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8,874,540 | 15 | 16 | 15. A method of semantically classifying a data set of numeric values contained in a data source having at least one non-numeric data set comprising: loading, by a processing device, a non-numeric data set comprising one or more non-numeric values; processing, by the processing device, the non-numeric data set to determine one or more classifications of the non-numeric data set; extracting, by the processing device, the numeric data set; querying, by the processing device, at least on EKB to determine if the one or more classifications and at least one numeric value of the numeric data set are known to the EKB and, if so, querying, by the processing device, the EKB for all data relating to the numeric values of the numeric data set; receiving, by the processing device, from the EKB at least a property and a value associated with each numeric value of the numeric data set; and determining, by the processing device at least one classification for the numeric data set based on at least a property received from the EKB. | 15. A method of semantically classifying a data set of numeric values contained in a data source having at least one non-numeric data set comprising: loading, by a processing device, a non-numeric data set comprising one or more non-numeric values; processing, by the processing device, the non-numeric data set to determine one or more classifications of the non-numeric data set; extracting, by the processing device, the numeric data set; querying, by the processing device, at least on EKB to determine if the one or more classifications and at least one numeric value of the numeric data set are known to the EKB and, if so, querying, by the processing device, the EKB for all data relating to the numeric values of the numeric data set; receiving, by the processing device, from the EKB at least a property and a value associated with each numeric value of the numeric data set; and determining, by the processing device at least one classification for the numeric data set based on at least a property received from the EKB. 16. The method of claim 15 , further comprising applying an acceptable tolerance in which to consider a value of the EKB to match a numeric value of the numerical value set. | 0.75 |
7,860,877 | 10 | 13 | 10. A computer implemented method to query data modeled by an XML schema, comprising the following steps: using at least one XML data schema describing contents of data to be queried, wherein a collection of data from multiple different databases that are not homogeneous is populated with instances of the at least one XML data schema, wherein the XML data schema is used to generate a query form user interface, wherein the query form user interface comprises an input portion and an output portion; generating query statements in XML Query Language through the use of at least one generator in response to user interaction with the input portion; and invoking from a query assembler to the generator to assemble and submit query requests received at the input portion to the multiple different databases for the execution of the specified query upon the collection of data, wherein a response to the query requests is displayed on the output portion; wherein the input portion of the query form comprises query form controls that are mapped to the XML data schema; wherein a first query form control comprises an instance of a control schema defined by an XML Schema Definition Language file and maps to a specific element of the XML data schema and identifies one or more subquery generators. | 10. A computer implemented method to query data modeled by an XML schema, comprising the following steps: using at least one XML data schema describing contents of data to be queried, wherein a collection of data from multiple different databases that are not homogeneous is populated with instances of the at least one XML data schema, wherein the XML data schema is used to generate a query form user interface, wherein the query form user interface comprises an input portion and an output portion; generating query statements in XML Query Language through the use of at least one generator in response to user interaction with the input portion; and invoking from a query assembler to the generator to assemble and submit query requests received at the input portion to the multiple different databases for the execution of the specified query upon the collection of data, wherein a response to the query requests is displayed on the output portion; wherein the input portion of the query form comprises query form controls that are mapped to the XML data schema; wherein a first query form control comprises an instance of a control schema defined by an XML Schema Definition Language file and maps to a specific element of the XML data schema and identifies one or more subquery generators. 13. The method of claim 10 , wherein a run-time engine includes the query assembler and a rendering engine. | 0.70442 |
9,293,134 | 5 | 11 | 5. One or more non-transitory computer-readable media maintaining instructions executable by one or more processors to perform acts comprising: receiving a first audio signal from a first device, wherein the first audio signal contains first user speech, wherein the first audio signal is captured by one or more microphones of the first device; receiving a second audio signal from the first device, wherein the second audio signal contains second user speech, the second audio signal is captured by one or more microphones of a second device, and the second audio signal is provided by the second device to the first device; performing automatic speech recognition (ASR) on the first audio signal using a first ASR model to recognize the first user speech; and performing ASR on the second audio signal using a second ASR model to recognize the second user speech, wherein the second ASR model is different from the first ASR model. | 5. One or more non-transitory computer-readable media maintaining instructions executable by one or more processors to perform acts comprising: receiving a first audio signal from a first device, wherein the first audio signal contains first user speech, wherein the first audio signal is captured by one or more microphones of the first device; receiving a second audio signal from the first device, wherein the second audio signal contains second user speech, the second audio signal is captured by one or more microphones of a second device, and the second audio signal is provided by the second device to the first device; performing automatic speech recognition (ASR) on the first audio signal using a first ASR model to recognize the first user speech; and performing ASR on the second audio signal using a second ASR model to recognize the second user speech, wherein the second ASR model is different from the first ASR model. 11. The one or more non-transitory computer-readable media of claim 5 , the acts further comprising: generating first responsive speech in response to the first user speech using a first text-to-speech (TTS) model; generating second responsive speech in response to the second user speech using a second text-to-speech (TTS) model; wherein the second TTS model is different from the first TTS model. | 0.5 |
9,424,823 | 1 | 14 | 1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule. | 1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule. 14. The method according to claim 1 , wherein detecting handwritten music notations comprises: detecting said handwritten music symbols which are inputted by a user on an input surface of said music symbol recognition apparatus. | 0.727273 |
8,554,701 | 12 | 13 | 12. The system of claim 6 , wherein determining sentiment scores for the terms in the list of terms comprises determining a positive sentiment score, a negative sentiment score, a mixed sentiment score, and a neutral sentiment score for each term in the list of terms utilizing a machine learning technique based on the plurality of labeled sentences. | 12. The system of claim 6 , wherein determining sentiment scores for the terms in the list of terms comprises determining a positive sentiment score, a negative sentiment score, a mixed sentiment score, and a neutral sentiment score for each term in the list of terms utilizing a machine learning technique based on the plurality of labeled sentences. 13. The system of claim 12 , wherein the machine learning technique comprises applying one or more logistic regression classifiers to the sentence having coefficients comprising the positive sentiment scores, negative sentiment scores, mixed sentiment scores, and neutral sentiment scores determined for the terms in the list of terms. | 0.5 |
9,836,552 | 4 | 5 | 4. The computer readable storage medium of claim 3 , wherein the presenting the shared terms comprises displaying each of the shared terms as a tag in a shared-tag tag cloud in addition to the multiple tag clouds. | 4. The computer readable storage medium of claim 3 , wherein the presenting the shared terms comprises displaying each of the shared terms as a tag in a shared-tag tag cloud in addition to the multiple tag clouds. 5. The computer readable storage medium of claim 4 , wherein the tag in the shared-tag tag cloud further displays one or more attributes associated with the tag. | 0.5 |
8,156,430 | 12 | 13 | 12. A method according to claim 8 , further comprising: assigning a primary status to those clusters that are larger than a minimum size; assigning a secondary status to the clusters that are smaller than the minimum size; and presenting the primary and secondary clusters. | 12. A method according to claim 8 , further comprising: assigning a primary status to those clusters that are larger than a minimum size; assigning a secondary status to the clusters that are smaller than the minimum size; and presenting the primary and secondary clusters. 13. A method according to claim 12 , wherein the minimum size is determined by one of a predetermined number of the messages in one such primary cluster and a function of a number of the messages in the tree structure. | 0.5 |
8,321,446 | 1 | 7 | 1. A computer-implemented method, comprising: receiving a search query for a particular application from an input field of a user interface; performing a keyword search based on the search query to generate keyword search results; performing a natural language search of a frequently-asked question database based on the search query to generate frequently-asked question search results; and outputting a first display page, wherein the first display page categorizes the keyword search results and the frequently-asked question search results into a plurality of categories, wherein each category of the first display page is associated with a category title, a first display region, and a second display region that is separate from the first display region, wherein the first display region of a particular category includes one or more keyword search results associated with the particular category and does not include any of the frequently-asked question search results, and wherein the second display region associated with the particular category includes one or more frequently-asked question search results associated with the particular category and does not include any of the keyword search results; wherein a statistical cluster analysis is performed to determine the plurality of categories for the particular application based on group assignments and name assignments. | 1. A computer-implemented method, comprising: receiving a search query for a particular application from an input field of a user interface; performing a keyword search based on the search query to generate keyword search results; performing a natural language search of a frequently-asked question database based on the search query to generate frequently-asked question search results; and outputting a first display page, wherein the first display page categorizes the keyword search results and the frequently-asked question search results into a plurality of categories, wherein each category of the first display page is associated with a category title, a first display region, and a second display region that is separate from the first display region, wherein the first display region of a particular category includes one or more keyword search results associated with the particular category and does not include any of the frequently-asked question search results, and wherein the second display region associated with the particular category includes one or more frequently-asked question search results associated with the particular category and does not include any of the keyword search results; wherein a statistical cluster analysis is performed to determine the plurality of categories for the particular application based on group assignments and name assignments. 7. The computer-implemented method of claim 1 , wherein the first display page includes a second user interface that enables refinement of the search query. | 0.762918 |
10,124,203 | 1 | 10 | 1. A student desk configured to incorporate brain-based movement into learning activities comprising: a frame comprising a table support including leg member portions extending upwardly from a front portion of the frame and a non-rotating seat support extending upwardly from a rear portion of the frame; a rotatable seat carried by the seat support and configured to rotate about the non-rotating seat support from a resting position to a first ending position in a first direction and from a resting position to a second ending position in a second direction; a table carried by the table support, the table having a substantially flat and smooth top face, a bottom face, and a near edge proximate to the seat; a sensory relief disposed a surface of the table other than the top face, the sensory relief comprising at least one face having at least one tactilely discernable feature accessible by a user of the student desk; a swinging footrest rotatably mounted between the leg member portions of the frame; a torsion spring having a pair of legs; a pair of barriers disposed on the seat support and associated with the torsion spring, each barrier configured to remain stationary while the seat rotates and to prevent one leg of the torsion spring from traveling in one direction from the resting position; and a pair of projections extending from the seat and operatively engaging one leg of the torsion spring, each projection moving with the seat as the seat rotates, the torsion spring opposing rotation of the seat by applying a force to the projection via the associated leg. | 1. A student desk configured to incorporate brain-based movement into learning activities comprising: a frame comprising a table support including leg member portions extending upwardly from a front portion of the frame and a non-rotating seat support extending upwardly from a rear portion of the frame; a rotatable seat carried by the seat support and configured to rotate about the non-rotating seat support from a resting position to a first ending position in a first direction and from a resting position to a second ending position in a second direction; a table carried by the table support, the table having a substantially flat and smooth top face, a bottom face, and a near edge proximate to the seat; a sensory relief disposed a surface of the table other than the top face, the sensory relief comprising at least one face having at least one tactilely discernable feature accessible by a user of the student desk; a swinging footrest rotatably mounted between the leg member portions of the frame; a torsion spring having a pair of legs; a pair of barriers disposed on the seat support and associated with the torsion spring, each barrier configured to remain stationary while the seat rotates and to prevent one leg of the torsion spring from traveling in one direction from the resting position; and a pair of projections extending from the seat and operatively engaging one leg of the torsion spring, each projection moving with the seat as the seat rotates, the torsion spring opposing rotation of the seat by applying a force to the projection via the associated leg. 10. The student desk of claim 1 wherein the first ending position and the second ending position have a maximum angular displacement of about 90° from the resting position. | 0.843636 |
8,069,185 | 1 | 3 | 1. A method of generating a concept dictionary for use in querying an information system comprising: (i) receiving an information search criterion; (ii) deriving from said received search criterion, using a lexical reference source, at least one different search criterion having related meaning to said received search criterion; (iii) identifying a set of information in said information system relevant to said received search criterion and a different set of information in said information system relevant to said at least one derived search criterion; (iv) analyzing the identified sets of information and deriving from similarities and differences therebetween relationships between said received search criterion and said at least one derived search criterion in the context of said information system; and (v) storing, in a concept dictionary, information relating to said received and said at least one derived search criterion and to respective said derived relationships therebetween, for use in querying said information system. | 1. A method of generating a concept dictionary for use in querying an information system comprising: (i) receiving an information search criterion; (ii) deriving from said received search criterion, using a lexical reference source, at least one different search criterion having related meaning to said received search criterion; (iii) identifying a set of information in said information system relevant to said received search criterion and a different set of information in said information system relevant to said at least one derived search criterion; (iv) analyzing the identified sets of information and deriving from similarities and differences therebetween relationships between said received search criterion and said at least one derived search criterion in the context of said information system; and (v) storing, in a concept dictionary, information relating to said received and said at least one derived search criterion and to respective said derived relationships therebetween, for use in querying said information system. 3. A method as in claim 1 , wherein, at step (ii), deriving at least one search criterion having related meaning comprises replacing a term of said received search criterion with a related term having a more specific meaning according to said lexical reference source. | 0.82732 |
10,146,755 | 19 | 20 | 19. The system as recited in claim 15 , wherein the program instructions of the computer program further comprise: receiving one or more identifiers to identify said one or more designated primary objects. | 19. The system as recited in claim 15 , wherein the program instructions of the computer program further comprise: receiving one or more identifiers to identify said one or more designated primary objects. 20. The system as recited in claim 19 , wherein the program instructions of the computer program further comprise: assigning said score for each of said one or more designated primary objects based on closeness in location of said each identified term to said one or more identifiers used to identify each of said one or more designated primary objects in said document. | 0.5 |
7,865,820 | 16 | 17 | 16. A computer program product tangibly embodied in a machine-readable storage device, the computer program product including instructions that, when executed, generate on a display device a graphical user interface for identifying a substitute relating to a business document model, the graphical user interface comprising: a modeling area configured to present multiple components of a business document model, the business document model comprising a semantic model used in generating one or more documents to be exchanged in electronic communication, and the multiple components comprising nodes and edges that represent semantics of a business document, the edges connecting nodes; and a substitution candidate area for presenting at least one substitute component such that a user can replace an indicated one of the multiple components in the business document model with the substitute component, the at least one substitute component being identified in a repository of preexisting business document models and using a graph structure of the business document model. | 16. A computer program product tangibly embodied in a machine-readable storage device, the computer program product including instructions that, when executed, generate on a display device a graphical user interface for identifying a substitute relating to a business document model, the graphical user interface comprising: a modeling area configured to present multiple components of a business document model, the business document model comprising a semantic model used in generating one or more documents to be exchanged in electronic communication, and the multiple components comprising nodes and edges that represent semantics of a business document, the edges connecting nodes; and a substitution candidate area for presenting at least one substitute component such that a user can replace an indicated one of the multiple components in the business document model with the substitute component, the at least one substitute component being identified in a repository of preexisting business document models and using a graph structure of the business document model. 17. The computer program product of claim 16 , wherein the substitution candidate area further is configured to present a quality value with the substitute component, the quality value representing a determination of a quality of the substitute component as a replacement for the indicated component. | 0.5 |
