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8,429,740 | 1 | 8 | 1. A search result presentation system, the search result presentation system comprising: one or more processors; system memory; a database comprising tagged data, said tagged data tagged from one or more documents, for each of said one or more documents, said tagged data identifying items in said document for which said document may be searched and also identifying portions of said document that are eligible for alteration, based on classification of said identified portions, when presented to a user that does not have access to the entire document contents; an information retrieval system that: receives a search request from a user, said search request comprising search terms; and searches for said search terms in said database to identify a plurality of search results, said search results comprising references to the one or more documents; and a presentation engine for presenting the plurality of search results that: identifies a search result from within said plurality of search results, said search result for a document from among the one or more documents, said search result referencing a first tagged portion and a second tagged portion of said document; determines that said user has access privileges to at least a portion of said document based on an access policy; determines that said user does not have access to said first tagged portion of said document based on classification of the first tagged portion and based on the access policy; alters said search result so that said tagged first portion is not presented as part of said search result; and transmits said altered search result, including said second tagged portion of the document for presentation to said user. | 1. A search result presentation system, the search result presentation system comprising: one or more processors; system memory; a database comprising tagged data, said tagged data tagged from one or more documents, for each of said one or more documents, said tagged data identifying items in said document for which said document may be searched and also identifying portions of said document that are eligible for alteration, based on classification of said identified portions, when presented to a user that does not have access to the entire document contents; an information retrieval system that: receives a search request from a user, said search request comprising search terms; and searches for said search terms in said database to identify a plurality of search results, said search results comprising references to the one or more documents; and a presentation engine for presenting the plurality of search results that: identifies a search result from within said plurality of search results, said search result for a document from among the one or more documents, said search result referencing a first tagged portion and a second tagged portion of said document; determines that said user has access privileges to at least a portion of said document based on an access policy; determines that said user does not have access to said first tagged portion of said document based on classification of the first tagged portion and based on the access policy; alters said search result so that said tagged first portion is not presented as part of said search result; and transmits said altered search result, including said second tagged portion of the document for presentation to said user. 8. The system of claim 1 , wherein tagged data identifying portions of a document for alteration comprises tagged data identifying portions of a document for alteration based on classifying the identified portions as sensitive data. | 0.842177 |
8,131,559 | 1 | 8 | 1. A method of accepting documents for publication at a server wherein shares in a first document are traded using tokens in a virtual market place, and participants in the virtual market place each own one or more tokens in the virtual market place, the method comprising: receiving from a submitting participant the first document; receiving a request from one or more purchasing participants to purchase shares in the first document, subtracting, at the server, one or more tokens from an account of the one or more purchasing participants and adding shares in the first document to the account of the one or more purchasing participants; accepting the first document for publication after a predetermined amount of shares in the first document are purchased in a predetermined period; and adding tokens to an account of at least one participant that owns shares in a second document cited in the first document. | 1. A method of accepting documents for publication at a server wherein shares in a first document are traded using tokens in a virtual market place, and participants in the virtual market place each own one or more tokens in the virtual market place, the method comprising: receiving from a submitting participant the first document; receiving a request from one or more purchasing participants to purchase shares in the first document, subtracting, at the server, one or more tokens from an account of the one or more purchasing participants and adding shares in the first document to the account of the one or more purchasing participants; accepting the first document for publication after a predetermined amount of shares in the first document are purchased in a predetermined period; and adding tokens to an account of at least one participant that owns shares in a second document cited in the first document. 8. The method according to claim 1 , wherein the method further comprises the step of adding shares in the first document to the account of the submitting participant. | 0.858953 |
9,454,957 | 5 | 12 | 5. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining first speech recognition results related to an utterance of a user; processing the first speech recognition results to identify: a first named entity; and a second named entity; determining that the first named entity is associated with the second named entity; performing a search of a data store for the first named entity and the second named entity, wherein the data store comprises a plurality of resolved named entities and information indicating relationships between resolved named entities in the plurality of resolved named entities; determining, from the search of the data store, that the first named entity corresponds to a first resolved named entity and that the second named entity corresponds to a second resolved named entity, wherein the information of the data store indicates that the first resolved named entity is related to the second resolved named entity; determining that a confidence score associated with the first resolved named entity meets or exceeds a threshold confidence score; obtaining second speech recognition results based on the first resolved name entity; and generating a response based at least partly on the second speech recognition results. | 5. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining first speech recognition results related to an utterance of a user; processing the first speech recognition results to identify: a first named entity; and a second named entity; determining that the first named entity is associated with the second named entity; performing a search of a data store for the first named entity and the second named entity, wherein the data store comprises a plurality of resolved named entities and information indicating relationships between resolved named entities in the plurality of resolved named entities; determining, from the search of the data store, that the first named entity corresponds to a first resolved named entity and that the second named entity corresponds to a second resolved named entity, wherein the information of the data store indicates that the first resolved named entity is related to the second resolved named entity; determining that a confidence score associated with the first resolved named entity meets or exceeds a threshold confidence score; obtaining second speech recognition results based on the first resolved name entity; and generating a response based at least partly on the second speech recognition results. 12. The computer-implemented method of claim 5 , wherein: the first speech recognition results comprise a plurality of candidate transcriptions of the utterance, each of the plurality of candidate transcriptions associated with a confidence score, and generating second speech recognition results based on the first resolved name entity comprises causing rescoring of a confidence score of a candidate transcription of the plurality of candidate transcriptions based at least partly on the first resolved named entity. | 0.719393 |
9,342,605 | 9 | 10 | 9. The method of claim 1 , wherein the past-search results comprise one or more past-search network resources determined based on a second-user search query associated with one or more of the second users. | 9. The method of claim 1 , wherein the past-search results comprise one or more past-search network resources determined based on a second-user search query associated with one or more of the second users. 10. The method of claim 9 , further comprising: determining one or more network resources from the past-search network resources that are relevant to the search query of the first user of the online social network; and displaying, at the client device, one or more of the network resources from the past-search network resources in addition to the one or more network resources that correspond to the search query of the first user. | 0.5 |
7,593,846 | 22 | 33 | 22. A computer-readable storage medium having computer-executable instructions, which when executed by a processor comprises: receiving input text; tokenizing the input text into portions of text; processing each portion of the text to provide indications of the meaning of at least some portion of the input text, wherein processing includes forming a self-describing fragment for each portion, the self-describing fragment being based on a hierarchical schema defining a domain with at least one top-level node and child nodes, wherein each self-describing fragment includes one or more indications of the nodes to form a hierarchical context with respect to the domain for each corresponding portion and positional information of words forming the corresponding portion in the input text; and combining one or more self-describing fragments to form one or more semantic solutions, each semantic solution being a potential meaning of at least a portion of the input text. | 22. A computer-readable storage medium having computer-executable instructions, which when executed by a processor comprises: receiving input text; tokenizing the input text into portions of text; processing each portion of the text to provide indications of the meaning of at least some portion of the input text, wherein processing includes forming a self-describing fragment for each portion, the self-describing fragment being based on a hierarchical schema defining a domain with at least one top-level node and child nodes, wherein each self-describing fragment includes one or more indications of the nodes to form a hierarchical context with respect to the domain for each corresponding portion and positional information of words forming the corresponding portion in the input text; and combining one or more self-describing fragments to form one or more semantic solutions, each semantic solution being a potential meaning of at least a portion of the input text. 33. The computer-readable storage medium of claim 22 wherein the schema includes encoded text of the domain contemplated to be in the input text, and wherein each node has associated encoded text therewith, and wherein processing includes analyzing each portion to identify if the portion comprises the encoded text, the encoded text being used to identify a node for the hierarchal context of the self-describing fragment. | 0.5 |
9,727,330 | 4 | 6 | 4. The method of claim 1 , wherein the build configuration object comprises an object that defines a build process for the application, and wherein the build configuration object takes as input the source files and the identified build image and generates a new application image. | 4. The method of claim 1 , wherein the build configuration object comprises an object that defines a build process for the application, and wherein the build configuration object takes as input the source files and the identified build image and generates a new application image. 6. The method of claim 4 , wherein the deployment configuration object is further to: determine that the image declares a volume; and match the volume to attached storage in the multi-tenant PaaS system, the attached storage to provide persistent storage for the application located at a file path defined by the volume declaration. | 0.558511 |
8,346,770 | 16 | 22 | 16. A system comprising: one or more processors to: receive a search query that includes one or more keywords; obtain a geographical identifier; determine a geographic location based, at least in part, on the geographical identifier, identify an area of interest within a certain distance of the geographic location, where the certain distance is dynamically determined based, at least in part, on the one or more keywords; identify documents that are associated with addresses located within the area of interest; determine ones of the identified documents that match the one or more keywords as relevant documents; group the relevant documents into one or more clusters based, at least in part, on the addresses associated with the relevant documents, each of the one or more clusters corresponding to a different one of the addresses; score the relevant documents based on at least one of a distance factor or a relevancy factor, the distance factor for a first of the relevant documents being based, at least in part, on a distance that an address associated with the first of the relevant documents is from the geographic center of the area of interest and the relevancy factor for a second of the relevant documents being based, at least in part, on a number of the one or more keywords present in the second of the relevant documents or a measure of how prominently the one or more keywords appear in the second of the relevant documents; rank the relevant documents within each of the one or more clusters based, at least in part, on the scoring; and present the one or more clusters. | 16. A system comprising: one or more processors to: receive a search query that includes one or more keywords; obtain a geographical identifier; determine a geographic location based, at least in part, on the geographical identifier, identify an area of interest within a certain distance of the geographic location, where the certain distance is dynamically determined based, at least in part, on the one or more keywords; identify documents that are associated with addresses located within the area of interest; determine ones of the identified documents that match the one or more keywords as relevant documents; group the relevant documents into one or more clusters based, at least in part, on the addresses associated with the relevant documents, each of the one or more clusters corresponding to a different one of the addresses; score the relevant documents based on at least one of a distance factor or a relevancy factor, the distance factor for a first of the relevant documents being based, at least in part, on a distance that an address associated with the first of the relevant documents is from the geographic center of the area of interest and the relevancy factor for a second of the relevant documents being based, at least in part, on a number of the one or more keywords present in the second of the relevant documents or a measure of how prominently the one or more keywords appear in the second of the relevant documents; rank the relevant documents within each of the one or more clusters based, at least in part, on the scoring; and present the one or more clusters. 22. The system of claim 16 , where, when grouping the relevant documents into one or more clusters, the one or more processors are further to: identify a first address associated with a first one of the relevant documents, determine one or more second ones of the relevant documents that are also associated with the first address, and group the first of the relevant documents and the one or more second relevant documents into a cluster. | 0.5 |
9,652,496 | 17 | 18 | 17. A system comprising: one or more first computers and one or more first storage devices storing instructions that are operable, when executed by the one or more first computers, to cause the one or more first computers to implement a join operator node that is operable to compute, according to a predicate expression in a query, a join result of pairs of first tuples of a first table and second tuples of a second table that have matching values, including matching first values of a first attribute of the first table, and matching second values of a second attribute of the second table, wherein the second table is partitioned by the second attribute of the second table; one or more second computers and one or more second storage devices storing instructions that are operable, when executed by the one or more second computers, to cause the one or more second computers to implement a table scanner node that is operable to obtain the first tuples of the first table from storage and provides the obtained first tuples to a partition selector node; one or more third computers and one or more third storage devices storing instructions that are operable, when executed by the one or more third computers, to cause the one or more third computers to implement a partition selector node that is operable to determine, according to a partition selection function for the second table, one or more partitions of the second table that may include second tuples having respective second values that match first values of the first tuples for the first attribute, and provide respective identifiers for the one or more partitions of the second table to a dynamic scanner node; one or more fourth computers and one or more fourth storage devices storing instructions that are operable, when executed by the one or more fourth computers, to cause the one or more fourth computers to implement a dynamic scanner node that is operable to receive, from the partition selector node, respective identifiers of the one or more partitions of the second table, obtain, using the respective identifiers of the one or more partitions of the second table, the second tuples of the one or more partitions from storage, and provide the obtained second tuples to the join operator node for use in computing the join result; and one or more fifth computers and one or more fifth storage devices storing instructions that are operable, when executed by the one or more fifth computers, to cause the one or more fifth computers to implement a master node that is operable to generate, using a representation of a query plan for the query, a modified query plan for the query that comprises a plurality of operators that, when executed by one or more computing nodes, cause the one or more computing nodes to compute a result for the query, wherein the modified query plan includes a join operator that represents the join operator node, a table scanner operator that represents the table scanner node, a partition selector operator that represents the partition selector node, and a dynamic scan operator that represents the dynamic scanner node; and wherein the master node is operable to generate the modified query plan by performing operations comprising: determining that the dynamic scan operator is defined in a subtree on an outer side of the join operator; and in response to determining that the dynamic scan operator is defined a subtree on the outer side of the join operator, pushing the partition selector operator to the subtree on the outer side of the join operator. | 17. A system comprising: one or more first computers and one or more first storage devices storing instructions that are operable, when executed by the one or more first computers, to cause the one or more first computers to implement a join operator node that is operable to compute, according to a predicate expression in a query, a join result of pairs of first tuples of a first table and second tuples of a second table that have matching values, including matching first values of a first attribute of the first table, and matching second values of a second attribute of the second table, wherein the second table is partitioned by the second attribute of the second table; one or more second computers and one or more second storage devices storing instructions that are operable, when executed by the one or more second computers, to cause the one or more second computers to implement a table scanner node that is operable to obtain the first tuples of the first table from storage and provides the obtained first tuples to a partition selector node; one or more third computers and one or more third storage devices storing instructions that are operable, when executed by the one or more third computers, to cause the one or more third computers to implement a partition selector node that is operable to determine, according to a partition selection function for the second table, one or more partitions of the second table that may include second tuples having respective second values that match first values of the first tuples for the first attribute, and provide respective identifiers for the one or more partitions of the second table to a dynamic scanner node; one or more fourth computers and one or more fourth storage devices storing instructions that are operable, when executed by the one or more fourth computers, to cause the one or more fourth computers to implement a dynamic scanner node that is operable to receive, from the partition selector node, respective identifiers of the one or more partitions of the second table, obtain, using the respective identifiers of the one or more partitions of the second table, the second tuples of the one or more partitions from storage, and provide the obtained second tuples to the join operator node for use in computing the join result; and one or more fifth computers and one or more fifth storage devices storing instructions that are operable, when executed by the one or more fifth computers, to cause the one or more fifth computers to implement a master node that is operable to generate, using a representation of a query plan for the query, a modified query plan for the query that comprises a plurality of operators that, when executed by one or more computing nodes, cause the one or more computing nodes to compute a result for the query, wherein the modified query plan includes a join operator that represents the join operator node, a table scanner operator that represents the table scanner node, a partition selector operator that represents the partition selector node, and a dynamic scan operator that represents the dynamic scanner node; and wherein the master node is operable to generate the modified query plan by performing operations comprising: determining that the dynamic scan operator is defined in a subtree on an outer side of the join operator; and in response to determining that the dynamic scan operator is defined a subtree on the outer side of the join operator, pushing the partition selector operator to the subtree on the outer side of the join operator. 18. The system of claim 17 , wherein the partition selector node provides the first tuples to the join operator node. | 0.87 |
8,744,607 | 7 | 8 | 7. The method of claim 6 , further comprising learning a set of relationships associated with product output based on the modifying of the initial recipe. | 7. The method of claim 6 , further comprising learning a set of relationships associated with product output based on the modifying of the initial recipe. 8. The method of claim 7 , further comprising generating an adjusted recipe to accomplish the target product output based at least in part on the set of relationships. | 0.5 |
7,685,514 | 54 | 55 | 54. An apparatus for processing a document, comprising: receiving means for receiving a first web document; receiving means for receiving a request to change a font attribute within the first document; receiving means for receiving a request to display page break indicators within the first web document; identifying means for identifying page break information for the first web document for an output device; and creating means for creating in a web browser a second web document from the first web document, wherein virtual font indicators are inserted into the second web document before and after text within the second web document, wherein at least one virtual page break indicator is inserted into the second web document, in response to the page break information, to indicate the location of page breaks, wherein the first web document and the second web document are markup language documents, and wherein identifying the page break information comprises identifying a location of the page break based on page setup information, document formatting information, and document content. | 54. An apparatus for processing a document, comprising: receiving means for receiving a first web document; receiving means for receiving a request to change a font attribute within the first document; receiving means for receiving a request to display page break indicators within the first web document; identifying means for identifying page break information for the first web document for an output device; and creating means for creating in a web browser a second web document from the first web document, wherein virtual font indicators are inserted into the second web document before and after text within the second web document, wherein at least one virtual page break indicator is inserted into the second web document, in response to the page break information, to indicate the location of page breaks, wherein the first web document and the second web document are markup language documents, and wherein identifying the page break information comprises identifying a location of the page break based on page setup information, document formatting information, and document content. 55. The apparatus of claim 54 , further comprising: removing means for removing the at least one virtual page break indicator; and printing means for printing the second web document. | 0.585973 |
9,729,717 | 10 | 11 | 10. The method of claim 1 , comprising evaluating the at least one voice interaction which includes providing a script compliance module accessible via a user interface and a communications network, the communications network including at least one of an analog telephone, a digital telephone, an internet-based network, a wireless network, and a selected voice communications supporting network. | 10. The method of claim 1 , comprising evaluating the at least one voice interaction which includes providing a script compliance module accessible via a user interface and a communications network, the communications network including at least one of an analog telephone, a digital telephone, an internet-based network, a wireless network, and a selected voice communications supporting network. 11. The method of claim 10 , comprising converting the at least one voice interaction received via the communications network into at least one digital signal comprising at least one spectral representation of the at least one voice interaction. | 0.5 |
