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9,245,015 | 19 | 21 |
19. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by a processor, cause the processor to: perform an alias analysis of text to identify a pair of terms, included in the text, that are alias terms, the alias analysis including at least two: a latent semantic analysis of a plurality of terms included in the text, the plurality of terms including the pair of terms; a tag-based analysis, of the pair of terms, that determines that the pair of terms are associated with compatible tags; a transitive analysis, of the pair of terms, that determines that a pair of neighbor terms, associated with the pair of terms, are associated with compatible tags; a co-location analysis, of the pair of terms, based on a distance between the pair of terms in the text; a glossary analysis, of the pair of terms, based on information that identifies synonyms associated with the pair of terms; and the alias analysis further including at least one of: a misspelling analysis, a short form analysis, or an explicit alias analysis; calculate, based on performing the alias analysis of the text, a first alias score for the pair of terms; calculate, using the first alias score for the pair of terms, a second alias score for the pair of terms; determine that the second alias score satisfies a threshold; generate, based on determining that the second alias score satisfies the threshold, a glossary that includes the pair of terms and an indication that the pair of terms are alias terms; and provide the glossary.
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19. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by a processor, cause the processor to: perform an alias analysis of text to identify a pair of terms, included in the text, that are alias terms, the alias analysis including at least two: a latent semantic analysis of a plurality of terms included in the text, the plurality of terms including the pair of terms; a tag-based analysis, of the pair of terms, that determines that the pair of terms are associated with compatible tags; a transitive analysis, of the pair of terms, that determines that a pair of neighbor terms, associated with the pair of terms, are associated with compatible tags; a co-location analysis, of the pair of terms, based on a distance between the pair of terms in the text; a glossary analysis, of the pair of terms, based on information that identifies synonyms associated with the pair of terms; and the alias analysis further including at least one of: a misspelling analysis, a short form analysis, or an explicit alias analysis; calculate, based on performing the alias analysis of the text, a first alias score for the pair of terms; calculate, using the first alias score for the pair of terms, a second alias score for the pair of terms; determine that the second alias score satisfies a threshold; generate, based on determining that the second alias score satisfies the threshold, a glossary that includes the pair of terms and an indication that the pair of terms are alias terms; and provide the glossary. 21. The non-transitory computer-readable medium of claim 19 , where the second alias score is an overall alias score for the pair of terms.
| 0.878709 |
7,827,210 | 1 | 2 |
1. A computer program product for creating an XML document that conforms to an XML schema, the computer program product comprising a computer readable medium tangibly encoded with instructions comprising instructions for: defining at least one shredding tree that each translate a hierarchical data structure into a relational data structure, each of the at least one shredding tree defining a hierarchical data structure comprising at least one cursor node and at least one data node, wherein each of the at least one cursor node defines, in conjunction with parent cursor nodes, a column within the relational data structure, and each of the at least one data node being an immediate child of a respective parent cursor node within the at least one cursor nodes, each of the at least one data node comprising a respective data element to be inserted at the column defined by the respective parent cursor node; reading at least one data element from a subset of the at least one data node of a first part of a hierarchical data structure instance using a tree traversal algorithm defined by the at least one shredding tree; storing the at least one data element in a first storage according to the relational data structure defined by a current shredding tree comprising the at least one data node containing the at least one data element; maintaining a set of tree commit counter, each tree commit counter being associated with a respective shredding tree within the at least one shredding tree; maintaining a global commit counter; decrementing, in response to the storing, a current tree commit counter within the set of tree commit counters, the current tree commit counter being associated with the current shredding tree; decrementing, in response to the storing, the global commit counter, determining, in response to the storing, that the first storage stores a quantity of data that is greater than a threshold; and outputting, in response to the determining, data stored in the first storage to a relational data structure according to the mapping.
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1. A computer program product for creating an XML document that conforms to an XML schema, the computer program product comprising a computer readable medium tangibly encoded with instructions comprising instructions for: defining at least one shredding tree that each translate a hierarchical data structure into a relational data structure, each of the at least one shredding tree defining a hierarchical data structure comprising at least one cursor node and at least one data node, wherein each of the at least one cursor node defines, in conjunction with parent cursor nodes, a column within the relational data structure, and each of the at least one data node being an immediate child of a respective parent cursor node within the at least one cursor nodes, each of the at least one data node comprising a respective data element to be inserted at the column defined by the respective parent cursor node; reading at least one data element from a subset of the at least one data node of a first part of a hierarchical data structure instance using a tree traversal algorithm defined by the at least one shredding tree; storing the at least one data element in a first storage according to the relational data structure defined by a current shredding tree comprising the at least one data node containing the at least one data element; maintaining a set of tree commit counter, each tree commit counter being associated with a respective shredding tree within the at least one shredding tree; maintaining a global commit counter; decrementing, in response to the storing, a current tree commit counter within the set of tree commit counters, the current tree commit counter being associated with the current shredding tree; decrementing, in response to the storing, the global commit counter, determining, in response to the storing, that the first storage stores a quantity of data that is greater than a threshold; and outputting, in response to the determining, data stored in the first storage to a relational data structure according to the mapping. 2. The computer program product of claim 1 , wherein each of the at least one shredding tree is associated with a single structured query language command to modify data within the relational data structure, and wherein the instructions for transferring include instructions for at least one structure query language command according to the mapping.
| 0.705882 |
8,139,900 | 24 | 26 |
24. The system of claim 21 , wherein the one or more processors are configured to perform a search of other images using a search criteria that specifies the object of the selection input.
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24. The system of claim 21 , wherein the one or more processors are configured to perform a search of other images using a search criteria that specifies the object of the selection input. 26. The system of claim 24 , wherein the search criteria is based on recognition information determined from the object of the selection input.
| 0.5 |
10,147,107 | 1 | 2 |
1. A method for generating a social sketch corresponding to a time period in response to a request, the method implemented by at least one processor having executable instructions that, when executed, perform operations comprising: obtaining social communications from a social networking service, the social communications including social communications generated during a first time period; filtering obtained social communications according to the first time period such that the filtered social communications correspond to the social communications generated during the first time period; clustering the filtered social communications according to the subject matter of the social communications to generate a plurality of clusters of filtered social communications, each cluster corresponding to a topic; identifying a set of clusters of the plurality of clusters of social communications comprising identifying those clusters of the plurality of clusters of social communications that have a sufficient volume of social communications within the cluster, each cluster of the set of the clusters being an identified cluster, and wherein the plurality of clusters of social communications that have a sufficient volume of social communications within the cluster comprises a predetermined number of clusters that have the greatest number of social communications of the plurality of clusters; for each identified cluster: extracting a topic from the identified cluster according to the subject matter of the social communications of the identified cluster; identifying a non-expert set of high-quality communications from the identified cluster, the non-expert set of high-quality communications corresponding to social communications of non-experts on the topic of the identified cluster; identifying an expert set of high-quality communications from the identified cluster, the expert set of high-quality communications corresponding to social communications of experts on the topic of the identified cluster; wherein the topic, the non-expert set of high-quality communications, and the expert set of high-quality communications comprise a cluster set of the identified cluster; and storing the cluster sets of each of the identified clusters as the social sketch corresponding to the identified time period.
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1. A method for generating a social sketch corresponding to a time period in response to a request, the method implemented by at least one processor having executable instructions that, when executed, perform operations comprising: obtaining social communications from a social networking service, the social communications including social communications generated during a first time period; filtering obtained social communications according to the first time period such that the filtered social communications correspond to the social communications generated during the first time period; clustering the filtered social communications according to the subject matter of the social communications to generate a plurality of clusters of filtered social communications, each cluster corresponding to a topic; identifying a set of clusters of the plurality of clusters of social communications comprising identifying those clusters of the plurality of clusters of social communications that have a sufficient volume of social communications within the cluster, each cluster of the set of the clusters being an identified cluster, and wherein the plurality of clusters of social communications that have a sufficient volume of social communications within the cluster comprises a predetermined number of clusters that have the greatest number of social communications of the plurality of clusters; for each identified cluster: extracting a topic from the identified cluster according to the subject matter of the social communications of the identified cluster; identifying a non-expert set of high-quality communications from the identified cluster, the non-expert set of high-quality communications corresponding to social communications of non-experts on the topic of the identified cluster; identifying an expert set of high-quality communications from the identified cluster, the expert set of high-quality communications corresponding to social communications of experts on the topic of the identified cluster; wherein the topic, the non-expert set of high-quality communications, and the expert set of high-quality communications comprise a cluster set of the identified cluster; and storing the cluster sets of each of the identified clusters as the social sketch corresponding to the identified time period. 2. The computer implemented method of claim 1 further comprising, for each of the identified clusters: re-clustering the identified cluster of social communications; identifying a set of sub-clusters of the identified cluster; and extracting a sub-topic from each of the identified sub-clusters of the set of sub-clusters of the identified cluster; wherein the topic, the non-expert set of high-quality communications, the expert set of high-quality communications, and the extracted sub-topics comprise a topic set of the identified cluster.
| 0.5 |
8,930,355 | 1 | 4 |
1. A method for searching within previous search results for new search results, the method comprising the steps of: a first computer receiving first search contexts from a second computer, the first search contexts including parameters including characteristics of elements of second search contexts and parameters including weight of importance to a user that the elements of the second search contexts includes the characteristics of the first search contexts, wherein the weight of importance represents characteristics of elements of the second search contexts that are visited by the user during a previous web page search, and wherein the characteristics of elements of second search contexts include an aggregate of search terms, search results, and data of the first search contexts and of the second search contexts, wherein the data includes user activities during a web page search of the first search contexts and the second search contexts including an accumulation of whether the user bookmarked the second search contexts and the first search contexts, how much time the user spent on the second search contexts and the first search contexts or how often the user visited the second search contexts or the first search contexts; the first computer searching for the characteristics of the elements of the second search contexts in a repository; the first computer determining a match between the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts, wherein the determination of the characteristics of elements is based on a match of uniform resource locators of the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts, wherein the determining further comprises: the first computer determining if accumulation of numerical values of both of the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts exceeds a defined threshold value, wherein the second search contexts and the first search contexts are considered a match if the accumulated numerical values exceeds the defined threshold value; the first computer determining if the second search contexts are related to the first search contexts based on the match, wherein the numerical values are assigned to the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts, and wherein the first computer ranks a first list of search results based on the determinations: the first computing merging the second search contexts and the first search contexts if the second search contexts are related to the first search contexts; the first computer creating a second list of search results based on the merge; and the first computer transmitting the second list to the second computer.
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1. A method for searching within previous search results for new search results, the method comprising the steps of: a first computer receiving first search contexts from a second computer, the first search contexts including parameters including characteristics of elements of second search contexts and parameters including weight of importance to a user that the elements of the second search contexts includes the characteristics of the first search contexts, wherein the weight of importance represents characteristics of elements of the second search contexts that are visited by the user during a previous web page search, and wherein the characteristics of elements of second search contexts include an aggregate of search terms, search results, and data of the first search contexts and of the second search contexts, wherein the data includes user activities during a web page search of the first search contexts and the second search contexts including an accumulation of whether the user bookmarked the second search contexts and the first search contexts, how much time the user spent on the second search contexts and the first search contexts or how often the user visited the second search contexts or the first search contexts; the first computer searching for the characteristics of the elements of the second search contexts in a repository; the first computer determining a match between the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts, wherein the determination of the characteristics of elements is based on a match of uniform resource locators of the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts, wherein the determining further comprises: the first computer determining if accumulation of numerical values of both of the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts exceeds a defined threshold value, wherein the second search contexts and the first search contexts are considered a match if the accumulated numerical values exceeds the defined threshold value; the first computer determining if the second search contexts are related to the first search contexts based on the match, wherein the numerical values are assigned to the characteristics of the elements of the second search contexts and the characteristics elements of the first search contexts, and wherein the first computer ranks a first list of search results based on the determinations: the first computing merging the second search contexts and the first search contexts if the second search contexts are related to the first search contexts; the first computer creating a second list of search results based on the merge; and the first computer transmitting the second list to the second computer. 4. The method of claim 1 , further comprising: the second computer displaying user interface elements that allows the user to search for the previous search results based on the first search contexts; the second computer transmitting the search of the first search contexts to the first computer; and the second computer displaying results of the search based on the first search contexts.
| 0.5 |
8,612,243 | 15 | 17 |
15. The non-transitory computer readable data storage medium article of manufacture of claim 13 , wherein the method further comprises: sending a message to a user based upon the first classification scheme of the interaction record.
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15. The non-transitory computer readable data storage medium article of manufacture of claim 13 , wherein the method further comprises: sending a message to a user based upon the first classification scheme of the interaction record. 17. The non-transitory computer readable data storage medium article of manufacture of claim 15 , wherein the method further comprises: providing an inventory of tag set definitions from which a user may choose to classify the interaction record.
| 0.5 |
9,858,349 | 1 | 10 |
1. A method comprising: analyzing contents of a document to identify a plurality of document elements that collectively constitute the contents of the document, and storing, for each of the identified document elements, a database entry having a unique respective document-element identifier; creating a plurality of anchors dispersed throughout the document by storing, for each of a plurality of anchor locations, a respective database entry comprising a unique anchor identifier; storing a document view that represents the document as an ordered list of the document-element identifiers of the identified document elements, and listing at least some of the anchor identifiers in the document view interspersed with or nested within the document-element identifiers; and in response to selection of a portion of the document, generating a referencing address uniquely identifying the selected portion, the referencing address comprising one or more anchor identifiers of one or more respective anchors associated with the selected portion.
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1. A method comprising: analyzing contents of a document to identify a plurality of document elements that collectively constitute the contents of the document, and storing, for each of the identified document elements, a database entry having a unique respective document-element identifier; creating a plurality of anchors dispersed throughout the document by storing, for each of a plurality of anchor locations, a respective database entry comprising a unique anchor identifier; storing a document view that represents the document as an ordered list of the document-element identifiers of the identified document elements, and listing at least some of the anchor identifiers in the document view interspersed with or nested within the document-element identifiers; and in response to selection of a portion of the document, generating a referencing address uniquely identifying the selected portion, the referencing address comprising one or more anchor identifiers of one or more respective anchors associated with the selected portion. 10. The method of claim 1 , further comprising receiving an annotation pertaining to the selected portion, and storing the referencing address of the selected portion and a unique identifier of the annotation in a reference index.
| 0.587814 |
8,776,015 | 5 | 6 |
5. The method according to claim 4 , further comprising: at least one of exporting or importing the created construct among selected client computers; and sharing the created construct by users of the selected computers.
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5. The method according to claim 4 , further comprising: at least one of exporting or importing the created construct among selected client computers; and sharing the created construct by users of the selected computers. 6. The method according to claim 5 , further comprising: automatically updating design tools of the selected client computers with the created construct.
| 0.5 |
9,946,772 | 2 | 3 |
2. The method of claim 1 , wherein the text query comprises one or more characters inputted by the first user at the client system into a query field, and wherein the one or more structured queries are sent for display to the first user as the user inputs each of the one or more characters at the client system.
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2. The method of claim 1 , wherein the text query comprises one or more characters inputted by the first user at the client system into a query field, and wherein the one or more structured queries are sent for display to the first user as the user inputs each of the one or more characters at the client system. 3. The method of claim 2 , further comprising: receiving, from the client system, an additional character of the text query inputted by the first user; and sending, to the client system responsive to receiving the additional character of the text query, one or more additional structured queries for display, each additional structured query being based on the additional character of the text query.
| 0.5 |
8,458,065 | 30 | 31 |
30. A method of processing an indexed financial database, said method comprising: causing at least one memory device to store a user preference including at least one of a past decision about a financial object and a preferred feature of a financial object; causing at least one processor to determine a processing algorithm based on at least one of the user preference and a user input; causing the at least one processor to apply the processing algorithm to a feature contained in the indexed financial database to result in a processed feature, the indexed financial database having been created by searching for each of a plurality of potential features in each a plurality of data sets, and for each feature found in each data set, said found feature having been stored in said indexed financial database in association with said data set to be usable as a query to search for said data set in said indexed financial database; causing at least one display device to display the processed feature to a user; enabling the user to provide feedback, via at least one input device, about the processed feature; causing the at least one memory device to store the user provided feedback; causing the at least one processor to modify the processing algorithm based on the user provided feedback; and causing the at least one processor to apply the modified processing algorithm to the feature contained in the indexed financial database.
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30. A method of processing an indexed financial database, said method comprising: causing at least one memory device to store a user preference including at least one of a past decision about a financial object and a preferred feature of a financial object; causing at least one processor to determine a processing algorithm based on at least one of the user preference and a user input; causing the at least one processor to apply the processing algorithm to a feature contained in the indexed financial database to result in a processed feature, the indexed financial database having been created by searching for each of a plurality of potential features in each a plurality of data sets, and for each feature found in each data set, said found feature having been stored in said indexed financial database in association with said data set to be usable as a query to search for said data set in said indexed financial database; causing at least one display device to display the processed feature to a user; enabling the user to provide feedback, via at least one input device, about the processed feature; causing the at least one memory device to store the user provided feedback; causing the at least one processor to modify the processing algorithm based on the user provided feedback; and causing the at least one processor to apply the modified processing algorithm to the feature contained in the indexed financial database. 31. The method of claim 30 , wherein the processing algorithm is at least one selected from the group consisting of: a noise removal algorithm, a customized trend removal algorithm, a customized signal filter, and a customized modeling algorithm.
| 0.780749 |
10,102,847 | 1 | 5 |
1. A method comprising: receiving, by a computer-based speech recognition system that is communicatively coupled to a communication network, a speech input including one or more words or phrases, the computer-based speech recognition system comprising at least one processor and at least one memory device, wherein the speech input is from a call to a call center via the communication network; determining, by the computer-based speech recognition system, to provide the speech input to a human; receiving a response from the human that identifies a first task for the speech input, the first task including a first transcription of the speech input; performing the first task that is identified by the human for the speech input; processing the speech input to identify a second task for the speech input, the processing using a set of internal representations of the computer-based speech recognition system, the set of internal representations comprising one or more machine-readable parameters for recognizing speech in a speech utterance, the second task including a second transcription of the speech input; comparing the first transcription of the speech input included in the first task identified by the human with the second transcription of the speech input included in the second task identified by the computer-based recognition system to determine one or more differences between the first transcription and the second transcription; modifying the set of internal representations of the computer-based speech recognition system based at least in part on the one or more differences between the first transcription and the second transcription to create a modified set of internal representations, wherein the modifying includes adjusting at least a portion of the set of internal representations; checking the performance of the modified set of internal representations to prevent the modification from degrading the set internal representations, wherein the checking comprises determining that a performance difference between the set of internal representations before and after modification is within a margin of error; receiving, by the computer-based speech recognition system, another input; and processing, by the at least one processor and based at least in part on the modified set of internal representations, the other input to identify a third task for the other input.