8,751,418 | 1 | 6 | 1. A computer-implemented method comprising: receiving focus information descriptive of a search engine advertising campaign from an advertising campaign manager, the focus information comprising two or more keyword search strings, each keyword search string paired with at least one bid parameter, a relative importance of each keyword search string characterized by the at least one bid parameter; accessing a respective consumption history of each of a plurality of entities in a storage; identifying, at an audience selection system, a training set of entities from the storage by examining each of the respective consumption histories for one or more proxy events, each proxy event comprising a keyword search matching at least one of the two or more keyword search strings described in the focus information; weighting each proxy event according to the at least one bid parameter paired with each proxy event's keyword search string; creating a weighted training set by weighting each entity in the training set according to the proxy event weights of the one or more proxy events found in each entity's respective consumption history; building a behavioral model based on the weighted training set; receiving a specified entity's consumption history; and assessing the suitability of the specific entity for selection by applying the behavioral model to the specified entity's consumption history. | 1. A computer-implemented method comprising: receiving focus information descriptive of a search engine advertising campaign from an advertising campaign manager, the focus information comprising two or more keyword search strings, each keyword search string paired with at least one bid parameter, a relative importance of each keyword search string characterized by the at least one bid parameter; accessing a respective consumption history of each of a plurality of entities in a storage; identifying, at an audience selection system, a training set of entities from the storage by examining each of the respective consumption histories for one or more proxy events, each proxy event comprising a keyword search matching at least one of the two or more keyword search strings described in the focus information; weighting each proxy event according to the at least one bid parameter paired with each proxy event's keyword search string; creating a weighted training set by weighting each entity in the training set according to the proxy event weights of the one or more proxy events found in each entity's respective consumption history; building a behavioral model based on the weighted training set; receiving a specified entity's consumption history; and assessing the suitability of the specific entity for selection by applying the behavioral model to the specified entity's consumption history. 6. The method of claim 1 wherein creating the weighted training set further comprises: weighting each entity in the training set according to a recency of the one or more matching keyword search strings in the entity's consumption history. | 0.504149 |
8,359,323 | 1 | 3 | 1. A computer program product comprising a storage device storing a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: receive a database language request from a database driver that is compatible with a software application, wherein the database language request is in a database language format, and wherein the database driver processes standard database calls; parse the database language request; convert the database language request into an intermediary data format, wherein the intermediary data format comprises a data object identifying an operation and data, wherein the data includes at least one field with an associated value; and provide the database language request in the intermediary data format to a common client interface builder that reformats the database language request into a format that is compatible with a system resource adapter, invokes the system resource adapter with the reformatted request, receives the data object that has been modified from the system resource adapter, and maps the received data object to a result set. | 1. A computer program product comprising a storage device storing a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: receive a database language request from a database driver that is compatible with a software application, wherein the database language request is in a database language format, and wherein the database driver processes standard database calls; parse the database language request; convert the database language request into an intermediary data format, wherein the intermediary data format comprises a data object identifying an operation and data, wherein the data includes at least one field with an associated value; and provide the database language request in the intermediary data format to a common client interface builder that reformats the database language request into a format that is compatible with a system resource adapter, invokes the system resource adapter with the reformatted request, receives the data object that has been modified from the system resource adapter, and maps the received data object to a result set. 3. The computer program product of claim 1 , wherein the database language format is Standard Query Language. | 0.66358 |
9,177,262 | 7 | 10 | 7. A system comprising: a database source computer module configured to extract data associated with a plurality of co-occurring topics in a document corpus; and a synchronizing framework computer module configured to: extract a plurality of topic identifies from the plurality of co-occurring topics; create a master topic computer model for the document corpus from a first plurality of term vectors; create a periodic new topic computer model by comparing topic significance among the plurality of topic identifiers, the periodic new topic computer model including a second plurality of term vectors; and select one or more new topics by identifying one or more term vectors from the second plurality of term vectors in the periodic new topic computer model that have no correlation with the first plurality of term vectors in the master topic computer model. | 7. A system comprising: a database source computer module configured to extract data associated with a plurality of co-occurring topics in a document corpus; and a synchronizing framework computer module configured to: extract a plurality of topic identifies from the plurality of co-occurring topics; create a master topic computer model for the document corpus from a first plurality of term vectors; create a periodic new topic computer model by comparing topic significance among the plurality of topic identifiers, the periodic new topic computer model including a second plurality of term vectors; and select one or more new topics by identifying one or more term vectors from the second plurality of term vectors in the periodic new topic computer model that have no correlation with the first plurality of term vectors in the master topic computer model. 10. The system of claim 7 wherein the master topic computer model is a multi-component extension of a Latent Dirichlet Allocation (MC-LDA) topic model. | 0.709615 |
8,005,879 | 1 | 2 | 1. A method comprising: determining a service executing on an originating device of a network of devices in which a plurality of services are deployed and configured to process information external to the network of devices and collected by at least one sensor associated with the network of devices, the service including executable code; determining a cause for re-deployment of the service executing on the originating device; mapping the service to a selected device from among the network of devices that includes the originating device and the selected device; and re-deploying the service on the selected device including transferring the executable code to the selected device for execution thereon and for continued processing of the external information therewith, wherein determining a cause for re-deployment of the service comprises: determining that the selected device is available for re-deployment of the service; and determining device metadata associated with the originating device and/or the selected device that indicates that the selected device is better able to execute the service, including determining the device metadata by representing device characteristics of the originating device and the selected device in a common format; value-matching the device characteristics of each of the originating device and the selected device to service characteristics of the service as represented in associated service metadata, and selecting the selected device as having a closer value-match of device characteristics to the service characteristics than the originating device. | 1. A method comprising: determining a service executing on an originating device of a network of devices in which a plurality of services are deployed and configured to process information external to the network of devices and collected by at least one sensor associated with the network of devices, the service including executable code; determining a cause for re-deployment of the service executing on the originating device; mapping the service to a selected device from among the network of devices that includes the originating device and the selected device; and re-deploying the service on the selected device including transferring the executable code to the selected device for execution thereon and for continued processing of the external information therewith, wherein determining a cause for re-deployment of the service comprises: determining that the selected device is available for re-deployment of the service; and determining device metadata associated with the originating device and/or the selected device that indicates that the selected device is better able to execute the service, including determining the device metadata by representing device characteristics of the originating device and the selected device in a common format; value-matching the device characteristics of each of the originating device and the selected device to service characteristics of the service as represented in associated service metadata, and selecting the selected device as having a closer value-match of device characteristics to the service characteristics than the originating device. 2. The method of claim 1 wherein determining a cause for re-deployment of the service comprises determining device metadata associated with the originating device and indicating that the originating device currently has insufficient device characteristics to continue adequately executing the service, based on service metadata associated with the service. | 0.5 |
8,209,665 | 1 | 6 | 1. A method, implemented at least in part by a computing device, for identifying topics in source code using Latent Dirichlet Allocation (LDA), the method comprising: receiving software source code; identifying domain specific keywords from the software source code; generating a keyword matrix, wherein the keyword matrix comprises weighted sums of occurrences of the domain specific keywords in the software source code; processing, using LDA, the keyword matrix and the software source code; and outputting, from the processing, collections of domain specific keywords and probabilities, wherein the collections corresponds to respective topics identified by LDA in the software source code. | 1. A method, implemented at least in part by a computing device, for identifying topics in source code using Latent Dirichlet Allocation (LDA), the method comprising: receiving software source code; identifying domain specific keywords from the software source code; generating a keyword matrix, wherein the keyword matrix comprises weighted sums of occurrences of the domain specific keywords in the software source code; processing, using LDA, the keyword matrix and the software source code; and outputting, from the processing, collections of domain specific keywords and probabilities, wherein the collections corresponds to respective topics identified by LDA in the software source code. 6. The method of claim 1 wherein each of the domain specific keywords of the keyword matrix is weighted based upon a location type of the domain specific keyword. | 0.837022 |
8,645,390 | 43 | 45 | 43. The non-transitory computer readable storage medium of claim 40 , wherein each search context is associated with a respective group of users and a respective class of search queries. | 43. The non-transitory computer readable storage medium of claim 40 , wherein each search context is associated with a respective group of users and a respective class of search queries. 45. The non-transitory computer readable storage medium of claim 43 , wherein the respective class for a particular search query is a query type determined in accordance with one or more of the terms of the particular search query. | 0.5 |
8,244,769 | 1 | 8 | 1. An ontology processing device for processing an ontology, comprising: a data input device; a memory; a processor; and a computer program with instructions that, when said processor executes said instructions, is configured as a structuralizing device which corrects a structure of ontology in a prescribed form created from a set of instance data containing a combination of a subject, a property, and an object expressed with a character string; wherein the structuralizing device comprises a necessity degree judging device which judges whether each of the properties contained in the ontology is an essential property or unessential property for a concept that is defined within the ontology and related to each of the properties according to statistical features of the objects contained in the set of the instance data, and corrects the structure of the ontology regarding the corresponding properties according to results of the judgments, and wherein the necessity degree judging device changes the property that is judged as unessential to a property having an inverted definition range and an inverted value range. | 1. An ontology processing device for processing an ontology, comprising: a data input device; a memory; a processor; and a computer program with instructions that, when said processor executes said instructions, is configured as a structuralizing device which corrects a structure of ontology in a prescribed form created from a set of instance data containing a combination of a subject, a property, and an object expressed with a character string; wherein the structuralizing device comprises a necessity degree judging device which judges whether each of the properties contained in the ontology is an essential property or unessential property for a concept that is defined within the ontology and related to each of the properties according to statistical features of the objects contained in the set of the instance data, and corrects the structure of the ontology regarding the corresponding properties according to results of the judgments, and wherein the necessity degree judging device changes the property that is judged as unessential to a property having an inverted definition range and an inverted value range. 8. The ontology processing device as claimed in claim 1 , wherein the ontology-making device comprises a metadata adding device which extracts metadata contained in the input data, and adds the metadata to the ontology written by the ontology writing device. | 0.887728 |
9,065,727 | 9 | 10 | 9. A system for building a device identifier similarity model with online event signals comprising a processing circuit including a processor and a memory coupled thereto, the processing circuit operable to: receive a first set of network device identifiers; identify an online event associated with network activity of each network device identifier of the first set; identify, for each network device identifier of the first set, one or more long-term browsing history events surrounding the identified online event based on the network device identifier's network activity, the long-term browsing history events corresponding to events occurring prior to a first time from the identified online event; identify, for each network device identifier of the first set, one or more short-term browsing history events surrounding the identified online event based on the network device identifier's network activity, the short-term browsing history events corresponding to events occurring after the first time from the identified online event; represent each device identifier of the first set as a vector based on feature data corresponding to each network device identifier's network activity, the feature data comprising keywords corresponding to content associated with the device identifier's network activity; apply abstractions on the feature data to form concepts, wherein each concept represents a category of interest; derive at least one hierarchy of the feature data based on the keywords and concepts of the feature data; expand the feature data based on the derived at least one hierarchy of the feature data; apply a clustering algorithm on each of the vectors to identify a plurality of clusters of device identifiers that share a common interest; provide at least one subset of network device identifiers corresponding to each of the plurality of clusters; and generate the device identifier similarity model based on the expanded feature data. | 9. A system for building a device identifier similarity model with online event signals comprising a processing circuit including a processor and a memory coupled thereto, the processing circuit operable to: receive a first set of network device identifiers; identify an online event associated with network activity of each network device identifier of the first set; identify, for each network device identifier of the first set, one or more long-term browsing history events surrounding the identified online event based on the network device identifier's network activity, the long-term browsing history events corresponding to events occurring prior to a first time from the identified online event; identify, for each network device identifier of the first set, one or more short-term browsing history events surrounding the identified online event based on the network device identifier's network activity, the short-term browsing history events corresponding to events occurring after the first time from the identified online event; represent each device identifier of the first set as a vector based on feature data corresponding to each network device identifier's network activity, the feature data comprising keywords corresponding to content associated with the device identifier's network activity; apply abstractions on the feature data to form concepts, wherein each concept represents a category of interest; derive at least one hierarchy of the feature data based on the keywords and concepts of the feature data; expand the feature data based on the derived at least one hierarchy of the feature data; apply a clustering algorithm on each of the vectors to identify a plurality of clusters of device identifiers that share a common interest; provide at least one subset of network device identifiers corresponding to each of the plurality of clusters; and generate the device identifier similarity model based on the expanded feature data. 10. The system of claim 9 , wherein the processing circuit is further operable to: determine a first online event signal and a second online event signal based on each network device identifier's network activity; and determine a time representation of the time between the first online event signal and the second online event signal. | 0.5 |
9,111,260 | 1 | 6 | 1. A method comprising: causing, to be displayed to a user, data that identifies a plurality of packages to which the user may subscribe; receiving, from the user, input that indicates a subscription, by the user, to one or more packages of the plurality of packages, each of which includes a plurality of pre-defined suggested words that were not selected for inclusion in the package by the user; sending, to a server over a network, a list that identifies each of the one or more packages for which the user has indicated a subscription; after sending the list to the server, receiving, from the server, the plurality of pre-defined suggested words associated with each package identified in the list; after receiving the plurality of pre-defined suggested words associated with each package in the list, determining whether any text within an electronic messaging (EM) conversation qualifies as a suggested word for the user in the EM conversation based, at least in part, on whether the text matches any of the plurality of pre-defined suggested words of the one or more packages; causing text within the EM conversation that qualifies as a suggested word to be displayed in a manner that visually distinguishes the suggested word from text of the EM conversation that does not qualify as a suggested word; in response to receiving, from the user, second input relative to the suggested word in the EM conversation, causing, to be initiated, an operation to retrieve information related to the suggested word; in response to receiving results of said operation, causing a display that reflects the results to be generated; wherein the one or more packages includes a first package that is associated with a first set of suggested words; after causing the display that reflects the results to be generated, receiving a second set of suggested words that are different than the first set of suggested words and that are to be associated with the first package; wherein the method is performed by one or more computing devices. | 1. A method comprising: causing, to be displayed to a user, data that identifies a plurality of packages to which the user may subscribe; receiving, from the user, input that indicates a subscription, by the user, to one or more packages of the plurality of packages, each of which includes a plurality of pre-defined suggested words that were not selected for inclusion in the package by the user; sending, to a server over a network, a list that identifies each of the one or more packages for which the user has indicated a subscription; after sending the list to the server, receiving, from the server, the plurality of pre-defined suggested words associated with each package identified in the list; after receiving the plurality of pre-defined suggested words associated with each package in the list, determining whether any text within an electronic messaging (EM) conversation qualifies as a suggested word for the user in the EM conversation based, at least in part, on whether the text matches any of the plurality of pre-defined suggested words of the one or more packages; causing text within the EM conversation that qualifies as a suggested word to be displayed in a manner that visually distinguishes the suggested word from text of the EM conversation that does not qualify as a suggested word; in response to receiving, from the user, second input relative to the suggested word in the EM conversation, causing, to be initiated, an operation to retrieve information related to the suggested word; in response to receiving results of said operation, causing a display that reflects the results to be generated; wherein the one or more packages includes a first package that is associated with a first set of suggested words; after causing the display that reflects the results to be generated, receiving a second set of suggested words that are different than the first set of suggested words and that are to be associated with the first package; wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein: the operation to retrieve information is based, at least in part, on the package that includes said suggested word; the package is associated with a search source; and the operation to retrieve information includes retrieving information from said search source. | 0.755738 |