8,755,912 | 1 | 2 | 1. A handheld apparatus for processing voice input, the apparatus comprising: a computer resource that is operable in a command-mode and in a text-entry mode; a display screen coupled to the computer resource; a component coupled to the computer resource and operable by the user in order to selectively switch operation of the computer resource between the command-mode and the text-entry mode; wherein the computer resource operable to execute a plurality of applications; wherein in the text-entry mode, the computer resource is operable to process voice input as text entry that is displayed on the display screen; wherein in the command-mode, the computer resource is operable to process voice input as a command for controlling at least one of (i) the computer resource, (ii) individual applications in the plurality of applications that are being executed by the computing resource, or (iii) one or more devices that communicate with the computer resource, wherein the component is touch-sensitive. | 1. A handheld apparatus for processing voice input, the apparatus comprising: a computer resource that is operable in a command-mode and in a text-entry mode; a display screen coupled to the computer resource; a component coupled to the computer resource and operable by the user in order to selectively switch operation of the computer resource between the command-mode and the text-entry mode; wherein the computer resource operable to execute a plurality of applications; wherein in the text-entry mode, the computer resource is operable to process voice input as text entry that is displayed on the display screen; wherein in the command-mode, the computer resource is operable to process voice input as a command for controlling at least one of (i) the computer resource, (ii) individual applications in the plurality of applications that are being executed by the computing resource, or (iii) one or more devices that communicate with the computer resource, wherein the component is touch-sensitive. 2. The apparatus of claim 1 , wherein the component is a touch pad. | 0.605882 |
5,583,988 | 36 | 38 | 36. A method for performing runtime checking on arguments passed to external libraries in a compiled programming environment, comprising the steps of: inserting argument restrictions into a source code file; generating argument runtime checking code based on said inserted argument restrictions; linking said argument runtime checking code to a library; executing a program which includes one or more calls to functions in said library, wherein said one or more calls to said functions in said library pass one or more arguments to said functions in said library; executing said argument runtime checking code to determine if said one or more arguments passed to said functions in said library violate said argument restrictions; reporting an error if said one or more arguments passed to said functions in said library violate said argument restrictions. | 36. A method for performing runtime checking on arguments passed to external libraries in a compiled programming environment, comprising the steps of: inserting argument restrictions into a source code file; generating argument runtime checking code based on said inserted argument restrictions; linking said argument runtime checking code to a library; executing a program which includes one or more calls to functions in said library, wherein said one or more calls to said functions in said library pass one or more arguments to said functions in said library; executing said argument runtime checking code to determine if said one or more arguments passed to said functions in said library violate said argument restrictions; reporting an error if said one or more arguments passed to said functions in said library violate said argument restrictions. 38. The method of claim 36, wherein said step of generating comprises generating argument runtime checking object code; and wherein said step of linking comprises linking said argument runtime checking object code with object code of said library. | 0.777076 |
9,305,226 | 1 | 2 | 1. A system, comprising: at least one processor; and memory device including instructions that, when executed by the at least one processor, cause the system to: obtain an image including text; process the image with a text recognition algorithm to produce text string data, the text string data including at least two options for at least one portion of the text string, each of the at least two options having a respective confidence value; process the text string data using a rule decision tree, the rule decision tree including a plurality of hierarchical nodes, at least a portion of the hierarchical nodes corresponding to a respective semantic boosting rule, wherein processing the text string using the decision tree includes, for at least one node of the nodes in the decision tree: determine that a pre-condition is satisfied for the semantic boosting rule, for a first node of the decision tree, with respect to the text string; apply the semantic boosting rule for the first node to the text string in response to determining that the pre-condition is satisfied, the applying of the semantic boosting rule causing in at least one confidence value for the text string to be adjusted and a refined version of the text string to be generated; and upon receiving the refined version of the text string, provide the refined version as recognized text for the image. | 1. A system, comprising: at least one processor; and memory device including instructions that, when executed by the at least one processor, cause the system to: obtain an image including text; process the image with a text recognition algorithm to produce text string data, the text string data including at least two options for at least one portion of the text string, each of the at least two options having a respective confidence value; process the text string data using a rule decision tree, the rule decision tree including a plurality of hierarchical nodes, at least a portion of the hierarchical nodes corresponding to a respective semantic boosting rule, wherein processing the text string using the decision tree includes, for at least one node of the nodes in the decision tree: determine that a pre-condition is satisfied for the semantic boosting rule, for a first node of the decision tree, with respect to the text string; apply the semantic boosting rule for the first node to the text string in response to determining that the pre-condition is satisfied, the applying of the semantic boosting rule causing in at least one confidence value for the text string to be adjusted and a refined version of the text string to be generated; and upon receiving the refined version of the text string, provide the refined version as recognized text for the image. 2. The system of claim 1 , wherein the instructions when executed further cause the system to: determine that the text string is the refined version in response to at least one of an overall confidence value for the text string data being equal to, or greater than, a minimum confidence value or each applicable rule of the decision tree being applied to the text string data. | 0.5 |
7,555,743 | 6 | 8 | 6. The method as set forth in claim 1 wherein the SNMP agent framework includes an SNMP table management object framework class, an object identifier converter class, an SNMP object stream class, an SNMP object stream finder class, an SNMP toolkit class, an SNMP table class, a managed object framework agent class, an SNMP table MAS class, and an object stream class. | 6. The method as set forth in claim 1 wherein the SNMP agent framework includes an SNMP table management object framework class, an object identifier converter class, an SNMP object stream class, an SNMP object stream finder class, an SNMP toolkit class, an SNMP table class, a managed object framework agent class, an SNMP table MAS class, and an object stream class. 8. The method as set forth in claim 6 wherein the object identifier converter class includes at least one of a $MOI2OID component, a $OID2MOI component, a setDNkey component, a getOIDindex component, a registerLeaf_AttrName component, a registerIndexLevel component, a registerConvTable component, and a deregisterConvTable component. | 0.514535 |
9,244,979 | 11 | 14 | 11. A method for estimating a cost of executing a query that targets a portion of XML data, the method comprising: storing summary data that is separate from the XML data and that indicates (a) a number of each element of a plurality of elements of an XML document that is part of the XML data and (b) a hierarchical relationship among the plurality of elements; identifying a plurality of predicates in the query, wherein the plurality of predicates includes a first set of one or more predicates and a second set of one or more predicates that are different than the first set of predicates; generating, based on the first set of predicates and the summary data, a first selectivity value; determining whether the first set of predicates is correlated with the second set of predicates; in response to determining that the first set of predicates is correlated with the second set of predicates, generating, based on the second set of predicates and the first set of predicates, a second selectivity value; and estimating, based on the first selectivity value and the second selectivity value, a cost of executing the query; wherein the method is performed by one or more computing devices. | 11. A method for estimating a cost of executing a query that targets a portion of XML data, the method comprising: storing summary data that is separate from the XML data and that indicates (a) a number of each element of a plurality of elements of an XML document that is part of the XML data and (b) a hierarchical relationship among the plurality of elements; identifying a plurality of predicates in the query, wherein the plurality of predicates includes a first set of one or more predicates and a second set of one or more predicates that are different than the first set of predicates; generating, based on the first set of predicates and the summary data, a first selectivity value; determining whether the first set of predicates is correlated with the second set of predicates; in response to determining that the first set of predicates is correlated with the second set of predicates, generating, based on the second set of predicates and the first set of predicates, a second selectivity value; and estimating, based on the first selectivity value and the second selectivity value, a cost of executing the query; wherein the method is performed by one or more computing devices. 14. The method of claim 11 , wherein determining that the first set of predicates is correlated with the second set of predicates includes determining, based on the first set of predicates, that a variable reference in the second set of predicates is constrained to certain values. | 0.725586 |
6,122,361 | 19 | 20 | 19. A method for performing speech recognition as defined in claim 18, comprising the steps of: a) providing a plurality of a priori data structures, each data structure establishing a correspondence between a plurality of vocabulary items in said speech recognition dictionary and corresponding probability data elements, each a priori data structure being assigned an identifier representative of a geographical location at which is located a terminal at which the user inputs the utterance, b) determining a value of said certain identifier; and c) searching the data structure corresponding to said certain identifier to extract probability data associated to several ones of the candidates. | 19. A method for performing speech recognition as defined in claim 18, comprising the steps of: a) providing a plurality of a priori data structures, each data structure establishing a correspondence between a plurality of vocabulary items in said speech recognition dictionary and corresponding probability data elements, each a priori data structure being assigned an identifier representative of a geographical location at which is located a terminal at which the user inputs the utterance, b) determining a value of said certain identifier; and c) searching the data structure corresponding to said certain identifier to extract probability data associated to several ones of the candidates. 20. A method for performing speech recognition as defined in claim 19, comprising the step of determining at least a portion of a telephone number of the terminal at which the user inputs the utterance to determine the value of the certain identifier. | 0.5 |
9,431,003 | 1 | 9 | 1. A method of imbuing an artificial intelligence system with idiomatic traits, the method comprising: collecting, by one or more processors, electronic units of speech from an electronic stream of speech, wherein the electronic stream of speech is generated by a first entity; identifying, by one or more processors, tokens from the electronic stream of speech, wherein each token identifies a particular electronic unit of speech from the electronic stream of speech, and wherein identification of the tokens is semantic-free such that the tokens are identified independently of a semantic meaning of a respective electronic unit of speech; populating, by one or more processors, nodes in a first speech graph with the tokens; identifying, by one or more processors, a first shape of the first speech graph; matching, by one or more processors, the first shape to a second shape, wherein the second shape is of a second speech graph from a second entity in a known category; assigning, by one or more processors, the first entity to the known category in response to the first shape matching the second shape; and modifying, by one or more processors, synthetic speech generated by an artificial intelligence system based on the first entity being assigned to the known category, wherein said modifying imbues the artificial intelligence system with idiomatic traits of persons in the known category. | 1. A method of imbuing an artificial intelligence system with idiomatic traits, the method comprising: collecting, by one or more processors, electronic units of speech from an electronic stream of speech, wherein the electronic stream of speech is generated by a first entity; identifying, by one or more processors, tokens from the electronic stream of speech, wherein each token identifies a particular electronic unit of speech from the electronic stream of speech, and wherein identification of the tokens is semantic-free such that the tokens are identified independently of a semantic meaning of a respective electronic unit of speech; populating, by one or more processors, nodes in a first speech graph with the tokens; identifying, by one or more processors, a first shape of the first speech graph; matching, by one or more processors, the first shape to a second shape, wherein the second shape is of a second speech graph from a second entity in a known category; assigning, by one or more processors, the first entity to the known category in response to the first shape matching the second shape; and modifying, by one or more processors, synthetic speech generated by an artificial intelligence system based on the first entity being assigned to the known category, wherein said modifying imbues the artificial intelligence system with idiomatic traits of persons in the known category. 9. The method of claim 1 , wherein the known category is for a group having a common level of education. | 0.971708 |
7,975,019 | 29 | 31 | 29. A method of dynamically supplementing a web page loaded by a web browser from a web site, the method comprising: generating a tag via a tag generation tool, and communicating the tag to an operator of said web site, said tag adapted for incorporation into web page coding of the web site; receiving, over a network, a request generated by the browser in response to said tag being included in the web page; and responding to the request by causing the browser to load and execute an update handler, wherein execution of the update handler causes the browser to at least (a) analyze content of the web page and to determine that the web page includes a link that matches a pre-specified link signature of a catalog page, said link including an identifier of a product, (b) retrieve, based on said identifier of the product, catalog content associated with the product, wherein the catalog content is retrieved over a network from a content server that is separate from the web site, and (c) supplement the web page with the catalog content; wherein the method, including generating the tag, receiving the request, and responding to the request, is performed by a system that comprises at least one machine. | 29. A method of dynamically supplementing a web page loaded by a web browser from a web site, the method comprising: generating a tag via a tag generation tool, and communicating the tag to an operator of said web site, said tag adapted for incorporation into web page coding of the web site; receiving, over a network, a request generated by the browser in response to said tag being included in the web page; and responding to the request by causing the browser to load and execute an update handler, wherein execution of the update handler causes the browser to at least (a) analyze content of the web page and to determine that the web page includes a link that matches a pre-specified link signature of a catalog page, said link including an identifier of a product, (b) retrieve, based on said identifier of the product, catalog content associated with the product, wherein the catalog content is retrieved over a network from a content server that is separate from the web site, and (c) supplement the web page with the catalog content; wherein the method, including generating the tag, receiving the request, and responding to the request, is performed by a system that comprises at least one machine. 31. The method of claim 29 , wherein causing the browser to load and execute the update handler comprises transmitting at least a portion of the update handler to the browser from the content server. | 0.725138 |
8,065,286 | 3 | 4 | 3. The method as recited in claim 1 , wherein said selecting comprises searching a database for a searcher matching the query. | 3. The method as recited in claim 1 , wherein said selecting comprises searching a database for a searcher matching the query. 4. The method as recited in claim 3 , comprising: associating searchers with the plurality of keywords where said registering comprises comparing popularity of keywords of the searcher to popularity of keywords associated with other searchers. | 0.5 |
9,639,578 | 1 | 3 | 1. A method comprising: receiving a search parameter with a computer that is configured with an improved search mechanism; deriving, with the computer and the improved search mechanism, a search criterion from the search parameter and using the search criterion to obtain one or more first values from a first-key value family of a key-value data repository stored in a data storage device that is coupled to the computer; obtaining based on the one or more first values, with the computer and the improved search mechanism, one or more compressed values from a second key-value family of the key-value data repository; wherein the key-value data repository comprises a cluster of a plurality of computing nodes: wherein at least one key of the first key-value family is mastered by at least one node of the plurality nodes and at least one other key of the first key-value family is mastered by at least one other node of the plurality of nodes; wherein each and every node of the cluster of nodes is configured to obtain values for any key of the first key-value family; uncompressing, with the computer and the improved search mechanism, the one or more compressed values to produce one or more uncompressed values; identifying, with the computer and the improved search mechanism, based on the one or more first values to identify one or more portions of the one or more uncompressed values; returning, with the computer and the improved search mechanism, the one or more portions of the one or more uncompressed values as search results. | 1. A method comprising: receiving a search parameter with a computer that is configured with an improved search mechanism; deriving, with the computer and the improved search mechanism, a search criterion from the search parameter and using the search criterion to obtain one or more first values from a first-key value family of a key-value data repository stored in a data storage device that is coupled to the computer; obtaining based on the one or more first values, with the computer and the improved search mechanism, one or more compressed values from a second key-value family of the key-value data repository; wherein the key-value data repository comprises a cluster of a plurality of computing nodes: wherein at least one key of the first key-value family is mastered by at least one node of the plurality nodes and at least one other key of the first key-value family is mastered by at least one other node of the plurality of nodes; wherein each and every node of the cluster of nodes is configured to obtain values for any key of the first key-value family; uncompressing, with the computer and the improved search mechanism, the one or more compressed values to produce one or more uncompressed values; identifying, with the computer and the improved search mechanism, based on the one or more first values to identify one or more portions of the one or more uncompressed values; returning, with the computer and the improved search mechanism, the one or more portions of the one or more uncompressed values as search results. 3. The method of claim 1 , wherein at least one of the one or more first values comprises an identifier of a compressed value of the one or more compressed values. | 0.75303 |
7,865,955 | 14 | 15 | 14. The apparatus according to claim 1 , wherein the signature frequency table includes a field denoting an observation period of each entry. | 14. The apparatus according to claim 1 , wherein the signature frequency table includes a field denoting an observation period of each entry. 15. The apparatus according to claim 14 , wherein the signature candidate extractor increases the frequency of signatures if an observation period is not elapsed and increases the frequency of a signature after initializing the frequency of a signature if an observation period is elapsed when a currently analyzing signature is present in the signature frequency table, and increases the frequency of signatures after generating and initializing an new entry for a signature when the currently analyzing signature is not present in the signature frequency table. | 0.5 |
8,180,834 | 28 | 29 | 28. The computer program product of claim 27 , wherein the operations further comprise: storing a plurality of received messages in a quarantine folder if the address associated with the sender of each message does not match an entry on the positive screening list. | 28. The computer program product of claim 27 , wherein the operations further comprise: storing a plurality of received messages in a quarantine folder if the address associated with the sender of each message does not match an entry on the positive screening list. 29. The computer program product of claim 28 , wherein the operations further comprise: applying an updated screening list to the plurality of received messages stored in the quarantine folder; and adding a first quarantined received message to an inbox of the first user if the sender of the quarantined received message matches an entry in the updated screening list. | 0.5 |
10,019,984 | 1 | 9 | 1. A system for diagnosing speech recognition errors, comprising: at least one processing component; and one or more media operably coupled to the at least one processing component and bearing one or more instructions that, when executed by the at least one processing component, perform operations including at least: determine that a speech recognition result is at least partially erroneous; perform a first error analysis of the at least partially erroneous speech recognition result to provide a first error analysis result; perform a second error analysis of the at least partially erroneous speech recognition result to provide a second error analysis result; and determine at least one category of recognition error associated with the at least partially erroneous speech recognition result based on a combination of the first error analysis result and the second error analysis result, including determine that the at least one category of recognition error includes at least an acoustic model error when (a) the first error analysis result indicates that a reference language model score associated with a reference speech is higher than a recognition language model score associated with the at least partially erroneous speech recognition result; and (b) the second error analysis result indicates that a reference acoustic model score associated with the reference speech is lower than a recognition acoustic model score associated with the at least partially erroneous speech recognition result; determine at least one corrective action to at least partially correct at least one aspect of a speech recognition component based at least partially on the at least one category of recognition error associated with the at least partially erroneous speech recognition result; and at least one of: provide an indication of the at least one corrective action; or adjust at least one aspect of the speech recognition component based on the at least one corrective action. | 1. A system for diagnosing speech recognition errors, comprising: at least one processing component; and one or more media operably coupled to the at least one processing component and bearing one or more instructions that, when executed by the at least one processing component, perform operations including at least: determine that a speech recognition result is at least partially erroneous; perform a first error analysis of the at least partially erroneous speech recognition result to provide a first error analysis result; perform a second error analysis of the at least partially erroneous speech recognition result to provide a second error analysis result; and determine at least one category of recognition error associated with the at least partially erroneous speech recognition result based on a combination of the first error analysis result and the second error analysis result, including determine that the at least one category of recognition error includes at least an acoustic model error when (a) the first error analysis result indicates that a reference language model score associated with a reference speech is higher than a recognition language model score associated with the at least partially erroneous speech recognition result; and (b) the second error analysis result indicates that a reference acoustic model score associated with the reference speech is lower than a recognition acoustic model score associated with the at least partially erroneous speech recognition result; determine at least one corrective action to at least partially correct at least one aspect of a speech recognition component based at least partially on the at least one category of recognition error associated with the at least partially erroneous speech recognition result; and at least one of: provide an indication of the at least one corrective action; or adjust at least one aspect of the speech recognition component based on the at least one corrective action. 9. The system of claim 1 , wherein determine at least one corrective action to at least partially correct at least one aspect of a speech recognition component based at least partially on the at least one category of recognition error associated with the at least partially erroneous speech recognition result comprises: determine at least one corrective action to at least partially correct at least one aspect of at least one of a language model, an acoustic model, a transcription model, a pruning model, a penalty model, or a grammar of a speech recognition component based at least partially on the at least one category of recognition error associated with the at least partially erroneous speech recognition result. | 0.5 |
