is associated to a search engine, using the first term as an automatically-generated query to perform a search and determine a relevance for a search result, and displaying the search result in a user interface, wherein the first term is displayed in the user interface for an enhanced user interface functionality of highlighting a key information item that is automatically discovered from an unstructured data source and used for determining the relevance of the search result, wherein the search engine comprises an enterprise search engine, a job-seeking search engine, a recruitment search engine, a text analytics tool, and a data mining search engine; when the first term is associated to a database, compiling a data source comprising the first term, wherein the data source indicates that the first term is associated with the first label representing the first attribute that is hidden in the raw unstructured data source. 3. The computer-implemented method of claim 1 , wherein the second term is identified as referring to or representing the second attribute, the method further comprising: determining, based on the second attribute, a likelihood value for determining whether the first term is the target term, and selecting the first term as the target term if the likelihood value is above a threshold. | 0.635161 |
9,361,086 | 6 | 9 | 6. A computer program product for collating and intelligent sequencing of installation documentation, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to automatically create annotations that include one or more tags and name/value pairs, through natural language processing (NLP), wherein an NLP engine examines one or more product installation documents, searching for procedure names; program instructions to identify parameters and prerequisites associated with the procedure names to generate complete annotations; program instructions to insert the complete annotations into the one or more product installation documents using a structured data model; program instructions to, responsive to the inserting, parse the one or more product installation documents to identify annotations within the one or more product installation documents associated with installation procedures; program instructions to extract installation procedure descriptions, parameters, and prerequisites associated with the identified annotations; and program instructions to generate prescriptive step-by-step installation instructions that integrate installation procedures contained within the one or more product installation documents. | 6. A computer program product for collating and intelligent sequencing of installation documentation, the computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions comprising: program instructions to automatically create annotations that include one or more tags and name/value pairs, through natural language processing (NLP), wherein an NLP engine examines one or more product installation documents, searching for procedure names; program instructions to identify parameters and prerequisites associated with the procedure names to generate complete annotations; program instructions to insert the complete annotations into the one or more product installation documents using a structured data model; program instructions to, responsive to the inserting, parse the one or more product installation documents to identify annotations within the one or more product installation documents associated with installation procedures; program instructions to extract installation procedure descriptions, parameters, and prerequisites associated with the identified annotations; and program instructions to generate prescriptive step-by-step installation instructions that integrate installation procedures contained within the one or more product installation documents. 9. The computer program product of claim 6 , wherein program instructions to generate prescriptive step-by-step installation instructions that integrate installation procedures contained within the one or more installation documents further comprises: program instructions to group the installation procedures contained within the one or more installation documents into a set of grouped tasks. | 0.644404 |
10,055,450 | 1 | 8 | 1. A computer implemented method for representing temporal knowledge in Resource Definition Framework (RDF), for storing RDF temporal knowledge in a Knowledge Base that is managed by a Knowledge Base Management System (KBMS) that utilizes a Data Base Management System (DBMS), and for querying the temporal knowledge stored in the Knowledge Base, the method includes instructions for at least one of creating a temporal RDF triple, adding that triple to the Knowledge Base and querying the RDF temporal knowledge stored in the Knowledge Base, where the Knowledge Base and the KBMS and the DBMS reside in non-transitory computer-readable medium, the method comprises: creating, in memory, a temporal subject comprising a first value representing a subject, called a Subject Name, and a first period defined by a Begin1 time instant and an End1 time instant where the Begin1 time instant is less than the End1 time instant and where the first period includes all time instants starting from and including the Begin1 time instant up to but not including the End1 time instant; creating, in memory, a temporal object comprising a second value representing an object, called an Object Name, and a second period defined by a Begin2 time instant and an End2 time instant where the Begin2 time instant is less than the End2 time instant and where the second period includes all time instants starting from and including the Begin2 time instant up to but not including the End2 time instant; creating, in memory, a temporal predicate comprising a third value representing a predicate, called a Predicate Name, and a third period defined by a Begin3 time instant and an End3 time instant where the Begin3 time instant is less than or equal to the End3 time instant and where the third period includes all time instants starting from and including the Begin3 time instant up to but not including the End3 time instant; combining, in memory, the temporal subject, the temporal predicate and the temporal object, collectively called as a temporal resource, to form a temporal RDF triple, where the third period is a subset of the overlapping time instants of the first period and the second period; storing in the Knowledge Base one or more of the temporal subjects or temporal objects, after determining the existence and the time reference of the temporal subject or the temporal object, in one column of an Entity Table that has at least one column where a first value in a row of the Entity Table and a second value in a different row of the Entity Table do not have overlapping periods if the Subject Name of the first value and the Subject Name of the second value are the same or if the Object Name part of the first value and the Object Name of the second value are the same; storing in the Knowledge Base one or more of the temporal predicate, after determining the existence and time reference of the temporal predicate, in one column of a Predicate Table that has at least one column where a first value in a row of the Predicate Table and a second value in a different row of the Predicate Table do not have overlapping periods if the Predicate Name of the first value and the Predicate Name of the second value are the same; transforming, in memory, the temporal RDF triple into a quadruple where the first value is a triple Id which is a serial number identifying the temporal RDF triple, the second value is the Subject Name, the third value is the temporal predicate, and the fourth value is the Object Name, and storing in the Knowledge Base one or more of that quadruple in one or more rows of a Triple Table that has at least four columns, one temporal RDF triple for each row; mapping, in KBMS, the Subject Name in a row of the Entity Table and the Subject Name in a row of the Triple table to link these two tables, the Predicate Name in a row of the Predicate Table and the Predicate Name of the temporal predicate in a row of the Triple Table to link these two tables, and the Object Name in a row of the Entity Table and the Object Name in a row of the Triple table to link these two tables; parsing the query to an equivalent SQL query that the DBMS processes. | 1. A computer implemented method for representing temporal knowledge in Resource Definition Framework (RDF), for storing RDF temporal knowledge in a Knowledge Base that is managed by a Knowledge Base Management System (KBMS) that utilizes a Data Base Management System (DBMS), and for querying the temporal knowledge stored in the Knowledge Base, the method includes instructions for at least one of creating a temporal RDF triple, adding that triple to the Knowledge Base and querying the RDF temporal knowledge stored in the Knowledge Base, where the Knowledge Base and the KBMS and the DBMS reside in non-transitory computer-readable medium, the method comprises: creating, in memory, a temporal subject comprising a first value representing a subject, called a Subject Name, and a first period defined by a Begin1 time instant and an End1 time instant where the Begin1 time instant is less than the End1 time instant and where the first period includes all time instants starting from and including the Begin1 time instant up to but not including the End1 time instant; creating, in memory, a temporal object comprising a second value representing an object, called an Object Name, and a second period defined by a Begin2 time instant and an End2 time instant where the Begin2 time instant is less than the End2 time instant and where the second period includes all time instants starting from and including the Begin2 time instant up to but not including the End2 time instant; creating, in memory, a temporal predicate comprising a third value representing a predicate, called a Predicate Name, and a third period defined by a Begin3 time instant and an End3 time instant where the Begin3 time instant is less than or equal to the End3 time instant and where the third period includes all time instants starting from and including the Begin3 time instant up to but not including the End3 time instant; combining, in memory, the temporal subject, the temporal predicate and the temporal object, collectively called as a temporal resource, to form a temporal RDF triple, where the third period is a subset of the overlapping time instants of the first period and the second period; storing in the Knowledge Base one or more of the temporal subjects or temporal objects, after determining the existence and the time reference of the temporal subject or the temporal object, in one column of an Entity Table that has at least one column where a first value in a row of the Entity Table and a second value in a different row of the Entity Table do not have overlapping periods if the Subject Name of the first value and the Subject Name of the second value are the same or if the Object Name part of the first value and the Object Name of the second value are the same; storing in the Knowledge Base one or more of the temporal predicate, after determining the existence and time reference of the temporal predicate, in one column of a Predicate Table that has at least one column where a first value in a row of the Predicate Table and a second value in a different row of the Predicate Table do not have overlapping periods if the Predicate Name of the first value and the Predicate Name of the second value are the same; transforming, in memory, the temporal RDF triple into a quadruple where the first value is a triple Id which is a serial number identifying the temporal RDF triple, the second value is the Subject Name, the third value is the temporal predicate, and the fourth value is the Object Name, and storing in the Knowledge Base one or more of that quadruple in one or more rows of a Triple Table that has at least four columns, one temporal RDF triple for each row; mapping, in KBMS, the Subject Name in a row of the Entity Table and the Subject Name in a row of the Triple table to link these two tables, the Predicate Name in a row of the Predicate Table and the Predicate Name of the temporal predicate in a row of the Triple Table to link these two tables, and the Object Name in a row of the Entity Table and the Object Name in a row of the Triple table to link these two tables; parsing the query to an equivalent SQL query that the DBMS processes. 8. The method of claim 1 , wherein the DBMS may be replaced by a relational DBMS, or by a NoSQL DBMS, or by an object relational DBMS, or a native triple store, or by any other DBMS software by changing the definitions of the Entity Table, the Predicate Table, and the Triple Table according to the definitional requirements of these DBMS. | 0.946898 |
9,740,922 | 35 | 40 | 35. The system of claim 20 , comprising transferring the data capsule to a repository coupled to the processor. | 35. The system of claim 20 , comprising transferring the data capsule to a repository coupled to the processor. 40. The system of claim 35 , wherein the repository provides linear sequencing of a plurality of data capsules. | 0.949129 |
8,612,208 | 24 | 30 | 24. An apparatus including a memory device having instructions stored thereon that, in response to execution by a computing device, cause the computing device to perform operations comprising: parsing content of a received query into elements; associating an annotation with respective ones of the elements; comparing a first condition of at least one rule from a rules dictionary against the elements and the annotation; comparing a second condition of at least one rule from the rules dictionary against peripheral information distinct from the content of the query; generating a query response based at least in part on the comparisons and displaying the generated query response as an answer to the query; selectively firing at least one action of at least one of the rules from the rules dictionary based on respective results of the comparisons, wherein the subset of the information retrieval technologies comprises a first information retrieval technology and a second information retrieval technology, wherein selectively firing at least one action comprises selectively firing a plurality of actions; in response to at least one of the firing actions, operating a subset of information retrieval technologies based on the selectively fired action to produce respective information; generating the query response based on said respective information; matching, via at least one of the rules from the rules dictionary, a plurality of the elements and the annotation to a concept representing an intent of the query content, wherein each of the plurality of the elements and the annotation corresponds to a word of the query content, wherein the matching utilizes a regular expression language and wherein the operations further comprise determining if at least one of the elements and the annotation shares a common ancestor in a multi-layered concept repository with a question example of the at least one of the rules; in response to a first one of the firing actions, operating the first information retrieval technology; in response to a second one of the firing actions, operating a second distinct one of the information retrieval technologies; and providing, via the second one of the information retrieval technologies, a managed answer. | 24. An apparatus including a memory device having instructions stored thereon that, in response to execution by a computing device, cause the computing device to perform operations comprising: parsing content of a received query into elements; associating an annotation with respective ones of the elements; comparing a first condition of at least one rule from a rules dictionary against the elements and the annotation; comparing a second condition of at least one rule from the rules dictionary against peripheral information distinct from the content of the query; generating a query response based at least in part on the comparisons and displaying the generated query response as an answer to the query; selectively firing at least one action of at least one of the rules from the rules dictionary based on respective results of the comparisons, wherein the subset of the information retrieval technologies comprises a first information retrieval technology and a second information retrieval technology, wherein selectively firing at least one action comprises selectively firing a plurality of actions; in response to at least one of the firing actions, operating a subset of information retrieval technologies based on the selectively fired action to produce respective information; generating the query response based on said respective information; matching, via at least one of the rules from the rules dictionary, a plurality of the elements and the annotation to a concept representing an intent of the query content, wherein each of the plurality of the elements and the annotation corresponds to a word of the query content, wherein the matching utilizes a regular expression language and wherein the operations further comprise determining if at least one of the elements and the annotation shares a common ancestor in a multi-layered concept repository with a question example of the at least one of the rules; in response to a first one of the firing actions, operating the first information retrieval technology; in response to a second one of the firing actions, operating a second distinct one of the information retrieval technologies; and providing, via the second one of the information retrieval technologies, a managed answer. 30. The apparatus of claim 24 , wherein the operations further comprise: determining a respective relevancy of each of at least some of the firing actions; and selectively performing each of the at least some of the firing actions based upon the respective relevancy. | 0.694508 |
9,020,972 | 18 | 21 | 18. The system of claim 17 , wherein the first template instruction includes a database query statement and the command keyword defines an operation of the database query statement. | 18. The system of claim 17 , wherein the first template instruction includes a database query statement and the command keyword defines an operation of the database query statement. 21. The system of claim 18 , wherein the database instruction includes an aggregate function, the aggregate function including a command parameter. | 0.970061 |
7,934,153 | 1 | 2 | 1. A computer for processing a structured document, the computer comprising: a user interface configured to receive user input; a document data storage configured to receive and store document data from the structured document; a data manipulator configured to receive the document data and the user input, said data manipulator operating to manipulate the received document data according to the user input, and to store the manipulated document data in said document data storage; and a data display unit configured to receive and process at least one of the user input and the document data, said data display unit operating to display different components of the processed document data in separate areas of a display pane, wherein said data display unit includes: a content display unit configured to display the content of the document data in a format appropriate for processing the content, said content display unit operating to display the content of the document data in a first area of the display pane; and a structure display unit configured to display the underlying structure of the document data in a graphical format appropriate for processing the underlying structure, wherein the display pane includes a visual document structure indicator pane, the visual document structure indicator pane including a WYSIWYG processing area in the first area of the display pane for processing and displaying the content of the document data; and a structure-based processing area in the second area of the display pane for processing and displaying the underlying structure of the document data, the underlying structure of the document comprising one or more blocks, each block comprising a portion of document content, each block being associated with one or more in-line elements, the structure based processing area including a first sub-pane for graphically displaying formatting information about in-line elements associated with a current block and the current character in the current block of the WYSIWYG processing area where a cursor is located, wherein each character that has formatting information associated with that character has the formatting information displayed in the second area of the display pane; and a second sub-pane for graphically displaying structural information about blocks being displayed in the WYSIWYG area, the structural information comprising information representing how the blocks are organized within the underlying structure of the document, wherein the structural information about the blocks being displayed in the WYSIWYG area is aligned with the corresponding block in the WYSIWYG area. | 1. A computer for processing a structured document, the computer comprising: a user interface configured to receive user input; a document data storage configured to receive and store document data from the structured document; a data manipulator configured to receive the document data and the user input, said data manipulator operating to manipulate the received document data according to the user input, and to store the manipulated document data in said document data storage; and a data display unit configured to receive and process at least one of the user input and the document data, said data display unit operating to display different components of the processed document data in separate areas of a display pane, wherein said data display unit includes: a content display unit configured to display the content of the document data in a format appropriate for processing the content, said content display unit operating to display the content of the document data in a first area of the display pane; and a structure display unit configured to display the underlying structure of the document data in a graphical format appropriate for processing the underlying structure, wherein the display pane includes a visual document structure indicator pane, the visual document structure indicator pane including a WYSIWYG processing area in the first area of the display pane for processing and displaying the content of the document data; and a structure-based processing area in the second area of the display pane for processing and displaying the underlying structure of the document data, the underlying structure of the document comprising one or more blocks, each block comprising a portion of document content, each block being associated with one or more in-line elements, the structure based processing area including a first sub-pane for graphically displaying formatting information about in-line elements associated with a current block and the current character in the current block of the WYSIWYG processing area where a cursor is located, wherein each character that has formatting information associated with that character has the formatting information displayed in the second area of the display pane; and a second sub-pane for graphically displaying structural information about blocks being displayed in the WYSIWYG area, the structural information comprising information representing how the blocks are organized within the underlying structure of the document, wherein the structural information about the blocks being displayed in the WYSIWYG area is aligned with the corresponding block in the WYSIWYG area. 2. The computer of claim 1 , wherein the structured document includes a mark-up language document. | 0.831034 |
7,818,340 | 1 | 3 | 1. A computer-implemented method comprising: interfacing with a search engine, the search engine to produce search results from one or more content datastores by matching a search query with content items stored in the one or more content datastores; receiving a sponsored concept from a sponsoring company at a server computer via a data network; receiving a first search query corresponding to a search by a first user, the first search query being used by the search engine to match with content items stored in the one or more content datastores, the first search query also being used to determine if the sponsored concept and the first search query fit within match criteria; determining, by use of a data processor, if the sponsored concept and the first search query fit within match criteria; generating for the first user, by use of the data processor, if the sponsored concept and the first search query fit within match criteria, a first link enabling the first user to initiate a conversation between the first user and an agent of the sponsoring company, the first link being a user interface element that can be activated by the first user; initiating a conversation between the first user and the agent of the sponsoring company upon activation of the first link; receiving a second search query corresponding to a search by a second user, the second search query being used by the search engine to match with content items stored in the one or more content datastores; determining if the first search query and the second search query fit within match criteria; generating for the first user, if the first search query and the second search query fit within match criteria, a second link enabling the first user to initiate a conversation between the first user and the second user, the second link being a user interface element that can be activated by the first user, the second link including at least a portion of the second search query from the second user; and initiating a conversation between the first user and the second user upon activation of the second link. | 1. A computer-implemented method comprising: interfacing with a search engine, the search engine to produce search results from one or more content datastores by matching a search query with content items stored in the one or more content datastores; receiving a sponsored concept from a sponsoring company at a server computer via a data network; receiving a first search query corresponding to a search by a first user, the first search query being used by the search engine to match with content items stored in the one or more content datastores, the first search query also being used to determine if the sponsored concept and the first search query fit within match criteria; determining, by use of a data processor, if the sponsored concept and the first search query fit within match criteria; generating for the first user, by use of the data processor, if the sponsored concept and the first search query fit within match criteria, a first link enabling the first user to initiate a conversation between the first user and an agent of the sponsoring company, the first link being a user interface element that can be activated by the first user; initiating a conversation between the first user and the agent of the sponsoring company upon activation of the first link; receiving a second search query corresponding to a search by a second user, the second search query being used by the search engine to match with content items stored in the one or more content datastores; determining if the first search query and the second search query fit within match criteria; generating for the first user, if the first search query and the second search query fit within match criteria, a second link enabling the first user to initiate a conversation between the first user and the second user, the second link being a user interface element that can be activated by the first user, the second link including at least a portion of the second search query from the second user; and initiating a conversation between the first user and the second user upon activation of the second link. 3. The computer-implemented method as claimed in claim 1 wherein the conversation initiated upon activation of the first link is accepted by a firewall on each of the systems operated by the sponsoring company and the first user. | 0.798415 |
