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9,075,449 | 9 | 10 | 9. The method of claim 1 , further comprising detecting an input from a touch screen display as being the input from the multiple-axis input device. | 9. The method of claim 1 , further comprising detecting an input from a touch screen display as being the input from the multiple-axis input device. 10. The method of claim 9 , further comprising outputting on the touch screen display a depiction representative of the multiple-axis input device. | 0.5 |
7,480,860 | 12 | 13 | 12. The method as defined in claim 11 , wherein the presentation-level transform generates an HTML document or a text file for end user presentation. | 12. The method as defined in claim 11 , wherein the presentation-level transform generates an HTML document or a text file for end user presentation. 13. The method as defined in claim 12 , wherein the subscription-level transform is mandatory and the organization-level and presentation-level transforms are optional. | 0.5 |
6,098,062 | 1 | 14 | 1. A system for facilitating a decision-making process comprising: a first computer having the computer readable program code means embodied on the first computer readable medium comprising: a first program code means for linking of a plurality of argument structure units into single hierarchial argument structure, wherein each of said argument structure unit includes data corresponding to a hypothesis and its corresponding counter-hypothesis; a second computer program code means for accepting inputs from a plurality of contributors and augmenting said inputs into said single hierarchial argument structure, wherein each input comprises data corresponding to at least one argument structure unit and that supports at least one of said hypothesis and the corresponding counter-hypothesis thereof; a third computer program means responsive to said second computer program code means and adapted to represent a degree of support for said hypothesis and said corresponding counter-hypothesis in said single hierarchial argument structure; and a fourth computer readable program code means responsive to said third computer readable program code means and adapted to visually display said degree of support for and against each claim in said single hierarchy; a plurality of contributor input programming means each stored in a computer readable medium located on one of a plurality of computers remote from said first computer, wherein each of said contributor input programming means comprises: programming means for accepting contributor input data from one of the plurality of contributors, wherein each input comprises data corresponding to at least one argument structure unit that supports at least one of said hypothesis and the corresponding counter-hypothesis thereof, and wherein said contributor input data are provided to said second computer program code means for combining into said single hierarchial argument structure. | 1. A system for facilitating a decision-making process comprising: a first computer having the computer readable program code means embodied on the first computer readable medium comprising: a first program code means for linking of a plurality of argument structure units into single hierarchial argument structure, wherein each of said argument structure unit includes data corresponding to a hypothesis and its corresponding counter-hypothesis; a second computer program code means for accepting inputs from a plurality of contributors and augmenting said inputs into said single hierarchial argument structure, wherein each input comprises data corresponding to at least one argument structure unit and that supports at least one of said hypothesis and the corresponding counter-hypothesis thereof; a third computer program means responsive to said second computer program code means and adapted to represent a degree of support for said hypothesis and said corresponding counter-hypothesis in said single hierarchial argument structure; and a fourth computer readable program code means responsive to said third computer readable program code means and adapted to visually display said degree of support for and against each claim in said single hierarchy; a plurality of contributor input programming means each stored in a computer readable medium located on one of a plurality of computers remote from said first computer, wherein each of said contributor input programming means comprises: programming means for accepting contributor input data from one of the plurality of contributors, wherein each input comprises data corresponding to at least one argument structure unit that supports at least one of said hypothesis and the corresponding counter-hypothesis thereof, and wherein said contributor input data are provided to said second computer program code means for combining into said single hierarchial argument structure. 14. The invention of claim 1 wherein said input further comprises: a modality associated with said contributor's input. | 0.904952 |
7,827,177 | 1 | 4 | 1. A computer implemented method comprising: accessing compound document declarations that specify how to section a given XML document into subdocuments of a compound document; one or more computing devices generating a compound document that includes a parent document and a plurality of subdocuments of said parent document; wherein content of said parent document includes for each subdocument of said plurality of subdocuments, a link to said each subdocument; and wherein generating said compound document includes applying said compound document declarations to a source XML document to generate said parent document and said plurality of subdocuments of said parent document. | 1. A computer implemented method comprising: accessing compound document declarations that specify how to section a given XML document into subdocuments of a compound document; one or more computing devices generating a compound document that includes a parent document and a plurality of subdocuments of said parent document; wherein content of said parent document includes for each subdocument of said plurality of subdocuments, a link to said each subdocument; and wherein generating said compound document includes applying said compound document declarations to a source XML document to generate said parent document and said plurality of subdocuments of said parent document. 4. The computer-implemented method of claim 1 , wherein said compound document declarations include one or more XPath expressions that identify content in said given XML document that comprises a given subdocument. | 0.778926 |
8,824,785 | 22 | 26 | 22. The system of claim 21 further comprising: the processor further operative to determine a location of the handwritten information on the document relative to the typographic information. | 22. The system of claim 21 further comprising: the processor further operative to determine a location of the handwritten information on the document relative to the typographic information. 26. The system of claim 22 further comprising: the processor further operative to determine an expected location of the handwritten information within the electronic document image relative to the typographic information, and store an indication of whether the location of the handwritten information within the electronic document relative to the typographic information coincides with the expected location of the handwritten information within the electronic document image relative to the typographic information. | 0.5 |
8,930,181 | 1 | 2 | 1. A method performed in a computer device having associated therewith a plurality of unstructured documents having words therein, the computing device also having associated therewith a way for a user of the computer device to provide input of at least components of words, the computing device comprising at least one processor, the method comprising: receiving in the computer device as an input, at least one component of a word; based upon the input, accessing using the computing device, at least one stored matrix accessible to the computer device, the at least one stored matrix containing words from the unstructured documents and, for each word, a value for at least one score type; retrieving from the at least one stored matrix at least two words as potential completion candidates and each's associated value for the at least one score type; based upon a lex ordering, specifying an order in which values of score types are to be analyzed; analyzing, using the computer device, the potential completion candidates by calculating an absolute value of the difference between the values of the potential completion candidates for a first score type specified by the lex ordering and comparing the absolute value of the difference to a threshold; when the threshold is met, ordering the potential completion candidates, using the computer device, such that the potential completion candidate with the greater value for the first score type is ahead of the potential completion candidate with the lesser value for the first score type; and presenting at least the one of the potential completion candidates that was placed ahead, to the user using the computer device, in response to the input such that the user can select the presented at least the one of the potential completion candidates to complete the user's input. | 1. A method performed in a computer device having associated therewith a plurality of unstructured documents having words therein, the computing device also having associated therewith a way for a user of the computer device to provide input of at least components of words, the computing device comprising at least one processor, the method comprising: receiving in the computer device as an input, at least one component of a word; based upon the input, accessing using the computing device, at least one stored matrix accessible to the computer device, the at least one stored matrix containing words from the unstructured documents and, for each word, a value for at least one score type; retrieving from the at least one stored matrix at least two words as potential completion candidates and each's associated value for the at least one score type; based upon a lex ordering, specifying an order in which values of score types are to be analyzed; analyzing, using the computer device, the potential completion candidates by calculating an absolute value of the difference between the values of the potential completion candidates for a first score type specified by the lex ordering and comparing the absolute value of the difference to a threshold; when the threshold is met, ordering the potential completion candidates, using the computer device, such that the potential completion candidate with the greater value for the first score type is ahead of the potential completion candidate with the lesser value for the first score type; and presenting at least the one of the potential completion candidates that was placed ahead, to the user using the computer device, in response to the input such that the user can select the presented at least the one of the potential completion candidates to complete the user's input. 2. The method of claim 1 , wherein the at least one score type comprises at least the first score type and a second score type, and wherein the threshold is a first threshold, and wherein when the first threshold is not met, the method comprises: analyzing, using the computer device, the potential completion candidates by calculating an absolute value of the difference between the values of the potential completion candidates for the second score type specified by the lex ordering and comparing the absolute value of the difference to a second threshold; and when the second threshold is met, ordering the potential completion candidates such that the potential completion candidate with the greater value for the second score type is ahead of the potential completion candidate with the lesser value for the second score type. | 0.5 |
7,752,266 | 29 | 31 | 29. A system to facilitate translation of communications between entities over a network, said system comprising: a communications server to communicate a plurality of predetermined language constructs in a first language to a first entity as a first transmission over said network, the plurality of predetermined language constructs in the first language displayed to the first entity in a first set of one or more interactive fields, each predetermined language construct of the plurality of language constructs in the first language being associated with a predetermined numerical identifier, and receive, from said first entity, an identifier of a second entity and a first numerical identifier of a first language construct selected by the first entity from said plurality of predetermined language constructs in the first language, the first numerical identifier comprising a numerical indicator of the first language construct and not including the text of the first language construct; and a processing server to determine a translated language construct corresponding to said first numerical identifier, said processing server to determine responsive to a receipt of said first numerical identifier, said processing server to determine the translated language construct further comprises: said processing server to retrieve entity information relating to said second entity based on the identifier of said second entity, said processing server to retrieve said translated language construct from a table based on said entity information and said first numerical identifier of the first language construct; said communication server further to communicate said translated language construct and the plurality of predetermined language constructs in a second language in a second set of one or more interactive fields to said second entity as a second transmission over said network, the second entity to respond to the first entity by selecting a second language construct from the plurality of predetermined language constructs in the second language, each predetermined language construct of the plurality of language constructs in the second language being associated with the predetermined numerical identifier. | 29. A system to facilitate translation of communications between entities over a network, said system comprising: a communications server to communicate a plurality of predetermined language constructs in a first language to a first entity as a first transmission over said network, the plurality of predetermined language constructs in the first language displayed to the first entity in a first set of one or more interactive fields, each predetermined language construct of the plurality of language constructs in the first language being associated with a predetermined numerical identifier, and receive, from said first entity, an identifier of a second entity and a first numerical identifier of a first language construct selected by the first entity from said plurality of predetermined language constructs in the first language, the first numerical identifier comprising a numerical indicator of the first language construct and not including the text of the first language construct; and a processing server to determine a translated language construct corresponding to said first numerical identifier, said processing server to determine responsive to a receipt of said first numerical identifier, said processing server to determine the translated language construct further comprises: said processing server to retrieve entity information relating to said second entity based on the identifier of said second entity, said processing server to retrieve said translated language construct from a table based on said entity information and said first numerical identifier of the first language construct; said communication server further to communicate said translated language construct and the plurality of predetermined language constructs in a second language in a second set of one or more interactive fields to said second entity as a second transmission over said network, the second entity to respond to the first entity by selecting a second language construct from the plurality of predetermined language constructs in the second language, each predetermined language construct of the plurality of language constructs in the second language being associated with the predetermined numerical identifier. 31. The system according to claim 29 , wherein said first language construct is a predetermined question that is asked by said first entity in an electronic commerce transaction over said network. | 0.809709 |
9,971,804 | 4 | 5 | 4. The method of claim 1 , wherein the plurality of entity population rules define an aggregation of the plurality of input records. | 4. The method of claim 1 , wherein the plurality of entity population rules define an aggregation of the plurality of input records. 5. The method of claim 4 , wherein the aggregation is computed by populating an index separate from the entity. | 0.5 |
9,576,249 | 1 | 4 | 1. A computer-implemented method of measuring a user's comprehension of subject matter of a text, the method comprising: receiving a summary generated by the user, the summary being a constructed response that summarizes a text; parsing the summary with a processing system to identify a number of sentences contained in the summary and to identify in the summary a plurality of multi-word sequences; processing the summary and a reference summary with the processing system to determine a first numerical measure indicative of a similarity between the summary and a reference summary, the reference summary having been designated as representative of the subject matter of the text; processing the summary with the processing system to determine a second numerical measure indicative of a degree to which a single sentence of the summary summarizes an entirety of the text; processing the summary and the text with the processing system to determine a third numerical measure indicative of a degree of copying in the summary of multi-word sequences present in the text; and applying a numerical model to the first numerical measure, the second numerical measure and the third numerical measure to determine a score for the summary indicative of the user's comprehension of the subject matter of the text, the numerical model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the first variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. | 1. A computer-implemented method of measuring a user's comprehension of subject matter of a text, the method comprising: receiving a summary generated by the user, the summary being a constructed response that summarizes a text; parsing the summary with a processing system to identify a number of sentences contained in the summary and to identify in the summary a plurality of multi-word sequences; processing the summary and a reference summary with the processing system to determine a first numerical measure indicative of a similarity between the summary and a reference summary, the reference summary having been designated as representative of the subject matter of the text; processing the summary with the processing system to determine a second numerical measure indicative of a degree to which a single sentence of the summary summarizes an entirety of the text; processing the summary and the text with the processing system to determine a third numerical measure indicative of a degree of copying in the summary of multi-word sequences present in the text; and applying a numerical model to the first numerical measure, the second numerical measure and the third numerical measure to determine a score for the summary indicative of the user's comprehension of the subject matter of the text, the numerical model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the first variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. 4. The computer-implemented method of claim 1 comprising: processing the summary with the processing system to determine a fourth numerical measure indicative of a number of discourse markers included in the summary; and applying the numerical model to the fourth numerical measure to determine the score for the summary, the numerical model including a fourth variable and an associated fourth weighting factor, the fourth variable receiving a value of the fourth numerical measure. | 0.67232 |
9,092,434 | 1 | 19 | 1. A method for processing and producing email documents, the method comprising: receiving, by a processor, information organizing a first plurality of email documents into a plurality of document groups; generating, by the processor, a graphical user interface for reviewing a document group from the plurality of document groups, the document group including a second plurality of email documents from the first plurality of email documents that are organized into the document group, wherein the second plurality of email documents represent an email thread, and wherein the graphical user interface comprises a first section displaying the document group and a second section to receive a plurality of review content to associate with each of the second plurality of email documents or to associate with each of the email documents of other document groups from the plurality of document groups based on a selection from the second section of the graphical user interface; receiving, by the processor, the plurality of review content comprising one or more annotations provided by a user of the graphical user interface that are applicable to the document group; associating, by the processor, the plurality of review content with the document group; for each review content of the plurality of review content: determining, by the processor, a propagation for the review content to the second plurality of emails, and propagating, by the processor, the review content to the second plurality of email documents based on the determined propagation for the review content, wherein the review content is propagated to each email document in the second plurality of email documents, or the review content is propagated to a subset of email documents in the second plurality of email documents, and wherein one or more of the email documents of the second plurality of email documents comprises at least one multiply annotated email document that is associated with the plurality of the review content and is annotated based on an aggregation of the plurality of review content; and producing, by the processor, a third plurality of email documents from the first plurality of email documents in response to one or more queries related to the one or more annotations in the review content that has been propagated, the third plurality of email documents including at least one email document from the second plurality of email documents in the document group. | 1. A method for processing and producing email documents, the method comprising: receiving, by a processor, information organizing a first plurality of email documents into a plurality of document groups; generating, by the processor, a graphical user interface for reviewing a document group from the plurality of document groups, the document group including a second plurality of email documents from the first plurality of email documents that are organized into the document group, wherein the second plurality of email documents represent an email thread, and wherein the graphical user interface comprises a first section displaying the document group and a second section to receive a plurality of review content to associate with each of the second plurality of email documents or to associate with each of the email documents of other document groups from the plurality of document groups based on a selection from the second section of the graphical user interface; receiving, by the processor, the plurality of review content comprising one or more annotations provided by a user of the graphical user interface that are applicable to the document group; associating, by the processor, the plurality of review content with the document group; for each review content of the plurality of review content: determining, by the processor, a propagation for the review content to the second plurality of emails, and propagating, by the processor, the review content to the second plurality of email documents based on the determined propagation for the review content, wherein the review content is propagated to each email document in the second plurality of email documents, or the review content is propagated to a subset of email documents in the second plurality of email documents, and wherein one or more of the email documents of the second plurality of email documents comprises at least one multiply annotated email document that is associated with the plurality of the review content and is annotated based on an aggregation of the plurality of review content; and producing, by the processor, a third plurality of email documents from the first plurality of email documents in response to one or more queries related to the one or more annotations in the review content that has been propagated, the third plurality of email documents including at least one email document from the second plurality of email documents in the document group. 19. The method of claim 1 wherein generating the graphical user interface configured for review of the document group includes generating information configured for reviewing each of the second plurality of email documents associated with the document group. | 0.572848 |
8,788,566 | 16 | 27 | 16. A policy engine for enforcing context model based Service-Oriented Architecture (SOA) policies, comprising: a memory; and a processor programmed to execute: a gathering module that gathers instance documents related to policy enforcement according to a business requirement, where the instance documents are instantiated from corresponding schema documents; a context model generator that generates an instantiated context model comprising references to the gathered instance documents from a context model definition; a policy set generator that generates a policy set to be enforced via the instantiated context model according to the gathered instance documents; a sequence determining module that determines an enforcement sequence of policies in the policy set; a policy applying module that applies the policies to the instantiated context model according to the enforcement sequence; and where the policy applying module and the context model generator are further configured to provide context model-based forward chaining, comprising being configured to: determine whether the instantiated context model should be updated; if the instantiated context model should be updated: update the instantiated context model with at least one updated instance document comprising executing an updating operation to create the at least one updated instance document; detect and resolving a conflict caused by the updating operation; generate the updated instantiated context model according to the at least one updated instance document and the instantiated context model; and re-apply the policies to only the at least one updated instance document within the updated instantiated context model according to the enforcement sequence. | 16. A policy engine for enforcing context model based Service-Oriented Architecture (SOA) policies, comprising: a memory; and a processor programmed to execute: a gathering module that gathers instance documents related to policy enforcement according to a business requirement, where the instance documents are instantiated from corresponding schema documents; a context model generator that generates an instantiated context model comprising references to the gathered instance documents from a context model definition; a policy set generator that generates a policy set to be enforced via the instantiated context model according to the gathered instance documents; a sequence determining module that determines an enforcement sequence of policies in the policy set; a policy applying module that applies the policies to the instantiated context model according to the enforcement sequence; and where the policy applying module and the context model generator are further configured to provide context model-based forward chaining, comprising being configured to: determine whether the instantiated context model should be updated; if the instantiated context model should be updated: update the instantiated context model with at least one updated instance document comprising executing an updating operation to create the at least one updated instance document; detect and resolving a conflict caused by the updating operation; generate the updated instantiated context model according to the at least one updated instance document and the instantiated context model; and re-apply the policies to only the at least one updated instance document within the updated instantiated context model according to the enforcement sequence. 27. The policy engine according to claim 16 , where the policy applying module comprises: a document validating unit that validates whether any instance document in the instantiated context model is matched using each of the policies; a validation report generating unit that generates a validation report for the matched policy; an action enforcing unit that enforces an action part of the matched policy according to the validation report. | 0.713636 |
6,101,515 | 15 | 26 | 15. A computer readable medium having a set of instructions stored therein, which when executed by a computer, causes the computer to perform the steps of: storing a classification system comprising a plurality of categories of terminology arranged in a hierarchy of categories so as to reflect associations among related categories; processing the input set of documents to generate contextual data by classifying the term in a plurality of categories of the classification system; and analyzing the contextual data by performing hierarchical clustering analysis on the selected categories of the hierarchy of categories in the classification system to identify a cluster of categories and to select a single category in the cluster from the plurality of selected categories to learn the term as the single category selected. | 15. A computer readable medium having a set of instructions stored therein, which when executed by a computer, causes the computer to perform the steps of: storing a classification system comprising a plurality of categories of terminology arranged in a hierarchy of categories so as to reflect associations among related categories; processing the input set of documents to generate contextual data by classifying the term in a plurality of categories of the classification system; and analyzing the contextual data by performing hierarchical clustering analysis on the selected categories of the hierarchy of categories in the classification system to identify a cluster of categories and to select a single category in the cluster from the plurality of selected categories to learn the term as the single category selected. 26. The computer readable medium as set forth in claim 15, further comprising instructions for removing inappropriate terms from consideration from learning. | 0.883704 |