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1. A method comprising: receiving, by a computer-based speech recognition system that is communicatively coupled to a communication network, a speech input including one or more words or phrases, the computer-based speech recognition system comprising at least one processor and at least one memory device, wherein the speech input is from a call to a call center via the communication network; determining, by the computer-based speech recognition system, to provide the speech input to a human; receiving a response from the human that identifies a first task for the speech input, the first task including a first transcription of the speech input; performing the first task that is identified by the human for the speech input; processing the speech input to identify a second task for the speech input, the processing using a set of internal representations of the computer-based speech recognition system, the set of internal representations comprising one or more machine-readable parameters for recognizing speech in a speech utterance, the second task including a second transcription of the speech input; comparing the first transcription of the speech input included in the first task identified by the human with the second transcription of the speech input included in the second task identified by the computer-based recognition system to determine one or more differences between the first transcription and the second transcription; modifying the set of internal representations of the computer-based speech recognition system based at least in part on the one or more differences between the first transcription and the second transcription to create a modified set of internal representations, wherein the modifying includes adjusting at least a portion of the set of internal representations; checking the performance of the modified set of internal representations to prevent the modification from degrading the set internal representations, wherein the checking comprises determining that a performance difference between the set of internal representations before and after modification is within a margin of error; receiving, by the computer-based speech recognition system, another input; and processing, by the at least one processor and based at least in part on the modified set of internal representations, the other input to identify a third task for the other input. 5. The method of claim 1 , further comprising: receiving, by the computer-based speech recognition system, another speech input; and processing, by the at least one processor and based at least partly on the modified set of internal representations, the other speech input to identify a particular transcription for the other speech input.
| 0.57197 |
7,721,205 | 1 | 3 |
1. A computer-readable storage medium having computer executable instructions executing on a processor for embedding a graphical object generated according to functionality of a first application in a document of a second application, the computer executable instructions comprising: storing the graphic object generated according to the functionality of the first application, wherein semantic data of the graphic object is stored separately from presentation data of the graphic object in a composite object server, wherein the semantic data identifies a hierarchical relationship of shapes in the graphic object, wherein the presentation data indicates a layout and style of the shapes of the graphic object; embedding the graphic object, via an anchor, in the document of the second application, wherein the embedded graphic object is rendered in the document of the second application by: identifying the anchor within the document of the second application, accessing the composite object server according to the anchor within the second application to obtain the stored presentation data and the stored semantic data of the graphic object, and combining the presentation data and the semantic data to generate a rendered view of the graphic object within the document of the second application, wherein the rendered view is editable according to the functionality of the first application without an executing instance of the first application.
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1. A computer-readable storage medium having computer executable instructions executing on a processor for embedding a graphical object generated according to functionality of a first application in a document of a second application, the computer executable instructions comprising: storing the graphic object generated according to the functionality of the first application, wherein semantic data of the graphic object is stored separately from presentation data of the graphic object in a composite object server, wherein the semantic data identifies a hierarchical relationship of shapes in the graphic object, wherein the presentation data indicates a layout and style of the shapes of the graphic object; embedding the graphic object, via an anchor, in the document of the second application, wherein the embedded graphic object is rendered in the document of the second application by: identifying the anchor within the document of the second application, accessing the composite object server according to the anchor within the second application to obtain the stored presentation data and the stored semantic data of the graphic object, and combining the presentation data and the semantic data to generate a rendered view of the graphic object within the document of the second application, wherein the rendered view is editable according to the functionality of the first application without an executing instance of the first application. 3. The computer readable storage medium of claim 1 , wherein the embedded graphic object is rendered in the document of the second application by generating a view interface, wherein the view interface combines the semantic data and the presentation data.
| 0.5 |
7,505,968 | 1 | 5 |
1. A method of evaluating a particular document relating to property, the method comprising: from a set of pre-selected documents, selecting the particular document, wherein each pre-selected document has associated therewith one or more search linkages that identify how the pre-selected document was selected, using user-supplied inputs, from a larger set of documents relating to property and wherein the set of pre-selected documents also have associated therewith one or more organizational linkages, each of which organizational linkages identifies a relationship between at least two pre-selected documents; using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document, wherein using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons; further comprising using the one or more organizational linkages to determine the relevance factor associated with the particular document, wherein using the one or more organizational linkages to determine the relevance factor associated with the particular document comprises adjusting a baseline relevance factor if a record date of the particular document predates a specific good stop associated with the document; and displaying to a user information relating to the document, wherein the information includes the relevance factor.
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1. A method of evaluating a particular document relating to property, the method comprising: from a set of pre-selected documents, selecting the particular document, wherein each pre-selected document has associated therewith one or more search linkages that identify how the pre-selected document was selected, using user-supplied inputs, from a larger set of documents relating to property and wherein the set of pre-selected documents also have associated therewith one or more organizational linkages, each of which organizational linkages identifies a relationship between at least two pre-selected documents; using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document, wherein using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons; further comprising using the one or more organizational linkages to determine the relevance factor associated with the particular document, wherein using the one or more organizational linkages to determine the relevance factor associated with the particular document comprises adjusting a baseline relevance factor if a record date of the particular document predates a specific good stop associated with the document; and displaying to a user information relating to the document, wherein the information includes the relevance factor. 5. The method of claim 1 , wherein determining a baseline relevance factor comprises assigning a relevance factor of 84.
| 0.78022 |
9,529,937 | 1 | 2 |
1. A method to extract data in a data store comprising: performing, by a computer system programmed with code stored in a memory and executing by a processor of the computer system that transforms the computer system into a machine: receiving a first query specifying one or more resource description framework (RDF) triples to be identified in a data store, where the first query is either schema-less or reflects a second storage schema; extracting data, represented by one or more tokens in the first query and included within context-specific grammar events represented by the one or more tokens, from the context-specific grammar events to generate a second query that specifies one or more RDF triples to be identified in the data store responsive to the first query and that reflects the first storage schema, wherein the events represent any of a declaration and a constraint specified in the first query; where the second query comprises: a single SQL SELECT statement with a WHERE clause containing three or more logical conditions limiting triples to be considered for retrieval from the RDF triples data store, where each logical condition specifies one or more RDF triples according to a Boolean condition; and applying the single SQL SELECT statement second query to the data store for identification of the one or more specified RDF triples responsive to the first query.
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1. A method to extract data in a data store comprising: performing, by a computer system programmed with code stored in a memory and executing by a processor of the computer system that transforms the computer system into a machine: receiving a first query specifying one or more resource description framework (RDF) triples to be identified in a data store, where the first query is either schema-less or reflects a second storage schema; extracting data, represented by one or more tokens in the first query and included within context-specific grammar events represented by the one or more tokens, from the context-specific grammar events to generate a second query that specifies one or more RDF triples to be identified in the data store responsive to the first query and that reflects the first storage schema, wherein the events represent any of a declaration and a constraint specified in the first query; where the second query comprises: a single SQL SELECT statement with a WHERE clause containing three or more logical conditions limiting triples to be considered for retrieval from the RDF triples data store, where each logical condition specifies one or more RDF triples according to a Boolean condition; and applying the single SQL SELECT statement second query to the data store for identification of the one or more specified RDF triples responsive to the first query. 2. The method of claim 1 , wherein the RDF triples store uses a hashed with origin schema.
| 0.961506 |
8,855,430 | 19 | 24 |
19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, for each image in a set of images, a corresponding set of labels, each label being determined to be indicative of subject matter of the image; for each label, determining one or more confidence values, each confidence value being a measure of confidence that the label accurately describes the subject matter of a threshold number of respective images to which it corresponds; identifying labels for which each of the one or more confidence values meets a respective confidence threshold as high confidence labels; for each image in the set of images, identifying the labels in its corresponding set of labels that are high confidence labels; and identifying images having a corresponding set of labels that include at least a respective threshold number of high confidence labels as high confidence images.
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19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving, for each image in a set of images, a corresponding set of labels, each label being determined to be indicative of subject matter of the image; for each label, determining one or more confidence values, each confidence value being a measure of confidence that the label accurately describes the subject matter of a threshold number of respective images to which it corresponds; identifying labels for which each of the one or more confidence values meets a respective confidence threshold as high confidence labels; for each image in the set of images, identifying the labels in its corresponding set of labels that are high confidence labels; and identifying images having a corresponding set of labels that include at least a respective threshold number of high confidence labels as high confidence images. 24. The non-transitory computer storage medium of claim 19 , wherein: determining one or more confidence values comprises determining, for the label, a number of images in the set of images that each include the label in its corresponding set of labels; and identifying labels for which each of the one or more confidence values meets a respective confidence threshold as high confidence labels comprises identifying labels for which the number of images in the set images meets a second frequency threshold.
| 0.774021 |
9,374,569 | 6 | 7 |
6. The non-transitory storage medium of claim 1 , wherein a first subset of said comprehensive dataset of media entities is linked to said first level submenu, and a second subset of said comprehensive dataset of media entities is linked to a second level submenu, wherein said method of enhanced search and retrieval of one or more relevant media entities from said comprehensive dataset of media entities stored on said non-transitory storage medium further comprises: processing, by said selection means, a third input comprising a selection of said first level submenu; and displaying said first subset of said comprehensive dataset of media entities linked to said first level submenu in response to said selection of said first level submenu, wherein said keywords interactive entity is also displayed on the same screen along with said first level submenu and said second level submenu.
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6. The non-transitory storage medium of claim 1 , wherein a first subset of said comprehensive dataset of media entities is linked to said first level submenu, and a second subset of said comprehensive dataset of media entities is linked to a second level submenu, wherein said method of enhanced search and retrieval of one or more relevant media entities from said comprehensive dataset of media entities stored on said non-transitory storage medium further comprises: processing, by said selection means, a third input comprising a selection of said first level submenu; and displaying said first subset of said comprehensive dataset of media entities linked to said first level submenu in response to said selection of said first level submenu, wherein said keywords interactive entity is also displayed on the same screen along with said first level submenu and said second level submenu. 7. The non-transitory storage medium of claim 6 , wherein said method of enhanced search and retrieval of one or more relevant media entities from said comprehensive dataset of media entities stored on said non-transitory storage medium further comprises: processing a selection of a media entity from said first subset and said second subset; and playing said media entity.
| 0.5 |
9,251,225 | 29 | 30 |
29. A computing system including: one or more data storage systems; an input device or port receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and at least one processor configured to process the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged.
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29. A computing system including: one or more data storage systems; an input device or port receiving mapping information that specifies one or more attributes of one or more destination entities in terms of one or more attributes of one or more source entities, at least some of the one or more source entities corresponding to respective sets of records in the one or more data storage systems; and at least one processor configured to process the mapping information to generate a procedural specification for computing values corresponding to at least some of the one or more attributes of one or more destination entities, the processing including generating a plurality of collections of nodes, each collection including a first node representing a first relational expression associated with an attribute specified by the mapping information, and at least some collections forming a directed acyclic graph that includes links to one or more other nodes representing respective relational expressions associated with at least one attribute of at least one source entity referenced by a relational expression of a node in the directed acyclic graph, and merging at least two of the collections with each other to form a third collection based on comparing relational expressions of nodes being merged. 30. The computing system of claim 29 , wherein the mapping information includes a first mapping rule that defines a value of an attribute of a destination entity in terms of a value of an attribute of a first source entity and a value of an attribute of a second source entity.
| 0.65201 |
9,652,547 | 1 | 6 |
1. A method of suggestion query completions before a user completes a query request, the method comprising: receiving, at a search engine system, a network request from a client device; ascertaining a general location and a specific location of the client device, the specific location being a more specific indication of the location of the client device than the general location; determining that the network request contains a query stem and not a completed query request; obtaining general queries containing the query stem; obtaining local queries containing the query stem and corresponding to the specific location; in response to determining that the network request contains the query stem, selecting, with one or more processors of the search engine system, suggested queries by performing steps comprising: selecting some of the suggested queries from among the general queries based on popularity of the general queries in an area corresponding to the general location, selecting some of the suggested queries from among the local queries based on popularity of the specific queries in an area corresponding to the specific location, and selecting one of the suggested queries from among the local queries in response to determining that the local query is a refinement of one of the general queries; and sending the suggested queries to the client device before the client device receives an input from the user submitting the completed query request.
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1. A method of suggestion query completions before a user completes a query request, the method comprising: receiving, at a search engine system, a network request from a client device; ascertaining a general location and a specific location of the client device, the specific location being a more specific indication of the location of the client device than the general location; determining that the network request contains a query stem and not a completed query request; obtaining general queries containing the query stem; obtaining local queries containing the query stem and corresponding to the specific location; in response to determining that the network request contains the query stem, selecting, with one or more processors of the search engine system, suggested queries by performing steps comprising: selecting some of the suggested queries from among the general queries based on popularity of the general queries in an area corresponding to the general location, selecting some of the suggested queries from among the local queries based on popularity of the specific queries in an area corresponding to the specific location, and selecting one of the suggested queries from among the local queries in response to determining that the local query is a refinement of one of the general queries; and sending the suggested queries to the client device before the client device receives an input from the user submitting the completed query request. 6. The method of claim 1 , comprising: ranking at least some of the local queries based on relative locations between the specific location and locations where the local queries were previously submitted; and selecting some of the suggested queries from among the local queries based on the ranking.
| 0.614691 |
6,116,907 | 16 | 17 |
16. The system of claim 15 wherein said image article signals cause said display means to display multiple forms of a selected article.
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16. The system of claim 15 wherein said image article signals cause said display means to display multiple forms of a selected article. 17. The system of claim 16 wherein said image article signals cause said display means to display a human shape and indica for selection of a form of a selected article of a desired sign and means to identify and select the form of the selected article.
| 0.5 |
8,881,015 | 11 | 12 |
11. A multifunction peripheral (MFP) system comprising: a document device for capturing electronic versions of a document; a document storage, coupled to the document device, configured to store electronic versions of the document; a user interface module, coupled to the document storage, configured to select a document selected from previously stored document; a job management module, coupled to the document storage, configured to: determine whether to capture the document or to transmit the document selected from previously stored documents, determine an availability of meeting information, workflow information, or a combination thereof for providing a list of participants associated with the meeting information, the workflow information, or a combination thereof, and an e-mail handling module, coupled to the job management module, configured to automatically transmit the document based on the availability for distributing the document to a workspace associated with an event, a task, or a combination thereof and an e-mail including an approver from an approver line of the task as a recipient, the document delivered to the participants for approving the document.
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11. A multifunction peripheral (MFP) system comprising: a document device for capturing electronic versions of a document; a document storage, coupled to the document device, configured to store electronic versions of the document; a user interface module, coupled to the document storage, configured to select a document selected from previously stored document; a job management module, coupled to the document storage, configured to: determine whether to capture the document or to transmit the document selected from previously stored documents, determine an availability of meeting information, workflow information, or a combination thereof for providing a list of participants associated with the meeting information, the workflow information, or a combination thereof, and an e-mail handling module, coupled to the job management module, configured to automatically transmit the document based on the availability for distributing the document to a workspace associated with an event, a task, or a combination thereof and an e-mail including an approver from an approver line of the task as a recipient, the document delivered to the participants for approving the document. 12. The system of claim 11 , further comprising: a calendar access module, coupled to the job management module, configured to receive the meeting information with the participants who have been invited to a meeting; and wherein: the e-mail handling module is configured to deliver the electronic version of the document to all of the participants invited to the meeting.
| 0.501344 |
9,628,827 | 15 | 16 |
15. An encoder for encoding a video into a data stream, comprising: an entropy encoder configured to encode syntax elements related to the video into the data stream based on one or more of a plurality of contexts used in binary entropy encoding, wherein the entropy encoder is configured to initialize each of the plurality of contexts based on, for each context, a slope value and an offset value, wherein the slope value and the offset value are determined based on first and second four-bit parts of an 8-bit initialization value associated with the context.
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15. An encoder for encoding a video into a data stream, comprising: an entropy encoder configured to encode syntax elements related to the video into the data stream based on one or more of a plurality of contexts used in binary entropy encoding, wherein the entropy encoder is configured to initialize each of the plurality of contexts based on, for each context, a slope value and an offset value, wherein the slope value and the offset value are determined based on first and second four-bit parts of an 8-bit initialization value associated with the context. 16. The encoder according to claim 15 , further comprising a symbolizer configured to binarize the syntax elements to obtain binarizations of the syntax elements, wherein the entropy encoder is configured to encode the binarizations based on the binary entropy decoding.
| 0.787402 |
6,064,961 | 9 | 13 |
9. The method of claim 1, wherein said initial text and said further text are contextual phrases including a target word and words immediately preceding and following said target word.
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9. The method of claim 1, wherein said initial text and said further text are contextual phrases including a target word and words immediately preceding and following said target word. 13. The method of claim 9, further comprising the step of displaying said target word in a box.
| 0.780093 |
8,145,655 | 1 | 4 |
1. A method, comprising: translating source code including at least one query statement written in a database query language into executable object code in a computer readable storage medium; generating a statement descriptor data structure in the object code including statement descriptor information for the translated at least one query statement including information on the at least one query statement as presented in the source code; executing the object code to cause execution of the at least one query statement; accessin˜the statement descriptor information in the statement descriptor data structure in the object code for the at least one executed query statement; and processing the accessed statement descriptor information to output information on the at least one query statement included in the statement descriptor information.
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1. A method, comprising: translating source code including at least one query statement written in a database query language into executable object code in a computer readable storage medium; generating a statement descriptor data structure in the object code including statement descriptor information for the translated at least one query statement including information on the at least one query statement as presented in the source code; executing the object code to cause execution of the at least one query statement; accessin˜the statement descriptor information in the statement descriptor data structure in the object code for the at least one executed query statement; and processing the accessed statement descriptor information to output information on the at least one query statement included in the statement descriptor information. 4. The method of claim 1 , further comprising: modifying the at least one query statement in the source code to produce at least one modified query statement; including the at least one modified query statement in the statement descriptor information; and translating the at least one modified query statement into the executable object code.
| 0.613122 |
9,262,384 | 1 | 30 |
1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values such that the one or more computer-readable semantic tags are each computer-readably associated with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; causing output of a report that is based on at least a portion of the at least one data structure, the report capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the report; and causing output of the computer-readable XML-compliant data document that is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input.
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1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values such that the one or more computer-readable semantic tags are each computer-readably associated with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; causing output of a report that is based on at least a portion of the at least one data structure, the report capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the report; and causing output of the computer-readable XML-compliant data document that is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. 30. The apparatus of claim 1 , wherein the system is configured such that multiple hierarchical relationships between two line items are searchable.
| 0.980824 |
9,984,152 | 15 | 16 |
15. A non-transitory computer readable medium that stores a set of instructions that are executable by at least one processor to cause the at least one processor to perform a method for providing a proactive validation of a transformation script, the method comprising: associating the transformation script with ontology parameters, wherein the ontology parameters include parameters that assign an entity as being an object or a property of an object; initiating a debugging operation of the transformation script having at least one condition, wherein the transformation script uses a builder that defines a definition of the entity as the entity being an object or a property of an object; importing, from a data source, at least one data item for transformation; determining, as part of the debugging operation, whether the at least one condition that uses the at least one data item is valid if the assignment of the entity associated with the transformation script is consistent with the definition of the entity, the determination whether the at least one condition that uses the at least one data item is valid being based on the ontology parameters; and providing an indication of a result associated with the determination, wherein the result is at least one of an expressed result or an implicit result.