7,676,743 | 19 | 20 | 19. A method of fitting graphical objects within a plurality of separate graphical frames in a document, each frame being associated with at least one value associated with a fitting attribute for fining one or more of the graphical objects in the frame, comprising: specifying details concerning the values of the attributes for the frames in a user interface; using an algorithm to automatically determine an optimized at least one value, wherein using the algorithm comprises: determining a plurality of intermediate optimized values, wherein each intermediate optimized value is associated with a particular frame; and selecting the optimized at least one value from said plurality of intermediate values, wherein said selecting is based on the specified details; and applying the optimized at least one value to each frame of the plurality of separate graphical frames to fit one or more of the graphical objects in each of the frames without modifying the size of the plurality of separate graphical frames. | 19. A method of fitting graphical objects within a plurality of separate graphical frames in a document, each frame being associated with at least one value associated with a fitting attribute for fining one or more of the graphical objects in the frame, comprising: specifying details concerning the values of the attributes for the frames in a user interface; using an algorithm to automatically determine an optimized at least one value, wherein using the algorithm comprises: determining a plurality of intermediate optimized values, wherein each intermediate optimized value is associated with a particular frame; and selecting the optimized at least one value from said plurality of intermediate values, wherein said selecting is based on the specified details; and applying the optimized at least one value to each frame of the plurality of separate graphical frames to fit one or more of the graphical objects in each of the frames without modifying the size of the plurality of separate graphical frames. 20. The method of claim 19 , further comprising, after applying the optimized at least one value, modifying at least one value for one frame in the group, and in response automatically modifying that value in the other frames in the group. | 0.770192 |
8,977,573 | 1 | 4 | 1. A method for identifying an author of a social media interaction, the method comprising: receiving a social media profile for a user interacting in a social media interaction in a social media environment, wherein the social media profile includes one or more identification parameters defining personal information registered to the user in the social media environment and one or more content parameters defining content of the user's social media interaction; for each of a plurality of customers registered in a contact center environment, receiving a contact center profile for the customer including one or more identification parameters defining personal information registered to the customer in the contact center environment and one or more content parameters defining content of the customer's past contact center interactions; and comparing the user's social media profile with the customer's contact center profile using an equivalence relationship that compares said respective identification parameters and content parameters of the profiles to determine a final equivalence of whether the social media user and contact center customer have the same identity, wherein a predetermined threshold is set to define a range for the equivalence relationship within which the social media user and contact center customer are determined to have the same identity, wherein the predetermined threshold is set in a testing phase to balance maximizing the accuracy and minimizing missed instances of determining users and customers to be identical that are previously known to be identical, wherein each of the user's and customer's profile is represented by a vector with each of the identification and content parameters thereof having values in a respective dimension and wherein the profiles are compared by calculating the vector difference between their representative vectors to measure a similarity between the social media profile and the contact center profile and wherein the content parameters comprise one or more content parameters selected from the group consisting of: linguistic richness, sentiment, tone, opinion, style, vocabulary, average length of sentences, slang and emoticons; and after determining the final equivalence that the social media user and contact center customer are determined to have the same identity, monitoring that user's social media interactions by the contact center for the associated customer. | 1. A method for identifying an author of a social media interaction, the method comprising: receiving a social media profile for a user interacting in a social media interaction in a social media environment, wherein the social media profile includes one or more identification parameters defining personal information registered to the user in the social media environment and one or more content parameters defining content of the user's social media interaction; for each of a plurality of customers registered in a contact center environment, receiving a contact center profile for the customer including one or more identification parameters defining personal information registered to the customer in the contact center environment and one or more content parameters defining content of the customer's past contact center interactions; and comparing the user's social media profile with the customer's contact center profile using an equivalence relationship that compares said respective identification parameters and content parameters of the profiles to determine a final equivalence of whether the social media user and contact center customer have the same identity, wherein a predetermined threshold is set to define a range for the equivalence relationship within which the social media user and contact center customer are determined to have the same identity, wherein the predetermined threshold is set in a testing phase to balance maximizing the accuracy and minimizing missed instances of determining users and customers to be identical that are previously known to be identical, wherein each of the user's and customer's profile is represented by a vector with each of the identification and content parameters thereof having values in a respective dimension and wherein the profiles are compared by calculating the vector difference between their representative vectors to measure a similarity between the social media profile and the contact center profile and wherein the content parameters comprise one or more content parameters selected from the group consisting of: linguistic richness, sentiment, tone, opinion, style, vocabulary, average length of sentences, slang and emoticons; and after determining the final equivalence that the social media user and contact center customer are determined to have the same identity, monitoring that user's social media interactions by the contact center for the associated customer. 4. The method of claim 1 , wherein the equivalence relationship defines a fuzzy comparison between the respective identification parameters and content parameters of the profiles to determine whether or not the social media user and contact center customer match. | 0.787903 |
7,970,660 | 1 | 13 | 1. A computer-implemented data mining method, comprising: storing, in an electronic data repository, user activity data associated with each of a plurality of users of an online system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog; programmatically identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization; programmatically analyzing the user activity data associated with the plurality of users, including the subset of users, by execution of code by a computer processor, to identify a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and creating, in computer storage, an association between the organization and the identified set of items. | 1. A computer-implemented data mining method, comprising: storing, in an electronic data repository, user activity data associated with each of a plurality of users of an online system that provides access to an electronic catalog, said user activity data reflecting user-generated events associated with particular items represented in the electronic catalog; programmatically identifying, among the plurality of users, a subset of users whose email addresses are associated with a particular organization; programmatically analyzing the user activity data associated with the plurality of users, including the subset of users, by execution of code by a computer processor, to identify a set of items that have experienced significantly higher levels of user activity among the subset of users than among the plurality of users; and creating, in computer storage, an association between the organization and the identified set of items. 13. The method of claim 1 , wherein the user-generated events include at least one of the following: (a) user submissions of item ratings, (b) shopping cart add events, (c) click-through events to item detail pages. | 0.714854 |
9,483,546 | 13 | 14 | 13. A non-transitory computer-readable medium storing a set of instructions that are executable by one or more processors to cause the one or more processors to perform a method to associate related records across a first list and a second list to a common entity, the method comprising: obtaining a first list and a second list, wherein the first list and the second list both include a plurality of records, and wherein each of the plurality of records is associated with a respective entity and includes one or more fields; grouping a record of the plurality of records of the first list into one or more first groups based on one or more fields of the record; grouping a record of the plurality of records of the second list into one or more second groups based on one or more fields of the record; pairing a record of the first group with a record of the second group, wherein the record of the first group and the record of the second group were grouped respectively based on similar one or more fields; evaluating, one or more times, a pair; associating, with an entity, the records of a pair, wherein the association is based on assessing the one or more evaluations of the pair. | 13. A non-transitory computer-readable medium storing a set of instructions that are executable by one or more processors to cause the one or more processors to perform a method to associate related records across a first list and a second list to a common entity, the method comprising: obtaining a first list and a second list, wherein the first list and the second list both include a plurality of records, and wherein each of the plurality of records is associated with a respective entity and includes one or more fields; grouping a record of the plurality of records of the first list into one or more first groups based on one or more fields of the record; grouping a record of the plurality of records of the second list into one or more second groups based on one or more fields of the record; pairing a record of the first group with a record of the second group, wherein the record of the first group and the record of the second group were grouped respectively based on similar one or more fields; evaluating, one or more times, a pair; associating, with an entity, the records of a pair, wherein the association is based on assessing the one or more evaluations of the pair. 14. The non-transitory computer-readable medium of claim 13 , wherein the grouping of records of the first group and the grouping of records of the second group are based on similar one or more fields. | 0.693598 |
9,652,483 | 1 | 6 | 1. A phrase-based indexing system comprising: a first tier of index servers including N index servers, each of which stores a portion of a phrase posting list for each of a plurality of phrases, each phrase posting list being associated with a phrase and a list of documents having at least one occurrence of the phrase; and M additional tiers of index servers, wherein: M is one to a predetermined number, each M th tier includes T index servers, where T is an integer multiple of N when M equals one and where T is an integer multiple of T for an (M−1) th tier when M is greater than or equal to two, and each M th tier index server stores a portion of a phrase posting list of each of a plurality of phrases, each phrase posting list being associated with a phrase and a list of documents having at least one occurrence of the phrase. | 1. A phrase-based indexing system comprising: a first tier of index servers including N index servers, each of which stores a portion of a phrase posting list for each of a plurality of phrases, each phrase posting list being associated with a phrase and a list of documents having at least one occurrence of the phrase; and M additional tiers of index servers, wherein: M is one to a predetermined number, each M th tier includes T index servers, where T is an integer multiple of N when M equals one and where T is an integer multiple of T for an (M−1) th tier when M is greater than or equal to two, and each M th tier index server stores a portion of a phrase posting list of each of a plurality of phrases, each phrase posting list being associated with a phrase and a list of documents having at least one occurrence of the phrase. 6. The system of claim 1 , wherein a given index server in the first tier communicates with at most the integer multiple of the N index servers in the M equals one tier during query processing. | 0.582251 |
8,458,592 | 14 | 17 | 14. A system for visual contextual search, the system comprising: a computer application having a graphical user interface (GUI) that is displayed to a user on a computer display; a visual map of the GUI that associates one or more topics with one or more GUI elements of the GUI; and a visual contextual search component comprising: a selection module configured to receive a selection area with user-defined boundaries encompassing a portion of the GUI of the computer application, wherein the selection area is drawn by a user of the GUI using a computer input device while the GUI is running; a topic module that determines, based on the visual map, a set of help topics that are related to the one or more GUI elements that are displayed within the selection area defined by the user; and a display module that displays for the user on the computer display a results section comprising one or more help topics in the set of help topics associated with the selection area defined by the user and a visual map of the GUI defining an association between the one or more help topics and the one or more GUI elements. | 14. A system for visual contextual search, the system comprising: a computer application having a graphical user interface (GUI) that is displayed to a user on a computer display; a visual map of the GUI that associates one or more topics with one or more GUI elements of the GUI; and a visual contextual search component comprising: a selection module configured to receive a selection area with user-defined boundaries encompassing a portion of the GUI of the computer application, wherein the selection area is drawn by a user of the GUI using a computer input device while the GUI is running; a topic module that determines, based on the visual map, a set of help topics that are related to the one or more GUI elements that are displayed within the selection area defined by the user; and a display module that displays for the user on the computer display a results section comprising one or more help topics in the set of help topics associated with the selection area defined by the user and a visual map of the GUI defining an association between the one or more help topics and the one or more GUI elements. 17. The system of claim 14 , wherein the visual contextual search component is a plug-in for the computer application having the GUI. | 0.838983 |
9,946,933 | 2 | 3 | 2. The method of claim 1 , wherein the second set of processing layers comprises a neural network. | 2. The method of claim 1 , wherein the second set of processing layers comprises a neural network. 3. The method of claim 2 , wherein at least one the second set of processing layers performs a linear vector projection and a non-linear vector transformation. | 0.931049 |
9,092,523 | 22 | 26 | 22. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback; and d) a first data store coupled to the content manager for storing supplemental information related to the search query, wherein the web page search results include the supplemental information, and multiple users are able to modify the same portions of the supplemental information, wherein after the second user modifies the supplemental information previously provided by a first user, any user, including the first user, is able to at least one of further modify the supplemental information or revert the modification of the second user. | 22. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback; and d) a first data store coupled to the content manager for storing supplemental information related to the search query, wherein the web page search results include the supplemental information, and multiple users are able to modify the same portions of the supplemental information, wherein after the second user modifies the supplemental information previously provided by a first user, any user, including the first user, is able to at least one of further modify the supplemental information or revert the modification of the second user. 26. The system of claim 22 , wherein the content manager is configured to receive the user input to add, edit, or delete a link to a description of a second concept, and the description of the second concept is part of the supplemental information. | 0.752495 |
9,812,130 | 1 | 3 | 1. A method performed on at least one processor for managing speech resources of a speech recognition engine, the method comprising the steps of: initiating a speech recognition engine with a first language model; converting audio received by the speech recognition engine to first interim text using the first language model, wherein the converting step includes correlating portions of the audio with corresponding portions of the first interim text; determining whether the first interim text matches at least one trigger; if it is determined that the first interim text does not match the at least one trigger, outputting the first interim text as recognized text; and if it is determined that the first interim text does match the at least one trigger: replacing the first language model with a second language model in the speech recognition engine, pausing the converting step until the first language model is replaced by the second language model, rewinding the audio based on the correlation between the portions of the audio and the corresponding portions of the first interim text, deleting a given portion of the first interim text that corresponds to a rewound portion of the audio, and resuming the converting step, wherein the rewound portion of the audio is re-input into the speech recognition engine and converted by the speech recognition engine to second interim text using only the second language model. | 1. A method performed on at least one processor for managing speech resources of a speech recognition engine, the method comprising the steps of: initiating a speech recognition engine with a first language model; converting audio received by the speech recognition engine to first interim text using the first language model, wherein the converting step includes correlating portions of the audio with corresponding portions of the first interim text; determining whether the first interim text matches at least one trigger; if it is determined that the first interim text does not match the at least one trigger, outputting the first interim text as recognized text; and if it is determined that the first interim text does match the at least one trigger: replacing the first language model with a second language model in the speech recognition engine, pausing the converting step until the first language model is replaced by the second language model, rewinding the audio based on the correlation between the portions of the audio and the corresponding portions of the first interim text, deleting a given portion of the first interim text that corresponds to a rewound portion of the audio, and resuming the converting step, wherein the rewound portion of the audio is re-input into the speech recognition engine and converted by the speech recognition engine to second interim text using only the second language model. 3. The method of claim 1 wherein correlating the portions of the audio with the corresponding portions of the first interim text includes creating a plurality of smaller audio files from the audio and converting the plurality of smaller audio files into a corresponding plurality of first interim text files, and wherein the outputted recognized text is concatenated from the plurality of first interim text files. | 0.609434 |
9,773,045 | 14 | 17 | 14. A system for providing search results, the system comprising: a memory; a processor; and a component that is stored in said memory, that executes on said processor, that receives a query from a user, that determines that said query is one to be asked to a person in addition to, or instead of, a search engine, that obtains objective results corresponding to the query from a corpus of information, that identifies one or more people in a social graph whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query, that creates person results that comprise a portion of said one or more people, that creates, for each of said one or more people, an explanation of each person's relevance to said query, and that provides, to said user, a set of results that comprise said objective results and said person results. | 14. A system for providing search results, the system comprising: a memory; a processor; and a component that is stored in said memory, that executes on said processor, that receives a query from a user, that determines that said query is one to be asked to a person in addition to, or instead of, a search engine, that obtains objective results corresponding to the query from a corpus of information, that identifies one or more people in a social graph whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query, that creates person results that comprise a portion of said one or more people, that creates, for each of said one or more people, an explanation of each person's relevance to said query, and that provides, to said user, a set of results that comprise said objective results and said person results. 17. The system of claim 14 , said aspect of relevance being based on a comparison of words in said query with a characteristic that is derived from declared affinities or text posts of a person in said social graph, said query being found to match said person based on words in said query matching said characteristic. | 0.791612 |
9,390,282 | 1 | 5 | 1. A method, for creating a document in a collaborative manner, comprising: providing a non-obfuscated original document (NOD) that is accessible to an outsourcing entity, the NOD having one or more sensitive items contained therein; obfuscating said one or more sensitive items in the NOD, to produce an obfuscated original document (OOD) containing obfuscated items; providing the OOD to a plurality of worker entities to make changes to the OOD, the changes producing a plurality of obfuscated transformed document (OTD) parts; receiving the OTD parts from the worker entities, the OTD parts containing the changes made by the worker entities to the OOD; and assembling the OTD parts into an obfuscated transformed document (OTD); de-obfuscating the OTD by restoring the obfuscated items to their corresponding sensitive items, to produce a content-restored transformed document (CTD); sending an instruction from the outsourcing entity to one of the plurality of worker entities via a communication mechanism; and receiving an updated OTD from the worker entity receiving the instruction from the outsourcing entity, the updated OTD containing at least one additional change made by the worker entity to the OOD, said providing the NOD, obfuscating, providing the OOD, receiving, assembling, sending, and de-obfuscating being performed by one or more computing devices. | 1. A method, for creating a document in a collaborative manner, comprising: providing a non-obfuscated original document (NOD) that is accessible to an outsourcing entity, the NOD having one or more sensitive items contained therein; obfuscating said one or more sensitive items in the NOD, to produce an obfuscated original document (OOD) containing obfuscated items; providing the OOD to a plurality of worker entities to make changes to the OOD, the changes producing a plurality of obfuscated transformed document (OTD) parts; receiving the OTD parts from the worker entities, the OTD parts containing the changes made by the worker entities to the OOD; and assembling the OTD parts into an obfuscated transformed document (OTD); de-obfuscating the OTD by restoring the obfuscated items to their corresponding sensitive items, to produce a content-restored transformed document (CTD); sending an instruction from the outsourcing entity to one of the plurality of worker entities via a communication mechanism; and receiving an updated OTD from the worker entity receiving the instruction from the outsourcing entity, the updated OTD containing at least one additional change made by the worker entity to the OOD, said providing the NOD, obfuscating, providing the OOD, receiving, assembling, sending, and de-obfuscating being performed by one or more computing devices. 5. The method of claim 1 , further comprising preventing at least one of the worker entities from modifying at least a portion of the OOD. | 0.72619 |
9,672,524 | 1 | 19 | 1. A system for organizing, managing, and reporting data relating to a corporate entity, comprising: at least one database configured to store a document record relating to a corporate action, the document record further comprising a core record reflecting human-readable information for incorporation into the generated document and stored with the document record, the document record further comprising a set of tags stored with the document record; a business logic module, coupled to the at least one database; and at least one document template stored in the at least one database and comprising instructions for generating, at the business logic module, a document based on the core record with an initial set of tags, wherein a first tag of the set of tags is in a text format and associates a human-readable document type with the document record, and wherein the at least one database is configured to store the document record with a hierarchically delimited child tag by storing the document record in association with both the hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags, thereby providing namespaced tagging and retrieval of document records. | 1. A system for organizing, managing, and reporting data relating to a corporate entity, comprising: at least one database configured to store a document record relating to a corporate action, the document record further comprising a core record reflecting human-readable information for incorporation into the generated document and stored with the document record, the document record further comprising a set of tags stored with the document record; a business logic module, coupled to the at least one database; and at least one document template stored in the at least one database and comprising instructions for generating, at the business logic module, a document based on the core record with an initial set of tags, wherein a first tag of the set of tags is in a text format and associates a human-readable document type with the document record, and wherein the at least one database is configured to store the document record with a hierarchically delimited child tag by storing the document record in association with both the hierarchically delimited child tag and additional tags that are hierarchically related as parent tags of the hierarchically delimited child tag, without requiring a user to request storage of both the child tag and the additional parent tags, thereby providing namespaced tagging and retrieval of document records. 19. The system of claim 1 , wherein the business logic module is configured to retrieve, for a given entity record, a prior-generated document storing a core record referenced by the given entity record and with an active status stored in a tag of the prior-generated document. | 0.667067 |