9,529,924 | 16 | 27 | 16. A system comprising: a user device having a display and a battery; one or more processors configured to perform operations comprising: providing an interface that: receives text for a search query; communicates with at least one search engine server via a network; in response to the receipt of a first portion of the text for the search query: displays a first set of localized results retrieved based on the first portion of text without displaying remote search results from the search engine server; while displaying the first set of localized results, receives a second portion of text for the search query; and in response to receiving the second portion of the text: in accordance with a determination that the first portion of text and the second portion of text together include more than a predetermined number of characters, wherein the predetermined number of characters is greater than 1 and is based on a low battery state of the battery, concurrently displays a plurality of results that include: a set of results received from the search engine server; and a second set of localized results associated with one or more applications on the device retrieved based on the first portion of the text and the second portion of the text. | 16. A system comprising: a user device having a display and a battery; one or more processors configured to perform operations comprising: providing an interface that: receives text for a search query; communicates with at least one search engine server via a network; in response to the receipt of a first portion of the text for the search query: displays a first set of localized results retrieved based on the first portion of text without displaying remote search results from the search engine server; while displaying the first set of localized results, receives a second portion of text for the search query; and in response to receiving the second portion of the text: in accordance with a determination that the first portion of text and the second portion of text together include more than a predetermined number of characters, wherein the predetermined number of characters is greater than 1 and is based on a low battery state of the battery, concurrently displays a plurality of results that include: a set of results received from the search engine server; and a second set of localized results associated with one or more applications on the device retrieved based on the first portion of the text and the second portion of the text. 27. The system of claim 16 , wherein the set of results received from the search engine server includes a suggested search term. | 0.863248 |
9,411,799 | 1 | 15 | 1. A method of creating a template, the method comprising: identifying at least one domain ontology concept based on at least a portion of a first text-string input into a clinical document for a clinical indication; proposing, in the clinical document for the clinical indication, at least one name or label corresponding to the at least one domain ontology concept for selection by a user; inserting the at least one name or label corresponding to the at least one domain ontology concept into the clinical document for the clinical indication in response to selection of the at least one name or label by the user, the clinical document including documentation of at least clinical observations by a physician, the inserting the at least one name or label including auto-completing the first text string based on the identified at least one domain ontology concept and a context of the portion of the first text string in the clinical document; analyzing the clinical document to identify at least one first candidate for structural content in the clinical document, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by the user; obtaining at least one domain specific structural element associated with at least one further domain ontology concept corresponding to the identified at least one first candidate, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, wherein if the at least one first candidate exists in a library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from the library of existing domain specific structures, and the plurality of second candidates are additional concepts identified as siblings of the at least one first candidate in the library of existing domain specific structures, and if the at least one first candidate does not exist in the library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from a domain ontology database based on a parent node corresponding to the at least one first candidate; and creating a template corresponding to the clinical document by inserting, into the clinical document, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template. | 1. A method of creating a template, the method comprising: identifying at least one domain ontology concept based on at least a portion of a first text-string input into a clinical document for a clinical indication; proposing, in the clinical document for the clinical indication, at least one name or label corresponding to the at least one domain ontology concept for selection by a user; inserting the at least one name or label corresponding to the at least one domain ontology concept into the clinical document for the clinical indication in response to selection of the at least one name or label by the user, the clinical document including documentation of at least clinical observations by a physician, the inserting the at least one name or label including auto-completing the first text string based on the identified at least one domain ontology concept and a context of the portion of the first text string in the clinical document; analyzing the clinical document to identify at least one first candidate for structural content in the clinical document, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by the user; obtaining at least one domain specific structural element associated with at least one further domain ontology concept corresponding to the identified at least one first candidate, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, wherein if the at least one first candidate exists in a library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from the library of existing domain specific structures, and the plurality of second candidates are additional concepts identified as siblings of the at least one first candidate in the library of existing domain specific structures, and if the at least one first candidate does not exist in the library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from a domain ontology database based on a parent node corresponding to the at least one first candidate; and creating a template corresponding to the clinical document by inserting, into the clinical document, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template. 15. A non-transitory computer readable medium storing including program segments for, when executed on a computer device, causing the computer device to implement the method of claim 1 . | 0.5 |
9,390,195 | 4 | 5 | 4. The method of claim 3 , wherein identifying the set of quota cells further includes traversing the graph database to identify a set of quota cell vertices each having at least one includes type of edge that encounters at least one of the profile parameter value vertices identified for the panelist, and that do not have at least one excludes type of edge that encounters at least one of the profile parameter value vertices identified for the panelist. | 4. The method of claim 3 , wherein identifying the set of quota cells further includes traversing the graph database to identify a set of quota cell vertices each having at least one includes type of edge that encounters at least one of the profile parameter value vertices identified for the panelist, and that do not have at least one excludes type of edge that encounters at least one of the profile parameter value vertices identified for the panelist. 5. The method of claim 4 , wherein identifying the set of quota cells further comprises determining an incomplete match to a quota cell in response to an edge of the quota cell vertex for the quota cell encountering a profile parameter value vertex representing a value of a profile parameter that is not determined for the panelist. | 0.5 |
8,131,647 | 33 | 40 | 33. A computer-implemented method for providing an annotation of a digital work, comprising: under control of instructions that are executed by one or more computing devices: obtaining a first representation of a digital work, the first representation comprising one or more images; obtaining a second representation of the digital work, the second representation comprising content of the digital work in a form that allows particular content of the digital work to be indicated, the particular content being correlatable with one or more locations in the one or more images at which the particular content is represented; receiving an annotation of the digital work in regard to indicated particular content of the digital work; and providing to a user the annotation in context with regard to the digital work. | 33. A computer-implemented method for providing an annotation of a digital work, comprising: under control of instructions that are executed by one or more computing devices: obtaining a first representation of a digital work, the first representation comprising one or more images; obtaining a second representation of the digital work, the second representation comprising content of the digital work in a form that allows particular content of the digital work to be indicated, the particular content being correlatable with one or more locations in the one or more images at which the particular content is represented; receiving an annotation of the digital work in regard to indicated particular content of the digital work; and providing to a user the annotation in context with regard to the digital work. 40. The method of claim 33 , wherein the annotation is provided to the user via an online marketplace. | 0.788382 |
9,152,612 | 1 | 7 | 1. A computer-based method of processing a document having a plurality of input controls, the method comprising: a) in response to a command to display the plurality of input controls, attaching the plurality of input controls to the document; b) in response to a command to hide the plurality of input controls, detaching the plurality of input controls from the document; c) inserting a substitute control in the document and displaying the substitute control in response to the command to hide the plurality of input controls, the command to display the plurality of input controls is invoked by a user selection of the substitute control; and d) sending a value of each input control to a server. | 1. A computer-based method of processing a document having a plurality of input controls, the method comprising: a) in response to a command to display the plurality of input controls, attaching the plurality of input controls to the document; b) in response to a command to hide the plurality of input controls, detaching the plurality of input controls from the document; c) inserting a substitute control in the document and displaying the substitute control in response to the command to hide the plurality of input controls, the command to display the plurality of input controls is invoked by a user selection of the substitute control; and d) sending a value of each input control to a server. 7. The computer-based method of claim 1 , further comprising: a) in response to the command to hide the plurality of input controls, encoding the value of each input control in a hidden field of the document; and b) receiving, after encoding the value of each input control in the hidden field, a command to send the value of each input control to the server, and in response, sending at least a portion of the hidden field to the server. | 0.5 |
9,075,792 | 1 | 6 | 1. A system comprising: one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: obtaining a token that comprises a sequence of characters in a source language, identifying (i) two or more candidate sub-words that are constituents of the token, and (ii) one or more morphological operations that are required to transform the candidate sub-words into the token, wherein at least one of the morphological operations involves a use of a non-dictionary word, determining a cost associated with each candidate sub-word and a cost associated with each morphological operation, performing a dynamic program model-based compound splitting process to selectively decompound the token into the candidate sub-words based on the costs to obtain one or more words, including: utilizing a recursive function to determine minimal costs for a number of split points in the token, and selectively decompounding the token into candidate sub-words having the minimal costs to obtain the one or more words; and performing phrase-based statistical machine translation (SMT) of the one or more words from the source language to a different target language, wherein the recursive function is: Q ( c 1 j ) = max n k , g k { ξ · Q ( c 1 n k - 1 ) · p ( c n k - 1 + 1 n k , n k - 1 g 1 K ) } , where Q(c 1 j ) represents the minimal costs that a cost function
p ( c n k-1 +1 n k ,n k-1 g 1 K ) assigns to a character string c 1 j when the dynamic program model-based compound splitting process uses K split points at positions n 1 k , where ξ represents a constant split penalty, and where g 1 K represents transformed lexemes from non-dictionary words. | 1. A system comprising: one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: obtaining a token that comprises a sequence of characters in a source language, identifying (i) two or more candidate sub-words that are constituents of the token, and (ii) one or more morphological operations that are required to transform the candidate sub-words into the token, wherein at least one of the morphological operations involves a use of a non-dictionary word, determining a cost associated with each candidate sub-word and a cost associated with each morphological operation, performing a dynamic program model-based compound splitting process to selectively decompound the token into the candidate sub-words based on the costs to obtain one or more words, including: utilizing a recursive function to determine minimal costs for a number of split points in the token, and selectively decompounding the token into candidate sub-words having the minimal costs to obtain the one or more words; and performing phrase-based statistical machine translation (SMT) of the one or more words from the source language to a different target language, wherein the recursive function is: Q ( c 1 j ) = max n k , g k { ξ · Q ( c 1 n k - 1 ) · p ( c n k - 1 + 1 n k , n k - 1 g 1 K ) } , where Q(c 1 j ) represents the minimal costs that a cost function
p ( c n k-1 +1 n k ,n k-1 g 1 K ) assigns to a character string c 1 j when the dynamic program model-based compound splitting process uses K split points at positions n 1 k , where ξ represents a constant split penalty, and where g 1 K represents transformed lexemes from non-dictionary words. 6. The system of claim 1 , wherein the non-dictionary word is a linking morpheme. | 0.922414 |
8,825,682 | 1 | 4 | 1. A system for receiving a retrieval request and generating a recognition result, the system comprising: a processor; a gateway having a plurality of inputs for receiving the retrieval request that includes at least an image portion and contextual information, the gateway processing the retrieval request to generate an image query and a recognition parameter, the gateway having a plurality of outputs for sending recognition results; a matching unit stored on a computer-readable storage medium and executable by the processor, the matching unit coupled to receive the image query and the recognition parameter from the gateway, the matching unit analyzing and comparing the image query and recognition parameter to an index table to generate the recognition result including a page identification number and a location on the recognition result, the matching unit coupled to send the recognition result to the gateway; and a hotspot database coupled to the matching unit, the hotspot database for retrieving hotspot information corresponding to the page and the location identified in the recognition result. | 1. A system for receiving a retrieval request and generating a recognition result, the system comprising: a processor; a gateway having a plurality of inputs for receiving the retrieval request that includes at least an image portion and contextual information, the gateway processing the retrieval request to generate an image query and a recognition parameter, the gateway having a plurality of outputs for sending recognition results; a matching unit stored on a computer-readable storage medium and executable by the processor, the matching unit coupled to receive the image query and the recognition parameter from the gateway, the matching unit analyzing and comparing the image query and recognition parameter to an index table to generate the recognition result including a page identification number and a location on the recognition result, the matching unit coupled to send the recognition result to the gateway; and a hotspot database coupled to the matching unit, the hotspot database for retrieving hotspot information corresponding to the page and the location identified in the recognition result. 4. The system of claim 1 further comprising a mobile device having plug-in module, the mobile device capable of capturing an image, the mobile device adapted for communication with the gateway, and the plug-in module adapted to process images, present a captured image on the mobile device, receive user selection of the captured image, and send the captured image to the gateway. | 0.686985 |
9,520,068 | 20 | 22 | 20. A device comprising: a processor device; memory in communication with the processor device; a display device operatively coupled to the processor and memory; and a storage medium storing a computer program product to configure the processor to: render text of an electronic representation of a document on the display device, with the text of the document having a first appearance that includes a first color and first style, and with at least first and second sentences of the document displayed on the display device in the first appearance; apply a first visual feedback indicium over all text of the first sentence displayed on the display device to indicate a current first sentence to be read, while having the second sentence displayed in the first appearance; receive audio from a user reading the first sentence aloud; determine, using speech recognition processing that converts the received audio for the first sentence a text file, when the user has reached a last word of the sentence; concurrently remove the first visual feedback indicium from the first sentence, return all of the displayed text of the first sentence to the first appearance and apply the first visual feedback indicium over all words in the second sentence after the user completes the last word of the first sentence; apply the first visual feedback indicium on the second sentence displayed on the display device, while the first sentence is displayed on the display device without the first visual feedback indicium; and generate in the presence of an intervention a visual intervention indicium for the word that required the intervention in the second sentence, by rendering the words in the second sentence that are prior to the word that required the intervention in a second color, the word that required the intervention rendered in a different color from the second color and with a highlight on the word that required the intervention, and with words in the second sentence subsequent to the word rendered in the different color. | 20. A device comprising: a processor device; memory in communication with the processor device; a display device operatively coupled to the processor and memory; and a storage medium storing a computer program product to configure the processor to: render text of an electronic representation of a document on the display device, with the text of the document having a first appearance that includes a first color and first style, and with at least first and second sentences of the document displayed on the display device in the first appearance; apply a first visual feedback indicium over all text of the first sentence displayed on the display device to indicate a current first sentence to be read, while having the second sentence displayed in the first appearance; receive audio from a user reading the first sentence aloud; determine, using speech recognition processing that converts the received audio for the first sentence a text file, when the user has reached a last word of the sentence; concurrently remove the first visual feedback indicium from the first sentence, return all of the displayed text of the first sentence to the first appearance and apply the first visual feedback indicium over all words in the second sentence after the user completes the last word of the first sentence; apply the first visual feedback indicium on the second sentence displayed on the display device, while the first sentence is displayed on the display device without the first visual feedback indicium; and generate in the presence of an intervention a visual intervention indicium for the word that required the intervention in the second sentence, by rendering the words in the second sentence that are prior to the word that required the intervention in a second color, the word that required the intervention rendered in a different color from the second color and with a highlight on the word that required the intervention, and with words in the second sentence subsequent to the word rendered in the different color. 22. The device of claim 20 further configured to assess the quality of the user's reading on a word-by-word basis. | 0.848806 |