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15. A non-transitory computer readable medium that stores a set of instructions that are executable by at least one processor to cause the at least one processor to perform a method for providing a proactive validation of a transformation script, the method comprising: associating the transformation script with ontology parameters, wherein the ontology parameters include parameters that assign an entity as being an object or a property of an object; initiating a debugging operation of the transformation script having at least one condition, wherein the transformation script uses a builder that defines a definition of the entity as the entity being an object or a property of an object; importing, from a data source, at least one data item for transformation; determining, as part of the debugging operation, whether the at least one condition that uses the at least one data item is valid if the assignment of the entity associated with the transformation script is consistent with the definition of the entity, the determination whether the at least one condition that uses the at least one data item is valid being based on the ontology parameters; and providing an indication of a result associated with the determination, wherein the result is at least one of an expressed result or an implicit result. 16. The non-transitory computer readable medium of claim 15 , wherein the data source includes unstructured data or the data source includes structured data.
| 0.644796 |
8,930,503 | 8 | 13 |
8. A system comprising: one or more data processing apparatus; and a data store storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: identifying a user device, including determining a device identifier corresponding to the user device; accessing, for the device identifier, visitation data that includes one or more resource locators that each specify a resource that was previously provided to the user device corresponding to the device identifier; identifying, based on one of the resource locators included in the visitation data, a content feed including content items that are eligible to be provided to the user device in response to one or more resource locators in the visitation data matching one or more character strings specified by a publisher associated with the content feed; identifying, from the one or more character strings, a matching character string that matches a particular resource locator from the one or more resource locators included in the visitation data; selecting a content item from the content items that are eligible to be provided to the user device based on the match between the particular resource locator and the matching character string; and providing, to the user device, data that causes presentation of the selected content item.
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8. A system comprising: one or more data processing apparatus; and a data store storing instructions that, when executed by the one or more data processing apparatus, cause the one or more data processing apparatus to perform operations comprising: identifying a user device, including determining a device identifier corresponding to the user device; accessing, for the device identifier, visitation data that includes one or more resource locators that each specify a resource that was previously provided to the user device corresponding to the device identifier; identifying, based on one of the resource locators included in the visitation data, a content feed including content items that are eligible to be provided to the user device in response to one or more resource locators in the visitation data matching one or more character strings specified by a publisher associated with the content feed; identifying, from the one or more character strings, a matching character string that matches a particular resource locator from the one or more resource locators included in the visitation data; selecting a content item from the content items that are eligible to be provided to the user device based on the match between the particular resource locator and the matching character string; and providing, to the user device, data that causes presentation of the selected content item. 13. The system of claim 8 , wherein each of the one or more character strings is a regular expression that specifies a set of matching character strings, and wherein at least one of the regular expressions includes a keyword and a metacharacter.
| 0.88476 |
9,207,860 | 29 | 30 |
29. The electronic device of claim 16 , wherein the method further comprises presenting a lock function indicator on the display if at least one stored swipe gesture is detected.
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29. The electronic device of claim 16 , wherein the method further comprises presenting a lock function indicator on the display if at least one stored swipe gesture is detected. 30. The electronic device of claim 29 , further comprising activating a lock function upon receiving a touch input at the lock function indicator.
| 0.5 |
10,133,732 | 18 | 20 |
18. A hardware device comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the processor implements an automated method for generating an answer to an input question comprising a location specific (L) word or phrase using NLP, said method comprising: generating and maintaining, by a processor of a hardware device, an online L-word dictionary, wherein said generating and maintaining comprises: determining a relationship between a plurality of L-words and a plurality of corresponding values, wherein said plurality of corresponding values include a plurality of related lookup phrases and a plurality of concept terms; mapping said plurality of L-words to said plurality of corresponding values based on said determined relationship; and storing said mapped plurality of L-words to said plurality of corresponding values in said online L-word Dictionary comprised by a specialized remotely located database computer; retrieving, by said processor via circuitry of a mobile device of a user, location specific attributes associated with a current location of said mobile device and said user; retrieving, by said processor, location specific settings and location specific preferences associated with said user; receiving, by said processor, said input question, wherein said input question is entered by said user via a graphical user interface associated with said mobile device; executing, by said processor, an NLP analysis with respect to said input question to extract a required value phrase; generating, by said processor, at least one mathematical equation based on the extracted required value phrase, wherein said generating said at least one mathematical equation comprises: identifying said location specific word or phrase comprised by said received input question, wherein a value associated with said identified location specific word or phrase varies according to a particular geographical point, and wherein said identifying comprises communicating online with said specialized remotely located database computer to access said online L-word Dictionary; and resolving said identified location specific word or phrase comprised by said received input question, wherein said resolving comprises said communicating online with said specialized remotely located database computer to access said online L-Word Dictionary and recursively mapping a plurality of variables associated with said location specific word or phrase to at least one formula contained in said L-Word Dictionary; forming, by said processor, at least one interim question based on said extracted required value phrase; solving, by said processor executing specialized circuitry, said at least one formed mathematical equation and the at least one formed interim question, wherein said solving comprises prompting said user via said graphical user interface for a plurality of digital input to resolve an ambiguity associated with said at least one formed mathematical equation and said at least one formed interim question; determining, by said processor, said answer to said input question in natural language based on said solved at least one interim question or said solved at least one mathematical equation, wherein said determining said answer comprises said hardware device simultaneously interacting with a specialized on-line question-answer system to simultaneously search: an internet, a plurality of online data repositories, a plurality of online databases, and a plurality of online corpuses according to said value associated with said identified location specific word or phrase associated with said particular geographical point; and narrating, by said processor, said answer to said input question in natural language based on said solved at least one interim question or said solved at least one mathematical equation, wherein said narrated answer comprises an automated interactive response from said hardware device in real time.
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18. A hardware device comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the processor implements an automated method for generating an answer to an input question comprising a location specific (L) word or phrase using NLP, said method comprising: generating and maintaining, by a processor of a hardware device, an online L-word dictionary, wherein said generating and maintaining comprises: determining a relationship between a plurality of L-words and a plurality of corresponding values, wherein said plurality of corresponding values include a plurality of related lookup phrases and a plurality of concept terms; mapping said plurality of L-words to said plurality of corresponding values based on said determined relationship; and storing said mapped plurality of L-words to said plurality of corresponding values in said online L-word Dictionary comprised by a specialized remotely located database computer; retrieving, by said processor via circuitry of a mobile device of a user, location specific attributes associated with a current location of said mobile device and said user; retrieving, by said processor, location specific settings and location specific preferences associated with said user; receiving, by said processor, said input question, wherein said input question is entered by said user via a graphical user interface associated with said mobile device; executing, by said processor, an NLP analysis with respect to said input question to extract a required value phrase; generating, by said processor, at least one mathematical equation based on the extracted required value phrase, wherein said generating said at least one mathematical equation comprises: identifying said location specific word or phrase comprised by said received input question, wherein a value associated with said identified location specific word or phrase varies according to a particular geographical point, and wherein said identifying comprises communicating online with said specialized remotely located database computer to access said online L-word Dictionary; and resolving said identified location specific word or phrase comprised by said received input question, wherein said resolving comprises said communicating online with said specialized remotely located database computer to access said online L-Word Dictionary and recursively mapping a plurality of variables associated with said location specific word or phrase to at least one formula contained in said L-Word Dictionary; forming, by said processor, at least one interim question based on said extracted required value phrase; solving, by said processor executing specialized circuitry, said at least one formed mathematical equation and the at least one formed interim question, wherein said solving comprises prompting said user via said graphical user interface for a plurality of digital input to resolve an ambiguity associated with said at least one formed mathematical equation and said at least one formed interim question; determining, by said processor, said answer to said input question in natural language based on said solved at least one interim question or said solved at least one mathematical equation, wherein said determining said answer comprises said hardware device simultaneously interacting with a specialized on-line question-answer system to simultaneously search: an internet, a plurality of online data repositories, a plurality of online databases, and a plurality of online corpuses according to said value associated with said identified location specific word or phrase associated with said particular geographical point; and narrating, by said processor, said answer to said input question in natural language based on said solved at least one interim question or said solved at least one mathematical equation, wherein said narrated answer comprises an automated interactive response from said hardware device in real time. 20. The hardware device of claim 18 , wherein said retrieving said location specific attributes comprises: identifying an GPS coordinates of said mobile device; and determining said current location based on based on said GPS coordinates.
| 0.603333 |
4,724,285 | 4 | 38 |
4. The steno translator system of claim 1 or 2 or 3 wherein the processor means further comprises: an exception dictionary memory for storing a list of dictionary entries, each dictionary entry comprising a subsequence of at least one lexical stroke symbol and an associated language part defining a translation of the subsequence for each dictionary entry; and searching means for comparing selected subsequences of lexical stroke symbols from the stroke symbol means, according to a predefined searching methodology, first against dictionary entries to identify a match, said match defined as a subsequence translation, and if no match is located in the exception dictionary memory next applying individual lexical stroke symbols to the scan chart memory to define a stroke symbol translation.
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4. The steno translator system of claim 1 or 2 or 3 wherein the processor means further comprises: an exception dictionary memory for storing a list of dictionary entries, each dictionary entry comprising a subsequence of at least one lexical stroke symbol and an associated language part defining a translation of the subsequence for each dictionary entry; and searching means for comparing selected subsequences of lexical stroke symbols from the stroke symbol means, according to a predefined searching methodology, first against dictionary entries to identify a match, said match defined as a subsequence translation, and if no match is located in the exception dictionary memory next applying individual lexical stroke symbols to the scan chart memory to define a stroke symbol translation. 38. The steno translation system of claim 4 further comprising: means for defining each stroke symbol translation, derived from the scan chart memory as a suffix, prefix or word root by applying the predetermined identifier rule set to the lexical stroke symbol.
| 0.859893 |
9,703,769 | 1 | 4 |
1. A method comprising: inserting, via a discriminative classification approach, boundary tags into speech utterance text, the boundary tags identifying boundaries selected from a group comprising phrase boundaries, sentence boundaries, and paragraph boundaries, wherein the discriminative classification approach utilizes syntactic features before and after each word being tagged, to yield boundary marked speech utterance text and unedited text; identifying, via a processor, a coordinating conjunction within the unedited text based on a conjunction tag, wherein the conjunction tag comprises conjunction span information indicating how many words to the left of the conjunction tag a corresponding conjunction includes; and identifying clauses in the speech utterance text based on the boundary marked speech utterance text and the coordinating conjunction.
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1. A method comprising: inserting, via a discriminative classification approach, boundary tags into speech utterance text, the boundary tags identifying boundaries selected from a group comprising phrase boundaries, sentence boundaries, and paragraph boundaries, wherein the discriminative classification approach utilizes syntactic features before and after each word being tagged, to yield boundary marked speech utterance text and unedited text; identifying, via a processor, a coordinating conjunction within the unedited text based on a conjunction tag, wherein the conjunction tag comprises conjunction span information indicating how many words to the left of the conjunction tag a corresponding conjunction includes; and identifying clauses in the speech utterance text based on the boundary marked speech utterance text and the coordinating conjunction. 4. The method of claim 1 , wherein a different classifier performs each step of the method.
| 0.792237 |
7,493,499 | 20 | 21 |
20. The method of claim 17 wherein step (h) comprises generating a document identifier for each encrypted document from the encrypted document content and a text string embedded in the publishing tool code.
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20. The method of claim 17 wherein step (h) comprises generating a document identifier for each encrypted document from the encrypted document content and a text string embedded in the publishing tool code. 21. The method of claim 20 wherein the text string embedded in the viewer code is the same as the text string embedded in the publishing tool code.
| 0.5 |
7,590,530 | 13 | 16 |
13. The method of claim 1 , wherein the dynamic modification of the noise model, the noise component estimation, and the noisy speech enhancement are repeatedly performed.
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13. The method of claim 1 , wherein the dynamic modification of the noise model, the noise component estimation, and the noisy speech enhancement are repeatedly performed. 16. The speech enhancement system of claim 13 , wherein the signal processor is configured to modify the at least one shape and the gain of the noise model without confinement to a speech pause.
| 0.5 |
7,533,338 | 3 | 4 |
3. The method according to claim 1 , wherein the first analysis context object includes a member selected from the group of: a group node, a paragraph node, a line node, an ink word node, an electronic drawing node, an ink drawing node, a list node, a list item node, an electronic bullet node, an ink bullet node, an electronic text word node, an image node, a table node, a row node, and a cell node.
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3. The method according to claim 1 , wherein the first analysis context object includes a member selected from the group of: a group node, a paragraph node, a line node, an ink word node, an electronic drawing node, an ink drawing node, a list node, a list item node, an electronic bullet node, an ink bullet node, an electronic text word node, an image node, a table node, a row node, and a cell node. 4. The method according to claim 3 , wherein the second analysis context object is selected from the group of: an unclassified ink node, a group node, a paragraph node, a line node, an ink word node, an ink drawing node, a list node, a list item node, an ink bullet node, a table node, a row node, and a cell node.
| 0.5 |
8,577,668 | 5 | 6 |
5. A method comprising: sending, using one or more processors, a request to translate a source web document from a first language text to a second language text; receiving a translated web document for display containing a translation of the source web document into the second language text; displaying the translated web document; and in response to interacting with a portion of the translated web document, displaying the first language text that corresponds to a portion of the translated web document in a graphical element overlaying the translated web document.
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5. A method comprising: sending, using one or more processors, a request to translate a source web document from a first language text to a second language text; receiving a translated web document for display containing a translation of the source web document into the second language text; displaying the translated web document; and in response to interacting with a portion of the translated web document, displaying the first language text that corresponds to a portion of the translated web document in a graphical element overlaying the translated web document. 6. The method of claim 5 , further comprising: displaying the first language text after a predetermined period of time has elapsed after the user points to the portion of the translated document; removing the display of the first language text after a second predetermined period of time has elapsed after a user ceases to point to the portion of the translated document; and canceling the removal of the display of the first language text if the user again points to the portion of the translated document before the second predetermined period of time has elapsed.
| 0.5 |
9,792,373 | 16 | 18 |
16. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising: determining at least one topic for potential presentation to a user based on an interaction of a connection of the user on a social networking system; determining a degree of separation between the user and the connection within the social networking system; determining a value of affinity between the user and the connection; determining a weight reflecting a value of interest similarity between the user and the connection; calculating a term based on the degree of separation, the value of affinity, and the weight reflecting a value of interest similarity; and combining terms associated with the at least one topic to generate a composite score associated with the at least one topic to determine whether to present the at least one topic to the user.
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16. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising: determining at least one topic for potential presentation to a user based on an interaction of a connection of the user on a social networking system; determining a degree of separation between the user and the connection within the social networking system; determining a value of affinity between the user and the connection; determining a weight reflecting a value of interest similarity between the user and the connection; calculating a term based on the degree of separation, the value of affinity, and the weight reflecting a value of interest similarity; and combining terms associated with the at least one topic to generate a composite score associated with the at least one topic to determine whether to present the at least one topic to the user. 18. The non-transitory computer-readable storage medium of claim 16 , wherein the weight reflecting a value of interest similarity between the user and the connection is based on similarity of recently interacted topics and categories at different levels of granularity.
| 0.5 |
6,119,087 | 1 | 2 |
1. A system architecture for efficiently distributing voice call data over a telephone network using speech recognition, the system architecture comprising: a) a first circuit for receiving incoming voice call data from a call, wherein the first circuit recognizes a grammar-type of the call; b) a plurality of processing circuits configured to process the voice call data; c) a load balancing circuit coupled each of the first circuit and the plurality of processing circuits for distributing the voice call data to a preferred processor circuit within the plurality of processors, wherein the preferred processor circuit is selected by the load balance circuit using criteria comprising the assigned grammar type and known processor efficiencies for each processor circuit for processing previously received voice call data having a same grammar type as the call.
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1. A system architecture for efficiently distributing voice call data over a telephone network using speech recognition, the system architecture comprising: a) a first circuit for receiving incoming voice call data from a call, wherein the first circuit recognizes a grammar-type of the call; b) a plurality of processing circuits configured to process the voice call data; c) a load balancing circuit coupled each of the first circuit and the plurality of processing circuits for distributing the voice call data to a preferred processor circuit within the plurality of processors, wherein the preferred processor circuit is selected by the load balance circuit using criteria comprising the assigned grammar type and known processor efficiencies for each processor circuit for processing previously received voice call data having a same grammar type as the call. 2. The system architecture of claim 1, wherein the first circuit submits a processing request to the load balancing circuit when the call is received, the load balance circuit identifies the preferred processor to the first circuit and the first circuit transfers the voice call data to the preferred processor circuit for processing.
| 0.5 |
9,805,139 | 4 | 6 |
4. The method of claim 1 , wherein the a posteriori information is responsive to a metric that measures a relevance between each of the concepts in the concept graph and each concept in a selected subset of the concepts extracted from the document.
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4. The method of claim 1 , wherein the a posteriori information is responsive to a metric that measures a relevance between each of the concepts in the concept graph and each concept in a selected subset of the concepts extracted from the document. 6. The method of claim 4 , wherein the selected subset of the concepts extracted from the document varies based on the concept in the concept graph and includes a specified number of the concepts extracted from the document that are the most relevant to the concept in the concept graph based on the metric.
| 0.5 |
8,050,923 | 1 | 2 |
1. A system for analyzing voice-based communication sessions, comprising: a player configured to replay a recording of a communication session; an analysis engine coupled to the player, the analysis engine configured to process a stored communication session to generate a result responsive to an utterance-of-interest in the stored communication session, wherein the analysis engine uses a language model specific to a speaker when an identity of the speaker is known; a presentor coupled to the analysis engine and configured to present a representation of the result; and a storage device coupled to the analysis engine, the storage device configured to cache a representation of the result, wherein the representation of the result comprises an indication of a match of the utterance-of-interest in the stored communication session and an indication of a certainty that the match is an actual match of the utterance-of-interest.
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1. A system for analyzing voice-based communication sessions, comprising: a player configured to replay a recording of a communication session; an analysis engine coupled to the player, the analysis engine configured to process a stored communication session to generate a result responsive to an utterance-of-interest in the stored communication session, wherein the analysis engine uses a language model specific to a speaker when an identity of the speaker is known; a presentor coupled to the analysis engine and configured to present a representation of the result; and a storage device coupled to the analysis engine, the storage device configured to cache a representation of the result, wherein the representation of the result comprises an indication of a match of the utterance-of-interest in the stored communication session and an indication of a certainty that the match is an actual match of the utterance-of-interest. 2. The system of claim 1 , wherein the representation further comprises one of a text file, a database entry, and an alternative format.
| 0.628415 |
8,923,491 | 21 | 24 |
21. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a spoken communication from a first user, the spoken communication comprising an address; extracting, via a processor, the address automatically from the spoken communication, to yield an extracted address; displaying to a second user a selection of addresses, the selection of addresses comprising the extracted address and an alternate address for the first user, the alternate address being stored in a contacts list, the selection of addresses displayed in an order prioritizing a preferred address of the extracted address and the alternate address, where the preferred address is determined based on a user history of the first user by the computing device; and receiving from the second user a selection of a selected address from the selection of addresses to initiate communication with the first user.