8,989,496 | 15 | 16 | 15. The medium of claim 13 , if executed, causes the computer to: generate time-series information comprising stroke data corresponding to the first strokes, the stroke data comprising a coordinate data series corresponding to points located on a locus of a stroke, a writing order of the first strokes recognizable in the stroke data; store the time-series information in a storage medium; and read out the time-series information from the storage medium and display loci corresponding to the first strokes on the display according to the readout time-series information. | 15. The medium of claim 13 , if executed, causes the computer to: generate time-series information comprising stroke data corresponding to the first strokes, the stroke data comprising a coordinate data series corresponding to points located on a locus of a stroke, a writing order of the first strokes recognizable in the stroke data; store the time-series information in a storage medium; and read out the time-series information from the storage medium and display loci corresponding to the first strokes on the display according to the readout time-series information. 16. The medium of claim 15 , if executed, causes the computer to: calculate a changing direction and a changing quantity to change the coordinate, by using a position of the first character recognizable from the strokes and the position of the second character recognizable from the strokes; and change a coordinate data series corresponding to the second character in the time-series information, in accordance with the changing direction and the changing quantity. | 0.803872 |
7,680,777 | 16 | 18 | 16. The method of claim 14 , wherein the section of the spatial arrangement is a selected region of the display, the copying or pasting is to a different region, and the query corresponding to the Original location is the query corresponding to the different region. | 16. The method of claim 14 , wherein the section of the spatial arrangement is a selected region of the display, the copying or pasting is to a different region, and the query corresponding to the Original location is the query corresponding to the different region. 18. The method of claim 16 , wherein pasting permits adjustment of the dimensions and orientation of the pasted region. | 0.956569 |
8,712,779 | 16 | 17 | 16. The information retrieval system according to claim 15 , further comprising: a text feature vector generation unit for computing a text feature vector from a speech recognition result generated by said speech recognition unit wherein said degree of similarity computation unit is further to compute degree of similarity between two or more text feature vectors computed by said text feature vector generation unit; wherein, after performing speech recognition of each of said input speech and a speech signal stored as speech information in said information storage unit by said speech recognition unit, text feature vectors of each thereof are computed by said text feature vector generation unit, degree of similarity between each of said text feature vectors is computed by said degree of similarity computation unit; and said information selection unit selects information with which speech information having a high degree of similarity to input speech is associated, based on degree of similarity computed by said degree of similarity computation unit. | 16. The information retrieval system according to claim 15 , further comprising: a text feature vector generation unit for computing a text feature vector from a speech recognition result generated by said speech recognition unit wherein said degree of similarity computation unit is further to compute degree of similarity between two or more text feature vectors computed by said text feature vector generation unit; wherein, after performing speech recognition of each of said input speech and a speech signal stored as speech information in said information storage unit by said speech recognition unit, text feature vectors of each thereof are computed by said text feature vector generation unit, degree of similarity between each of said text feature vectors is computed by said degree of similarity computation unit; and said information selection unit selects information with which speech information having a high degree of similarity to input speech is associated, based on degree of similarity computed by said degree of similarity computation unit. 17. The information retrieval system according to claim 16 , wherein said speech recognition unit divides said input speech into blocks of arbitrary size, and sequentially outputs a speech recognition result for each block; and for each speech recognition result output, said text feature vector generation unit generates a text feature vector for a speech recognition result of each of said blocks; and in addition, said degree of similarity computation unit re-computes degree of similarity of said speech information and speech recognition results of all blocks that have been outputted; and said information selection unit re-selects information with which speech information having a high degree of similarity to input speech is associated, based on degree of similarity that has been re-computed. | 0.786702 |
9,569,231 | 1 | 5 | 1. A method of providing interactive guidance to a user of a computerized application, the method comprising: receiving a user request to obtain interactive guidance with respect to said computerized application; based on the user request, selectively retrieving an interactive guidance script from a repository of previously-recorded interactive guidance scripts, wherein said interactive guidance script comprises instructions for performing one or more actions in said computerized application on behalf of the user, for displaying guidance text associated with at least one of said actions, and for enabling the user to enter data comprising a character string into one or more fields in the computerized application in response to at least some of said guidance text; and playing said interactive guidance script, to automatically execute said one or more actions in said computerized application on behalf of the user, to display said guidance text in association with at least one of said actions, and to enable the user to enter said data into said one or more fields in said computerized application, in response to at least some of said guidance text. | 1. A method of providing interactive guidance to a user of a computerized application, the method comprising: receiving a user request to obtain interactive guidance with respect to said computerized application; based on the user request, selectively retrieving an interactive guidance script from a repository of previously-recorded interactive guidance scripts, wherein said interactive guidance script comprises instructions for performing one or more actions in said computerized application on behalf of the user, for displaying guidance text associated with at least one of said actions, and for enabling the user to enter data comprising a character string into one or more fields in the computerized application in response to at least some of said guidance text; and playing said interactive guidance script, to automatically execute said one or more actions in said computerized application on behalf of the user, to display said guidance text in association with at least one of said actions, and to enable the user to enter said data into said one or more fields in said computerized application, in response to at least some of said guidance text. 5. The method of claim 1 , wherein playing said interactive guidance script comprises at least one of: calling from said interactive guidance script another interactive guidance script; checking whether or not a condition holds true in order to determine whether or not perform a script action; jumping from a first location of said interactive guidance script to a second location of said interactive guidance script; and validating data received from said user during the playing of said interactive guidance script. | 0.724175 |
9,195,222 | 1 | 5 | 1. A method of evaluating stability of software code for a control system, the method comprising: receiving a set of initial trajectories; determining, by a semidefinite programming solver module, one or more candidate Lyapunov functions based on the set of initial trajectories; performing a plurality of simulations using a model of the control system to create a set of discovered trajectories; and evaluating the set of discovered trajectories to determine one or more counterexample trajectories that violate one or more Lyapunov conditions, wherein if one or more counterexample trajectories are discovered: inputting the set of discovered trajectories including the one or more counterexample trajectories into the semidefinite programming solver module; and determining, by the semidefinite programming solver module, one or more additional candidate Lyapunov functions based on the set of initial trajectories and the set of discovered trajectories. | 1. A method of evaluating stability of software code for a control system, the method comprising: receiving a set of initial trajectories; determining, by a semidefinite programming solver module, one or more candidate Lyapunov functions based on the set of initial trajectories; performing a plurality of simulations using a model of the control system to create a set of discovered trajectories; and evaluating the set of discovered trajectories to determine one or more counterexample trajectories that violate one or more Lyapunov conditions, wherein if one or more counterexample trajectories are discovered: inputting the set of discovered trajectories including the one or more counterexample trajectories into the semidefinite programming solver module; and determining, by the semidefinite programming solver module, one or more additional candidate Lyapunov functions based on the set of initial trajectories and the set of discovered trajectories. 5. The method of claim 1 , further comprising, if no counterexample trajectories are discovered, performing a convex optimization on the set of initial trajectories and the set of discovered trajectories to determine an invariant set of trajectories. | 0.779152 |
8,676,793 | 1 | 7 | 1. A system for building a custom word list for use in text operations on an electronic device comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising: determining a source associated with a text item, identifying words in the text item composed by and associated with a user, and assigning a weighting to each identified word based in part on the source of the text item, wherein the source is determined based on an identity of the user associated with at least one portion of the text item. | 1. A system for building a custom word list for use in text operations on an electronic device comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising: determining a source associated with a text item, identifying words in the text item composed by and associated with a user, and assigning a weighting to each identified word based in part on the source of the text item, wherein the source is determined based on an identity of the user associated with at least one portion of the text item. 7. The system of claim 1 , wherein the instructions further cause the processor to perform the operation of receiving a selection input to select text items to be included in the text item. | 0.77972 |
9,430,051 | 14 | 20 | 14. A system comprising: a display device; a sensor configured to detect user contact; an input device coupled to the sensor; and a processing unit operatively associated with the sensor, the input device, and the display device, the processing unit being configured to: receive a plurality of text units input into a computing device; determine a character variant that is phonetically similar to at least one of the plurality of text units; associate a first portion of a touch-sensitive display with the character variant, wherein the touch-sensitive display is in communicative contact with the computing device; receive a first selection corresponding to the character variant; replace at least one of the plurality of text units with the character variant; receive, by the touch-sensitive display at a second portion of the touch-sensitive display, a second selection of the character variant; based at least upon receiving the second selection corresponding to the character variant, display at least one alternative character; receive a third selection to select one of the alternative characters; and replace the character variant with the selected alternative character. | 14. A system comprising: a display device; a sensor configured to detect user contact; an input device coupled to the sensor; and a processing unit operatively associated with the sensor, the input device, and the display device, the processing unit being configured to: receive a plurality of text units input into a computing device; determine a character variant that is phonetically similar to at least one of the plurality of text units; associate a first portion of a touch-sensitive display with the character variant, wherein the touch-sensitive display is in communicative contact with the computing device; receive a first selection corresponding to the character variant; replace at least one of the plurality of text units with the character variant; receive, by the touch-sensitive display at a second portion of the touch-sensitive display, a second selection of the character variant; based at least upon receiving the second selection corresponding to the character variant, display at least one alternative character; receive a third selection to select one of the alternative characters; and replace the character variant with the selected alternative character. 20. The system of claim 14 , wherein the processing unit is further configured to: receive confirmation that the text unit has been replaced; and return a cursor back to a prior position immediately before entering a text unit replacement mode. | 0.718245 |
9,135,653 | 176 | 183 | 176. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a nonmobile Web browser identifier to a mobile Web browser identifier; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; and updating a first value associated with the first edge to a second value based on a time elapsed from at least one of the first activity information or second activity information. | 176. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a nonmobile Web browser identifier to a mobile Web browser identifier; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; and updating a first value associated with the first edge to a second value based on a time elapsed from at least one of the first activity information or second activity information. 183. The method of claim 176 wherein the collection resource at a Web site used to collect first activity information comprises a URL shortening. | 0.905229 |
9,043,314 | 1 | 7 | 1. A method for customizing search engine queries for a plurality of users of a search engine, comprising: receiving first user input, from a first user of the plurality of users, comprising one or more web sites, said user input further providing data for grouping one or more web sites into one or more web search query results known only to the first user; storing the one or more web sites and raising an assigned rating of the one or more websites stored in a data store based on the one or more websites being received in the first user input; associating each of the one or more websites stored in a data store with each of the one or more web search query results, and raising a second assigned rating for each of the one or more websites upon association with each of the one or more web search query results based on the one or more websites and the one or more web search query results of the first user input; receiving from a second user of the plurality of users, a generated search string, comprising a search query having one or more keywords; determining that said search string comprising a search of or within a web search category of the one or more web search query results by accessing the search history of the plurality of users stored in the data store and determining one or more web search query results that have been previously searched by the first user when searching the same one or more keywords in said search string; updating the rating assigned to the one or more web sites based upon the second user generated search string; conducting a user-initiated search on the at least one selected web site associated with the one or more web search query results by passing the user generated search string to at least one search engine; returning results of the search engine query, the results modified based on the matching of one of more web search query results of the first user input, and returning search results where at least one website in the one or more web search query results is ranked higher based on the matching. | 1. A method for customizing search engine queries for a plurality of users of a search engine, comprising: receiving first user input, from a first user of the plurality of users, comprising one or more web sites, said user input further providing data for grouping one or more web sites into one or more web search query results known only to the first user; storing the one or more web sites and raising an assigned rating of the one or more websites stored in a data store based on the one or more websites being received in the first user input; associating each of the one or more websites stored in a data store with each of the one or more web search query results, and raising a second assigned rating for each of the one or more websites upon association with each of the one or more web search query results based on the one or more websites and the one or more web search query results of the first user input; receiving from a second user of the plurality of users, a generated search string, comprising a search query having one or more keywords; determining that said search string comprising a search of or within a web search category of the one or more web search query results by accessing the search history of the plurality of users stored in the data store and determining one or more web search query results that have been previously searched by the first user when searching the same one or more keywords in said search string; updating the rating assigned to the one or more web sites based upon the second user generated search string; conducting a user-initiated search on the at least one selected web site associated with the one or more web search query results by passing the user generated search string to at least one search engine; returning results of the search engine query, the results modified based on the matching of one of more web search query results of the first user input, and returning search results where at least one website in the one or more web search query results is ranked higher based on the matching. 7. The method of claim 1 , wherein conducting the user-initiated search further comprises: generating for each of the one or more search engines a query string based on the one or more search terms and the selected at least one web site, wherein format of the query string complies with syntax of the corresponding search engine; submitting each of the one or more query strings to the corresponding search engine for a web search; and obtaining and displaying search results from the one or more search engines. | 0.500975 |
8,827,708 | 10 | 15 | 10. A computer system, comprising: a first computer simulator configured to run a first simulation of a system based on a model of said system, said model having a plurality of state variables; a first user interface for receiving input data representative of user interaction with said first computer simulation to change values of one or more of said state variables in a manner consistent with an interaction with the simulated system; a first data output device delivering output from said first computer simulator; a second computer simulator configured to run, contemporaneously with said first computer simulation, a second computer simulation of said system based on the same model as said first simulation, said second simulation being accelerated relative to said first simulation so as to be running at further progression than said first simulation at a current time under the assumption of no further user interaction than those represented by the input data received from the first user input interface, said second computer simulation being used to generate information representing expected future events in said first simulation; a second user input interface for outputting said information representing expected future events, and for receiving input data while said first simulation is run and said information representing expected future events is outputted, said input data received by the second user input interface being used to adjust the extent to which a condition is present in said first simulation; a second data output device delivering as output from said second computer simulator the information representing expected future events in said first simulation; and a module configured to, while said first simulation is running, translate said input from said second user input interface to values for one or more state variables in said first computer simulation consistent with a description of said condition in terms of rules embodied in the model. | 10. A computer system, comprising: a first computer simulator configured to run a first simulation of a system based on a model of said system, said model having a plurality of state variables; a first user interface for receiving input data representative of user interaction with said first computer simulation to change values of one or more of said state variables in a manner consistent with an interaction with the simulated system; a first data output device delivering output from said first computer simulator; a second computer simulator configured to run, contemporaneously with said first computer simulation, a second computer simulation of said system based on the same model as said first simulation, said second simulation being accelerated relative to said first simulation so as to be running at further progression than said first simulation at a current time under the assumption of no further user interaction than those represented by the input data received from the first user input interface, said second computer simulation being used to generate information representing expected future events in said first simulation; a second user input interface for outputting said information representing expected future events, and for receiving input data while said first simulation is run and said information representing expected future events is outputted, said input data received by the second user input interface being used to adjust the extent to which a condition is present in said first simulation; a second data output device delivering as output from said second computer simulator the information representing expected future events in said first simulation; and a module configured to, while said first simulation is running, translate said input from said second user input interface to values for one or more state variables in said first computer simulation consistent with a description of said condition in terms of rules embodied in the model. 15. The computer system of claim 10 , wherein said module is further configured to translate the values of one or more state variables in said first computer simulation to a representation of the extent to which a condition is present in said simulation. | 0.501961 |
8,484,028 | 1 | 2 | 1. A system for document navigation, comprising: a display; a display module displaying a text document on the display; a text-to-speech (“TTS”) engine converting a text of the text document into at least one audible sound; an audio module presenting the at least one audible sound; and a document navigation application displaying a section of the text document corresponding to the audible sound and navigating a displayed cursor indicating the text corresponding to the at least one audible sound as the at least one audible sound is played, wherein upon displaying the section of the document containing a link which points to a region of interest, the document navigation application pans to the region of interest pointed to by the link, when the link is referenced by the audible sound. | 1. A system for document navigation, comprising: a display; a display module displaying a text document on the display; a text-to-speech (“TTS”) engine converting a text of the text document into at least one audible sound; an audio module presenting the at least one audible sound; and a document navigation application displaying a section of the text document corresponding to the audible sound and navigating a displayed cursor indicating the text corresponding to the at least one audible sound as the at least one audible sound is played, wherein upon displaying the section of the document containing a link which points to a region of interest, the document navigation application pans to the region of interest pointed to by the link, when the link is referenced by the audible sound. 2. The system of claim 1 , further comprising a linking module creating at least one link from at least one section of the text in the document to the region of interest. | 0.587379 |
9,245,523 | 1 | 7 | 1. A method for expansion of search queries on large vocabulary continuous speech recognition transcripts comprising: obtaining a textual transcript of audio interaction generated by the large vocabulary continuous speech recognition; generating a topic model from the textual transcripts; said topic model comprises a plurality of topics wherein each topic of the plurality of topics comprises a list of keywords; obtaining a search term; associating a topic from the topic model with the search term; and generating a list of candidate term expansion words by selecting keywords from the list of keywords of the associated topic; said candidate term expansion words are of high probability to be substitution errors of the search term that are generated by the large vocabulary continuous speech recognition. | 1. A method for expansion of search queries on large vocabulary continuous speech recognition transcripts comprising: obtaining a textual transcript of audio interaction generated by the large vocabulary continuous speech recognition; generating a topic model from the textual transcripts; said topic model comprises a plurality of topics wherein each topic of the plurality of topics comprises a list of keywords; obtaining a search term; associating a topic from the topic model with the search term; and generating a list of candidate term expansion words by selecting keywords from the list of keywords of the associated topic; said candidate term expansion words are of high probability to be substitution errors of the search term that are generated by the large vocabulary continuous speech recognition. 7. The method according to claim 1 wherein associating a topic from the topic model with the search term is performed by detecting keywords on the lists of keywords that are similar to the search term. | 0.525943 |
9,639,528 | 11 | 12 | 11. A system comprising: a computer device comprising a processor, graphical interface, and a system memory in communication with the processor via a communication medium, the system memory configured to store programmed computer code, which when executed by the processor, causes the processor to perform operations for accommodating a plurality of translations of a source text string into a limited available display area of a visual element in the graphical interface, the operations comprising: receiving an input source text string in the display area of the visual element; receiving input specifying a source language for the source text string; receiving input selecting two or more target languages for the source text string to be translated into; obtaining translations of the source text string in each of the selected two or more target languages; displaying, in response to the input source text string, a set of translation vectors, each translation vector comprising one possible translation of the source text string for each of the selected two or more target languages; receiving a selection of a translation vector that contains a translation of the source text string corresponding to an intended meaning of the source text string; and calculating a minimum display area necessary for the visual element to display a longest translation of the translations contained in the selected translation vector, wherein the display area of the visual element in the graphical interface is adjusted to encompass the minimum display area such that the longest translation fits within the display area of the visual element. | 11. A system comprising: a computer device comprising a processor, graphical interface, and a system memory in communication with the processor via a communication medium, the system memory configured to store programmed computer code, which when executed by the processor, causes the processor to perform operations for accommodating a plurality of translations of a source text string into a limited available display area of a visual element in the graphical interface, the operations comprising: receiving an input source text string in the display area of the visual element; receiving input specifying a source language for the source text string; receiving input selecting two or more target languages for the source text string to be translated into; obtaining translations of the source text string in each of the selected two or more target languages; displaying, in response to the input source text string, a set of translation vectors, each translation vector comprising one possible translation of the source text string for each of the selected two or more target languages; receiving a selection of a translation vector that contains a translation of the source text string corresponding to an intended meaning of the source text string; and calculating a minimum display area necessary for the visual element to display a longest translation of the translations contained in the selected translation vector, wherein the display area of the visual element in the graphical interface is adjusted to encompass the minimum display area such that the longest translation fits within the display area of the visual element. 12. The system of claim 11 wherein the minimum display area corresponds to a minimum length of the longest translation corresponding to a length selected from the group consisting of number of characters, number of pixels, and number of EM units required to display the longest translation in the visual element. | 0.761468 |