9,171,202 | 1 | 6 | 1. A computer-implemented method for accessing information in a mixed media document system, the method comprising: receiving an image patch of a target document; determining, with one or more processors, from the received image patch, a query that indicates a two-dimensional geometric relationship between a pair of document features in the target document, the two-dimensional geometric relationship including an indication that the pair of document features in the target document are a horizontally adjacent pair of document features or a vertically adjacent pair of document features; comparing, with the one or more processors, the query to an index table of document features from mixed media documents to identify candidate regions in the mixed media documents that comprise the query, the index table comprising locations of the document features in the mixed media documents; and responsive to comparing the query to the document features in the index table, identifying one or more of the mixed media documents comprising the identified candidate regions comprising the query by: adding a weight to an array of an accumulator for each cell in a zone around each pair of document features based on an inverse document frequency associated with each pair of document features, the inverse document frequency being inversely proportional to a number of document pages that contain the image patch; searching the array of the accumulator for a cell with a maximum value; and in response to the maximum value exceeding a threshold, reporting coordinates of the cell as a location of the image patch. | 1. A computer-implemented method for accessing information in a mixed media document system, the method comprising: receiving an image patch of a target document; determining, with one or more processors, from the received image patch, a query that indicates a two-dimensional geometric relationship between a pair of document features in the target document, the two-dimensional geometric relationship including an indication that the pair of document features in the target document are a horizontally adjacent pair of document features or a vertically adjacent pair of document features; comparing, with the one or more processors, the query to an index table of document features from mixed media documents to identify candidate regions in the mixed media documents that comprise the query, the index table comprising locations of the document features in the mixed media documents; and responsive to comparing the query to the document features in the index table, identifying one or more of the mixed media documents comprising the identified candidate regions comprising the query by: adding a weight to an array of an accumulator for each cell in a zone around each pair of document features based on an inverse document frequency associated with each pair of document features, the inverse document frequency being inversely proportional to a number of document pages that contain the image patch; searching the array of the accumulator for a cell with a maximum value; and in response to the maximum value exceeding a threshold, reporting coordinates of the cell as a location of the image patch. 6. The method of claim 1 further comprising: identifying one of the candidate regions that is most consistent with the query; and in response to determining that the identified candidate region satisfies pre-defined matching criteria, confirming the identified candidate region as a match to the target document. | 0.5 |
8,626,758 | 1 | 6 | 1. A computer-implemented method for ranking documents, the method comprising: maintaining, in a profile associated with the user, documents selected by a user for viewing within a predetermined time period; generating at least one positive word vector using words contained in at least a segment of at least one of the documents stored in the profile; generating at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generating document word vectors for a group of documents to be ranked; performing, using at least one processor, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; ranking, using the at least one processor, the group of documents based on the performed vector space relationship analysis; classifying the documents selected by the user for viewing in predetermined categories; ranking, based on the ranked group of documents, the predetermined categories; and storing the ranked categories in the profile. | 1. A computer-implemented method for ranking documents, the method comprising: maintaining, in a profile associated with the user, documents selected by a user for viewing within a predetermined time period; generating at least one positive word vector using words contained in at least a segment of at least one of the documents stored in the profile; generating at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generating document word vectors for a group of documents to be ranked; performing, using at least one processor, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; ranking, using the at least one processor, the group of documents based on the performed vector space relationship analysis; classifying the documents selected by the user for viewing in predetermined categories; ranking, based on the ranked group of documents, the predetermined categories; and storing the ranked categories in the profile. 6. The method of claim 1 , further comprising: sending the ranked categories to an ad server; and receiving advertisements associated with the ranked categories from the ad server. | 0.618644 |
9,082,310 | 50 | 62 | 50. The non-transitory computer-readable medium of claim 34 , wherein the method further comprises: instructions to automatically generate a first answer to the first question instance based on the first question instance and the data set. | 50. The non-transitory computer-readable medium of claim 34 , wherein the method further comprises: instructions to automatically generate a first answer to the first question instance based on the first question instance and the data set. 62. The non-transitory computer-readable medium of claim 50 , wherein the first question instance further comprises a first question definition, and wherein the instructions to automatically generate a first answer comprises instructions to process the first question definition to automatically generate the first answer. | 0.690385 |
8,826,357 | 1 | 11 | 1. A computer-implemented method comprising: storing a source video file in a video database; storing annotations in an annotations database in association with the source video file; providing to a remote client device a user interface comprising a video area displaying one or more frames of the source video file; providing to the client device a first web-based user interface portion associated with the source video file and comprising visual representations of a plurality of different annotation types; responsive to receiving a user selection of one of the annotation types from the client device, providing to the client device a second web-based user interface portion comprising at least one text area for entering a start time, an end time, and a uniform resource locator (URL) for a new annotation; receiving a user designation of a spatial location in a frame of the source video file based on a user click within the displayed one or more frames of the source video file; receiving a user designation of the start time, the end time, and the URL from the client device via the second user interface portion, the URL separately encoding both an identifier of a target video file and a time location within the target video file, the target video file being different from the source video file; adding, to the annotations database in association with the source video file, a first annotation corresponding to the designated start time, end time, and URL, and further corresponding to the spatial location in the frame of the source video file; responsive to receiving a request from the client device for the source video file, transmitting the source video file and the associated first annotation to the client device; and responsive to receiving a user selection of the first annotation, causing playback of the target video file to begin at the time location within the target video file. | 1. A computer-implemented method comprising: storing a source video file in a video database; storing annotations in an annotations database in association with the source video file; providing to a remote client device a user interface comprising a video area displaying one or more frames of the source video file; providing to the client device a first web-based user interface portion associated with the source video file and comprising visual representations of a plurality of different annotation types; responsive to receiving a user selection of one of the annotation types from the client device, providing to the client device a second web-based user interface portion comprising at least one text area for entering a start time, an end time, and a uniform resource locator (URL) for a new annotation; receiving a user designation of a spatial location in a frame of the source video file based on a user click within the displayed one or more frames of the source video file; receiving a user designation of the start time, the end time, and the URL from the client device via the second user interface portion, the URL separately encoding both an identifier of a target video file and a time location within the target video file, the target video file being different from the source video file; adding, to the annotations database in association with the source video file, a first annotation corresponding to the designated start time, end time, and URL, and further corresponding to the spatial location in the frame of the source video file; responsive to receiving a request from the client device for the source video file, transmitting the source video file and the associated first annotation to the client device; and responsive to receiving a user selection of the first annotation, causing playback of the target video file to begin at the time location within the target video file. 11. The method of claim 1 , wherein the client device displays the first annotation as part of the source video file during playback of the source video file, and wherein the user selection of the first annotation occurs during the playback of the source video file. | 0.623229 |
9,672,268 | 17 | 19 | 17. The method of claim 1 , wherein the first and each further dataset is a list of unique identifiers and associated attributes, preferably events, and the dataset obtained from the first and one or more further real result tables is a list of unique identifiers. | 17. The method of claim 1 , wherein the first and each further dataset is a list of unique identifiers and associated attributes, preferably events, and the dataset obtained from the first and one or more further real result tables is a list of unique identifiers. 19. The method of claim 17 , wherein the relational database is a medical record database, the unique identifiers being patient identifiers, and wherein the attributes are patient events, preferably selected from categories including one or more of; medical events, clinical events, therapeutic events, product prescribed, medical condition diagnosed and test result. | 0.5 |
9,672,206 | 38 | 39 | 38. The method according to claim 37 , further comprising the step of removing low frequency co-occurrences. | 38. The method according to claim 37 , further comprising the step of removing low frequency co-occurrences. 39. The method according to claim 38 , further comprising the step of removing low variance co-occurrences. | 0.5 |
8,289,282 | 2 | 3 | 2. The method of claim 1 , further comprising: associating the word frame with the identified language object. | 2. The method of claim 1 , further comprising: associating the word frame with the identified language object. 3. The method of claim 2 , wherein storing the word frame in a memory further comprises: storing the word frame in a word frame table in the memory. | 0.5 |
9,400,782 | 3 | 5 | 3. The system of claim 1 , wherein the word evaluation component calculates the matching metric for each candidate object by summing distance values calculated from each contact location in the input sequence to the location assigned to the character in the corresponding position of the candidate object, and applying a weighting function according to a frequency of use associated with the object. | 3. The system of claim 1 , wherein the word evaluation component calculates the matching metric for each candidate object by summing distance values calculated from each contact location in the input sequence to the location assigned to the character in the corresponding position of the candidate object, and applying a weighting function according to a frequency of use associated with the object. 5. The system of claim 3 , wherein the frequency of use associated with each candidate object comprises an ordinal ranking of the object with respect to other objects, wherein an object associated with a higher relative frequency corresponds to a numerically lower ordinal ranking. | 0.614011 |
7,917,843 | 1 | 9 | 1. A computer-implemented method for finding data related to the contents of a document using a first computer program running on a computer, the method comprising: displaying the document electronically using the first computer program; while the document is being displayed, analyzing, in a computer process, first information from the document to determine if the first information is at least one of a plurality of types of information that can be searched for in order to find second information related to the first information; retrieving the first information; providing an input device, configured by the first computer program, that allows a user to enter a user command to initiate an operation, the operation comprising (i) performing a search using at least part of the first information as a search term in order to find the second information, of a specific type or types, associated with the search term in an information source external to the document, wherein the specific type or types of second information is dependent at least in part on the type or types of the first information, and (ii) performing an action using at least part of the second information; in consequence of receipt by the first computer program of the user command from the input device, causing a search for the search term in the information source, using a second computer program, in order to find second information related to the search term; and if searching finds any second information related to the search term, performing the action using at least part of the second information, wherein the action is of a type depending at least in part on the type or types of the first information. | 1. A computer-implemented method for finding data related to the contents of a document using a first computer program running on a computer, the method comprising: displaying the document electronically using the first computer program; while the document is being displayed, analyzing, in a computer process, first information from the document to determine if the first information is at least one of a plurality of types of information that can be searched for in order to find second information related to the first information; retrieving the first information; providing an input device, configured by the first computer program, that allows a user to enter a user command to initiate an operation, the operation comprising (i) performing a search using at least part of the first information as a search term in order to find the second information, of a specific type or types, associated with the search term in an information source external to the document, wherein the specific type or types of second information is dependent at least in part on the type or types of the first information, and (ii) performing an action using at least part of the second information; in consequence of receipt by the first computer program of the user command from the input device, causing a search for the search term in the information source, using a second computer program, in order to find second information related to the search term; and if searching finds any second information related to the search term, performing the action using at least part of the second information, wherein the action is of a type depending at least in part on the type or types of the first information. 9. A method according to claim 1 , further comprising, if the search is not successful, providing a prompt for updating the information source to include the first information. | 0.627119 |
9,679,049 | 10 | 12 | 10. A method for providing visual suggestions for document classification via injection, comprising: obtaining clusters of unclassified documents; obtaining a set of reference documents, each reference document associated with a classification code; comparing one or more of the unclassified documents within one such cluster to the reference documents; identifying for the cluster, one or more of the reference documents that are similar to the compared unclassified documents; injecting the similar reference documents into the cluster; setting a threshold for a number of the similar reference documents to be injected into the cluster; displaying each of the similar reference documents in the cluster with a visual indicator representative of the associated classification code and further displaying the unclassified documents of the cluster; and providing a suggestion for classification for one of the unclassified documents within each cluster based on the visual indicators of the similar reference documents. | 10. A method for providing visual suggestions for document classification via injection, comprising: obtaining clusters of unclassified documents; obtaining a set of reference documents, each reference document associated with a classification code; comparing one or more of the unclassified documents within one such cluster to the reference documents; identifying for the cluster, one or more of the reference documents that are similar to the compared unclassified documents; injecting the similar reference documents into the cluster; setting a threshold for a number of the similar reference documents to be injected into the cluster; displaying each of the similar reference documents in the cluster with a visual indicator representative of the associated classification code and further displaying the unclassified documents of the cluster; and providing a suggestion for classification for one of the unclassified documents within each cluster based on the visual indicators of the similar reference documents. 12. The method according to claim 10 , further comprising: generating the reference set, comprising: clustering a set of uncoded documents; applying selection criteria to the clusters; selecting one or more of the clusters that satisfy the selection criteria; assigning the classification codes to the uncoded documents in the selected clusters; and grouping the uncoded documents with the assigned classification codes as the reference set. | 0.719822 |
8,646,029 | 35 | 36 | 35. The computer-implemented method of claim 27 , further comprising: enabling unified programming access between the web browser's scripting engine and layout engine and enabling one or more properties associated with the layout engine to be virtually replaced by the scripting engine. | 35. The computer-implemented method of claim 27 , further comprising: enabling unified programming access between the web browser's scripting engine and layout engine and enabling one or more properties associated with the layout engine to be virtually replaced by the scripting engine. 36. The computer-implemented method of claim 35 , at least one property of the one or more properties associated with the layout engine comprising a read-only value. | 0.5 |
7,650,286 | 140 | 141 | 140. The system of claim 135 , wherein each said at least one resume comprises a document in an electronic format. | 140. The system of claim 135 , wherein each said at least one resume comprises a document in an electronic format. 141. The system of claim 140 , wherein the electronic format includes a standard digital document format. | 0.5 |
8,560,548 | 9 | 10 | 9. The computer-implemented method of claim 1 , further comprising: maintaining a priority queue of the top-k most frequent phrases while intersecting the hit list with the globally frequent phrases, wherein the estimating comprises: randomizing the globally frequent phrases in the text index to produce the first randomized posting list; and randomizing the hit list to produce the second randomized posting list, wherein the algorithm is a modified zipper algorithm. | 9. The computer-implemented method of claim 1 , further comprising: maintaining a priority queue of the top-k most frequent phrases while intersecting the hit list with the globally frequent phrases, wherein the estimating comprises: randomizing the globally frequent phrases in the text index to produce the first randomized posting list; and randomizing the hit list to produce the second randomized posting list, wherein the algorithm is a modified zipper algorithm. 10. The computer-implemented method of claim 9 , wherein the estimating further comprises multiplying a Jaccard Distance estimator with a union estimator to produce an estimate for the intersection of the first randomized posting list and the second randomized posting list. | 0.5 |
9,110,971 | 26 | 27 | 26. The computer-based system of claim 25 , wherein the re-ranking module is further adapted to generate for each of the first set of candidate patent documents a set of feature scores associated with the set of patent features, the re-ranking module being adapted to re-rank to generate the second set of ranked patent documents based at least in part on the set of feature scores. | 26. The computer-based system of claim 25 , wherein the re-ranking module is further adapted to generate for each of the first set of candidate patent documents a set of feature scores associated with the set of patent features, the re-ranking module being adapted to re-rank to generate the second set of ranked patent documents based at least in part on the set of feature scores. 27. The computer-based system of claim 26 , wherein the re-ranking module is further adapted to generate for each of the first set of candidate patent documents a collective score derived at least in part from a set of feature scores, the re-ranking module being adapted to re-rank to generate the second set of ranked patent documents based at least in part on the collective score associated with each patent in the first set of candidate patent documents. | 0.5 |
10,162,904 | 1 | 4 | 1. A computer program product for capturing and managing knowledge from social networking interactions comprising: a non-transitory computer readable storage medium, said computer readable storage medium comprising computer readable program code embodied therewith, said computer readable program code comprising program instructions that, when executed, causes a processor to: present a marking element in a social networking interaction, wherein said marking element allows a user to specify whether a corresponding message corresponds to at least one member of a group consisting of a question and an answer; receive a first user selection indicating a portion of said social network interaction as a question; receive a second user selection indicating a portion of said social networking interaction as an answer; create a knowledge element in response to a user activating said marking element in said social networking interaction; populate the knowledge element with information about: the portion of the social networking interaction indicated as a question; and the portion of the social networking interaction indicated as an answer; store said knowledge element in a catalog of knowledge elements; present an evaluation element for evaluating said knowledge element in said social networking interaction; present an editing element for editing said knowledge element; present knowledge element indicators to accompany said corresponding messages, which knowledge element indicators indicate whether corresponding messages correspond to at least one of a group consisting of a question and an answer; provide access to information associated with the knowledge element via the knowledge element indicators; and alter said knowledge element in response to a user evaluating or editing said knowledge element. | 1. A computer program product for capturing and managing knowledge from social networking interactions comprising: a non-transitory computer readable storage medium, said computer readable storage medium comprising computer readable program code embodied therewith, said computer readable program code comprising program instructions that, when executed, causes a processor to: present a marking element in a social networking interaction, wherein said marking element allows a user to specify whether a corresponding message corresponds to at least one member of a group consisting of a question and an answer; receive a first user selection indicating a portion of said social network interaction as a question; receive a second user selection indicating a portion of said social networking interaction as an answer; create a knowledge element in response to a user activating said marking element in said social networking interaction; populate the knowledge element with information about: the portion of the social networking interaction indicated as a question; and the portion of the social networking interaction indicated as an answer; store said knowledge element in a catalog of knowledge elements; present an evaluation element for evaluating said knowledge element in said social networking interaction; present an editing element for editing said knowledge element; present knowledge element indicators to accompany said corresponding messages, which knowledge element indicators indicate whether corresponding messages correspond to at least one of a group consisting of a question and an answer; provide access to information associated with the knowledge element via the knowledge element indicators; and alter said knowledge element in response to a user evaluating or editing said knowledge element. 4. The computer program product of claim 1 , wherein indicating a portion of said social networking interaction as an answer comprises pairing said answer to said question. | 0.764384 |
9,898,666 | 1 | 2 | 1. A method of providing primitive visual knowledge performed by a primitive visual knowledge providing apparatus, the method comprising: receiving an image video in a form of a digital image sequence; dividing the received image video into scenes; extracting a representative shot from each of the scenes; extracting objects from frames which compose the representative shot; extracting action verbs based on a mutual relationship between the extracted objects; selecting a frame best expressing the mutual relationship with the objects, which are the basis for the extracting of the action verbs, as a key frame; generating the primitive visual knowledge based on the selected key frame; storing the generated primitive visual knowledge in a database; and visualizing the primitive visual knowledge stored in the database to provide the primitive visual knowledge to a manager, wherein the extracting of the representative shot includes: calculating an entropy in a section while moving along sections of separate scenes; and extracting a section having the highest entropy as the representative shot. | 1. A method of providing primitive visual knowledge performed by a primitive visual knowledge providing apparatus, the method comprising: receiving an image video in a form of a digital image sequence; dividing the received image video into scenes; extracting a representative shot from each of the scenes; extracting objects from frames which compose the representative shot; extracting action verbs based on a mutual relationship between the extracted objects; selecting a frame best expressing the mutual relationship with the objects, which are the basis for the extracting of the action verbs, as a key frame; generating the primitive visual knowledge based on the selected key frame; storing the generated primitive visual knowledge in a database; and visualizing the primitive visual knowledge stored in the database to provide the primitive visual knowledge to a manager, wherein the extracting of the representative shot includes: calculating an entropy in a section while moving along sections of separate scenes; and extracting a section having the highest entropy as the representative shot. 2. The method of claim 1 , wherein the dividing of the received image video into scenes includes: monitoring a change amount of the image video in the received image video; tagging a time point at which the change amount goes beyond a critical amount as a start point of a scene, and continuing to monitor the change amount of the image; tagging a time point at which the change amount is equal to or smaller than the critical amount as an end point of the scene; and separating an image video in a section between the start point and the end point of the scene, and storing the separated image video as a scene for analysis. | 0.5 |