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21. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a spoken communication from a first user, the spoken communication comprising an address; extracting, via a processor, the address automatically from the spoken communication, to yield an extracted address; displaying to a second user a selection of addresses, the selection of addresses comprising the extracted address and an alternate address for the first user, the alternate address being stored in a contacts list, the selection of addresses displayed in an order prioritizing a preferred address of the extracted address and the alternate address, where the preferred address is determined based on a user history of the first user by the computing device; and receiving from the second user a selection of a selected address from the selection of addresses to initiate communication with the first user. 24. The computer-readable storage device of claim 21 , wherein the address comprises one of a phone number, an email address, a website, an internet protocol address, a file transfer protocol server, an instant messaging address, global positioning system coordinates, and a physical address.
| 0.75626 |
8,001,232 | 1 | 7 |
1. A method for handling events in a distributed computing system including a plurality of devices connected by a network, said method comprising: obtaining, from a remote location, a markup language schema on a client platform, wherein said markup language schema defines a message interface of a remote service for a plurality of events generated by the remote service and indicates the plurality of events to be published by the remote service; obtaining an address for said remote service within the distributed computing system; automatically constructing, by computer-executable message endpoint construction code on the client platform, an event message endpoint on the client platform according to the markup language schema and the obtained address for the remote service, wherein said automatically constructing is performed within a runtime system of the client platform, and wherein the event message endpoint implements an API to send and receive event messages to and from the service; receiving, by the event message endpoint on the client platform in the distributed computing system, indications from one or more client processes registering interest in receiving one or more of the plurality of events generated by the remote service in the distributed computing system; the event message endpoint automatically subscribing to the one or more events with the remote service in response to said indications registering interest in the one or more events received from the one or more client processes such that the event message endpoint becomes subscribed to the one or more events; receiving, by the event message endpoint over a network, a message in a markup language sent to the client platform in the distributed computing system from the remote service in the distributed computing system, wherein the message is received at the event message endpoint from the remote service over the network in the distributed computing system, and wherein the message includes a markup language representation of one of the one or more events generated by the remote service to which the event message endpoint is subscribed; and sending, from the event message endpoint, the markup language representation of the event to at least one of the one or more client processes registered with the event message endpoint to receive the event, wherein said markup language representation is in a data representation format which is independent of said client platform.
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1. A method for handling events in a distributed computing system including a plurality of devices connected by a network, said method comprising: obtaining, from a remote location, a markup language schema on a client platform, wherein said markup language schema defines a message interface of a remote service for a plurality of events generated by the remote service and indicates the plurality of events to be published by the remote service; obtaining an address for said remote service within the distributed computing system; automatically constructing, by computer-executable message endpoint construction code on the client platform, an event message endpoint on the client platform according to the markup language schema and the obtained address for the remote service, wherein said automatically constructing is performed within a runtime system of the client platform, and wherein the event message endpoint implements an API to send and receive event messages to and from the service; receiving, by the event message endpoint on the client platform in the distributed computing system, indications from one or more client processes registering interest in receiving one or more of the plurality of events generated by the remote service in the distributed computing system; the event message endpoint automatically subscribing to the one or more events with the remote service in response to said indications registering interest in the one or more events received from the one or more client processes such that the event message endpoint becomes subscribed to the one or more events; receiving, by the event message endpoint over a network, a message in a markup language sent to the client platform in the distributed computing system from the remote service in the distributed computing system, wherein the message is received at the event message endpoint from the remote service over the network in the distributed computing system, and wherein the message includes a markup language representation of one of the one or more events generated by the remote service to which the event message endpoint is subscribed; and sending, from the event message endpoint, the markup language representation of the event to at least one of the one or more client processes registered with the event message endpoint to receive the event, wherein said markup language representation is in a data representation format which is independent of said client platform. 7. The method as recited in claim 1 , further comprising: at least one client process unregistering interest in a first event of the service with the event message endpoint; and the event message endpoint automatically unsubscribing to the first event with the service in response to said unregistering interest by the at least one client process; wherein the service is configured to not send messages including markup language representations of the first event to event message endpoints that are unsubscribed to the first event.
| 0.669975 |
7,774,202 | 12 | 19 |
12. A method to provide speech-activated control of aerial vehicle components, the method comprising the steps of: (a) sampling a speech signal representing speech to define sampled data; (b) performing an integrity check on the sampled data to identify when the speech is below a preselected standard; (c) aligning the sampled data in an observation window to enhance analysis of the speech; (d) performing noise reduction processing to remove noise from within and around speech formants, to include: estimating noise power for each separate set of a plurality of bins having a same frequency range across a plurality of time slices of the sampled data to thereby provide a plurality of frequency range-specific noise power estimates, equalizing energy values of each set of bins having a same frequency range across the plurality of time slices responsive to the respective frequency range-specific noise power estimate, and thresholding each equalized bin by a parameterized threshold value to remove noise from within and around speech formants of the sampled data; (e) developing a set of feature vectors representing energy of a frequency content of the sampled data to thereby determine a unique pattern; and (f) applying a speech recognition engine to the set of feature vectors to perform one of the following functions: forming at least one speech recognition model associated with the speech signal, and matching the speech signal to the at least one speech recognition model.
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12. A method to provide speech-activated control of aerial vehicle components, the method comprising the steps of: (a) sampling a speech signal representing speech to define sampled data; (b) performing an integrity check on the sampled data to identify when the speech is below a preselected standard; (c) aligning the sampled data in an observation window to enhance analysis of the speech; (d) performing noise reduction processing to remove noise from within and around speech formants, to include: estimating noise power for each separate set of a plurality of bins having a same frequency range across a plurality of time slices of the sampled data to thereby provide a plurality of frequency range-specific noise power estimates, equalizing energy values of each set of bins having a same frequency range across the plurality of time slices responsive to the respective frequency range-specific noise power estimate, and thresholding each equalized bin by a parameterized threshold value to remove noise from within and around speech formants of the sampled data; (e) developing a set of feature vectors representing energy of a frequency content of the sampled data to thereby determine a unique pattern; and (f) applying a speech recognition engine to the set of feature vectors to perform one of the following functions: forming at least one speech recognition model associated with the speech signal, and matching the speech signal to the at least one speech recognition model. 19. The method as defined in claim 12 , wherein the step of developing a set of feature vectors representing energy of a frequency content of the sampled data includes the operations of: transforming a spectrum comprising normalized post-noise-reduction speech data using Mel frequency bands to form a plurality of Mel coefficients; applying a Fourier transform to the Mel coefficients to form a Mel Spaced Cepstrum; and determining first and second derivatives of the Mel Spaced Cepstrum.
| 0.710651 |
7,747,552 | 15 | 22 |
15. The method of claim 7 further comprising: establishing one or more intermediate nodes; and where coupling the root nodes to the leaf nodes to enable the Bayesian network to predict sand-grain composition and texture comprises: coupling at least some of the one or more root nodes to at least some of the one or more leaf nodes through the one or more intermediate nodes.
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15. The method of claim 7 further comprising: establishing one or more intermediate nodes; and where coupling the root nodes to the leaf nodes to enable the Bayesian network to predict sand-grain composition and texture comprises: coupling at least some of the one or more root nodes to at least some of the one or more leaf nodes through the one or more intermediate nodes. 22. The method of claim 15 where each leaf node has a predefined number of inputs and where creating the probability table for each leaf node comprises: creating a probability table having the respective predefined number of input dimensions.
| 0.789565 |
5,434,777 | 20 | 22 |
20. A method as recited in claim 17 further comprising the steps of: examining a different substring including at least one different word object when said mapping routine does not map said substring; and mapping said different substring into a database using said mapping routine, wherein said steps of examining a different substring and mapping said different substring are accomplished before said step of decreasing said number of words in said substring.
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20. A method as recited in claim 17 further comprising the steps of: examining a different substring including at least one different word object when said mapping routine does not map said substring; and mapping said different substring into a database using said mapping routine, wherein said steps of examining a different substring and mapping said different substring are accomplished before said step of decreasing said number of words in said substring. 22. A method as recited in claim 20 wherein said mapping routine is a dynamic mapping routine.
| 0.696774 |
7,734,459 | 4 | 5 |
4. The computer-implemented method of claim 1 wherein associating includes forming tentative correspondences between nodes wherein one of the nodes comprises more lexical elements than the other node.
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4. The computer-implemented method of claim 1 wherein associating includes forming tentative correspondences between nodes wherein one of the nodes comprises more lexical elements than the other node. 5. The computer-implemented method of claim 4 wherein said one of the nodes is a single word in one of the languages and said other node comprises at least two words in the other language.
| 0.5 |
7,605,938 | 13 | 16 |
13. A device for printing data, the device comprising: a storage module that stores a file to be printed; a control module that generates a first mark-up document that describes the stored file, the first mark-up document comprising text data and link data that indicates a location at which the file is stored in a storage unit, and a second mark-up document that describes the file, the second mark-up document comprising identification information that identifies the file at the location indicated by the link data, and that generates a document to be transmitted to a printing device using the first mark-up document and the second mark-up document; and an external-device interface module that transmits the generated document to the printing device, wherein the printing device analyzes the document to obtain the link data and the identification information, transmits a request for the file to the device for printing data based on the extracted link data and identification information, receives the file from the device for printing data that is extracted from the storage module based on the extracted link data and identification information, and outputs the file.
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13. A device for printing data, the device comprising: a storage module that stores a file to be printed; a control module that generates a first mark-up document that describes the stored file, the first mark-up document comprising text data and link data that indicates a location at which the file is stored in a storage unit, and a second mark-up document that describes the file, the second mark-up document comprising identification information that identifies the file at the location indicated by the link data, and that generates a document to be transmitted to a printing device using the first mark-up document and the second mark-up document; and an external-device interface module that transmits the generated document to the printing device, wherein the printing device analyzes the document to obtain the link data and the identification information, transmits a request for the file to the device for printing data based on the extracted link data and identification information, receives the file from the device for printing data that is extracted from the storage module based on the extracted link data and identification information, and outputs the file. 16. The device according to claim 13 , wherein the first mark-up document is an extensible Hyper Text Markup Language (XHTML) document.
| 0.639037 |
9,798,803 | 1 | 2 |
1. A security system for an area under surveillance comprising: a first memory including ontology data stored thereon, the ontology data defining interrelationships between a scanner associated with access to a room of an area under surveillance, a camera with a field of view at least partially overlapping a footprint of the room, an identifier configured to be scanned by the scanner and associated with a person, and a security policy including one or more predefined conditions, which when satisfied, indicate when a security threat exists, wherein the security policy includes a response an operator is to perform if the conditions are satisfied; a relational database including temporal data and spatial data stored thereon, the temporal data including time series entries corresponding to scan logs of the scanner including a scan read that indicates a time at which the identifier was scanned, the scanner that scanned the identifier, and whether the person was allowed or denied access based on the scan read, and the spatial data including a location of the camera, a coverage area of the camera, one or more locations of one or more doors to the room, a location of an asset in the room, and a location of the scanner; a query module, executable by a processor configured to receive a query and search the ontology data, the temporal data, and the spatial data in response to receiving the query, wherein the query module is configured to run periodic pre-programmed queries to the first memory and the relational database to determine if the security policy has been violated, and wherein the security policy includes an asset-missing security response configured to automatically send a series of queries to the query module, the series of queries configured to search the ontology data, the spatial data, and the temporal data to: determine, using the spatial data, the room where an asset that went missing is supposed to be; determine, using the spatial data, one or more scanners associated with the room; identify, using the temporal data, one or more identifiers in a list of identifiers that were scanned by the one or more scanners in a specified time window; identify, using the temporal data, one or more other scanners that have scanned the one or more identifiers in another list of identifiers in another specified time window: calculate the predicted future path of one or more persons associated with the one or more identifiers based on the identified one or more scanners and one or more other scanners; and identify one or more cameras with a field of view that intersects the predicted future path; and a display module configured to generate a display signal to show a floor plan of the area under surveillance, the floor plan including one or more icons overlaid thereon, the one or more icons indicating the location of the camera, the field of view of the camera, the location of the scanner, a location of the identifier, the one or more doors, a predicted future path of the person, a real-time image capture of the camera when a field of view of the camera intersects with the predicted future path of the person, and a historical path of the person, the display signal further shows security response steps in accordance with the security policy.
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1. A security system for an area under surveillance comprising: a first memory including ontology data stored thereon, the ontology data defining interrelationships between a scanner associated with access to a room of an area under surveillance, a camera with a field of view at least partially overlapping a footprint of the room, an identifier configured to be scanned by the scanner and associated with a person, and a security policy including one or more predefined conditions, which when satisfied, indicate when a security threat exists, wherein the security policy includes a response an operator is to perform if the conditions are satisfied; a relational database including temporal data and spatial data stored thereon, the temporal data including time series entries corresponding to scan logs of the scanner including a scan read that indicates a time at which the identifier was scanned, the scanner that scanned the identifier, and whether the person was allowed or denied access based on the scan read, and the spatial data including a location of the camera, a coverage area of the camera, one or more locations of one or more doors to the room, a location of an asset in the room, and a location of the scanner; a query module, executable by a processor configured to receive a query and search the ontology data, the temporal data, and the spatial data in response to receiving the query, wherein the query module is configured to run periodic pre-programmed queries to the first memory and the relational database to determine if the security policy has been violated, and wherein the security policy includes an asset-missing security response configured to automatically send a series of queries to the query module, the series of queries configured to search the ontology data, the spatial data, and the temporal data to: determine, using the spatial data, the room where an asset that went missing is supposed to be; determine, using the spatial data, one or more scanners associated with the room; identify, using the temporal data, one or more identifiers in a list of identifiers that were scanned by the one or more scanners in a specified time window; identify, using the temporal data, one or more other scanners that have scanned the one or more identifiers in another list of identifiers in another specified time window: calculate the predicted future path of one or more persons associated with the one or more identifiers based on the identified one or more scanners and one or more other scanners; and identify one or more cameras with a field of view that intersects the predicted future path; and a display module configured to generate a display signal to show a floor plan of the area under surveillance, the floor plan including one or more icons overlaid thereon, the one or more icons indicating the location of the camera, the field of view of the camera, the location of the scanner, a location of the identifier, the one or more doors, a predicted future path of the person, a real-time image capture of the camera when a field of view of the camera intersects with the predicted future path of the person, and a historical path of the person, the display signal further shows security response steps in accordance with the security policy. 2. The system of claim 1 , the one or more icons further indicating at least one chosen from the group consisting of an entrance and an exit, or a combination thereof.
| 0.567358 |
8,994,741 | 11 | 18 |
11. A method comprising: prefetching, in an image processing pipeline, a plurality of translations to translate addresses of image data in an image being fetched by the image processing pipeline, wherein the plurality of translations translate at least two rows of tiles in the image, and wherein the image processing pipeline is configured to initiate fetching of the image data and, responsive to initiating the fetching, the image processing pipeline discarding all translations and prefetching at least the translations for the first two rows of tiles in the image; and fetching, in the image processing pipeline, the image data using the addresses translated by the plurality of translations.
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11. A method comprising: prefetching, in an image processing pipeline, a plurality of translations to translate addresses of image data in an image being fetched by the image processing pipeline, wherein the plurality of translations translate at least two rows of tiles in the image, and wherein the image processing pipeline is configured to initiate fetching of the image data and, responsive to initiating the fetching, the image processing pipeline discarding all translations and prefetching at least the translations for the first two rows of tiles in the image; and fetching, in the image processing pipeline, the image data using the addresses translated by the plurality of translations. 18. The method as recited in claim 11 further comprising: receiving, in a translation unit coupled to an image processor, memory operations from the image processor; translating, in the translation unit, virtual addresses in the memory operations; transmitting the memory operations with the translated addresses from the translation unit to a memory system.
| 0.630928 |
9,509,884 | 5 | 7 |
5. A skew detection apparatus for estimating a skew angle of a document, comprising: an input to receive in sequence a plurality of segments of an image of the document, each segment comprising a plurality of rows of pixels; a hardware processor to: generate an estimate of skew for each segment; generate a combined estimate of the skew angle, based on the estimate of skew for at least one such segment; and determine a confidence value of the combined estimate of the skew angle, wherein to determine the confidence value, the hardware processor is to: determine an angle of a line joining two pixels for each side of the image; calculate a side confidence value for each angle; combine the angles by clustering them into groups; calculate a group confidence value for each group based on a sum of the side confidence values of the angles in the group; select the group having a highest group confidence value; and estimate the confidence value based on a comparison between the highest group confidence value and a second highest group confidence value.
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5. A skew detection apparatus for estimating a skew angle of a document, comprising: an input to receive in sequence a plurality of segments of an image of the document, each segment comprising a plurality of rows of pixels; a hardware processor to: generate an estimate of skew for each segment; generate a combined estimate of the skew angle, based on the estimate of skew for at least one such segment; and determine a confidence value of the combined estimate of the skew angle, wherein to determine the confidence value, the hardware processor is to: determine an angle of a line joining two pixels for each side of the image; calculate a side confidence value for each angle; combine the angles by clustering them into groups; calculate a group confidence value for each group based on a sum of the side confidence values of the angles in the group; select the group having a highest group confidence value; and estimate the confidence value based on a comparison between the highest group confidence value and a second highest group confidence value. 7. The skew detection apparatus of claim 5 , wherein to generate an estimate of skew for each segment, the hardware processor is to: generate a first estimate of the skew angle based on a mutual alignment of peripheral boundary points of the document itself or peripheral boundary points of foreground content of the document; and generate a second estimate of the skew angle based on the orientation of foreground or background content in the interior of the document.
| 0.5 |
10,002,543 | 1 | 8 |
1. A computer operable method for transforming phonemes, graphemes, and other language structures into interactive elements, comprising the steps of: receiving a word, wherein the word consists of a group of phonemes; forming a group of graphemes, wherein the group of graphemes is constructed using information relating to the group of phonemes; and for each phoneme or grapheme in the group of phonemes or group of graphemes, determining a graphical manipulative, wherein each graphical manipulative is constructed using information relating to the phoneme or grapheme and each graphical manipulative corresponds to an individual phoneme or grapheme within the group of phonemes or group of graphemes, to form a group of graphical manipulatives; displaying the group of graphemes and the group of graphical manipulatives; receiving a selection of a first graphical manipulative and expanding the selection to include a first phoneme and first grapheme associated with the first graphical manipulative; receiving a change request via the first graphical manipulative, wherein the change request contains a request to alter the first phoneme or first grapheme associated with the first graphical manipulative; evaluating the change request to determine a phonotactic validity value, an orthographic validity value, or an instructional validity value of the change request; approving the change request only if the phonotactic validity value, the orthographic validity value, or the instructional validity value are allowed by one or more validity thresholds; and if the change request is approved, determining any changes in the group of phonemes, the group of graphemes, or the group of graphical manipulatives and updating the display of the group of graphemes and the group of graphical manipulatives.