8,705,707 | 1 | 8 | 1. A method performed by at least one processor of a communication device, the method comprising: determining, by the communication device, that a call has been answered, missed, or terminated by the communication device; generating, at a graphical user interface associated with the communication device, an indication of the call being answered, missed, or terminated; responsive to determining that the call has been answered, missed, or terminated by the communication device, automatically: determining, by the communication device, one or more contextual identifiers associated with the call, wherein the one or more contextual identifiers are based on a geographic location of the communication device at a time of the call, and storing the one or more contextual identifiers in association with the indication of the call in at least one data structure that includes other contextual identifiers associated with other indications of other calls, wherein the one or more contextual identifiers and the other contextual identifiers included in the at least one data structure are searchable; and determining that the one or more contextual identifiers satisfy a search query based at least in part on a second input received at the graphical user interface, wherein the one or more contextual identifiers and the indication of the call are determined in response to the search query. | 1. A method performed by at least one processor of a communication device, the method comprising: determining, by the communication device, that a call has been answered, missed, or terminated by the communication device; generating, at a graphical user interface associated with the communication device, an indication of the call being answered, missed, or terminated; responsive to determining that the call has been answered, missed, or terminated by the communication device, automatically: determining, by the communication device, one or more contextual identifiers associated with the call, wherein the one or more contextual identifiers are based on a geographic location of the communication device at a time of the call, and storing the one or more contextual identifiers in association with the indication of the call in at least one data structure that includes other contextual identifiers associated with other indications of other calls, wherein the one or more contextual identifiers and the other contextual identifiers included in the at least one data structure are searchable; and determining that the one or more contextual identifiers satisfy a search query based at least in part on a second input received at the graphical user interface, wherein the one or more contextual identifiers and the indication of the call are determined in response to the search query. 8. The method of claim 1 , wherein at least one contextual identifier in the at least one data structure is further based on weather data received by the communication device. | 0.849914 |
8,086,960 | 1 | 6 | 1. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a window; and in response to said receiving: generating a comment based on or including the input; storing the comment in a comment section of a data structure for the electronic document, wherein said storing comprises formatting the comment using a tag to identify the comment, wherein the comment section of the data structure is separate from a body section of the data structure, wherein the body section of the data structure includes content for the body of the electronic markup language document; and displaying the body of the electronic markup language document and an action user interface element in the window, wherein the action user interface element can be activated to perform an action in regard to at least part of the comment stored in the comment section of the data structure, wherein the action includes one or more of view, accept, reject, modify, delete, insert, or replace. | 1. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a window; and in response to said receiving: generating a comment based on or including the input; storing the comment in a comment section of a data structure for the electronic document, wherein said storing comprises formatting the comment using a tag to identify the comment, wherein the comment section of the data structure is separate from a body section of the data structure, wherein the body section of the data structure includes content for the body of the electronic markup language document; and displaying the body of the electronic markup language document and an action user interface element in the window, wherein the action user interface element can be activated to perform an action in regard to at least part of the comment stored in the comment section of the data structure, wherein the action includes one or more of view, accept, reject, modify, delete, insert, or replace. 6. The method of claim 1 , wherein the action user interface element is generated using JavaScript. | 0.805118 |
9,710,239 | 1 | 2 | 1. A method for software application lifecycle management, the method comprising: obtaining, by a software application lifecycle management platform computing device, software application related data and one or more outcomes of prior corresponding software application deliveries from at least one of a knowledge repository or a learning repository based on the software application related data; generating, by the software application lifecycle management platform computing device, a set of models based on the outcomes of the prior corresponding software application deliveries, wherein the generating further comprises deriving a confidence level for each of the set of models, generating a search query based on the software application related data, and searching the knowledge repository for the outcomes of the prior corresponding software application deliveries based on the search query, wherein the searching is executed against the learning repository when there is no match in the knowledge repository; and outputting, by the software application lifecycle management platform computing device, one or more options for selection based on the set of models along with the corresponding confidence level. | 1. A method for software application lifecycle management, the method comprising: obtaining, by a software application lifecycle management platform computing device, software application related data and one or more outcomes of prior corresponding software application deliveries from at least one of a knowledge repository or a learning repository based on the software application related data; generating, by the software application lifecycle management platform computing device, a set of models based on the outcomes of the prior corresponding software application deliveries, wherein the generating further comprises deriving a confidence level for each of the set of models, generating a search query based on the software application related data, and searching the knowledge repository for the outcomes of the prior corresponding software application deliveries based on the search query, wherein the searching is executed against the learning repository when there is no match in the knowledge repository; and outputting, by the software application lifecycle management platform computing device, one or more options for selection based on the set of models along with the corresponding confidence level. 2. The method of claim 1 , further comprising prompting, by the software application lifecycle management platform computing device, a user to input a required outcome and a decision factor via a provided user interface, wherein the decision factor comprises a combination of input and desired output factors and requirement-to-requirement modeling, requirement-to-tasks modeling, requirement-to-test cases modeling, test cases-to-test cases modeling, or requirement-to-end-to-end solution modeling. | 0.5 |
8,224,641 | 8 | 9 | 8. The method of claim 7 wherein the default score component S δ (M) for the language M is given by: S δ ( M ) = ∑ B = default ( M ) w B * log [ 1 P M ( B ) ] , wherein the sum is over the bigrams B in the target document that do not have greater than the default probability of occurring in language M and wherein w B is proportional to the number of occurrences of the bigram B in the target document. | 8. The method of claim 7 wherein the default score component S δ (M) for the language M is given by: S δ ( M ) = ∑ B = default ( M ) w B * log [ 1 P M ( B ) ] , wherein the sum is over the bigrams B in the target document that do not have greater than the default probability of occurring in language M and wherein w B is proportional to the number of occurrences of the bigram B in the target document. 9. The method of claim 8 wherein the alternative language score S M ′(L) for each language L in the set N(M) is given by: S M ′ ( L ) = ∑ B = default ( M ) w B * log [ 1 P L ( B ) ] , wherein the sum is over the bigrams B in the target document that do not have greater than the default probability of occurring in the language M, wherein w B is proportional to the number of occurrences of the bigram B in the target document, and wherein P L (B) is the probability of the bigram B occurring in the language L. | 0.5 |
8,773,359 | 4 | 5 | 4. The method of claim 1 wherein considering at least one likelihood of at least one interpretation of the key assertion comprises, at least in part, according a likelihood advantage to one particular interpretation of the key assertion. | 4. The method of claim 1 wherein considering at least one likelihood of at least one interpretation of the key assertion comprises, at least in part, according a likelihood advantage to one particular interpretation of the key assertion. 5. The method of claim 4 wherein the likelihood advantage is not necessarily dispositive. | 0.5 |
9,002,713 | 1 | 7 | 1. A method comprising: recognizing speech received from a plurality of speakers to yield recognized speech for each of the speakers, wherein each speaker in the plurality of speakers interacts with a speech interface that uses a set of allocated resources comprising a first resource and a second resource that is associated with the each speaker in the plurality of speakers, and wherein the set of allocated resources comprise at least one of bandwidth and processor time; recording metrics associated with the recognized speech for each of the plurality of speakers, wherein the metrics comprise a speech recognition confidence score, a processing speed, a dialog behavior, a request for repetition, a negative response to confirmation, and a task completion; after recording the metrics, while recording further speech from each speaker in the plurality of speakers, modifying at least one of the first resource and the second resource commensurate with the metrics, to yield a modified set of allocated resources; and recognizing additional speech during a conference call from an identified speaker in the plurality of speakers using the modified set of allocated resources for speakers predetermined to be frustrated and have great difficulty in a prior session. | 1. A method comprising: recognizing speech received from a plurality of speakers to yield recognized speech for each of the speakers, wherein each speaker in the plurality of speakers interacts with a speech interface that uses a set of allocated resources comprising a first resource and a second resource that is associated with the each speaker in the plurality of speakers, and wherein the set of allocated resources comprise at least one of bandwidth and processor time; recording metrics associated with the recognized speech for each of the plurality of speakers, wherein the metrics comprise a speech recognition confidence score, a processing speed, a dialog behavior, a request for repetition, a negative response to confirmation, and a task completion; after recording the metrics, while recording further speech from each speaker in the plurality of speakers, modifying at least one of the first resource and the second resource commensurate with the metrics, to yield a modified set of allocated resources; and recognizing additional speech during a conference call from an identified speaker in the plurality of speakers using the modified set of allocated resources for speakers predetermined to be frustrated and have great difficulty in a prior session. 7. The method of claim 1 , wherein modifying at least one of the first resource and second resource is based on a difficulty threshold associated with how well the speaker interacts with the speech interface. | 0.5 |
6,141,641 | 4 | 5 | 4. The method of claim 3 wherein each of the deep senones is represented by a single discrete output distribution and wherein identifying a pair of parameters to be merged comprises: identifying a pair of output distributions to be merged based on an amount of reduction in likelihood of generating a dataset aligned with the pair of output distributions which results from merging the pair of output distributions. | 4. The method of claim 3 wherein each of the deep senones is represented by a single discrete output distribution and wherein identifying a pair of parameters to be merged comprises: identifying a pair of output distributions to be merged based on an amount of reduction in likelihood of generating a dataset aligned with the pair of output distributions which results from merging the pair of output distributions. 5. The method of claim 4 wherein identifying a pair of output distributions to be merged comprises: selecting first and second output distributions; determining a likelihood of generating a first set of data and a second set of data, before merging the first and second selected output distributions, wherein the first set of data is aligned with the first selected output distribution and the second set of data is aligned with the second selected output distribution; determining a reduction in the likelihood of generating the first and second sets of data after merging the first and second selected output distributions; and identifying the pair of output distributions to be merged based on the reduction in the likelihood of generating the first and second sets of data. | 0.5 |
7,502,738 | 32 | 35 | 32. The system according to claim 1 , further comprising an extension and modification facility that allows users and content developers to configure behavior of the agent architecture. | 32. The system according to claim 1 , further comprising an extension and modification facility that allows users and content developers to configure behavior of the agent architecture. 35. The system according to claim 32 , wherein the extension and modification facility provides a generic agent that can be used to create a new domain agent. | 0.754658 |
8,433,698 | 24 | 25 | 24. A non-transitory computer-readable storage medium storing modules that, when executed by a processor, cause a computer to perform a method of searching for media objects associated with a search term, the method comprising: receiving a first search term from a user; performing a first search of Internet data, wherein the first search identifies web pages including the first search term; analyzing a plurality of positional relationships between the first search term and additional terms within an individual one of the web pages; scoring the plurality of positional relationships; determining, based on the scoring the plurality of positional relationships, at least one additional search term; and performing a second search for media objects relating to the at least one additional search term. | 24. A non-transitory computer-readable storage medium storing modules that, when executed by a processor, cause a computer to perform a method of searching for media objects associated with a search term, the method comprising: receiving a first search term from a user; performing a first search of Internet data, wherein the first search identifies web pages including the first search term; analyzing a plurality of positional relationships between the first search term and additional terms within an individual one of the web pages; scoring the plurality of positional relationships; determining, based on the scoring the plurality of positional relationships, at least one additional search term; and performing a second search for media objects relating to the at least one additional search term. 25. The non-transitory computer-readable storage medium of claim 24 , where the scoring is based upon a distance between the first search term and the additional terms within the individual one of the web pages. | 0.5 |
10,007,658 | 1 | 10 | 1. A method, comprising: performing, by a computer system, a lexico-morphological analysis of a natural language text comprising a plurality of tokens, each token comprising at least one natural language word; determining, based on the lexico-morphological analysis, one or more lexical meanings and grammatical meanings associated with each token of the plurality of tokens; for each token of the plurality of tokens, evaluating one or more classifier functions using the lexical and grammatical meanings associated with the tokens, wherein a value of each classifier function is indicative of a degree of association of the token with a category of named entities; performing a syntactico-semantic analysis of at least part of the natural language text to produce a plurality of semantic structures representing the part of the natural language text; and interpreting the semantic structures using a set of production rules to determine, for one or more tokens comprised by the part of the natural language text, a degree of association of the token with a category of named entities. | 1. A method, comprising: performing, by a computer system, a lexico-morphological analysis of a natural language text comprising a plurality of tokens, each token comprising at least one natural language word; determining, based on the lexico-morphological analysis, one or more lexical meanings and grammatical meanings associated with each token of the plurality of tokens; for each token of the plurality of tokens, evaluating one or more classifier functions using the lexical and grammatical meanings associated with the tokens, wherein a value of each classifier function is indicative of a degree of association of the token with a category of named entities; performing a syntactico-semantic analysis of at least part of the natural language text to produce a plurality of semantic structures representing the part of the natural language text; and interpreting the semantic structures using a set of production rules to determine, for one or more tokens comprised by the part of the natural language text, a degree of association of the token with a category of named entities. 10. The method of claim 1 , wherein each semantic structure of the plurality of semantic structures is represented by a graph comprising a plurality of nodes corresponding to a plurality of semantic classes and a plurality of edges corresponding to a plurality of semantic relationships. | 0.524834 |
8,001,140 | 1 | 3 | 1. A computer-implemented method, comprising: at a computer having memory, a display, and one or more processors, receiving a search keyword provided by a user, wherein the search keyword satisfies a predefined expression pattern; determining an archetype for the search keyword; identifying a query operator for the archetype, wherein the query operator includes a generalized expression of the search keyword; applying the identified query operator to a document; identifying a chunk within the document that satisfies the identified query operator, wherein the chunk does not include an instance of the search keyword; and returning the chunk for display to the user. | 1. A computer-implemented method, comprising: at a computer having memory, a display, and one or more processors, receiving a search keyword provided by a user, wherein the search keyword satisfies a predefined expression pattern; determining an archetype for the search keyword; identifying a query operator for the archetype, wherein the query operator includes a generalized expression of the search keyword; applying the identified query operator to a document; identifying a chunk within the document that satisfies the identified query operator, wherein the chunk does not include an instance of the search keyword; and returning the chunk for display to the user. 3. The method of claim 1 , wherein the identified query operator has a parameter defining a numeric scope. | 0.789683 |
8,249,892 | 7 | 11 | 7. The method of claim 3 , further comprising: providing feedback, on a display of said computer system, to said service provider based upon said clinical outcomes, and efficiency measures. | 7. The method of claim 3 , further comprising: providing feedback, on a display of said computer system, to said service provider based upon said clinical outcomes, and efficiency measures. 11. The method of claim 7 , further comprising: performing comparative analysis of technology performance to determine technology impact on workflow. | 0.640097 |
9,216,041 | 10 | 16 | 10. A medical implant assembly comprising: a) first and second bone anchors cooperating with a longitudinal connecting member having a tensioned cord and a spacer, the spacer located between the first and second bone anchors and having a first through bore, the tensioned cord extending through the spacer, each of the first and second bone anchors having a first pair of opposed upstanding arms and a compression insert, each compression insert having a second pair of upstanding arms forming an insert channel therebetween, each second pair of upstanding arms of the compression inserts having a top surface; b) a sleeve for attachment to one of the bone anchors, the sleeve having: i) a second through bore sized and shaped for slidably receiving the tensioned cord, ii) an aperture formed in the sleeve substantially transverse to the second through bore, the aperture sized and shaped for receiving a lower extension of a cord gripping closure top, iii) first and second body portions, the first body portion sized and shaped for being closely received within a respective channel of the second pair of upstanding arms of a respective compression insert and the second body portion being sized and shaped to be received between the first pair of opposed upstanding arms of a respective bone anchor and also engage the top surfaces of the second pair of upstanding arms of the respective compression insert. | 10. A medical implant assembly comprising: a) first and second bone anchors cooperating with a longitudinal connecting member having a tensioned cord and a spacer, the spacer located between the first and second bone anchors and having a first through bore, the tensioned cord extending through the spacer, each of the first and second bone anchors having a first pair of opposed upstanding arms and a compression insert, each compression insert having a second pair of upstanding arms forming an insert channel therebetween, each second pair of upstanding arms of the compression inserts having a top surface; b) a sleeve for attachment to one of the bone anchors, the sleeve having: i) a second through bore sized and shaped for slidably receiving the tensioned cord, ii) an aperture formed in the sleeve substantially transverse to the second through bore, the aperture sized and shaped for receiving a lower extension of a cord gripping closure top, iii) first and second body portions, the first body portion sized and shaped for being closely received within a respective channel of the second pair of upstanding arms of a respective compression insert and the second body portion being sized and shaped to be received between the first pair of opposed upstanding arms of a respective bone anchor and also engage the top surfaces of the second pair of upstanding arms of the respective compression insert. 16. The medical implant assembly of claim 10 , wherein the sleeve further includes a first end, a second end, and an elongate solid rod portion extending from the second end. | 0.763587 |