10,140,989 | 1 | 3 | 1. A speech recognition system, comprising: an instant messaging server (IMS) configured to: assign a unique identifier to speech information received from a sending end to serve as a speech ID; send the speech information to a receiving end; and in response to a determination that a speech recognition request issued from a user of the receiving end corresponding to the speech information is received: extract the speech ID corresponding to the speech information from the speech recognition request; look up the speech information; and deliver a speech recognition command in the speech recognition request and the looked-up speech information to one of a speech recognition module, a speech recognition server, or a speech recognition server cluster; the one of the speech recognition module, the speech recognition server, or the speech recognition server cluster configured to: perform speech recognition based on the speech information and the speech recognition command; and convert the speech information to obtain text information corresponding to the speech information, wherein the IMS obtains the text information from the one of the speech recognition module, the speech recognition server, or the speech recognition server cluster; and a sending module configured to send the obtained text information back as a speech recognition result to the receiving end, wherein the speech recognition module is set up in the one of the IMS, the speech recognition server, or the speech recognition server cluster, wherein the IMS is further configured to: store the obtained text information in a cache in correspondence with the speech ID; and in response to a determination that another speech recognition request for the same speech information is received: extract a speech ID from the other speech recognition request; and locate the text information corresponding to the speech ID from the other speech recognition request. | 1. A speech recognition system, comprising: an instant messaging server (IMS) configured to: assign a unique identifier to speech information received from a sending end to serve as a speech ID; send the speech information to a receiving end; and in response to a determination that a speech recognition request issued from a user of the receiving end corresponding to the speech information is received: extract the speech ID corresponding to the speech information from the speech recognition request; look up the speech information; and deliver a speech recognition command in the speech recognition request and the looked-up speech information to one of a speech recognition module, a speech recognition server, or a speech recognition server cluster; the one of the speech recognition module, the speech recognition server, or the speech recognition server cluster configured to: perform speech recognition based on the speech information and the speech recognition command; and convert the speech information to obtain text information corresponding to the speech information, wherein the IMS obtains the text information from the one of the speech recognition module, the speech recognition server, or the speech recognition server cluster; and a sending module configured to send the obtained text information back as a speech recognition result to the receiving end, wherein the speech recognition module is set up in the one of the IMS, the speech recognition server, or the speech recognition server cluster, wherein the IMS is further configured to: store the obtained text information in a cache in correspondence with the speech ID; and in response to a determination that another speech recognition request for the same speech information is received: extract a speech ID from the other speech recognition request; and locate the text information corresponding to the speech ID from the other speech recognition request. 3. The system as described in claim 1 , wherein the IMS is further configured to: assign the speech ID to the speech information sent by the sending end; send the speech information to the receiving end; perform speech recognition based on the speech information, the speech recognition converting the speech information to obtain the text information corresponding to the speech information; store the text information corresponding to the speech ID, the speech information, or a combination thereof; receive the speech recognition request from the sending end; and look up the text information corresponding to the speech ID based on the speech ID in the speech recognition request. | 0.5 |
6,128,612 | 7 | 8 | 7. A computer program product, for use in a data processing system, the computer program product comprising: a computer usable medium having computer readable program code embodied in said medium for translating an ad-hoc query input string to a string of common table expressions, said computer program including: computer readable program code means for creating a postfix queue by parsing each item of the input string until all items are parsed: computer readable program code means, if the item is a joiner object or left parenthesis, for adding the joiner object or left parenthesis to a temporary pushdown stack and then returning to parse the next item of the input string; computer readable program code means, if the item is a query clause, for adding the query clause to the postfix queue, and computer readable program code means, if the object is a query clause or right parenthesis and if the temporary pushdown stack is empty, for returning to parse the next item of the input string; if the temporary pushdown stack is not empty and the next item in the temporary pushdown stack is not a joiner object, for returning to parse the next item of the input string; and if the temporary pushdown stack is not empty and the next item in the temporary pushdown stack is a joiner object, for adding the next item in the pushdown stack to the postfix queue and returning to parse the next item of the input string; and computer readable program code means for processing each item of the postfix queue to translate the input string to an initially empty string of common table expressions until all items are processed: computer readable program code means, if the item is a query clause, for forming a common table expression to return a unique key field of all records matching the specification of the query clause, placing that expression into a second temporary pushdown stack, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue; and computer readable program code means, if the item is not a query clause and if the item is an "AND" joiner object, for forming a common table expression to represent an "INNER JOIN" of the top two items of the second temporary pushdown stack, said expression returning a unique key field, replacing the top two items of the second temporary pushdown stack with the expression just created, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue; if the item is an "OR" joiner object, for forming a common table expression to represent a "UNION" of the top two items of the second temporary pushdown stack, said expression returning a unique key field, replacing the top two items of the second temporary pushdown stack with the expression just created, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue; and if the item is a "NOT" joiner object, for forming a common table expression to represent an "EXCLUDE" of the top item of the second temporary pushdown stack from the results of the second item of the second temporary pushdown stack, said expression returning a unique key field, replacing the top two items of the second temporary pushdown stack with the expression just created, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue. | 7. A computer program product, for use in a data processing system, the computer program product comprising: a computer usable medium having computer readable program code embodied in said medium for translating an ad-hoc query input string to a string of common table expressions, said computer program including: computer readable program code means for creating a postfix queue by parsing each item of the input string until all items are parsed: computer readable program code means, if the item is a joiner object or left parenthesis, for adding the joiner object or left parenthesis to a temporary pushdown stack and then returning to parse the next item of the input string; computer readable program code means, if the item is a query clause, for adding the query clause to the postfix queue, and computer readable program code means, if the object is a query clause or right parenthesis and if the temporary pushdown stack is empty, for returning to parse the next item of the input string; if the temporary pushdown stack is not empty and the next item in the temporary pushdown stack is not a joiner object, for returning to parse the next item of the input string; and if the temporary pushdown stack is not empty and the next item in the temporary pushdown stack is a joiner object, for adding the next item in the pushdown stack to the postfix queue and returning to parse the next item of the input string; and computer readable program code means for processing each item of the postfix queue to translate the input string to an initially empty string of common table expressions until all items are processed: computer readable program code means, if the item is a query clause, for forming a common table expression to return a unique key field of all records matching the specification of the query clause, placing that expression into a second temporary pushdown stack, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue; and computer readable program code means, if the item is not a query clause and if the item is an "AND" joiner object, for forming a common table expression to represent an "INNER JOIN" of the top two items of the second temporary pushdown stack, said expression returning a unique key field, replacing the top two items of the second temporary pushdown stack with the expression just created, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue; if the item is an "OR" joiner object, for forming a common table expression to represent a "UNION" of the top two items of the second temporary pushdown stack, said expression returning a unique key field, replacing the top two items of the second temporary pushdown stack with the expression just created, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue; and if the item is a "NOT" joiner object, for forming a common table expression to represent an "EXCLUDE" of the top item of the second temporary pushdown stack from the results of the second item of the second temporary pushdown stack, said expression returning a unique key field, replacing the top two items of the second temporary pushdown stack with the expression just created, appending the new common table expression to the initially empty string, and returning to process the next item of the postfix queue. 8. The computer program product of claim 7, further comprising computer readable program code means, if all items in the postfix queue have been processed, for forming a common table expression to return items represented by the last expression in the second temporary pushdown stack; for removing the last expression from the second temporary pushdown stack; and for forming a final SELECT statement. | 0.5 |
8,719,244 | 6 | 8 | 6. The method of claim 1 , wherein the selecting the first entry comprises computing a relevance score. | 6. The method of claim 1 , wherein the selecting the first entry comprises computing a relevance score. 8. The method of claim 6 , wherein the relevance score computation favors sentence fragments having search terms appearing relatively closer to one another therein over sentence fragments having search terms appearing relatively farther from one another therein. | 0.610119 |
9,104,648 | 2 | 12 | 2. A non-transitory computer readable medium having instructions for causing a computer to create an interactive graphic user interface (GUI) for providing a diagram of patent claims, the diagram comprising: an interactive graphical user interface (GUI) viewable on an electronic display, the GUI including a diagram of at least part of a patent claims series from a patent or a patent application; the claims being parsed hierarchically and each independent claim being parsed into its sub-elements, wherein the sub-elements are parsed patent invention elements or steps of the independent patent invention claim, wherein the hierarchically parsed patent claims comprises hierarchical elements and sub-elements and the diagram comprising a graphical claim structure and a textual claim content associated with each patent claim and, for each patent claim, the graphical claim structure fully includes the textual claim content; and the claims, including both the graphical claim structure and the fully included textual claim content, are dynamically compressible hierarchically; the graphical claim structure comprises multiple geometric outlines, the textual claim content of each hierarchical element and each sub-element are fully included in each of the geometric outlines of the graphical claim structure, wherein coloration and shading are used for the multiple geometric outlines to differentiate the included textual claim content hierarchically, and at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis; and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series. | 2. A non-transitory computer readable medium having instructions for causing a computer to create an interactive graphic user interface (GUI) for providing a diagram of patent claims, the diagram comprising: an interactive graphical user interface (GUI) viewable on an electronic display, the GUI including a diagram of at least part of a patent claims series from a patent or a patent application; the claims being parsed hierarchically and each independent claim being parsed into its sub-elements, wherein the sub-elements are parsed patent invention elements or steps of the independent patent invention claim, wherein the hierarchically parsed patent claims comprises hierarchical elements and sub-elements and the diagram comprising a graphical claim structure and a textual claim content associated with each patent claim and, for each patent claim, the graphical claim structure fully includes the textual claim content; and the claims, including both the graphical claim structure and the fully included textual claim content, are dynamically compressible hierarchically; the graphical claim structure comprises multiple geometric outlines, the textual claim content of each hierarchical element and each sub-element are fully included in each of the geometric outlines of the graphical claim structure, wherein coloration and shading are used for the multiple geometric outlines to differentiate the included textual claim content hierarchically, and at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis; and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series. 12. The non-transitory computer readable medium having instructions for causing a computer to create an interactive GUI of claim 2 , wherein the at least part of a series of claims can be moved up or down in the diagram relative to one another. | 0.504065 |
8,024,282 | 8 | 10 | 8. The system of claim 1 , wherein the objects comprise the intensities of one or more features and/or one or more peaks in mass spectrometry data. | 8. The system of claim 1 , wherein the objects comprise the intensities of one or more features and/or one or more peaks in mass spectrometry data. 10. The system of claim 8 , wherein the objects in the training set comprise the data obtained from two classes of patients: 1) a first class of patients that derive benefit from a particular therapy for treatment of a health condition and 2) a second class of patients that either do not derive benefit, or suffer adverse effects from the particular therapy for treatment of the medical condition, and wherein the classes assigned to the objects correspond to the two classes of patients. | 0.5 |
9,805,615 | 1 | 3 | 1. A computer-implemented method for preparing, taking and scoring tests for a class of students and reporting the results thereof, the method comprising: electronically storing test questions and analysis in a database; electronically storing student identification information, including an email address for each student and authorized time accommodations pertaining to students in the class; electronic transmitting a URL to the email address for each student in the class providing a link to a test; individually accessing the test using the URL sent electronically by the teacher; and electronically retrieving and applying time accommodations corresponding to the student receiving the URL; automatically applying teacher preferences for each student accessing the test; automatically generating test questions saved in the database for each student accessing the test based on the teacher preferences; electronically responding to the questions and submitting the test for scoring; electronically scoring answers to the test questions for each of the students taking the test; electronically analyzing the answers to the tests provided by each of the students taking the test and grading each of the tests based on the teacher preferences; electronically sending each student the score and analysis corresponding to the test taken by the student; and electronically storing the score for each student in the database. | 1. A computer-implemented method for preparing, taking and scoring tests for a class of students and reporting the results thereof, the method comprising: electronically storing test questions and analysis in a database; electronically storing student identification information, including an email address for each student and authorized time accommodations pertaining to students in the class; electronic transmitting a URL to the email address for each student in the class providing a link to a test; individually accessing the test using the URL sent electronically by the teacher; and electronically retrieving and applying time accommodations corresponding to the student receiving the URL; automatically applying teacher preferences for each student accessing the test; automatically generating test questions saved in the database for each student accessing the test based on the teacher preferences; electronically responding to the questions and submitting the test for scoring; electronically scoring answers to the test questions for each of the students taking the test; electronically analyzing the answers to the tests provided by each of the students taking the test and grading each of the tests based on the teacher preferences; electronically sending each student the score and analysis corresponding to the test taken by the student; and electronically storing the score for each student in the database. 3. The method of claim 1 , wherein the questions include questions requiring a multiple choice answer. | 0.804598 |
7,864,989 | 33 | 37 | 33. The apparatus according to claim 21 , further including a similarity measurement unit, wherein said formula selection unit selects formulas from said plurality of formulas for a plurality of pairs of persons from said plurality of persons, and said similarity measurement unit estimates a plurality of probabilities relating to similarities of identities of persons in said plurality of pairs. | 33. The apparatus according to claim 21 , further including a similarity measurement unit, wherein said formula selection unit selects formulas from said plurality of formulas for a plurality of pairs of persons from said plurality of persons, and said similarity measurement unit estimates a plurality of probabilities relating to similarities of identities of persons in said plurality of pairs. 37. The apparatus according to claim 33 , further comprising a classification unit for incorporating in an arrangement of said plurality of probabilities at least one hard constraint relating to persons from said plurality of persons, to obtain constrained inter-relational data results, performing a spectral analysis to obtain eigenvector results from said constrained inter-relational data results, and performing discretization of said eigenvector results using constrained clustering with a criterion to enforce said at least one hard constraint to obtain clusters relating to identities of persons from said plurality of persons. | 0.5 |
9,436,662 | 9 | 10 | 9. A non-transitory, computer readable medium that includes code stored therein and executable by one or more data processors to configure a computer system into a machine for generating a computer readable document utilized for input into an application by: obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to bind a user interface object to an underlying object, wherein the application is incompatible with the first grammar level; performing a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; performing a second transformation of the framework to generate a first presentation style for the first grammar level; obtaining the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and applying the first set of rules and the first presentation style to the binding specification to generate the computer readable document having the output binding specifications in a second grammar level compatible with the application. | 9. A non-transitory, computer readable medium that includes code stored therein and executable by one or more data processors to configure a computer system into a machine for generating a computer readable document utilized for input into an application by: obtaining a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to bind a user interface object to an underlying object, wherein the application is incompatible with the first grammar level; performing a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; performing a second transformation of the framework to generate a first presentation style for the first grammar level; obtaining the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and applying the first set of rules and the first presentation style to the binding specification to generate the computer readable document having the output binding specifications in a second grammar level compatible with the application. 10. The computer readable medium of claim 9 , wherein the obtaining a framework comprises: obtaining at least one file having contents comprising grammar definitions conforming to a second set of rules; and transforming the contents of the at least one file into the framework using a second presentation style conforming to the framework. | 0.5 |
7,650,286 | 180 | 194 | 180. A method for using a computer to identify a matching resume for a job description, comprising: receiving the job description in a memory device resident in the computer, the job description including at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; storing the job description; associating, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; storing at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; receiving at least one resume; parsing each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute, by the computer, a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; storing each said at least one resume; computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and determining whether each said at least one resume is the matching resume that satisfies the job description. | 180. A method for using a computer to identify a matching resume for a job description, comprising: receiving the job description in a memory device resident in the computer, the job description including at least one job requirement, each said at least one job requirement comprising a required skill or experience-related phrase and a required term of experience for the required skill or experience-related phrase; storing the job description; associating, for each said at least one job requirement, the required skill or experience-related phrase with at least one implying skill or experience-related phrase; storing at least one searchable phrase for each said at least one job requirement, one of said at least one searchable phrase including the required skill or experience-related phrase, and said at least one searchable phrase including each said at least one implying skill or experience-related phrase; receiving at least one resume; parsing each said at least one resume to: locate at least one of said at least one searchable phrase in the resume; determine an experience range for each searchable phrase located in the resume by examining a use of each searchable phrase in the resume; and compute, by the computer, a term of experience for each searchable phrase located in the resume based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range, wherein each resume summarizes a candidate's career and qualifications, and wherein each resume conveys personal and business-related characteristics that the candidate believes to be relevant to a prospective employer; storing each said at least one resume; computing, for each said at least one resume, a term of experience for the required skill or experience-related phrase for each said at least one job requirement; and determining whether each said at least one resume is the matching resume that satisfies the job description. 194. The method of claim 180 , wherein said at least one skill or experience-related phrase includes at least one attribute for a candidate. | 0.840547 |
9,110,993 | 15 | 16 | 15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: transmitting, by a client device, a search query to a search engine; receiving, by the client device and from the search engine, data identifying resources that are responsive to the search query; obtaining a subset of the identified resources; determining, by the client device, a number of times that each term of a set of terms that occur in the obtained resources occurs in the obtained resources; transmitting, by the client device and to the search engine, an occurrence count that specifies the number of times that each term of the set of terms occurs in the obtained resources; and receiving, by the client device and from the search engine, code that, when invoked by the client device, implements controls for automatically reformulating the search query to include or exclude one or more frequently occurring terms identified in the occurrence count. | 15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: transmitting, by a client device, a search query to a search engine; receiving, by the client device and from the search engine, data identifying resources that are responsive to the search query; obtaining a subset of the identified resources; determining, by the client device, a number of times that each term of a set of terms that occur in the obtained resources occurs in the obtained resources; transmitting, by the client device and to the search engine, an occurrence count that specifies the number of times that each term of the set of terms occurs in the obtained resources; and receiving, by the client device and from the search engine, code that, when invoked by the client device, implements controls for automatically reformulating the search query to include or exclude one or more frequently occurring terms identified in the occurrence count. 16. The medium of claim 15 , comprising: determining, by the client device, that a particular resource is hosted by the search engine; transmitting, by the client device and to the search engine, a request for the particular resource; and receiving, by the client device and from the search engine, the occurrence count of the particular resource. | 0.687387 |