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1. A computer operable method for transforming phonemes, graphemes, and other language structures into interactive elements, comprising the steps of: receiving a word, wherein the word consists of a group of phonemes; forming a group of graphemes, wherein the group of graphemes is constructed using information relating to the group of phonemes; and for each phoneme or grapheme in the group of phonemes or group of graphemes, determining a graphical manipulative, wherein each graphical manipulative is constructed using information relating to the phoneme or grapheme and each graphical manipulative corresponds to an individual phoneme or grapheme within the group of phonemes or group of graphemes, to form a group of graphical manipulatives; displaying the group of graphemes and the group of graphical manipulatives; receiving a selection of a first graphical manipulative and expanding the selection to include a first phoneme and first grapheme associated with the first graphical manipulative; receiving a change request via the first graphical manipulative, wherein the change request contains a request to alter the first phoneme or first grapheme associated with the first graphical manipulative; evaluating the change request to determine a phonotactic validity value, an orthographic validity value, or an instructional validity value of the change request; approving the change request only if the phonotactic validity value, the orthographic validity value, or the instructional validity value are allowed by one or more validity thresholds; and if the change request is approved, determining any changes in the group of phonemes, the group of graphemes, or the group of graphical manipulatives and updating the display of the group of graphemes and the group of graphical manipulatives. 8. A computer operable method according to claim 1 , wherein the size of each graphical manipulative is based on whether a phoneme associated with the graphical manipulative is a digraph or a trigraph.
| 0.769495 |
8,228,824 | 1 | 8 |
1. A method for processing contextual information relating to an exchange of a conversation on a communication channel between a first client and a second client, comprising: establishing between the first client and the second client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit contextual information before and after the communication channel is established; obtaining first contextual information relating to the first client; wherein the first contextual information is packetized and arranged according to the predefined structured hierarchy; wherein the contextual information comprises client preferences, a set of rules, and device functionality; determining a set of rules by processing the obtained first contextual information; obtaining second contextual information relating to the second client; determining conditions of the second client by processing the second contextual information; comparing the set of rules with the conditions of the second client; if the conditions of the second client satisfy the set of rules, establishing, or maintaining a communication channel connection as indicated by the set of rules; and after establishing the communication channel as indicated by the set of rules performing operations comprising: obtaining additional contextual information; determining current conditions of the second client by processing the additional contextual information; comparing the set of rules with the additional conditions of the second client; and providing a notification of terminating the communication channel when at least one rule of the set of rules does not satisfy a connection condition with the first client based on the condition of the second client, wherein the connection condition is at least one of a desired mood; a desired subject of the conversation; and a desired location.
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1. A method for processing contextual information relating to an exchange of a conversation on a communication channel between a first client and a second client, comprising: establishing between the first client and the second client a predefined structured hierarchy to use to transmit contextual information; wherein the predefined structured hierarchy is used to transmit contextual information before and after the communication channel is established; obtaining first contextual information relating to the first client; wherein the first contextual information is packetized and arranged according to the predefined structured hierarchy; wherein the contextual information comprises client preferences, a set of rules, and device functionality; determining a set of rules by processing the obtained first contextual information; obtaining second contextual information relating to the second client; determining conditions of the second client by processing the second contextual information; comparing the set of rules with the conditions of the second client; if the conditions of the second client satisfy the set of rules, establishing, or maintaining a communication channel connection as indicated by the set of rules; and after establishing the communication channel as indicated by the set of rules performing operations comprising: obtaining additional contextual information; determining current conditions of the second client by processing the additional contextual information; comparing the set of rules with the additional conditions of the second client; and providing a notification of terminating the communication channel when at least one rule of the set of rules does not satisfy a connection condition with the first client based on the condition of the second client, wherein the connection condition is at least one of a desired mood; a desired subject of the conversation; and a desired location. 8. The method of claim 1 , wherein the set of rules includes a rule indicating a desired subject relating to the conversation.
| 0.714932 |
9,250,894 | 1 | 11 |
1. A computer-implemented method, comprising: utilizing a computing system to perform: receiving a program, wherein the program specifies a plurality of operations using a variable within a logical tick such that the variable has multiple values within the logical tick; statically analyzing the program according to a specified model of computation that specifies program execution based on logical ticks, wherein said statically analyzing the program includes: determining that the program has deterministic semantics, wherein the deterministic semantics specify deterministic results for each logical tick during execution of the program, including specifying deterministic results of the plurality of operations performed within the logical tick; wherein the deterministic semantics is based on, within a given logical tick: a scheduling of operations that are sequential with respect to each other as specified by the program according to the specified sequence; and a scheduling of operations that are concurrent with each other such that assignments to a variable are performed before reads of the variable, including scheduling the assignment operations to the variable that are concurrent with each other such that a first assignment operation is scheduled before one or more other assignment operations, wherein the order of the one or more other assignment operations does not influence a final result of the variable for the logical tick; and validating the program in accordance with the specified model of computation in response to said determining.
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1. A computer-implemented method, comprising: utilizing a computing system to perform: receiving a program, wherein the program specifies a plurality of operations using a variable within a logical tick such that the variable has multiple values within the logical tick; statically analyzing the program according to a specified model of computation that specifies program execution based on logical ticks, wherein said statically analyzing the program includes: determining that the program has deterministic semantics, wherein the deterministic semantics specify deterministic results for each logical tick during execution of the program, including specifying deterministic results of the plurality of operations performed within the logical tick; wherein the deterministic semantics is based on, within a given logical tick: a scheduling of operations that are sequential with respect to each other as specified by the program according to the specified sequence; and a scheduling of operations that are concurrent with each other such that assignments to a variable are performed before reads of the variable, including scheduling the assignment operations to the variable that are concurrent with each other such that a first assignment operation is scheduled before one or more other assignment operations, wherein the order of the one or more other assignment operations does not influence a final result of the variable for the logical tick; and validating the program in accordance with the specified model of computation in response to said determining. 11. The method of claim 1 , wherein the one or more other assignment operations specify the same commutative and associative operation.
| 0.680095 |
9,275,152 | 9 | 10 |
9. The method of claim 1 , further comprising: determining a respective ranking score for each of the entities of the second entity type; and ordering the entities of the second entity type according to the ranking scores.
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9. The method of claim 1 , further comprising: determining a respective ranking score for each of the entities of the second entity type; and ordering the entities of the second entity type according to the ranking scores. 10. The method of claim 9 , wherein the ranking score for a particular entity of the second entity type is based at least in part on how frequently a recognized reference to the particular entity co-occurs with a recognized reference to the first entity in resources indexed by an indexing engine.
| 0.558036 |
9,373,031 | 1 | 3 |
1. A method comprising: receiving, by a processor, a first template document, wherein the first template document comprises a first plurality of text objects; and receiving by the processor, a reference document, wherein the reference document comprises second a plurality of text objects, wherein at least one of the first template document and the reference document are misaligned or upside down during the following steps: identifying by the processor, the first plurality of text objects in the first template document; identifying by the processor, the second plurality of text objects in the reference document; identifying by the processor, a plurality of common identical text objects between the first template document and the reference document; identifying by the processor, locations of the plurality of common identical text objects in the first template document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the first template document; identifying by the processor, locations of the plurality of common identical text objects in the reference document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the reference document; determining, by the processor, that the two or more distances between the plurality of common identical text objects in the first template document are within a given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document; and in response to determining that the two or more distances between the plurality of common identical text objects in the first template document are within the given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document, grouping the first template document and the reference document as common documents, wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the first template document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the first template document and wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the reference document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the reference document.
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1. A method comprising: receiving, by a processor, a first template document, wherein the first template document comprises a first plurality of text objects; and receiving by the processor, a reference document, wherein the reference document comprises second a plurality of text objects, wherein at least one of the first template document and the reference document are misaligned or upside down during the following steps: identifying by the processor, the first plurality of text objects in the first template document; identifying by the processor, the second plurality of text objects in the reference document; identifying by the processor, a plurality of common identical text objects between the first template document and the reference document; identifying by the processor, locations of the plurality of common identical text objects in the first template document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the first template document; identifying by the processor, locations of the plurality of common identical text objects in the reference document; identifying by the processor, two or more distances between the locations of the plurality of common identical text objects in the reference document; determining, by the processor, that the two or more distances between the plurality of common identical text objects in the first template document are within a given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document; and in response to determining that the two or more distances between the plurality of common identical text objects in the first template document are within the given percentage of variance as the two or more distances between the plurality of common identical text objects in the reference document, grouping the first template document and the reference document as common documents, wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the first template document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the first template document and wherein an endpoint of a first one of the two or more distances between the plurality of common identical text objects in the reference document is used as a starting point for a second one of the two or more distances between the plurality of common identical text objects in the reference document. 3. The method of claim 1 , wherein determining that the plurality of distances are within the given percentage of variance is based on a relative distance using a number of Dots Per Inch (DPI) between the plurality of common identical text objects in the first template document and the plurality of common identical text objects in the reference document.
| 0.897288 |
8,793,203 | 1 | 2 |
1. A method for estimating effort for implementing a system associated with a document, comprising: quantifying a structure of the document and evaluating a format of the document using a computing device; identifying a domain of an application associated with the document; defining a set of complexity variables associated with the document based on the structure of the document, a format of the document and a domain of the document; using a neural network to estimate an effort based on the set of complexity variables; and outputting the effort via a tangible medium; wherein quantifying the structure of the document comprises determining a volume of text in the document and determining a distribution of text in the document; wherein evaluating the format of the document comprises comparing the document to a predefined standard; and wherein identifying the domain of the document comprises identifying a subject of the document.
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1. A method for estimating effort for implementing a system associated with a document, comprising: quantifying a structure of the document and evaluating a format of the document using a computing device; identifying a domain of an application associated with the document; defining a set of complexity variables associated with the document based on the structure of the document, a format of the document and a domain of the document; using a neural network to estimate an effort based on the set of complexity variables; and outputting the effort via a tangible medium; wherein quantifying the structure of the document comprises determining a volume of text in the document and determining a distribution of text in the document; wherein evaluating the format of the document comprises comparing the document to a predefined standard; and wherein identifying the domain of the document comprises identifying a subject of the document. 2. The method of claim 1 , wherein the document comprises a use case.
| 0.808333 |
7,962,853 | 10 | 11 |
10. The method of claim 5 , wherein the notification to a first reviewer of the plurality of reviewers comprises a link to the document.
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10. The method of claim 5 , wherein the notification to a first reviewer of the plurality of reviewers comprises a link to the document. 11. The method of claim 10 , wherein the notification to the first reviewer further comprises each comment directed to the first reviewer and the portion of the document associated with each comment directed to the first reviewer.
| 0.5 |
8,782,518 | 8 | 9 |
8. The medical diagnosis system of claim 7 , wherein a. a multilingual directive is associated with a filename, and b. wherein the medical diagnosis system further comprises a display screen configured to display a list of a plurality of multilingual filenames.
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8. The medical diagnosis system of claim 7 , wherein a. a multilingual directive is associated with a filename, and b. wherein the medical diagnosis system further comprises a display screen configured to display a list of a plurality of multilingual filenames. 9. The medical diagnosis system of claim 8 , wherein a patient identifier is attached to the filename as a prefix.
| 0.589928 |
8,584,208 | 1 | 4 |
1. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to at least: receive an indication of markup language based content loaded at a browser; parse the content loaded at the browser for a context resource request in a context resource description language that provides a specification of information embedded within the received content, wherein the information of said context resource request provides an identification of properties requested at the browser in association with a service operating on the apparatus from which the content was loaded at the browser; and cause one or more of the requested properties to be managed on the apparatus with conflict resolution according to property settings and user permissions for provision to the service.
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1. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to at least: receive an indication of markup language based content loaded at a browser; parse the content loaded at the browser for a context resource request in a context resource description language that provides a specification of information embedded within the received content, wherein the information of said context resource request provides an identification of properties requested at the browser in association with a service operating on the apparatus from which the content was loaded at the browser; and cause one or more of the requested properties to be managed on the apparatus with conflict resolution according to property settings and user permissions for provision to the service. 4. The apparatus of claim 1 , wherein the at least one memory and the computer program code are further configured to, with the at least one processor, cause the apparatus to enable the resolution of a conflict with respect to requested properties associated with different modes of service via conversion between the respective different modes of service.
| 0.517615 |
8,996,982 | 1 | 6 |
1. A requirements planning management method comprising: identifying in a requirements planning system executing in memory of a host computing platform, each approving stakeholder for a version of a requirement in a requirements plan of requirements for a software system; creating traceability links between each approving stakeholder and the version of the requirement, each traceability link connecting a stakeholder with a specific version of the requirement requiring the approval of the stakeholder and tracking different approval status values for different versions of a corresponding requirement; notifying each approving stakeholder having the traceability link to the version of the requirement whenever a new version of the requirement is proposed by the stakeholder; merging all versions of the requirement into a single document for displaying the single document to a viewing approving stakeholder; and marking up the single document to reflect differences between the single document and a most recent version of the requirement approved by the viewing approving stakeholder.
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1. A requirements planning management method comprising: identifying in a requirements planning system executing in memory of a host computing platform, each approving stakeholder for a version of a requirement in a requirements plan of requirements for a software system; creating traceability links between each approving stakeholder and the version of the requirement, each traceability link connecting a stakeholder with a specific version of the requirement requiring the approval of the stakeholder and tracking different approval status values for different versions of a corresponding requirement; notifying each approving stakeholder having the traceability link to the version of the requirement whenever a new version of the requirement is proposed by the stakeholder; merging all versions of the requirement into a single document for displaying the single document to a viewing approving stakeholder; and marking up the single document to reflect differences between the single document and a most recent version of the requirement approved by the viewing approving stakeholder. 6. The method of claim 1 , further comprising: applying a question type annotation to the version of the requirement; identifying a stakeholder responsible for creating the version of the requirement; and, notifying the identified stakeholder of the question to solicit a comment type annotation by the identified stakeholder as a response to the question type annotation.
| 0.523077 |
7,958,501 | 4 | 5 |
4. A computer-readable storage medium storing program code, the program code comprising: code to call a constructor to register an interface to a description of a persistent class; code to access the registered interface to determine an internal structure of the persistent class; code to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object; code to determine, based on the determined internal structure, members of the persistent database object that are filled with default values; code to store the persistent database object in a database; code to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database; code to read the persistent database object from the database after the storing of the persistent database object in the database; code to populate the determined members of the persistent database object with the default values after the reading of the persistent database object from the database; code to define an index associated with one or more members of the instance based on the determined internal structure; and code to verify referential integrity of the instance.
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4. A computer-readable storage medium storing program code, the program code comprising: code to call a constructor to register an interface to a description of a persistent class; code to access the registered interface to determine an internal structure of the persistent class; code to process an instance of the persistent class based on the determined internal structure, wherein the instance of the persistent class is a persistent database object; code to determine, based on the determined internal structure, members of the persistent database object that are filled with default values; code to store the persistent database object in a database; code to reduce storage demands on the database by removing the default values from the persistent database object before the storing of the persistent database object in the database; code to read the persistent database object from the database after the storing of the persistent database object in the database; code to populate the determined members of the persistent database object with the default values after the reading of the persistent database object from the database; code to define an index associated with one or more members of the instance based on the determined internal structure; and code to verify referential integrity of the instance. 5. The medium according to claim 4 , the program code further comprising: code to register the persistent class in an object management system, and wherein the interface is registered in the object management system.
| 0.678571 |
9,853,925 | 12 | 16 |
12. A computer program product for automatic transformation of messages between service versions, the computer program product comprising a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by a computer to perform a method comprising: identifying and collecting message data of messages sent to two or more versions of a service, using a proxy system, and storing the collected message data in a historical message data store using the proxy system; transforming a message of the messages using message transformation rules generated based on the collected message data in the historical message data store, the message transformation rules for transforming a message format for an earlier version of the service to a message format for a later version of the service, using the proxy system, the transforming the message being in response to identifying, using the proxy system, the message being for the earlier version of the service and there being the later version of the service; forwarding the transformed message to the later version of the service, using the proxy system:, identifying the message data as relating to a version of a service; inferring relationships between structure and content of the messages sent to different versions of a service; creating the message transformation rules based on the inferred relationships, the message transformation rules being for transforming the message format for the earlier version of the service to the message format for the later version of the service; and receiving the message for the version of the service, using the proxy system.
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12. A computer program product for automatic transformation of messages between service versions, the computer program product comprising a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by a computer to perform a method comprising: identifying and collecting message data of messages sent to two or more versions of a service, using a proxy system, and storing the collected message data in a historical message data store using the proxy system; transforming a message of the messages using message transformation rules generated based on the collected message data in the historical message data store, the message transformation rules for transforming a message format for an earlier version of the service to a message format for a later version of the service, using the proxy system, the transforming the message being in response to identifying, using the proxy system, the message being for the earlier version of the service and there being the later version of the service; forwarding the transformed message to the later version of the service, using the proxy system:, identifying the message data as relating to a version of a service; inferring relationships between structure and content of the messages sent to different versions of a service; creating the message transformation rules based on the inferred relationships, the message transformation rules being for transforming the message format for the earlier version of the service to the message format for the later version of the service; and receiving the message for the version of the service, using the proxy system. 16. The computer program product as claimed in claim 12 , comprising: identifying a new service version based on monitored message traffic; and comparing the new service version with known service versions to match to an earlier version of the service.
| 0.5 |
9,292,688 | 11 | 14 |
11. A computer-implemented method for improved zero-day malware detection comprising: receiving, at a computer that includes one or more processors and memory, a set of training files which are each known to be either malign or benign, wherein the training files comprise one or more types of computer files; analyzing, using the one or more computer processors, the set of training files to determine features of the training files, wherein the analyzing determines n-gram features; receiving, using the one or more computer processors, a feature set description that includes a semantic label for each attribute class present in the training files and a set of corresponding attributes that make up the attribute class; generating, using the one or more computer processors, a plurality of attribute class-specific feature vectors (FVs) for the training files using the determined n-gram features and the feature set description, wherein the FVs are vectors of n-gram features present in malign files of the attribute class; concatenating, using the one or more computer processors, the plurality of attribute class-specific FVs into an extended feature vector (EFV) for the training files; and generating, using the one or more computer processors, a target file classifier based on the EFV using a plurality of classifier algorithms.
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11. A computer-implemented method for improved zero-day malware detection comprising: receiving, at a computer that includes one or more processors and memory, a set of training files which are each known to be either malign or benign, wherein the training files comprise one or more types of computer files; analyzing, using the one or more computer processors, the set of training files to determine features of the training files, wherein the analyzing determines n-gram features; receiving, using the one or more computer processors, a feature set description that includes a semantic label for each attribute class present in the training files and a set of corresponding attributes that make up the attribute class; generating, using the one or more computer processors, a plurality of attribute class-specific feature vectors (FVs) for the training files using the determined n-gram features and the feature set description, wherein the FVs are vectors of n-gram features present in malign files of the attribute class; concatenating, using the one or more computer processors, the plurality of attribute class-specific FVs into an extended feature vector (EFV) for the training files; and generating, using the one or more computer processors, a target file classifier based on the EFV using a plurality of classifier algorithms. 14. The method of claim 11 further comprising parsing, using the one or more computer processors, the feature set description and defining a data structure that holds the attribute classes and sets of corresponding attributes as key-value pairs.
| 0.857226 |
8,082,215 | 24 | 30 |
24. The system of claim 1 , further comprising: one or more sensors to sense physical characteristics of the first authoring user and the second authoring user, the first inference data and the second inference data derived based, at least in part, on the sensed physical characteristics of the first authoring user and the second authoring user.
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24. The system of claim 1 , further comprising: one or more sensors to sense physical characteristics of the first authoring user and the second authoring user, the first inference data and the second inference data derived based, at least in part, on the sensed physical characteristics of the first authoring user and the second authoring user. 30. The system of claim 24 , wherein said one or more sensors to sense physical characteristics of the first authoring user and the second authoring user, the first inference data and the second inference data derived based, at least in part, on the sensed physical characteristics of the first authoring user and the second authoring user, comprises: an electroencephalography (EEG) device.
| 0.609 |
8,661,399 | 9 | 10 |
9. The computer program of claim 8 , further comprising: receiving a module reference file (MRF) including a BIST organizational file for a plurality of memory wrappers in at least one module.