8,776,009 | 8 | 11 | 8. A system for task modeling interactive sequential applications for one or more mobile devices, comprising: a) a central processing unit (CPU) having a software tool for defining a generic meta-model of the target applications, wherein said generic meta-model consists of a static model of application components, and a dynamic model of identifiers of application screens and connections that are based on an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models; b) a passive Task Model database, being in data communication with said CPU, for storing said generic meta-model for future reuse, which further comprises static instances of the generic meta-model specifically generated for a variety of mobile devices; c) a tracker module in said processing unit for: c1) real-time tracking and monitoring user's actions during user-system interactions and creating a screen unique identifier for each application's screen visited by the user of said mobile device by choosing an identifier that matches a signature of each application's screen, wherein created identifiers are used for generating active models of the user's actual usage; and c2) generating a unique identifier for each captured screen that is presented to said user; d) an active Task Model database, being in data communication with said processing unit, for storing said active model, wherein data transferring and storing is minimized to screen unique identifier and; e) an analyzer for comparing said active Task Model to said passive Task Model and for generating usage patterns for said user. | 8. A system for task modeling interactive sequential applications for one or more mobile devices, comprising: a) a central processing unit (CPU) having a software tool for defining a generic meta-model of the target applications, wherein said generic meta-model consists of a static model of application components, and a dynamic model of identifiers of application screens and connections that are based on an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models; b) a passive Task Model database, being in data communication with said CPU, for storing said generic meta-model for future reuse, which further comprises static instances of the generic meta-model specifically generated for a variety of mobile devices; c) a tracker module in said processing unit for: c1) real-time tracking and monitoring user's actions during user-system interactions and creating a screen unique identifier for each application's screen visited by the user of said mobile device by choosing an identifier that matches a signature of each application's screen, wherein created identifiers are used for generating active models of the user's actual usage; and c2) generating a unique identifier for each captured screen that is presented to said user; d) an active Task Model database, being in data communication with said processing unit, for storing said active model, wherein data transferring and storing is minimized to screen unique identifier and; e) an analyzer for comparing said active Task Model to said passive Task Model and for generating usage patterns for said user. 11. The system according to claim 8 , wherein the mobile device further comprises a real-time recommender engine, for offering the client real-time help, marketing and content determined by the provider. | 0.777412 |
10,037,319 | 2 | 6 | 2. The system of claim 1 , wherein the memory stores instructions that, when executed by the processor, configure the processor to generate a subset of the one or more candidates based on the probability assigned to each candidate. | 2. The system of claim 1 , wherein the memory stores instructions that, when executed by the processor, configure the processor to generate a subset of the one or more candidates based on the probability assigned to each candidate. 6. The system of claim 2 , wherein input sequence is generated from user input signals by generating a sequence of sets of characters, each set of characters having a probability distribution over the characters in the set, such that there is a probability value associated with each character in each set. | 0.875306 |
9,805,030 | 1 | 2 | 1. A computer implemented language interpretation platform, for providing a language interpretation session between a user and a human staff language interpreter, comprising: a processor that determines available languages for which language interpretation resources are currently available based on at least one user criterion and language interpreter availability, wherein the processor also determines available modalities for the available languages, wherein the available modalities are selected from the group consisting of: voice, text, and video; and a routing engine that receives, via an Application Programming Interface, a request, from a computing device being used by the user, for the available languages and sends the available languages and the available modalities to the computing device such that the computing device displays the available languages and, after receiving a user selection of one of the available languages, displays the available modalities for the user selected language and receives a user selection of one of the available modalities for establishing a language interpretation session with a language interpreter for the user selected language, wherein the request includes the at least one user criterion, the routing engine further sending a real-time update of the available modalities to the computing device prior to a user selection of one of the available modalities such that the computing device changes the available modalities that are displayed based on the real-time update, the real-time update being based on a change in the modality availability. | 1. A computer implemented language interpretation platform, for providing a language interpretation session between a user and a human staff language interpreter, comprising: a processor that determines available languages for which language interpretation resources are currently available based on at least one user criterion and language interpreter availability, wherein the processor also determines available modalities for the available languages, wherein the available modalities are selected from the group consisting of: voice, text, and video; and a routing engine that receives, via an Application Programming Interface, a request, from a computing device being used by the user, for the available languages and sends the available languages and the available modalities to the computing device such that the computing device displays the available languages and, after receiving a user selection of one of the available languages, displays the available modalities for the user selected language and receives a user selection of one of the available modalities for establishing a language interpretation session with a language interpreter for the user selected language, wherein the request includes the at least one user criterion, the routing engine further sending a real-time update of the available modalities to the computing device prior to a user selection of one of the available modalities such that the computing device changes the available modalities that are displayed based on the real-time update, the real-time update being based on a change in the modality availability. 2. The computer implemented language interpretation platform of claim 1 , wherein the routing engine sends a real-time update of the available modalities to the computing device after the user selection of the user selected language. | 0.725882 |
9,170,826 | 1 | 4 | 1. A computer implemented method comprising: obtaining a first textual expression contained within an application, wherein the first textual expression is expressed in a first language; generating a unique key from a hash of the first textual expression, the unique key being generated based on a location of where the first textual expression is used within the application and a type of object of the application using the first textual expression; determining a language code representative of a second language, the language code being associated with the unique key; determining, based on the generated unique key and the determined language code, a second textual expression in the second language representative of a translation from the first language into the second language indicated by the language code; and providing, based on the location and the type of object, the second textual expression to the application to replace the first textual expression in a view presented to a user. | 1. A computer implemented method comprising: obtaining a first textual expression contained within an application, wherein the first textual expression is expressed in a first language; generating a unique key from a hash of the first textual expression, the unique key being generated based on a location of where the first textual expression is used within the application and a type of object of the application using the first textual expression; determining a language code representative of a second language, the language code being associated with the unique key; determining, based on the generated unique key and the determined language code, a second textual expression in the second language representative of a translation from the first language into the second language indicated by the language code; and providing, based on the location and the type of object, the second textual expression to the application to replace the first textual expression in a view presented to a user. 4. The method according to claim 1 , wherein the determining the second textual expression further comprises: accessing a table including the generated unique key and the determined language code mapped to the second language expression. | 0.74183 |
8,447,111 | 1 | 6 | 1. A method comprising: receiving, at a server device, a sequence of characters optically or acoustically captured from a rendered document by a capture device remote from the server device; identifying, using the server device, a document that includes a sequence of characters that matches the captured sequence of characters; identifying, using the server device, a position, within the identified document, of the sequence of characters that matches the captured sequence of characters; and identifying, using the server device, a word, phrase or symbol that is within the sequence of characters at the identified position within the identified document and that is associated with an action. | 1. A method comprising: receiving, at a server device, a sequence of characters optically or acoustically captured from a rendered document by a capture device remote from the server device; identifying, using the server device, a document that includes a sequence of characters that matches the captured sequence of characters; identifying, using the server device, a position, within the identified document, of the sequence of characters that matches the captured sequence of characters; and identifying, using the server device, a word, phrase or symbol that is within the sequence of characters at the identified position within the identified document and that is associated with an action. 6. The method of claim 1 , further comprising: using the server device to perform the action associated with the identified word, phrase or symbol, wherein performing the action associated with the identified word, phrase or symbol comprises the server device retrieving, from a web site of the World Wide Web, a web page associated with the identified word, phrase or symbol. | 0.739972 |
8,812,518 | 1 | 8 | 1. A computer-implemented method comprising: obtaining first search results that were generated for a search query; determining, by operation of a system, a first search results score associated with the first search results, wherein the first search results score is based on (i) a respective rank of each first search result, and (ii) a respective first popularity score associated with each first search result; revising the search query using a query revision rule; obtaining second search results that were generated for the revised search query; determining a second search results score associated with the second search results, wherein the second search results score is based on (i) a respective rank of each second search result, and (ii) a respective second popularity score associated with each second search result; determining that a difference between the first search results score and the second search results score satisfies a specified threshold; and in response to determining that a difference between the first search results score and the second search results score satisfies the specified threshold, identifying the query revision rule as a good revision rule for the search query. | 1. A computer-implemented method comprising: obtaining first search results that were generated for a search query; determining, by operation of a system, a first search results score associated with the first search results, wherein the first search results score is based on (i) a respective rank of each first search result, and (ii) a respective first popularity score associated with each first search result; revising the search query using a query revision rule; obtaining second search results that were generated for the revised search query; determining a second search results score associated with the second search results, wherein the second search results score is based on (i) a respective rank of each second search result, and (ii) a respective second popularity score associated with each second search result; determining that a difference between the first search results score and the second search results score satisfies a specified threshold; and in response to determining that a difference between the first search results score and the second search results score satisfies the specified threshold, identifying the query revision rule as a good revision rule for the search query. 8. The method of claim 1 , further comprising: storing the query revision rule for use in revising the search query. | 0.935627 |
7,979,267 | 1 | 5 | 1. A method for specifying a subset of data, comprising: receiving a first input at a user interface of a computing device for a first field of a natural language expression, the first input indicates a first data value for the first field; accessing options for a second field of the natural language expression that are determined based on the first data value and data stored in data group; displaying the second field and the options for the second field; receiving a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field; accessing options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group; displaying the third field and the options for the third field; receiving a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language; and accessing and reporting a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language. | 1. A method for specifying a subset of data, comprising: receiving a first input at a user interface of a computing device for a first field of a natural language expression, the first input indicates a first data value for the first field; accessing options for a second field of the natural language expression that are determined based on the first data value and data stored in data group; displaying the second field and the options for the second field; receiving a second input at the user interface for the second field of the natural language expression, the second input indicates a second data value for the second field from the options for the second field; accessing options for a third field of the natural language expression that are determined based on the second data value and data stored in the data group; displaying the third field and the options for the third field; receiving a third input at the user interface for the third field of the natural language expression, the third input indicates a third data value for the third field, the second data value indicates a relationship between the first data value and the third data value that exists in the data group, a result of receiving the third input is an updated version of the natural language expression that includes the first data value, the second data value and the third data value as natural language; and accessing and reporting a subset of the data group that corresponds to the natural language expression that includes the first data value, the second data value and the third data value as natural language. 5. The method of claim 1 , wherein: the reporting the subset of the data group includes displaying the subset of the data group on a display device associated with the computing device. | 0.912488 |
7,899,812 | 9 | 10 | 9. The system according to claim 1 , further comprising a fourth display part in the user interface for forming a term filter comprising one or more term instances and filtering criteria, the term filter uses the one or more term instances and filtering criteria to compose a new query, in order to search a new document list. | 9. The system according to claim 1 , further comprising a fourth display part in the user interface for forming a term filter comprising one or more term instances and filtering criteria, the term filter uses the one or more term instances and filtering criteria to compose a new query, in order to search a new document list. 10. The system according to claim 9 , wherein the filtering criteria comprise at least one of an AND relation of the term instances and an OR relation of the term instances; at least one term instance is input to the system in advance or is dynamically extracted from a previous document list. | 0.904186 |
8,751,231 | 3 | 8 | 3. The method of claim 1 , wherein the identifying the utterances comprises: computing a first moving average using a first moving window of a first number of audio samples of the audio data; computing a second moving average using a second moving window of a second number of the audio samples with gradients to detect peak transitions of the audio samples, wherein the second number is greater than the first number; computing a voice activity indicator of the audio samples; segmenting the audio samples into the utterances using the first moving average, the second moving average and the voice activity indicator, wherein each of the utterances comprise an utterance length; and assigning an utterance identifier to each of the utterances. | 3. The method of claim 1 , wherein the identifying the utterances comprises: computing a first moving average using a first moving window of a first number of audio samples of the audio data; computing a second moving average using a second moving window of a second number of the audio samples with gradients to detect peak transitions of the audio samples, wherein the second number is greater than the first number; computing a voice activity indicator of the audio samples; segmenting the audio samples into the utterances using the first moving average, the second moving average and the voice activity indicator, wherein each of the utterances comprise an utterance length; and assigning an utterance identifier to each of the utterances. 8. The method of claim 3 , further comprising: performing a spectral analysis of each of the identified utterances to generate utterance time-series data; generating a spectral signature of each of the identified utterances based on the spectral analysis; and detecting repetition of utterances based on the spectral signatures. | 0.813848 |
10,031,910 | 3 | 4 | 3. The computing system of claim 1 , wherein the processor is further configured to: identify a grammatical attribute associated with the first term or with the second term, wherein the grammatical attribute comprises a grammatical role of a subject, an object, a head, a modifier, or parts of speech of a noun, a verb, a preposition, an adjective, or an adverb, wherein the derived sentiment or opinion type is determined based on the grammatical attribute. | 3. The computing system of claim 1 , wherein the processor is further configured to: identify a grammatical attribute associated with the first term or with the second term, wherein the grammatical attribute comprises a grammatical role of a subject, an object, a head, a modifier, or parts of speech of a noun, a verb, a preposition, an adjective, or an adverb, wherein the derived sentiment or opinion type is determined based on the grammatical attribute. 4. The computing system of claim 3 , where in the processor is further configured to: identify a first grammatical attribute associated with the first term, and a second grammatical attribute associated with the second term, wherein the derived sentiment or opinion type is determined based on the first grammatical attribute and the second grammatical attribute. | 0.943599 |
8,165,879 | 1 | 4 | 1. A voice output device, comprising: a compound word voice data storage unit that stores voice data respectively associated with a plurality of compound words each of which includes a plurality of words; a text display unit that displays text containing a plurality of words; a word designation unit that designates a word from among the plurality of words in the text displayed by the text display unit as a designated word based on a user's operation; a headword addition unit that retrieves a designated headword coinciding with the designated word, and adds the designated headword to a candidate list; a compound word addition unit that retrieves, from the compound word voice data storage unit, a compound word which includes the designated word and a word consecutive to the designated word in a given direction, and adds the compound word to the candidate list when the compound word is retrieved; a candidate list display unit that displays the designated headword added to the candidate list by the headword addition unit and the compound word added to the candidate list by the compound word addition unit, in a list form; a candidate choice unit that chooses, based on the user's operation, between the designated headword and the compound word displayed by the candidate list display unit; and a voice output unit that outputs voice data associated with the designated headword or voice data associated with the compound word chosen by the candidate choice unit as a voice. | 1. A voice output device, comprising: a compound word voice data storage unit that stores voice data respectively associated with a plurality of compound words each of which includes a plurality of words; a text display unit that displays text containing a plurality of words; a word designation unit that designates a word from among the plurality of words in the text displayed by the text display unit as a designated word based on a user's operation; a headword addition unit that retrieves a designated headword coinciding with the designated word, and adds the designated headword to a candidate list; a compound word addition unit that retrieves, from the compound word voice data storage unit, a compound word which includes the designated word and a word consecutive to the designated word in a given direction, and adds the compound word to the candidate list when the compound word is retrieved; a candidate list display unit that displays the designated headword added to the candidate list by the headword addition unit and the compound word added to the candidate list by the compound word addition unit, in a list form; a candidate choice unit that chooses, based on the user's operation, between the designated headword and the compound word displayed by the candidate list display unit; and a voice output unit that outputs voice data associated with the designated headword or voice data associated with the compound word chosen by the candidate choice unit as a voice. 4. The voice output device according to claim 1 , further comprising a voice output speed control unit that controls a voice output speed of the voice output by the voice output unit. | 0.932721 |
9,342,496 | 17 | 20 | 17. A system for automatically completing a remainder portion of a name as it is being entered, comprising: processing circuitry configured to execute instructions stored on a memory: receive at least a prescribed number of starting characters of a name being entered into a first cell, wherein: the first cell is disposed in a document; the document includes a first sheet having a first sheet name and a second sheet having a second sheet name; the first sheet includes a first table having a first table name and the second sheet includes a second table having a second table name; the first table includes a first row or column having a first or column name and the second table includes a second row or column having a second row or column name; the first row or column name and the second row or column name are the same; and the starting characters of the name being entered into the first cell are part of a string of characters found in the first row or column name and the second row or column name; determine a set of valid reference names that include the starting characters of the name being entered into the first cell, wherein: a first valid reference name of the set of valid reference names comprises the first row or column name; a second valid reference name of the set of valid reference names comprises the second row or column name; and the first valid reference name comprises the first table name and the first sheet name, or the second valid reference name comprises the second table name and the second sheet name; and provide the set of valid reference names as selectable auto-completion options to enable selection between the first row or column name and the second row or column name; and the memory coupled to the processing circuitry and configured to provide instructions to the processing circuitry. | 17. A system for automatically completing a remainder portion of a name as it is being entered, comprising: processing circuitry configured to execute instructions stored on a memory: receive at least a prescribed number of starting characters of a name being entered into a first cell, wherein: the first cell is disposed in a document; the document includes a first sheet having a first sheet name and a second sheet having a second sheet name; the first sheet includes a first table having a first table name and the second sheet includes a second table having a second table name; the first table includes a first row or column having a first or column name and the second table includes a second row or column having a second row or column name; the first row or column name and the second row or column name are the same; and the starting characters of the name being entered into the first cell are part of a string of characters found in the first row or column name and the second row or column name; determine a set of valid reference names that include the starting characters of the name being entered into the first cell, wherein: a first valid reference name of the set of valid reference names comprises the first row or column name; a second valid reference name of the set of valid reference names comprises the second row or column name; and the first valid reference name comprises the first table name and the first sheet name, or the second valid reference name comprises the second table name and the second sheet name; and provide the set of valid reference names as selectable auto-completion options to enable selection between the first row or column name and the second row or column name; and the memory coupled to the processing circuitry and configured to provide instructions to the processing circuitry. 20. A system as recited in claim 17 , wherein each valid reference name of the set of valid reference names includes one or more of a row name, column name, table name, sheet name, and document name. | 0.880265 |