9,911,092 | 14 | 15 | 14. The method of claim 13 wherein the step of executing the code using the workflow engine module to manage the concurrency of the particular workflow is performed by managing threads. | 14. The method of claim 13 wherein the step of executing the code using the workflow engine module to manage the concurrency of the particular workflow is performed by managing threads. 15. The method of claim 14 wherein the step of generating executable code does not entail generating code to manage the threads. | 0.786667 |
9,262,535 | 16 | 25 | 16. A system comprising: an organizational tool at a first client computer, wherein the organizational tool is configured to: present a plurality of content items, wherein the plurality of content items are received from one or more sources, via a network, at the first client computer, and wherein each of the plurality of content items is a copy of a content item or a reference to a content item; receive a first user's interactions with the plurality of content items, wherein the first user's interactions comprise steps to organize the plurality of content items within a first local hierarchy of folders maintained by the organizational tool; and transmit the first user's interactions, via the network, to a server computer; and a policy engine at the server computer, wherein the policy engine is configured to determine whether to update a global hierarchy of folders comprising the plurality of content items based on the first user's interactions and interactions of at least one other user. | 16. A system comprising: an organizational tool at a first client computer, wherein the organizational tool is configured to: present a plurality of content items, wherein the plurality of content items are received from one or more sources, via a network, at the first client computer, and wherein each of the plurality of content items is a copy of a content item or a reference to a content item; receive a first user's interactions with the plurality of content items, wherein the first user's interactions comprise steps to organize the plurality of content items within a first local hierarchy of folders maintained by the organizational tool; and transmit the first user's interactions, via the network, to a server computer; and a policy engine at the server computer, wherein the policy engine is configured to determine whether to update a global hierarchy of folders comprising the plurality of content items based on the first user's interactions and interactions of at least one other user. 25. The system of claim 16 , wherein the organizational tool is further configured to receive the plurality of content items in an organized format based on the organization of the global hierarchy of folders. | 0.739401 |
7,693,829 | 4 | 5 | 4. The method of claim 2 , further comprising determining document scores for the set of documents, wherein a respective document score is based on a highest match score and a total number of matches between the search pattern and the respective document in the set of documents. | 4. The method of claim 2 , further comprising determining document scores for the set of documents, wherein a respective document score is based on a highest match score and a total number of matches between the search pattern and the respective document in the set of documents. 5. The method of claim 4 , wherein the respective document score is further based on a quality of document metric. | 0.88 |
8,489,583 | 19 | 20 | 19. The system of claim 17 wherein the processor is configured to communicate the first electronic document to an image capture device. | 19. The system of claim 17 wherein the processor is configured to communicate the first electronic document to an image capture device. 20. The system of claim 19 wherein the image capture device is a mobile phone equipped with a camera and the processor is configured to communicate the first electronic document to the mobile phone via a wireless network. | 0.5 |
9,400,783 | 19 | 20 | 19. The apparatus of claim 18 wherein the method performed by the computer further comprises: sampling a language model of the natural language represented by the ARPA table by generating an upper bound on the language model and then sequentially refining the upper bound during the sampling process using max-backoff values w(A,z) computed using the operation (4). | 19. The apparatus of claim 18 wherein the method performed by the computer further comprises: sampling a language model of the natural language represented by the ARPA table by generating an upper bound on the language model and then sequentially refining the upper bound during the sampling process using max-backoff values w(A,z) computed using the operation (4). 20. The apparatus of claim 19 wherein the method performed by the computer further comprises: performing statistical machine translation or part-of-speech tagging using the sampling of the natural language. | 0.5 |
8,046,717 | 1 | 4 | 1. A computer-implemented method, comprising: analyzing a plurality of pages of a multi-page document to identify quantity and type of rich content in each one of the plurality of pages; assigning a score to each one of the plurality of pages in the multi-page document, wherein the score for a respective one of the plurality of pages is dependent on the quantity of rich content items on the respective one of the plurality of pages and the type of each rich content item on the respective one of the plurality of pages, wherein said assigning comprises scoring each page based on the quantity and type of rich content items within that page; identifying a page of the plurality of pages with the highest score; and designating the page with the highest score to be displayed as a thumbnail of the multi-page document, wherein the thumbnail is a single visual representation for the multi-page document. | 1. A computer-implemented method, comprising: analyzing a plurality of pages of a multi-page document to identify quantity and type of rich content in each one of the plurality of pages; assigning a score to each one of the plurality of pages in the multi-page document, wherein the score for a respective one of the plurality of pages is dependent on the quantity of rich content items on the respective one of the plurality of pages and the type of each rich content item on the respective one of the plurality of pages, wherein said assigning comprises scoring each page based on the quantity and type of rich content items within that page; identifying a page of the plurality of pages with the highest score; and designating the page with the highest score to be displayed as a thumbnail of the multi-page document, wherein the thumbnail is a single visual representation for the multi-page document. 4. The method of claim 1 , further comprising displaying said thumbnail of the designated page of the multi-page document. | 0.763566 |
10,067,854 | 1 | 6 | 1. A method of debugging, comprising: receiving by a hardware debug server executing on a computer system, a first high-level language (HLL) debugging command for setting a breakpoint in an HLL software specification; translating by the hardware debug server, the first HLL debugging command into a first hardware debugging command that specifies a condition of a hardware finite state machine that is representation of the software specification; inputting the first hardware debugging command to a simulator executing on the computer system; adding a conditional breakpoint on the finite state machine by the simulator in response to the first hardware debugging command; executing a simulation of the finite state machine representation; suspending execution of the simulation in response to detecting the condition in the finite state machine; inputting by the hardware debug server, debugging information associated with the HLL software specification; inputting by the hardware debug server, debugging information that provides a mapping of elements of the HLL software specification to elements of the hardware finite state machine; and cross-referencing the debugging information associated with the HLL software specification with the mapping of the elements of the HLL software specification to the elements of the hardware finite state machine in a database, wherein the translating includes determining from the database an element of the hardware finite state machine, cross-referenced with a HLL statement specified in the first HLL debugging command. | 1. A method of debugging, comprising: receiving by a hardware debug server executing on a computer system, a first high-level language (HLL) debugging command for setting a breakpoint in an HLL software specification; translating by the hardware debug server, the first HLL debugging command into a first hardware debugging command that specifies a condition of a hardware finite state machine that is representation of the software specification; inputting the first hardware debugging command to a simulator executing on the computer system; adding a conditional breakpoint on the finite state machine by the simulator in response to the first hardware debugging command; executing a simulation of the finite state machine representation; suspending execution of the simulation in response to detecting the condition in the finite state machine; inputting by the hardware debug server, debugging information associated with the HLL software specification; inputting by the hardware debug server, debugging information that provides a mapping of elements of the HLL software specification to elements of the hardware finite state machine; and cross-referencing the debugging information associated with the HLL software specification with the mapping of the elements of the HLL software specification to the elements of the hardware finite state machine in a database, wherein the translating includes determining from the database an element of the hardware finite state machine, cross-referenced with a HLL statement specified in the first HLL debugging command. 6. The method of claim 1 , further comprising: wherein the hardware state machine references a value in a memory that is modeled in a language other than a hardware description language in which the hardware state machine is specified; registering with the simulator a callback function that accesses the memory; receiving by the hardware debug server, a second HLL debugging command that requests a value of a variable of the HLL software specification; translating by the hardware debug server, the second HLL debugging command into a second hardware debugging command that obtains a value of a signal of the hardware finite state machine; inputting the second hardware debugging command to the simulator; executing the callback function to read the value of the signal by the simulator from the memory; and outputting the value of the signal in association with a name of the variable. | 0.5 |
9,424,249 | 10 | 11 | 10. The system of claim 8 , wherein the plurality of computer instructions further cause the at least one computing device to at least designate the series of characters in the text block as the text unit according to at least one rule. | 10. The system of claim 8 , wherein the plurality of computer instructions further cause the at least one computing device to at least designate the series of characters in the text block as the text unit according to at least one rule. 11. The system of claim 10 , wherein the at least one rule specifies designating the series of characters as the text unit in response to a presence of at least one sentinel character in the text block. | 0.553097 |
9,256,597 | 3 | 4 | 3. The method of claim 2 , wherein the complementary information distance operation defines D min (x,y)=E min (x,y) that when executed yields an information distance between a first set of entities, and a second set of entities, that determines the most accurate entity by disregarding irrelevant information, where there may be irrelevant information in one or more of the sets, for the purpose of determining the most accurate entity. | 3. The method of claim 2 , wherein the complementary information distance operation defines D min (x,y)=E min (x,y) that when executed yields an information distance between a first set of entities, and a second set of entities, that determines the most accurate entity by disregarding irrelevant information, where there may be irrelevant information in one or more of the sets, for the purpose of determining the most accurate entity. 4. The method of claim 3 , wherein the information distance analysis provides a mechanism for finding the most plausible question q such that q fits one of the question patterns in Q, and q has a close distance to I. | 0.5 |
8,185,380 | 1 | 15 | 1. An information providing apparatus for a vehicle comprising: a conversation input device which inputs conversation by an audio input or manual operation by a user on a vehicle; a conversation support device, which is made to perform as a user's false conversation partner, including: a reference-keyword dictionary storage memory which memorizes a reference-keyword dictionary, in which a plurality of reference keywords are registered; a reference-keyword extraction device for retrieving a reference keyword by comparing input contents of the conversation of the user with the reference-keyword dictionary; a response sentence model storage memory which memorizes a plurality of response sentence models with an insertion blank part, in which a retrieved reference keyword or another reference keyword preliminary linked to the retrieved reference keyword within the keyword dictionary is inserted as a leading keyword so as to lead a user's next conversation input; and a conversation-leading-response-sentence creating and outputting device for creating and outputting a conversation leading response sentence, which leads the next conversation input by the user, the conversation leading response sentence being created by inserting the leading keyword corresponding to the retrieved reference keyword into the insertion blank part of the response sentence model, which is selected in accordance with the reference keyword and retrieved in an orderly manner from the response sentence model storage memory at each time of input of the conversation input by the user; a base data accumulation device for determining a user interest, which accumulates base data for determining a user interest based on a series of conversation contents of the user inputted in response to leading of the conversation support device; a service information collecting device for analyzing an object of the user interest based on contents of the accumulated base data for determining the user interest, and for collecting service information which is matched with the analyzed object of the user interest; and a service information output device for outputting the collected service information in a form of an image, audio, or those combination, wherein the conversation support device has a conversation support base data which includes the reference keyword dictionary and the response sentence models, the conversation support base data having a plurality of base data sets, each of which has different content adapted to a predetermined conversation support scene, wherein the conversation support device further includes: a conversation support scene determining device for determining occurrence of one of the predetermined conversation support scenes, and a conversation support base data switching device for switching the base data sets of the conversation support base data in response to a determined conversation support scene, wherein the reference-keyword extraction device does not conduct a syntax analysis for determining modification relation and grammatical logic analysis for word arrangement, wherein the reference-keyword extraction device retrieves the reference keyword, which is a word matched in a character string with a certain reference keyword memorized in the reference-keyword dictionary storage memory, wherein the conversation support device is configured as a chatterbot engine, which performs only both of a character string matching by referencing the reference-keyword dictionary storage memory with using the reference-keyword extraction device, and insertion of the leading keyword into the response sentence model, which is memorized in the response sentence model storage memory, with using the conversation-leading-response-sentence creating and outputting device. | 1. An information providing apparatus for a vehicle comprising: a conversation input device which inputs conversation by an audio input or manual operation by a user on a vehicle; a conversation support device, which is made to perform as a user's false conversation partner, including: a reference-keyword dictionary storage memory which memorizes a reference-keyword dictionary, in which a plurality of reference keywords are registered; a reference-keyword extraction device for retrieving a reference keyword by comparing input contents of the conversation of the user with the reference-keyword dictionary; a response sentence model storage memory which memorizes a plurality of response sentence models with an insertion blank part, in which a retrieved reference keyword or another reference keyword preliminary linked to the retrieved reference keyword within the keyword dictionary is inserted as a leading keyword so as to lead a user's next conversation input; and a conversation-leading-response-sentence creating and outputting device for creating and outputting a conversation leading response sentence, which leads the next conversation input by the user, the conversation leading response sentence being created by inserting the leading keyword corresponding to the retrieved reference keyword into the insertion blank part of the response sentence model, which is selected in accordance with the reference keyword and retrieved in an orderly manner from the response sentence model storage memory at each time of input of the conversation input by the user; a base data accumulation device for determining a user interest, which accumulates base data for determining a user interest based on a series of conversation contents of the user inputted in response to leading of the conversation support device; a service information collecting device for analyzing an object of the user interest based on contents of the accumulated base data for determining the user interest, and for collecting service information which is matched with the analyzed object of the user interest; and a service information output device for outputting the collected service information in a form of an image, audio, or those combination, wherein the conversation support device has a conversation support base data which includes the reference keyword dictionary and the response sentence models, the conversation support base data having a plurality of base data sets, each of which has different content adapted to a predetermined conversation support scene, wherein the conversation support device further includes: a conversation support scene determining device for determining occurrence of one of the predetermined conversation support scenes, and a conversation support base data switching device for switching the base data sets of the conversation support base data in response to a determined conversation support scene, wherein the reference-keyword extraction device does not conduct a syntax analysis for determining modification relation and grammatical logic analysis for word arrangement, wherein the reference-keyword extraction device retrieves the reference keyword, which is a word matched in a character string with a certain reference keyword memorized in the reference-keyword dictionary storage memory, wherein the conversation support device is configured as a chatterbot engine, which performs only both of a character string matching by referencing the reference-keyword dictionary storage memory with using the reference-keyword extraction device, and insertion of the leading keyword into the response sentence model, which is memorized in the response sentence model storage memory, with using the conversation-leading-response-sentence creating and outputting device. 15. The information providing apparatus for the vehicle claimed in claim 1 , further comprising: a car-navigation system, wherein the service information collecting device searches and collects the destination information, which suits user interesting information, as the service information on the car-navigation system. | 0.850975 |
8,856,099 | 1 | 7 | 1. A method performed by a system comprising one or more computers, the method comprising: analyzing contents of each of a plurality of resources to identify entities of a first entity type that are related to the resource, wherein analyzing the contents of each of the plurality of resources comprises: identifying occurrences of names of entities in the contents of the resource, and determining that each entity whose name occurs in the resource more than a threshold number of occurrences is related to the resource; annotating each of the plurality of resources in an index database with annotations identifying the entities that are related to the resource; determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with the first entity type; obtaining search results for the first search query from a search engine, the search results identifying a plurality of search result resources; identifying entities of the first entity type that are related to any of the plurality of search result resources identified by the search results; and selecting names of one or more of the identified entities of the first entity type to include in a response to the first search query. | 1. A method performed by a system comprising one or more computers, the method comprising: analyzing contents of each of a plurality of resources to identify entities of a first entity type that are related to the resource, wherein analyzing the contents of each of the plurality of resources comprises: identifying occurrences of names of entities in the contents of the resource, and determining that each entity whose name occurs in the resource more than a threshold number of occurrences is related to the resource; annotating each of the plurality of resources in an index database with annotations identifying the entities that are related to the resource; determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with the first entity type; obtaining search results for the first search query from a search engine, the search results identifying a plurality of search result resources; identifying entities of the first entity type that are related to any of the plurality of search result resources identified by the search results; and selecting names of one or more of the identified entities of the first entity type to include in a response to the first search query. 7. The method of claim 1 , further comprising: promoting one or more search results that identify resources that are related to one or more of the selected entity names in a ranking of the obtained search results. | 0.73038 |
8,966,478 | 11 | 14 | 11. A method according to claim 6 , wherein executing the first VM comprises executing a first instance of the first VM using a first programmable hardware component that is associated with a first hardware specification, said method further comprising: programming a second programmable hardware component that is associated with a second hardware specification based on the HDL description; and executing a second instance of the first VM using the second programmable hardware component. | 11. A method according to claim 6 , wherein executing the first VM comprises executing a first instance of the first VM using a first programmable hardware component that is associated with a first hardware specification, said method further comprising: programming a second programmable hardware component that is associated with a second hardware specification based on the HDL description; and executing a second instance of the first VM using the second programmable hardware component. 14. A method according to claim 11 , further comprising: executing a first instance of the software application using the first instance of the first VM; and executing a second instance of the software application using the second instance of the first VM, wherein the software application is certified to execute on the target hardware platform described by the HDL description. | 0.5 |
7,865,394 | 65 | 68 | 65. A method as recited in claim 60 , wherein the delivery of the multimedia message to said recipient is performed by sending emails to the recipients, wherein a unique URL is embedded in each email which points to stored message content, wherein upon the client opening the email the URL is activated and the individualized multimedia message is played for the client. | 65. A method as recited in claim 60 , wherein the delivery of the multimedia message to said recipient is performed by sending emails to the recipients, wherein a unique URL is embedded in each email which points to stored message content, wherein upon the client opening the email the URL is activated and the individualized multimedia message is played for the client. 68. A method as noted in claim 65 , wherein the unique URL is correlated with unique content in the message for the same recipient and wherein in the step of delivering the multimedia message, it is delivered in response to opening the email. | 0.5 |
7,708,429 | 16 | 19 | 16. A method for illuminating a document in a manner to receive visual information from the document while minimizing non-document light transmission comprising the acts of: providing a document housing including a transparent member; housing a document within the document housing such that the document can be viewed through the transparent member; coupling an illumination device to the document housing; directing illumination from the illumination device toward the document, wherein the act of directing the illumination from the illumination device includes bending the document housing; and blocking illumination from the illumination device that is directed in directions other than the document. | 16. A method for illuminating a document in a manner to receive visual information from the document while minimizing non-document light transmission comprising the acts of: providing a document housing including a transparent member; housing a document within the document housing such that the document can be viewed through the transparent member; coupling an illumination device to the document housing; directing illumination from the illumination device toward the document, wherein the act of directing the illumination from the illumination device includes bending the document housing; and blocking illumination from the illumination device that is directed in directions other than the document. 19. The method of claim 16 , wherein the act of blocking illumination from the illumination device that is directed in directions other than the document includes covering portions of the illumination device that would enable illumination to be directed in directions other than the document. | 0.5 |