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9. The computer program of claim 8 , further comprising: receiving a module reference file (MRF) including a BIST organizational file for a plurality of memory wrappers in at least one module. 10. The computer program of claim 9 , wherein only the plurality of memory wrappers in the modules not listed in the MRF are scanned and at least one reference statement corresponding to a specified view of each occurrence is of the modules listed in the MRF added to the BIST organizational file.
| 0.5 |
9,031,950 | 1 | 7 |
1. A non-transitory computer readable storage medium having a computer program stored thereon, the computer program causing a computer to perform the steps of: (a) determining a set of possible elements; (b) ordering the set of possible elements according to one or more attributes, each of the ordered elements making up a group; (c) determining a first covariance only between a first of the groups and a second of the groups; (d) determining that the first group is a good enough subset of the ordered set of possible elements if the first covariance is greater than the predetermined threshold; (e) combining the first of the groups and the second of the groups to form a new first group of elements from the ordered set of possible elements if the first covariance is determined to be less than a predetermined threshold; (f) determining a second covariance between the new first group of elements and a next group of the ordered set of possible elements; (g) determining that the new first group is a good enough subset of the ordered set of possible elements if the second covariance is greater than the predetermined threshold; (h) combining the new first of the groups and the second of the groups to form a new first group of elements from the ordered set of possible elements if the second covariance is determined to be less than a predetermined threshold; and repeating steps (f)-(h) until the top group of elements is determined to be a good enough subset of the ordered set of possible elements.
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1. A non-transitory computer readable storage medium having a computer program stored thereon, the computer program causing a computer to perform the steps of: (a) determining a set of possible elements; (b) ordering the set of possible elements according to one or more attributes, each of the ordered elements making up a group; (c) determining a first covariance only between a first of the groups and a second of the groups; (d) determining that the first group is a good enough subset of the ordered set of possible elements if the first covariance is greater than the predetermined threshold; (e) combining the first of the groups and the second of the groups to form a new first group of elements from the ordered set of possible elements if the first covariance is determined to be less than a predetermined threshold; (f) determining a second covariance between the new first group of elements and a next group of the ordered set of possible elements; (g) determining that the new first group is a good enough subset of the ordered set of possible elements if the second covariance is greater than the predetermined threshold; (h) combining the new first of the groups and the second of the groups to form a new first group of elements from the ordered set of possible elements if the second covariance is determined to be less than a predetermined threshold; and repeating steps (f)-(h) until the top group of elements is determined to be a good enough subset of the ordered set of possible elements. 7. The non-transitory computer readable storage medium of claim 1 , wherein the first covariance between the first and second of the groups of elements and the second covariance between the new first group and the second group of elements are determined at least in part by comparing the first and second groups and the new first group and the next group to a user query.
| 0.5 |
8,032,509 | 1 | 4 |
1. A computer system comprising: (a) at least one processor; (b) at least one memory, wherein the at least one memory includes a relation store and a data set information store; and (c) computer program instructions stored in the memory and configured to be executed by the processor to provide a requested data set, including: (i) instructions for receiving a first query language statement referencing a plurality of data sets; (ii) instructions for storing information in the data set information store regarding the data sets referenced in the first query language statement, including temporal information regarding the data sets referenced in the first query language statement; (iii) instructions for composing a first plurality of algebraic relations referencing the data sets specified in the first query language statement, wherein each of the algebraic relations in the first plurality of algebraic relations comprises a respective first expression including a symbolic representation of at least a first respective data set, a respective second expression including a symbolic representation of at least a second respective data set, and a relational operator symbolically defining a mathematical relationship between the respective first expression and the respective second expression; (iv) instructions for storing the first plurality of algebraic relations in the relation store; (v) instructions for receiving a second query language statement referencing a second plurality of data sets; (vi) instructions for composing a second plurality of algebraic relations referencing the data sets specified in the second query language statement; (vii) instructions for storing the second plurality of algebraic relations in the relation store; (viii) instructions for providing the requested data set in response to the second query language statement using at least one algebraic relation from the first plurality of algebraic relations and at least one algebraic relation from the second plurality of algebraic relations; and (ix) instructions for removing at least some of the first plurality of algebraic relations from the relation store based, at least in part, on the temporal information regarding the data sets referenced in the first query language statement.
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1. A computer system comprising: (a) at least one processor; (b) at least one memory, wherein the at least one memory includes a relation store and a data set information store; and (c) computer program instructions stored in the memory and configured to be executed by the processor to provide a requested data set, including: (i) instructions for receiving a first query language statement referencing a plurality of data sets; (ii) instructions for storing information in the data set information store regarding the data sets referenced in the first query language statement, including temporal information regarding the data sets referenced in the first query language statement; (iii) instructions for composing a first plurality of algebraic relations referencing the data sets specified in the first query language statement, wherein each of the algebraic relations in the first plurality of algebraic relations comprises a respective first expression including a symbolic representation of at least a first respective data set, a respective second expression including a symbolic representation of at least a second respective data set, and a relational operator symbolically defining a mathematical relationship between the respective first expression and the respective second expression; (iv) instructions for storing the first plurality of algebraic relations in the relation store; (v) instructions for receiving a second query language statement referencing a second plurality of data sets; (vi) instructions for composing a second plurality of algebraic relations referencing the data sets specified in the second query language statement; (vii) instructions for storing the second plurality of algebraic relations in the relation store; (viii) instructions for providing the requested data set in response to the second query language statement using at least one algebraic relation from the first plurality of algebraic relations and at least one algebraic relation from the second plurality of algebraic relations; and (ix) instructions for removing at least some of the first plurality of algebraic relations from the relation store based, at least in part, on the temporal information regarding the data sets referenced in the first query language statement. 4. The computer system of claim 1 , further comprising a data store for storing at least some of the data sets, wherein at least one of the data sets specified in the second query language statement has not been stored in the data store at the time the second query language statement is received.
| 0.647268 |
7,809,536 | 1 | 2 |
1. A computer-based method of defining a model of an information processing system, comprising: defining a set of discovery instructions configured to discover first snapshot data via a computer communications network about hardware and/or software resources within said information processing system, including a client and a server computer system, wherein said model: defines a set of components of said information processing system, the set being a subset of said resources needed to deploy an instance of an application, defines properties of said components, and provides said discovery instructions to said application to discover first said snapshot data about a state of said properties; and executing on a computer system a software program configured to provide visualization and analysis of said information processing system based on said first snapshot data wherein said analysis includes at least one of: loading and comparing a second snapshot data to said first snapshot data, loading an analysis overlay and using said analysis overlay to evaluate said first snapshot data.
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1. A computer-based method of defining a model of an information processing system, comprising: defining a set of discovery instructions configured to discover first snapshot data via a computer communications network about hardware and/or software resources within said information processing system, including a client and a server computer system, wherein said model: defines a set of components of said information processing system, the set being a subset of said resources needed to deploy an instance of an application, defines properties of said components, and provides said discovery instructions to said application to discover first said snapshot data about a state of said properties; and executing on a computer system a software program configured to provide visualization and analysis of said information processing system based on said first snapshot data wherein said analysis includes at least one of: loading and comparing a second snapshot data to said first snapshot data, loading an analysis overlay and using said analysis overlay to evaluate said first snapshot data. 2. The method of claim 1 further comprising: defining a relationship between a model of the client computer system and a model of the server computer system, and providing an instruction configured to discover data about said relationship.
| 0.635671 |
8,874,541 | 7 | 8 |
7. The computer-implemented method of claim 6 , wherein the method further comprises receiving, from the business, a selection of the option to publish the selected at least one search keyword on the online information resource.
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7. The computer-implemented method of claim 6 , wherein the method further comprises receiving, from the business, a selection of the option to publish the selected at least one search keyword on the online information resource. 8. The computer-implemented method of claim 7 , wherein the selected at least one search keyword is published to the online information resource according to the selection, by the business, of the option to publish the selected at least one search keyword.
| 0.5 |
6,065,001 | 9 | 12 |
9. An information association apparatus according to claim 8 further comprising: said association degree dictionary composed of an interval association degree dictionary which stores the correlation degree of key words found by calculating the association degree between said two key words based on the minimum time interval which is the smallest value among time intervals during which each query extracted for each search user was used from the queries used during the past predetermined period, and adding said association degrees calculated for a plurality of said search users, and a correlation degree dictionary which stores the correlation degrees for key words found by compiling said queries for each user for each predetermined time interval from queries used during said past predetermined time interval, calculating for each of said users the number of uses of key words among said queries within said predetermined time interval, adding said number of uses of each key word for all of said search users, and calculating the association degree between two key words based on the number of uses of each of said key words, and further characterized by: said initialization unit which generates initial groups for grouping key words according to the interval association degree and the correlation degree stored in said interval association degree dictionary, and said grouping unit grouping associated key words by sequentially making groups satisfying predetermined conditions into one group using said initial groups and the interval association degree between key words stored in said interval association degree dictionary and the correlation degree between key words stored in said correlation degree dictionary.
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9. An information association apparatus according to claim 8 further comprising: said association degree dictionary composed of an interval association degree dictionary which stores the correlation degree of key words found by calculating the association degree between said two key words based on the minimum time interval which is the smallest value among time intervals during which each query extracted for each search user was used from the queries used during the past predetermined period, and adding said association degrees calculated for a plurality of said search users, and a correlation degree dictionary which stores the correlation degrees for key words found by compiling said queries for each user for each predetermined time interval from queries used during said past predetermined time interval, calculating for each of said users the number of uses of key words among said queries within said predetermined time interval, adding said number of uses of each key word for all of said search users, and calculating the association degree between two key words based on the number of uses of each of said key words, and further characterized by: said initialization unit which generates initial groups for grouping key words according to the interval association degree and the correlation degree stored in said interval association degree dictionary, and said grouping unit grouping associated key words by sequentially making groups satisfying predetermined conditions into one group using said initial groups and the interval association degree between key words stored in said interval association degree dictionary and the correlation degree between key words stored in said correlation degree dictionary. 12. An information associating apparatus according to claim 9 further characterized by: said initializing unit further comprising a cosine calculation unit which calculates the cosine value between each key word by generating a vector for each word using the interval association degree between a predetermined key word and each key word by using said interval association degree dictionary, and calculating the cosine value between the vectors of two key words, and is further characterized in said initializing unit generating initial groups such that using the cosine value calculated by said cosine calculation unit the cosine values between all key words included in each group are larger than a predetermined threshold value.
| 0.607411 |
7,725,309 | 1 | 4 |
1. A method for performing speech recognition, the method being performed by one or more processors that perform steps comprising: identifying a plurality of entries from a sequence of phonetic units that are recognized from a spoken input, wherein the plurality of entries individually match to one or more items that comprise one or more records of a database that comprises a plurality of records; accessing a search node for the database, wherein the search node includes, for each record of at least some of the plurality of records, multiple phonetic representations, including at least one phonetic representation that contains at least one of (i) an abbreviation of an entry that is included in the record, or (ii) a null use of an entry that is included in the record when that entry is combined with one or more other entries; and selecting, from the search node, a matching record of the database for the spoken input, wherein selecting the matching record includes comparing the plurality of entries identified from the spoken input to the phonetic representations of the individual records, including to the multiple phonetic representations of records in the at least some of the plurality of records.
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1. A method for performing speech recognition, the method being performed by one or more processors that perform steps comprising: identifying a plurality of entries from a sequence of phonetic units that are recognized from a spoken input, wherein the plurality of entries individually match to one or more items that comprise one or more records of a database that comprises a plurality of records; accessing a search node for the database, wherein the search node includes, for each record of at least some of the plurality of records, multiple phonetic representations, including at least one phonetic representation that contains at least one of (i) an abbreviation of an entry that is included in the record, or (ii) a null use of an entry that is included in the record when that entry is combined with one or more other entries; and selecting, from the search node, a matching record of the database for the spoken input, wherein selecting the matching record includes comparing the plurality of entries identified from the spoken input to the phonetic representations of the individual records, including to the multiple phonetic representations of records in the at least some of the plurality of records. 4. The method of claim 1 , wherein identifying a plurality of entries from a sequence of phonetic units includes ignoring an entry corresponding to a title of a person.
| 0.766667 |
8,341,665 | 18 | 21 |
18. A method of providing information, comprising: providing a video stream; applying automatic image recognition to the video stream; selecting information responsive to the image recognition; and displaying the selected information within ten minutes from performing the image recognition leading to selection of the displayed information, wherein providing the video stream comprises providing a video stream acquired by a camera included in a mobile communication terminal.
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18. A method of providing information, comprising: providing a video stream; applying automatic image recognition to the video stream; selecting information responsive to the image recognition; and displaying the selected information within ten minutes from performing the image recognition leading to selection of the displayed information, wherein providing the video stream comprises providing a video stream acquired by a camera included in a mobile communication terminal. 21. A method according to claim 18 , wherein displaying the selected information comprises displaying advertisements.
| 0.74115 |
9,881,610 | 11 | 17 |
11. An article of manufacture comprising a non-transitory computer readable storage medium for storing computer readable program code which, when executed, causes a computer to: determine a vicinity from which speech input to a speech recognition system originates, wherein the determination of the vicinity comprises an estimation of a sound direction of a source of the speech input based on a signal processing method; obtain non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein the obtaining of the non-acoustic data comprises program code that causes the computer to capture visual data of the vicinity of the speech input; indenify a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein the identification of the subject speaker comprises program code that causes the computer to: segment one or more faces from the captured visual data; detect mouth motion on the one or more faces, wherein the detection of the mouth motion comprises an application of temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and select a face corresponding to the subject speaker from the one or more faces in response to a determination that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extract one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyze the one or more non-acoustic attributes, and assign at least one demographic to the subject speaker based on the analysis; select at least one model for use by the speech recognition system based on the demographic assigned to the subject speaker; adjust the speech recognition system using the at least one selected model; and process the speech input using the adjusted speech recognition system.
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11. An article of manufacture comprising a non-transitory computer readable storage medium for storing computer readable program code which, when executed, causes a computer to: determine a vicinity from which speech input to a speech recognition system originates, wherein the determination of the vicinity comprises an estimation of a sound direction of a source of the speech input based on a signal processing method; obtain non-acoustic data from the vicinity of the speech input using one or more non-acoustic sensors, wherein the obtaining of the non-acoustic data comprises program code that causes the computer to capture visual data of the vicinity of the speech input; indenify a subject speaker as the source of the speech input from the obtained non-acoustic data, wherein the identification of the subject speaker comprises program code that causes the computer to: segment one or more faces from the captured visual data; detect mouth motion on the one or more faces, wherein the detection of the mouth motion comprises an application of temporal differencing on each of the one or more faces by comparing a first pixel intensity associated at a first time with a second pixel intensity at a second time; and select a face corresponding to the subject speaker from the one or more faces in response to a determination that a number of significantly changed pixels between the first pixel intensity and the second pixel intensity exceeds a threshold; extract one or more non-acoustic attributes associated with the subject speaker from the obtained non-acoustic data; analyze the one or more non-acoustic attributes, and assign at least one demographic to the subject speaker based on the analysis; select at least one model for use by the speech recognition system based on the demographic assigned to the subject speaker; adjust the speech recognition system using the at least one selected model; and process the speech input using the adjusted speech recognition system. 17. The article of claim 11 , wherein the direction of the source of the speech input is estimated based on at least one of a beamformer based method, a time delay of arrival based method, and a spectrum estimation based method.
| 0.693548 |
8,166,001 | 9 | 10 |
9. The system of claim 6 wherein the processor is further configured to execute instructions comprising: tracking an indication of members of the set of control statements that are not linked to a corresponding policy.
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9. The system of claim 6 wherein the processor is further configured to execute instructions comprising: tracking an indication of members of the set of control statements that are not linked to a corresponding policy. 10. The system of claim 9 wherein the processor is further configured to execute instructions comprising: displaying an indication of each control statement not linked to the corresponding policy.
| 0.577586 |
9,524,342 | 8 | 12 |
8. An apparatus for implementation of a panoptic visualization document navigation system, the apparatus comprising a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to implement at least: a navigation engine configured to receive a layout of document components of a panoptic visualization document collection having a plurality of document components each of which includes respective media content and has associated metadata providing information about the respective document component, the layout including a panoptic arrangement of visual representations of the document components of the layout according to the associated metadata of the respective document components, wherein the navigation engine is configured to select one or more navigation options from a plurality of navigation options for navigating a visual presentation of the layout, the navigation options being selected according to the associated metadata for the document components of the layout, and wherein the navigation engine is configured to communicate the selected navigation options to a graphical user interface for presentation to a user along with the visual presentation of the layout, the selected navigation options thereby being selectable by the user to request an adjustment of the visual presentation of the layout; and a request interface coupled to the navigation engine and configured to receive a request according to one or more of the selected navigation options presented by the graphical user interface, the request interface also being configured to communicate the request to the navigation engine, wherein the navigation engine is further configured to effect an adjustment of the visual presentation of the layout in response to the request and according to the request, and wherein the navigation engine is configured to communicate the adjustment to the graphical user interface for presentation to the user.
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8. An apparatus for implementation of a panoptic visualization document navigation system, the apparatus comprising a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to implement at least: a navigation engine configured to receive a layout of document components of a panoptic visualization document collection having a plurality of document components each of which includes respective media content and has associated metadata providing information about the respective document component, the layout including a panoptic arrangement of visual representations of the document components of the layout according to the associated metadata of the respective document components, wherein the navigation engine is configured to select one or more navigation options from a plurality of navigation options for navigating a visual presentation of the layout, the navigation options being selected according to the associated metadata for the document components of the layout, and wherein the navigation engine is configured to communicate the selected navigation options to a graphical user interface for presentation to a user along with the visual presentation of the layout, the selected navigation options thereby being selectable by the user to request an adjustment of the visual presentation of the layout; and a request interface coupled to the navigation engine and configured to receive a request according to one or more of the selected navigation options presented by the graphical user interface, the request interface also being configured to communicate the request to the navigation engine, wherein the navigation engine is further configured to effect an adjustment of the visual presentation of the layout in response to the request and according to the request, and wherein the navigation engine is configured to communicate the adjustment to the graphical user interface for presentation to the user. 12. The apparatus of claim 8 , wherein the navigation engine is configured to effect the adjustment of the visual presentation of the layout including adjustment of the layout.
| 0.944479 |
7,848,947 | 15 | 19 |
15. A computer-implemented performance management apparatus operable in an enterprise comprising individuals organized according to a hierarchy, the apparatus comprising: a user interface allowing a user to define a data dictionary, the data dictionary defining processing of performance management data, wherein the data dictionary comprises one or more data fields, an operator for defining an operation to be applied to performance management data in at least one of the data fields, and wherein each data dictionary field comprises a user-selectable level of the hierarchy to which the data dictionary field is to be applied; an information management function executed on a performance management transaction server to receive performance management data, to apply the received performance management data against the data dictionary, and to create for an employee an individual performance measurement according to the operation at the user-selectable level of the hierarchy.