7,610,264 | 11 | 12 | 11. A system to accelerate execution of a query on a federated database system, the federated database system being associated with an external data source, the query utilizing the external data source and being performed based upon a query execution plan, the system comprising: a hardware mechanism that provides an optimizer query generator to generate at least one optimizer query for the external data source utilized by the query, the optimizer query used in generating a future query execution plan, the at least one optimizer query being based on the query and obtains data related to the external data source, the at least one optimizer query being provided to the external data source to be executed, wherein the optimizer query generator is included in a federated sewer of the federated database system, and wherein the external data source is independent with respect to the federated server; a query feedback warehouse to store statistics from execution of the at least one optimizer query, the statistics to be used in generating the future query execution plan; a monitor to collect the at least one resultant from execution of the at least one optimizer query, and wherein the optimizer query generator further parses the query to determine a portion of the query utilizing the external data source and generates the at least one optimizer query based on the portion of the query utilizing the external data source and the external data source utilizes at least one operator to execute the query and wherein the at least one optimizer query is used in determining the statistics for the at least one operator. | 11. A system to accelerate execution of a query on a federated database system, the federated database system being associated with an external data source, the query utilizing the external data source and being performed based upon a query execution plan, the system comprising: a hardware mechanism that provides an optimizer query generator to generate at least one optimizer query for the external data source utilized by the query, the optimizer query used in generating a future query execution plan, the at least one optimizer query being based on the query and obtains data related to the external data source, the at least one optimizer query being provided to the external data source to be executed, wherein the optimizer query generator is included in a federated sewer of the federated database system, and wherein the external data source is independent with respect to the federated server; a query feedback warehouse to store statistics from execution of the at least one optimizer query, the statistics to be used in generating the future query execution plan; a monitor to collect the at least one resultant from execution of the at least one optimizer query, and wherein the optimizer query generator further parses the query to determine a portion of the query utilizing the external data source and generates the at least one optimizer query based on the portion of the query utilizing the external data source and the external data source utilizes at least one operator to execute the query and wherein the at least one optimizer query is used in determining the statistics for the at least one operator. 12. The system of claim 11 further comprising: a query feedback analyzer to determine, based on the query execution plan and at least one previous optimizer query, whether the at least one resultant for the external data source should be collected using the at least one optimizer query. | 0.501736 |
9,659,578 | 19 | 21 | 19. A computer implemented method for identifying significant speech frames within speech signals for facilitating speech recognition, said method comprising: storing instructions and data in a memory; receiving, using a processor, said instructions and data from said memory; storing, a set of computing instructions related to spectral analysis into a first repository, a set of computing instructions related to feature vector extractions into a second repository, a set of computing instructions related to frame weighting and a set of computing instructions related to suitability measure; receiving, by an input module, at least an input speech signal, wherein the speech signal is represented by a plurality of feature vectors; dividing, using a divider of a spectrum analyzer, the input speech signal into a plurality of speech frames and computing at least a spectral magnitude of each of the speech frames; extracting, using an extractor, at least a feature vector from each of the speech frames; receiving at a suitability engine of said computer, the speech frames and the corresponding spectral magnitude of each of speech frames for the purpose of computing a suitability measure for each of the speech frames: computing, by a spectral flatness module of said suitability engine, a spectral flatness measure for each of the speech frames and determining, by said spectral flatness module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the spectral flatness measure computed; computing, by an energy normalized variance module of said suitability engine, an energy normalized variance for each of the speech frame and determining, by said energy normalized variance module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the energy normalized variance computed; computing, by an entropy module of said suitability engine, an entropy for each of the speech frame and determining, by said entropy module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the entropy computed; computing, by a signal-to-noise ratio module of said suitability engine, a signal-to-noise ratio for each of the speech frame and determining, by said signal-to-noise ratio module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the signal-to-noise ratio computed; computing, by a similarity module of said suitability engine, a similarity measure for each of the speech frame and determining, by said similarity module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to similarity measure computed; calculating, by a final suitability measure module of said suitability engine, a final suitability measure by considering the spectral flatness measure, the energy normalized variance, the entropy, the signal-to-noise ratio and the similarity measure along with the corresponding suitability measures computed for each of said speech frames; and computing and assigning, by a frame weight assigner of said computer, at least a weight for each of the speech frames to identify significant speech frames based on the spectral magnitude and the final suitability measure of respective speech frame. | 19. A computer implemented method for identifying significant speech frames within speech signals for facilitating speech recognition, said method comprising: storing instructions and data in a memory; receiving, using a processor, said instructions and data from said memory; storing, a set of computing instructions related to spectral analysis into a first repository, a set of computing instructions related to feature vector extractions into a second repository, a set of computing instructions related to frame weighting and a set of computing instructions related to suitability measure; receiving, by an input module, at least an input speech signal, wherein the speech signal is represented by a plurality of feature vectors; dividing, using a divider of a spectrum analyzer, the input speech signal into a plurality of speech frames and computing at least a spectral magnitude of each of the speech frames; extracting, using an extractor, at least a feature vector from each of the speech frames; receiving at a suitability engine of said computer, the speech frames and the corresponding spectral magnitude of each of speech frames for the purpose of computing a suitability measure for each of the speech frames: computing, by a spectral flatness module of said suitability engine, a spectral flatness measure for each of the speech frames and determining, by said spectral flatness module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the spectral flatness measure computed; computing, by an energy normalized variance module of said suitability engine, an energy normalized variance for each of the speech frame and determining, by said energy normalized variance module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the energy normalized variance computed; computing, by an entropy module of said suitability engine, an entropy for each of the speech frame and determining, by said entropy module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the entropy computed; computing, by a signal-to-noise ratio module of said suitability engine, a signal-to-noise ratio for each of the speech frame and determining, by said signal-to-noise ratio module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to the signal-to-noise ratio computed; computing, by a similarity module of said suitability engine, a similarity measure for each of the speech frame and determining, by said similarity module of said suitability engine, a corresponding suitability measure for each of the speech frames corresponding to similarity measure computed; calculating, by a final suitability measure module of said suitability engine, a final suitability measure by considering the spectral flatness measure, the energy normalized variance, the entropy, the signal-to-noise ratio and the similarity measure along with the corresponding suitability measures computed for each of said speech frames; and computing and assigning, by a frame weight assigner of said computer, at least a weight for each of the speech frames to identify significant speech frames based on the spectral magnitude and the final suitability measure of respective speech frame. 21. The method as claimed in claim 19 , wherein the step of computing the similarity measure for each of the speech frame further includes a step of accepting at least a pre-trained speech model and at least a pre-trained noise model for computing the similarity measure. | 0.807801 |
8,976,108 | 1 | 4 | 1. In a mobile computing device having a telephone functionality, a computer-implemented method comprising: receiving keyed input requesting a base symbol for insertion into textual content on a display of the computing device; receiving keyed input requesting one or more alternate symbols associated with the base symbol, wherein the one or more alternate symbols are accented versions of the base symbol; displaying, simultaneously on the display, the one or more alternate symbols and the base symbol; and responsive to a user selection of one of the displayed alternate symbols, replacing the base symbol with the selected alternate symbol in the textual content. | 1. In a mobile computing device having a telephone functionality, a computer-implemented method comprising: receiving keyed input requesting a base symbol for insertion into textual content on a display of the computing device; receiving keyed input requesting one or more alternate symbols associated with the base symbol, wherein the one or more alternate symbols are accented versions of the base symbol; displaying, simultaneously on the display, the one or more alternate symbols and the base symbol; and responsive to a user selection of one of the displayed alternate symbols, replacing the base symbol with the selected alternate symbol in the textual content. 4. The method of claim 1 , wherein the displaying comprises: displaying a menu in a portion of the display, the menu including the one or more alternate symbols. | 0.892667 |
8,959,123 | 1 | 7 | 1. A computer-implemented method for initializing an application's user interface components, the method comprising: connecting, by a computing device, an application view defined in semantic application logic to events generated when a user interacts with a visual display of the computing device, wherein connecting the application view to events generated when a user interacts with a visual display of the computing device includes: registering a listener on a document object model (DOM) object used by a Web browser to render the application view; and inserting a unique identifier in the DOM object to associate a graphical element with the runtime object; using, by the computing device, the semantic application logic to render graphical elements of at least one user interface component, wherein to render the graphical elements of the at least one user interface component includes: transforming the semantic application logic into a format for parsing and rendering; rendering, by a rendering component used by a client-side component executed by the computing device, graphical elements of the at least one user interface component; and presenting, by the visual display of the computing device, the rendered graphical elements of the at least one user interface component; instantiating, by the client-side component executed by the computing device, a runtime object that provides computational logic of the user interface component, wherein the semantic application logic used to visually render the at least one user interface component is defined independently from the computational logic of the runtime object and can be modified to change the visual rendering of the at least one user interface component without affecting functions of the runtime object; and initializing, by the computing device, the computational logic of the runtime object on the visual rendering of the at least one user interface component. | 1. A computer-implemented method for initializing an application's user interface components, the method comprising: connecting, by a computing device, an application view defined in semantic application logic to events generated when a user interacts with a visual display of the computing device, wherein connecting the application view to events generated when a user interacts with a visual display of the computing device includes: registering a listener on a document object model (DOM) object used by a Web browser to render the application view; and inserting a unique identifier in the DOM object to associate a graphical element with the runtime object; using, by the computing device, the semantic application logic to render graphical elements of at least one user interface component, wherein to render the graphical elements of the at least one user interface component includes: transforming the semantic application logic into a format for parsing and rendering; rendering, by a rendering component used by a client-side component executed by the computing device, graphical elements of the at least one user interface component; and presenting, by the visual display of the computing device, the rendered graphical elements of the at least one user interface component; instantiating, by the client-side component executed by the computing device, a runtime object that provides computational logic of the user interface component, wherein the semantic application logic used to visually render the at least one user interface component is defined independently from the computational logic of the runtime object and can be modified to change the visual rendering of the at least one user interface component without affecting functions of the runtime object; and initializing, by the computing device, the computational logic of the runtime object on the visual rendering of the at least one user interface component. 7. The method as recited in claim 1 , wherein initializing the computational logic of the runtime object includes setting default states of the user interface component utilizing a method defined in accordance with component APIs without having an application provide any source or script code. | 0.501695 |
8,423,583 | 12 | 22 | 12. A user-interface method of selecting and presenting a collection of content items, the method comprising: providing access to a set of content items; determining an organizational or social relationship of the user to at least one other person; determining content items of the set consumed by the at least one other person; associating a relevance weight with at least one of the content items of the set, wherein the associated relevance weight is based in part on the organizational or social relationship of the user to the other person and whether the at least one content item of the set was consumed by the other person; subsequent to associating the relevance weight with the at least one of the content items of the set, selecting and presenting a subset of content items to the user as a hierarchy of content items browsable by the user, wherein the content items are ordered at least in part by the initial associated relevance weights of the content items. | 12. A user-interface method of selecting and presenting a collection of content items, the method comprising: providing access to a set of content items; determining an organizational or social relationship of the user to at least one other person; determining content items of the set consumed by the at least one other person; associating a relevance weight with at least one of the content items of the set, wherein the associated relevance weight is based in part on the organizational or social relationship of the user to the other person and whether the at least one content item of the set was consumed by the other person; subsequent to associating the relevance weight with the at least one of the content items of the set, selecting and presenting a subset of content items to the user as a hierarchy of content items browsable by the user, wherein the content items are ordered at least in part by the initial associated relevance weights of the content items. 22. The method of claim 12 , wherein the organizational relationship is a hierarchy containing superiors, peers, and subordinates. | 0.841849 |
8,244,720 | 21 | 22 | 21. A method performed by one or more server devices, the method comprising: identifying, by at least one of the one or more server devices, a blog document that is responsive to a search query; generating, by at least one of the one or more server devices, a first score for the blog document based on a relevance of the blog document to the search query; generating, by at least one of the one or more server devices, a second score for the blog document based on a quality of the blog document independent of the search query, where the second score is based on: a first indication of whether ads appear in a blogroll associated with the blog document or blog metadata associated with the blog document, and a second indication of whether ads appear in blog posts in the blog document; generating, by at least one of the one or more server devices, a third score based on the first and second scores; and providing, by at least one of the one or more server devices, information relating to the blog document based on the third score. | 21. A method performed by one or more server devices, the method comprising: identifying, by at least one of the one or more server devices, a blog document that is responsive to a search query; generating, by at least one of the one or more server devices, a first score for the blog document based on a relevance of the blog document to the search query; generating, by at least one of the one or more server devices, a second score for the blog document based on a quality of the blog document independent of the search query, where the second score is based on: a first indication of whether ads appear in a blogroll associated with the blog document or blog metadata associated with the blog document, and a second indication of whether ads appear in blog posts in the blog document; generating, by at least one of the one or more server devices, a third score based on the first and second scores; and providing, by at least one of the one or more server devices, information relating to the blog document based on the third score. 22. The method of claim 21 , where generating the third score includes: increasing or decreasing the first score based on the second score. | 0.877856 |
10,049,097 | 1 | 9 | 1. A method for creating a multi-layered Optical Character Recognition (OCR) document, the method comprising: receiving a scanned image corresponding to a document, the document includes text information; generating a binary image from the scanned image; performing a morphological dilation operation to create one or more text groups, using a horizontal structuring element and a vertical structuring element; applying OCR on each text group to generate a corresponding OCR layer; combining the one or more OCR layers while creating a multi-layered OCR document; and superimposing the combined OCR layers as invisible text layers over the scanned image to create the multi-layered OCR document, the multi-layered OCR document facilitates selection of a text group corresponding to the OCR layer. | 1. A method for creating a multi-layered Optical Character Recognition (OCR) document, the method comprising: receiving a scanned image corresponding to a document, the document includes text information; generating a binary image from the scanned image; performing a morphological dilation operation to create one or more text groups, using a horizontal structuring element and a vertical structuring element; applying OCR on each text group to generate a corresponding OCR layer; combining the one or more OCR layers while creating a multi-layered OCR document; and superimposing the combined OCR layers as invisible text layers over the scanned image to create the multi-layered OCR document, the multi-layered OCR document facilitates selection of a text group corresponding to the OCR layer. 9. The method as claimed in claim 1 further comprising assigning a unique color to each OCR layer of the multi-layered OCR document. | 0.93038 |
9,812,121 | 2 | 3 | 2. The method according to claim 1 , wherein the voice database comprises storing voice data of the sender of the first text data and text data corresponding to the second voice data for each sentence, each word, and each syllable. | 2. The method according to claim 1 , wherein the voice database comprises storing voice data of the sender of the first text data and text data corresponding to the second voice data for each sentence, each word, and each syllable. 3. The method according to claim 2 , before the outputting the converted speech in the voice characteristics of the sender, further comprising: conducting a search to determine whether the sender's first voice data is present in the voice database; extracting, from the voice database, voice data of the sender corresponding to the first text data based on a search result of the conducting the search; and transmitting the voice data of the sender extracted, wherein the extracting voice data comprises: extracting, from the voice database, voice data of the sender that matches a sentence included in the first text data; extracting, from the voice database, voice data of the sender that matches a word included in the first text data; and extracting, from the voice database, voice data of the sender that matches a syllable included in the first text data. | 0.757191 |
8,244,539 | 10 | 11 | 10. A system, comprising: at least one processor; and a memory coupled to the at least one processor, wherein the memory stores program instructions, and wherein the program instructions are executable by the at least one processor to cause the system to: identify content requested by a client, wherein the requested content includes first audio data having a first set of one or more phonemes; and cause another content to be delivered to the client, wherein the another content includes second audio data having a second set of one or more phonemes, and wherein the causing is based, at least in part, upon a comparison between the first and second sets of one or more phonemes. | 10. A system, comprising: at least one processor; and a memory coupled to the at least one processor, wherein the memory stores program instructions, and wherein the program instructions are executable by the at least one processor to cause the system to: identify content requested by a client, wherein the requested content includes first audio data having a first set of one or more phonemes; and cause another content to be delivered to the client, wherein the another content includes second audio data having a second set of one or more phonemes, and wherein the causing is based, at least in part, upon a comparison between the first and second sets of one or more phonemes. 11. The system of claim 10 , wherein the requested content includes at least one of a web page, a video file, or an audio file. | 0.802181 |
8,351,706 | 2 | 7 | 2. A document extracting apparatus comprising: a processing device; a storage device storing instructions that, when executed by the processing device, cause the processing device to implement: storing a document index, the document index including a page index having page indices respectively indicating pages of the document data and a number of pages for each document in association with document data corresponding to each page included in the document; storing feature data, calculated based on a feature point extracted from the document data and indicative of a feature of the document data, in association with the document data; obtaining input document data serving as new document data; extracting a feature point from the input document data; generating feature data indicative of a feature of the input document data based on the extracted feature point; comparing the generated feature data with the stored feature data, thereby judging similarity between the document data associated with the feature data and the input document data; obtaining a document index associated with document data that is judged as document data highly similar to the input document data; and extracting a plurality of pieces of document data corresponding to a plurality of pages included in a document indicated by the obtained document index. | 2. A document extracting apparatus comprising: a processing device; a storage device storing instructions that, when executed by the processing device, cause the processing device to implement: storing a document index, the document index including a page index having page indices respectively indicating pages of the document data and a number of pages for each document in association with document data corresponding to each page included in the document; storing feature data, calculated based on a feature point extracted from the document data and indicative of a feature of the document data, in association with the document data; obtaining input document data serving as new document data; extracting a feature point from the input document data; generating feature data indicative of a feature of the input document data based on the extracted feature point; comparing the generated feature data with the stored feature data, thereby judging similarity between the document data associated with the feature data and the input document data; obtaining a document index associated with document data that is judged as document data highly similar to the input document data; and extracting a plurality of pieces of document data corresponding to a plurality of pages included in a document indicated by the obtained document index. 7. The document extracting apparatus according to claim 2 , further comprising: storing, in association with a document index, a predetermined output condition necessary for outputting document data corresponding to each page included in a document indicated by the document index; determining whether an output condition, associated with a document index associated with document data extracted by the document data extracting section, is satisfied; outputting, when the output condition is determined to be satisfied, a plurality of pieces of document data corresponding to a plurality of pages included in a document indicated by the document index; and inhibiting, when the output condition is determined to be not satisfied, output of a plurality of pieces of document data corresponding to a plurality of pages included in a document indicated by the document index. | 0.500573 |