8,332,386 | 1 | 16 | 1. A method comprising: storing bonds that reflect relationships between searchable items; wherein the searchable items include a plurality of documents; wherein the bonds are not stored as part of the searchable items; wherein the bonds do not reflect storage location relationships between said searchable items; receiving a search request to perform a search for searchable items that are associated with a keyword, wherein the search request specifies the keyword; determining that a particular searchable item is to be the starting point of the search; responding to said search request by performing the search relative to the particular searchable item that is to be used as a starting point for said search, wherein performing the search includes at least one of: (a) ranking documents that match said search based, at least in part, on the minimum number of bonds that have to be traversed from the particular searchable item to arrive at each document, wherein the documents that match said search include a first document and a second document, wherein the minimum number of bonds that have to be traversed from said particular searchable to arrive at said first document is different than the minimum number of bonds that have to be traversed from said particular searchable item to arrive at said second document; (b) searching against documents that are within one bond of said particular searchable item; and if the number of documents, within one bond of said particular searchable item, that match the search is less than a target number, then expanding the search to documents that are within two bonds of said particular searchable item; and repeatedly expanding the search to documents that are one further bond away from the particular searchable item until at least the target number of documents that match the search have been identified; or (c) sequentially performing a series of searches relative to said particular searchable item until a predetermined maximum number of bonds from said particular searchable item has been reached, wherein the series of searches includes a first search and one or more subsequent searches, wherein each search of said one or more subsequent searches is performed against documents that are at a greater minimum number of bonds that have to be traversed from said particular searchable item than the documents that were searched in any search that preceded said search in said series; wherein the method is performed by one or more computing devices. | 1. A method comprising: storing bonds that reflect relationships between searchable items; wherein the searchable items include a plurality of documents; wherein the bonds are not stored as part of the searchable items; wherein the bonds do not reflect storage location relationships between said searchable items; receiving a search request to perform a search for searchable items that are associated with a keyword, wherein the search request specifies the keyword; determining that a particular searchable item is to be the starting point of the search; responding to said search request by performing the search relative to the particular searchable item that is to be used as a starting point for said search, wherein performing the search includes at least one of: (a) ranking documents that match said search based, at least in part, on the minimum number of bonds that have to be traversed from the particular searchable item to arrive at each document, wherein the documents that match said search include a first document and a second document, wherein the minimum number of bonds that have to be traversed from said particular searchable to arrive at said first document is different than the minimum number of bonds that have to be traversed from said particular searchable item to arrive at said second document; (b) searching against documents that are within one bond of said particular searchable item; and if the number of documents, within one bond of said particular searchable item, that match the search is less than a target number, then expanding the search to documents that are within two bonds of said particular searchable item; and repeatedly expanding the search to documents that are one further bond away from the particular searchable item until at least the target number of documents that match the search have been identified; or (c) sequentially performing a series of searches relative to said particular searchable item until a predetermined maximum number of bonds from said particular searchable item has been reached, wherein the series of searches includes a first search and one or more subsequent searches, wherein each search of said one or more subsequent searches is performed against documents that are at a greater minimum number of bonds that have to be traversed from said particular searchable item than the documents that were searched in any search that preceded said search in said series; wherein the method is performed by one or more computing devices. 16. The method of claim 1 , further comprising automatically creating bonds in response to one or more actions detected in a system. | 0.89372 |
8,346,815 | 2 | 5 | 2. The system of claim 1 , wherein the data processing apparatus instructions cause the data processing apparatus to perform operations comprising: determining an image intent score for the search query; and generating an image insertion request when the image intent score exceeds an intent threshold. | 2. The system of claim 1 , wherein the data processing apparatus instructions cause the data processing apparatus to perform operations comprising: determining an image intent score for the search query; and generating an image insertion request when the image intent score exceeds an intent threshold. 5. The system of claim 2 , wherein determining dimensions of the image display environment comprises: determining a distribution score that is indicative of the distribution of quality scores of the images that are responsive to the search query; determining a product of the distribution score and the image intent score; and determining a number of rows of images to display in the image display environment from the product of the distribution score and the image intent score. | 0.617834 |
8,117,203 | 4 | 5 | 4. The method of claim 1 , wherein the clustering further includes: finding a most likely value of a clustering variable after all virtual-evidence have been propagated through the Bayesian belief network by means of a greedy agglomerative search process including: consider all pairs of clusters; evaluating a set of edges connecting one sample in one cluster to another sample in another cluster to choose one pair of clusters; and merging repeatedly the chosen pair of clusters to create a larger cluster until only one cluster results. | 4. The method of claim 1 , wherein the clustering further includes: finding a most likely value of a clustering variable after all virtual-evidence have been propagated through the Bayesian belief network by means of a greedy agglomerative search process including: consider all pairs of clusters; evaluating a set of edges connecting one sample in one cluster to another sample in another cluster to choose one pair of clusters; and merging repeatedly the chosen pair of clusters to create a larger cluster until only one cluster results. 5. The method of claim 4 , wherein the greedy agglomerative search process further includes: assigning a score to each of the pairs of clusters, the score being a product of probabilities associated with the edges and a pair of clusters with a highest score being merged when the merging is repeated. | 0.5 |
8,584,226 | 1 | 17 | 1. A method for a geographic country of origin filter of information transmitting on a network: a) a network object on which the method is embodied, which extracts a network address from Internet traffic routed or collected by said network object; and performs at least one data lookup operation to obtain country of origin geographic information pertaining to said Internet network address; b) configuring said geographic country of origin filter by: Sending or receiving information used to generate a set of persistent geographic country of origin associations comprising a plurality of Internet address blocks; Performing at least one data processing operating to associate a geographic country of origin location pertaining to each block; and Generating at least one geographic country of origin security assertion wherein a device action is defined for at least one geographic country of origin association wherein the device action is triggered for any Internet address belonging to a defined network address block having an estimated country of origin geographic location, wherein the device action either: Allows Internet traffic to be sent or received from said Internet address to the desired destination; Disallows Internet traffic to be sent or received from said Internet address to the desired destination; or Mows Internet traffic to be sent or received from said Internet address to an undesired destination determined by said geographic filter; c) Optimizing said geographic country of origin information pertaining to Internet network addresses in accordance with at least one algorithm, wherein an algorithm is applied to the plurality of geographic country of origin associations between IP address blocks and geographic country of origin locations. | 1. A method for a geographic country of origin filter of information transmitting on a network: a) a network object on which the method is embodied, which extracts a network address from Internet traffic routed or collected by said network object; and performs at least one data lookup operation to obtain country of origin geographic information pertaining to said Internet network address; b) configuring said geographic country of origin filter by: Sending or receiving information used to generate a set of persistent geographic country of origin associations comprising a plurality of Internet address blocks; Performing at least one data processing operating to associate a geographic country of origin location pertaining to each block; and Generating at least one geographic country of origin security assertion wherein a device action is defined for at least one geographic country of origin association wherein the device action is triggered for any Internet address belonging to a defined network address block having an estimated country of origin geographic location, wherein the device action either: Allows Internet traffic to be sent or received from said Internet address to the desired destination; Disallows Internet traffic to be sent or received from said Internet address to the desired destination; or Mows Internet traffic to be sent or received from said Internet address to an undesired destination determined by said geographic filter; c) Optimizing said geographic country of origin information pertaining to Internet network addresses in accordance with at least one algorithm, wherein an algorithm is applied to the plurality of geographic country of origin associations between IP address blocks and geographic country of origin locations. 17. The method of claim 1 , wherein the information used to generate a set of persistent geographic associations is retrieved by an automated process. | 0.778761 |
9,769,208 | 1 | 8 | 1. A method for building a security policy query component executable by a processor, the method comprising the steps of: (a) providing subjects and permissions related to making a security policy decision, as well as a training set of permission-to-subject assignments, as inputs to the security policy query component; (b) extracting semantic attributes from natural language freeform text descriptions of the subjects and the permissions, wherein the step (b) of extracting the semantic attributes comprises the step of: building subject-topic models and permission-topic models independently for the subjects and the permissions directly from the natural language freeform text descriptions of the subjects and the permissions; and (c) using machine learning to build the security policy query component based on the permission-to-subject assignments in the training set and the semantic attributes extracted in step (b), wherein the step (c) of using machine learning to build the security policy query component comprises the step of: using assignment of permissions-to-subjects and non-assignment of permissions-to-subjects in the training set as classes to build classifiers with the subject-topic models and the permission-topic models as features. | 1. A method for building a security policy query component executable by a processor, the method comprising the steps of: (a) providing subjects and permissions related to making a security policy decision, as well as a training set of permission-to-subject assignments, as inputs to the security policy query component; (b) extracting semantic attributes from natural language freeform text descriptions of the subjects and the permissions, wherein the step (b) of extracting the semantic attributes comprises the step of: building subject-topic models and permission-topic models independently for the subjects and the permissions directly from the natural language freeform text descriptions of the subjects and the permissions; and (c) using machine learning to build the security policy query component based on the permission-to-subject assignments in the training set and the semantic attributes extracted in step (b), wherein the step (c) of using machine learning to build the security policy query component comprises the step of: using assignment of permissions-to-subjects and non-assignment of permissions-to-subjects in the training set as classes to build classifiers with the subject-topic models and the permission-topic models as features. 8. The method of claim 1 , further comprising the step of: using the security policy query component in making the security policy decision. | 0.646465 |
9,444,772 | 13 | 14 | 13. A system comprising: a processor; and computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: receiving a question from an asker in which the question is associated with one or more topics; selecting a plurality of candidate answerers based at least partly on each candidate answerer's respective social relationship to the asker within a computer-implemented social network; determining a respective wait time for each candidate answerer in the plurality of candidate answerers, where the respective wait time is based on one or more of a respective communication channel used by the candidate answerer and a historical responsiveness of the candidate answerer for the respective communication channel, wherein the respective communication channel comprising one of an instant message, an electronic mail, a blog post, and a short message service message; selecting a first candidate answerer based on a ranking of the plurality of candidate answerers; sending the question to the first candidate answerer of the plurality of candidate answerers through the respective communication channel of the first candidate answerer; determining that the respective wait time of the first candidate answerer for a first answer from the first candidate answerer has expired without receiving the first answer, and in response: selecting a second candidate answerer based on the ranking of the plurality of candidate answerers, and sending the question to the second candidate answerer of the plurality of candidate answerers through the respective communication channel of the second candidate answerer; receiving a second answer to the question from the second candidate answerer; and sending the second answer to the asker and information that identifies the second answerer. | 13. A system comprising: a processor; and computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: receiving a question from an asker in which the question is associated with one or more topics; selecting a plurality of candidate answerers based at least partly on each candidate answerer's respective social relationship to the asker within a computer-implemented social network; determining a respective wait time for each candidate answerer in the plurality of candidate answerers, where the respective wait time is based on one or more of a respective communication channel used by the candidate answerer and a historical responsiveness of the candidate answerer for the respective communication channel, wherein the respective communication channel comprising one of an instant message, an electronic mail, a blog post, and a short message service message; selecting a first candidate answerer based on a ranking of the plurality of candidate answerers; sending the question to the first candidate answerer of the plurality of candidate answerers through the respective communication channel of the first candidate answerer; determining that the respective wait time of the first candidate answerer for a first answer from the first candidate answerer has expired without receiving the first answer, and in response: selecting a second candidate answerer based on the ranking of the plurality of candidate answerers, and sending the question to the second candidate answerer of the plurality of candidate answerers through the respective communication channel of the second candidate answerer; receiving a second answer to the question from the second candidate answerer; and sending the second answer to the asker and information that identifies the second answerer. 14. The system of claim 13 , where selecting the plurality of candidate answerers comprises selecting candidate answerers that communicate using a communication channel of the asker. | 0.855096 |
9,870,393 | 12 | 13 | 12. A computer-implemented method comprising: receiving a graph query on data representing a graph including a plurality of nodes, the graph query involving a traversal from a source node to a sink node that is adjacent to the source node; converting the graph query into a structured query language (SQL) query over the first table and a second table; retrieving, from a source table in a relational database, a record corresponding to the source node, the record containing a multi-valued field that stores a multi-valued non-local property of the source node, the multi-valued non-local property including a reference to at least one adjacent node of the source node; obtaining, based on the multi-valued non-local property of the source node, data of the sink node from a sink table with the SQL query; storing, for each node in the graph, an adjacency list in the multi-valued field, the adjacency list containing the reference to the at least one adjacent node; transforming the adjacency list to a temporary table; and using the temporary table to locate the corresponding record. | 12. A computer-implemented method comprising: receiving a graph query on data representing a graph including a plurality of nodes, the graph query involving a traversal from a source node to a sink node that is adjacent to the source node; converting the graph query into a structured query language (SQL) query over the first table and a second table; retrieving, from a source table in a relational database, a record corresponding to the source node, the record containing a multi-valued field that stores a multi-valued non-local property of the source node, the multi-valued non-local property including a reference to at least one adjacent node of the source node; obtaining, based on the multi-valued non-local property of the source node, data of the sink node from a sink table with the SQL query; storing, for each node in the graph, an adjacency list in the multi-valued field, the adjacency list containing the reference to the at least one adjacent node; transforming the adjacency list to a temporary table; and using the temporary table to locate the corresponding record. 13. The method of claim 12 , wherein the temporary table is a junction table and obtaining the data of the sink node comprises: creating the junction table that associates the source node and the reference to the at least one adjacent node; and obtaining the data of the sink node with a join between the junction table and the sink table. | 0.752915 |