9,430,495 | 15 | 16 | 15. A computer program product comprising a computer-readable storage medium including instructions that, when executed by a processor, cause the processor to: generate a location store comprising a plurality of entries maintained by a social networking system, each entry including a physical location description and one or more terms associated with the physical location description; identify a plurality of entries having a physical location description within an area; determine a local frequency associated with each term included the identified plurality of entries, the local frequency of a term representing a number of occurrences of the term within the identified plurality of entries; determine a global frequency associated with each term included in the identified plurality of entries, the global frequency of the term representing a number of occurrences of the term within the location store; identify one or more terms having an associated local frequency exceeding an associated global frequency by at least a threshold amount as trending terms; generate a score for an entry from the plurality of entries based at least in part on one or more difference between terms in the entry from the plurality of entries and terms in an additional entry from a plurality of entries and whether a term in the entry differing from a term in the additional entry is a trending term; and generate a combined entry including terms from the entry and from the additional entry if the score is less than a threshold value. | 15. A computer program product comprising a computer-readable storage medium including instructions that, when executed by a processor, cause the processor to: generate a location store comprising a plurality of entries maintained by a social networking system, each entry including a physical location description and one or more terms associated with the physical location description; identify a plurality of entries having a physical location description within an area; determine a local frequency associated with each term included the identified plurality of entries, the local frequency of a term representing a number of occurrences of the term within the identified plurality of entries; determine a global frequency associated with each term included in the identified plurality of entries, the global frequency of the term representing a number of occurrences of the term within the location store; identify one or more terms having an associated local frequency exceeding an associated global frequency by at least a threshold amount as trending terms; generate a score for an entry from the plurality of entries based at least in part on one or more difference between terms in the entry from the plurality of entries and terms in an additional entry from a plurality of entries and whether a term in the entry differing from a term in the additional entry is a trending term; and generate a combined entry including terms from the entry and from the additional entry if the score is less than a threshold value. 16. The computer program product of claim 15 , wherein generate the score for the entry from the plurality of entries comprises: align terms in the entry with terms in the additional entry; compare each term in the entry with a corresponding aligned term in the additional entry; determine a cost associated with each term in the entry based at least in part on a difference between the term in the entry and the corresponding aligned term in the additional entry; generate a modified cost for one or more terms identified as trending terms by discounting a cost associated with a term identified as a trending term; and generate the score based at least in part on the costs and the modified costs. | 0.5 |
8,200,866 | 9 | 11 | 9. The apparatus of claim 8 wherein the first alphabetic characters of the alphanumeric character set comprises a set of ordered letters, each ordered letter corresponding to a DTMF signal consistent with ordered letters of a conventional telephone keypad layout. | 9. The apparatus of claim 8 wherein the first alphabetic characters of the alphanumeric character set comprises a set of ordered letters, each ordered letter corresponding to a DTMF signal consistent with ordered letters of a conventional telephone keypad layout. 11. The apparatus of claim 9 wherein the ordered letters are arranged to provide selection of letters with a higher probability of use before letters with a lower probability of use during consecutive activations of the at least one input key. | 0.5 |
7,653,541 | 2 | 5 | 2. The speech processing device according to claim 1 , further comprising pattern determination means for determining whether the result of the recognition matches a predetermined word sequence, wherein the registering means registers the word if the result of the recognition matches the predetermined word sequence. | 2. The speech processing device according to claim 1 , further comprising pattern determination means for determining whether the result of the recognition matches a predetermined word sequence, wherein the registering means registers the word if the result of the recognition matches the predetermined word sequence. 5. The speech processing device according to claim 2 , wherein the registering means registers the other information while associating the other information with the matched pattern if the pattern determination means determines that the result of the recognition matches the word sequence. | 0.650121 |
7,721,271 | 3 | 5 | 3. The process according to claim 1 , further comprising the step of: simplifying and normalizing said intercepted data. | 3. The process according to claim 1 , further comprising the step of: simplifying and normalizing said intercepted data. 5. The process according to claim 3 , wherein said simplifying and normalizing step further comprising the step of: removing control characters. | 0.652174 |
7,647,349 | 1 | 3 | 1. A computer-implemented method for exchanging meta-documents between meta-document servers, comprising: importing, at an importing meta-document server, a meta-document from an exporting meta-document server; the imported meta-document including one or more document service requests fulfilled using one or more document services available at the exporting meta-document server; developing at the importing meta-document server an ontology of namespaces that describe entities in the imported meta-document; binding at least a selected one of the one or more document service requests in the imported meta-document to one of a plurality of document services available at the importing meta-document server when: (a) properties of the selected document service request in the imported meta-document map to properties of one of the plurality of document services available at the importing meta-document server; or (b) the selected document service request in the imported meta-document and one of the plurality of document services available at the importing meta-document server (i) map to the same category in the developed ontology, and (ii) have at least one dictionary and one key in common. | 1. A computer-implemented method for exchanging meta-documents between meta-document servers, comprising: importing, at an importing meta-document server, a meta-document from an exporting meta-document server; the imported meta-document including one or more document service requests fulfilled using one or more document services available at the exporting meta-document server; developing at the importing meta-document server an ontology of namespaces that describe entities in the imported meta-document; binding at least a selected one of the one or more document service requests in the imported meta-document to one of a plurality of document services available at the importing meta-document server when: (a) properties of the selected document service request in the imported meta-document map to properties of one of the plurality of document services available at the importing meta-document server; or (b) the selected document service request in the imported meta-document and one of the plurality of document services available at the importing meta-document server (i) map to the same category in the developed ontology, and (ii) have at least one dictionary and one key in common. 3. The method according to claim 1 , wherein two keys are in common with each other when one of the two keys associated with a first service and the other of the two keys associated with a second service reduce to a common generic key. | 0.639571 |
9,923,925 | 14 | 16 | 14. A computer implemented method comprising: receiving a ruleset at a second entity of a plurality of entities, wherein the ruleset comprises instructions selectably applicable by an entity of the plurality of entities to detect one or more security attacks, wherein the ruleset was generated by a first entity of the plurality of entities, wherein the ruleset is associated with a first plurality of security attack data, and wherein each entity of the plurality of entities comprises a network of computing devices; and applying the ruleset at the second entity to identify a potential or actual security attack at the second entity, wherein applying the ruleset comprises: identifying a plurality of network communications associated with a network of computing devices of the second entity, wherein the plurality of network communications are from the network of computing devices of the second entity to an external computing device; identifying an elapsed time between at least two communications of the plurality of network communications; and determining that the elapsed time is within a predetermined time interval, wherein said determination indicates beaconing behavior. | 14. A computer implemented method comprising: receiving a ruleset at a second entity of a plurality of entities, wherein the ruleset comprises instructions selectably applicable by an entity of the plurality of entities to detect one or more security attacks, wherein the ruleset was generated by a first entity of the plurality of entities, wherein the ruleset is associated with a first plurality of security attack data, and wherein each entity of the plurality of entities comprises a network of computing devices; and applying the ruleset at the second entity to identify a potential or actual security attack at the second entity, wherein applying the ruleset comprises: identifying a plurality of network communications associated with a network of computing devices of the second entity, wherein the plurality of network communications are from the network of computing devices of the second entity to an external computing device; identifying an elapsed time between at least two communications of the plurality of network communications; and determining that the elapsed time is within a predetermined time interval, wherein said determination indicates beaconing behavior. 16. The computer implemented method of claim 14 , wherein applying the ruleset at the second entity further comprises identifying an external IP address associated with the potential or actual security attack. | 0.852609 |
8,090,740 | 12 | 17 | 12. A method for organizing and displaying search queries and associated search result histories on a computer display, comprising: receiving multiple search queries related to more than one topic being searched from a user and multiple search results associated with each of the multiple search queries accessed by a user and sites accessed by the user via a trail of links within the accessed search results; automatically, without user action, displaying on the computer display in a hierarchically organized manner each of the more than one search topic at the highest level, each search query of the multiple search queries associated with a search topic indented on a separate line on the second level below the associated topic, and the search results associated with each search query that the user accessed and each site accessed by the user via a trail of links originating from within the accessed search results indented on a separate line below the associated search query that returned the search results. | 12. A method for organizing and displaying search queries and associated search result histories on a computer display, comprising: receiving multiple search queries related to more than one topic being searched from a user and multiple search results associated with each of the multiple search queries accessed by a user and sites accessed by the user via a trail of links within the accessed search results; automatically, without user action, displaying on the computer display in a hierarchically organized manner each of the more than one search topic at the highest level, each search query of the multiple search queries associated with a search topic indented on a separate line on the second level below the associated topic, and the search results associated with each search query that the user accessed and each site accessed by the user via a trail of links originating from within the accessed search results indented on a separate line below the associated search query that returned the search results. 17. The method of claim 12 further comprising naming each search result accessed by the user with a name of a web site associated with the search result accessed by the user. | 0.759003 |
8,548,796 | 11 | 16 | 11. A method machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-phrases, each of the bi-phrases including a text fragment from the first language and a text fragment from the second language, at least some of the bi-phrases comprising words tagged with restricted part of speech tags, at least one of the restricted part of speech tags configured for identifying a compoundable word from the second language as being one which also forms a part of a known closed compound word; retrieving text fragments in the second language from the library corresponding to text fragments in the source text; generating at least one target hypothesis, each of the target hypotheses comprising text fragments selected from the retrieved text fragments in the second language; and evaluating the target hypothesis based at least in part on combinations of restricted part of speech tags of corresponding compoundable words, comprising: for each of at least one specified combination of consecutive restricted part of speech tags of corresponding compoundable words from different bi-phrases, identifying occurrences of the specified combination in the hypothesis; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions taking into account the occurrences of the specified combination of the restricted part of speech tags of the corresponding compoundable words from different bi-phrases in the hypothesis; and based on the evaluation, outputting one of the at least one target hypothesis as the optimal hypothesis for forming the translation; and wherein at least one of the accessing, retrieving, evaluating and outputting is performed with a computer processor. | 11. A method machine translation method for translating source text from a first language to target text in a second language, comprising: receiving the source text in the first language; accessing a library of bi-phrases, each of the bi-phrases including a text fragment from the first language and a text fragment from the second language, at least some of the bi-phrases comprising words tagged with restricted part of speech tags, at least one of the restricted part of speech tags configured for identifying a compoundable word from the second language as being one which also forms a part of a known closed compound word; retrieving text fragments in the second language from the library corresponding to text fragments in the source text; generating at least one target hypothesis, each of the target hypotheses comprising text fragments selected from the retrieved text fragments in the second language; and evaluating the target hypothesis based at least in part on combinations of restricted part of speech tags of corresponding compoundable words, comprising: for each of at least one specified combination of consecutive restricted part of speech tags of corresponding compoundable words from different bi-phrases, identifying occurrences of the specified combination in the hypothesis; and evaluating the target hypothesis with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions taking into account the occurrences of the specified combination of the restricted part of speech tags of the corresponding compoundable words from different bi-phrases in the hypothesis; and based on the evaluation, outputting one of the at least one target hypothesis as the optimal hypothesis for forming the translation; and wherein at least one of the accessing, retrieving, evaluating and outputting is performed with a computer processor. 16. The method of claim 11 , wherein the translation scoring function comprises a log-linear translation scoring function in which weights are assigned to each of the feature functions and wherein the evaluation of the at least one hypothesis includes selecting a hypothesis from a plurality of hypotheses which optimizes the log-linear translation scoring function. | 0.613924 |
8,200,617 | 1 | 24 | 1. A method for automatically mapping a pattern of a location identifier of an object to a semantic type using metadata associated with the object, the method, comprising: determining the location identifier for the object; wherein, the metadata corresponds to the semantic type with which the object or content embodied therein has a semantic relationship; extracting the pattern from the location identifier of the object; storing the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type; wherein, the pattern corresponds to the semantic type with which the object or the content embodied therein has a semantic relationship; wherein, the metadata has an associated weighting; and wherein, the pattern extracted from the location identifier has a trustworthiness rating that corresponds to the associated weighting of the metadata. | 1. A method for automatically mapping a pattern of a location identifier of an object to a semantic type using metadata associated with the object, the method, comprising: determining the location identifier for the object; wherein, the metadata corresponds to the semantic type with which the object or content embodied therein has a semantic relationship; extracting the pattern from the location identifier of the object; storing the pattern in a database embodied in a machine-readable storage medium as being mapped to the semantic type; wherein, the pattern corresponds to the semantic type with which the object or the content embodied therein has a semantic relationship; wherein, the metadata has an associated weighting; and wherein, the pattern extracted from the location identifier has a trustworthiness rating that corresponds to the associated weighting of the metadata. 24. The method of claim 1 , wherein, the object is visually sorted in a search results page according to the semantic relationship with the semantic type. | 0.767372 |
8,056,128 | 61 | 63 | 61. The system of claim 56 , where the suspect document is associated with an electronic message and where the processing unit is further to: inhibit access to the electronic message if the trustworthiness value indicates that the suspect document is untrustworthy. | 61. The system of claim 56 , where the suspect document is associated with an electronic message and where the processing unit is further to: inhibit access to the electronic message if the trustworthiness value indicates that the suspect document is untrustworthy. 63. The system of claim 61 , where, when inhibiting access to the electronic message, the processing unit is further to: delete the electronic message prior to user access if the trustworthiness value indicates that the suspect document is untrustworthy. | 0.5 |
8,370,347 | 16 | 19 | 16. A method for assessing information in natural language contents, comprising: receiving an object name as a query term from a user interface by a computer processing system; retrieving an object-specific data set related to the object name from a computer storage system, wherein the object-specific data set includes a plurality of property names and association-strength values, each property name being associated with an association-strength value, wherein the association strength values of the plurality of property names are above a predetermined threshold value, wherein the plurality of property names includes a first property name and a second property name; retrieving, by the computer processing system, a plurality of documents containing text in a natural language; counting a first frequency of the first property name in one of the plurality of documents by the computer processing system; counting a second frequency of the second property name in the in one of the plurality of documents by the computer processing system; calculating a relevance score as a function of the first frequency and the second frequency; ranking the plurality of documents using their respective relevance scores; and returning one or more documents to the user interface based on the ranking of the plurality of documents. | 16. A method for assessing information in natural language contents, comprising: receiving an object name as a query term from a user interface by a computer processing system; retrieving an object-specific data set related to the object name from a computer storage system, wherein the object-specific data set includes a plurality of property names and association-strength values, each property name being associated with an association-strength value, wherein the association strength values of the plurality of property names are above a predetermined threshold value, wherein the plurality of property names includes a first property name and a second property name; retrieving, by the computer processing system, a plurality of documents containing text in a natural language; counting a first frequency of the first property name in one of the plurality of documents by the computer processing system; counting a second frequency of the second property name in the in one of the plurality of documents by the computer processing system; calculating a relevance score as a function of the first frequency and the second frequency; ranking the plurality of documents using their respective relevance scores; and returning one or more documents to the user interface based on the ranking of the plurality of documents. 19. The method of claim 16 , wherein the function depends on the sum of a first multiplication of the first frequency and its corresponding association-strength value and a second multiplication of the second frequency and its corresponding association-strength value. | 0.8479 |
7,899,671 | 9 | 10 | 9. The results postprocessor of claim 8 , wherein the changes to the results list include removing results that have been rejected during a current recognition transaction. | 9. The results postprocessor of claim 8 , wherein the changes to the results list include removing results that have been rejected during a current recognition transaction. 10. The results postprocessor of claim 9 , wherein the processing module is further operative to retrieve user and historical information and to make changes to the results list based on the user and historical information. | 0.5 |
6,078,321 | 2 | 6 | 2. A computer system permitting interoperation between first and second computers irrespective of hardware and/or operating system differences between the first and second computers, wherein: said first computer comprises: a first storage device storing a document written in hypertext markup language (HTML), said HTML document including an applet tag for invoking a Universal Client device and computer readable instructions for generating said Universal Client device; and a first communications device permitting said HTML document and said computer readable instructions for generating said Universal Client device to be downloaded to a second computer; and said second computer comprises: a second storage device storing computer readable instructions for permitting said second computer to utilize a World Wide Web browser providing a JAVA.TM. virtual machine; a second communications device permitting said second computer to receive said HTML document and said computer readable instructions for generating said Universal Client device provided by said first computer; and a processor for initializing and executing said Universal Client device on said second computer using said JAVA.TM. virtual machine to parse and process a script to thereby generate predetermined graphical user interface (GUI) objects and project said GUI objects on said second computer. | 2. A computer system permitting interoperation between first and second computers irrespective of hardware and/or operating system differences between the first and second computers, wherein: said first computer comprises: a first storage device storing a document written in hypertext markup language (HTML), said HTML document including an applet tag for invoking a Universal Client device and computer readable instructions for generating said Universal Client device; and a first communications device permitting said HTML document and said computer readable instructions for generating said Universal Client device to be downloaded to a second computer; and said second computer comprises: a second storage device storing computer readable instructions for permitting said second computer to utilize a World Wide Web browser providing a JAVA.TM. virtual machine; a second communications device permitting said second computer to receive said HTML document and said computer readable instructions for generating said Universal Client device provided by said first computer; and a processor for initializing and executing said Universal Client device on said second computer using said JAVA.TM. virtual machine to parse and process a script to thereby generate predetermined graphical user interface (GUI) objects and project said GUI objects on said second computer. 6. The computer system as recited in claim 2, wherein said Universal Client device running on said second computer selectively modifies and replaces said predetermined GUI objects responsive to an incoming datagram corresponding to changing parameters associated with said first computer. | 0.515152 |
8,479,149 | 1 | 15 | 1. A computer-implemented method, comprising: receiving one or more viewing concepts of a software system; identifying one or more viewing instances comprising one or more concept instances or descendants of the one or more concept instances, the one or more concept instances or descendants of the one or more concept instances associated with at least one of the one or more viewing concepts or one or more sub-concepts of the one or more viewing concepts; and assigning layer indices to the one or more viewing instances based on one or more associated viewing instances relationships for use in generating a visualization of the one or more viewing instances and/or the one or more viewing instances relationships, the visualization generated for rendering on an output device in communication with a computer, wherein at least one of the one or more viewing instances relationships are inbound uses relationships; wherein the assigning layer indices to the one or more viewing instances comprises: a) initializing a current layer index value; b) selecting at least one unindexed viewing instance having no inbound uses relationships associated with at least one other unindexed viewing instance, wherein the selecting the at least one unindexed viewing instance comprises removing a cycle condition if respective of unindexed viewing instances have at least one inbound uses relationship associated with at least one other unindexed viewing instance; and c) assigning the current layer index value to the selected at least one unindexed viewing instance; wherein the removing the cycle condition comprises iteratively selecting at least one viewing instances uses relationship associated with at least one unindexed viewing instance until at least one unindexed viewing instance has no inbound uses associated with at least one other unindexed viewing instance based on viewing instances uses relationships associated with unindexed viewing instances minus the at least one selected viewing instances uses relationship or until viewing uses instances relationships with unindexed viewing instances have been selected at least once. | 1. A computer-implemented method, comprising: receiving one or more viewing concepts of a software system; identifying one or more viewing instances comprising one or more concept instances or descendants of the one or more concept instances, the one or more concept instances or descendants of the one or more concept instances associated with at least one of the one or more viewing concepts or one or more sub-concepts of the one or more viewing concepts; and assigning layer indices to the one or more viewing instances based on one or more associated viewing instances relationships for use in generating a visualization of the one or more viewing instances and/or the one or more viewing instances relationships, the visualization generated for rendering on an output device in communication with a computer, wherein at least one of the one or more viewing instances relationships are inbound uses relationships; wherein the assigning layer indices to the one or more viewing instances comprises: a) initializing a current layer index value; b) selecting at least one unindexed viewing instance having no inbound uses relationships associated with at least one other unindexed viewing instance, wherein the selecting the at least one unindexed viewing instance comprises removing a cycle condition if respective of unindexed viewing instances have at least one inbound uses relationship associated with at least one other unindexed viewing instance; and c) assigning the current layer index value to the selected at least one unindexed viewing instance; wherein the removing the cycle condition comprises iteratively selecting at least one viewing instances uses relationship associated with at least one unindexed viewing instance until at least one unindexed viewing instance has no inbound uses associated with at least one other unindexed viewing instance based on viewing instances uses relationships associated with unindexed viewing instances minus the at least one selected viewing instances uses relationship or until viewing uses instances relationships with unindexed viewing instances have been selected at least once. 15. The computer-implemented method of claim 1 , further comprising dissociating the at least one selected viewing instances uses relationship from the viewing instances related by the at least one selected viewing instances uses relationship if at least one unindexed viewing instance has no inbound uses relationships associated with at least one other unindexed viewing instance based on the viewing instances uses relationships associated with unindexed viewing instances minus the at least one selected viewing instances uses relationship. | 0.500917 |