9,547,832 | 1 | 11 | 1. A method comprising: receiving, by a computer system, a content item from a communication channel, wherein: the content item comprises: a communication from an individual; and a statement by the individual, the statement comprising committing language about an intent to attend an event; identifying the event as a topic of interest in the content item; determining, by the computer system, a commitment score of the individual to attend the event by: calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item; calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item; calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel; and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining, by the computer system, an action based on the commitment score of the individual to attend the event. | 1. A method comprising: receiving, by a computer system, a content item from a communication channel, wherein: the content item comprises: a communication from an individual; and a statement by the individual, the statement comprising committing language about an intent to attend an event; identifying the event as a topic of interest in the content item; determining, by the computer system, a commitment score of the individual to attend the event by: calculating a strength value of the intent of the individual to attend the event by performing a natural language analysis of the committing language of the statement by the individual in the content item; calculating a sentiment value of the intent of the individual to attend the event by performing a semantic analysis on the content item, the semantic analysis comprising identifying a description of a probability related to the event identified in the content item; calculating a social impact value of the intent of the individual to attend the event by performing a social impact analysis of the content item based on a number of receiving subscribers to the content item on the communication channel; and calculating a magnitude value of the intent of the individual to attend the event by performing a magnitude of commitment analysis of the content item based on a cost of attending the event, wherein: the commitment score comprises a combination of the strength value, the sentiment value, the social impact value, and the magnitude value; and determining, by the computer system, an action based on the commitment score of the individual to attend the event. 11. The method of claim 1 , wherein the event comprises a conference, seminar, a training class, a promotional event, a user group, a meeting with coworkers, a meeting, a movie, a meal, or a vacation. | 0.837662 |
7,870,161 | 14 | 16 | 14. A string signature scanning system, the system comprising: a machine-readable storage device including a computer program; and one or more processors or one or more special purpose logic circuits operable to execute the computer program, and perform operations including providing one or more modules including: a signature pre-processing module operable to process one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; a fingerprint scan engine operable to identify one or more fingerprints associated with one or more signatures on an input string field, the identifying including scanning the input string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size; a signature search engine operable to identify signatures for the identified fingerprints. | 14. A string signature scanning system, the system comprising: a machine-readable storage device including a computer program; and one or more processors or one or more special purpose logic circuits operable to execute the computer program, and perform operations including providing one or more modules including: a signature pre-processing module operable to process one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; a fingerprint scan engine operable to identify one or more fingerprints associated with one or more signatures on an input string field, the identifying including scanning the input string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size; a signature search engine operable to identify signatures for the identified fingerprints. 16. The system of claim 14 , where the signature search engine further includes a fixed-size signature search engine operable to identify fixed-size signatures or fixed-size substrings of variable-size signatures for identified fingerprints and a variable-size signature search engine operable to identify variable-size signatures including synthesizing identified fixed-size substrings into any variable-size signatures. | 0.663738 |
9,286,618 | 11 | 15 | 11. A non-transitory machine-readable medium storing a program of instructions thereon which, when executed by a processor, cause the processor to: designate a merchant location database entry appearing in a master merchant location database or a transaction data stream to be compared as a subject merchant location database entry, the subject merchant location database entry having a DBA name text field designating the doing business as (DBA) name of the merchant location, a street address text field designating the street address of the location of the merchant location, and one or more additional descriptive fields descriptive of one or more predetermined characteristics of the merchant location; populate a set with one or more candidate merchant location database entries located in a data warehouse database maintained by a network operator for comparison to the subject merchant location database entry, selected from a data warehouse database of merchant location entries, each candidate merchant location database entry having a DBA name text field designating the doing business as (DBA) name of the merchant location, a street address text field designating the street address of the location of the merchant location, and one or more additional descriptive fields descriptive of one or more predetermined characteristics of the merchant location, each candidate merchant location database entry being selected as a member of the set from and each candidate merchant location database entry having a predetermined minimum textural similarity with the subject merchant location database entry on the basis of respective DBA name text field or street address text field; compare the subject merchant location database entry with each of the candidate database entries on the basis of the one or more additional descriptive fields retrieved from the data warehouse database; perform a logistic regression using the results of the comparing to calculate a probability that the merchant location corresponding to the subject merchant location database entry and the merchant location corresponding to one or more of the candidate merchant location database entries are the same merchant location; and output the results of the logistic regression, wherein the one or more additional descriptive fields retrieved from the data warehouse include a classification code, the classification code derived from a hierarchical classification, and the comparing determines whether the subject merchant location database entry or the candidate merchant location database entry includes a classification code related to an industry which is experientially known to have merchant location identification data that is either more stable or less stable than other industries, and the logistic regression weights the merchant location classification code with regard to whether the related industry is known to have more or less stable merchant location identification data. | 11. A non-transitory machine-readable medium storing a program of instructions thereon which, when executed by a processor, cause the processor to: designate a merchant location database entry appearing in a master merchant location database or a transaction data stream to be compared as a subject merchant location database entry, the subject merchant location database entry having a DBA name text field designating the doing business as (DBA) name of the merchant location, a street address text field designating the street address of the location of the merchant location, and one or more additional descriptive fields descriptive of one or more predetermined characteristics of the merchant location; populate a set with one or more candidate merchant location database entries located in a data warehouse database maintained by a network operator for comparison to the subject merchant location database entry, selected from a data warehouse database of merchant location entries, each candidate merchant location database entry having a DBA name text field designating the doing business as (DBA) name of the merchant location, a street address text field designating the street address of the location of the merchant location, and one or more additional descriptive fields descriptive of one or more predetermined characteristics of the merchant location, each candidate merchant location database entry being selected as a member of the set from and each candidate merchant location database entry having a predetermined minimum textural similarity with the subject merchant location database entry on the basis of respective DBA name text field or street address text field; compare the subject merchant location database entry with each of the candidate database entries on the basis of the one or more additional descriptive fields retrieved from the data warehouse database; perform a logistic regression using the results of the comparing to calculate a probability that the merchant location corresponding to the subject merchant location database entry and the merchant location corresponding to one or more of the candidate merchant location database entries are the same merchant location; and output the results of the logistic regression, wherein the one or more additional descriptive fields retrieved from the data warehouse include a classification code, the classification code derived from a hierarchical classification, and the comparing determines whether the subject merchant location database entry or the candidate merchant location database entry includes a classification code related to an industry which is experientially known to have merchant location identification data that is either more stable or less stable than other industries, and the logistic regression weights the merchant location classification code with regard to whether the related industry is known to have more or less stable merchant location identification data. 15. The medium according to claim 11 , wherein populating the set with one or more candidate merchant location database entries comprises selecting those entries whose DBA name text field or street address text field exhibit a threshold numerically calculated degree of textual similarity with the corresponding DBA name text field or street address text field of the subject merchant location database entry. | 0.791963 |
8,543,409 | 12 | 13 | 12. The article of manufacture of claim 11 , wherein said synchronized set is determined by a gap assessment between said outcome narratives and a current state of handling said identified issues. | 12. The article of manufacture of claim 11 , wherein said synchronized set is determined by a gap assessment between said outcome narratives and a current state of handling said identified issues. 13. The article of manufacture of claim 12 , wherein said gap assessment identifies any of: gaps, implications of said gaps, and barriers inherent to said gaps. | 0.979019 |
5,566,330 | 3 | 5 | 3. The stored program computer of claim 2 wherein: said database interface object is programmed to display said retrieved data on a computer display; and at least some of said modifying methods are programmed to accept commands from an interactive user. | 3. The stored program computer of claim 2 wherein: said database interface object is programmed to display said retrieved data on a computer display; and at least some of said modifying methods are programmed to accept commands from an interactive user. 5. The stored program computer of claim 3 wherein: said column/style associations record a specification selected by said applications programmer of respective display formats for said displayable columns, said selectable data formats including built-in formats for displaying retrieved data of associated columns in a fixed format, and code-table formats displaying data of associated columns in a format tailorable by said applications programmer. | 0.928571 |
7,893,850 | 5 | 6 | 5. The method of claim 1 , further comprising providing a rotatable thumbwheel, and detecting a rotational input of the thumbwheel and an actuation of the <NEXT> second input member as being substantially identical to one another. | 5. The method of claim 1 , further comprising providing a rotatable thumbwheel, and detecting a rotational input of the thumbwheel and an actuation of the <NEXT> second input member as being substantially identical to one another. 6. The method of claim 5 , further comprising disposing the <NEXT> second input member substantially adjacent another input member, and disposing the thumbwheel at a location spaced from the <NEXT> second input member and the another input member. | 0.9012 |
7,685,195 | 17 | 27 | 17. A system, comprising: a processor; a computer-readable storage medium containing software instructions executable on the processor to cause the processor to perform operations including: receiving, using one or more processors, a session log; transmitting a first request from a web browser to a web server requesting access to one or more web pages of a web site, the first request including one or more referring search terms; using the one or more referring search terms to identify one or more web pages; storing content of the one or more web pages and content of a referring web page corresponding to the web browser in the session log, wherein the referring web page includes information used to ascertain the location of a user prior to the first request; receiving a current search term list including one or more purchased current search terms used to locate information associated with the web site; processing the session log to identify one or more candidate search terms in the one or more web pages and the referring web page stored in the session log; comparing the one or more candidate search terms with the one or more purchased current search terms, wherein the comparison identifies one or more additional search terms to add to the current search term list, and storing the one or more additional search terms. | 17. A system, comprising: a processor; a computer-readable storage medium containing software instructions executable on the processor to cause the processor to perform operations including: receiving, using one or more processors, a session log; transmitting a first request from a web browser to a web server requesting access to one or more web pages of a web site, the first request including one or more referring search terms; using the one or more referring search terms to identify one or more web pages; storing content of the one or more web pages and content of a referring web page corresponding to the web browser in the session log, wherein the referring web page includes information used to ascertain the location of a user prior to the first request; receiving a current search term list including one or more purchased current search terms used to locate information associated with the web site; processing the session log to identify one or more candidate search terms in the one or more web pages and the referring web page stored in the session log; comparing the one or more candidate search terms with the one or more purchased current search terms, wherein the comparison identifies one or more additional search terms to add to the current search term list, and storing the one or more additional search terms. 27. The system of claim 17 , further comprising: storing the one or more referring search terms used to locate the web site from the referring web page; using a search term validation program configured to group a plurality of session logs according to the one or more referring search terms; and processing the plurality of session logs to calculate probability information relating to the one or more referring search terms and the one or more web pages within each session log. | 0.65812 |
9,529,863 | 1 | 7 | 1. A method for ingesting data for a data model using a network computer that employs one or more processors to execute instructions that perform actions, comprising: providing one or more raw data sets to an ingestion engine, wherein each raw data set includes one or more raw records; providing one or more ingestion rules associated with one or more confidence scores and one or more known data sets based on a type of the one or more raw records; employing the ingestion engine to iteratively execute the one or more ingestion rules, performing further actions, including: providing a comparison of one or more portions of the one or more raw records to the one or more known data sets; transforming contents of the one or more raw records into one or more model record values based on the comparison to the one or more known data sets; storing the one or more model record values in one or more model records; providing a score value that indicates a confidence level that the one or more model records are correct based on the one or more confidence scores; and storing an association of the one or more ingestion rules used to transform the raw record contents into the model record values stored in the one or more model records; and when the score value that indicates the confidence level of the one or more model records is less than a threshold value, performing further actions, including: providing a user-interface to interactively edit the one or more raw records or the one or more ingestion rules, wherein the edited one or more ingestion rules produce an increase change or a decrease change in the one or more confidence scores, wherein the one or more changed confidence scores are employed to provide the score value; and storing the one or more model records in a data store, wherein the one or more model records are added to the data model. | 1. A method for ingesting data for a data model using a network computer that employs one or more processors to execute instructions that perform actions, comprising: providing one or more raw data sets to an ingestion engine, wherein each raw data set includes one or more raw records; providing one or more ingestion rules associated with one or more confidence scores and one or more known data sets based on a type of the one or more raw records; employing the ingestion engine to iteratively execute the one or more ingestion rules, performing further actions, including: providing a comparison of one or more portions of the one or more raw records to the one or more known data sets; transforming contents of the one or more raw records into one or more model record values based on the comparison to the one or more known data sets; storing the one or more model record values in one or more model records; providing a score value that indicates a confidence level that the one or more model records are correct based on the one or more confidence scores; and storing an association of the one or more ingestion rules used to transform the raw record contents into the model record values stored in the one or more model records; and when the score value that indicates the confidence level of the one or more model records is less than a threshold value, performing further actions, including: providing a user-interface to interactively edit the one or more raw records or the one or more ingestion rules, wherein the edited one or more ingestion rules produce an increase change or a decrease change in the one or more confidence scores, wherein the one or more changed confidence scores are employed to provide the score value; and storing the one or more model records in a data store, wherein the one or more model records are added to the data model. 7. The method of claim 1 , wherein providing the one or more raw data sets to an ingestion engine, comprises further actions, including: caching at least a portion of the one or more raw data sets when network communication is disabled; and providing the cached at least portion of the one or more raw data sets when network communication is enabled. | 0.814225 |
9,349,052 | 1 | 7 | 1. A computer-implemented method comprising: storing user profiles for each of a plurality of users of a social networking system; storing information for each of a plurality of objects in the social networking system; storing a plurality of connections between each of the plurality of the users and the other users or objects in the social networking system; accessing a plurality of images provided by a posting user of the plurality of users; receiving a request from a viewing user of the plurality of users to access an album, the album comprising a set of images selected from the plurality of images; identifying one or more tagged objects in the images in the album, where a tagged object is an object of the plurality of objects in the social networking system; computing a plurality of types of scores for one or more of the plurality of images, where the plurality of the types of scores for an image are based at least in part on an association between information from a user profile of the viewing user and the one or more tagged objects in the image; adjusting one or more of the computed plurality of types of scores to select a subset of the plurality of images based on the computed scores such that the selected subset of the plurality of images is diverse with respect to the types of scores, the subset selected based on the types of the scores for the images; sending for display to the viewing user an album, the album comprising the selected subset of the plurality of images. | 1. A computer-implemented method comprising: storing user profiles for each of a plurality of users of a social networking system; storing information for each of a plurality of objects in the social networking system; storing a plurality of connections between each of the plurality of the users and the other users or objects in the social networking system; accessing a plurality of images provided by a posting user of the plurality of users; receiving a request from a viewing user of the plurality of users to access an album, the album comprising a set of images selected from the plurality of images; identifying one or more tagged objects in the images in the album, where a tagged object is an object of the plurality of objects in the social networking system; computing a plurality of types of scores for one or more of the plurality of images, where the plurality of the types of scores for an image are based at least in part on an association between information from a user profile of the viewing user and the one or more tagged objects in the image; adjusting one or more of the computed plurality of types of scores to select a subset of the plurality of images based on the computed scores such that the selected subset of the plurality of images is diverse with respect to the types of scores, the subset selected based on the types of the scores for the images; sending for display to the viewing user an album, the album comprising the selected subset of the plurality of images. 7. The computer-implemented method of claim 1 , wherein the score for an image is further based in part on tagged objects associated with the other images in the plurality of images. | 0.810811 |
9,483,738 | 16 | 22 | 16. A non-transitory computer-readable storage medium containing instructions, that when executed, control a computer system to be configured for: defining information for a set of genomes, the set of genomes describing characteristics of media programs; defining which genomes in the set of genomes correspond to which topics in a set of topics; inputting textual information for a plurality of media programs and the information for the set of genomes into a model; training the model to determine a probability distribution of terms for the set of topics based on analyzing the textual information and the information for the set of genomes, wherein training comprises incorporating a parameter that prevents topics from being submerged by other topics that are larger via a first item in the model; and outputting the trained model, wherein the probability distribution of terms is usable to determine genomes for each of the plurality of media programs, wherein a genome corresponds to a topic and is associated with a media program based on terms found in the textual information for the media program and the probability distribution of terms for the topic corresponding to the genome. | 16. A non-transitory computer-readable storage medium containing instructions, that when executed, control a computer system to be configured for: defining information for a set of genomes, the set of genomes describing characteristics of media programs; defining which genomes in the set of genomes correspond to which topics in a set of topics; inputting textual information for a plurality of media programs and the information for the set of genomes into a model; training the model to determine a probability distribution of terms for the set of topics based on analyzing the textual information and the information for the set of genomes, wherein training comprises incorporating a parameter that prevents topics from being submerged by other topics that are larger via a first item in the model; and outputting the trained model, wherein the probability distribution of terms is usable to determine genomes for each of the plurality of media programs, wherein a genome corresponds to a topic and is associated with a media program based on terms found in the textual information for the media program and the probability distribution of terms for the topic corresponding to the genome. 22. The non-transitory computer-readable storage medium of claim 16 , wherein defining information for the set of genomes comprises defining terms that co-occur in a topic or cannot occur in the topic based on domain knowledge. | 0.824303 |
9,098,494 | 17 | 18 | 17. A method of generating a process that provides linguistic services in a first application from an already existing process that provides the services in a second language that is different from the first language, the method comprising the steps of: generating a hybrid process to act as a starting point, the hybrid process comprising: pre-existing components, of the already existing process, which provide linguistic services in the second language, a machine translation component that translates between the first language and the second language, an input recognition component that recognizes linguistic input received in the first language into text-based linguistic input, and an output generation component that generates output, in a manner receivable by the user, in the first language; generating components providing linguistic services in the first language that are analogous to pre-existing components which provide linguistic services in the second language; improving the generated components that provide the linguistic services in the first language based on received input and responsive processing performed by the generated hybrid process; and replacing the pre-existing components and the machine translation component with the generated and improved components that provide the linguistic services in the first language. | 17. A method of generating a process that provides linguistic services in a first application from an already existing process that provides the services in a second language that is different from the first language, the method comprising the steps of: generating a hybrid process to act as a starting point, the hybrid process comprising: pre-existing components, of the already existing process, which provide linguistic services in the second language, a machine translation component that translates between the first language and the second language, an input recognition component that recognizes linguistic input received in the first language into text-based linguistic input, and an output generation component that generates output, in a manner receivable by the user, in the first language; generating components providing linguistic services in the first language that are analogous to pre-existing components which provide linguistic services in the second language; improving the generated components that provide the linguistic services in the first language based on received input and responsive processing performed by the generated hybrid process; and replacing the pre-existing components and the machine translation component with the generated and improved components that provide the linguistic services in the first language. 18. The method of claim 17 , wherein the hybrid process further comprises a language identification component that identifies a language within which input to the hybrid process is provided. | 0.889148 |