8,818,998 | 1 | 3 | 1. An apparatus for analyzing non-deterministic results of a search query of data representing analogue information, such as audio data, comprising: a processor and a user interface, the processor being operably in communication with a plurality of audio data sources or databases representing the content thereof and adapted to communicate with the user interface which enables the user to query one or more audio data sources for the presence of search constituents within the audio data, wherein the processor is adapted to determine the non-deterministic likelihood of occurrence of the search constituent within at least part of each of the searched data sources for a user query and the user interface is adapted to present to the user the search results in a form including: a portlet presenting the overall search results (such as search strings) against part or all of the search query structure for a data source(s); a portlet presenting the data source (such as by source name) of one or more data source(s); a portlet presenting a data source filter tree for selecting currently active source(s); a portlet presenting the hit(s) of the search phrase(s) for a data source; and a portlet presenting the hit location(s) within a data source, and wherein at least one of the portlets presents the user with information related to the non-deterministic likelihood of occurrence of the search constituent as a probability of the relevance of a searched data source of the search query and parts of the search query, and the user interface further enabling the user to select and inspect at least part of the searched data source(s) for the presence of the search constituents; wherein each of the portlets is presented to the user with relevancy scores to the data as determined by the non-deterministic results and each portlet is updated and synchronized during a change-of-state cascade event whenever the state is changed within any one of the portlets; and wherein each of the portlets enable a user to edit the probable relevance of the data source, convert the non-deterministic results that are returned by the search of the audio data to deterministic results based on the relevancy score by the user interaction with the data source, and altering the relevance of that data source computed for the overall query. | 1. An apparatus for analyzing non-deterministic results of a search query of data representing analogue information, such as audio data, comprising: a processor and a user interface, the processor being operably in communication with a plurality of audio data sources or databases representing the content thereof and adapted to communicate with the user interface which enables the user to query one or more audio data sources for the presence of search constituents within the audio data, wherein the processor is adapted to determine the non-deterministic likelihood of occurrence of the search constituent within at least part of each of the searched data sources for a user query and the user interface is adapted to present to the user the search results in a form including: a portlet presenting the overall search results (such as search strings) against part or all of the search query structure for a data source(s); a portlet presenting the data source (such as by source name) of one or more data source(s); a portlet presenting a data source filter tree for selecting currently active source(s); a portlet presenting the hit(s) of the search phrase(s) for a data source; and a portlet presenting the hit location(s) within a data source, and wherein at least one of the portlets presents the user with information related to the non-deterministic likelihood of occurrence of the search constituent as a probability of the relevance of a searched data source of the search query and parts of the search query, and the user interface further enabling the user to select and inspect at least part of the searched data source(s) for the presence of the search constituents; wherein each of the portlets is presented to the user with relevancy scores to the data as determined by the non-deterministic results and each portlet is updated and synchronized during a change-of-state cascade event whenever the state is changed within any one of the portlets; and wherein each of the portlets enable a user to edit the probable relevance of the data source, convert the non-deterministic results that are returned by the search of the audio data to deterministic results based on the relevancy score by the user interaction with the data source, and altering the relevance of that data source computed for the overall query. 3. The apparatus according to claim 1 , wherein at least three portlets are provided and the probable relevance of a search query for a data source is presented in at least two portlets. | 0.776978 |
8,639,763 | 1 | 4 | 1. A method performed by a first extensible markup language (XML) document management (XDM) server, the method comprising: receiving, from a second XDM server, an XML document command protocol (XDCP) forward request specifying a first uniform resource identifier (URI) corresponding to contact information to be forwarded to a recipient according to a contact share request from a converged address book (CAB) client, the XDCP forward request further specifying a second URI corresponding to the recipient; if preference information indicates that the recipient will accept the contact information to be forwarded: receiving the contact information from the second XDM server; and providing the contact information for storage in an address book of the recipient. | 1. A method performed by a first extensible markup language (XML) document management (XDM) server, the method comprising: receiving, from a second XDM server, an XML document command protocol (XDCP) forward request specifying a first uniform resource identifier (URI) corresponding to contact information to be forwarded to a recipient according to a contact share request from a converged address book (CAB) client, the XDCP forward request further specifying a second URI corresponding to the recipient; if preference information indicates that the recipient will accept the contact information to be forwarded: receiving the contact information from the second XDM server; and providing the contact information for storage in an address book of the recipient. 4. A method as defined in claim 1 wherein the XDCP forward request further specifies filter information to filter details from the contact information. | 0.665929 |
10,102,277 | 1 | 19 | 1. A method for user identification of a desired document, comprising: providing, accessibly to a computer system, a database identifying a catalog of documents in an embedding space; calculating a Prior probability score for each document of a candidate list including at least a portion of the documents of the embedding space, the Prior probability score indicating a preliminary probability, for each particular document of the candidate list, that the particular document is the desired document; a computer system identifying toward the user an initial (i=0) collection of N0>1 candidate documents from the candidate list in dependence on the calculated Prior probability scores for the documents in the candidate list, the initial collection of candidate documents having fewer documents than the candidate list; and for each i'th iteration in a plurality of iterations, beginning with a first iteration (i=1) and in response to user selection of an i'th selected document from the (i−1)'th collection of candidate documents, identifying toward the user an i'th collection of Ni>1 candidate documents from the candidate list in dependence on Posterior probability scores for at least a portion of the documents in the candidate list, Ni being smaller than the number of documents in the candidate list, the Posterior probability score for each given document D being given by P(C|D)P(D), where C is the sequence of documents c 1 , . . . , c i selected by the user up through the i'th iteration, where P(C|D) is the system's view of the probability of C if the desired document is D and where P(D) is the calculated Prior probability score for document D. | 1. A method for user identification of a desired document, comprising: providing, accessibly to a computer system, a database identifying a catalog of documents in an embedding space; calculating a Prior probability score for each document of a candidate list including at least a portion of the documents of the embedding space, the Prior probability score indicating a preliminary probability, for each particular document of the candidate list, that the particular document is the desired document; a computer system identifying toward the user an initial (i=0) collection of N0>1 candidate documents from the candidate list in dependence on the calculated Prior probability scores for the documents in the candidate list, the initial collection of candidate documents having fewer documents than the candidate list; and for each i'th iteration in a plurality of iterations, beginning with a first iteration (i=1) and in response to user selection of an i'th selected document from the (i−1)'th collection of candidate documents, identifying toward the user an i'th collection of Ni>1 candidate documents from the candidate list in dependence on Posterior probability scores for at least a portion of the documents in the candidate list, Ni being smaller than the number of documents in the candidate list, the Posterior probability score for each given document D being given by P(C|D)P(D), where C is the sequence of documents c 1 , . . . , c i selected by the user up through the i'th iteration, where P(C|D) is the system's view of the probability of C if the desired document is D and where P(D) is the calculated Prior probability score for document D. 19. The method of claim 1 , wherein identifying toward the user an i'th collection of documents comprises: calculating the Posterior probability scores for at least a subset of more than Ni of the candidate documents from the candidate list; and identifying toward the user the candidate documents having the Ni highest calculated Posterior probability scores. | 0.869565 |
9,953,636 | 6 | 7 | 6. The method of claim 1 , further comprising receiving a verbal command for an application that is associated, using a recognizer implementing the language model, with a text command. | 6. The method of claim 1 , further comprising receiving a verbal command for an application that is associated, using a recognizer implementing the language model, with a text command. 7. The method of claim 6 , wherein the language model assigns the verbal command to a sub-grammar slot. | 0.5 |
7,754,955 | 1 | 28 | 1. An integrated interactive electronic virtual reality multimedia recording and learning platform and system adapted for a top down butterfly morpheus music notation comprising: a) a central processing unit complete with plurality of input means, output means and a variety of memory means; b) a butterfly morpheus musical instrument with plurality of manual input means each with a first unique visible indicia interfaced to said central processing unit; c) a plurality of finger adapters each with a second unique visible indicia donned on respective fingers; d) a first custom butterfly morpheus music notation computer interface comprising a plurality of bars, staves, scales, keys chords, arpeggios, notes frequencies customized to said music instrument and said finger adapters; e) a second custom butterfly morpheus music notation computer interface comprising a plurality of virtual characters assigned to specific positional coordinates, virtual musical instruments representations vertical/horizontal scroll bars and a virtual command screen display; f) a custom graphics tablet connected to said computer with plurality of input means, output means and a variety of memory means; g) a custom Digital Stylus interfaced between said plurality of input means and said central processing unit; h) a custom set of external controllers for controlling and executing said input and output of commands requested by the user utilizing a new generation music notation system, routed through said central processing unit; i) a custom playback means with plurality of input and output means interfaced to said CPU of said system; j) a custom color designation means applied upon said first unique visible indicia to indicate eight specific note value lengths; and k) a custom midi interactive program operable in said central processing unit to display program messages and specific notes utilizing said first visible indicia, specific hand configurations utilizing said second visible indicia and specific note value lengths utilizing said eight specific colors. | 1. An integrated interactive electronic virtual reality multimedia recording and learning platform and system adapted for a top down butterfly morpheus music notation comprising: a) a central processing unit complete with plurality of input means, output means and a variety of memory means; b) a butterfly morpheus musical instrument with plurality of manual input means each with a first unique visible indicia interfaced to said central processing unit; c) a plurality of finger adapters each with a second unique visible indicia donned on respective fingers; d) a first custom butterfly morpheus music notation computer interface comprising a plurality of bars, staves, scales, keys chords, arpeggios, notes frequencies customized to said music instrument and said finger adapters; e) a second custom butterfly morpheus music notation computer interface comprising a plurality of virtual characters assigned to specific positional coordinates, virtual musical instruments representations vertical/horizontal scroll bars and a virtual command screen display; f) a custom graphics tablet connected to said computer with plurality of input means, output means and a variety of memory means; g) a custom Digital Stylus interfaced between said plurality of input means and said central processing unit; h) a custom set of external controllers for controlling and executing said input and output of commands requested by the user utilizing a new generation music notation system, routed through said central processing unit; i) a custom playback means with plurality of input and output means interfaced to said CPU of said system; j) a custom color designation means applied upon said first unique visible indicia to indicate eight specific note value lengths; and k) a custom midi interactive program operable in said central processing unit to display program messages and specific notes utilizing said first visible indicia, specific hand configurations utilizing said second visible indicia and specific note value lengths utilizing said eight specific colors. 28. The integrated interactive electronic virtual reality multimedia recording and learning environment adapted for a top down butterfly morpheus music notation system of claim 1 wherein a custom said color designation means applied upon said first unique visible indicia indicates the eight specific note value lengths of music. | 0.877604 |
8,793,646 | 3 | 4 | 3. The method of claim 1 , wherein said aggregating comprises writing references to the plurality of constraints into a definition of the stereotype of the first profile. | 3. The method of claim 1 , wherein said aggregating comprises writing references to the plurality of constraints into a definition of the stereotype of the first profile. 4. The method of claim 3 further comprising writing references to the second profile and the third profile into the definition of the stereotype of the first profile. | 0.5 |
8,126,712 | 17 | 18 | 17. The information communication terminal according to claim 1 , wherein the subject extraction processing module calculates, depending on a distance of the shortest route, an evaluation value of a word positioned at an end of the shortest route to give the word existing on the shortest distance a point considering the evaluation value. | 17. The information communication terminal according to claim 1 , wherein the subject extraction processing module calculates, depending on a distance of the shortest route, an evaluation value of a word positioned at an end of the shortest route to give the word existing on the shortest distance a point considering the evaluation value. 18. The information communication terminal according to claim 17 , wherein the subject extraction processing module gives a higher point to a word existing on the shortest distance as the shortest route has a shorter distance. | 0.581481 |
8,151,292 | 1 | 25 | 1. A system comprising: a processor coupled to a database, the database including a media instance and reaction data, the media instance comprising a plurality of media events, the reaction data received from a plurality of viewers viewing the media instance; a first module coupled to the processor, the first module generating aggregated reaction data by aggregating the reaction data from the plurality of viewers, the first module generating synchronized data by synchronizing the plurality of media events of the media instance with corresponding aggregated reaction data; and a second module coupled to the processor, the second module comprising a plurality of renderings and a user interface (UI) that provide controlled access to the synchronized data from a remote device, wherein the controlled access includes interactive control of analysis of the reaction data and the corresponding events of the media instance. | 1. A system comprising: a processor coupled to a database, the database including a media instance and reaction data, the media instance comprising a plurality of media events, the reaction data received from a plurality of viewers viewing the media instance; a first module coupled to the processor, the first module generating aggregated reaction data by aggregating the reaction data from the plurality of viewers, the first module generating synchronized data by synchronizing the plurality of media events of the media instance with corresponding aggregated reaction data; and a second module coupled to the processor, the second module comprising a plurality of renderings and a user interface (UI) that provide controlled access to the synchronized data from a remote device, wherein the controlled access includes interactive control of analysis of the reaction data and the corresponding events of the media instance. 25. The system of claim 1 , wherein the reaction data includes physiological responses. | 0.861022 |
8,863,128 | 9 | 12 | 9. A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to optimized a task graph that delineates a plurality of tasks to be evaluated in a parallel processing environment, by performing the steps of: generating a first task aggregation topology associated with the task graph that divides the plurality of tasks into a first collection of sets, wherein each set in the first collection of sets includes one or more tasks from the plurality of tasks, each task of the plurality of tasks belongs to only one set included in the first collection of sets, and the first task aggregation topology comprises a bit mask that indicates two or more tasks of the plurality of tasks that are included in a first set in the first collection of sets; compiling the plurality of tasks according to the first task aggregation topology to generate units of work to be executed in the parallel processing environment, wherein the two or more tasks included in the first set are compiled to generate a single unit of work that is executed by a first processing engine included in the parallel processing environment; collecting statistics associated with executing the units of work in the parallel processing environment; and determining whether the first task aggregation topology is more efficient in execution than any previously-defined task aggregation topology based on the statistics; and if the task aggregation topology is more efficient in execution than any previously-defined task aggregation topology, then selecting the first task aggregation topology as the most optimal task aggregation topology, or if the first task aggregation topology is not more efficient in execution than any previously-defined task aggregation topology, then selecting a second task aggregation topology as the most optimal task aggregation topology. | 9. A non-transitory computer readable medium storing instructions that, when executed by a processor, cause the processor to optimized a task graph that delineates a plurality of tasks to be evaluated in a parallel processing environment, by performing the steps of: generating a first task aggregation topology associated with the task graph that divides the plurality of tasks into a first collection of sets, wherein each set in the first collection of sets includes one or more tasks from the plurality of tasks, each task of the plurality of tasks belongs to only one set included in the first collection of sets, and the first task aggregation topology comprises a bit mask that indicates two or more tasks of the plurality of tasks that are included in a first set in the first collection of sets; compiling the plurality of tasks according to the first task aggregation topology to generate units of work to be executed in the parallel processing environment, wherein the two or more tasks included in the first set are compiled to generate a single unit of work that is executed by a first processing engine included in the parallel processing environment; collecting statistics associated with executing the units of work in the parallel processing environment; and determining whether the first task aggregation topology is more efficient in execution than any previously-defined task aggregation topology based on the statistics; and if the task aggregation topology is more efficient in execution than any previously-defined task aggregation topology, then selecting the first task aggregation topology as the most optimal task aggregation topology, or if the first task aggregation topology is not more efficient in execution than any previously-defined task aggregation topology, then selecting a second task aggregation topology as the most optimal task aggregation topology. 12. The non-transitory computer readable medium of claim 9 , wherein the execution statistics include a total amount of memory consumed when executing the units of work in the parallel processing environment. | 0.784679 |
9,779,080 | 10 | 16 | 10. A non-transitory computer-readable storage medium containing a computer-readable code that when read by a computer causes the computer to perform a method for text auto-correction, the method comprising: receiving an input text string on an electronic text input interface device, the input text string comprising N words and a categorical topic; generating a subsequent text string comprising a plurality of N−1 subsequent words forming a subsequent phrase within the categorical topic by determining probabilities that the N−1 subsequent words follow the N words in the input test string; generating a preceding text string comprising a plurality of N−1 preceding words forming a preceding phrase for the input text string within the categorical topic by determining probabilities that the N−1 preceding words following precede the N words in the input test string; creating a corrected text string by inserting the preceding phrase before the input text string and appending the subsequent phrase after the input text string; and displaying the corrected text string on the electronic text input interface device. | 10. A non-transitory computer-readable storage medium containing a computer-readable code that when read by a computer causes the computer to perform a method for text auto-correction, the method comprising: receiving an input text string on an electronic text input interface device, the input text string comprising N words and a categorical topic; generating a subsequent text string comprising a plurality of N−1 subsequent words forming a subsequent phrase within the categorical topic by determining probabilities that the N−1 subsequent words follow the N words in the input test string; generating a preceding text string comprising a plurality of N−1 preceding words forming a preceding phrase for the input text string within the categorical topic by determining probabilities that the N−1 preceding words following precede the N words in the input test string; creating a corrected text string by inserting the preceding phrase before the input text string and appending the subsequent phrase after the input text string; and displaying the corrected text string on the electronic text input interface device. 16. The non-transitory computer-readable medium of claim 10 , wherein: the method further comprises determining the categorical topic related to the N words. | 0.928441 |