9,934,331 | 7 | 9 | 7. A system configured to provide query suggestions, the system comprising: one or more hardware processors; and a computer-readable storage medium storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising: detecting access at a data source; collecting non-query data based on the detected access, the non-query data comprising metadata describing identity data, profile data, or contextual information; determining an initial query suggestion for a query of the data source based on the non-query data, the determining comprising: comparing the non-query data to prior query information; determining that at least a portion of the non-query data is associated with a portion of the prior query information; and generating an initial query suggestion based, at least in part, in the portion of the prior query information; returning the initial query suggestion to the client; receiving an indication of action on the initial query suggestion; determining an additional query suggestion for the query for the data source, the query comprises data indicative of at least a portion of a query statement; and returning the additional query suggestion. | 7. A system configured to provide query suggestions, the system comprising: one or more hardware processors; and a computer-readable storage medium storing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform operations comprising: detecting access at a data source; collecting non-query data based on the detected access, the non-query data comprising metadata describing identity data, profile data, or contextual information; determining an initial query suggestion for a query of the data source based on the non-query data, the determining comprising: comparing the non-query data to prior query information; determining that at least a portion of the non-query data is associated with a portion of the prior query information; and generating an initial query suggestion based, at least in part, in the portion of the prior query information; returning the initial query suggestion to the client; receiving an indication of action on the initial query suggestion; determining an additional query suggestion for the query for the data source, the query comprises data indicative of at least a portion of a query statement; and returning the additional query suggestion. 9. The system of claim 7 , wherein the receiving the indication of the action comprises: determining that the indication of the action includes a change in response to providing the query suggestion; and applying the change to the query, wherein the additional query suggestion for the query for the data source is based on the applied change. | 0.5 |
7,586,654 | 1 | 2 | 1. A scanner for generating an electronic representation of a hardcopy document, said scanner comprising: a scanner bed including a flat scanner with a lid; a user interface for inputting material to be added to a scanned document, wherein said user interface comprises a touch screen disposed on said lid of the flat scanner; and a processor for receiving an electronic representation of a hardcopy document from said scanner bed and said material to be added to a scanned document from said user interface; wherein said processor adds said material from said user interface to said electronic representation of the hardcopy document to produce an annotated electronic document; wherein said processor displays an image of the hardcopy document on said touch screen using said electronic representation of the hardcopy document from the scanner bed; and wherein a user selectively adds said material at any point of said displayed image of said hardcopy document and said processor adds that material at a corresponding location within said annotated electronic document. | 1. A scanner for generating an electronic representation of a hardcopy document, said scanner comprising: a scanner bed including a flat scanner with a lid; a user interface for inputting material to be added to a scanned document, wherein said user interface comprises a touch screen disposed on said lid of the flat scanner; and a processor for receiving an electronic representation of a hardcopy document from said scanner bed and said material to be added to a scanned document from said user interface; wherein said processor adds said material from said user interface to said electronic representation of the hardcopy document to produce an annotated electronic document; wherein said processor displays an image of the hardcopy document on said touch screen using said electronic representation of the hardcopy document from the scanner bed; and wherein a user selectively adds said material at any point of said displayed image of said hardcopy document and said processor adds that material at a corresponding location within said annotated electronic document. 2. The scanner of claim 1 , further comprising a connection to a printer for outputting said annotated electronic document for printing. | 0.636364 |
8,775,406 | 28 | 34 | 28. A method of predicting content of a news story with a computing system comprising: a) identifying a first event described in first content published in a knowledge domain including one or more social network domains, news content domains, blog domains and/or message board domains; b) automatically determining a plurality of different alternative predicted states for said first event, based on a comparison of characteristics of said first event to characteristics of prior events of a same type; c) automatically generating queries to said knowledge domain and/or at least one search engine to locate published new content associated with said plurality of different predicted states; d) presenting search results or news stories to a user with the computing system which includes at least some of said new published content when such is identified at step (c); e) generating a set of future sources to be consulted for said new content based on predicted changes in a state of said first event. | 28. A method of predicting content of a news story with a computing system comprising: a) identifying a first event described in first content published in a knowledge domain including one or more social network domains, news content domains, blog domains and/or message board domains; b) automatically determining a plurality of different alternative predicted states for said first event, based on a comparison of characteristics of said first event to characteristics of prior events of a same type; c) automatically generating queries to said knowledge domain and/or at least one search engine to locate published new content associated with said plurality of different predicted states; d) presenting search results or news stories to a user with the computing system which includes at least some of said new published content when such is identified at step (c); e) generating a set of future sources to be consulted for said new content based on predicted changes in a state of said first event. 34. The method of claim 28 wherein said different alternative predicted states for said first event are derived from predicted semantic changes in selected content in said first content. | 0.614108 |
9,665,622 | 4 | 5 | 4. A method as recited in claim 1 , rewriting the input keyword comprises: labeling a respective importance value for each word included in the input keyword; and deleting one or more words whose respective importance values are lower than a preset importance value threshold from the input keyword. | 4. A method as recited in claim 1 , rewriting the input keyword comprises: labeling a respective importance value for each word included in the input keyword; and deleting one or more words whose respective importance values are lower than a preset importance value threshold from the input keyword. 5. A method as recited in claim 4 , wherein the respective importance value for each word included in the input keyword is labeled based on one or more of a respective syntax, grammar, semantics, or statistical characteristic of a respective word. | 0.5 |
6,016,380 | 20 | 27 | 20. A computer system for generating a representation of a video program as sequence of edit events to be used by a digital video editor for editing the video program, the computer system comprising: input means for receiving a video edit decision list in a first syntax for a first machine, wherein the video edit decision list comprises a formatted list of computer instructions for an edit controller for assembling the video program, wherein each instruction defines source material and a destination of an edit event; a format template library providing a plurality of format specifiers wherein each format specifier specifies a syntax of an edit decision list for a different machine, including a first format specifier for the first syntax, selecting means, connected to the input means and the format template library, for selecting the first format specifier in the format template library, and generating means for generating, according to the edit decision list and the first format specifier, the representation of the sequence of edit events corresponding to instructions in the video edit decision list. | 20. A computer system for generating a representation of a video program as sequence of edit events to be used by a digital video editor for editing the video program, the computer system comprising: input means for receiving a video edit decision list in a first syntax for a first machine, wherein the video edit decision list comprises a formatted list of computer instructions for an edit controller for assembling the video program, wherein each instruction defines source material and a destination of an edit event; a format template library providing a plurality of format specifiers wherein each format specifier specifies a syntax of an edit decision list for a different machine, including a first format specifier for the first syntax, selecting means, connected to the input means and the format template library, for selecting the first format specifier in the format template library, and generating means for generating, according to the edit decision list and the first format specifier, the representation of the sequence of edit events corresponding to instructions in the video edit decision list. 27. The system according to claim 20, wherein each of said format specifiers includes control information for the corresponding format. | 0.722222 |
9,158,847 | 6 | 13 | 6. A method of creating a data structure, which is a Cognitive Signature, using a computer having a microprocessor for each step, the method comprising: inputting a network; generating a Globally Unique Identity Designation (GUID); identifying a contraction level of a plurality of contraction levels of the network; generating an ordered list of first vectors in a field T, each first vector corresponding to the contraction level of the network; generating a list of second vectors in a field G, each second vector corresponding to the contraction level of the network; computing a Bloom Filter as a binary vector comprised of values of each of the first vectors in field T and the second vectors in field G based on a first threshold vector corresponding to field T and second threshold vector corresponding to field G; labeling the network with a set of symbols S; generating a Discrete Unlabeled Network Representation Code (DUNRC) and generating a Discrete Colored Network Representation Code (DCNRC); executing contraction tree operator expressions to identify whether the network was contracted by a contraction rule; and generating a pointer to a next Cognitive Signature at an incremented level of contraction. | 6. A method of creating a data structure, which is a Cognitive Signature, using a computer having a microprocessor for each step, the method comprising: inputting a network; generating a Globally Unique Identity Designation (GUID); identifying a contraction level of a plurality of contraction levels of the network; generating an ordered list of first vectors in a field T, each first vector corresponding to the contraction level of the network; generating a list of second vectors in a field G, each second vector corresponding to the contraction level of the network; computing a Bloom Filter as a binary vector comprised of values of each of the first vectors in field T and the second vectors in field G based on a first threshold vector corresponding to field T and second threshold vector corresponding to field G; labeling the network with a set of symbols S; generating a Discrete Unlabeled Network Representation Code (DUNRC) and generating a Discrete Colored Network Representation Code (DCNRC); executing contraction tree operator expressions to identify whether the network was contracted by a contraction rule; and generating a pointer to a next Cognitive Signature at an incremented level of contraction. 13. The method of claim 6 , wherein the step of generating the DUNRC further comprises: computing the DUNRC based on a plurality of codes obtained from an upper triangular portion of a connectivity matrix of the network. | 0.517544 |
7,945,632 | 31 | 40 | 31. The hardware-implemented system of claim 1 , wherein said correlation module configured to correlate the acquired subjective user state data with the acquired objective occurrence data by determining at least one sequential pattern associated with the at least one subjective user state and the at least one objective occurrence comprises: a sequential pattern comparison module configured to compare the one sequential pattern to a second sequential pattern to determine whether the one sequential pattern at least substantially matches the second sequential pattern. | 31. The hardware-implemented system of claim 1 , wherein said correlation module configured to correlate the acquired subjective user state data with the acquired objective occurrence data by determining at least one sequential pattern associated with the at least one subjective user state and the at least one objective occurrence comprises: a sequential pattern comparison module configured to compare the one sequential pattern to a second sequential pattern to determine whether the one sequential pattern at least substantially matches the second sequential pattern. 40. The hardware-implemented system of claim 31 , wherein said sequential pattern comparison module configured to compare the one sequential pattern to a second sequential pattern to determine whether the one sequential pattern at least substantially matches the second sequential pattern comprises: a temporal relationship comparison module configured to compare a first temporal relationship between the one subjective user state and the one objective occurrence associated with the one sequential pattern to a second temporal relationship between a second subjective user state and a second objective occurrence associated with the second sequential pattern. | 0.5 |
9,275,411 | 1 | 2 | 1. A method, comprising: receiving, at a voice action system comprising at least one server computing system, a plurality of electronic voice action bids from a plurality of advertisers that each represent an offer for modifying the voice action system to include a voice action associated with an electronic voice action bid of the plurality of electronic voice action bids, wherein the voice action comprises a triggering phrase and an action; selecting, by the voice action system based on a predetermined criteria, one or more electronic voice action bids from among the plurality of electronic voice action bids; modifying, by the voice action system, data associated with the voice action system to include the voice action for each of the selected one or more electronic voice action bids, wherein the voice action system performs the action associated with the respective voice action responsive to voice input received from a user corresponding to the triggering phrase associated with the respective voice action; and setting, by the voice action system, a parameter in a voice action language model database to increase a likelihood that the voice action system determines that the voice input received from the user corresponds to the triggering phrase of the selected one or more electronic voice action bids, wherein at least one voice action bid comprises an offer for modifying the voice action system to include a voice action grammar associated with the voice action bid, wherein the voice action grammar comprises a plurality of voice actions, and wherein modifying the voice action system comprises, for each of the at least one voice action bids having a voice action grammar associated therewith that is selected, modifying the voice action system to include the plurality of voice actions associated with the voice action grammar. | 1. A method, comprising: receiving, at a voice action system comprising at least one server computing system, a plurality of electronic voice action bids from a plurality of advertisers that each represent an offer for modifying the voice action system to include a voice action associated with an electronic voice action bid of the plurality of electronic voice action bids, wherein the voice action comprises a triggering phrase and an action; selecting, by the voice action system based on a predetermined criteria, one or more electronic voice action bids from among the plurality of electronic voice action bids; modifying, by the voice action system, data associated with the voice action system to include the voice action for each of the selected one or more electronic voice action bids, wherein the voice action system performs the action associated with the respective voice action responsive to voice input received from a user corresponding to the triggering phrase associated with the respective voice action; and setting, by the voice action system, a parameter in a voice action language model database to increase a likelihood that the voice action system determines that the voice input received from the user corresponds to the triggering phrase of the selected one or more electronic voice action bids, wherein at least one voice action bid comprises an offer for modifying the voice action system to include a voice action grammar associated with the voice action bid, wherein the voice action grammar comprises a plurality of voice actions, and wherein modifying the voice action system comprises, for each of the at least one voice action bids having a voice action grammar associated therewith that is selected, modifying the voice action system to include the plurality of voice actions associated with the voice action grammar. 2. The method of claim 1 , wherein the voice action system comprises the voice action language model database including words that the voice action system is configured to recognize as being associated with the triggering phrases of the selected one or more electronic voice action bids, and wherein the method further comprises, for each of the words of the triggering phrases for the selected voice action bids: determining if a word is included in the voice action language model database; and adding the word to the voice action language model database when the word is not already included in the voice action language model database. | 0.606042 |
8,285,702 | 1 | 9 | 1. A computer-implemented method for improving findability of a web-site's content, the method comprising: receiving a document set representing said web-site's web page(s); for each web-page, performing a meta-data extraction to obtain one or more features of each web-page related to findability of each web-page; determining one or more important terms associated with said web-site based upon said features; for each important term found for said web-site, implementing, via a search engine, a search query using said term and retrieving the returned results of at least one web page having said term; identifying, based on the query results, the place of each web-page of said web-site in the rank of the returned results; and providing at least one recommendation for improving said web site based upon said results ranking; wherein said at least one recommendation is based on a ranking, of at least one web-page in a domain not belonging to said web-site, that is ranked higher than all of said web-site's web page(s) for at least one important term; and wherein said at least one recommendation is directed to improving said findability of said web-site's content. | 1. A computer-implemented method for improving findability of a web-site's content, the method comprising: receiving a document set representing said web-site's web page(s); for each web-page, performing a meta-data extraction to obtain one or more features of each web-page related to findability of each web-page; determining one or more important terms associated with said web-site based upon said features; for each important term found for said web-site, implementing, via a search engine, a search query using said term and retrieving the returned results of at least one web page having said term; identifying, based on the query results, the place of each web-page of said web-site in the rank of the returned results; and providing at least one recommendation for improving said web site based upon said results ranking; wherein said at least one recommendation is based on a ranking, of at least one web-page in a domain not belonging to said web-site, that is ranked higher than all of said web-site's web page(s) for at least one important term; and wherein said at least one recommendation is directed to improving said findability of said web-site's content. 9. The computer-implemented method as claimed in claim 1 , wherein said important terms determination comprises: computing, for each important term associated with said web-site, a distribution of said important term over said web-site, said computing comprising: determining a total number of occurrences of said important term associated with said web-site, and determining the number of occurrences of said important term associated with each web- page. | 0.5 |
8,306,808 | 13 | 14 | 13. A computer program product comprising a computer-readable storage device including instructions that, when executed, cause a computer system to perform operations comprising: accessing a string of characters that are associated with a computing device; identifying a plurality of candidate languages for segmenting the string of characters, wherein the plurality of candidate languages are identified based on one or more language indicators associated with the string of characters or the computing device; determining weights for the plurality of candidate languages based on the one or more language indicators, wherein each of the weights indicates a probability that a corresponding candidate language from the plurality of candidate languages is an appropriate language to use for interpreting the string of characters based on the string of characters or the computing device; determining one or more segmented results from the string of characters for each of the plurality of candidate languages, wherein a segmented result comprises a plurality of tokens that are created by inserting one or more breaks into the string of characters; identifying, from the plurality of candidate languages, an operable language for the string of characters based, at least in part, on a comparison of weighted frequencies associated with the candidate languages, wherein each of the weighted frequencies comprises a frequency with which the segmented results occur in a corpus associated with a corresponding candidate language, the frequency being weighted according to a corresponding weight from the determined weights that is associated with the corresponding candidate language; and providing information that identifies the operable language. | 13. A computer program product comprising a computer-readable storage device including instructions that, when executed, cause a computer system to perform operations comprising: accessing a string of characters that are associated with a computing device; identifying a plurality of candidate languages for segmenting the string of characters, wherein the plurality of candidate languages are identified based on one or more language indicators associated with the string of characters or the computing device; determining weights for the plurality of candidate languages based on the one or more language indicators, wherein each of the weights indicates a probability that a corresponding candidate language from the plurality of candidate languages is an appropriate language to use for interpreting the string of characters based on the string of characters or the computing device; determining one or more segmented results from the string of characters for each of the plurality of candidate languages, wherein a segmented result comprises a plurality of tokens that are created by inserting one or more breaks into the string of characters; identifying, from the plurality of candidate languages, an operable language for the string of characters based, at least in part, on a comparison of weighted frequencies associated with the candidate languages, wherein each of the weighted frequencies comprises a frequency with which the segmented results occur in a corpus associated with a corresponding candidate language, the frequency being weighted according to a corresponding weight from the determined weights that is associated with the corresponding candidate language; and providing information that identifies the operable language. 14. The computer program product of claim 13 , wherein the string of characters is received as part of a request from the computing device, and wherein the information is provided for further processing of the string of characters in association with the received request. | 0.823377 |
7,624,338 | 12 | 13 | 12. A machine-readable storage medium, with instruction which when processed, result in a machine: defining a document model for generation of documents, wherein the document model includes: a header model including a set of header methods to provide interaction capabilities to other portions of a system, one or more item models, including a set of item methods to provide interaction capabilities to other portions of the system, wherein the header model and the one or more item models each include an association with one or more component models, and wherein each component model includes: a set of component methods to provide interaction capabilities to other portions of the system, and component specific logic accessible through the component methods, providing a first map within the header model between the set of header methods and the set of item methods, providing a second map within the item model between the set of item methods and the set of component methods, and providing a link between the set of component methods and the component specific logic. | 12. A machine-readable storage medium, with instruction which when processed, result in a machine: defining a document model for generation of documents, wherein the document model includes: a header model including a set of header methods to provide interaction capabilities to other portions of a system, one or more item models, including a set of item methods to provide interaction capabilities to other portions of the system, wherein the header model and the one or more item models each include an association with one or more component models, and wherein each component model includes: a set of component methods to provide interaction capabilities to other portions of the system, and component specific logic accessible through the component methods, providing a first map within the header model between the set of header methods and the set of item methods, providing a second map within the item model between the set of item methods and the set of component methods, and providing a link between the set of component methods and the component specific logic. 13. The machine-readable medium of claim 12 , wherein the instructions when processed, further result in the machine: storing the document model. | 0.624352 |
7,657,006 | 10 | 16 | 10. A computer readable medium having a computer program for translating a message, the program having instructions for performing: generating an electronic message in an understood language of an originating party; receiving instructions to translate contents of the electronic message to another language; prompting a receiving party to select the another language; converting the electronic message to the another language in accordance with the instructions; and delivering the converted electronic message to the receiving party. | 10. A computer readable medium having a computer program for translating a message, the program having instructions for performing: generating an electronic message in an understood language of an originating party; receiving instructions to translate contents of the electronic message to another language; prompting a receiving party to select the another language; converting the electronic message to the another language in accordance with the instructions; and delivering the converted electronic message to the receiving party. 16. The computer readable medium of claim 10 , wherein instructions are received from the originating party. | 0.823529 |
8,358,290 | 38 | 42 | 38. The method according to claim 26 , wherein said at least one other page from said first document or from the second document comprises a plurality of thumbnails displayed with the current page. | 38. The method according to claim 26 , wherein said at least one other page from said first document or from the second document comprises a plurality of thumbnails displayed with the current page. 42. The method according to claim 38 , wherein the proportional distance criteria includes displaying the plurality of thumbnails at different distances from the current page according to a duration of time displayed. | 0.530303 |
10,061,985 | 1 | 3 | 1. A method comprising: by one or more computing devices, accessing a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; by one or more computing devices, accessing a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; by one or more computing devices, accessing a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; by one or more computing devices, determining a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and by one or more computing devices, determining a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object. | 1. A method comprising: by one or more computing devices, accessing a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; by one or more computing devices, accessing a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; by one or more computing devices, accessing a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; by one or more computing devices, determining a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and by one or more computing devices, determining a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object. 3. The method of claim 1 , further comprising: by one or more computing devices, receiving a request to access the video-content object from a client device of a user of the social-networking system; by one or more computing devices, generating a recommendation for a second video-content object based on the feature vector of the video-content object and a user profile for the user; and by one or more computing devices, sending, to the client device, the recommendation. | 0.744324 |