9,779,317 | 2 | 3 | 2. The image processing apparatus of claim 1 , wherein the scanner is configured to read image information from the answered questionnaire sheet. | 2. The image processing apparatus of claim 1 , wherein the scanner is configured to read image information from the answered questionnaire sheet. 3. The image processing apparatus of claim 2 , wherein the operation interface circuitry further includes a questionnaire result data memory that stores the image information as questionnaire result data, and the second processor is further configured to compile entries for each of the items across pieces of the questionnaire result data. | 0.88498 |
8,504,507 | 14 | 15 | 14. A computer-implemented method for performing a sentiment analysis based on an estimated actual age, the method comprising: identifying, by a computer, a set of related members for a first member, wherein the first member and each member in the set of related members are members of a social networking website, and wherein each member in the set of related members is connected to the first member in the social network website; examining, by the computer, age information associated with one or more members in the set of related members in the set of related members; when a threshold number of members in the set of related members have an estimated actual age within a certain age range, estimating, by the computer, an actual age of the first member based on the estimated actual age of the members in the set of related members; and using, by the computer, the member's estimated actual age as an input to a sentiment analysis application for determining sentiments for a demographic that includes the member's age range. | 14. A computer-implemented method for performing a sentiment analysis based on an estimated actual age, the method comprising: identifying, by a computer, a set of related members for a first member, wherein the first member and each member in the set of related members are members of a social networking website, and wherein each member in the set of related members is connected to the first member in the social network website; examining, by the computer, age information associated with one or more members in the set of related members in the set of related members; when a threshold number of members in the set of related members have an estimated actual age within a certain age range, estimating, by the computer, an actual age of the first member based on the estimated actual age of the members in the set of related members; and using, by the computer, the member's estimated actual age as an input to a sentiment analysis application for determining sentiments for a demographic that includes the member's age range. 15. The method of claim 14 , wherein the sentiment analysis pertains to sentiments about one or more of: events, policies, products, companies, and people. | 0.836152 |
9,229,979 | 1 | 3 | 1. At a computer system, the computer system including one or more processors and system memory, the computer system connected to a plurality of compute nodes configured in a shared-nothing architecture, a distributed database distributed across the plurality of compute nodes, each compute node in the plurality of compute nodes maintaining a portion of the database in a local database instance, a method for identifying and propagating interesting properties within a query plan search space, the method comprising: accessing a query plan search space for a query of the distributed database, the query plan search space including a plurality of groups of logical operators arranged in a hierarchically structure, the hierarchical structure including a root group, one or more intermediate groups, and one or more leaf groups, each group of logical operators including one or more logical operators on one or more input groups; and formulating an annotated query plan search space by, for at least one group selected from among the root group and the one or more intermediate groups: for at least one child group of the at least one group: identifying a distribution property indicating an interesting type of distribution relevant to the child group, the distribution property identifying a column that data for a parent group of the child group is distributed on; and annotating the child group with the interesting type of distribution by attaching an indication of the identified column to the child group within the hierarchical structure to propagate the identified interesting type of distribution down to the child group for use in subsequent query plan pruning based on the annotated query plan search space. | 1. At a computer system, the computer system including one or more processors and system memory, the computer system connected to a plurality of compute nodes configured in a shared-nothing architecture, a distributed database distributed across the plurality of compute nodes, each compute node in the plurality of compute nodes maintaining a portion of the database in a local database instance, a method for identifying and propagating interesting properties within a query plan search space, the method comprising: accessing a query plan search space for a query of the distributed database, the query plan search space including a plurality of groups of logical operators arranged in a hierarchically structure, the hierarchical structure including a root group, one or more intermediate groups, and one or more leaf groups, each group of logical operators including one or more logical operators on one or more input groups; and formulating an annotated query plan search space by, for at least one group selected from among the root group and the one or more intermediate groups: for at least one child group of the at least one group: identifying a distribution property indicating an interesting type of distribution relevant to the child group, the distribution property identifying a column that data for a parent group of the child group is distributed on; and annotating the child group with the interesting type of distribution by attaching an indication of the identified column to the child group within the hierarchical structure to propagate the identified interesting type of distribution down to the child group for use in subsequent query plan pruning based on the annotated query plan search space. 3. The method of claim 1 , wherein identifying a distribution property indicating an interesting distribution relevant to the child group comprises identifying a distribution property for a top operator. | 0.948372 |
8,606,562 | 6 | 7 | 6. The method of claim 5 , wherein generating a number of language objects in response to detecting the second delimited ambiguous input further comprises: generating a number of prefix objects corresponding with the second delimited ambiguous input; identifying the language objects corresponding with the prefix objects, each of the language objects being associated with a frequency object; associating the frequency objects of the language objects with the corresponding prefix objects; and generating an output set from at least a portion of the prefix objects. | 6. The method of claim 5 , wherein generating a number of language objects in response to detecting the second delimited ambiguous input further comprises: generating a number of prefix objects corresponding with the second delimited ambiguous input; identifying the language objects corresponding with the prefix objects, each of the language objects being associated with a frequency object; associating the frequency objects of the language objects with the corresponding prefix objects; and generating an output set from at least a portion of the prefix objects. 7. The method of claim 6 , further comprising: storing the output set; and associating the output set with the second delimited ambiguous input. | 0.943262 |
10,007,786 | 12 | 16 | 12. A system for detecting malware, the system comprising: an identification module, stored in memory, that identifies a behavioral trace of a program, the behavioral trace comprising a sequence of runtime behaviors exhibited by the program; a division module, stored in memory, that divides the behavioral trace to identify a plurality of n-grams within the behavioral trace, each runtime behavior within the sequence of runtime behaviors corresponding to an n-gram token; an analysis module, stored in memory, that analyzes the plurality of n-grams to generate a feature vector of the behavioral trace comprising: applying, for each given n-gram in the plurality of n-grams, a feature function to the behavioral trace that describes an occurrence characteristic of the given n-gram within the behavioral trace; and including a result of the feature function in the feature vector; wherein: the feature vector comprises a plurality of dimensions, each n-gram within the plurality of n-grams corresponding to a dimension within the plurality of dimensions; the plurality of n-grams map to the plurality of dimensions according to a non-injective surjection; and including the result of the feature function in the feature vector comprises aggregating a subset of outputs of the feature function derived from a subset of the plurality of n-grams into a value and assigning the value to a dimension within the plurality of dimensions according to the non-injective surjection; a classification module, stored in memory, that classifies the program based at least in part on the feature vector of the behavioral trace to determine whether the program is malicious; and at least one physical processor configured to execute the identification module, the division module, the analysis module, and the classification module. | 12. A system for detecting malware, the system comprising: an identification module, stored in memory, that identifies a behavioral trace of a program, the behavioral trace comprising a sequence of runtime behaviors exhibited by the program; a division module, stored in memory, that divides the behavioral trace to identify a plurality of n-grams within the behavioral trace, each runtime behavior within the sequence of runtime behaviors corresponding to an n-gram token; an analysis module, stored in memory, that analyzes the plurality of n-grams to generate a feature vector of the behavioral trace comprising: applying, for each given n-gram in the plurality of n-grams, a feature function to the behavioral trace that describes an occurrence characteristic of the given n-gram within the behavioral trace; and including a result of the feature function in the feature vector; wherein: the feature vector comprises a plurality of dimensions, each n-gram within the plurality of n-grams corresponding to a dimension within the plurality of dimensions; the plurality of n-grams map to the plurality of dimensions according to a non-injective surjection; and including the result of the feature function in the feature vector comprises aggregating a subset of outputs of the feature function derived from a subset of the plurality of n-grams into a value and assigning the value to a dimension within the plurality of dimensions according to the non-injective surjection; a classification module, stored in memory, that classifies the program based at least in part on the feature vector of the behavioral trace to determine whether the program is malicious; and at least one physical processor configured to execute the identification module, the division module, the analysis module, and the classification module. 16. The system of claim 12 , wherein the classification module further determines the program is malware based on the classification of the program. | 0.842553 |
8,441,449 | 14 | 15 | 14. The handheld device of claim 11 , wherein retrieving a word frame corresponding with the ambiguous input further comprises: comparing the ambiguous input with word frames stored in the memory. | 14. The handheld device of claim 11 , wherein retrieving a word frame corresponding with the ambiguous input further comprises: comparing the ambiguous input with word frames stored in the memory. 15. The handheld device of claim 14 , further comprising: an input apparatus comprising a plurality of input keys, wherein comparing the ambiguous input with word frames further comprises: determining whether the ambiguous input includes a subset comprising sequential selections of one of the input keys. | 0.843268 |
9,916,377 | 7 | 10 | 7. An apparatus comprising: a memory; at least one processor, coupled to said memory; and a non-transitory computer readable medium comprising computer executable instructions which when loaded into said memory configure said at least one processor to: obtain a base query having a plurality of base query terms; access a plurality of problem log files; extract words, contained in a corpus vocabulary, from said plurality of problem log files; based on said words extracted from said plurality of problem log files, generate a first expanded query from said base query; and query said corpus, via a query engine and a corpus index, with a second expanded query related to said first expanded query; wherein said instructions further configure said at least one processor to determine that at least one of said query terms is in said corpus vocabulary; and wherein said generating comprises, responsive to said determining that at least one of said query terms is in said corpus vocabulary: picking one or more words having highest relevance to said query terms from among said words extracted in said extracting step, based on a topic model of said corpus; and adding at least one of said words having said highest relevance to said base query to generate said first expanded query. | 7. An apparatus comprising: a memory; at least one processor, coupled to said memory; and a non-transitory computer readable medium comprising computer executable instructions which when loaded into said memory configure said at least one processor to: obtain a base query having a plurality of base query terms; access a plurality of problem log files; extract words, contained in a corpus vocabulary, from said plurality of problem log files; based on said words extracted from said plurality of problem log files, generate a first expanded query from said base query; and query said corpus, via a query engine and a corpus index, with a second expanded query related to said first expanded query; wherein said instructions further configure said at least one processor to determine that at least one of said query terms is in said corpus vocabulary; and wherein said generating comprises, responsive to said determining that at least one of said query terms is in said corpus vocabulary: picking one or more words having highest relevance to said query terms from among said words extracted in said extracting step, based on a topic model of said corpus; and adding at least one of said words having said highest relevance to said base query to generate said first expanded query. 10. The apparatus of claim 7 , wherein: said non-transitory computer readable medium comprising said computer executable instructions embodies: a pre-processor module having a word extraction sub-module, a decision logic sub-module, and a generative sub-module; and a search engine module having a query engine sub-module; said at least one processor is configured to extract said words by executing said word extraction sub-module of said pre-processor module; said at least one processor is configured to determine whether at least one of said query terms is in said corpus vocabulary by executing said decision logic sub-module of said pre-processor module; said at least one processor is configured to pick and add steps by executing said generative sub-module of said pre-processor module; and said at least one processor is configured to query by executing said query engine sub-module of said search engine module. | 0.500542 |
9,098,570 | 2 | 3 | 2. The method of claim 1 , wherein the term weight values are generated using inverse frequency scores. | 2. The method of claim 1 , wherein the term weight values are generated using inverse frequency scores. 3. The method of claim 2 , wherein the paragraph scores are generated by limiting the number of times a paragraph term can be counted to generate a paragraph score. | 0.953541 |
9,275,152 | 3 | 4 | 3. The method of claim 1 , wherein the information identifying the one or more entities of the second entity type comprises a respective image corresponding to each of the one or more entities, and wherein the method further comprises: obtaining, for each of the one or more entities of the second entity type, the respective image corresponding to the entity from an image search engine in response to a search query derived from the name of the entity. | 3. The method of claim 1 , wherein the information identifying the one or more entities of the second entity type comprises a respective image corresponding to each of the one or more entities, and wherein the method further comprises: obtaining, for each of the one or more entities of the second entity type, the respective image corresponding to the entity from an image search engine in response to a search query derived from the name of the entity. 4. The method of claim 3 , wherein obtaining the image for a particular entity of the one or more entities of the second type comprises: determining that a particular search query including the name of the particular entity is ambiguous, wherein determining that the particular search query is ambiguous comprises determining, from search results provided for the particular search query by the search engine, that the particular search query either does not relate to any entity in an index that maps each of a plurality of resources to a specific entity of a specific type or relates to more than one entity in the index; generating a second search query that includes the name of the particular entity and at least one of: a reference to the first entity of the first entity type or a reference to the second entity type; obtaining image search results for the second search query from the image search engine; and selecting the image for the particular entity from images identified by the image search results for the second search query. | 0.741319 |
10,152,299 | 16 | 18 | 16. The method of claim 1 , further comprising: determining whether the electronic device is communicatively coupled to a second electronic device, wherein in response to determining that the electronic device is communicatively coupled to the second electronic device: the representation of the speech input is transmitted to the server via the second electronic device; the domain signal is received from the server via the second electronic device; and the data content is received from the server via the second electronic device. | 16. The method of claim 1 , further comprising: determining whether the electronic device is communicatively coupled to a second electronic device, wherein in response to determining that the electronic device is communicatively coupled to the second electronic device: the representation of the speech input is transmitted to the server via the second electronic device; the domain signal is received from the server via the second electronic device; and the data content is received from the server via the second electronic device. 18. The method of claim 16 , wherein in response to determining that the electronic device is not communicatively coupled to the second electronic device: the representation of the speech input is transmitted directly to a server; the domain signal is received directly from the server; and the data content is received directly from the server. | 0.875181 |
7,890,876 | 12 | 15 | 12. The system of claim 11 wherein the application retrieves multiple items of graphical and textual content from the contextual storefront content server based upon keywords detected in the text content of messages sent or received via the system. | 12. The system of claim 11 wherein the application retrieves multiple items of graphical and textual content from the contextual storefront content server based upon keywords detected in the text content of messages sent or received via the system. 15. The system of claim 12 wherein the graphical and textual items are grouped together by subject matter in a database in or accessed by the contextual storefront content server. | 0.948236 |
8,818,999 | 17 | 19 | 17. An apparatus comprising: a memory device storing instructions for determining relevant search results; and a processor executing the instructions to perform the steps of: performing a search on a document database according to a search query containing query terms; obtaining, from the document database over a network, documents resulting from performing the search query, the documents containing terms that match the search query; determining base relevancy scores for the documents; adjusting the base relevancy scores by applying a lead boosting value calculated according to an influence function, the influence function promoting a particular word position in a document, the particular word position being a predetermined number of words from the beginning of the document; and ranking the documents according to the adjusted base relevancy scores. | 17. An apparatus comprising: a memory device storing instructions for determining relevant search results; and a processor executing the instructions to perform the steps of: performing a search on a document database according to a search query containing query terms; obtaining, from the document database over a network, documents resulting from performing the search query, the documents containing terms that match the search query; determining base relevancy scores for the documents; adjusting the base relevancy scores by applying a lead boosting value calculated according to an influence function, the influence function promoting a particular word position in a document, the particular word position being a predetermined number of words from the beginning of the document; and ranking the documents according to the adjusted base relevancy scores. 19. The apparatus of claim 17 , the processor executing the instructions to perform the further steps of: calculating a plurality of probability distribution functions for the search query, wherein one of the plurality of probability distribution functions corresponds to one of the query terms in the search query; determining, based on the plurality of probability distribution functions, a level of consistency between the plurality of probability distribution functions; calculating a hit-consistency boosting values based on the level of consistency between the plurality of probability distribution functions; and applying the hit-consistency boost values to the base relevancy scores of the documents. | 0.509695 |
8,214,359 | 22 | 29 | 22. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and providing the set of final search results. | 22. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and providing the set of final search results. 29. The computer storage medium of claim 22 , wherein the query-relevant parts are paragraphs. | 0.955366 |
9,799,350 | 13 | 18 | 13. The method of claim 10 , wherein the performing of the utterance verification includes: separately calculating word-specific confidence scores of words of sections in which the events have occurred and words for which no event has occurred; calculating confidence scores in units of sentences or utterances based on the calculated word-specific confidence scores; calculating sentence-specific confidence scores to which the events are applied without separating words from each other using section information of the sections in which the events have occurred and estimated values of a plurality of feature parameters; analyzing sentence structures and meanings of speech recognition result sentences and calculating confidence scores of sentences; and comparing the calculated confidence scores with a preset threshold value and determining whether or not to accept the speech recognition result sentences according to comparison results. | 13. The method of claim 10 , wherein the performing of the utterance verification includes: separately calculating word-specific confidence scores of words of sections in which the events have occurred and words for which no event has occurred; calculating confidence scores in units of sentences or utterances based on the calculated word-specific confidence scores; calculating sentence-specific confidence scores to which the events are applied without separating words from each other using section information of the sections in which the events have occurred and estimated values of a plurality of feature parameters; analyzing sentence structures and meanings of speech recognition result sentences and calculating confidence scores of sentences; and comparing the calculated confidence scores with a preset threshold value and determining whether or not to accept the speech recognition result sentences according to comparison results. 18. The method of claim 13 , wherein the determining of whether or not to accept the speech recognition result sentences includes accepting the speech recognition result sentences when two or more kinds of scores among the three kinds of calculated scores are larger than the preset threshold value, rejecting the speech recognition result sentences when all of the three kinds of scores are smaller than the preset threshold value, and determining that the speech recognition result sentences are indeterminable when one kind of scores among the three kinds of scores is larger than the preset threshold value and the other two kinds of scores are smaller than the preset threshold value. | 0.780713 |
7,630,895 | 1 | 9 | 1. A speaker verification method comprising: performing operations executed by a speaker verification machine, the operations comprising: comparing a plurality of different test utterances to a plurality of training utterances for a speaker to form a plurality of preliminary verification decisions, one preliminary verification decision for each of the plurality of different test utterances; weighting each of the plurality of preliminary verification decisions based on a historical error rate corresponding to a respective one of the test utterances; and combining the weighted preliminary verification decisions to form a verification decision. | 1. A speaker verification method comprising: performing operations executed by a speaker verification machine, the operations comprising: comparing a plurality of different test utterances to a plurality of training utterances for a speaker to form a plurality of preliminary verification decisions, one preliminary verification decision for each of the plurality of different test utterances; weighting each of the plurality of preliminary verification decisions based on a historical error rate corresponding to a respective one of the test utterances; and combining the weighted preliminary verification decisions to form a verification decision. 9. The method of claim 1 , further comprising selecting a male variance vector to weight each of the plurality of preliminary verification decisions based on whether the speaker is a male. | 0.770171 |
9,720,655 | 7 | 8 | 7. The computer system of claim 6 , wherein the processing device is further configured to: provide a definition interface to allow a rule for an event of the user interface component type to be defined based on the associated business domain object. | 7. The computer system of claim 6 , wherein the processing device is further configured to: provide a definition interface to allow a rule for an event of the user interface component type to be defined based on the associated business domain object. 8. The computer system of claim 7 , wherein the definition interface is provided in a spreadsheet format. | 0.965731 |
8,195,468 | 8 | 9 | 8. The mobile device of claim 1 , wherein the conversational voice user interface subsequently receives one or more follow-up multi-modal inputs, the follow-up multi-modal inputs including at least one of a follow-up natural language utterance or a follow-up non-speech input. | 8. The mobile device of claim 1 , wherein the conversational voice user interface subsequently receives one or more follow-up multi-modal inputs, the follow-up multi-modal inputs including at least one of a follow-up natural language utterance or a follow-up non-speech input. 9. The mobile device of claim 8 , wherein the identified domain agent updates the context stack and the semantic knowledge-based model in response to processing the request. | 0.953793 |