9,015,150 | 11 | 20 | 11. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: receiving a request for data; identifying a group of results responsive to the request, each result in the group of results comprising values assigned to fields in a common set of fields; calculating relevance scores for the fields in the common set of fields; selecting from the common set of fields, based on a comparison of the relevance scores, a subset of highly relevant fields for the group of results, the subset of highly relevant fields being smaller than the common set of fields; generating, for each result in the group of results, a respective view of data in said each result, the view emphasizing data for the subset of highly relevant fields for the group of results; and generating a report comprising, for each result in the group of results, the respective view of data in said each result. | 11. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: receiving a request for data; identifying a group of results responsive to the request, each result in the group of results comprising values assigned to fields in a common set of fields; calculating relevance scores for the fields in the common set of fields; selecting from the common set of fields, based on a comparison of the relevance scores, a subset of highly relevant fields for the group of results, the subset of highly relevant fields being smaller than the common set of fields; generating, for each result in the group of results, a respective view of data in said each result, the view emphasizing data for the subset of highly relevant fields for the group of results; and generating a report comprising, for each result in the group of results, the respective view of data in said each result. 20. The one or more non-transitory computer-readable media of claim 11 , wherein the request comprises search terms. | 0.846154 |
8,775,403 | 1 | 2 | 1. A method of scheduling document indexing, comprising: at a computing system having one or more processors and memory storing programs for execution by the one or more processors: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a rank of the corresponding document relative to other documents in a set of documents; determining a first score for the document identifier that is a function of the determined query-independent score, a determined content change frequency of the corresponding document, and an age of the corresponding document; comparing the first score against a threshold value thereby obtaining a result, wherein the threshold value is a function of a speed of the engine crawler system; and conditionally scheduling the corresponding document for indexing based on the result. | 1. A method of scheduling document indexing, comprising: at a computing system having one or more processors and memory storing programs for execution by the one or more processors: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a rank of the corresponding document relative to other documents in a set of documents; determining a first score for the document identifier that is a function of the determined query-independent score, a determined content change frequency of the corresponding document, and an age of the corresponding document; comparing the first score against a threshold value thereby obtaining a result, wherein the threshold value is a function of a speed of the engine crawler system; and conditionally scheduling the corresponding document for indexing based on the result. 2. The method of claim 1 , wherein the first score for the document identifier is a function of the determined query-independent score. | 0.747191 |
8,396,783 | 1 | 6 | 1. An online computer network implemented method for arranging delivery of personal medical and/or healthcare services, said method comprising: configuring at least one computer data processor coupled to a communications network to effect posting, for accessing by other processors via said communications network, at least one proffered medical service in association with information identifying a provider of such service; defining and posting online via said computer data processor a complexity rating scale having one or more levels of medical procedural complexity and associated rating values for use by prospective online bidders; receiving, via said communications network, a bid to hire a provider for a proffered service; and receiving with said bid an online complexity rating value associated therewith , the complexity rating value having an indication of an estimated medical procedural complexity level based on concurrent personal medical problems/pre-existing conditions known to the bidder. | 1. An online computer network implemented method for arranging delivery of personal medical and/or healthcare services, said method comprising: configuring at least one computer data processor coupled to a communications network to effect posting, for accessing by other processors via said communications network, at least one proffered medical service in association with information identifying a provider of such service; defining and posting online via said computer data processor a complexity rating scale having one or more levels of medical procedural complexity and associated rating values for use by prospective online bidders; receiving, via said communications network, a bid to hire a provider for a proffered service; and receiving with said bid an online complexity rating value associated therewith , the complexity rating value having an indication of an estimated medical procedural complexity level based on concurrent personal medical problems/pre-existing conditions known to the bidder. 6. An online computerized method as in claim 1 further comprising posting online a complexity rating scale which defines levels of medical procedure complexity and associates rating values for each level for use by a physician/provider of such proffered service in setting a price adjustment to a submitted bid for such service. | 0.5 |
8,010,358 | 3 | 4 | 3. The method of claim 1 wherein obtaining a voice signal includes over-sampling the voice signal at a sampling frequency that is greater than a working feature analysis frequency. | 3. The method of claim 1 wherein obtaining a voice signal includes over-sampling the voice signal at a sampling frequency that is greater than a working feature analysis frequency. 4. The method of claim 3 wherein the sampling frequency is greater than a training time speech sampling rate. | 0.5 |
8,150,698 | 23 | 25 | 23. A method for invoking a tapered prompt associated with a multimodal application, the method being implemented on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the method comprising acts of: identifying a first prompt element and a second prompt element of the tapered prompt; identifying a first value of at least one first attribute associated with the first prompt element; rendering a first multimodal prompt associated with the first prompt element in a first style selected from a plurality of styles based at least in part on the first value of the at least one first attribute, the first multimodal prompt comprising a first speech prompt and a first textual prompt, the first style comprising a first speech style for the first speech prompt and a first textual style for the first textual prompt; identifying a second value of at least one second attribute associated with the second prompt element; and rendering a second multimodal prompt associated with the second prompt element in a second style selected from the plurality of styles based at least in part on the second value of the at least one second attribute, the second multimodal prompt comprising a second speech prompt and a second textual prompt, the second style comprising a second speech style for the second speech prompt and a second textual style for the second textual prompt, the second speech style being different from the first speech style, the second textual style being different from the first textual style and being selected to match the second speech style. | 23. A method for invoking a tapered prompt associated with a multimodal application, the method being implemented on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the method comprising acts of: identifying a first prompt element and a second prompt element of the tapered prompt; identifying a first value of at least one first attribute associated with the first prompt element; rendering a first multimodal prompt associated with the first prompt element in a first style selected from a plurality of styles based at least in part on the first value of the at least one first attribute, the first multimodal prompt comprising a first speech prompt and a first textual prompt, the first style comprising a first speech style for the first speech prompt and a first textual style for the first textual prompt; identifying a second value of at least one second attribute associated with the second prompt element; and rendering a second multimodal prompt associated with the second prompt element in a second style selected from the plurality of styles based at least in part on the second value of the at least one second attribute, the second multimodal prompt comprising a second speech prompt and a second textual prompt, the second style comprising a second speech style for the second speech prompt and a second textual style for the second textual prompt, the second speech style being different from the first speech style, the second textual style being different from the first textual style and being selected to match the second speech style. 25. The method of claim 23 , wherein the at least one first attribute comprises a prompt counter shadow variable and a source expression attribute whose value depends upon a value of the prompt counter shadow variable, and wherein the method further comprises: identifying the first speech prompt based at least in part on the value of the source expression attribute. | 0.5 |
7,479,943 | 1 | 6 | 1. A portable electronic system comprising: a processor; a bus coupled to said processor; an electronic display device coupled to said bus; a memory device coupled to said bus; and a user removable data input device providing a plurality of different methods of data input to the portable electronic system coupled to said bus, said user removable data input device comprising: a data input surface for detecting a gesture performed thereon by a user and for facilitating recognition of said gesture as corresponding to a particular data input, wherein said data input surface is responsive to a touch thereon and is in a location relative to a perimeter of said electronic display device that is spaced from the electronic display device, wherein said data input surface has one of a plurality of marking configurations, wherein each marking configuration facilitates operating said data input surface in one of a plurality of functional configurations, wherein said data input surface includes a first data input area and a second data input area, wherein said first data input area is configured to facilitate recognition of one or more first gestures, and wherein said second data input area is configured to facilitate recognition of one or more second gestures associated with one of said functional configurations, and wherein said user removable data input device is configured to couple to said portable electronic system and to uncouple from said portable electronic system. | 1. A portable electronic system comprising: a processor; a bus coupled to said processor; an electronic display device coupled to said bus; a memory device coupled to said bus; and a user removable data input device providing a plurality of different methods of data input to the portable electronic system coupled to said bus, said user removable data input device comprising: a data input surface for detecting a gesture performed thereon by a user and for facilitating recognition of said gesture as corresponding to a particular data input, wherein said data input surface is responsive to a touch thereon and is in a location relative to a perimeter of said electronic display device that is spaced from the electronic display device, wherein said data input surface has one of a plurality of marking configurations, wherein each marking configuration facilitates operating said data input surface in one of a plurality of functional configurations, wherein said data input surface includes a first data input area and a second data input area, wherein said first data input area is configured to facilitate recognition of one or more first gestures, and wherein said second data input area is configured to facilitate recognition of one or more second gestures associated with one of said functional configurations, and wherein said user removable data input device is configured to couple to said portable electronic system and to uncouple from said portable electronic system. 6. A portable electronic system as recited in claim 1 wherein said second data input area is an electronic game control template wherein any one of a plurality of electronic game controls is selected by performing said one or more second gestures. | 0.539179 |
9,514,222 | 1 | 17 | 1. A method for configuring a computer system to provide a set of selectable topic names on an interface for providing access to stored electronic resources by topic name, at least some of which are assigned to named storage sets in a folder structure, the method comprising: (1) determining a topic framework for providing the set of topic names for providing access to the electronic resources by topic name on the interface, the topic framework storing topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names by: (i) determining the topic names for the topic framework from the names assigned to storage sets and the attributes of individual electronic resources by: generating one or more topic names from the names assigned to storage sets; and generating one or more topic names from attributes of individual electronic resources; and (ii) forming the associations between each of the stored electronic resources and one or more topic names by: associating electronic resources assigned to a storage set with one or more topic names which were generated from the name of the storage set; and associating electronic resources having an attribute or attributes with one or more topic names which were generated from the respective attribute or attributes of the electronic resources; (iii) associating one or more topic names with one or more other topic names by: generating associations between topic names from the relationships within the folder structure between the respective storage sets from which the topic names were generated; (2) storing the topic framework to provide the set of topic names for providing access to the electronic resources by topic name on the interface, wherein the topic framework stores the set of topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names; and (3) using the topic framework to configure the computer system to present the interface through which: (i) a list of topic names is presented through which one or more topic names of the topic framework are selectable; (ii) when a topic name associated by the topic framework with one or more other topic names is selected, at least a list of the one or more other topic names is presented through which the one or more other topic names are selectable; and (iii) a group of stored electronic resources associated with a selected one or more topic names is presented so that one or more of the group of electronic resources can be selected for access. | 1. A method for configuring a computer system to provide a set of selectable topic names on an interface for providing access to stored electronic resources by topic name, at least some of which are assigned to named storage sets in a folder structure, the method comprising: (1) determining a topic framework for providing the set of topic names for providing access to the electronic resources by topic name on the interface, the topic framework storing topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names by: (i) determining the topic names for the topic framework from the names assigned to storage sets and the attributes of individual electronic resources by: generating one or more topic names from the names assigned to storage sets; and generating one or more topic names from attributes of individual electronic resources; and (ii) forming the associations between each of the stored electronic resources and one or more topic names by: associating electronic resources assigned to a storage set with one or more topic names which were generated from the name of the storage set; and associating electronic resources having an attribute or attributes with one or more topic names which were generated from the respective attribute or attributes of the electronic resources; (iii) associating one or more topic names with one or more other topic names by: generating associations between topic names from the relationships within the folder structure between the respective storage sets from which the topic names were generated; (2) storing the topic framework to provide the set of topic names for providing access to the electronic resources by topic name on the interface, wherein the topic framework stores the set of topic names, associations between each of the stored electronic resources and one or more topic names, and associations between topic names; and (3) using the topic framework to configure the computer system to present the interface through which: (i) a list of topic names is presented through which one or more topic names of the topic framework are selectable; (ii) when a topic name associated by the topic framework with one or more other topic names is selected, at least a list of the one or more other topic names is presented through which the one or more other topic names are selectable; and (iii) a group of stored electronic resources associated with a selected one or more topic names is presented so that one or more of the group of electronic resources can be selected for access. 17. A method wherein a topic framework has been created using the method of claim 1 , the method further comprising: partitioning the results of a search based on the topic names of a user's topic framework. | 0.889894 |
9,460,419 | 1 | 8 | 1. A method implemented by at least one computing device of a cloud computing environment, the method comprising: receiving multiple authoring inputs from a document creation client device identifying multiple portions of multiple websites, the multiple authoring inputs including a first authoring input identifying a first author-identified portion of a first website that contains first unstructured data and a second authoring input identifying a second author-identified portion of a second website that contains second unstructured data; obtaining a first pointer that links to the first author-identified portion of the first website; obtaining a second pointer that links to the second author-identified portion of the second website; storing the first pointer to the first author-identified portion of the first website and the second pointer to the second author-identified portion of the second website in a document in the cloud computing environment; receiving validation inputs from a validating client device indicating that the document is a validated document, wherein the validation inputs include a correction to part of the document and the validated document includes the correction; storing the validated document in the cloud computing environment; detecting when the first website and the second website are updated; automatically obtaining updated first unstructured data from the first author-identified portion of the first website via the first pointer stored in the validated document and automatically obtaining updated second unstructured data from the second author-identified portion of the second website via the second pointer stored in the validated document; and providing the updated first unstructured data and the updated second unstructured data to an accessing client device in response to a request by the accessing client device to access the validated document. | 1. A method implemented by at least one computing device of a cloud computing environment, the method comprising: receiving multiple authoring inputs from a document creation client device identifying multiple portions of multiple websites, the multiple authoring inputs including a first authoring input identifying a first author-identified portion of a first website that contains first unstructured data and a second authoring input identifying a second author-identified portion of a second website that contains second unstructured data; obtaining a first pointer that links to the first author-identified portion of the first website; obtaining a second pointer that links to the second author-identified portion of the second website; storing the first pointer to the first author-identified portion of the first website and the second pointer to the second author-identified portion of the second website in a document in the cloud computing environment; receiving validation inputs from a validating client device indicating that the document is a validated document, wherein the validation inputs include a correction to part of the document and the validated document includes the correction; storing the validated document in the cloud computing environment; detecting when the first website and the second website are updated; automatically obtaining updated first unstructured data from the first author-identified portion of the first website via the first pointer stored in the validated document and automatically obtaining updated second unstructured data from the second author-identified portion of the second website via the second pointer stored in the validated document; and providing the updated first unstructured data and the updated second unstructured data to an accessing client device in response to a request by the accessing client device to access the validated document. 8. The method of claim 1 , further comprising: receiving ranking inputs from the other client devices to rank an author of the document and other contributors to the validated document; compiling scores for the author and the other contributors to the validated document based on the ranking inputs; ranking the author and the other contributors based on the compiled scores; and displaying the ranking of the author and the other contributors with the updated first unstructured data and the updated second unstructured data when the validated document is accessed by the other client devices. | 0.5 |