9,361,400 | 1 | 2 | 1. A non-transitory computer-readable medium having stored therein a set of instructions, which when executed by a computer, cause the computer to perform a method of initializing an extensible markup language (XML) database, the method comprising: dynamically generating an empty structure for the XML database and code to access and handle objects in the XML database, the dynamically generated XML database structure and code corresponding to an XML file, the dynamically generating comprising: parsing the XML file to extract a plurality of records therefrom, the records arranged in a hierarchical form; creating, for each record extracted from the XML file, a corresponding class that defines a part of the empty structure for the XML database, each class having associated therewith one or more attributes of the each record; and creating a plurality of handling methods for each of one or more attributes associated with each object within a class, the handling methods defining how data associated with the attributes can be accessed in the database. | 1. A non-transitory computer-readable medium having stored therein a set of instructions, which when executed by a computer, cause the computer to perform a method of initializing an extensible markup language (XML) database, the method comprising: dynamically generating an empty structure for the XML database and code to access and handle objects in the XML database, the dynamically generated XML database structure and code corresponding to an XML file, the dynamically generating comprising: parsing the XML file to extract a plurality of records therefrom, the records arranged in a hierarchical form; creating, for each record extracted from the XML file, a corresponding class that defines a part of the empty structure for the XML database, each class having associated therewith one or more attributes of the each record; and creating a plurality of handling methods for each of one or more attributes associated with each object within a class, the handling methods defining how data associated with the attributes can be accessed in the database. 2. The non-transitory computer-readable medium of claim 1 , wherein the method further comprises: generating an XML schema representing the hierarchical relationship among the records. | 0.65283 |
9,503,582 | 9 | 13 | 9. The method of claim 8 , wherein the message is an e-mail message, another Short Message Service (SMS) message or an instant message. | 9. The method of claim 8 , wherein the message is an e-mail message, another Short Message Service (SMS) message or an instant message. 13. The method of claim 9 , wherein the voicemail message conforms to G.711 or G.722. | 0.876093 |
7,523,434 | 1 | 4 | 1. A method for implementing a symbolic specification using dynamically configurable arithmetic unit, the method comprising: receiving a plurality of mathematical expressions comprising a plurality of input variables; generating the symbolic specification from the plurality of mathematical expressions, wherein the symbolic specification is devoid of hardware description; assigning the plurality of input variables to input ports of the dynamically configurable arithmetic unit, wherein the dynamically reconfigurable arithmetic unit comprises a fixed number of components and a fixed number of input ports, wherein at least two input ports have different bit widths and at least two of the plurality of input variables have different binary point; determining from the symbolic specification a list of operations to be performed by the dynamically configurable arithmetic unit in order to sequentially execute the plurality of mathematical expressions; and generating an interface to the dynamically configurable arithmetic unit based on at least in part the assigning step and the list of operations, wherein the interface performs an alignment of selected ones of plurality of input variables for each mathematical expression to be sequentially executed, wherein at least two consecutive alignments of the plurality of input variables are performed differently, and wherein each alignment is performed according to the binary point of the input variables and which input ports are to be multiplied or added together for the mathematical expression to be executed, wherein the generating the interface comprises creating one or more multiplexers; and wherein one or more multiplexers are formed in programmable logic in an integrated circuit device. | 1. A method for implementing a symbolic specification using dynamically configurable arithmetic unit, the method comprising: receiving a plurality of mathematical expressions comprising a plurality of input variables; generating the symbolic specification from the plurality of mathematical expressions, wherein the symbolic specification is devoid of hardware description; assigning the plurality of input variables to input ports of the dynamically configurable arithmetic unit, wherein the dynamically reconfigurable arithmetic unit comprises a fixed number of components and a fixed number of input ports, wherein at least two input ports have different bit widths and at least two of the plurality of input variables have different binary point; determining from the symbolic specification a list of operations to be performed by the dynamically configurable arithmetic unit in order to sequentially execute the plurality of mathematical expressions; and generating an interface to the dynamically configurable arithmetic unit based on at least in part the assigning step and the list of operations, wherein the interface performs an alignment of selected ones of plurality of input variables for each mathematical expression to be sequentially executed, wherein at least two consecutive alignments of the plurality of input variables are performed differently, and wherein each alignment is performed according to the binary point of the input variables and which input ports are to be multiplied or added together for the mathematical expression to be executed, wherein the generating the interface comprises creating one or more multiplexers; and wherein one or more multiplexers are formed in programmable logic in an integrated circuit device. 4. The method of claim 1 further comprising aligning the plurality of input variables by adding one or more registers coupled to the dynamically configurable arithmetic unit. | 0.868182 |
9,740,922 | 70 | 71 | 70. The system of claim 69 , wherein the tracking component automatically adapts to changes in the object poses. | 70. The system of claim 69 , wherein the tracking component automatically adapts to changes in the object poses. 71. The system of claim 70 , wherein the tracking component generates a model of a pose and a physical size of the at least one object. | 0.648438 |
8,184,022 | 1 | 3 | 1. A method of enabling input on a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a linguistic source stored on a memory, the input apparatus having a number of keys, including one or more keys each having at least one non-diacritical version of a linguistic element assigned thereto and at least one diacritical version of the linguistic element assigned thereto, the method comprising: detecting selection of one of the keys; based at least in part on the detection of the key selection, determining whether to output (i) a non-diacritical version of a linguistic element assigned to the selected key or (ii) a diacritical version of the linguistic element assigned to the selected key in response to the selection, the determination comprising: determining whether the selection corresponds to a first alphanumeric input for the enabled input, based upon a determination that the selection corresponds to the first alphanumeric input for the enabled input, determining to output the non-diacritical version of the linguistic element assigned to the selected key, and based upon a determination that there have been previous alphanumeric inputs for the enabled input, determining whether to output the non-diacritical version or the diacritical version of the linguistic element based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus. | 1. A method of enabling input on a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a linguistic source stored on a memory, the input apparatus having a number of keys, including one or more keys each having at least one non-diacritical version of a linguistic element assigned thereto and at least one diacritical version of the linguistic element assigned thereto, the method comprising: detecting selection of one of the keys; based at least in part on the detection of the key selection, determining whether to output (i) a non-diacritical version of a linguistic element assigned to the selected key or (ii) a diacritical version of the linguistic element assigned to the selected key in response to the selection, the determination comprising: determining whether the selection corresponds to a first alphanumeric input for the enabled input, based upon a determination that the selection corresponds to the first alphanumeric input for the enabled input, determining to output the non-diacritical version of the linguistic element assigned to the selected key, and based upon a determination that there have been previous alphanumeric inputs for the enabled input, determining whether to output the non-diacritical version or the diacritical version of the linguistic element based on whether the previous alphanumeric inputs satisfy a predetermined condition; and outputting the determined output using the output apparatus. 3. The method according to claim 1 , further comprising detecting an operative language of the handheld electronic device, wherein determining whether to output the non-diacritical version or the diacritical version is at least in part based on the detected operative language. | 0.5 |
8,768,950 | 2 | 4 | 2. The non-transitory computer readable storage medium according to claim 1 , wherein the input program further causes the computer to at least: receive an operation which the user performs for selecting a second option word, and obtain, from the at least one first option word obtained, at least one first option word, as a respective at least one second option word, and, when the operation of selecting a second option word from the at least one obtained second option word has been received, set the second option word as a fixed word to be output. | 2. The non-transitory computer readable storage medium according to claim 1 , wherein the input program further causes the computer to at least: receive an operation which the user performs for selecting a second option word, and obtain, from the at least one first option word obtained, at least one first option word, as a respective at least one second option word, and, when the operation of selecting a second option word from the at least one obtained second option word has been received, set the second option word as a fixed word to be output. 4. The non-transitory computer readable storage medium according to claim 2 , wherein a fixed word determination process is performed for determining the fixed word, only when the operation for selecting a second option word has been received. | 0.5 |
8,838,457 | 1 | 2 | 1. A method of allowing a user to control a mobile communication facility comprising: receiving speech and information currently displayed in a mobile communication facility from a user using a mobile communication facility resident capture facility, wherein the speech presented by the user includes a command and a subject and wherein the speech and information was transmitted from the mobile communication facility to a speech recognition facility; utilizing, by the speech recognition facility, (i) contextual information not provided in the speech and (ii) at least one statistical language model to recognize the command and a subject from the speech presented by the user, wherein the contextual information includes usage history of the mobile communication facility, information from a user's favorites list, information about the user's address book or contact list, email content, or information currently displayed in by the mobile communication facility; determining, by the speech recognition facility, at least one application to invoke on the mobile communication facility to perform an operation on the mobile communication facility based on the contextual information, the command, and the subject of the speech, wherein the operation includes an action defined by the command using parameters based on the subject; and causing the mobile communication facility to automatically perform the operation on the mobile communication facility using the determined at least one application. | 1. A method of allowing a user to control a mobile communication facility comprising: receiving speech and information currently displayed in a mobile communication facility from a user using a mobile communication facility resident capture facility, wherein the speech presented by the user includes a command and a subject and wherein the speech and information was transmitted from the mobile communication facility to a speech recognition facility; utilizing, by the speech recognition facility, (i) contextual information not provided in the speech and (ii) at least one statistical language model to recognize the command and a subject from the speech presented by the user, wherein the contextual information includes usage history of the mobile communication facility, information from a user's favorites list, information about the user's address book or contact list, email content, or information currently displayed in by the mobile communication facility; determining, by the speech recognition facility, at least one application to invoke on the mobile communication facility to perform an operation on the mobile communication facility based on the contextual information, the command, and the subject of the speech, wherein the operation includes an action defined by the command using parameters based on the subject; and causing the mobile communication facility to automatically perform the operation on the mobile communication facility using the determined at least one application. 2. The method of claim 1 further comprising deciding whether the at least one statistical language model provides insufficient recognition output and selecting at least one other language model apart from the set of language models based on speech recognized by the selected at least one statistical language model. | 0.5 |
7,630,993 | 1 | 11 | 1. A method, with an information processing system, for generating a plurality of candidate database schemas including relational and mark-up language elements, the method comprising: receiving an information model comprising a plurality of entities and at least one relationship defined there between, wherein the information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic; analyzing the information model that has been annotated; associating a score, in response to the analyzing, with each entity based at least in part on attributes associated with each entity; classifying, in response to associating a score, each entity as one of a relational element and a mark-up language element; partitioning, in response to the classifying, the information model that has been annotated into a plurality of relational element mappings and a plurality of mark-up language element mappings; and generating, in response to the partitioning, a plurality of database schemas associated with the information model that has been annotated. | 1. A method, with an information processing system, for generating a plurality of candidate database schemas including relational and mark-up language elements, the method comprising: receiving an information model comprising a plurality of entities and at least one relationship defined there between, wherein the information model has been annotated with at least one semantic characteristic, operational characteristic, and evolutional characteristic; analyzing the information model that has been annotated; associating a score, in response to the analyzing, with each entity based at least in part on attributes associated with each entity; classifying, in response to associating a score, each entity as one of a relational element and a mark-up language element; partitioning, in response to the classifying, the information model that has been annotated into a plurality of relational element mappings and a plurality of mark-up language element mappings; and generating, in response to the partitioning, a plurality of database schemas associated with the information model that has been annotated. 11. The method of claim 1 , wherein information model includes at least one model element that has been annotated with constraints on a granularity for reuse associated with the model element. | 0.818868 |
9,454,602 | 18 | 20 | 18. The non-transitory computer-readable medium of claim 17 , where the one or more instructions further cause the one or more processors to: calculate a requirement similarity score between a pair of requirements included in the set of requirements; determine that the requirement similarity score, for the pair of requirements, satisfies a second threshold; merge the pair of requirements to form a requirement cluster based on determining that the requirement similarity score, for the pair of requirements, satisfying the second threshold; and provide information that identifies the requirement cluster. | 18. The non-transitory computer-readable medium of claim 17 , where the one or more instructions further cause the one or more processors to: calculate a requirement similarity score between a pair of requirements included in the set of requirements; determine that the requirement similarity score, for the pair of requirements, satisfies a second threshold; merge the pair of requirements to form a requirement cluster based on determining that the requirement similarity score, for the pair of requirements, satisfying the second threshold; and provide information that identifies the requirement cluster. 20. The non-transitory computer-readable medium of claim 18 , where the one or more instructions further cause the one or more processors to: calculate an average similarity score between terms included in the term cluster and requirements included in the requirement cluster; determine that the average similarity score satisfies a third threshold; and provide an indication that the term cluster and the requirement cluster are related based on that the average similarity score satisfying the third threshold. | 0.509579 |
7,770,158 | 11 | 12 | 11. An apparatus comprising: means for providing a first class library comprising a first plurality of classes of a first language; means for providing a second class library comprising a second plurality of classes of the first language each containing one or more of the first plurality of classes of the first language; means for providing a third class library comprising a first plurality of classes of a second language; means for providing a fourth class library comprising a second plurality of classes of the second language each containing one or more of the first plurality of classes of the second language; means for receiving source code of the first language defining a third plurality of classes of the first language, one or more calls to one or more of the first plurality of classes of the first language, and one or more calls to one or more of the second plurality of classes of the first language; means for translating the third plurality of classes of the first language into a third plurality of classes of the second language; means for translating the calls to the first plurality of classes of the first language into calls to the third class library without modifying the calls to the second plurality of classes of the first language; and means for generating bytecode of the first language based on the source code of the first language, the second class library, and the first class library; and wherein the third plurality of classes of the first language are translated into the third plurality of classes of the second language based on the bytecode of the first language, wherein the source code of the first language relies upon classes of the first class library, wherein the source code of the second language relies upon classes of the third class library, wherein the second plurality of classes of the first language normalize the interfaces of the classes of the first class library, and wherein the second plurality of classes of the second language normalize the interfaces of the classes of the third class library, wherein the fourth class library is such that classes of the fourth class library have the same method signatures as corresponding classes in the second class library, wherein the translation of source code of the second language into source code of the first language does not require the translation of the fourth class library, but instead calls to a class of the fourth class library become calls to a corresponding class in the second class library with the same method signatures, and wherein the means run on at least one processor. | 11. An apparatus comprising: means for providing a first class library comprising a first plurality of classes of a first language; means for providing a second class library comprising a second plurality of classes of the first language each containing one or more of the first plurality of classes of the first language; means for providing a third class library comprising a first plurality of classes of a second language; means for providing a fourth class library comprising a second plurality of classes of the second language each containing one or more of the first plurality of classes of the second language; means for receiving source code of the first language defining a third plurality of classes of the first language, one or more calls to one or more of the first plurality of classes of the first language, and one or more calls to one or more of the second plurality of classes of the first language; means for translating the third plurality of classes of the first language into a third plurality of classes of the second language; means for translating the calls to the first plurality of classes of the first language into calls to the third class library without modifying the calls to the second plurality of classes of the first language; and means for generating bytecode of the first language based on the source code of the first language, the second class library, and the first class library; and wherein the third plurality of classes of the first language are translated into the third plurality of classes of the second language based on the bytecode of the first language, wherein the source code of the first language relies upon classes of the first class library, wherein the source code of the second language relies upon classes of the third class library, wherein the second plurality of classes of the first language normalize the interfaces of the classes of the first class library, and wherein the second plurality of classes of the second language normalize the interfaces of the classes of the third class library, wherein the fourth class library is such that classes of the fourth class library have the same method signatures as corresponding classes in the second class library, wherein the translation of source code of the second language into source code of the first language does not require the translation of the fourth class library, but instead calls to a class of the fourth class library become calls to a corresponding class in the second class library with the same method signatures, and wherein the means run on at least one processor. 12. The apparatus of claim 11 , wherein all of the classes of the first class library have different method signatures from all of the classes of the third class library. | 0.5 |
9,734,845 | 1 | 3 | 1. A system comprising: a microphone array configured to produce microphone audio signals; an audio beamformer configured to process the microphone audio signals to produce directional audio signals, wherein a first directional audio signal of the directional audio signals corresponds to a first direction with respect to the microphone array and wherein a second directional audio signal of the directional audio signals corresponds to a second direction with respect to the microphone array, wherein the first directional audio signal and the second directional audio signal emphasize sound from the first direction and the second direction, respectively; a speech activity detector configured to analyze one or more frequency characteristics of the first directional audio signal and the second directional audio signal to determine a first level of speech presence and a second level of speech presence occurring in the first direction and the second direction, respectively, over time; a source detector configured to analyze the first level of speech presence and the second level of speech presence occurring over a past time period to determine that an electronic source of sound is located in the first direction or the second direction; and an expression detector configured to perform actions comprising: identifying the first direction where a first occurring level of speech presence is a highest level of speech presence; determining that the first direction corresponds to a direction in which the electronic source of sound is located; identifying the second direction where a second occurring level of speech presence is a second highest level of speech presence; analyzing the first directional audio signal corresponding to the first direction to produce a first score indicating a first likelihood that a trigger expression is represented in the first directional audio signal; analyzing the second directional audio signal corresponding to the second direction to produce a second score indicating a second likelihood that the trigger expression is represented in the second directional audio signal; comparing the first score to a first threshold; comparing the second score to a second threshold, wherein the second threshold is less than the first threshold; determining that (i) the first score is greater than the first threshold or (ii) the second score is greater than the second threshold; concluding that the trigger expression has been uttered; and performing speech recognition on subsequent speech, based at least in part on the trigger expression. | 1. A system comprising: a microphone array configured to produce microphone audio signals; an audio beamformer configured to process the microphone audio signals to produce directional audio signals, wherein a first directional audio signal of the directional audio signals corresponds to a first direction with respect to the microphone array and wherein a second directional audio signal of the directional audio signals corresponds to a second direction with respect to the microphone array, wherein the first directional audio signal and the second directional audio signal emphasize sound from the first direction and the second direction, respectively; a speech activity detector configured to analyze one or more frequency characteristics of the first directional audio signal and the second directional audio signal to determine a first level of speech presence and a second level of speech presence occurring in the first direction and the second direction, respectively, over time; a source detector configured to analyze the first level of speech presence and the second level of speech presence occurring over a past time period to determine that an electronic source of sound is located in the first direction or the second direction; and an expression detector configured to perform actions comprising: identifying the first direction where a first occurring level of speech presence is a highest level of speech presence; determining that the first direction corresponds to a direction in which the electronic source of sound is located; identifying the second direction where a second occurring level of speech presence is a second highest level of speech presence; analyzing the first directional audio signal corresponding to the first direction to produce a first score indicating a first likelihood that a trigger expression is represented in the first directional audio signal; analyzing the second directional audio signal corresponding to the second direction to produce a second score indicating a second likelihood that the trigger expression is represented in the second directional audio signal; comparing the first score to a first threshold; comparing the second score to a second threshold, wherein the second threshold is less than the first threshold; determining that (i) the first score is greater than the first threshold or (ii) the second score is greater than the second threshold; concluding that the trigger expression has been uttered; and performing speech recognition on subsequent speech, based at least in part on the trigger expression. 3. The system of claim 1 , wherein the source detector is further configured to determine that the electronic source of sound is located in the first direction by determining that the first level of speech presence corresponding to the first direction has exceeded a level threshold for at least a threshold amount of time during the past time period. | 0.653846 |