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15. A computer-implemented performance management apparatus operable in an enterprise comprising individuals organized according to a hierarchy, the apparatus comprising: a user interface allowing a user to define a data dictionary, the data dictionary defining processing of performance management data, wherein the data dictionary comprises one or more data fields, an operator for defining an operation to be applied to performance management data in at least one of the data fields, and wherein each data dictionary field comprises a user-selectable level of the hierarchy to which the data dictionary field is to be applied; an information management function executed on a performance management transaction server to receive performance management data, to apply the received performance management data against the data dictionary, and to create for an employee an individual performance measurement according to the operation at the user-selectable level of the hierarchy. 19. The apparatus of claim 15 wherein the information management function is to generate a report based on a result of applying the received performance data against the data dictionary.
| 0.527919 |
9,703,548 | 19 | 20 |
19. The non-transitory computer readable storage medium as claimed in claim 18 , wherein the project template data comprises project category data representing at least one project category and further comprising instructions for storing, in the database, the project template data in relation to the project category data.
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19. The non-transitory computer readable storage medium as claimed in claim 18 , wherein the project template data comprises project category data representing at least one project category and further comprising instructions for storing, in the database, the project template data in relation to the project category data. 20. The non-transitory computer readable storage medium as claimed in claim 19 , wherein the at least one project category comprises at least one of module, parent project type, project type and sub type categories.
| 0.5 |
7,975,215 | 2 | 6 |
2. The method of claim 1 , further comprising: generating a monochrome annotation mask based on the image; rendering the annotations on the annotation mask; generating the OIC on the annotation mask by copying pixels obscured by the annotations on the image to the annotation mask; and persisting the annotation mask and the OIC data.
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2. The method of claim 1 , further comprising: generating a monochrome annotation mask based on the image; rendering the annotations on the annotation mask; generating the OIC on the annotation mask by copying pixels obscured by the annotations on the image to the annotation mask; and persisting the annotation mask and the OIC data. 6. The method of claim 2 , further comprising: expanding a count of pixels on the annotation mask for capturing OIC from the image.
| 0.811239 |
9,984,484 | 5 | 8 |
5. A system according to claim 1 , wherein the central processing unit generates one such spine group by arranging two or more clusters of documents along a spine based on concepts of the clusters and grafting at least one other spine of clusters to one of the clusters arranged along the spine.
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5. A system according to claim 1 , wherein the central processing unit generates one such spine group by arranging two or more clusters of documents along a spine based on concepts of the clusters and grafting at least one other spine of clusters to one of the clusters arranged along the spine. 8. A system according to claim 5 , wherein the central processing unit places a different spine of clusters having less similarity to the clusters arranged along the spine adjacent one of the clusters arranged along with spine that is most similar to the different spine of clusters.
| 0.5 |
8,460,103 | 9 | 17 |
9. A mobile hand-held device for use in a casino gaming network, comprising: a gaming controller; memory; a first display; at least one interface configured to communicate with at least one other device in the gaming network; a first gesture input interface device configured to detect movements associated with one or more persons; and a first gesture interpretation component configured to identify selected movements detected by the first gesture input interface device, and configured to generate gesture interpretation information relating to interpretation of the selected movements; wherein the hand-held device is configured to: control a wager-based game provided by the hand-held device, determine a current location of the hand-held device, select a hand-held device operating mode from a plurality of operating modes corresponding to different types of gaming activities provided in different locations based on the current location of the hand-held device, detect a first gesture by a first player participating in a first game session with the hand-held device, interpret the first gesture based on the selected operating mode and with respect to a first set of criteria, identify at least one first action to be initiated in response to the first gesture interpretation, initiate the at least one first action, and present a game interface on the first display, wherein the game interface is configured to facilitate interaction with the wager-based game by the first player.
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9. A mobile hand-held device for use in a casino gaming network, comprising: a gaming controller; memory; a first display; at least one interface configured to communicate with at least one other device in the gaming network; a first gesture input interface device configured to detect movements associated with one or more persons; and a first gesture interpretation component configured to identify selected movements detected by the first gesture input interface device, and configured to generate gesture interpretation information relating to interpretation of the selected movements; wherein the hand-held device is configured to: control a wager-based game provided by the hand-held device, determine a current location of the hand-held device, select a hand-held device operating mode from a plurality of operating modes corresponding to different types of gaming activities provided in different locations based on the current location of the hand-held device, detect a first gesture by a first player participating in a first game session with the hand-held device, interpret the first gesture based on the selected operating mode and with respect to a first set of criteria, identify at least one first action to be initiated in response to the first gesture interpretation, initiate the at least one first action, and present a game interface on the first display, wherein the game interface is configured to facilitate interaction with the wager-based game by the first player. 17. The hand-held device of claim 9 , wherein the first game session relates to a casino card game and wherein the at least one first action includes at least one action selected from a group consisting of: initiating dealing of at least one card, initiating discarding of at least one card, initiating collection of at least one card, and initiating selection of at least one card.
| 0.697306 |
8,775,447 | 1 | 14 |
1. A method for processing related datasets, the method including: receiving over an input device or port records from multiple datasets, the records of a given dataset having one or more values for one or more respective fields; and processing records from each of the multiple datasets in a data processing system, the processing including analyzing at least one constraint specification stored in a data storage system to determine a processing order for the multiple datasets, the constraint specification specifying one or more constraints for preserving referential integrity or statistical consistency among a group of related datasets that includes the multiple datasets, applying one or more transformations to records from each of the multiple datasets in the determined processing order, where the transformations are applied to records from a first dataset of the multiple datasets before the transformations are applied to records from a second dataset of the multiple datasets, and the transformations applied to the records from the second dataset are applied based at least in part on results of applying the transformations to the records from the first dataset and at least one constraint between the first dataset and the second dataset specified by the constraint specification, and storing or outputting results of the transformations to the records from each of the multiple datasets.
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1. A method for processing related datasets, the method including: receiving over an input device or port records from multiple datasets, the records of a given dataset having one or more values for one or more respective fields; and processing records from each of the multiple datasets in a data processing system, the processing including analyzing at least one constraint specification stored in a data storage system to determine a processing order for the multiple datasets, the constraint specification specifying one or more constraints for preserving referential integrity or statistical consistency among a group of related datasets that includes the multiple datasets, applying one or more transformations to records from each of the multiple datasets in the determined processing order, where the transformations are applied to records from a first dataset of the multiple datasets before the transformations are applied to records from a second dataset of the multiple datasets, and the transformations applied to the records from the second dataset are applied based at least in part on results of applying the transformations to the records from the first dataset and at least one constraint between the first dataset and the second dataset specified by the constraint specification, and storing or outputting results of the transformations to the records from each of the multiple datasets. 14. The method of claim 1 , wherein the one or more transformations applied to records of a given dataset include a subsetting transformation that reduces a number of records in the given dataset based on values in at least one field of the given dataset.
| 0.894715 |
7,516,198 | 13 | 22 |
13. A method in a network node, the method comprising: receiving by the network node, for transfer between an application server configured for outputting a flow of data packets associated with an application service and a destination device configured for receiving the flow of data packets, a message having XML tags specifying prescribed user-selected quality of service attributes for the application service, the network node distinct from the destination device and the application server; parsing by the network node the XML tags for determining the prescribed user-selected quality of service attributes; selecting network parameters by the network node, based on the network node interpreting the XML tags and the prescribed user-selected quality of service attributes, enabling the flow of data packets to be transferred for the application service according to the user-selected quality of service attributes; and identifying and transferring by the network node the flow of data packets between the application server and toward the destination device according to an open network protocol and the selected network parameters.
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13. A method in a network node, the method comprising: receiving by the network node, for transfer between an application server configured for outputting a flow of data packets associated with an application service and a destination device configured for receiving the flow of data packets, a message having XML tags specifying prescribed user-selected quality of service attributes for the application service, the network node distinct from the destination device and the application server; parsing by the network node the XML tags for determining the prescribed user-selected quality of service attributes; selecting network parameters by the network node, based on the network node interpreting the XML tags and the prescribed user-selected quality of service attributes, enabling the flow of data packets to be transferred for the application service according to the user-selected quality of service attributes; and identifying and transferring by the network node the flow of data packets between the application server and toward the destination device according to an open network protocol and the selected network parameters. 22. The method of claim 13 , wherein the network node is configured as any one of a router of an open protocol network, and or an edge server of a private network.
| 0.855496 |
9,208,440 | 12 | 13 |
12. The method according to claim 11 wherein developing the syntactical model includes representing the events of a hypothetical scenario as independent clauses, each of which has only one verb, and represents an event including sets of entities.
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12. The method according to claim 11 wherein developing the syntactical model includes representing the events of a hypothetical scenario as independent clauses, each of which has only one verb, and represents an event including sets of entities. 13. The method according to claim 12 wherein the entity is performing an action.
| 0.652174 |
8,140,339 | 12 | 13 |
12. The apparatus of claim 1 , wherein said shoulder sensor comprises a first sensor configured to detect twisting of the arm.
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12. The apparatus of claim 1 , wherein said shoulder sensor comprises a first sensor configured to detect twisting of the arm. 13. The apparatus of claim 12 , wherein said first sensor of said shoulder sensor comprises a resistive angular sensor.
| 0.693299 |
7,529,668 | 1 | 10 |
1. A system for performing a speech recognition dictionary refinement procedure, comprising: a database analyzer that identifies first vocabulary words that are present in a training database and identifies second vocabulary words that are not present in said training database, said first vocabulary words and said second vocabulary words being from an initial dictionary; a relevance module that separates first pronunciations of said first vocabulary words into initial short word pronunciations and initial long word pronunciations, said relevance module performing a cumulative threshold procedure upon said initial short word pronunciations to create final short word pronunciations that are used to populate a refined dictionary, said relevance module performing a standardized distance threshold procedure upon said initial long word pronunciations to create final long word pronunciations that are used to populate said refined dictionary; and a consensus module that computes plurality pronunciations for second pronunciations of said second vocabulary words, said consensus module comparing said plurality pronunciations to said second pronunciations to identify final consensus pronunciations that are used to populate said refined dictionary, said consensus module determining whether said plurality pronunciations are validly represented in said second pronunciations.
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1. A system for performing a speech recognition dictionary refinement procedure, comprising: a database analyzer that identifies first vocabulary words that are present in a training database and identifies second vocabulary words that are not present in said training database, said first vocabulary words and said second vocabulary words being from an initial dictionary; a relevance module that separates first pronunciations of said first vocabulary words into initial short word pronunciations and initial long word pronunciations, said relevance module performing a cumulative threshold procedure upon said initial short word pronunciations to create final short word pronunciations that are used to populate a refined dictionary, said relevance module performing a standardized distance threshold procedure upon said initial long word pronunciations to create final long word pronunciations that are used to populate said refined dictionary; and a consensus module that computes plurality pronunciations for second pronunciations of said second vocabulary words, said consensus module comparing said plurality pronunciations to said second pronunciations to identify final consensus pronunciations that are used to populate said refined dictionary, said consensus module determining whether said plurality pronunciations are validly represented in said second pronunciations. 10. The system of claim 1 wherein said relevance module performs said cumulative threshold procedure to retain as said final short word pronunciations only said initial short word pronunciations that cumulatively account for a pre-determined percentage of corresponding pronunciation observations from said training database.
| 0.675649 |
9,130,997 | 1 | 8 |
1. A computer-implemented method comprising: maintaining, in an online system, a set of feature loops, wherein a feature loop comprises an expression capable of being processed by a computer processor to map a set of input values to an output value, the expression evaluating to a value describing one or more entities in the online system, wherein evaluating the feature loop comprises aggregating values of the expression across a plurality of user actions; receiving information describing a modification to the set of feature loops, wherein the modification to the set of feature loops is performed while the online system is executing; responsive to the set of feature loops being modified, evaluating feature loops of the set of modified feature loops for a subsequent user action; and responding to the subsequent user action based on the values of feature loops from the set of modified feature loops.
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1. A computer-implemented method comprising: maintaining, in an online system, a set of feature loops, wherein a feature loop comprises an expression capable of being processed by a computer processor to map a set of input values to an output value, the expression evaluating to a value describing one or more entities in the online system, wherein evaluating the feature loop comprises aggregating values of the expression across a plurality of user actions; receiving information describing a modification to the set of feature loops, wherein the modification to the set of feature loops is performed while the online system is executing; responsive to the set of feature loops being modified, evaluating feature loops of the set of modified feature loops for a subsequent user action; and responding to the subsequent user action based on the values of feature loops from the set of modified feature loops. 8. The computer-implemented method of claim 1 , wherein a feature loop determines a number of users that performed an action of a particular type during a previous time interval.
| 0.850921 |
8,478,792 | 9 | 10 |
9. An information retrieval and communication system comprising: a namespace data store configured to store a plurality of grouping labels, wherein each grouping label is includable by a plurality of publishers in a plurality of content items in a corpus; an index data store configured to store an index identifying, for each of the plurality of grouping labels stored in the namespace data store, each content item, of the plurality of content items, in the corpus that includes said each grouping label of the plurality of grouping labels; and an information server including: a client interface module configured to receive requests from a client computer system for identification of content items related to a first content item, wherein each request including a first grouping label extracted from the first content item; and an index interface module configured to access the index to identify a second content item having the first grouping label extracted from the first content item included therein, wherein the client interface module is further configured to return a reference to the second content item to the client computer system.
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9. An information retrieval and communication system comprising: a namespace data store configured to store a plurality of grouping labels, wherein each grouping label is includable by a plurality of publishers in a plurality of content items in a corpus; an index data store configured to store an index identifying, for each of the plurality of grouping labels stored in the namespace data store, each content item, of the plurality of content items, in the corpus that includes said each grouping label of the plurality of grouping labels; and an information server including: a client interface module configured to receive requests from a client computer system for identification of content items related to a first content item, wherein each request including a first grouping label extracted from the first content item; and an index interface module configured to access the index to identify a second content item having the first grouping label extracted from the first content item included therein, wherein the client interface module is further configured to return a reference to the second content item to the client computer system. 10. The system of claim 9 further comprising: a namespace manager communicably coupled to the namespace data store and configured to provide a namespace interface configured to support searching the plurality of grouping labels, the namespace interface being accessible to the plurality of publishers.
| 0.5 |
8,832,549 | 26 | 35 |
26. A method for analyzing a document that comprises a plurality of primitive elements, the primitive elements are present in the document prior to analysis, the method comprising: identifying a set of potential boundaries as rectilinearly aligned graphical primitive elements that satisfy a set of size constraints; identifying a subset of the potential boundaries as actual boundaries by eliminating from the set (i) potential boundaries identified from the graphical primitive elements that intersect with primitive elements that are not in the set of potential boundaries and (ii) potential boundaries identified from the graphical primitive elements that do not intersect at least two additional potential boundaries; identifying regions bounded by the actual boundaries; and defining a structured document based on the regions and the primitive elements.
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26. A method for analyzing a document that comprises a plurality of primitive elements, the primitive elements are present in the document prior to analysis, the method comprising: identifying a set of potential boundaries as rectilinearly aligned graphical primitive elements that satisfy a set of size constraints; identifying a subset of the potential boundaries as actual boundaries by eliminating from the set (i) potential boundaries identified from the graphical primitive elements that intersect with primitive elements that are not in the set of potential boundaries and (ii) potential boundaries identified from the graphical primitive elements that do not intersect at least two additional potential boundaries; identifying regions bounded by the actual boundaries; and defining a structured document based on the regions and the primitive elements. 35. The method of claim 26 , wherein the document is an unstructured document.
| 0.823529 |
8,099,281 | 20 | 22 |
20. The at least one machine readable memory of claim 17 , wherein the measures of impurity comprise an entropy measure.
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20. The at least one machine readable memory of claim 17 , wherein the measures of impurity comprise an entropy measure. 22. The at least one machine readable memory of claim 20 , wherein the entropy measure comprises a Gini entropy.
| 0.513043 |
8,601,367 | 7 | 12 |
7. A processor-based method, comprising: receiving, by a processor, at least one of numerical and textual input from at least one of: a user input device, a data file containing spreadsheet based data, and a data file containing word processor based data; generating, by the processor, a first human readable document including numerical and textual data; generating an XBRL representation of the first document; generating a second human readable document based on the first document including a subset of the numerical and textual data from the first document and an interpretive context determined by performing the following operations: retrieving fact details for a navkey that references an XBRL fact; retrieving one or more extended links associated with the selected XBRL fact; and receiving a user-selection of one or more extended links that are associated with the navkey; generating an XBRL representation of the second document; generating an HTML representation of at least one of the first and second documents when a user selectable option is selected; storing first and second source files associated with the respective first and second documents; automatically validating, by the processor, the XBRL representations of the first and second documents; providing access to at least one of the first and second documents over the internet; and generating a reference locator to be used to access the at least one of the first and second documents, wherein the reference locator can comprise a URL or a QR code.
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7. A processor-based method, comprising: receiving, by a processor, at least one of numerical and textual input from at least one of: a user input device, a data file containing spreadsheet based data, and a data file containing word processor based data; generating, by the processor, a first human readable document including numerical and textual data; generating an XBRL representation of the first document; generating a second human readable document based on the first document including a subset of the numerical and textual data from the first document and an interpretive context determined by performing the following operations: retrieving fact details for a navkey that references an XBRL fact; retrieving one or more extended links associated with the selected XBRL fact; and receiving a user-selection of one or more extended links that are associated with the navkey; generating an XBRL representation of the second document; generating an HTML representation of at least one of the first and second documents when a user selectable option is selected; storing first and second source files associated with the respective first and second documents; automatically validating, by the processor, the XBRL representations of the first and second documents; providing access to at least one of the first and second documents over the internet; and generating a reference locator to be used to access the at least one of the first and second documents, wherein the reference locator can comprise a URL or a QR code. 12. The method of claim 7 , further comprising: generating the XBRL representation of the second document based on at least one of: a technical minimum scope, and a logical minimum scope, wherein the technical minimum scope refers to the minimum amount of information needed for presentation of the selected data only, and the logical minimum scope refers to the minimum amount of information needed for presentation of the selected data in user-selected interpretive context(s).
| 0.685283 |
8,224,839 | 1 | 5 |
1. A method comprising: at a computer device: retrieving a set of queries related to a search query from a query repository, wherein the search query includes one or more search words provided to the computer device by a user, and wherein at least one search word of the one or more search words is included in each query in the set of queries; generating a set of context word based on one or more computer-readable files retrieved from the computer device; calculating an intersection of the set of queries and the set of context words; and creating an extended search query of the search query and the calculated intersection; displaying the calculated intersection, wherein the calculated intersection includes a plurality of intersection words; and receiving a user selection of at least one of the plurality of intersection words, wherein the extended search query is created by adding the at least one user selected intersection word to the search query.