7,712,118 | 1 | 7 | 1. A broadcast program retrieval system for retrieving a desired broadcast program among a plurality of broadcast programs, comprising: a data server including a database configured to receive and store broadcast program information, and at least one function for searching the broadcast program information, which includes at least one program retrieval identification code and other information related to broadcast programs, wherein the program retrieval identification code is a function of content and a time slot; and a user server configured to receive and store the broadcast program information, said user server operating to send to the data server at least one content keyword for searching the broadcast program information for the desired broadcast program, wherein said user server is configured to receive from the data server only program retrieval identification codes, wherein the user server that receives the program retrieval codes previously received the broadcast program information, and wherein each program identification code is included in an event information table appended to the broadcast program information, and wherein only a select number of program retrieval identification codes are received, each of the program retrieval identification codes related to said at least one content keyword as a result of the searching by the data server, wherein said broadcast program information stored on said data server is identical to said broadcast program information stored on said user server, and wherein the select number of program retrieval identification codes received from the data server enables said user server to retrieve a select number of broadcast program information stored in the user server, and allows a user to review the select number of broadcast program information and to select the desired broadcast program from among a select number of broadcast programs corresponding to the reviewed select number of broadcast program information, said broadcast programs broadcast by digital satellite. | 1. A broadcast program retrieval system for retrieving a desired broadcast program among a plurality of broadcast programs, comprising: a data server including a database configured to receive and store broadcast program information, and at least one function for searching the broadcast program information, which includes at least one program retrieval identification code and other information related to broadcast programs, wherein the program retrieval identification code is a function of content and a time slot; and a user server configured to receive and store the broadcast program information, said user server operating to send to the data server at least one content keyword for searching the broadcast program information for the desired broadcast program, wherein said user server is configured to receive from the data server only program retrieval identification codes, wherein the user server that receives the program retrieval codes previously received the broadcast program information, and wherein each program identification code is included in an event information table appended to the broadcast program information, and wherein only a select number of program retrieval identification codes are received, each of the program retrieval identification codes related to said at least one content keyword as a result of the searching by the data server, wherein said broadcast program information stored on said data server is identical to said broadcast program information stored on said user server, and wherein the select number of program retrieval identification codes received from the data server enables said user server to retrieve a select number of broadcast program information stored in the user server, and allows a user to review the select number of broadcast program information and to select the desired broadcast program from among a select number of broadcast programs corresponding to the reviewed select number of broadcast program information, said broadcast programs broadcast by digital satellite. 7. A broadcast program retrieval system according to claim 1 , further comprising: a keyword database in the data server, said keyword database including a plurality of keywords used to match said at least one content keyword received from the user server. | 0.703016 |
8,744,987 | 14 | 19 | 14. At least one computer program provided on at least one tangible non-transitory computer readable storage medium and comprising code that when executed causes at least one computer to perform the following: training a machine learning classifier with a set of labeled training data, such that the trained classifier is operable to determine a score with respect to the classification of cases for a category; determining at least one first distribution of scores for positive cases in the training set, wherein a positive case is a case that belongs to the category; determining at least one second distribution of scores for negative cases in the training set, wherein a negative case is a case that does not belong to the category; determining a mixture of the at least one first distribution of scores and the at least one second distribution of scores; determining a third distribution of scores generated by the classifier classifying cases in a set of target data; and estimating a proportion of cases in the target set that are positive cases by fitting the mixture to the third distribution. | 14. At least one computer program provided on at least one tangible non-transitory computer readable storage medium and comprising code that when executed causes at least one computer to perform the following: training a machine learning classifier with a set of labeled training data, such that the trained classifier is operable to determine a score with respect to the classification of cases for a category; determining at least one first distribution of scores for positive cases in the training set, wherein a positive case is a case that belongs to the category; determining at least one second distribution of scores for negative cases in the training set, wherein a negative case is a case that does not belong to the category; determining a mixture of the at least one first distribution of scores and the at least one second distribution of scores; determining a third distribution of scores generated by the classifier classifying cases in a set of target data; and estimating a proportion of cases in the target set that are positive cases by fitting the mixture to the third distribution. 19. The at least one computer program of claim 14 , further comprising: wherein the training data comprises a plurality of disjoint subsets of cases; the at least one first distribution comprises a distribution of scores for positive cases determined for each subset; and the at least one second distribution comprises a distribution of scores for negative cases determined for each subset. | 0.737903 |
10,074,361 | 18 | 19 | 18. The method of claim 15 , wherein the calculating of the acoustic score of the first speech comprises using two acoustic scores of frames of the second speech as acoustic scores of two frames of the first speech that correspond to the two frames of the second speech and using at least one acoustic score of the frames of the second speech for an acoustic score of an adjacent frame, of the first speech, that is adjacent to the two frames of the first speech. | 18. The method of claim 15 , wherein the calculating of the acoustic score of the first speech comprises using two acoustic scores of frames of the second speech as acoustic scores of two frames of the first speech that correspond to the two frames of the second speech and using at least one acoustic score of the frames of the second speech for an acoustic score of an adjacent frame, of the first speech, that is adjacent to the two frames of the first speech. 19. The method of claim 18 , wherein the calculating of the acoustic score of the first speech comprises using an acoustic score of either one of the two frames of the first speech or one of the two frames of the second speech as the acoustic score of the adjacent frame based on a determined temporal distance between the adjacent frame and the two frames of the first speech which are temporally on both sides of the adjacent frame. | 0.637124 |
8,788,270 | 1 | 2 | 1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker. | 1. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristics of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristics of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein determining the emotion state of the speaker based on the comparison occurs within one day of receiving the subject utterance of speech by the speaker. 2. The method according to claim 1 , wherein providing an acoustic space comprises analyzing training data to determine the at least one baseline acoustic characteristic for each of the one or more dimensions of the acoustic space. | 0.834527 |
8,155,943 | 24 | 34 | 24. A computer-implemented method for converting a computer aided design drawing file of an electrical power system comprising a plurality of components into one or more component objects for power analytic analysis and simulation, comprising: monitoring real-time data from one or more sensors interfaced with the electrical power system; monitoring predicted operational data generated using a virtual system model of the electrical power system, the virtual system model comprising virtual component data corresponding to the plurality of components of the electrical power system; synchronizing the virtual system model in real-time based on a difference between the real-time data and the predicted operational data importing a computer aided design drawing file; parsing, by at least one computer processor, the computer aided design drawing file into a plurality of component objects corresponding to the plurality of components of the electrical power system, each of the plurality of component objects comprising a component symbol; assigning a component classification to the component symbol of each of the plurality of component objects, wherein the component classification comprises one or more attributes which define at least one of an electrical characteristic, connectivity characteristics, and interdependency characteristic of the associated component object; receiving a modification of one or more attributes of a component classification; updating the computer aided design drawing file based on the modification; and updating the virtual system model based on the updated computer aided design drawing file. | 24. A computer-implemented method for converting a computer aided design drawing file of an electrical power system comprising a plurality of components into one or more component objects for power analytic analysis and simulation, comprising: monitoring real-time data from one or more sensors interfaced with the electrical power system; monitoring predicted operational data generated using a virtual system model of the electrical power system, the virtual system model comprising virtual component data corresponding to the plurality of components of the electrical power system; synchronizing the virtual system model in real-time based on a difference between the real-time data and the predicted operational data importing a computer aided design drawing file; parsing, by at least one computer processor, the computer aided design drawing file into a plurality of component objects corresponding to the plurality of components of the electrical power system, each of the plurality of component objects comprising a component symbol; assigning a component classification to the component symbol of each of the plurality of component objects, wherein the component classification comprises one or more attributes which define at least one of an electrical characteristic, connectivity characteristics, and interdependency characteristic of the associated component object; receiving a modification of one or more attributes of a component classification; updating the computer aided design drawing file based on the modification; and updating the virtual system model based on the updated computer aided design drawing file. 34. The computer-implemented method for converting a computer aided design drawing file of an electrical power system into one or more component objects for power analytic analysis and simulation, as recited in claim 24 , wherein the one or more attributes are stored in an equipment attribute database. | 0.620301 |
7,844,599 | 14 | 20 | 14. A machine-readable volatile or non-volatile medium storing instructions, wherein said instructions are instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: receiving a not-yet-submitted user search query from a client node; wherein the not-yet-submitted user search query is a partial, not completely formed search query; wherein the not-yet-submitted user search query is received after the steps of: prior to the user finalizing and submitting the search query, determining that the not-yet-submitted user search query meets search initiation criteria; in response to receiving the not-yet submitted user search query, generating a set of suggested query candidates; generating a biased parameter, wherein the parameter is associated with a suggested query candidate of the set of suggested query candidates, and the parameter is biased based on an attribute associated with the suggested query candidate; selecting one or more of suggested query candidates of the set of suggested query candidates to be suggested queries for the search query based on the biased parameter associated with the suggested query candidate; determining relevance of at least one of the suggested queries of the one or more suggested query candidates; in response to determining that the relevance of said at least one of the suggested queries meets or exceeds a relevance threshold, providing said at least one of the suggested queries to the client node; receiving, from the client node, a search request including one of the suggested queries as a completely formed query; and in response to receiving the search request including one of the suggested queries as a completely formed query, sending search results back to the client node; wherein search results include a list of links to files or pages. | 14. A machine-readable volatile or non-volatile medium storing instructions, wherein said instructions are instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of: receiving a not-yet-submitted user search query from a client node; wherein the not-yet-submitted user search query is a partial, not completely formed search query; wherein the not-yet-submitted user search query is received after the steps of: prior to the user finalizing and submitting the search query, determining that the not-yet-submitted user search query meets search initiation criteria; in response to receiving the not-yet submitted user search query, generating a set of suggested query candidates; generating a biased parameter, wherein the parameter is associated with a suggested query candidate of the set of suggested query candidates, and the parameter is biased based on an attribute associated with the suggested query candidate; selecting one or more of suggested query candidates of the set of suggested query candidates to be suggested queries for the search query based on the biased parameter associated with the suggested query candidate; determining relevance of at least one of the suggested queries of the one or more suggested query candidates; in response to determining that the relevance of said at least one of the suggested queries meets or exceeds a relevance threshold, providing said at least one of the suggested queries to the client node; receiving, from the client node, a search request including one of the suggested queries as a completely formed query; and in response to receiving the search request including one of the suggested queries as a completely formed query, sending search results back to the client node; wherein search results include a list of links to files or pages. 20. The machine-readable volatile or non-volatile medium as recited in claim 14 , wherein the suggested queries comprise at least one of: a) a predictive search query wherein a predictive search query is determined by predicting what the search query will be when completed; or b) an alternative search query wherein an alternative search query differs from the predicted search query and is determined based on the predicted search query. | 0.52694 |
7,966,304 | 1 | 7 | 1. A method of performing a search over a network, comprising: sending, from a mobile device to a server, a search request message that comprises at least one search term comprising an abbreviation, wherein the server associates context information with the at least one search term, and wherein the abbreviation is operative as a partial index; determining an interim result corresponding to the abbreviation by indexing the abbreviation into a partial index, the interim result comprising a name; and providing a result to the mobile device based on at least the interim result and the context information. | 1. A method of performing a search over a network, comprising: sending, from a mobile device to a server, a search request message that comprises at least one search term comprising an abbreviation, wherein the server associates context information with the at least one search term, and wherein the abbreviation is operative as a partial index; determining an interim result corresponding to the abbreviation by indexing the abbreviation into a partial index, the interim result comprising a name; and providing a result to the mobile device based on at least the interim result and the context information. 7. The method of claim 1 , wherein the search term consists of one or more abbreviations. | 0.932371 |
8,549,016 | 11 | 13 | 11. A computer-implemented system for providing topic broadening in interactive building of electronically-stored social indexes, comprising: electronically-stored data, comprising: a corpus of articles each comprised of online textual materials; and a hierarchically-structured tree of topics; and a social indexing system, comprising: a finite state modeler comprising: a selection module configured to designate, for each of the topics, a set of the articles in the corpus as on-topic positive training examples; and a pattern evaluator configured to find a fine-grained topic model comprising a finite state pattern that matches the on-topic positive training examples, each finite state pattern comprising a pattern evaluable against the articles, wherein the pattern identifies such articles matching the on-topic positive training examples for the corresponding topic; a characteristic word modeler configured to generate a coarse-grained topic model for each of the topics corresponding to a center of the topic, comprising: a random sampling module configured to randomly select a set of the articles in the corpus, to identify a set of characteristic words in each of the randomly-selected articles, and to determine a frequency of occurrence of each of the characteristic words identified in the set of randomly-selected articles; a selective sampling module configured to identify a set of characteristic words in each of the articles in the on-topic positive training examples, and to determine a frequency of occurrence of each of the characteristic words identified in the articles in the on-topic training examples; and a scoring module configured to assign a score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the articles in the on-topic training examples and in the set of randomly-selected articles; a filter module configured to filter new articles received into the corpus, comprising: a matching module configured to match the finite state patterns to each new article; a characteristic word evaluator configured to identify a set of characteristic words in each new article, and to determine a frequency of occurrence of each of the characteristic words identified in the each article; and a similarity scoring module configured to assign a similarity score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the new article and in the set of randomly-selected articles; and a display module configured to order the new articles for each of the topics, comprising: a new article matching module configured to match the new articles to the finite state pattern of the fine-grained topic model for the topic; a new article comparison module configured to compare, for each new article that does not match the fine-grained topic model for the topic, similarity scores for each of the characteristic words identified in the new article to the scores of the corresponding characteristic words in the coarse-grained topic model for the topic; and a display configured to display each of the new articles that was not matched by the topic's fine-grained topic model and which has similarity scores close to the topic's coarse-grained topic model's characteristic word scores as candidate articles for additional positive training examples. | 11. A computer-implemented system for providing topic broadening in interactive building of electronically-stored social indexes, comprising: electronically-stored data, comprising: a corpus of articles each comprised of online textual materials; and a hierarchically-structured tree of topics; and a social indexing system, comprising: a finite state modeler comprising: a selection module configured to designate, for each of the topics, a set of the articles in the corpus as on-topic positive training examples; and a pattern evaluator configured to find a fine-grained topic model comprising a finite state pattern that matches the on-topic positive training examples, each finite state pattern comprising a pattern evaluable against the articles, wherein the pattern identifies such articles matching the on-topic positive training examples for the corresponding topic; a characteristic word modeler configured to generate a coarse-grained topic model for each of the topics corresponding to a center of the topic, comprising: a random sampling module configured to randomly select a set of the articles in the corpus, to identify a set of characteristic words in each of the randomly-selected articles, and to determine a frequency of occurrence of each of the characteristic words identified in the set of randomly-selected articles; a selective sampling module configured to identify a set of characteristic words in each of the articles in the on-topic positive training examples, and to determine a frequency of occurrence of each of the characteristic words identified in the articles in the on-topic training examples; and a scoring module configured to assign a score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the articles in the on-topic training examples and in the set of randomly-selected articles; a filter module configured to filter new articles received into the corpus, comprising: a matching module configured to match the finite state patterns to each new article; a characteristic word evaluator configured to identify a set of characteristic words in each new article, and to determine a frequency of occurrence of each of the characteristic words identified in the each article; and a similarity scoring module configured to assign a similarity score to each characteristic word as a ratio of the respective frequencies of occurrence of the characteristic word in the new article and in the set of randomly-selected articles; and a display module configured to order the new articles for each of the topics, comprising: a new article matching module configured to match the new articles to the finite state pattern of the fine-grained topic model for the topic; a new article comparison module configured to compare, for each new article that does not match the fine-grained topic model for the topic, similarity scores for each of the characteristic words identified in the new article to the scores of the corresponding characteristic words in the coarse-grained topic model for the topic; and a display configured to display each of the new articles that was not matched by the topic's fine-grained topic model and which has similarity scores close to the topic's coarse-grained topic model's characteristic word scores as candidate articles for additional positive training examples. 13. A computer-implemented system according to claim 11 , further comprising: the selective sampling module further configured to randomly select a set of the articles in the corpus, which match the finite state patterns as a further fine-grained topic model in lieu of designating a set of the articles in the corpus as the on-topic positive training examples; and a term vector module configured to form term vectors for the characteristic words in each of the articles in the further fine-grained topic model comprising frequencies of occurrence within the further fine-grained topic model, and to average the term vectors. | 0.5 |
9,846,806 | 6 | 7 | 6. The method of claim 4 , wherein the first set of imaging data comprises at least one image of the object, wherein the at least one visual cue is expressed within the at least one image of the object. | 6. The method of claim 4 , wherein the first set of imaging data comprises at least one image of the object, wherein the at least one visual cue is expressed within the at least one image of the object. 7. The method of claim 6 , further comprising: presenting, by at least one human, at least one of the object or the at least one visual cue within a field of view of the at least one imaging device at a first time, wherein the at least one image is captured by the at least one imaging device at the first time. | 0.5 |
9,606,784 | 7 | 8 | 7. A system for determining a common sequence of ordered statements comprising: a memory; and a processor device communicatively coupled to the memory, wherein the memory is encoded with instructions for determining a common sequence of statements from one or more sets of ordered statements, and wherein the processor device is configured to: create a global list comprising a first set of links generated from a first sequence of statements of a first script, wherein a link in the first set of links indicates an ordered mapping between a source statement and a destination statement selected from the first sequence of statements, and an ordered mapping indicates that a source statement is executed before a destination statement is executed; add, to the global list, a second set of links generated from a second sequence of statements of a second script, wherein a link in the second set of links indicates an ordered mapping between a source statement and a destination statement selected from the second sequence of statements; determine, from the global list, two or more links having equivalent source statements and equivalent destination statements; add at least one of the two or more links to a first group of common sequences; and store the first group of common sequences in a database. | 7. A system for determining a common sequence of ordered statements comprising: a memory; and a processor device communicatively coupled to the memory, wherein the memory is encoded with instructions for determining a common sequence of statements from one or more sets of ordered statements, and wherein the processor device is configured to: create a global list comprising a first set of links generated from a first sequence of statements of a first script, wherein a link in the first set of links indicates an ordered mapping between a source statement and a destination statement selected from the first sequence of statements, and an ordered mapping indicates that a source statement is executed before a destination statement is executed; add, to the global list, a second set of links generated from a second sequence of statements of a second script, wherein a link in the second set of links indicates an ordered mapping between a source statement and a destination statement selected from the second sequence of statements; determine, from the global list, two or more links having equivalent source statements and equivalent destination statements; add at least one of the two or more links to a first group of common sequences; and store the first group of common sequences in a database. 8. The system of claim 7 , wherein the processor device is further configured to: determine that a first link of the first group of common sequences has a destination statement equivalent to a source statement of a second link of the first group of common sequences; determine that the first link and the second link were each generated from sequences of statements of two or more common scripts; generate a third link comprising a source statement of the first link and a destination statement of the second link; add the third link to a second group of common sequences; and store the second group of common sequences in the database. | 0.5 |