9,436,755 | 1 | 5 | 1. A method performed by one or more processors based on instructions stored in memory, comprising: identifying, by one or more of the processors based on the instructions stored in the memory, a plurality of messages from one or more databases; determining, by one or more of the processors based on the instructions stored in the memory, a plurality of interrogative sentences from the messages; determining, by one or more of the processors based on the instructions stored in the memory, starting n-grams from the interrogative sentences; determining, by one or more of the processors based on the instructions stored in the memory, a group of task indications, wherein each of the task indications of the group is based on a set of one or more of the starting n-grams, and wherein determining to include a given task indication of the task indications in the group is based on a count of the starting n-grams that conform to the given task indication; providing, by one or more of the processors based on the instructions stored in the memory, the group of the task indications; receiving, by one or more of the processors based on the instructions stored in the memory and in response to providing the group of the task indications, one or more task association measures for each of the task indications of the group, wherein a given task association measure for a given task indication is indicative of likelihood that the given task indication is associated with a task request; determining, by one or more of the processors based on the instructions stored in the memory, a task association score for each of the task indications of the group, wherein the task association score for the given task indication is based on the one or more task association measures received for the given task indication; and storing, by one or more of the processors based on the instructions stored in the memory, the task association score for each of a plurality of the task indications of the group. | 1. A method performed by one or more processors based on instructions stored in memory, comprising: identifying, by one or more of the processors based on the instructions stored in the memory, a plurality of messages from one or more databases; determining, by one or more of the processors based on the instructions stored in the memory, a plurality of interrogative sentences from the messages; determining, by one or more of the processors based on the instructions stored in the memory, starting n-grams from the interrogative sentences; determining, by one or more of the processors based on the instructions stored in the memory, a group of task indications, wherein each of the task indications of the group is based on a set of one or more of the starting n-grams, and wherein determining to include a given task indication of the task indications in the group is based on a count of the starting n-grams that conform to the given task indication; providing, by one or more of the processors based on the instructions stored in the memory, the group of the task indications; receiving, by one or more of the processors based on the instructions stored in the memory and in response to providing the group of the task indications, one or more task association measures for each of the task indications of the group, wherein a given task association measure for a given task indication is indicative of likelihood that the given task indication is associated with a task request; determining, by one or more of the processors based on the instructions stored in the memory, a task association score for each of the task indications of the group, wherein the task association score for the given task indication is based on the one or more task association measures received for the given task indication; and storing, by one or more of the processors based on the instructions stored in the memory, the task association score for each of a plurality of the task indications of the group. 5. The method of claim 1 , wherein determining the plurality of interrogative sentences includes determining the interrogative sentences based on at least one n-gram of the interrogative sentences, wherein the at least one n-gram is indicative of an interrogative sentence. | 0.662963 |
7,650,272 | 49 | 60 | 49. A computer program product for automatically evaluating Bayesian network models for decision support, the computer program product comprising means, encoded in a computer-readable medium for: receiving a Bayesian Network (BN) model including evidence nodes and conclusion nodes, where the conclusion nodes are linked with the evidence nodes by causal dependency links, and where the evidence nodes have evidence states and the conclusion nodes have conclusion states; setting the states of the conclusion nodes to desired conclusion states and determining, by propagating down the causal dependency links, a corresponding probability of occurrence of evidence states of the evidence nodes and producing, from the probability of occurrence, a plurality of samples of most likely states of the evidence nodes; setting the states of the evidence nodes to states corresponding to the plurality of samples of the evidence states, and propagating the evidence states back up the causal dependency links to the conclusion nodes, to obtain a plurality of probabilities of the resulting states of the conclusion nodes; and outputting a representation of the plurality of the probabilities of the resulting states of the conclusion nodes. | 49. A computer program product for automatically evaluating Bayesian network models for decision support, the computer program product comprising means, encoded in a computer-readable medium for: receiving a Bayesian Network (BN) model including evidence nodes and conclusion nodes, where the conclusion nodes are linked with the evidence nodes by causal dependency links, and where the evidence nodes have evidence states and the conclusion nodes have conclusion states; setting the states of the conclusion nodes to desired conclusion states and determining, by propagating down the causal dependency links, a corresponding probability of occurrence of evidence states of the evidence nodes and producing, from the probability of occurrence, a plurality of samples of most likely states of the evidence nodes; setting the states of the evidence nodes to states corresponding to the plurality of samples of the evidence states, and propagating the evidence states back up the causal dependency links to the conclusion nodes, to obtain a plurality of probabilities of the resulting states of the conclusion nodes; and outputting a representation of the plurality of the probabilities of the resulting states of the conclusion nodes. 60. A computer program product for automatically evaluating Bayesian network models for decision support as set forth in claim 49 , wherein the outputted representation is a graphical representation. | 0.786022 |
7,870,386 | 13 | 15 | 13. A data processing system comprising a computer readable memory unit, said memory unit containing computer readable program code stored therein, said program code configured to be executed in the data processing system to implement a method for selective decryption within an encrypted document, said method comprising: detecting an encrypted portion of a document, said encrypted portion having been selected and marked for decryption, said encrypted portion being an encryption of a text portion of the document, said text portion comprising a known character string that had been added to the text portion prior to the text portion being encrypted; receiving a selection of a valid key configured to decrypt the encrypted portion; ascertaining that an attempt to convert the encrypted portion into a decrypted portion of the document by decrypting the encrypted portion using the valid key was successful, said ascertaining comprising determining that the decrypted portion includes the known character string; in response to said ascertaining, removing the known character string from the decrypted portion; after said removing the known character string, displaying the decrypted portion. | 13. A data processing system comprising a computer readable memory unit, said memory unit containing computer readable program code stored therein, said program code configured to be executed in the data processing system to implement a method for selective decryption within an encrypted document, said method comprising: detecting an encrypted portion of a document, said encrypted portion having been selected and marked for decryption, said encrypted portion being an encryption of a text portion of the document, said text portion comprising a known character string that had been added to the text portion prior to the text portion being encrypted; receiving a selection of a valid key configured to decrypt the encrypted portion; ascertaining that an attempt to convert the encrypted portion into a decrypted portion of the document by decrypting the encrypted portion using the valid key was successful, said ascertaining comprising determining that the decrypted portion includes the known character string; in response to said ascertaining, removing the known character string from the decrypted portion; after said removing the known character string, displaying the decrypted portion. 15. The system of claim 13 , wherein the document comprises multiple copies of the encrypted portion, wherein each copy of the multiple copies is encrypted with a different encryption key, wherein said decrypting the encrypted portion comprises permanently decrypting the encrypted portion resulting in the decrypted portion being permitted to be edited, and wherein the method further comprises: in response to said ascertaining, removing from the document each copy of the multiple copies of the encrypted portion such that only plain text of the decrypted portion is retained in the document. | 0.5 |
6,016,499 | 47 | 50 | 47. The system of claim 28, wherein the directory services repository component includes an effective class, the relational database language statement identifies a table, and the drive and API together map the effective class to the table. | 47. The system of claim 28, wherein the directory services repository component includes an effective class, the relational database language statement identifies a table, and the drive and API together map the effective class to the table. 50. The system of claim 47, wherein the directory services repository component includes an object having a context, the relational database language statement identifies a subset restriction, and the driver and the API together map the context to the subset restriction. | 0.552805 |
9,659,059 | 1 | 5 | 1. A system for matching large sets of words, the system comprising: one or more processors; and a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to: store a plurality of word phrases in a phrase-based data structure; store each word in the phrase-based data structure as a corresponding keyword in a keyword-based data structure, wherein each corresponding keyword is associated with corresponding usage attributes identifying use of a corresponding word in a corresponding word phrase in the phrase-based data structure; store, for each word in the phrase-based data structure, any corresponding preceding words associated with a corresponding keyword, and a mapping from any corresponding preceding words to a corresponding word phrase; determine whether a word from an inputted word string matches any keyword in the keyword-based data structure; determine whether any corresponding preceding words associated with any matching keyword comprises a preceding word which precedes the matching word in the word string in response to a determination that the word in the word string matches any keyword in the keyword-based data structure; update corresponding match attributes in a match-based data structure in response to a determination that any corresponding preceding words associated with any matching keyword comprises the preceding word which precedes the matching word in the word string, wherein the corresponding match attributes indicate use of the matching word in the word string and use of the matching word in a corresponding word phrase in the phrase-based data structure; determine, based on the usage attributes and the match attributes associated with a plurality of matching words, whether at least one of the word phrases in the phrase-based data structure is present in the word string. | 1. A system for matching large sets of words, the system comprising: one or more processors; and a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to: store a plurality of word phrases in a phrase-based data structure; store each word in the phrase-based data structure as a corresponding keyword in a keyword-based data structure, wherein each corresponding keyword is associated with corresponding usage attributes identifying use of a corresponding word in a corresponding word phrase in the phrase-based data structure; store, for each word in the phrase-based data structure, any corresponding preceding words associated with a corresponding keyword, and a mapping from any corresponding preceding words to a corresponding word phrase; determine whether a word from an inputted word string matches any keyword in the keyword-based data structure; determine whether any corresponding preceding words associated with any matching keyword comprises a preceding word which precedes the matching word in the word string in response to a determination that the word in the word string matches any keyword in the keyword-based data structure; update corresponding match attributes in a match-based data structure in response to a determination that any corresponding preceding words associated with any matching keyword comprises the preceding word which precedes the matching word in the word string, wherein the corresponding match attributes indicate use of the matching word in the word string and use of the matching word in a corresponding word phrase in the phrase-based data structure; determine, based on the usage attributes and the match attributes associated with a plurality of matching words, whether at least one of the word phrases in the phrase-based data structure is present in the word string. 5. The system of claim 1 , wherein the match-based data structure comprises an array having a length equal to a total number of word phrases in the phrase-based data structure, and an index corresponding to the total number of word phrases in the phrase-based data structure. | 0.686788 |
8,185,455 | 21 | 27 | 21. A non-transitory computer-readable storage medium including computer executable instructions that, when executed by a processor, cause the processor to: receive a selection of a first audit rule and a selection of a second audit rule; apply the first audit rule to audit billing data and to produce first audit rule results; apply the second audit rule to audit the billing data and to produce second audit rule results, wherein the first audit rule results identify a first subset of exceptions of a plurality of exceptions within the billing data and the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the billing data, and wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the billing data; display audit results including the first audit rule results and the second audit rule results; and after displaying the first audit rule results and the second audit rule results, receive a selection of a particular audit rule, wherein the selection of the particular audit rule is based on the audit results, and wherein the particular audit rule is one of the first audit rule and the second audit rule. | 21. A non-transitory computer-readable storage medium including computer executable instructions that, when executed by a processor, cause the processor to: receive a selection of a first audit rule and a selection of a second audit rule; apply the first audit rule to audit billing data and to produce first audit rule results; apply the second audit rule to audit the billing data and to produce second audit rule results, wherein the first audit rule results identify a first subset of exceptions of a plurality of exceptions within the billing data and the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the billing data, and wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the billing data; display audit results including the first audit rule results and the second audit rule results; and after displaying the first audit rule results and the second audit rule results, receive a selection of a particular audit rule, wherein the selection of the particular audit rule is based on the audit results, and wherein the particular audit rule is one of the first audit rule and the second audit rule. 27. The computer-readable storage medium of claim 21 , wherein the audit results are displayed at a results user interface. | 0.851449 |
8,073,803 | 10 | 11 | 10. A computer readable medium, said computer readable medium comprising a set of computer instructions implementing a system for ranking an electronic advertisement relative to target content, said set of computer instructions performing the steps of: extracting a title and keywords from said electronic advertisement and a landing page associated with said electronic advertisement for creating a first set of elements, and keywords from said target content on said web page for creating a second set of elements, said first and second sets of elements comprising a plurality of multi-word expressions; calculating, using a computer, a first content match feature using said first and second set of elements, the content match feature to evaluate how well said electronic advertisement matches said target content on said web page; calculating, using a computer, a second content match feature using said first and second set of elements, said second content match feature comprising a semantic association feature based on a degree of correlation between pairs of said plurality of words; and processing said first content match feature and said second content match features with a machine learning model to output a relevance score of said electronic advertisement relative to said target content. | 10. A computer readable medium, said computer readable medium comprising a set of computer instructions implementing a system for ranking an electronic advertisement relative to target content, said set of computer instructions performing the steps of: extracting a title and keywords from said electronic advertisement and a landing page associated with said electronic advertisement for creating a first set of elements, and keywords from said target content on said web page for creating a second set of elements, said first and second sets of elements comprising a plurality of multi-word expressions; calculating, using a computer, a first content match feature using said first and second set of elements, the content match feature to evaluate how well said electronic advertisement matches said target content on said web page; calculating, using a computer, a second content match feature using said first and second set of elements, said second content match feature comprising a semantic association feature based on a degree of correlation between pairs of said plurality of words; and processing said first content match feature and said second content match features with a machine learning model to output a relevance score of said electronic advertisement relative to said target content. 11. The computer readable medium as set forth in claim 10 wherein said first content match feature comprises a text similarity feature. | 0.618644 |
9,164,778 | 10 | 17 | 10. A system for modal progress dialog comprising: a system interface to receive an action request associated with a resource; a resource manager, comprising at least one processor, to process the action on the resource; and a progress manager, comprising at least one processor, to determine when a progress dialog is to be displayed triggered on a predicted duration of the processing of the action, the predicted duration being a function of the action requested, the resource associated with the action requested, a location of the resource, or a measured time to execute a portion of the action, where the process manager displays the progress dialog when the determination is triggered by the predicted duration exceeding a threshold. | 10. A system for modal progress dialog comprising: a system interface to receive an action request associated with a resource; a resource manager, comprising at least one processor, to process the action on the resource; and a progress manager, comprising at least one processor, to determine when a progress dialog is to be displayed triggered on a predicted duration of the processing of the action, the predicted duration being a function of the action requested, the resource associated with the action requested, a location of the resource, or a measured time to execute a portion of the action, where the process manager displays the progress dialog when the determination is triggered by the predicted duration exceeding a threshold. 17. The system for modal progress dialog of claim 10 , where the returned result of the action request indicates a failure of the action when the user has operated the control to cancel the action. | 0.5 |
7,685,119 | 12 | 16 | 12. A query expansion system for augmenting a query, the query expansion system comprising: a processor; a memory coupled to the processor, the memory comprising instructions that cause the processor to: obtain a first popularity ranking associated with a received user query; associate the received user query with a first geographic locality where the received user query comprises a geographic component; identify a plurality of neighboring geographic localities comprising geographic localities that are proximate to the first geographic locality; identify, based on the first popularity ranking, a first neighboring geographic locality from among the plurality of neighboring geographic localities; rank the plurality of neighboring geographic localities based on the first popularity ranking, where ranking the plurality of neighboring geographic localities comprises weighting each geographic locality of the plurality of neighboring geographic localities based on the first popularity ranking; generate an augmented query by augmenting the received user query based on the first popularity ranking, the first neighboring geographic locality identified based on the first popularity ranking, and the ranking of the plurality of neighboring geographic localities, where the augmenting of the received user query comprises expanding the received user query to include the weighted geographic localities of the plurality of neighboring geographic localities; and provide the augmented query to a search engine. | 12. A query expansion system for augmenting a query, the query expansion system comprising: a processor; a memory coupled to the processor, the memory comprising instructions that cause the processor to: obtain a first popularity ranking associated with a received user query; associate the received user query with a first geographic locality where the received user query comprises a geographic component; identify a plurality of neighboring geographic localities comprising geographic localities that are proximate to the first geographic locality; identify, based on the first popularity ranking, a first neighboring geographic locality from among the plurality of neighboring geographic localities; rank the plurality of neighboring geographic localities based on the first popularity ranking, where ranking the plurality of neighboring geographic localities comprises weighting each geographic locality of the plurality of neighboring geographic localities based on the first popularity ranking; generate an augmented query by augmenting the received user query based on the first popularity ranking, the first neighboring geographic locality identified based on the first popularity ranking, and the ranking of the plurality of neighboring geographic localities, where the augmenting of the received user query comprises expanding the received user query to include the weighted geographic localities of the plurality of neighboring geographic localities; and provide the augmented query to a search engine. 16. The query expansion system of claim 12 , where the first neighboring geographic locality identified based on the first popularity ranking was not included in the user query, and where the augmenting of the received user query comprises expanding the user query to include the first neighboring geographic locality identified based on the first popularity ranking. | 0.5 |
9,424,278 | 9 | 12 | 9. A method of identifying customers of productive assets, comprising: machine-searching a number of Uniform Commercial Code financing statements filed for finance transactions wherein at least some of the financing statements include an image within a field for collateral information on specific productive assets that are supplied as collateral for a transaction underlying a particular financing statement, and corresponding party information of the collateral information; machine-recording the corresponding party information from each financing statement; machine-retrieving the collateral information image from the field within the at least some of the financing statements and performing an Optical Character Recognition (OCR) process on the retrieved collateral image to derive digital text representing the collateral information; machine-organizing the collateral information in conjunction with the corresponding party information into records in a searchable database, including keyword mapping the collateral information into particular equipment specific categories; and machine-presenting the records in a format with hyperlinks for the collateral information and the corresponding party information, wherein one of the hyperlinks for the corresponding party information includes a web-based interactive map. | 9. A method of identifying customers of productive assets, comprising: machine-searching a number of Uniform Commercial Code financing statements filed for finance transactions wherein at least some of the financing statements include an image within a field for collateral information on specific productive assets that are supplied as collateral for a transaction underlying a particular financing statement, and corresponding party information of the collateral information; machine-recording the corresponding party information from each financing statement; machine-retrieving the collateral information image from the field within the at least some of the financing statements and performing an Optical Character Recognition (OCR) process on the retrieved collateral image to derive digital text representing the collateral information; machine-organizing the collateral information in conjunction with the corresponding party information into records in a searchable database, including keyword mapping the collateral information into particular equipment specific categories; and machine-presenting the records in a format with hyperlinks for the collateral information and the corresponding party information, wherein one of the hyperlinks for the corresponding party information includes a web-based interactive map. 12. The method of claim 9 , wherein each financing statement includes initial filing information and addendum information, and the method further includes overriding the initial filing information with the addendum information to create a single record. | 0.602201 |
8,713,421 | 1 | 2 | 1. A computer-implemented method, the method comprising: identifying a drawing scale for a graphical view of a drawing from a file that stores the drawing, the drawing scale specifying a ratio of two units; selecting one or more annotations associated with the view that supports the drawing scale; retrieving from the file for each of the selected annotations, associated context for the drawing scale, the context specifying one or more of: the annotation's position in the view, the annotation's style in the view, or the annotation's rotation in the view; adding a graphical representation of each of the selected annotations to the view according to the drawing scale and each annotation's respective context; and removing any one or more of the annotations from the view that does not support the drawing scale. | 1. A computer-implemented method, the method comprising: identifying a drawing scale for a graphical view of a drawing from a file that stores the drawing, the drawing scale specifying a ratio of two units; selecting one or more annotations associated with the view that supports the drawing scale; retrieving from the file for each of the selected annotations, associated context for the drawing scale, the context specifying one or more of: the annotation's position in the view, the annotation's style in the view, or the annotation's rotation in the view; adding a graphical representation of each of the selected annotations to the view according to the drawing scale and each annotation's respective context; and removing any one or more of the annotations from the view that does not support the drawing scale. 2. The method of claim 1 where the two units are paper units and drawing units. | 0.717857 |
8,856,051 | 10 | 14 | 10. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, actions of the computer program instructions comprising: accessing a set of digital objects; determining degrees of similarity between pairs of the objects; and for each object of a plurality of the objects, training a classifier for the object, the training comprising: forming, for the object, a training set comprising other ones of the objects based at least in part on the degrees of similarity; and training the classifier for the object based at least in part on features extracted from the objects in the training set; applying the trained classifier for a first one of the objects to a second one of the objects to determine a degree of similarity between the second one of the objects and the first one of the objects; and responsive to the degree of similarity being above a threshold value: based on the degree of similarity, reducing cluster weights derived from user-supplied textual metadata of the first one of the objects, thereby obtaining first reduced cluster weight metadata; and associating the first reduced cluster weight metadata as metadata of the second one of the objects. | 10. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, actions of the computer program instructions comprising: accessing a set of digital objects; determining degrees of similarity between pairs of the objects; and for each object of a plurality of the objects, training a classifier for the object, the training comprising: forming, for the object, a training set comprising other ones of the objects based at least in part on the degrees of similarity; and training the classifier for the object based at least in part on features extracted from the objects in the training set; applying the trained classifier for a first one of the objects to a second one of the objects to determine a degree of similarity between the second one of the objects and the first one of the objects; and responsive to the degree of similarity being above a threshold value: based on the degree of similarity, reducing cluster weights derived from user-supplied textual metadata of the first one of the objects, thereby obtaining first reduced cluster weight metadata; and associating the first reduced cluster weight metadata as metadata of the second one of the objects. 14. The non-transitory computer-readable storage medium of claim 10 , wherein the degrees of similarity between pairs of the objects are determined based on co-play counts of the videos in the pair. | 0.879268 |
8,806,333 | 13 | 14 | 13. The method of claim 11 , wherein the integration process enables instructions executing within the virtual machine to retrieve information from the computing environment of the computing device by providing a query to a search engine within the computing environment. | 13. The method of claim 11 , wherein the integration process enables instructions executing within the virtual machine to retrieve information from the computing environment of the computing device by providing a query to a search engine within the computing environment. 14. The method of claim 13 , further comprising searching for information within the storage of the computing device using the search engine by: generating an index of the storage of the computing device; querying the index using metadata that identifies information stored within the storage of the computing device; and retrieving the information stored within the storage of the computing device. | 0.5 |