7,975,019 | 29 | 44 | 29. A method of dynamically supplementing a web page loaded by a web browser from a web site, the method comprising: generating a tag via a tag generation tool, and communicating the tag to an operator of said web site, said tag adapted for incorporation into web page coding of the web site; receiving, over a network, a request generated by the browser in response to said tag being included in the web page; and responding to the request by causing the browser to load and execute an update handler, wherein execution of the update handler causes the browser to at least (a) analyze content of the web page and to determine that the web page includes a link that matches a pre-specified link signature of a catalog page, said link including an identifier of a product, (b) retrieve, based on said identifier of the product, catalog content associated with the product, wherein the catalog content is retrieved over a network from a content server that is separate from the web site, and (c) supplement the web page with the catalog content; wherein the method, including generating the tag, receiving the request, and responding to the request, is performed by a system that comprises at least one machine. | 29. A method of dynamically supplementing a web page loaded by a web browser from a web site, the method comprising: generating a tag via a tag generation tool, and communicating the tag to an operator of said web site, said tag adapted for incorporation into web page coding of the web site; receiving, over a network, a request generated by the browser in response to said tag being included in the web page; and responding to the request by causing the browser to load and execute an update handler, wherein execution of the update handler causes the browser to at least (a) analyze content of the web page and to determine that the web page includes a link that matches a pre-specified link signature of a catalog page, said link including an identifier of a product, (b) retrieve, based on said identifier of the product, catalog content associated with the product, wherein the catalog content is retrieved over a network from a content server that is separate from the web site, and (c) supplement the web page with the catalog content; wherein the method, including generating the tag, receiving the request, and responding to the request, is performed by a system that comprises at least one machine. 44. The method of claim 29 , wherein generating the tag comprises incorporating an identifier of the web site operator into the tag, and the method further comprises using said identifier to track user referrals attributable to the web site operator. | 0.655647 |
8,155,969 | 12 | 14 | 12. A non-transitory storage device comprising a program product which allows a computer to realize: using a processor device configured to perform: recognizing speech in a presentation to produce subtitles; extracting keywords from document data used in the presentation; adding the extracted keywords to a voice recognition dictionary; and assigning word attribute weights to the keywords extracted from the presentation based on word attributes read from a word attribute database, wherein said word attributes comprise at least one of: a title, character size, character underlining, and boldface character; recording a time that the page is turned and a time when a next page is turned to determine time spent on the page; storing the time spent as a timestamp; calculating a weight of the keywords on a page based on a combination of: a duration during which said page is displayed in the presentation when it is determined that the extraction of the keyword has been successful; and the word attribute weights assigned to the keywords; a function of determining, among the subtitles obtained by recognizing speech generated with reference to a predetermined document, a specific subtitle obtained by recognizing the speech generated with reference to a specific page of the document; and a function of storing a correspondence between the specific subtitle and the specific page. | 12. A non-transitory storage device comprising a program product which allows a computer to realize: using a processor device configured to perform: recognizing speech in a presentation to produce subtitles; extracting keywords from document data used in the presentation; adding the extracted keywords to a voice recognition dictionary; and assigning word attribute weights to the keywords extracted from the presentation based on word attributes read from a word attribute database, wherein said word attributes comprise at least one of: a title, character size, character underlining, and boldface character; recording a time that the page is turned and a time when a next page is turned to determine time spent on the page; storing the time spent as a timestamp; calculating a weight of the keywords on a page based on a combination of: a duration during which said page is displayed in the presentation when it is determined that the extraction of the keyword has been successful; and the word attribute weights assigned to the keywords; a function of determining, among the subtitles obtained by recognizing speech generated with reference to a predetermined document, a specific subtitle obtained by recognizing the speech generated with reference to a specific page of the document; and a function of storing a correspondence between the specific subtitle and the specific page. 14. The program product according to claim 12 , further allowing the computer to realize a function of retrieving character strings, with the retrieval target range extended from the specific subtitle to text data contained in the specific page. | 0.761673 |
8,615,707 | 26 | 30 | 26. A system comprising: a client device comprising a display screen; and one or more computers programmed to interact with the client device and to perform operations comprising: receiving description data describing a preexisting structured presentation, a visual presentation of the preexisting structured presentation visually presenting information in a systematic arrangement that conforms with a structured design, the preexisting structured presentation including values that each characterize a respective attribute of an instance, the preexisting structured presentation denoting characterization of attributes of a particular instance by particular values by virtue of an arrangement of an identifier of the particular instance and the particular values in a visual presentation of the preexisting structured presentation; conducting, by the machine, a search of an unstructured collection of electronic documents by comparing characteristics of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new attribute that is relevant to the preexisting structured presentation; adding in response to the locating of the electronic documents an identifier of the new attribute to the preexisting structured presentation to form an expanded structured presentation, wherein adding the identifier of the new attribute comprises: formulating a collection of attribute suggestions, wherein formulating the collection of attribute suggestions comprises: identifying a first document in the electronic document collection that is relevant to one of the instances identified in the preexisting structured presentation and that is arranged in accordance with a template, where the template is a pattern for the arrangement of the content of the first document; and adding an attribute used in the first document to characterize the instance in the attribute suggestion collection; providing the attribute suggestion collection to a user; and receiving a user selection of the new attribute, wherein the new attribute is in the collection of attribute suggestions; and outputting instructions for presenting the expanded structured presentation on the display screen. | 26. A system comprising: a client device comprising a display screen; and one or more computers programmed to interact with the client device and to perform operations comprising: receiving description data describing a preexisting structured presentation, a visual presentation of the preexisting structured presentation visually presenting information in a systematic arrangement that conforms with a structured design, the preexisting structured presentation including values that each characterize a respective attribute of an instance, the preexisting structured presentation denoting characterization of attributes of a particular instance by particular values by virtue of an arrangement of an identifier of the particular instance and the particular values in a visual presentation of the preexisting structured presentation; conducting, by the machine, a search of an unstructured collection of electronic documents by comparing characteristics of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new attribute that is relevant to the preexisting structured presentation; adding in response to the locating of the electronic documents an identifier of the new attribute to the preexisting structured presentation to form an expanded structured presentation, wherein adding the identifier of the new attribute comprises: formulating a collection of attribute suggestions, wherein formulating the collection of attribute suggestions comprises: identifying a first document in the electronic document collection that is relevant to one of the instances identified in the preexisting structured presentation and that is arranged in accordance with a template, where the template is a pattern for the arrangement of the content of the first document; and adding an attribute used in the first document to characterize the instance in the attribute suggestion collection; providing the attribute suggestion collection to a user; and receiving a user selection of the new attribute, wherein the new attribute is in the collection of attribute suggestions; and outputting instructions for presenting the expanded structured presentation on the display screen. 30. The system of claim 26 , wherein comparing the characteristics of the preexisting structured presentation with the content of the electronic documents comprises comparing the instances characterized in the preexisting structured presentation with the content of the electronic documents. | 0.568249 |
8,234,561 | 1 | 21 | 1. A method comprising: observing values entered in form field objects; generating likelihood assessments for possible values to be entered in a current form field object based on the observed values, the likelihood assessments indicating relative probability of the possible values being entered in the current form field object; and predicting a value for the current form field object based on the generated likelihood assessments, wherein generating likelihood assessments comprises: determining a semantic similarity between the current form field object and a form field for which values have been observed; and generating a likelihood assessment for a possible value based on the observed values for the form field and the determined semantic similarity. | 1. A method comprising: observing values entered in form field objects; generating likelihood assessments for possible values to be entered in a current form field object based on the observed values, the likelihood assessments indicating relative probability of the possible values being entered in the current form field object; and predicting a value for the current form field object based on the generated likelihood assessments, wherein generating likelihood assessments comprises: determining a semantic similarity between the current form field object and a form field for which values have been observed; and generating a likelihood assessment for a possible value based on the observed values for the form field and the determined semantic similarity. 21. The method of claim 1 , wherein predicting a value for the current form field object comprises: receiving user input activating the current form field object and entering one or more characters; and in response to the user input, displaying a selected value in the current form field object, the selected value being a value from the possible values with a highest likelihood assessment that also matches the one or more characters. | 0.756696 |
9,767,796 | 29 | 30 | 29. The language dialogue system as recited in claim 27 , wherein the records included in the properties database further comprises a public downloaded record data corresponding to the keyword, a public cited record data corresponding to the keyword, a public recommendation record data corresponding to the keyword, a public comment record data corresponding to the keyword, or a public referral record data corresponding to the keyword. | 29. The language dialogue system as recited in claim 27 , wherein the records included in the properties database further comprises a public downloaded record data corresponding to the keyword, a public cited record data corresponding to the keyword, a public recommendation record data corresponding to the keyword, a public comment record data corresponding to the keyword, or a public referral record data corresponding to the keyword. 30. The language dialogue system as recited in claim 29 , wherein the at least one first report answer is selected according to the public downloaded record data included in the records, the public cited record data included in the records, the public recommendation record data included in the records, the public comment record data included in the records, the public referral record data included in the records, or at least a combination of two of said public record data. | 0.890244 |
6,112,304 | 26 | 46 | 26. A computer system implementing an ecosystem computing architecture, the computer system comprising: an operational environment for distributed computing processes here termed denizens, each denizen including a configuration portion an origin portion, and an executable portion, each denizen performing at least one step on itself, the operational environment including at least two locations, each location providing access to a processor for executing instructions and providing a memory accessible to the processor for storing instructions; a transport means for denizens to travel between the locations; and at least one denizen that is a user denizen which receives instructions, evaluates different locations in the operational environment in view of the received instructions, selects a location based on that evaluation, moves itself to the selected location, and executes at least a portion of the received instructions at the selected location. | 26. A computer system implementing an ecosystem computing architecture, the computer system comprising: an operational environment for distributed computing processes here termed denizens, each denizen including a configuration portion an origin portion, and an executable portion, each denizen performing at least one step on itself, the operational environment including at least two locations, each location providing access to a processor for executing instructions and providing a memory accessible to the processor for storing instructions; a transport means for denizens to travel between the locations; and at least one denizen that is a user denizen which receives instructions, evaluates different locations in the operational environment in view of the received instructions, selects a location based on that evaluation, moves itself to the selected location, and executes at least a portion of the received instructions at the selected location. 46. The computer system of claim 26, further comprising a set of templates which define denizen inheritance information and which can be used to build denizens. | 0.65368 |
9,128,918 | 1 | 3 | 1. A method implemented on a computer having at least one processor, storage, and a communication platform for providing translated web content, comprising the steps of: receiving a request, via a public network connection, from an online user for consuming content in a second language translated from content in a first language; obtaining, upon receiving the request, the content in the first language from an Internet source that hosts the content in the first language; dividing the obtained content in the first language into a plurality of translatable components; determining, with respect to each of the plurality of translatable components, whether there is a corresponding translated component previously stored; generating, if a number of translatable components that have corresponding translated components exceeds a threshold, the content in the second language by replacing each of the number of translatable components with a corresponding translated component; automatically placing an address of the content in the first language onto a translation queue, if the number of translatable components that have corresponding translated components does not exceed the threshold, so that the content in the first language represented by the address is to be translated via machine translation with human post-editing to create the content in the second language; and sending the content in the second language to the online user as a response to the request. | 1. A method implemented on a computer having at least one processor, storage, and a communication platform for providing translated web content, comprising the steps of: receiving a request, via a public network connection, from an online user for consuming content in a second language translated from content in a first language; obtaining, upon receiving the request, the content in the first language from an Internet source that hosts the content in the first language; dividing the obtained content in the first language into a plurality of translatable components; determining, with respect to each of the plurality of translatable components, whether there is a corresponding translated component previously stored; generating, if a number of translatable components that have corresponding translated components exceeds a threshold, the content in the second language by replacing each of the number of translatable components with a corresponding translated component; automatically placing an address of the content in the first language onto a translation queue, if the number of translatable components that have corresponding translated components does not exceed the threshold, so that the content in the first language represented by the address is to be translated via machine translation with human post-editing to create the content in the second language; and sending the content in the second language to the online user as a response to the request. 3. The method of claim 1 , wherein the Internet source is different from a system where the request is received. | 0.681818 |
9,299,010 | 3 | 4 | 3. The method of claim 2 , wherein the forming a weighted combination of the first class designation, the second class designation and the third class designation comprises weighting the first class designation with a weight of 2, weighting the second class designation with a weight of 2, and weighting the third class designation with a weight of 1. | 3. The method of claim 2 , wherein the forming a weighted combination of the first class designation, the second class designation and the third class designation comprises weighting the first class designation with a weight of 2, weighting the second class designation with a weight of 2, and weighting the third class designation with a weight of 1. 4. The method of claim 3 , comprising combining the first class designation, the second class designation and the third class designation to generate a confidence metric. | 0.95589 |
6,069,939 | 52 | 54 | 52. The apparatus of claim 48, further comprising means for enabling said calling party to select specific languages or dialects for delivery of audio prompts to specific cities. | 52. The apparatus of claim 48, further comprising means for enabling said calling party to select specific languages or dialects for delivery of audio prompts to specific cities. 54. The apparatus of claim 52, wherein said means for enabling includes means for enabling said calling party to determine a limited number of specific languages or dialects for delivery of audio prompts to a limited number of specific cities. | 0.796823 |
10,121,517 | 7 | 8 | 7. The computer implemented method of claim 1 , further comprising determining the number of characters recited in the displayed text. | 7. The computer implemented method of claim 1 , further comprising determining the number of characters recited in the displayed text. 8. The computer implemented method of claim 7 , further comprising identifying a second portion of the displayed text comprising a first number of consecutive characters starting form the first character, wherein the first number of consecutive characters divided by the total number of characters is equal to or approximately equal to the calculated percentage of time the first video was viewed. | 0.816713 |
8,606,769 | 9 | 15 | 9. A system for determining a rank for URL, the system comprising: a memory; a processor in communication with the memory; the processor effective to send a search query to a search engine; receive a search engine results page from the search engine including a result with a URL; determine a first rank of the URL based on the search engine results page; render a result on the search engine results page; determine a horizontal or vertical location on the search engine results page where the result is rendered; and modify the first rank based on the horizontal or vertical location to produce a modified rank for the URL; wherein the processor is effective to determine the horizontal or vertical location by being effective to determine a vertical distance between the result in the search engine results page and a to edge of the search engine results page. | 9. A system for determining a rank for URL, the system comprising: a memory; a processor in communication with the memory; the processor effective to send a search query to a search engine; receive a search engine results page from the search engine including a result with a URL; determine a first rank of the URL based on the search engine results page; render a result on the search engine results page; determine a horizontal or vertical location on the search engine results page where the result is rendered; and modify the first rank based on the horizontal or vertical location to produce a modified rank for the URL; wherein the processor is effective to determine the horizontal or vertical location by being effective to determine a vertical distance between the result in the search engine results page and a to edge of the search engine results page. 15. The system as recited in claim 9 , wherein: the search engine results page is a first search engine results page; the first search engine results page includes a results area including results of a first size and results or additional data of a second size; and the processor is effective to modify the first rank by being effective to compare the horizontal or vertical location to a second search engine results page with a results area including results of only the first size. | 0.501031 |
9,202,140 | 1 | 9 | 1. A computer-implemented method for classifying an object, comprising: (a) constructing, by a processor, at least one quotient appearance manifold mapping based on a sample image to untangle appearance fiber bundles of different objects, wherein the at least one quotient appearance manifold mapping associates points of an appearance manifold to a quotient manifold; (b) reducing, by the processor, dimensionality of the quotient appearance manifold mapping to generate at least one feature characteristic of the sample image; and (c) training, by the processor, based on said feature, at least one classifier adapted for associating the object with an object class. | 1. A computer-implemented method for classifying an object, comprising: (a) constructing, by a processor, at least one quotient appearance manifold mapping based on a sample image to untangle appearance fiber bundles of different objects, wherein the at least one quotient appearance manifold mapping associates points of an appearance manifold to a quotient manifold; (b) reducing, by the processor, dimensionality of the quotient appearance manifold mapping to generate at least one feature characteristic of the sample image; and (c) training, by the processor, based on said feature, at least one classifier adapted for associating the object with an object class. 9. The method of claim 1 wherein the step (a) comprises: (d) associating a neighborhood with a pixel of the sample image; and (e) constructing a quotient manifold of the neighborhood. | 0.702922 |
4,658,370 | 64 | 65 | 64. The computer as claimed in claim 59, wherein said factual knowledge base includes means for defining attributes capable of having respective values, and means for defining designated ones of the attributes as Boolean attributes having values from the set of values including true and false, and means for defining designated ones of the attributes as subsumed by designated respective ones of said Boolean attributes, and wherein said inference engine includes means for determining the value of an attribute by testing whether the attribute is subsumed by one of said Boolean attributes determining the value of any such Boolean attribute, and determining that the value of the subsumed attribute is known to be irrelevant when the value of such Boolean attribute is false. | 64. The computer as claimed in claim 59, wherein said factual knowledge base includes means for defining attributes capable of having respective values, and means for defining designated ones of the attributes as Boolean attributes having values from the set of values including true and false, and means for defining designated ones of the attributes as subsumed by designated respective ones of said Boolean attributes, and wherein said inference engine includes means for determining the value of an attribute by testing whether the attribute is subsumed by one of said Boolean attributes determining the value of any such Boolean attribute, and determining that the value of the subsumed attribute is known to be irrelevant when the value of such Boolean attribute is false. 65. The computer as claimed in claim 64, wherein said inference engine comprises post-determination means, operative when a value for an attribute is determined, for testing whether the attribute is subsumed by one of said Boolean attributes, and determining any such Boolean attribute to be true when the subsumed attribute is known to have a value. | 0.945141 |
7,609,881 | 12 | 13 | 12. An image processing method according to the claim 9 , wherein said extracting step includes a first extracting step of extracting text image areas, graphic image areas, and photographic image areas from image data, and a second extracting step of extracting filled closed areas, unfilled closed areas, and line areas that do not form any closed areas from the extracted graphic image areas; wherein said step of recognizing attributes includes recognizing attributes concerning whether each extracted image area is a text image area, a photographic image area, a filled closed area, an unfilled closed area or a line area; and said setting up step includes setting up the overlaying sequence for each image area of text image areas, photographic image areas, filled closed areas, unfilled closed areas, and line areas in accordance with the recognition results of the attributes. | 12. An image processing method according to the claim 9 , wherein said extracting step includes a first extracting step of extracting text image areas, graphic image areas, and photographic image areas from image data, and a second extracting step of extracting filled closed areas, unfilled closed areas, and line areas that do not form any closed areas from the extracted graphic image areas; wherein said step of recognizing attributes includes recognizing attributes concerning whether each extracted image area is a text image area, a photographic image area, a filled closed area, an unfilled closed area or a line area; and said setting up step includes setting up the overlaying sequence for each image area of text image areas, photographic image areas, filled closed areas, unfilled closed areas, and line areas in accordance with the recognition results of the attributes. 13. An image processing method according to the claim 12 wherein said setting up step includes setting up the overlaying sequence to overlay text image areas in front, filled closed areas and photographic image areas in back, and unfilled closed areas and line areas are in between them. | 0.874563 |
8,204,213 | 17 | 18 | 17. The method of claim 1 , wherein the obfuscation function includes a cryptographic function. | 17. The method of claim 1 , wherein the obfuscation function includes a cryptographic function. 18. The method of claim 17 , wherein the cryptographic function occurs on a secure hardware device. | 0.976179 |
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