8,315,870 | 11 | 14 | 11. A speech recognition method comprising the steps of: performing a word search based on an acoustic distance between a phonetic model and a feature amount of input speech and a phoneme of a word in a language model including the phoneme and a prosodic label of the word, outputting a word hypothesis and a first score representing likelihood of the word hypothesis as a word search result, and when assuming that a recognition result of the input speech is the word hypothesis, outputting a prosodic interval and a prosodic label of the prosodic interval in the input speech; outputting a second score representing likelihood of the output prosodic label based on one of feature amounts of the input speech corresponding to the output prosodic interval; and correcting the output first score of the word hypothesis using the output second score, wherein the prosodic label is one of a tone label and an accent type, and the prosodic interval is one of a vowel interval and an accent interval. | 11. A speech recognition method comprising the steps of: performing a word search based on an acoustic distance between a phonetic model and a feature amount of input speech and a phoneme of a word in a language model including the phoneme and a prosodic label of the word, outputting a word hypothesis and a first score representing likelihood of the word hypothesis as a word search result, and when assuming that a recognition result of the input speech is the word hypothesis, outputting a prosodic interval and a prosodic label of the prosodic interval in the input speech; outputting a second score representing likelihood of the output prosodic label based on one of feature amounts of the input speech corresponding to the output prosodic interval; and correcting the output first score of the word hypothesis using the output second score, wherein the prosodic label is one of a tone label and an accent type, and the prosodic interval is one of a vowel interval and an accent interval. 14. A speech recognition method according to claim 11 , wherein the prosodic label is the tone label, and the prosodic interval is the vowel interval. | 0.732143 |
8,543,715 | 15 | 16 | 15. The system of claim 13 , wherein the network engine is configured to: increment a redirect counter value in response to receiving the redirect request; compare the incremented redirect counter value with the determined redirect limit; and ignore the redirect request when the redirect counter value exceeds the determined redirect limit. | 15. The system of claim 13 , wherein the network engine is configured to: increment a redirect counter value in response to receiving the redirect request; compare the incremented redirect counter value with the determined redirect limit; and ignore the redirect request when the redirect counter value exceeds the determined redirect limit. 16. The system of claim 15 , wherein the network engine is further configured to transmit an error code to the third-party content delivery system when the redirect counter value exceeds the determined redirect limit. | 0.5 |
9,746,929 | 10 | 18 | 10. An apparatus for recognizing gesture, comprising: one or more gesture capturing sensors; a raw data capture block configured to generate raw data of a gesture from the gesture capturing sensors; a gesture elements categorizing block configured to categorize the raw data into a plurality of gesture elements and to recategorize the raw data into different gesture elements based on a contextual dependency between the plurality of gesture elements, wherein each gesture element corresponds to a predetermined movement identified from the raw data; a contextual dependency determining block configured to determine a contextual dependency between the plurality of gesture elements, wherein the contextual dependency comprises probabilities of the plurality of gesture elements appearing next to each other in a temporal order or sequence; and a gesture recognition block configured to recognize the gesture based on the determined gesture elements. | 10. An apparatus for recognizing gesture, comprising: one or more gesture capturing sensors; a raw data capture block configured to generate raw data of a gesture from the gesture capturing sensors; a gesture elements categorizing block configured to categorize the raw data into a plurality of gesture elements and to recategorize the raw data into different gesture elements based on a contextual dependency between the plurality of gesture elements, wherein each gesture element corresponds to a predetermined movement identified from the raw data; a contextual dependency determining block configured to determine a contextual dependency between the plurality of gesture elements, wherein the contextual dependency comprises probabilities of the plurality of gesture elements appearing next to each other in a temporal order or sequence; and a gesture recognition block configured to recognize the gesture based on the determined gesture elements. 18. The apparatus of claim 10 , wherein the gesture elements categorizing block is configured to process the raw data using a Hidden Markov Model based method to determine the gesture elements. | 0.770784 |
9,058,614 | 10 | 14 | 10. A system for dynamically clustering data items, the system comprising at least one processing unit configured to: receive (a) a plurality of data items originating from at least two sources; (b) a plurality of distinct metadata details; (c) data indicative of associations between said data items and said metadata details, wherein each data item is associated with at least one metadata detail, and wherein at least a first data item originating from a first source and a second data item originating from a second source are related data items associated with at least one shared metadata detail; grade strengths of relationships between at least one of said data items and at least one of said metadata details; and cluster said data items into one or more clusters, based on the calculated grade wherein at least one of said clusters comprises related data items originating from more than one source, wherein said grade comprises applying weighting functions, and the weighting functions are rule-based weighting functions. | 10. A system for dynamically clustering data items, the system comprising at least one processing unit configured to: receive (a) a plurality of data items originating from at least two sources; (b) a plurality of distinct metadata details; (c) data indicative of associations between said data items and said metadata details, wherein each data item is associated with at least one metadata detail, and wherein at least a first data item originating from a first source and a second data item originating from a second source are related data items associated with at least one shared metadata detail; grade strengths of relationships between at least one of said data items and at least one of said metadata details; and cluster said data items into one or more clusters, based on the calculated grade wherein at least one of said clusters comprises related data items originating from more than one source, wherein said grade comprises applying weighting functions, and the weighting functions are rule-based weighting functions. 14. The system of claim 10 , wherein said processing unit is further configured to associate at least one data item with at least one additional metadata detail by utilizing information stored in a global relationships table, and wherein said grade is performed also for the at least one additional metadata detail. | 0.5 |
7,656,315 | 1 | 2 | 1. A computer Chinese character input method comprising: Selecting 10 elements corresponding to the 10 simplified Chinese character simplified strokes which are and Selecting 46 elements corresponding to the 46 stroke combination sets whose representative visual representations are: ; Assigning said 46 elements, and 8 elements, excluding and from said 10 elements, to the keyboard in the following way: TABLE 4 in the table above, elements in the same line are assigned to the same keys, while those in different lines are assigned to different keys; and Determining desired input characters based on the keystrokes typed by a user on this keyboard. | 1. A computer Chinese character input method comprising: Selecting 10 elements corresponding to the 10 simplified Chinese character simplified strokes which are and Selecting 46 elements corresponding to the 46 stroke combination sets whose representative visual representations are: ; Assigning said 46 elements, and 8 elements, excluding and from said 10 elements, to the keyboard in the following way: TABLE 4 in the table above, elements in the same line are assigned to the same keys, while those in different lines are assigned to different keys; and Determining desired input characters based on the keystrokes typed by a user on this keyboard. 2. The invention of claim 1 , further comprising the step of assigning said 46 elements and the 8 elements to the standard English QWERTY keyboard in the following way: A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Caps Lock in the table above, the first 26 items in the first column from the left “stand for” are the English letter of the QWERTY keyboard, and “Caps Lock” is the capital lock key on the QWERTY keyboard. Elements in the same lines are assigned to the key that the English letter or the “Caps Lock” in that line is on. | 0.5 |
8,012,181 | 13 | 18 | 13. A bone stabilization component comprising: a deflectable post mounted in a shield; the deflectable post having a mount at a proximal end; the mount extending beyond the shield; the deflectable post being configured to allow compliant deflection of the mount relative to the shield; and a connector attached to the shield and adapted to secure the shield to a bone anchor so that the deflectable post is substantially in-line with the bone anchor and the mount is exposed and adapted for connection of a bone-stabilizing rod; and wherein: the deflectable post comprises a flexible shaft located within a bore of the shield; the bore of the shield and the shaft are substantially coaxial with the shield; and a compliant sleeve is positioned within the bore of the shield between the flexible shaft and the shield. | 13. A bone stabilization component comprising: a deflectable post mounted in a shield; the deflectable post having a mount at a proximal end; the mount extending beyond the shield; the deflectable post being configured to allow compliant deflection of the mount relative to the shield; and a connector attached to the shield and adapted to secure the shield to a bone anchor so that the deflectable post is substantially in-line with the bone anchor and the mount is exposed and adapted for connection of a bone-stabilizing rod; and wherein: the deflectable post comprises a flexible shaft located within a bore of the shield; the bore of the shield and the shaft are substantially coaxial with the shield; and a compliant sleeve is positioned within the bore of the shield between the flexible shaft and the shield. 18. The bone stabilization component of claim 13 , wherein said connector is releasable to permit removal of the bone stabilization component from the bone anchor. | 0.806413 |
8,457,968 | 3 | 5 | 3. The method of claim 1 , wherein the update process computes an estimated new belief. | 3. The method of claim 1 , wherein the update process computes an estimated new belief. 5. The method of claim 3 , wherein the estimated new belief further comprises a term which accounts for all actions not yet observed. | 0.67561 |
7,680,749 | 20 | 21 | 20. The method of claim 17 wherein for implicit conditions, learning conditional variants further comprises: for each driving session, forming a mini-model for a target attribute by statistically merging attribute data computed for that driving session; identifying pairs of like mini-models using a similarity metric; and forming a conditional variant model based on attribute data from pairs of like mini-models. | 20. The method of claim 17 wherein for implicit conditions, learning conditional variants further comprises: for each driving session, forming a mini-model for a target attribute by statistically merging attribute data computed for that driving session; identifying pairs of like mini-models using a similarity metric; and forming a conditional variant model based on attribute data from pairs of like mini-models. 21. The method of claim 20 further comprising: in response to a stopping criterion not being met, repeating the identifying and forming a conditional variant model until the stopping criterion is met. | 0.5 |
7,650,272 | 17 | 18 | 17. An apparatus for automatically evaluating Bayesian network models for decision support, the apparatus comprising a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving user input and data input, and an output coupled with the processor for outputting display data, wherein the computer system further comprises means, residing in its processor and memory, 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. | 17. An apparatus for automatically evaluating Bayesian network models for decision support, the apparatus comprising a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving user input and data input, and an output coupled with the processor for outputting display data, wherein the computer system further comprises means, residing in its processor and memory, 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. 18. An apparatus for automatically evaluating Bayesian network models for decision support as set forth in claim 17 , wherein the BN model further includes at least one auxiliary node causally linked between at least one evidence node and at least one conclusion node. | 0.702882 |
7,634,398 | 11 | 12 | 11. A computer-readable storage medium having encoded thereon computer-executable instructions that when executed by a processor cause the processor to perform steps comprising: forming an initial parse structure having multiple levels of nodes for an input text, each node above a lowest level formed by executing a respective rule that accepts at least one node from a lower level to form the node; identifying one of the nodes in the initial parse structure as a reattach node; forming a queue comprising a list of nodes and rules used to form the initial parse structure and at least one additional rule that accepts two nodes from a lower level to form a node, the list comprising a separate entry for each node and each rule, the queue formed by deconstructing the initial parse structure and adding the at least one additional rule to the queue, wherein the at least one additional rule is not deconstructed from the initial parse structure and wherein the queue does not include a rule that accepted the reattach node as a node from a lower level to form a node in the initial parse structure and wherein at least one node in the queue is not affected by moving the reattach node from its position in the initial parse structure; and forming a reconstructed parse structure based on the nodes and rules in the queue by: sequentially retrieving entries from the queue based on the order of the entries in the queue; for each node retrieved from the queue, placing the node in a working stack; and for each rule retrieved from the queue, including the at least one additional rule: determining a number of nodes required by the rule; removing the determined number of nodes from the top of the working stack; executing the rule using the nodes removed from the working stack to form a resulting node for the reconstructed parse structure; and placing the resulting node at the top of the working stack. | 11. A computer-readable storage medium having encoded thereon computer-executable instructions that when executed by a processor cause the processor to perform steps comprising: forming an initial parse structure having multiple levels of nodes for an input text, each node above a lowest level formed by executing a respective rule that accepts at least one node from a lower level to form the node; identifying one of the nodes in the initial parse structure as a reattach node; forming a queue comprising a list of nodes and rules used to form the initial parse structure and at least one additional rule that accepts two nodes from a lower level to form a node, the list comprising a separate entry for each node and each rule, the queue formed by deconstructing the initial parse structure and adding the at least one additional rule to the queue, wherein the at least one additional rule is not deconstructed from the initial parse structure and wherein the queue does not include a rule that accepted the reattach node as a node from a lower level to form a node in the initial parse structure and wherein at least one node in the queue is not affected by moving the reattach node from its position in the initial parse structure; and forming a reconstructed parse structure based on the nodes and rules in the queue by: sequentially retrieving entries from the queue based on the order of the entries in the queue; for each node retrieved from the queue, placing the node in a working stack; and for each rule retrieved from the queue, including the at least one additional rule: determining a number of nodes required by the rule; removing the determined number of nodes from the top of the working stack; executing the rule using the nodes removed from the working stack to form a resulting node for the reconstructed parse structure; and placing the resulting node at the top of the working stack. 12. The computer-readable storage medium of claim 11 wherein forming a queue comprises: identifying a target node in the initial parse structure, wherein the reattach node was not combined with the target node by a rule to form another node in the initial parse structure; selecting a reattach rule to combine the reattach node to the target node to form a node at a higher level from the target node in the reconstructed parse structure; and placing the reattach rule in the queue as the at least one additional rule. | 0.5 |
8,185,373 | 1 | 16 | 1. A method of assessing quality of language translation and interpretation, comprising the steps of: a) receiving on a computing device source material in a first language and a translation of the source material, where the language of the translation is selected from the group of languages consisting of a language that is different from the first language, a language that is the same as the first language but in a different dialect, and the same language as the first language, where a translation into the same language includes translation slang in a first language to proper speech in the first language; b) identifying on the computing device the source material's content and format; c) assigning on the computing device a first rating to the source material's level of difficulty in translating the source material based on the result of step (b); d) determining on the computing device the translation's type; e) assigning on the computing device a second rating to the translation's accuracy as compared to the source material for its type as determined in step (d); f) assigning on the computing device a third rating to the degree to which the translation interprets the source material's intended message; g) assigning on the computing device a fourth rating to the format of the translation; and h) evaluating on the computing device the results of step (c), step (e), step (f), and step (g) to determine an assessment of the translation's language translation and interpretation. | 1. A method of assessing quality of language translation and interpretation, comprising the steps of: a) receiving on a computing device source material in a first language and a translation of the source material, where the language of the translation is selected from the group of languages consisting of a language that is different from the first language, a language that is the same as the first language but in a different dialect, and the same language as the first language, where a translation into the same language includes translation slang in a first language to proper speech in the first language; b) identifying on the computing device the source material's content and format; c) assigning on the computing device a first rating to the source material's level of difficulty in translating the source material based on the result of step (b); d) determining on the computing device the translation's type; e) assigning on the computing device a second rating to the translation's accuracy as compared to the source material for its type as determined in step (d); f) assigning on the computing device a third rating to the degree to which the translation interprets the source material's intended message; g) assigning on the computing device a fourth rating to the format of the translation; and h) evaluating on the computing device the results of step (c), step (e), step (f), and step (g) to determine an assessment of the translation's language translation and interpretation. 16. The method of claim 1 , wherein said step of determining on the computing device the translation's type is comprised of the step of determining on the computing device the translation's type selected from the group of translation types consisting of verbatim translation of the source material, gist of the source material, gist of the source material on a user-definable topic, and any combination thereof. | 0.818783 |
7,502,770 | 6 | 8 | 6. The system of claim 2 , wherein said tutor keeps track of data about said user, and data about said database; and wherein all user-specific data are private and inaccessible to others. | 6. The system of claim 2 , wherein said tutor keeps track of data about said user, and data about said database; and wherein all user-specific data are private and inaccessible to others. 8. The system of claim 6 , wherein said tutor follows explicit paths that have been laid down by teachers, taking advantage of their suggestions about how to present said data. | 0.627119 |
7,614,052 | 23 | 33 | 23. A distributed computing system for developing and deploying a smart client application from a server to a client machine via a network, said system comprising: a server-side application comprising at least one markup document and at least one business logic component, wherein said markup document is written using any declarative Extensible Markup Language (XML) and said business logic component is written using any programming language; a compiler for compiling said business logic component into a specific executable code, wherein said compiler is adapted to receive a business logic component written in any programming language and to compile said business logic component into a specific executable code that can be executed by a specific execution engine in said client machine; a markup language converter for converting said markup document into a specific markup language document, wherein said markup language converter is adapted to receive a markup document written in any XML language and to convert said markup document into a specific markup language document that is compatible with a specific client runtime environment (CRE) of said client machine; and a network server for deploying said specific markup document and said specific executable code to said client machine via said network. | 23. A distributed computing system for developing and deploying a smart client application from a server to a client machine via a network, said system comprising: a server-side application comprising at least one markup document and at least one business logic component, wherein said markup document is written using any declarative Extensible Markup Language (XML) and said business logic component is written using any programming language; a compiler for compiling said business logic component into a specific executable code, wherein said compiler is adapted to receive a business logic component written in any programming language and to compile said business logic component into a specific executable code that can be executed by a specific execution engine in said client machine; a markup language converter for converting said markup document into a specific markup language document, wherein said markup language converter is adapted to receive a markup document written in any XML language and to convert said markup document into a specific markup language document that is compatible with a specific client runtime environment (CRE) of said client machine; and a network server for deploying said specific markup document and said specific executable code to said client machine via said network. 33. The system of claim 23 wherein said at least one markup document is written in HTML language and said markup language converter converts said HTML markup document into an XML markup document. | 0.723011 |
9,767,788 | 1 | 9 | 1. A method for speech synthesis based on a large Chinese corpus, comprising: utilizing a prosodic structure prediction model to carry out prosodic structure prediction processing on input text to provide at least two alternative prosodic boundary partitioning solutions, prosodic units located at a same location in the at least two alternative prosodic boundary partitioning solutions being different; acquiring structure probability information about a prosodic unit in the at least two alternative prosodic boundary partitioning solutions according to statistics taken beforehand on data in a Chinese speech corpus, wherein the structure probability information includes a structure probability that the prosodic unit appears at a head or a tail of a prosodic word, a prosodic phrase or an intonation phrase in the Chinese speech corpus; calculating output probabilities of the at least two alternative prosodic boundary partitioning solutions utilizing an output probability calculation function according to the structure probability information; and determining, in the at least two alternative prosodic boundary partitioning solutions, an alternative prosodic boundary partitioning solution of which the output probability is the maximum as a prosodic boundary partitioning solution; and carrying out speech synthesis by acoustic processing to convert the input text into a speech having a pause point and a pause time length according to the determined alternative prosodic boundary partitioning solution. | 1. A method for speech synthesis based on a large Chinese corpus, comprising: utilizing a prosodic structure prediction model to carry out prosodic structure prediction processing on input text to provide at least two alternative prosodic boundary partitioning solutions, prosodic units located at a same location in the at least two alternative prosodic boundary partitioning solutions being different; acquiring structure probability information about a prosodic unit in the at least two alternative prosodic boundary partitioning solutions according to statistics taken beforehand on data in a Chinese speech corpus, wherein the structure probability information includes a structure probability that the prosodic unit appears at a head or a tail of a prosodic word, a prosodic phrase or an intonation phrase in the Chinese speech corpus; calculating output probabilities of the at least two alternative prosodic boundary partitioning solutions utilizing an output probability calculation function according to the structure probability information; and determining, in the at least two alternative prosodic boundary partitioning solutions, an alternative prosodic boundary partitioning solution of which the output probability is the maximum as a prosodic boundary partitioning solution; and carrying out speech synthesis by acoustic processing to convert the input text into a speech having a pause point and a pause time length according to the determined alternative prosodic boundary partitioning solution. 9. The method of claim 1 , wherein the prosodic units at the same location in the at least two alternative prosodic boundary partitioning solutions includes the prosodic units at a same target location of a same target prosodic hierarchy at a same sequential position in each of the at least two alternative prosodic boundary partitioning solutions, wherein the target prosodic hierarchy includes a prosodic word, a prosodic phrase, or an intonation phrase, and the target location include a head or a tail. | 0.64446 |