7,870,113 | 12 | 13 | 12. The method of claim 1 , wherein said organizing the data, based on relationships among the data, into a network comprises forming a relational table indicative of relationships between instances of said at least one predecessor group and instances of a first one of said plurality of descendant groups. | 12. The method of claim 1 , wherein said organizing the data, based on relationships among the data, into a network comprises forming a relational table indicative of relationships between instances of said at least one predecessor group and instances of a first one of said plurality of descendant groups. 13. The method of claim 12 , wherein said forming a relational table comprises forming a many-to-many transfer file indicative of relationships between said instances of said at least one predecessor group and said instances of said first one of said plurality of descendant groups. | 0.5 |
9,171,081 | 1 | 14 | 1. In a computing environment, a computer-implemented method performed at least in part on at least one processor for returning data to complete at least part of an augmentation task, comprising: receiving a query as input in the form of a query table including one or more entity names in a first query column and zero or more entity attributes in a second query column, accessing relationship-based data corresponding to relationships between a plurality of relational tables, the relationship-based data mined offline from at least one corpus and preprocessed offline into a plurality of indexes, and using the relationship-based data to: identify a direct relationship between the query table and a first relational table of the plurality of relational tables, identify an indirect relationship between the query table and a second relational table of the plurality of relational tables, identify a first score representing a first match between the query table and the first relational table, identify a second score representing a second match between the first relational table and the second relational table, and determine one or more entity attributes to return to augment the query table and complete the at least part of the augmentation task, the one or more entity attributes determined based at least partially on the first score and the second score. | 1. In a computing environment, a computer-implemented method performed at least in part on at least one processor for returning data to complete at least part of an augmentation task, comprising: receiving a query as input in the form of a query table including one or more entity names in a first query column and zero or more entity attributes in a second query column, accessing relationship-based data corresponding to relationships between a plurality of relational tables, the relationship-based data mined offline from at least one corpus and preprocessed offline into a plurality of indexes, and using the relationship-based data to: identify a direct relationship between the query table and a first relational table of the plurality of relational tables, identify an indirect relationship between the query table and a second relational table of the plurality of relational tables, identify a first score representing a first match between the query table and the first relational table, identify a second score representing a second match between the first relational table and the second relational table, and determine one or more entity attributes to return to augment the query table and complete the at least part of the augmentation task, the one or more entity attributes determined based at least partially on the first score and the second score. 14. The computer-implemented method of claim 1 , wherein receiving a query comprises receiving a first header for the first query column and receiving a second header for the second query column, and using the relationship-based data comprises identifying the first relational table that includes a first relational column with one or more data values correlating with the one or more entity names in the query table and a second relational column having a header correlating with the second header. | 0.530132 |
9,870,485 | 10 | 16 | 10. A system for detecting sensitive user input leakages in a software application comprising, a processor, memory and an interface, wherein said memory is configured to store: a layout parsing module which parses a user interface (UI) layout file of the software application to identify input fields and obtain information concerning the input fields from the UI layout file; an identification module which identifies the input fields that contain sensitive information and generates a list of sensitive input fields; and a taint analysis module which detects information leaks in the sensitive input fields based on the list of sensitive input fields and notifies a user of the information leaks in the sensitive input fields to avoid use of the software application by the user, wherein the taint analysis module identifies widget variables for sensitive input fields and associates the widget variables with corresponding UI layouts in order to avoid duplicate widgets. | 10. A system for detecting sensitive user input leakages in a software application comprising, a processor, memory and an interface, wherein said memory is configured to store: a layout parsing module which parses a user interface (UI) layout file of the software application to identify input fields and obtain information concerning the input fields from the UI layout file; an identification module which identifies the input fields that contain sensitive information and generates a list of sensitive input fields; and a taint analysis module which detects information leaks in the sensitive input fields based on the list of sensitive input fields and notifies a user of the information leaks in the sensitive input fields to avoid use of the software application by the user, wherein the taint analysis module identifies widget variables for sensitive input fields and associates the widget variables with corresponding UI layouts in order to avoid duplicate widgets. 16. The system as recited in claim 10 , wherein the taint analysis module identifies sink locations in the software application based upon a sink database in order to detect information leaks. | 0.761194 |
6,128,611 | 20 | 21 | 20. The computerized method of claim 14 further comprising the data object providing a business object with business logic for the application program. | 20. The computerized method of claim 14 further comprising the data object providing a business object with business logic for the application program. 21. The computerized method of claim 20 further comprising the business object invoking one or more methods of the data object to perform the necessary operations on the database. | 0.5 |
7,543,024 | 1 | 3 | 1. A method for monitoring multiple online resources in different formats, the method comprising the steps of: identifying a plurality of online resources to monitor, the plurality of online resources being stored in a plurality of formats, at least one of the plurality of online resources including data in a non-strict architectural structure; identifying whether each of the online resources of the plurality of online resources is a non-HyperText Markup Language application; for each of the plurality of online resources from the non-HyperText Markup Language application, converting the online resource from the non-HyperText Markup Language application to a HyperText Markup Language application; for each of the online resources of the plurality of online resources, determining whether the online resource meets a minimum level of content structure to allow an Extensible Style Sheet Transform to be used to convert the online resource to the strict formatted file; converting each of the plurality of online resources that is determined as meeting the minimum level of content structure to a strict formatted file having a common format, wherein the strict formatted file is an Extensible Markup Language application, and wherein data in the plurality of formats of the plurality of online resources is converted into a strict architectural structure; converting each of the plurality of online resources that is determined as not meeting the minimum level of content structure to a strict formatted file, wherein the strict formatted file is a document object model of the online resource; after converting to the strict formatted file, identifying relevant data in each of the strict formatted files based on the strict architectural structure of the data using an analytic parser; and comparing the identified relevant data to a most recent archived copy of the identified relevant data to determine whether the identified relevant data has been altered. | 1. A method for monitoring multiple online resources in different formats, the method comprising the steps of: identifying a plurality of online resources to monitor, the plurality of online resources being stored in a plurality of formats, at least one of the plurality of online resources including data in a non-strict architectural structure; identifying whether each of the online resources of the plurality of online resources is a non-HyperText Markup Language application; for each of the plurality of online resources from the non-HyperText Markup Language application, converting the online resource from the non-HyperText Markup Language application to a HyperText Markup Language application; for each of the online resources of the plurality of online resources, determining whether the online resource meets a minimum level of content structure to allow an Extensible Style Sheet Transform to be used to convert the online resource to the strict formatted file; converting each of the plurality of online resources that is determined as meeting the minimum level of content structure to a strict formatted file having a common format, wherein the strict formatted file is an Extensible Markup Language application, and wherein data in the plurality of formats of the plurality of online resources is converted into a strict architectural structure; converting each of the plurality of online resources that is determined as not meeting the minimum level of content structure to a strict formatted file, wherein the strict formatted file is a document object model of the online resource; after converting to the strict formatted file, identifying relevant data in each of the strict formatted files based on the strict architectural structure of the data using an analytic parser; and comparing the identified relevant data to a most recent archived copy of the identified relevant data to determine whether the identified relevant data has been altered. 3. The method of claim 1 wherein at least one of the online resources is a non-HyperText Markup Language application. | 0.717391 |
7,506,040 | 1 | 9 | 1. A system, comprising: one or more processors; and one or more memory mediums coupled to the one or more processors, wherein the one or more memory mediums store program instructions executable to implement: a storage area network (SAN) management server comprising: a SAN access layer configured to discover a plurality of SAN components coupled to a SAN fabric; wherein the SAN management server is configured to monitor the discovered SAN components coupled to the SAN fabric; and a SAN manager client coupled to said SAN management server, wherein the SAN manager client is configured to provide a centralized user interface for centralized management of the SAN through interaction with the SAN management server, wherein the SAN management server is configured to perform one or more SAN management tasks in response to interactions of said centralized user interface, and wherein said centralized management of the SAN provides management of the discovered plurality of SAN components. | 1. A system, comprising: one or more processors; and one or more memory mediums coupled to the one or more processors, wherein the one or more memory mediums store program instructions executable to implement: a storage area network (SAN) management server comprising: a SAN access layer configured to discover a plurality of SAN components coupled to a SAN fabric; wherein the SAN management server is configured to monitor the discovered SAN components coupled to the SAN fabric; and a SAN manager client coupled to said SAN management server, wherein the SAN manager client is configured to provide a centralized user interface for centralized management of the SAN through interaction with the SAN management server, wherein the SAN management server is configured to perform one or more SAN management tasks in response to interactions of said centralized user interface, and wherein said centralized management of the SAN provides management of the discovered plurality of SAN components. 9. The system as recited in claim 1 , wherein the SAN components comprise one or more fabric switches, a plurality of storage systems coupled to the SAN fabric, and one or more host systems coupled to the SAN fabric. | 0.816949 |
9,626,438 | 18 | 19 | 18. A system comprising: a processor; and memory in communication with the processor and storing instructions that, when executed by the processor, cause the system to: receive search data from a server hosting a first website, the search data including first information regarding content accessed by a user subsequent to a search, the first information indicative of a first content format accessed by the user, the first content format corresponding to a first search result of a plurality of search results provided to the user from the search, and the plurality of search results including content in a second content format that is different from the first content format, wherein the user does not access the second content format; identify a category related to at least a portion of the search data, the identifying based at least on formats of content on target websites; determine, based on the search data, a topic for first content associated with the identified category; determine a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data, information regarding different formats of content offered on the first website, the format of content accessed by the user on the first website, and the user not accessing the second content format; and present the topic and the score to a content provider for producing the first content for the target websites, the content provider to select a format for the first content based on the score and on user interaction with the plurality of search results. | 18. A system comprising: a processor; and memory in communication with the processor and storing instructions that, when executed by the processor, cause the system to: receive search data from a server hosting a first website, the search data including first information regarding content accessed by a user subsequent to a search, the first information indicative of a first content format accessed by the user, the first content format corresponding to a first search result of a plurality of search results provided to the user from the search, and the plurality of search results including content in a second content format that is different from the first content format, wherein the user does not access the second content format; identify a category related to at least a portion of the search data, the identifying based at least on formats of content on target websites; determine, based on the search data, a topic for first content associated with the identified category; determine a score indicative of a level of popularity for the topic, wherein determining the score is based on the search data, information regarding different formats of content offered on the first website, the format of content accessed by the user on the first website, and the user not accessing the second content format; and present the topic and the score to a content provider for producing the first content for the target websites, the content provider to select a format for the first content based on the score and on user interaction with the plurality of search results. 19. The system of claim 18 , wherein determining the score includes determining a first score for content for the topic having a first format, and determining a second score for content for the topic having a second format, and wherein the instructions further cause the system to transmit, over a network, the first score and the second score to a client device of the content provider. | 0.5 |
9,974,506 | 1 | 3 | 1. A method for associating coronary angiography image annotations with a SYNTAX score for assessment of coronary artery disease comprising: receiving and processing, by a system comprising one or more processors, a plurality of angiogram videos from a coronary angiography study into a plurality of frames for each of the plurality of angiogram videos; extracting, by the system, a key frame from the plurality of frames for each of the plurality of angiogram videos, wherein extracting the key frame for each of the plurality of angiogram videos comprises detecting, by the system, a presence of a contrast agent in one or more frames of the plurality of frames of each given angiogram video, and using edge detection, edge curve following and pairing of curves on opposing sides of an artery to identify a representative frame of the given angiogram video having extended parallel curves; displaying to a user, by the system via a browsing interface, each of the extracted key frames; in response to receiving a selection from the user of a key frame from the displayed key frames, displaying, by the system via a video view interface, the angiogram video that is associated with the selected key frame; receiving, by the system, a lesion annotation from the user for a frame of the angiogram video; based on receiving the lesion annotation, displaying, by the system, a SYNTAX score questionnaire in the video viewer interface; based on receiving answers to the SYNTAX score questionnaire from the user, annotating, by the system, the frame of the angiogram video with the answers to the SYNTAX score questionnaire from the user; saving, by the system, the answers to the SYNTAX score questionnaire with the annotated frame in a database; computing and displaying a SYNTAX score for the lesion based on the answers to the SYNTAX score questionnaire; and generating a lesion report for a selected lesion that shows the answers of the SYNTAX score questionnaire for the selected lesion along with one or more frames illustrating the selected lesion. | 1. A method for associating coronary angiography image annotations with a SYNTAX score for assessment of coronary artery disease comprising: receiving and processing, by a system comprising one or more processors, a plurality of angiogram videos from a coronary angiography study into a plurality of frames for each of the plurality of angiogram videos; extracting, by the system, a key frame from the plurality of frames for each of the plurality of angiogram videos, wherein extracting the key frame for each of the plurality of angiogram videos comprises detecting, by the system, a presence of a contrast agent in one or more frames of the plurality of frames of each given angiogram video, and using edge detection, edge curve following and pairing of curves on opposing sides of an artery to identify a representative frame of the given angiogram video having extended parallel curves; displaying to a user, by the system via a browsing interface, each of the extracted key frames; in response to receiving a selection from the user of a key frame from the displayed key frames, displaying, by the system via a video view interface, the angiogram video that is associated with the selected key frame; receiving, by the system, a lesion annotation from the user for a frame of the angiogram video; based on receiving the lesion annotation, displaying, by the system, a SYNTAX score questionnaire in the video viewer interface; based on receiving answers to the SYNTAX score questionnaire from the user, annotating, by the system, the frame of the angiogram video with the answers to the SYNTAX score questionnaire from the user; saving, by the system, the answers to the SYNTAX score questionnaire with the annotated frame in a database; computing and displaying a SYNTAX score for the lesion based on the answers to the SYNTAX score questionnaire; and generating a lesion report for a selected lesion that shows the answers of the SYNTAX score questionnaire for the selected lesion along with one or more frames illustrating the selected lesion. 3. The method of claim 1 , further comprising computing and displaying a total SYNTAX score for the coronary angiography study based on the answers to the SYNTAX score questionnaire for all identified lesions in the coronary angiography study. | 0.652857 |
8,381,299 | 83 | 84 | 83. The system of claim 74 , wherein the number of n-grams in the first plurality of most-heavily weighted n-grams is predetermined. | 83. The system of claim 74 , wherein the number of n-grams in the first plurality of most-heavily weighted n-grams is predetermined. 84. The system of claim 83 , wherein the number of n-grams in the first plurality of most-heavily weighted n-grams can be adjusted. | 0.5 |
8,224,810 | 5 | 6 | 5. The computer readable storage medium of claim 4 , wherein the graphical user interface is configured to: receive, via the query specification display area, user input specifying the abstract query comprising the result fields for which data is to be returned from the database. | 5. The computer readable storage medium of claim 4 , wherein the graphical user interface is configured to: receive, via the query specification display area, user input specifying the abstract query comprising the result fields for which data is to be returned from the database. 6. The computer readable storage medium of claim 5 , wherein the graphical user interface is further configured to: receive a user selection to perform the abstract query using the classification field; include the classification field with the abstract query; and pass the abstract query and classification field to a runtime component configured to generate an executable query on the basis of the abstract query and the included classification field. | 0.5 |
8,635,561 | 1 | 5 | 1. A method comprising: receiving, by a processor, a plurality of email snippets, each respective email snippet from the plurality of email snippets being based on a respective email from a plurality of emails and each respective email snippet including a subject of the respective email, a sender of the respective email, and a respective portion of a body of the respective email, wherein the respective portion of the body of the respective email comprises, at most, a first predetermined maximum amount of the body of the respective email; outputting, by the processor, and for simultaneous display at a touch-sensitive display: an expanded view of a first snippet from the plurality of snippets, the first snippet being based on a first email from the plurality of emails, the expanded view including at least a portion of the subject of the first email, at least an indication of the sender of the first email, and an expanded portion of the body of the snippet of the first email, wherein the expanded portion comprises, at most, a second predetermined maximum amount of the body of the first email; and a condensed view of a second snippet from the plurality of snippets, the second snippet being based on a second email from the plurality of emails, the condensed view including at least a portion of the subject of the second email, at least an indication of the sender of the second email, and a condensed portion of the body of the snippet of the second email, wherein the condensed portion comprises, at most, a third predetermined maximum amount of the body of the second email; and receiving an indication of a single swipe gesture received at the touch-sensitive display; responsive to determining that the gesture corresponds to one or more of deleting, archiving, and marking actions, sorting the first email based on the corresponding actions; and outputting, for display, an expanded view of the second snippet from the plurality of snippets in place of the expanded view of the first snippet from the plurality of snippets. | 1. A method comprising: receiving, by a processor, a plurality of email snippets, each respective email snippet from the plurality of email snippets being based on a respective email from a plurality of emails and each respective email snippet including a subject of the respective email, a sender of the respective email, and a respective portion of a body of the respective email, wherein the respective portion of the body of the respective email comprises, at most, a first predetermined maximum amount of the body of the respective email; outputting, by the processor, and for simultaneous display at a touch-sensitive display: an expanded view of a first snippet from the plurality of snippets, the first snippet being based on a first email from the plurality of emails, the expanded view including at least a portion of the subject of the first email, at least an indication of the sender of the first email, and an expanded portion of the body of the snippet of the first email, wherein the expanded portion comprises, at most, a second predetermined maximum amount of the body of the first email; and a condensed view of a second snippet from the plurality of snippets, the second snippet being based on a second email from the plurality of emails, the condensed view including at least a portion of the subject of the second email, at least an indication of the sender of the second email, and a condensed portion of the body of the snippet of the second email, wherein the condensed portion comprises, at most, a third predetermined maximum amount of the body of the second email; and receiving an indication of a single swipe gesture received at the touch-sensitive display; responsive to determining that the gesture corresponds to one or more of deleting, archiving, and marking actions, sorting the first email based on the corresponding actions; and outputting, for display, an expanded view of the second snippet from the plurality of snippets in place of the expanded view of the first snippet from the plurality of snippets. 5. The method of claim 1 , the second predetermined maximum amount being approximately 160 characters. | 0.853448 |
9,053,427 | 1 | 12 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on a provider of the target information, wherein if the provider of the target information has a validity rating less than a first validity threshold, then the segments of the target information from the provider are prioritized in a highest priority group, and if the provider of the target information has the validity rating greater than or equal to the first threshold and less than a second threshold, then the segments of the target information from the provider are prioritized in a second highest priority group which has a lower priority than the highest priority group, and if the provider of the target information has the validity rating greater than or equal to the second threshold, then the segments of the target information from the provider are prioritized in a third highest priority group which has a lower priority than the second highest priority group; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on a provider of the target information, wherein if the provider of the target information has a validity rating less than a first validity threshold, then the segments of the target information from the provider are prioritized in a highest priority group, and if the provider of the target information has the validity rating greater than or equal to the first threshold and less than a second threshold, then the segments of the target information from the provider are prioritized in a second highest priority group which has a lower priority than the highest priority group, and if the provider of the target information has the validity rating greater than or equal to the second threshold, then the segments of the target information from the provider are prioritized in a third highest priority group which has a lower priority than the second highest priority group; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information. 12. The method of claim 1 wherein fact checking includes only fact checking randomly selected segments. | 0.954586 |
8,938,450 | 11 | 12 | 11. The method of claim 1 , further comprising: identifying sentiment metadata by performing a sentiment analysis on the microcontent message; and associating the sentiment metadata with the microcontent message. | 11. The method of claim 1 , further comprising: identifying sentiment metadata by performing a sentiment analysis on the microcontent message; and associating the sentiment metadata with the microcontent message. 12. The method of claim 11 , wherein the sentiment analysis is based on a Naïve Bayesian classifier that is trained offline to an annotated set of positive, negative and neutral microcontent messages. | 0.5 |
8,490,052 | 1 | 6 | 1. A method of issuing at least two operations on a data set accessible through a host according to a protocol, comprising: expressing the operations as a declarative resource script in a declarative script language comprising: at least one declarative data set instruction applying a verb of the protocol to the data set, and at least one declarative flow control instruction configured to alter an execution flow of the declarative resource script according to a flow control operation selected from a flow control operation set comprising: conditional executing of at least one operation; relocating to a target operation of the declarative resource script; iterative executing of at least one operation; concurrent executing of at least two operations; and asynchronous executing of at least one operation, wherein the declarative resource script comprises at least one declarative flow control instruction and at least two declarative data set instructions that, unless logically ordered by a declarative flow control instruction, may be executed in any logical order; and interpreting the declarative resource script through a declarative script processor configured to perform operations on the data set by issuing the verbs of the protocol specified by the declarative data set instructions to the host. | 1. A method of issuing at least two operations on a data set accessible through a host according to a protocol, comprising: expressing the operations as a declarative resource script in a declarative script language comprising: at least one declarative data set instruction applying a verb of the protocol to the data set, and at least one declarative flow control instruction configured to alter an execution flow of the declarative resource script according to a flow control operation selected from a flow control operation set comprising: conditional executing of at least one operation; relocating to a target operation of the declarative resource script; iterative executing of at least one operation; concurrent executing of at least two operations; and asynchronous executing of at least one operation, wherein the declarative resource script comprises at least one declarative flow control instruction and at least two declarative data set instructions that, unless logically ordered by a declarative flow control instruction, may be executed in any logical order; and interpreting the declarative resource script through a declarative script processor configured to perform operations on the data set by issuing the verbs of the protocol specified by the declarative data set instructions to the host. 6. The method of claim 1 , at least one declarative flow control instruction specifying a custom operation performable on the data set that is specified in a custom module. | 0.806306 |