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1. A method comprising: at a computer device: retrieving a set of queries related to a search query from a query repository, wherein the search query includes one or more search words provided to the computer device by a user, and wherein at least one search word of the one or more search words is included in each query in the set of queries; generating a set of context word based on one or more computer-readable files retrieved from the computer device; calculating an intersection of the set of queries and the set of context words; and creating an extended search query of the search query and the calculated intersection; displaying the calculated intersection, wherein the calculated intersection includes a plurality of intersection words; and receiving a user selection of at least one of the plurality of intersection words, wherein the extended search query is created by adding the at least one user selected intersection word to the search query. 5. The method of claim 1 , wherein the query repository includes a query log associated with a search engine, wherein the search engine is remote from the computer device, and wherein the computer-readable files include user information and are stored locally within the computer device.
| 0.520067 |
8,938,512 | 1 | 3 |
1. A method comprising: identifying a creating user of a social networking system; accessing a user profile in the social networking system including information about the creating user; identifying a set of users associated with the creating user in the social networking system; accessing user profiles associated with each user in the set of users by the social networking system; identifying, based on the user profile in the social networking system and the user profiles associated with each user in the set of users, one or more common characteristics between the creating user and at least one user in the set of users; selecting a common characteristic from the one or more common characteristics between the creating user and at least one user in the set of users; generating, by a processor, a group recommendation based on the selected common characteristic, the group recommendation for a social networking system group to be created by the creating user; and presenting the group recommendation to the creating user.
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1. A method comprising: identifying a creating user of a social networking system; accessing a user profile in the social networking system including information about the creating user; identifying a set of users associated with the creating user in the social networking system; accessing user profiles associated with each user in the set of users by the social networking system; identifying, based on the user profile in the social networking system and the user profiles associated with each user in the set of users, one or more common characteristics between the creating user and at least one user in the set of users; selecting a common characteristic from the one or more common characteristics between the creating user and at least one user in the set of users; generating, by a processor, a group recommendation based on the selected common characteristic, the group recommendation for a social networking system group to be created by the creating user; and presenting the group recommendation to the creating user. 3. The method of claim 1 , wherein selecting the common characteristic from the one or more common characteristics between the creating user and at least one user in the set of users comprises: identifying a priority associated with each of the one or more common characteristics; ranking the one or more common characteristics based on the priorities; and selecting the common characteristics based on the ranking.
| 0.543956 |
8,209,352 | 22 | 23 |
22. A computer program product that includes a non-transitory computer readable storage medium, the non-transitory computer readable storage medium comprising a plurality of computer instructions which, when executed by a processor, cause the processor to execute a process for storing XML data from an XML document into a relational database, the process comprising: identifying a document identifier for an XML document, wherein the XML document comprises a plurality of nodes; analyzing the XML document to identify a node; and for the identified node in the XML document, storing path information for the node in a volatile or non-volatile computer usable storage medium, where the path string comprises a full path for the node from a root node of the XML document.
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22. A computer program product that includes a non-transitory computer readable storage medium, the non-transitory computer readable storage medium comprising a plurality of computer instructions which, when executed by a processor, cause the processor to execute a process for storing XML data from an XML document into a relational database, the process comprising: identifying a document identifier for an XML document, wherein the XML document comprises a plurality of nodes; analyzing the XML document to identify a node; and for the identified node in the XML document, storing path information for the node in a volatile or non-volatile computer usable storage medium, where the path string comprises a full path for the node from a root node of the XML document. 23. The computer program product of claim 22 in which hierarchical information is stored in volatile or non-volatile computer usable storage medium, where the hierarchical information comprises a hierarchical level within the XML document.
| 0.5 |
9,195,769 | 1 | 2 |
1. A computer-implemented method for evaluation of an entity by a target user based at least on stored data about the target user, wherein the entity is an entity of a set of entities, and evaluation is related to the entity, the method comprising: receiving, at a server computer, entity data relating to a particular entity, wherein the entity data includes a relevance based on a rating and a weight based on a relationship with the target user for a particular user that provided the entity data through a particular data source; determining, by the server computer, a set of entity evaluations to request from the target user based on the weight and the relevance; from the set of entity evaluations to request, generating, at the server computer, a set of predicted entity evaluations for one or more entities relevant to the target user based on the entity data, user data, and relevance; determining an order of relevance of the relevant entities based at least in part on the relevance and the weight to increase accuracy of the predicted entity evaluations; and communicating, from the server computer to the target user, the order of relevance of the one or more relevant entities; after communicating the order of relevance, receiving, from a user device, evaluation data from the target user that is based on an evaluation received through input via the user device; in response to receiving the evaluation data, increasing the accuracy of the predicted entity evaluations by computing a similarity among the target user and the particular user.
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1. A computer-implemented method for evaluation of an entity by a target user based at least on stored data about the target user, wherein the entity is an entity of a set of entities, and evaluation is related to the entity, the method comprising: receiving, at a server computer, entity data relating to a particular entity, wherein the entity data includes a relevance based on a rating and a weight based on a relationship with the target user for a particular user that provided the entity data through a particular data source; determining, by the server computer, a set of entity evaluations to request from the target user based on the weight and the relevance; from the set of entity evaluations to request, generating, at the server computer, a set of predicted entity evaluations for one or more entities relevant to the target user based on the entity data, user data, and relevance; determining an order of relevance of the relevant entities based at least in part on the relevance and the weight to increase accuracy of the predicted entity evaluations; and communicating, from the server computer to the target user, the order of relevance of the one or more relevant entities; after communicating the order of relevance, receiving, from a user device, evaluation data from the target user that is based on an evaluation received through input via the user device; in response to receiving the evaluation data, increasing the accuracy of the predicted entity evaluations by computing a similarity among the target user and the particular user. 2. The method of claim 1 , further comprising: obtaining, at the server computer, personal data from the one or more of data sources, wherein the personal data is associated with the target user in a plurality of users; storing the personal data at the server computer, wherein personal data associated with the plurality of users is stored in a user database; merging, by the server computer, the personal data from the plurality of data sources; mapping, by the server computer, the personal data from the plurality of data sources to the target user; updating the user database with the personal data and stored data associated with the target user; determining, at the server computer, whether an entity is associated with the personal data from the target user; wherein the order of relevance of the set of entity evaluations to request is based at least in part on the personal data from the target user.
| 0.591562 |
8,751,498 | 1 | 12 |
1. A method for identifying documents referring to an entity, the entity being associated with a first set of features, the method comprising: at a computer having one or more processors and memory storing programs for execution by the one or more processors: identifying a first set of documents based on a first model and the first set of features, wherein the first model includes a first set of rules specifying at least one combination of features from the first set of features that are sufficient for identifying a document referring to the entity, and each document in the first set of documents includes a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the first model; determining a second model based on features included in one or more documents in the first set of documents, wherein the second model includes a second set of rules specifying at least one combination of features from the first set of documents that are sufficient for identifying a document referring to the entity; identifying a second set of documents based on the second model, wherein each document in the second set of documents includes a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the second model, and wherein the second set of documents includes at least one document not included in the first set of documents; and extracting one or more facts from the second set of documents and associating the extracted facts with the entity.
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1. A method for identifying documents referring to an entity, the entity being associated with a first set of features, the method comprising: at a computer having one or more processors and memory storing programs for execution by the one or more processors: identifying a first set of documents based on a first model and the first set of features, wherein the first model includes a first set of rules specifying at least one combination of features from the first set of features that are sufficient for identifying a document referring to the entity, and each document in the first set of documents includes a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the first model; determining a second model based on features included in one or more documents in the first set of documents, wherein the second model includes a second set of rules specifying at least one combination of features from the first set of documents that are sufficient for identifying a document referring to the entity; identifying a second set of documents based on the second model, wherein each document in the second set of documents includes a sufficient number of features in common with the first set of features to identify a document referring to the entity according to the second model, and wherein the second set of documents includes at least one document not included in the first set of documents; and extracting one or more facts from the second set of documents and associating the extracted facts with the entity. 12. The method of claim 1 , further comprising: associating at least one of the documents of the second set of documents with the entity.
| 0.883305 |
10,134,385 | 1 | 2 |
1. A method comprising: at one or more processors: receiving a name; mapping the name to one or more sets of monosyllabic components that represent alternative phonetic pronunciations for at least a portion of the name, wherein monosyllabic components from the one or more sets of monosyllabic components are combinable to construct a phonetic pronunciation of the name; displaying the one or more sets of monosyllabic components; receiving a user selection of a monosyllabic component from each of the one or more sets of monosyllabic components; and combining the selected monosyllabic component from each of the one or more sets of monosyllabic components to construct the phonetic pronunciation of the name; wherein displaying the one or more sets of monosyllabic components comprises displaying a first portion of the one or more sets of monosyllabic components via a user interface, and further displaying a second portion of the one or more sets of monosyllabic components in response to a user selection of one of the first portion of the one or more sets of monosyllabic components.
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1. A method comprising: at one or more processors: receiving a name; mapping the name to one or more sets of monosyllabic components that represent alternative phonetic pronunciations for at least a portion of the name, wherein monosyllabic components from the one or more sets of monosyllabic components are combinable to construct a phonetic pronunciation of the name; displaying the one or more sets of monosyllabic components; receiving a user selection of a monosyllabic component from each of the one or more sets of monosyllabic components; and combining the selected monosyllabic component from each of the one or more sets of monosyllabic components to construct the phonetic pronunciation of the name; wherein displaying the one or more sets of monosyllabic components comprises displaying a first portion of the one or more sets of monosyllabic components via a user interface, and further displaying a second portion of the one or more sets of monosyllabic components in response to a user selection of one of the first portion of the one or more sets of monosyllabic components. 2. The method of claim 1 comprising outputting the phonetic pronunciation via a user interface.
| 0.660714 |
9,378,647 | 15 | 20 |
15. A method for automatically deconstructing an educational course into discrete learning units, the method comprising: analyzing content related to an educational course stored by an education platform; extracting distinct concepts from the content; identifying passive, active, and recall user activities associated with respective distinct concepts, by: extracting a time duration for each passive, active, and recall activity from users activity logs, normalizing the extracted time durations across users, and reporting the normalized extracted time durations; generating a plurality of learning units, each learning unit comprising a distinct concept and the passive, active, and recall user activities associated with the distinct concept; and delivering at least one discrete learning unit to a registered user through the education platform.
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15. A method for automatically deconstructing an educational course into discrete learning units, the method comprising: analyzing content related to an educational course stored by an education platform; extracting distinct concepts from the content; identifying passive, active, and recall user activities associated with respective distinct concepts, by: extracting a time duration for each passive, active, and recall activity from users activity logs, normalizing the extracted time durations across users, and reporting the normalized extracted time durations; generating a plurality of learning units, each learning unit comprising a distinct concept and the passive, active, and recall user activities associated with the distinct concept; and delivering at least one discrete learning unit to a registered user through the education platform. 20. The method of claim 15 , wherein identifying passive, active, and recall activities associated with respective distinct concepts comprises: extracting a time at which passive, active, and recall activities are performed by a plurality of users from users activity logs; normalizing the extracted times by school; and reporting the normalized extracted times.
| 0.522427 |
8,886,522 | 14 | 15 |
14. A computer-implemented method as in claim 10 , further comprising instructions for: establishing a third level in said hierarchical structure, said third level having a third decision node, said third level being a further simplified pattern of said second level to capture triplets that are not identical to said at least one extracted triplet, said third decision node having a different level of detail than said first and second decision nodes; and as a result of said extracted textual clause failing to match said second level, extracting said at least one triplet from said extracted textual clause by attempting to match said extracted textual clause to said third level; identifying extraction of said at least one triplet as true if said extracted textual clause matches said third level; and identifying extraction of said at least one et as false if said extracted textual clause fails to match said third level.
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14. A computer-implemented method as in claim 10 , further comprising instructions for: establishing a third level in said hierarchical structure, said third level having a third decision node, said third level being a further simplified pattern of said second level to capture triplets that are not identical to said at least one extracted triplet, said third decision node having a different level of detail than said first and second decision nodes; and as a result of said extracted textual clause failing to match said second level, extracting said at least one triplet from said extracted textual clause by attempting to match said extracted textual clause to said third level; identifying extraction of said at least one triplet as true if said extracted textual clause matches said third level; and identifying extraction of said at least one et as false if said extracted textual clause fails to match said third level. 15. A computer-implemented method as in claim 14 , further comprising: said further simplified pattern of said third level automatically created by grouping analogous interaction words with said interaction word to permit extraction of non-annotated data not containing said interaction word but containing one of said analogous interaction words.
| 0.5 |
9,967,380 | 22 | 24 |
22. A communication system comprising: a hard of hearing user's captioned device, the captioned device including a display screen and a processor, the processor in the captioned device configured to: establish communication with a hard of hearing user's phone device that is independent of the hard of hearing user's captioned device; receive a text communication originating at a relay, the text communication corresponding to a transcription of a hearing user's voice signal; and display a text caption corresponding to the text communication on the display of the hard of hearing user's captioned device; wherein at least one of the captioned device and the hard of hearing user's phone device is configured to establish a first communication link directly with the relay for routing the hearing user's voice signal to the relay; and wherein the captioned device receives the text communication from the relay on a second communication link that is independent of the first communication link.
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22. A communication system comprising: a hard of hearing user's captioned device, the captioned device including a display screen and a processor, the processor in the captioned device configured to: establish communication with a hard of hearing user's phone device that is independent of the hard of hearing user's captioned device; receive a text communication originating at a relay, the text communication corresponding to a transcription of a hearing user's voice signal; and display a text caption corresponding to the text communication on the display of the hard of hearing user's captioned device; wherein at least one of the captioned device and the hard of hearing user's phone device is configured to establish a first communication link directly with the relay for routing the hearing user's voice signal to the relay; and wherein the captioned device receives the text communication from the relay on a second communication link that is independent of the first communication link. 24. The communication system of claim 22 wherein the captioned device receives the text communication directly via the second communication link without passing through the hard of hearing user's phone device.
| 0.5 |
8,984,398 | 1 | 5 |
1. A method comprising: extracting, by a computing platform comprising one or more processors, a group of two or more sentences of an electronic document; segmenting individual sentences of said of said two or more sentences into a first phrase and at least a second phrase, said first phrase comprising at least one word not contained within said at least a second phrase; determining two or more paths between phrases of said individual sentences, individual paths of said two or more paths comprising no more than one phrase from individual ones of said individual sentences; at least partially in response to receiving a search query, determining respective scores for said individual paths based at least in part on a utility metric and a ranking of said two or more sentences with respect to said search query; generating an abstract of said electronic document, said abstract comprising individual ones of said phrases associated with a first path of said two or more paths, said first path being associated with a highest of said respective scores, wherein a first phrase of said phrases associated with said first path is different from a second phrase of said phrases associated with said first path; and transmitting one or more search results comprising at least said abstract to a user at least partially in response to receiving said search query from said user.
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1. A method comprising: extracting, by a computing platform comprising one or more processors, a group of two or more sentences of an electronic document; segmenting individual sentences of said of said two or more sentences into a first phrase and at least a second phrase, said first phrase comprising at least one word not contained within said at least a second phrase; determining two or more paths between phrases of said individual sentences, individual paths of said two or more paths comprising no more than one phrase from individual ones of said individual sentences; at least partially in response to receiving a search query, determining respective scores for said individual paths based at least in part on a utility metric and a ranking of said two or more sentences with respect to said search query; generating an abstract of said electronic document, said abstract comprising individual ones of said phrases associated with a first path of said two or more paths, said first path being associated with a highest of said respective scores, wherein a first phrase of said phrases associated with said first path is different from a second phrase of said phrases associated with said first path; and transmitting one or more search results comprising at least said abstract to a user at least partially in response to receiving said search query from said user. 5. The method of claim 1 , wherein said utility metric comprises at least one of a measure of readability of a given phrase, a measure of relevance of a given phrase with respect to a given query, a measure of relevance of a given phrase with respect to said electronic document, or a measure of length of a given phrase.
| 0.768398 |
7,707,023 | 1 | 5 |
1. A method of automatically finding one or more answers to a natural language question in a computer stored natural language text database, wherein said natural language text database has been analyzed with respect to syntactic functions of constituents, lexical meaning of word tokens, and initial clause boundaries, and wherein said natural language question comprises a question clause, comprising the steps of: analyzing, in an analyzing means of a computer system, a computer readable representation of said question clause with respect to syntactic functions of its constituents and the lexical meaning of its word tokens; defining, in a defining means of a computer system, in response to the analysis step, a set of conditions for an initial clause in said natural language text database to constitute an answer to said question clause, said conditions comprising a condition stipulating that, for an initial clause in said natural language text database to constitute an answer to said questions clause, at least one of the constituents of said question clause should have a corresponding constituent in said initial clause having the same syntactic function and an equivalent lexical meaning; identifying, in an answer finding means of a computer system, initial clauses in said natural language text database that satisfy said conditions; and returning, in an answer finding means of a computer system, answers to said question clause by means of the identified initial clauses that match said conditions.
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1. A method of automatically finding one or more answers to a natural language question in a computer stored natural language text database, wherein said natural language text database has been analyzed with respect to syntactic functions of constituents, lexical meaning of word tokens, and initial clause boundaries, and wherein said natural language question comprises a question clause, comprising the steps of: analyzing, in an analyzing means of a computer system, a computer readable representation of said question clause with respect to syntactic functions of its constituents and the lexical meaning of its word tokens; defining, in a defining means of a computer system, in response to the analysis step, a set of conditions for an initial clause in said natural language text database to constitute an answer to said question clause, said conditions comprising a condition stipulating that, for an initial clause in said natural language text database to constitute an answer to said questions clause, at least one of the constituents of said question clause should have a corresponding constituent in said initial clause having the same syntactic function and an equivalent lexical meaning; identifying, in an answer finding means of a computer system, initial clauses in said natural language text database that satisfy said conditions; and returning, in an answer finding means of a computer system, answers to said question clause by means of the identified initial clauses that match said conditions. 5. The method according to claim 1 , wherein said set of conditions in the defining step comprises: a manner adverb condition stipulating that a clause constitutes an answer to said question clause if a lexically headed constituent having the syntactic function of manner adverb of said question clause has a corresponding lexically headed constituent in said clause having the syntactic function of manner adverb and having an equivalent lexical meaning.
| 0.5 |
9,258,373 | 1 | 6 |
1. A method for generating a geofeed based on one or more altitude parameters, the method being implemented in a computer that includes one or more processors configured to execute one or more computer program modules, the method comprising: obtaining, by a geofeed creation module, content associated with the geofeed, the content aggregated from a plurality of content providers based on one or more geographically definable locations, the content being provided by the plurality of content providers based on respective requests formatted specifically for individual ones of the plurality of content providers, wherein the respective requests comprise the one or more geographically definable locations; identifying, by an altitude module, the one or more altitude parameters; determining, by the altitude module, one or more altitude attributes related to the content; filtering, by the altitude module, in or out the content based on the one or more altitude parameters and the one or more altitude attributes related to the content; and communicating, by a communication module, the geofeed comprising the filtered content.
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1. A method for generating a geofeed based on one or more altitude parameters, the method being implemented in a computer that includes one or more processors configured to execute one or more computer program modules, the method comprising: obtaining, by a geofeed creation module, content associated with the geofeed, the content aggregated from a plurality of content providers based on one or more geographically definable locations, the content being provided by the plurality of content providers based on respective requests formatted specifically for individual ones of the plurality of content providers, wherein the respective requests comprise the one or more geographically definable locations; identifying, by an altitude module, the one or more altitude parameters; determining, by the altitude module, one or more altitude attributes related to the content; filtering, by the altitude module, in or out the content based on the one or more altitude parameters and the one or more altitude attributes related to the content; and communicating, by a communication module, the geofeed comprising the filtered content. 6. The method of claim 1 , wherein the one or more altitude attributes related to the content are determined by the altitude module.
| 0.5 |
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