10,120,968 | 10 | 12 | 10. A system for defining and processing hardware description language (HDL) groups for use with an electronic circuit design to be fabricated comprising: a computing device having at least one processor configured to map one or more tool-specific objects into a group graph having one or more groups arranged as nodes in the group graph, wherein the group graph is configured as a data structure, wherein each of the one or more groups includes at least one sub-group, library information, and HDL design information, generate a search order associated with each of the one or more groups within the group graph and wherein the search order is determined, based upon, at least in part, a command line structure, wherein the search order associated with each of the one or more groups is based upon, at least in part, a hierarchical design configuration of the group graph, identify one or more undefined references from within a first group of the one or more groups within the group graph, bind one or more defined references from within the first group to one or more electronic circuit design components, and identify the one or more undefined references from within a second group of the one or more groups within the group graph, wherein the second group is selected based upon, at least in part, the one or more undefined references and the search order associated with the first group of the one or more groups. | 10. A system for defining and processing hardware description language (HDL) groups for use with an electronic circuit design to be fabricated comprising: a computing device having at least one processor configured to map one or more tool-specific objects into a group graph having one or more groups arranged as nodes in the group graph, wherein the group graph is configured as a data structure, wherein each of the one or more groups includes at least one sub-group, library information, and HDL design information, generate a search order associated with each of the one or more groups within the group graph and wherein the search order is determined, based upon, at least in part, a command line structure, wherein the search order associated with each of the one or more groups is based upon, at least in part, a hierarchical design configuration of the group graph, identify one or more undefined references from within a first group of the one or more groups within the group graph, bind one or more defined references from within the first group to one or more electronic circuit design components, and identify the one or more undefined references from within a second group of the one or more groups within the group graph, wherein the second group is selected based upon, at least in part, the one or more undefined references and the search order associated with the first group of the one or more groups. 12. The system of claim 10 , wherein the at least one processor is further configured to generate a library catalog with information acquired during the identification of the one or more undefined references from within the first group and the identification of the one or more undefined references from within the second group. | 0.548209 |
9,753,909 | 26 | 30 | 26. A tangible computer-readable memory having instructions stored in the memory that implement the actions including: accessing in memory a set of events each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data; causing display of a first user interface including a plurality of events; receiving data indicating selection of a first event from among the plurality of events; causing display of a second user interface presenting the first event to be used to define field extraction; receiving data indicating a selection of one or more portions of text within the first event to be extracted as one or more fields; automatically determining at least one field extraction rule that extracts one or more values for the one or more fields from the respective selections of the portions of text within the events when the extraction rule is applied to the events; causing display of a third user interface including an annotated version of the plurality of events, wherein the annotated version indicates the portions of text within the plurality of events extracted by the field extraction rule and presenting a second event to be used to refine field extraction; and receiving further data indicating a selection of at least one portion of text within the second event to be extracted as into at least one of the fields by at least one updated field extraction rule. | 26. A tangible computer-readable memory having instructions stored in the memory that implement the actions including: accessing in memory a set of events each event identified by an associated time stamp; wherein each event in the set of events includes a portion of raw data; causing display of a first user interface including a plurality of events; receiving data indicating selection of a first event from among the plurality of events; causing display of a second user interface presenting the first event to be used to define field extraction; receiving data indicating a selection of one or more portions of text within the first event to be extracted as one or more fields; automatically determining at least one field extraction rule that extracts one or more values for the one or more fields from the respective selections of the portions of text within the events when the extraction rule is applied to the events; causing display of a third user interface including an annotated version of the plurality of events, wherein the annotated version indicates the portions of text within the plurality of events extracted by the field extraction rule and presenting a second event to be used to refine field extraction; and receiving further data indicating a selection of at least one portion of text within the second event to be extracted as into at least one of the fields by at least one updated field extraction rule. 30. The tangible computer-readable memory of claim 26 , further including: the second user interface providing tools that implement user selection of among the fields; receiving further data indicating a selection of a selected field; and transmitting data for a frequency display of values of the selected field extracted from a sample of the events, wherein the frequency display includes a list of values extracted and for each value in the list a frequency and an active filter control, wherein the active filter control filters events to be displayed based on a selected value. | 0.5 |
10,019,428 | 9 | 10 | 9. The computer program product of claim 1 wherein the commercial data includes data for at least data for at least one of products, stores, and transactions. | 9. The computer program product of claim 1 wherein the commercial data includes data for at least data for at least one of products, stores, and transactions. 10. The computer program product of claim 9 wherein the commercial data includes at least one of a total volume of sales of a product at a particular store, a collection of stores, or a geographic area. | 0.5 |
9,015,043 | 1 | 18 | 1. A computer-implemented method comprising: receiving an electronic representation of a conversation between a plurality of human voices; recognizing one or more words in a first portion of the electronic representation of the conversation; recognizing one or more words in a second portion of the electronic representation of the conversation, wherein the second portion is different from the first portion, wherein the first portion has a duration from a first time to a second time, and wherein the second portion has a duration from a third time to a fourth time, the third time being after the first time and before the second time; selecting search terms for a search query, wherein the search terms include: at least one word from the one or more recognized words in the first portion that is selected as a search term based on whether the word is a proper noun, based on an inverse of a frequency of the word in a corpus of documents, and based on a number of times that the word is recognized in the first portion of the electronic representation of the conversation, at least one word that was not spoken in the conversation and is related to a word that was spoken in the conversation, and one or more words recognized in the second portion of the electronic representation of the conversation; causing the search terms to be displayed on a display device in a text format; receiving a search query that includes at least one of the search terms. | 1. A computer-implemented method comprising: receiving an electronic representation of a conversation between a plurality of human voices; recognizing one or more words in a first portion of the electronic representation of the conversation; recognizing one or more words in a second portion of the electronic representation of the conversation, wherein the second portion is different from the first portion, wherein the first portion has a duration from a first time to a second time, and wherein the second portion has a duration from a third time to a fourth time, the third time being after the first time and before the second time; selecting search terms for a search query, wherein the search terms include: at least one word from the one or more recognized words in the first portion that is selected as a search term based on whether the word is a proper noun, based on an inverse of a frequency of the word in a corpus of documents, and based on a number of times that the word is recognized in the first portion of the electronic representation of the conversation, at least one word that was not spoken in the conversation and is related to a word that was spoken in the conversation, and one or more words recognized in the second portion of the electronic representation of the conversation; causing the search terms to be displayed on a display device in a text format; receiving a search query that includes at least one of the search terms. 18. The method of claim 1 , wherein selecting the search terms for the search query is further based on a time at which the word was spoken in the conversation, wherein words spoken more recently are displayed more prominently on the display device. | 0.741164 |
8,612,230 | 7 | 12 | 7. Apparatus for automatic speech recognition (‘ASR’) for use with a speech recognition grammar of a multimodal application, with the multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and a visual mode, the multimodal application operatively coupled to a grammar interpreter and configured to enable a user of the multimodal application to select or deselect multiple items in a selection list using a single utterance, the apparatus comprising: a computer processor; and a computer memory operatively coupled to the computer processor, the computer memory storing a computer program that, when executed by the computer processor, performs a method comprising: accepting by the multimodal application speech input corresponding to the single utterance for selecting or deselecting one or more items in the selection list; providing, from the multimodal application to the grammar interpreter, the speech input and a speech recognition grammar associated with the selection list; receiving, by the multimodal application from the grammar interpreter, interpretation results, the interpretation results including at least one matched word from the grammar that identifies at least one item in the selection list and a separate indication of whether to select or deselect the at least one item in the selection list, wherein the separate indication is based, at least in part, on the speech input; and selecting or deselecting, based, at least in part, on the separate indication, the at least one item in the selection list that corresponds to the at least one matched word. | 7. Apparatus for automatic speech recognition (‘ASR’) for use with a speech recognition grammar of a multimodal application, with the multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and a visual mode, the multimodal application operatively coupled to a grammar interpreter and configured to enable a user of the multimodal application to select or deselect multiple items in a selection list using a single utterance, the apparatus comprising: a computer processor; and a computer memory operatively coupled to the computer processor, the computer memory storing a computer program that, when executed by the computer processor, performs a method comprising: accepting by the multimodal application speech input corresponding to the single utterance for selecting or deselecting one or more items in the selection list; providing, from the multimodal application to the grammar interpreter, the speech input and a speech recognition grammar associated with the selection list; receiving, by the multimodal application from the grammar interpreter, interpretation results, the interpretation results including at least one matched word from the grammar that identifies at least one item in the selection list and a separate indication of whether to select or deselect the at least one item in the selection list, wherein the separate indication is based, at least in part, on the speech input; and selecting or deselecting, based, at least in part, on the separate indication, the at least one item in the selection list that corresponds to the at least one matched word. 12. The apparatus of claim 7 wherein the multimodal device further comprises a thin multimodal client device, the thin multimodal client device obtaining grammar interpretation, semantic interpretation, and speech recognition services from a voice server located remotely across a network from the thin multimodal client device. | 0.81798 |
9,921,659 | 1 | 2 | 1. A computer-implemented method, comprising: acquiring, by a computing device, image data over a period of time; storing the image data in a buffer; determining a first movement of at least a portion of a hand represented in a first portion of the image data; determining the first movement does not match gesture information in a gesture library; determining, after determining the first movement does not match the gesture information, a second movement of at least a portion of the hand represented in a second portion of the image data stored in the buffer, the second portion of the image data being acquired previous to the first portion of the image data in the period of time; determining, from the first movement and the second movement, a combined movement; determining gesture information in the gesture library that matches the combined movement; and sending an input, corresponding to the gesture information, to an application executing on the computing device. | 1. A computer-implemented method, comprising: acquiring, by a computing device, image data over a period of time; storing the image data in a buffer; determining a first movement of at least a portion of a hand represented in a first portion of the image data; determining the first movement does not match gesture information in a gesture library; determining, after determining the first movement does not match the gesture information, a second movement of at least a portion of the hand represented in a second portion of the image data stored in the buffer, the second portion of the image data being acquired previous to the first portion of the image data in the period of time; determining, from the first movement and the second movement, a combined movement; determining gesture information in the gesture library that matches the combined movement; and sending an input, corresponding to the gesture information, to an application executing on the computing device. 2. The computer-implemented method of claim 1 , wherein the first portion of the image data and the second portion of the image data correspond to at least one of partially overlapping or adjacent periods in time. | 0.754042 |
8,335,802 | 2 | 3 | 2. The method of claim 1 , wherein the data is retrieved from the one or more data repositories using a reporting object, wherein the user interface includes a page from which the producer method is selected from the plurality of producer methods, the converted method is selected from the plurality of converter methods, and the distributor method is selected from the plurality of distributor methods. | 2. The method of claim 1 , wherein the data is retrieved from the one or more data repositories using a reporting object, wherein the user interface includes a page from which the producer method is selected from the plurality of producer methods, the converted method is selected from the plurality of converter methods, and the distributor method is selected from the plurality of distributor methods. 3. The method of claim 2 , wherein the document generated with the producer method is defined by the reporting object. | 0.593103 |
8,332,251 | 1 | 11 | 1. A computer-implemented method, used in an Agile environment, for allocating resources across a plurality of stories in a project during a release and scheduling the stories across a plurality of iterations within the release, wherein 1) each story represents at least one task executable by an appropriate resource and 2) the release represents a deadline for delivering the stories and is divided into one or more iterations representative of a sequence of time periods within the release, the method comprising: receiving, at a computing device, (i) resource information representing a plurality of resources available for allocation to the stories, (ii) one or more story-level constraints corresponding to each story, and iii) one or more optimization criteria for a level different from a story level, including an objective function defined by the equation max ( ∑ k = 1 n F [ S k ] S [ S k ] ) wherein n represents the number of stories in one or more iterations, S k represents the kth story in the one or more iterations, function F represents a feature-points function, and function S represents a successful and on-time completion function; applying, using the computing device, a first-level optimization scheme to generate a plurality of story-level allocation scenarios, wherein applying the first-level optimization scheme comprises: assigning an iteration to each of the stories; allocating one or more of the plurality of resources to one or more of the stories; and satisfying the one or more story-level constraints associated with each story; and applying, using the computing device, a second-level optimization scheme to determine one or more optimized story-level allocation scenarios from the plurality of story-level allocation scenarios, by optimizing assignment of iterations and allocation of resources to the stories while satisfying the one or more optimization criteria. | 1. A computer-implemented method, used in an Agile environment, for allocating resources across a plurality of stories in a project during a release and scheduling the stories across a plurality of iterations within the release, wherein 1) each story represents at least one task executable by an appropriate resource and 2) the release represents a deadline for delivering the stories and is divided into one or more iterations representative of a sequence of time periods within the release, the method comprising: receiving, at a computing device, (i) resource information representing a plurality of resources available for allocation to the stories, (ii) one or more story-level constraints corresponding to each story, and iii) one or more optimization criteria for a level different from a story level, including an objective function defined by the equation max ( ∑ k = 1 n F [ S k ] S [ S k ] ) wherein n represents the number of stories in one or more iterations, S k represents the kth story in the one or more iterations, function F represents a feature-points function, and function S represents a successful and on-time completion function; applying, using the computing device, a first-level optimization scheme to generate a plurality of story-level allocation scenarios, wherein applying the first-level optimization scheme comprises: assigning an iteration to each of the stories; allocating one or more of the plurality of resources to one or more of the stories; and satisfying the one or more story-level constraints associated with each story; and applying, using the computing device, a second-level optimization scheme to determine one or more optimized story-level allocation scenarios from the plurality of story-level allocation scenarios, by optimizing assignment of iterations and allocation of resources to the stories while satisfying the one or more optimization criteria. 11. The computer-implemented method of claim 1 wherein the resource information comprises attribute information for one or more of the plurality of resources. | 0.84981 |
9,613,132 | 12 | 13 | 12. The method of claim 1 , further comprising: (h) receiving by the client application from a user via the at least one first graphical object a tentative selection of one of the first suggested search query refinements, the tentative selection corresponding to a tentative refined search query, the tentative refined search query including the at least one first search term and at least one tentative additional search term; and (i) displaying by the client application in the search bar the tentative refined search query. | 12. The method of claim 1 , further comprising: (h) receiving by the client application from a user via the at least one first graphical object a tentative selection of one of the first suggested search query refinements, the tentative selection corresponding to a tentative refined search query, the tentative refined search query including the at least one first search term and at least one tentative additional search term; and (i) displaying by the client application in the search bar the tentative refined search query. 13. The method of claim 12 , wherein: (c) includes displaying by the client application a first plurality of buttons selectable by a user, each button in the first plurality of buttons corresponding to one of the first suggested search query refinements and including text representative of that suggested search query refinement; and (h) is receiving by the client application an indication that a pointer controlled by a user is located over a button from the first plurality of buttons. | 0.5 |
8,920,472 | 12 | 14 | 12. A system for correcting a spinal deformity, the system comprising: a first rod adapted to extend along a first side of a spine of a patient; a first anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the first anchor and the first rod is allowed to slide axially relative to the first anchor through a first pivot point and to change in at least two of pitch, yaw, and roll about the first pivot point during correction; a second anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the second anchor and is allowed to change in at least pitch and yaw about a second pivot point during correction; a second rod adapted to extend along a second side of the spine of the patient; a third anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the third anchor; a fourth anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the fourth anchor; and a lateral coupling adapted to extend laterally between the first rod and the second rod such that the lateral coupling facilitates derotation and translation of the spine, the lateral coupling comprising: an arm adapted to extend from the second side of the spine toward the first side of the spine and to receive the second rod; an adjuster adapted to be secured to the first rod; and a first connector adapted to be secured between the arm and the adjuster such that the adjuster is actuable to tension the arm toward the first rod. | 12. A system for correcting a spinal deformity, the system comprising: a first rod adapted to extend along a first side of a spine of a patient; a first anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the first anchor and the first rod is allowed to slide axially relative to the first anchor through a first pivot point and to change in at least two of pitch, yaw, and roll about the first pivot point during correction; a second anchor adapted to be fixed to a vertebra of the spine and to receive the first rod such that the first rod is secured against substantial lateral translation relative to the second anchor and is allowed to change in at least pitch and yaw about a second pivot point during correction; a second rod adapted to extend along a second side of the spine of the patient; a third anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the third anchor; a fourth anchor adapted to be fixed to a vertebra of the spine and to receive the second rod such that the second rod is secured against substantial lateral translation relative to the fourth anchor; and a lateral coupling adapted to extend laterally between the first rod and the second rod such that the lateral coupling facilitates derotation and translation of the spine, the lateral coupling comprising: an arm adapted to extend from the second side of the spine toward the first side of the spine and to receive the second rod; an adjuster adapted to be secured to the first rod; and a first connector adapted to be secured between the arm and the adjuster such that the adjuster is actuable to tension the arm toward the first rod. 14. The system of claim 12 configured such that actuation of the adjuster causes a first portion of the lateral coupling to engage with a second portion of the lateral coupling to derotate and translate the spine. | 0.561728 |
8,127,224 | 10 | 13 | 10. The computer system of claim 4 , further comprising: document editing logic configured to edit the document content entered into the data fields. | 10. The computer system of claim 4 , further comprising: document editing logic configured to edit the document content entered into the data fields. 13. The computer system of claim 10 , wherein when a particular keystroke is depressed, the document editing logic causes an input screen to be displayed to allow a user to enter information into the input screen. | 0.5 |
8,914,354 | 1 | 2 | 1. A method of estimating selectivity of a base table predicate, the method comprising: receiving, with a processor, a database query, the query comprising one or more query predicates and referencing one or more database tables; identifying, with the processor, one or more join indexes, wherein each of the one or more join index(es) is respectively defined on a single one of database tables referenced by the database query, the join index(es) comprising one or more join index predicates; calculating, with the processor, a row count of rows of the database tables referenced by the database query selected by the query predicates at least partly using a row count of the one or more join indexes or statistics of the one or more join indexes; and calculating, with the processor, selectivity of at least one of the query predicates at least partly from the calculated row count. | 1. A method of estimating selectivity of a base table predicate, the method comprising: receiving, with a processor, a database query, the query comprising one or more query predicates and referencing one or more database tables; identifying, with the processor, one or more join indexes, wherein each of the one or more join index(es) is respectively defined on a single one of database tables referenced by the database query, the join index(es) comprising one or more join index predicates; calculating, with the processor, a row count of rows of the database tables referenced by the database query selected by the query predicates at least partly using a row count of the one or more join indexes or statistics of the one or more join indexes; and calculating, with the processor, selectivity of at least one of the query predicates at least partly from the calculated row count. 2. The method of claim 1 wherein the selectivity of the at least one of the query predicates is calculated from a function of the calculated row count and a base table row count of a database table associated with the at least one of the query predicates. | 0.5 |
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