4,882,703 | 1 | 3 | 1. A computer implemented method for processing words from a standard dictionary into a special dictionary by using a programmable digital computer system comprising the following steps: (a) inputting a word in upper case letters from the standard dictionary as a first of two string variables for use by the computer, creating a second such string variable from the first string variable by alphabetizing the letters in the first string variable and converting said letters to lower case, then appending the first string variable to the second string variable to provide a concatenated record and storing the result as one record in a different sequential disk file respectively created for each different length record, (b) repeating step a) for each different word of said standard dictionary. (c) placing the concatenated records in each sequential file in alphabetic order on disk media of the computer after input of such dictionary words is complete, (d) creating a corresponding random file for each sequential file in which the length of a record is equal to the length of the word so input from the standard dictionary in the sequential file, then reserving the first two words in each such random file for a finger index, (e) reading each sequential file, then writing both the lower and upper case words read to the corresponding random file, but if a succeeding record has the same lower case prefix as the one just written, then writing only the upper case word following the record just written, and (f) scanning the lower case words in each random file and storing the record number at which certain preselected letter prefixes change in a predetermined location of said first two words of the random file as a pointer or finger index. | 1. A computer implemented method for processing words from a standard dictionary into a special dictionary by using a programmable digital computer system comprising the following steps: (a) inputting a word in upper case letters from the standard dictionary as a first of two string variables for use by the computer, creating a second such string variable from the first string variable by alphabetizing the letters in the first string variable and converting said letters to lower case, then appending the first string variable to the second string variable to provide a concatenated record and storing the result as one record in a different sequential disk file respectively created for each different length record, (b) repeating step a) for each different word of said standard dictionary. (c) placing the concatenated records in each sequential file in alphabetic order on disk media of the computer after input of such dictionary words is complete, (d) creating a corresponding random file for each sequential file in which the length of a record is equal to the length of the word so input from the standard dictionary in the sequential file, then reserving the first two words in each such random file for a finger index, (e) reading each sequential file, then writing both the lower and upper case words read to the corresponding random file, but if a succeeding record has the same lower case prefix as the one just written, then writing only the upper case word following the record just written, and (f) scanning the lower case words in each random file and storing the record number at which certain preselected letter prefixes change in a predetermined location of said first two words of the random file as a pointer or finger index. 3. A computer implemented procedure for finding all words contained in any given word of the special dictionary created by the method according to claim 1 comprising the following steps: (a) inputting to the computer system in upper case letters a word and creating an anagram of such word by alphabetizing the letters in such word and converting those letters to lower case, thus creating an alphabetized lower case word constituting such anagram, (b) computing permutations of the letters in the anagram for successively decreasing lengths down to a selected minimum length, each length forming a respective group of juxtaposed letters, (c) comparing the permutations of juxtaposed letters for each specific word length to the lower case words in the random file for a record size equal to said specific word length from a starting point located by the finger index for the respective random file to the last permutation of letters so computed for the respective group of juxtaposed letters in search of a match, (d) taking the upper case words following any such match to the lower case permutation found in step c) up to the next lower case word and moving them to a solution queue, and, when all permutations of the letters in the alphabetized word have been searched, then (e) outputting the words in the solution queue in some readable form after optionally alphabetizing same. | 0.5 |
9,171,262 | 17 | 20 | 17. A portable processor-based device comprising: geographic location identification hardware; and one or more processors configured to: capture one or more usage behaviors; deliver the one or more usage behaviors to a computer-implemented function that infers a first expertise level of a first person who is a first user of the portable processor-based device from the one or more usage behaviors; receive one or more computer-implemented objects that are selected from a plurality of computer-implemented objects that do not represent users of a computer-implemented system and that have associated computer-implemented directionally distinct relationships between pairs of the plurality of computer-implemented objects, wherein the selecting is performed in accordance with the first expertise level, at least one of the computer-implemented directionally distinct relationships, and a first automatically determined geographic location; and deliver the one or more computer-implemented objects to the first person. | 17. A portable processor-based device comprising: geographic location identification hardware; and one or more processors configured to: capture one or more usage behaviors; deliver the one or more usage behaviors to a computer-implemented function that infers a first expertise level of a first person who is a first user of the portable processor-based device from the one or more usage behaviors; receive one or more computer-implemented objects that are selected from a plurality of computer-implemented objects that do not represent users of a computer-implemented system and that have associated computer-implemented directionally distinct relationships between pairs of the plurality of computer-implemented objects, wherein the selecting is performed in accordance with the first expertise level, at least one of the computer-implemented directionally distinct relationships, and a first automatically determined geographic location; and deliver the one or more computer-implemented objects to the first person. 20. The device of claim 17 comprising the one or more processors configured to: receive the one or more computer-implemented objects that are selected from the plurality of computer-implemented objects, wherein at least one of the selected one or more computer-implemented objects comprises a reference to a physical object. | 0.506098 |
9,031,947 | 1 | 2 | 1. A method for identifying elements of a system, the method implemented by at least one computer processor coupled to at least one data storage device and comprising: providing a system element store comprising machine-readable representations of system models comprising system elements classified as a whole element of a whole-part relationship, an entity element of an entity-relation-entity relationship, a pair of entity elements of an entity-relation-entity relationship, or a relation element of an entity-relation-entity relationship; electronically receiving a graphical user interface input identifying a system model as a selected electronic representation of the system; in response to the graphical user interface input, extracting corresponding system elements of the identified system model from the system element store, and automatically formulating a query from the extracted system elements, wherein the extracted system elements represent a set of system objectives; searching one or more mereological and functional relationship databases using a knowledge search engine, the one or more merelogical and functional relationship databases including one or more general document repositories that are semantically indexed and contain non-hierarchical database structures and additional one or more knowledge bases selected from the group consisting of: one or more locally accessible knowledge bases, one or more knowledge bases containing corporate knowledge, and one or more publicly accessible knowledge bases; using the query to retrieve component elements useful to form the extracted system elements and identify functional interactions between the component elements, wherein the component elements represent parts of entity-relationship-entity relationships represented in the identified system model; and storing and displaying the retrieved component elements and identified functional interactions as search results in association with the extracted system elements, wherein the search results are represented as user-selectable options indicating design alternatives to satisfy the set of system objectives of the system. | 1. A method for identifying elements of a system, the method implemented by at least one computer processor coupled to at least one data storage device and comprising: providing a system element store comprising machine-readable representations of system models comprising system elements classified as a whole element of a whole-part relationship, an entity element of an entity-relation-entity relationship, a pair of entity elements of an entity-relation-entity relationship, or a relation element of an entity-relation-entity relationship; electronically receiving a graphical user interface input identifying a system model as a selected electronic representation of the system; in response to the graphical user interface input, extracting corresponding system elements of the identified system model from the system element store, and automatically formulating a query from the extracted system elements, wherein the extracted system elements represent a set of system objectives; searching one or more mereological and functional relationship databases using a knowledge search engine, the one or more merelogical and functional relationship databases including one or more general document repositories that are semantically indexed and contain non-hierarchical database structures and additional one or more knowledge bases selected from the group consisting of: one or more locally accessible knowledge bases, one or more knowledge bases containing corporate knowledge, and one or more publicly accessible knowledge bases; using the query to retrieve component elements useful to form the extracted system elements and identify functional interactions between the component elements, wherein the component elements represent parts of entity-relationship-entity relationships represented in the identified system model; and storing and displaying the retrieved component elements and identified functional interactions as search results in association with the extracted system elements, wherein the search results are represented as user-selectable options indicating design alternatives to satisfy the set of system objectives of the system. 2. The method according to claim 1 , wherein the system elements of the system element store are classified prior to formulating the query. | 0.670616 |
10,127,927 | 22 | 24 | 22. The system of claim 14 , wherein the method further comprises: receiving one or more test speech samples; generating a set of test data by extracting one or more acoustic features from every frame of the one or more test speech samples; transforming the set of test data into transformed data using the PLDA model to capture emotion and/or speaking style in the transformed data; and using the transformed data for clustering and/or classification to discover speech with emotion or speaking styles similar to that captured in the transformed data. | 22. The system of claim 14 , wherein the method further comprises: receiving one or more test speech samples; generating a set of test data by extracting one or more acoustic features from every frame of the one or more test speech samples; transforming the set of test data into transformed data using the PLDA model to capture emotion and/or speaking style in the transformed data; and using the transformed data for clustering and/or classification to discover speech with emotion or speaking styles similar to that captured in the transformed data. 24. The system of claim 22 , wherein transforming the set of test data includes transforming the set of test data into dimension reduced GMM supervectors using Probabilistic Linear Discriminant Analysis (PLDA). | 0.733503 |
9,649,552 | 46 | 53 | 46. A non-transitory computer readable storage medium comprising instructions that, when executed on a system, cause the system to at least: cause generation of a graphical user interface operative to display an interactive mathematical puzzle having only one solution, the interactive puzzle including first areas of the puzzle having a plurality of clue regions and second areas of the puzzle having a plurality of mystery number regions, wherein the first areas of the puzzle and the second areas of the puzzle are in separate locations, wherein the plurality of clue regions include a pair clue region interposed between a pair of mystery number regions, wherein each of the mystery number regions corresponds to a mystery number value with no limitation on an amount of times a single mystery number value between 1-R appears in the puzzle when the puzzle is solved except that a same pair of mystery number values corresponding to the pair of mystery number regions interposing any pair clue region can only appear once in the puzzle, wherein R is a whole number within a range of whole number values, wherein the puzzle can only have one solution when each mystery number value associated with each mystery number region among the plurality of mystery numbers regions are solved, wherein the pair clue region corresponds to a pair plus clue representing an arithmetic sum of mystery number values of the mystery number regions interposing the pair clue region or a pair times clue representing an arithmetic product of mystery number values of the mystery number regions interposing the pair clue region, and wherein the puzzle layout is initially devoid of pair plus clues, pair times clues, and mystery number values; reveal at least one pair plus clue or one pair times clue within at least one pair clue region among the plurality of pair clue regions; enable a user to enter an integer value in place of each mystery number region through a number entry system; and indicate to the user whether the integer value entered by the user in each of the mystery number regions is correct. | 46. A non-transitory computer readable storage medium comprising instructions that, when executed on a system, cause the system to at least: cause generation of a graphical user interface operative to display an interactive mathematical puzzle having only one solution, the interactive puzzle including first areas of the puzzle having a plurality of clue regions and second areas of the puzzle having a plurality of mystery number regions, wherein the first areas of the puzzle and the second areas of the puzzle are in separate locations, wherein the plurality of clue regions include a pair clue region interposed between a pair of mystery number regions, wherein each of the mystery number regions corresponds to a mystery number value with no limitation on an amount of times a single mystery number value between 1-R appears in the puzzle when the puzzle is solved except that a same pair of mystery number values corresponding to the pair of mystery number regions interposing any pair clue region can only appear once in the puzzle, wherein R is a whole number within a range of whole number values, wherein the puzzle can only have one solution when each mystery number value associated with each mystery number region among the plurality of mystery numbers regions are solved, wherein the pair clue region corresponds to a pair plus clue representing an arithmetic sum of mystery number values of the mystery number regions interposing the pair clue region or a pair times clue representing an arithmetic product of mystery number values of the mystery number regions interposing the pair clue region, and wherein the puzzle layout is initially devoid of pair plus clues, pair times clues, and mystery number values; reveal at least one pair plus clue or one pair times clue within at least one pair clue region among the plurality of pair clue regions; enable a user to enter an integer value in place of each mystery number region through a number entry system; and indicate to the user whether the integer value entered by the user in each of the mystery number regions is correct. 53. The non-transitory computer readable storage medium as recited in claim 46 , wherein the graphical user interface is operative to provide the user with one or more hints including one or more pair plus clues or pair times clues for one or more of the pair clue regions. | 0.89941 |
8,935,150 | 1 | 2 | 1. A method for suggesting translation text comprising: receiving content for translation from a source language to a target language, and metadata describing a translation job; extracting an auto-suggest dictionary from translation units including sentence pairs comprising a sentence in a source language and a translation of the sentence in the target language; generating a translation package including the extracted auto-suggest dictionary and the received content and the metadata; sending the translation package to a remote device configured for assisting a user in translating the received content, the assisting including: displaying to a user a graphical user interface (GUI) containing the received content; receiving from the user one or more first characters of a translation of the displayed content; predicting a plurality of subsequent characters of the translation of the displayed content based on the auto-suggest dictionary and the metadata; displaying to the user the received one or more first characters and the plurality of subsequent characters of the translation; and receiving from the user a selection from the plurality of subsequent characters; receiving translation units of the source language content from the remote device, the translation units of the source language content based on the selection from the plurality of subsequent characters; and updating the auto-suggest dictionary from the received translation units of the source language content. | 1. A method for suggesting translation text comprising: receiving content for translation from a source language to a target language, and metadata describing a translation job; extracting an auto-suggest dictionary from translation units including sentence pairs comprising a sentence in a source language and a translation of the sentence in the target language; generating a translation package including the extracted auto-suggest dictionary and the received content and the metadata; sending the translation package to a remote device configured for assisting a user in translating the received content, the assisting including: displaying to a user a graphical user interface (GUI) containing the received content; receiving from the user one or more first characters of a translation of the displayed content; predicting a plurality of subsequent characters of the translation of the displayed content based on the auto-suggest dictionary and the metadata; displaying to the user the received one or more first characters and the plurality of subsequent characters of the translation; and receiving from the user a selection from the plurality of subsequent characters; receiving translation units of the source language content from the remote device, the translation units of the source language content based on the selection from the plurality of subsequent characters; and updating the auto-suggest dictionary from the received translation units of the source language content. 2. The method of claim 1 , further comprising monitoring keystrokes of a translator providing the one or more first characters. | 0.862256 |
8,793,249 | 1 | 6 | 1. A network device, comprising: a transceiver to send and receive data over a network; and a processor that is operative to perform actions, including: determining a plurality of document features for each document in a plurality of documents, wherein the plurality of documents include at least one document defined as having sufficient subject matter specificity, and at least one other document having insufficient subject matter specificity; training a document classifier based at least on the plurality of document features including at least a frequency of visual line breaks and a frequency of images for the at least one document having sufficient subject matter specificity; providing to the trained document classifier, the at least one other document, wherein the trained document classifier determines a first quality value for the at least one other document; if the first determined quality value of the at least one other document is above a quality threshold value, identifying the at least one other document to have sufficient subject matter specificity, and providing the at least one other document to a client device for display; if the first determined quality value of the at least one other document is at an unacceptable level, re-training the document classifier based on at least the plurality of features for the at least one other document; and if a second quality value of the at least one other document is determined by the retrained document classifier to be above the quality threshold, providing the at least one other document to the client device for display. | 1. A network device, comprising: a transceiver to send and receive data over a network; and a processor that is operative to perform actions, including: determining a plurality of document features for each document in a plurality of documents, wherein the plurality of documents include at least one document defined as having sufficient subject matter specificity, and at least one other document having insufficient subject matter specificity; training a document classifier based at least on the plurality of document features including at least a frequency of visual line breaks and a frequency of images for the at least one document having sufficient subject matter specificity; providing to the trained document classifier, the at least one other document, wherein the trained document classifier determines a first quality value for the at least one other document; if the first determined quality value of the at least one other document is above a quality threshold value, identifying the at least one other document to have sufficient subject matter specificity, and providing the at least one other document to a client device for display; if the first determined quality value of the at least one other document is at an unacceptable level, re-training the document classifier based on at least the plurality of features for the at least one other document; and if a second quality value of the at least one other document is determined by the retrained document classifier to be above the quality threshold, providing the at least one other document to the client device for display. 6. The network device of claim 1 , wherein the processor that is operative to perform actions, including: re-training the document classifier based at least in part on user feedback. | 0.717391 |
8,312,025 | 1 | 7 | 1. An information processing apparatus comprising: an information acquisition device configured to acquire a plurality of meta information items; a storage apparatus that stores a plurality of modules each having rules defined for creating a sort-ready text according to readings representative of how the corresponding acquired meta information item is read; a sort-ready text creation device configured to create automatically the sort-ready text for each of the meta information items acquired by use of at least one of the stored modules which includes rules applicable to predetermined conditions; and a sort execution device configured to sort each of said meta information items corresponding to each of said sort-ready texts based on the sort-ready text which has been created automatically for each of said meta information items, thereby automatically creating sorted meta information made up of a plurality of sorted meta information items; wherein, if each of the acquired meta information items is made up of at least two character types, then said sort execution device classifies the meta information items by each of said character types and sorts each of the classified meta information items based on the sort-ready text associated with the classified meta information item in question, thereby creating sorted meta information for each of said character types. | 1. An information processing apparatus comprising: an information acquisition device configured to acquire a plurality of meta information items; a storage apparatus that stores a plurality of modules each having rules defined for creating a sort-ready text according to readings representative of how the corresponding acquired meta information item is read; a sort-ready text creation device configured to create automatically the sort-ready text for each of the meta information items acquired by use of at least one of the stored modules which includes rules applicable to predetermined conditions; and a sort execution device configured to sort each of said meta information items corresponding to each of said sort-ready texts based on the sort-ready text which has been created automatically for each of said meta information items, thereby automatically creating sorted meta information made up of a plurality of sorted meta information items; wherein, if each of the acquired meta information items is made up of at least two character types, then said sort execution device classifies the meta information items by each of said character types and sorts each of the classified meta information items based on the sort-ready text associated with the classified meta information item in question, thereby creating sorted meta information for each of said character types. 7. The information processing apparatus according to claim 1 , wherein said initial information creation device merges the meta information items sorted by each of said character types and adds said initial information to each of said meta information items included in the merged sorted meta information, thereby creating the sorted meta information furnished with said initial information. | 0.617417 |
9,870,389 | 1 | 8 | 1. A computer system comprising: one or more hardware computer processors configured to execute code in order to cause the one or more hardware computer processors to: provide a user interface configured to display at least a first panel, a second panel, and a third panel, wherein: the first panel is configured to provide an analysis path visualization, the second panel is configured to provide one or more selectable elements for analyzing one or more data sets, and the third panel is configured to provide one or more data visualizations; in response to a first user input selecting a first selectable element of the one or more selectable elements: determine a first analysis type associated with the first selectable element; add a first data visualization to the third panel representing results of an analysis of the first analysis type of a data set; and add a first icon to the first panel representing the first analysis type associated with the first selectable element; and in response to a second user input selecting a second selectable element of the one or more selectable elements: determine a second analysis type associated with the second selectable element; add a second icon to the first panel representing the second analysis type associated with the second selectable element; and add an edge to the first panel connecting the first and second icons so as to visually indicate an analysis path. | 1. A computer system comprising: one or more hardware computer processors configured to execute code in order to cause the one or more hardware computer processors to: provide a user interface configured to display at least a first panel, a second panel, and a third panel, wherein: the first panel is configured to provide an analysis path visualization, the second panel is configured to provide one or more selectable elements for analyzing one or more data sets, and the third panel is configured to provide one or more data visualizations; in response to a first user input selecting a first selectable element of the one or more selectable elements: determine a first analysis type associated with the first selectable element; add a first data visualization to the third panel representing results of an analysis of the first analysis type of a data set; and add a first icon to the first panel representing the first analysis type associated with the first selectable element; and in response to a second user input selecting a second selectable element of the one or more selectable elements: determine a second analysis type associated with the second selectable element; add a second icon to the first panel representing the second analysis type associated with the second selectable element; and add an edge to the first panel connecting the first and second icons so as to visually indicate an analysis path. 8. The computer system of claim 1 , wherein the one or more hardware computer processors are configured to execute code in order to cause the one or more hardware computer processors to further: generate, based on the analysis path, a query to apply to the one or more data sets; and apply the query to the one or more data sets. | 0.754478 |
9,747,491 | 27 | 32 | 27. A handwriting verification method executed in a computer system, the method comprising: obtaining a test sample and a reference sample each containing a plurality of feature points, wherein each of the feature points includes: (i) geometric features including an x-coordinate value and a y-coordinate value, and (ii) a non-geometric feature; finding mappings between feature points of the test sample and feature points of the reference sample based on the geometric features of the test sample and reference sample, wherein the finding mappings comprises determining, based on a pseudo-random value, whether to (a) remove a mapping from a selected feature point in the reference sample, or (b) define a new mapping between the selected feature point in the reference sample and a selected feature point in the test sample; and after the finding mappings, comparing the non-geometric features of each of the mapped feature points of the test sample and the reference sample. | 27. A handwriting verification method executed in a computer system, the method comprising: obtaining a test sample and a reference sample each containing a plurality of feature points, wherein each of the feature points includes: (i) geometric features including an x-coordinate value and a y-coordinate value, and (ii) a non-geometric feature; finding mappings between feature points of the test sample and feature points of the reference sample based on the geometric features of the test sample and reference sample, wherein the finding mappings comprises determining, based on a pseudo-random value, whether to (a) remove a mapping from a selected feature point in the reference sample, or (b) define a new mapping between the selected feature point in the reference sample and a selected feature point in the test sample; and after the finding mappings, comparing the non-geometric features of each of the mapped feature points of the test sample and the reference sample. 32. The method of claim 27 , wherein the finding mappings is based on a count of consecutive unlinked feature points in the test sample. | 0.710638 |
9,608,916 | 1 | 6 | 1. A method for performing collaborative application classification in a system including a classification aggregator communicatively coupled to a plurality of traffic classifiers, the plurality of traffic classifiers including a first and second traffic classifier, the method comprising: receiving, at the classification aggregator, classification information from the first traffic classifier, the classification information including a destination Internet protocol (IP) address, a destination port number, a protocol and a first application name associated with a first communication flow classified by the first traffic classifier; storing the classification information in a data store of the classification aggregator, the data store containing multiple entries, each of the entries mapping a group of characteristics, including a destination IP address, a destination port number and a protocol, to a corresponding application name; receiving, at the classification aggregator, a query requesting an application name associated with a second communication flow from a second classifier; and providing the first application name, in response to determining that the second communication flow is associated with the first application name, to the second classifier, wherein determining that the second communication flow is associated with the first application name is based on one or more of the entries of the data store of the classification aggregator. | 1. A method for performing collaborative application classification in a system including a classification aggregator communicatively coupled to a plurality of traffic classifiers, the plurality of traffic classifiers including a first and second traffic classifier, the method comprising: receiving, at the classification aggregator, classification information from the first traffic classifier, the classification information including a destination Internet protocol (IP) address, a destination port number, a protocol and a first application name associated with a first communication flow classified by the first traffic classifier; storing the classification information in a data store of the classification aggregator, the data store containing multiple entries, each of the entries mapping a group of characteristics, including a destination IP address, a destination port number and a protocol, to a corresponding application name; receiving, at the classification aggregator, a query requesting an application name associated with a second communication flow from a second classifier; and providing the first application name, in response to determining that the second communication flow is associated with the first application name, to the second classifier, wherein determining that the second communication flow is associated with the first application name is based on one or more of the entries of the data store of the classification aggregator. 6. The method of claim 1 , further comprising deleting an entry of the data store if, during a period of time, no traffic classifier accesses that entry. | 0.802835 |
8,176,120 | 1 | 6 | 1. A method of composing a web page, comprising: at a server, transmitting an authoring web page including an embedded authoring tool to a client computer of a publisher of the web page using a network, the authoring tool for composing the web page; and receiving from the client computer web-page content corresponding to the composed web page, wherein the composed web page includes one or more advertisement regions that are placeholders designated for displaying one or more advertisements having one or more links to one or more content locations; and wherein the composed web page is configured for display at run-time at respective clients devices that download the composed web page from a web page server. | 1. A method of composing a web page, comprising: at a server, transmitting an authoring web page including an embedded authoring tool to a client computer of a publisher of the web page using a network, the authoring tool for composing the web page; and receiving from the client computer web-page content corresponding to the composed web page, wherein the composed web page includes one or more advertisement regions that are placeholders designated for displaying one or more advertisements having one or more links to one or more content locations; and wherein the composed web page is configured for display at run-time at respective clients devices that download the composed web page from a web page server. 6. The method of claim 1 , further comprising providing a financial incentive to the publisher of the composed web page in accordance with activation of one of the links associated with the one or more advertisements by a user of a client device that has downloaded the composed web page. | 0.727788 |
8,078,452 | 21 | 27 | 21. An article of manufacture comprising a storage device in the form of a memory or a computer readable disk, the storage device comprising programming instructions for identifying phrasal terms in a text, the programming instructions when executed causing a processing system to carry out steps comprising: receiving a text having a plurality of words; determining a plurality of context, wherein a context comprises one or more words proximate to another word in the text; for each context, determining a first frequency based on a number of occurrences of the context within the text; assigning a first rank to at least one context based on the first frequency for the at least one context; determining multiple word-context pairs; for each word-context pair, determining a second frequency based on a number of occurrences of the word associated with the word-context pair being used in the context; assigning a second rank to at least one word-context pair based on the second frequency for the at least one word-context pair; determining a rank ratio for each word-context pair based on the first rank and the second rank associated with the word-context pair; determining a mutual rank ratio based on multiple rank ratios; and identifying a phrasal term based on the mutual rank ratio. | 21. An article of manufacture comprising a storage device in the form of a memory or a computer readable disk, the storage device comprising programming instructions for identifying phrasal terms in a text, the programming instructions when executed causing a processing system to carry out steps comprising: receiving a text having a plurality of words; determining a plurality of context, wherein a context comprises one or more words proximate to another word in the text; for each context, determining a first frequency based on a number of occurrences of the context within the text; assigning a first rank to at least one context based on the first frequency for the at least one context; determining multiple word-context pairs; for each word-context pair, determining a second frequency based on a number of occurrences of the word associated with the word-context pair being used in the context; assigning a second rank to at least one word-context pair based on the second frequency for the at least one word-context pair; determining a rank ratio for each word-context pair based on the first rank and the second rank associated with the word-context pair; determining a mutual rank ratio based on multiple rank ratios; and identifying a phrasal term based on the mutual rank ratio. 27. The article of claim 21 , wherein at least one of the context comprises a gap. | 0.964098 |
8,908,969 | 17 | 18 | 17. A system comprising: a processor; and a memory coupled to the processor, the memory storing instructions which when executed by the processor causes the system to perform a method, the method comprising: obtaining an image of a document; detecting image objects on the image; matching by a processor the image objects to a predetermined document type, wherein image objects distinguish the document type from other document types, and wherein image objects include anchor elements; generating by the processor a flexible structure description corresponding to the predetermined document type based on the detected image objects, wherein the flexible structure description includes a set of search elements for each data field in the image of the document, each search element having an associated search criterion; searching, via a search algorithm, additional document images to determine a respective document type of the additional document images, wherein each of the additional document images are of a document type corresponding to the predetermined document type; modifying the flexible structure description based on said searching of additional document images, wherein the search algorithm is configured to detect data fields based on the flexible structure description, said data fields corresponding to the predetermined document type; and repeating said searching and modifying of the flexible structure description until a defined level of precision is achieved or exceeded. | 17. A system comprising: a processor; and a memory coupled to the processor, the memory storing instructions which when executed by the processor causes the system to perform a method, the method comprising: obtaining an image of a document; detecting image objects on the image; matching by a processor the image objects to a predetermined document type, wherein image objects distinguish the document type from other document types, and wherein image objects include anchor elements; generating by the processor a flexible structure description corresponding to the predetermined document type based on the detected image objects, wherein the flexible structure description includes a set of search elements for each data field in the image of the document, each search element having an associated search criterion; searching, via a search algorithm, additional document images to determine a respective document type of the additional document images, wherein each of the additional document images are of a document type corresponding to the predetermined document type; modifying the flexible structure description based on said searching of additional document images, wherein the search algorithm is configured to detect data fields based on the flexible structure description, said data fields corresponding to the predetermined document type; and repeating said searching and modifying of the flexible structure description until a defined level of precision is achieved or exceeded. 18. The system of claim 17 , wherein said modifying of the flexible document description includes adding a type element to the set of search elements for a data field corresponding to a data type associated with the data field. | 0.814845 |
9,984,161 | 7 | 11 | 7. A blog search engine data processing system comprising: a host server comprising memory and at least one processor and configured for coupling to different client computing devices over a computer communications network; a blog search engine executing in the memory of the host server and configured to query blog content according to different query terms; and, an authorship sensitive relevance module coupled to the blog search engine, the authorship sensitive relevance module comprising program code enabled upon execution in the memory of the host server to extract authorship criteria from a search engine query provided in a form completed by a user specifying both query terms to query World Wide Web (“Web”) content (“blog content”) and also authorship criteria for authors of blog content, to evaluate the authorship criteria for each blog author of corresponding blog content returned by the search engine query based upon a degree to which the blog author of the corresponding blog content is deemed both authoritative and trustworthy, blog authors of corresponding blog content determined to be more authoritative and trustworthy having a higher ranking than blog authors of the corresponding blog content determined to be less authoritative and trustworthy, to compute a relevance for each entry in a results set based upon the evaluated authorship criteria, wherein entries for blog authors of higher ranking are computed to have a higher relevance and entries for blog authors of lower ranking are computed to have a lower relevance, to sort the results set from an entry in the results set of highest relevance to an entry in the results set of lowest relevance and to present in order of relevance a listing of blog content corresponding to the results set, wherein the authorship criteria includes an indication of a degree to which a blog author of blog content in the results set is deemed both authoritative and trustworthy, wherein authoritativeness is computed by determining a number of others whom have subscribed to blog content authored by the blog author, and wherein trustworthiness is computed by at least one of determining whether the blog author is known to a querying end user through inclusion in a list of contacts for the end user and frequent communications exchanged by the end user with the blog author, the blog author being a writer of blog content; and, wherein the program code of the module further extracts from the search engine query provided in the form completed by the user, content criteria for the blog content in the respective entries of the results set returned by the search engine query, evaluates the content criteria for blog content returned by the search engine query, and computes the relevance for each entry in the results set based both upon the evaluated authorship criteria and also the evaluated content criteria. | 7. A blog search engine data processing system comprising: a host server comprising memory and at least one processor and configured for coupling to different client computing devices over a computer communications network; a blog search engine executing in the memory of the host server and configured to query blog content according to different query terms; and, an authorship sensitive relevance module coupled to the blog search engine, the authorship sensitive relevance module comprising program code enabled upon execution in the memory of the host server to extract authorship criteria from a search engine query provided in a form completed by a user specifying both query terms to query World Wide Web (“Web”) content (“blog content”) and also authorship criteria for authors of blog content, to evaluate the authorship criteria for each blog author of corresponding blog content returned by the search engine query based upon a degree to which the blog author of the corresponding blog content is deemed both authoritative and trustworthy, blog authors of corresponding blog content determined to be more authoritative and trustworthy having a higher ranking than blog authors of the corresponding blog content determined to be less authoritative and trustworthy, to compute a relevance for each entry in a results set based upon the evaluated authorship criteria, wherein entries for blog authors of higher ranking are computed to have a higher relevance and entries for blog authors of lower ranking are computed to have a lower relevance, to sort the results set from an entry in the results set of highest relevance to an entry in the results set of lowest relevance and to present in order of relevance a listing of blog content corresponding to the results set, wherein the authorship criteria includes an indication of a degree to which a blog author of blog content in the results set is deemed both authoritative and trustworthy, wherein authoritativeness is computed by determining a number of others whom have subscribed to blog content authored by the blog author, and wherein trustworthiness is computed by at least one of determining whether the blog author is known to a querying end user through inclusion in a list of contacts for the end user and frequent communications exchanged by the end user with the blog author, the blog author being a writer of blog content; and, wherein the program code of the module further extracts from the search engine query provided in the form completed by the user, content criteria for the blog content in the respective entries of the results set returned by the search engine query, evaluates the content criteria for blog content returned by the search engine query, and computes the relevance for each entry in the results set based both upon the evaluated authorship criteria and also the evaluated content criteria. 11. The system of claim 7 , wherein the content criteria comprises a number of page views for corresponding blog content. | 0.660112 |
8,903,813 | 7 | 12 | 7. A computer program product for identifying non-synthetic event elements in electronic files, the computer program product comprising: a non-transitory computer readable storage media; first program instructions to receive, from a requesting computer, a first set of binary data that describes a synthetic event, wherein the synthetic event is a non-executable descriptor of a set of context-related factors; second program instructions to perform a context-based search of a database of electronic files to identify a relevant electronic file, wherein the relevant electronic file comprises the synthetic event; third program instructions to search the relevant electronic file for at least one non-synthetic event element, wherein the non-synthetic event element is absent from the synthetic event; fourth program instructions to, in response to determining that the relevant electronic file comprises said at least one non-synthetic event, transmit a second set of binary data to the requesting computer, wherein the second set of binary data comprises the relevant electronic file and a description of an identified non-synthetic event element within the relevant electronic file; fifth program instructions to limit the context-based search to search only files that are not related to activities that generated the synthetic event, wherein an activity that generated the synthetic event was medical disease research, and wherein the context-based search is limited to searching non-medical literature; and sixth program instructions to establish a connection between the synthetic event and non-synthetic event elements found in the non-medical literature; and wherein the first, second, third, fourth, fifth, and sixth program instructions are stored on the non-transitory computer readable storage media. | 7. A computer program product for identifying non-synthetic event elements in electronic files, the computer program product comprising: a non-transitory computer readable storage media; first program instructions to receive, from a requesting computer, a first set of binary data that describes a synthetic event, wherein the synthetic event is a non-executable descriptor of a set of context-related factors; second program instructions to perform a context-based search of a database of electronic files to identify a relevant electronic file, wherein the relevant electronic file comprises the synthetic event; third program instructions to search the relevant electronic file for at least one non-synthetic event element, wherein the non-synthetic event element is absent from the synthetic event; fourth program instructions to, in response to determining that the relevant electronic file comprises said at least one non-synthetic event, transmit a second set of binary data to the requesting computer, wherein the second set of binary data comprises the relevant electronic file and a description of an identified non-synthetic event element within the relevant electronic file; fifth program instructions to limit the context-based search to search only files that are not related to activities that generated the synthetic event, wherein an activity that generated the synthetic event was medical disease research, and wherein the context-based search is limited to searching non-medical literature; and sixth program instructions to establish a connection between the synthetic event and non-synthetic event elements found in the non-medical literature; and wherein the first, second, third, fourth, fifth, and sixth program instructions are stored on the non-transitory computer readable storage media. 12. The computer program product of claim 7 , further comprising: seventh program instructions to rank a source of the relevant electronic file, wherein the ranking is based on a public reputation of the source; and eighth program instructions to weight the identified non-synthetic event element based on said ranking; and wherein the seventh and eighth program instructions are stored on the non-transitory computer readable storage media. | 0.586304 |
6,081,774 | 1 | 2 | 1. An information retrieval system using natural language queries to retrieve information from a language-based database containing one or more files, comprising: a non-real-time development system for automatically creating a database index having one or more content-based database keywords of the database; and a real-time retrieval system that, in response to a user's natural language queries, searches said database index for one or more content-based query keywords derived from a natural language query, wherein said development system and said retrieval system morphologically, syntactically and linguistically analyze said language-based database and said natural language query, respectively, to generate said one or more database keywords and query keywords representing the content of said language-based database and said natural language query, respectively. | 1. An information retrieval system using natural language queries to retrieve information from a language-based database containing one or more files, comprising: a non-real-time development system for automatically creating a database index having one or more content-based database keywords of the database; and a real-time retrieval system that, in response to a user's natural language queries, searches said database index for one or more content-based query keywords derived from a natural language query, wherein said development system and said retrieval system morphologically, syntactically and linguistically analyze said language-based database and said natural language query, respectively, to generate said one or more database keywords and query keywords representing the content of said language-based database and said natural language query, respectively. 2. The information retrieval system of claim 1, wherein said development system comprises: a software development system for creating said database index utilizing a pattern dictionary that includes synonyms and skip words and a morphosyntactic dictionary that includes morphological and syntactic information for words in the natural language of the language-based database and natural language query. | 0.5 |
7,865,491 | 1 | 3 | 1. A computer-readable storage medium containing a program, which when executed on a computer system performs an operation for accessing data stored in an underlying physical database, comprising: receiving a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in an underlying database; retrieving, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and performing the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation. | 1. A computer-readable storage medium containing a program, which when executed on a computer system performs an operation for accessing data stored in an underlying physical database, comprising: receiving a user request to perform a model entity operation, wherein the user request includes a user selection of a first instance of a model entity selected from a plurality of instances of the model entity included in a first query result and a selected query operation, wherein the model entity is defined by a database abstraction model logically describing an underlying database and wherein the model entity defines a focus for the selected query operation, and wherein instances of the model entity are distinguished by an identifier in an underlying database; retrieving, in response to the user request, a linking function configured to identify instances of the model entity that are related to the first instance of the model entity, according to a predefined relationship; and performing the model entity operation by: invoking the linking function to retrieve any instances of the model entity that are related to the first instance of the model entity; executing the selected query operation against the retrieved instances of the model entity; and returning, as a second query result, at least a second instance of the model entity that satisfies any conditions specified by the selected query operation. 3. The computer-readable storage medium of claim 1 , wherein the first instance of the model entity is selected from a display of query results retrieved in response to executing an abstract query, wherein the abstract query is composed from a plurality of logical fields defined by the database abstraction model, wherein each logical field specifies a mapping for a logical field to data in the underlying physical database. | 0.5 |
10,102,245 | 6 | 13 | 6. The method of claim 1 , wherein the search query input is received from the first user through a query filed, and wherein the suggested queries are displayed to the first user in a drop-down menu associated with the query field while the first user inputs characters into the query field. | 6. The method of claim 1 , wherein the search query input is received from the first user through a query filed, and wherein the suggested queries are displayed to the first user in a drop-down menu associated with the query field while the first user inputs characters into the query field. 13. The method of claim 6 , wherein the suggested queries comprise one or more elements associated with the identified terms for one or more matching objects, wherein the elements comprise one or more of: a name string; a description; a metadata; a link to a webpage; a reference to the matching objects; a Uniform Resource Locators (URLs) for the matching objects, or a mechanisms for retrieving the Uniform Resource Locators (URLs). | 0.5 |
7,865,362 | 1 | 16 | 1. A method for recognizing speech, the method comprising the steps of: analyzing speech input with an apparatus using at least one hardware-implemented processor to generate a hypothesis and a confidence factor associated with the hypothesis; comparing said confidence factor to an acceptance threshold for accepting or rejecting the hypothesis; and comparing the hypothesis to an expected response, and if the comparison is favorable, adjusting the acceptance threshold in order to affect the acceptance of the hypothesis. | 1. A method for recognizing speech, the method comprising the steps of: analyzing speech input with an apparatus using at least one hardware-implemented processor to generate a hypothesis and a confidence factor associated with the hypothesis; comparing said confidence factor to an acceptance threshold for accepting or rejecting the hypothesis; and comparing the hypothesis to an expected response, and if the comparison is favorable, adjusting the acceptance threshold in order to affect the acceptance of the hypothesis. 16. The method of claim 1 wherein the comparison is favorable when the hypothesis semantically matches the expected response. | 0.737395 |
6,154,212 | 4 | 5 | 4. The method of claim 1 wherein the step of generating the network view portion of the network interface further includes the steps of: retrieving one or more network data structures from the database; utilizing a given one of the network base classes to generate functions common to multiple views; and utilizing a given one of the display classes derived from the given network base class to generate operations specific to a particular view. | 4. The method of claim 1 wherein the step of generating the network view portion of the network interface further includes the steps of: retrieving one or more network data structures from the database; utilizing a given one of the network base classes to generate functions common to multiple views; and utilizing a given one of the display classes derived from the given network base class to generate operations specific to a particular view. 5. The method of claim 4 wherein the given display class is inherited from the corresponding network base class by overloading at least one C++ function in the network base class. | 0.735988 |
9,596,246 | 5 | 6 | 5. The method of claim 4 wherein the application is provided by an independent software vendor (ISV) that provides the application hosted on the server computer for use by the organization. | 5. The method of claim 4 wherein the application is provided by an independent software vendor (ISV) that provides the application hosted on the server computer for use by the organization. 6. The method of claim 5 wherein the authorized user comprises an ISV support representative performing maintenance functions for the hosted application, and wherein the ISV support representative is granted privileges allowing the support representative to view and modify the metadata in relation to performing debugging functions on the application. | 0.5 |
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