10,032,118 | 11 | 14 | 11. A media processor, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance of operations, the operations comprising: receiving a selection to present a media program as a selected media program; submitting to a device a request for a subset of blogs from a plurality of blogs that are relevant to the selected media program, wherein the device identifies the subset of blogs by performing operations comprising: obtaining, through a search application programming interface, an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a selected media program or not relevant to the selected media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the selected media program with unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify subsets of blogs relevant to the selected media program as selected blogs; performing a sentiment analysis on the selected blogs to determine a trend based on pattern recognition, wherein the trend is related to the selected media program; concurrently presenting a graphical user interface that presents the selected blogs, the trend, and the selected media program; subdividing the subset of blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. | 11. A media processor, comprising: a memory that stores instructions; and a processing system including a processor coupled to the memory, wherein execution of the instructions facilitates performance of operations, the operations comprising: receiving a selection to present a media program as a selected media program; submitting to a device a request for a subset of blogs from a plurality of blogs that are relevant to the selected media program, wherein the device identifies the subset of blogs by performing operations comprising: obtaining, through a search application programming interface, an initial set of annotated blogs, wherein the initial set of annotated blogs are annotated as being either relevant to a selected media program or not relevant to the selected media program; training a first classifier based on the initial set of annotated blogs to generate a trained first classifier; applying the trained first classifier to unannotated blogs from the plurality of blogs to generate a first set of features associating the selected media program with unannotated blogs; training a second classifier according to the first set of features generated by the trained first classifier to generate a trained second classifier; and applying the trained second classifier to the plurality of blogs to identify subsets of blogs relevant to the selected media program as selected blogs; performing a sentiment analysis on the selected blogs to determine a trend based on pattern recognition, wherein the trend is related to the selected media program; concurrently presenting a graphical user interface that presents the selected blogs, the trend, and the selected media program; subdividing the subset of blogs into blog subgroups comprising one of blogs favorable to the media program or blogs unfavorable to the media program; and selecting scheduled media programming according to the subset of blogs. 14. The media processor of claim 11 , wherein the operations further comprise: receiving a blog message; identifying a blog leader associated with the blog message; and directing the blog message to a blog group of the blog leader. | 0.56903 |
8,527,486 | 1 | 8 | 1. A method for performing a text search defined by a plurality of alphanumeric characters and initiated on a first mobile communication device associated with a first user, the method comprising: searching for partial or full matches to the alphanumeric characters on data stored on the first mobile communication device; searching for partial or full matches to the alphanumeric characters on data made available to the first user for sharing by a first plurality of other private users who are within a social mobile network of the first user, said first plurality of other private users being associated with a plurality of mobile communication devices, the first mobile communication device and the plurality of mobile communication devices being in communication with a server; searching for partial or full matches to the alphanumeric characters on application programs running on the plurality of mobile communication devices; and ranking a first partially or fully matching application program name higher than a second partially or fully matching application program name that has been used less frequently than the first partially or fully matching application program; and displaying matching search results. | 1. A method for performing a text search defined by a plurality of alphanumeric characters and initiated on a first mobile communication device associated with a first user, the method comprising: searching for partial or full matches to the alphanumeric characters on data stored on the first mobile communication device; searching for partial or full matches to the alphanumeric characters on data made available to the first user for sharing by a first plurality of other private users who are within a social mobile network of the first user, said first plurality of other private users being associated with a plurality of mobile communication devices, the first mobile communication device and the plurality of mobile communication devices being in communication with a server; searching for partial or full matches to the alphanumeric characters on application programs running on the plurality of mobile communication devices; and ranking a first partially or fully matching application program name higher than a second partially or fully matching application program name that has been used less frequently than the first partially or fully matching application program; and displaying matching search results. 8. The method of claim 1 further comprising: identifying users having matching application programs. | 0.813433 |
8,239,362 | 8 | 11 | 8. A method for dynamically creating work instructions comprising: converting a set of documents to structured XML files and a plurality of tagged elements to create a library; utilizing filter criteria to define manufacturing process to be completed; accessing a web service to apply the filter criteria to identify current files from the library applicable to the manufacturing process; selecting and applying the current files to a plan; and using the plan to complete the manufacturing process. | 8. A method for dynamically creating work instructions comprising: converting a set of documents to structured XML files and a plurality of tagged elements to create a library; utilizing filter criteria to define manufacturing process to be completed; accessing a web service to apply the filter criteria to identify current files from the library applicable to the manufacturing process; selecting and applying the current files to a plan; and using the plan to complete the manufacturing process. 11. The method of claim 8 , further comprising tracking the structured XML files and the plurality of tagged elements to determine the location of the structured XML files and to recognize missing tagged elements. | 0.5 |
7,865,352 | 11 | 12 | 11. The method of claim 8 wherein the textual input comprises a plurality of content words, wherein parsing comprises: parsing the textual input into the plurality of phrases based on the content words. | 11. The method of claim 8 wherein the textual input comprises a plurality of content words, wherein parsing comprises: parsing the textual input into the plurality of phrases based on the content words. 12. The method of claim 11 wherein outputting comprises: outputting the selected textual phrase including both a content word included in the selected textual phrase and the identified grammatical element assigned to the selected textual phrase. | 0.5 |
9,600,228 | 16 | 18 | 16. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform: displaying a user interface configured to enable a user to enter a travel query; storing an accommodation template, an activity template, a plurality of auto-complete rules and a plurality of auto-suggest rules; receiving an initial partial user input; selecting the accommodation template or the activity template based on the initial partial user input; applying the plurality of auto-complete rules and the plurality of auto-suggest rules to generate a complete query, wherein the auto-suggest rules select alternative keywords by classification and the auto-complete rules suggest words to complete the initial partial input based on text characters; wherein auto-complete values for the plurality of auto-complete rules or auto-suggest values for the plurality of auto-suggest values are provided in the form of one or more widgets that offer a visual indicia receptive for user interaction with the user interface. | 16. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform: displaying a user interface configured to enable a user to enter a travel query; storing an accommodation template, an activity template, a plurality of auto-complete rules and a plurality of auto-suggest rules; receiving an initial partial user input; selecting the accommodation template or the activity template based on the initial partial user input; applying the plurality of auto-complete rules and the plurality of auto-suggest rules to generate a complete query, wherein the auto-suggest rules select alternative keywords by classification and the auto-complete rules suggest words to complete the initial partial input based on text characters; wherein auto-complete values for the plurality of auto-complete rules or auto-suggest values for the plurality of auto-suggest values are provided in the form of one or more widgets that offer a visual indicia receptive for user interaction with the user interface. 18. The apparatus of claim 16 , wherein the one or more widgets include a plurality of dialer menus. | 0.514563 |
8,028,239 | 23 | 24 | 23. A computer system comprising: a display; a central processing unit; computer memory; a user interface service stored in computer memory and executable using the central processing unit, the user interface service comprising: a set of management element definitions, the management element definitions comprising respective metadata indications comparable against a current context to determine whether a respective user interface element definition is to be chosen for display and further comprising logic for retrieving data to be displayed, the respective user interface element definition comprising trouble ticket functionality for a managed item; and a first management element definition context-based filter operable to filter before a query to a management element store; a second management element definition context-based filter operable to filter after a query to the management element store, the second management element definition context-based filter being associated with the management element store; a third management element definition context-based filter operable to filter after receiving a definition of a user interface surface, the third management element definition context-based filter being associated with the definition of the user interface surface; wherein the first, second, and third management element definition context-based filters are further operable to compare the current context against the respective metadata indications of the set of management element definitions to determine whether the respective user interface element definition is to be chosen for display; wherein the user interface service supports a hierarchy of user element definition types and wherein the first, second, and third management element definition context-based filters are operable to filter out parent user element types while allowing child user element types to pass through for display. | 23. A computer system comprising: a display; a central processing unit; computer memory; a user interface service stored in computer memory and executable using the central processing unit, the user interface service comprising: a set of management element definitions, the management element definitions comprising respective metadata indications comparable against a current context to determine whether a respective user interface element definition is to be chosen for display and further comprising logic for retrieving data to be displayed, the respective user interface element definition comprising trouble ticket functionality for a managed item; and a first management element definition context-based filter operable to filter before a query to a management element store; a second management element definition context-based filter operable to filter after a query to the management element store, the second management element definition context-based filter being associated with the management element store; a third management element definition context-based filter operable to filter after receiving a definition of a user interface surface, the third management element definition context-based filter being associated with the definition of the user interface surface; wherein the first, second, and third management element definition context-based filters are further operable to compare the current context against the respective metadata indications of the set of management element definitions to determine whether the respective user interface element definition is to be chosen for display; wherein the user interface service supports a hierarchy of user element definition types and wherein the first, second, and third management element definition context-based filters are operable to filter out parent user element types while allowing child user element types to pass through for display. 24. The computer system of claim 23 further comprising: a user interface presenter for presenting user interface elements based on the management element definitions chosen by the first, second, and third management element definition context-based filters. | 0.5 |
9,442,929 | 11 | 13 | 11. A computing system for determining documents that are nearest to a query, comprising: a processor that is adapted to execute stored instructions; and a system memory, wherein the system memory comprises code configured to: construct a vantage point tree based on a plurality of document vectors; traverse the vantage point tree using one or more vantage points for each of a plurality of nodes in the vantage point tree by removing any of the plurality of document vectors that are outside a hypersphere of a specified search radius centered about a query vector and remove any of the plurality of document vectors that do not satisfy a triangle inequality condition for the specified search radius between a vantage point, the document vector, and the query vector; determine a plurality of nearest neighbor document vectors to the query vector based on a distance between each remaining document vector and the query vector; and adjust the specified search radius such that only a specified number of nearest neighbor document vectors are remaining after document vectors that are outside the hypersphere of the specified search radius for the query vector and document vectors that do not satisfy the triangle inequality condition have been removed. | 11. A computing system for determining documents that are nearest to a query, comprising: a processor that is adapted to execute stored instructions; and a system memory, wherein the system memory comprises code configured to: construct a vantage point tree based on a plurality of document vectors; traverse the vantage point tree using one or more vantage points for each of a plurality of nodes in the vantage point tree by removing any of the plurality of document vectors that are outside a hypersphere of a specified search radius centered about a query vector and remove any of the plurality of document vectors that do not satisfy a triangle inequality condition for the specified search radius between a vantage point, the document vector, and the query vector; determine a plurality of nearest neighbor document vectors to the query vector based on a distance between each remaining document vector and the query vector; and adjust the specified search radius such that only a specified number of nearest neighbor document vectors are remaining after document vectors that are outside the hypersphere of the specified search radius for the query vector and document vectors that do not satisfy the triangle inequality condition have been removed. 13. The system of claim 11 , wherein the system comprises a plurality of computing devices; wherein construction of child nodes for a vantage point tree node in upper levels of the vantage point tree is performed using a coordinating computing device randomly chosen from the plurality of computing devices which contain document vectors corresponding to the vantage point tree node; and wherein the system memory of the coordinating computing device is configured to: determine a vantage point; and send the vantage point to each of the plurality of computing devices; and wherein the system memory of each of the plurality of computing devices is configured to compute distances between the document vectors corresponding to the vantage point tree node that are stored on the computing device and the vantage point; and wherein the system memory of the coordinating computing device is further configured to: redistribute the document vectors stored on the plurality of computing devices according to the distances; and partition the plurality of computing devices according to the distances to construct the child nodes; and wherein the process is repeated until all the document vectors corresponding to the vantage point tree node reside on a single computing device, and wherein lower levels of the vantage point tree are constructed using document vectors on the single computing device and a vantage point for each node in the lower levels of the vantage point tree. | 0.549786 |
8,533,211 | 1 | 10 | 1. A computer-implemented method for bridging terminology differences between at least two subject areas, comprising executing the following steps on a computer: computing a first affinity measure between a first term in a first corpus, corresponding to a first subject area, and a bridge term; computing a second affinity measure between a second term in a second corpus, corresponding to a second subject area, and the bridge term; computing a third affinity measure between the first term and the second term based on the first affinity measure and the second affinity measure; wherein the bridge term is a term that appears in both the first corpus and the second corpus, wherein computing at least one of the first affinity measure and the second affinity measure comprises computing a transitive closure of an affinity matrix of at least one of the first corpus and the second corpus; assigning a score for a pair of terms in the transitive closure of the affinity matrix using a composite path probability, wherein the composite path probability is a computation of a sum of path probabilities for n paths between the pair of terms, wherein n is an integer greater than 0. | 1. A computer-implemented method for bridging terminology differences between at least two subject areas, comprising executing the following steps on a computer: computing a first affinity measure between a first term in a first corpus, corresponding to a first subject area, and a bridge term; computing a second affinity measure between a second term in a second corpus, corresponding to a second subject area, and the bridge term; computing a third affinity measure between the first term and the second term based on the first affinity measure and the second affinity measure; wherein the bridge term is a term that appears in both the first corpus and the second corpus, wherein computing at least one of the first affinity measure and the second affinity measure comprises computing a transitive closure of an affinity matrix of at least one of the first corpus and the second corpus; assigning a score for a pair of terms in the transitive closure of the affinity matrix using a composite path probability, wherein the composite path probability is a computation of a sum of path probabilities for n paths between the pair of terms, wherein n is an integer greater than 0. 10. The method of claim 1 , wherein the third affinity measure comprises a composite path probability of the first term, the bridge term, and the second term. | 0.608911 |
9,830,380 | 4 | 5 | 4. The image tagging apparatus according to claim 2 , wherein the processor further executes the instructions to: update the second score TS a according to the tag score TS c obtained by the linear combination; and solve the linear weight w according to the updated second score TS a , so as to update the tag score TS c obtained by the linear combination. | 4. The image tagging apparatus according to claim 2 , wherein the processor further executes the instructions to: update the second score TS a according to the tag score TS c obtained by the linear combination; and solve the linear weight w according to the updated second score TS a , so as to update the tag score TS c obtained by the linear combination. 5. The image tagging apparatus according to claim 4 , wherein the processor further executes the instruction to: judge whether a predetermined condition is satisfied; and if the predetermined condition is satisfied, take the obtained tag score TS c as the final scores about all the tags; and if the predetermined condition is not satisfied, proceeds with updating the second score TS a . | 0.5 |
9,483,733 | 13 | 15 | 13. A querying system comprising: memory which stores instructions for executing a query for retrieving results from an associated knowledge resource, the instructions including: a query engine which executes a query containing a global backreference and retrieves results from the knowledge resource responsive to the query, the query including a set of conditions, a first of the conditions including a regular expression that identifies strings in the knowledge resource that match the regular expression, the regular expression including a capturing group for capturing a substring of an identified matching string, the global backreference retrieving the substring captured by the capturing group and wherein the global backreference comprises a remote backreference which is outside the first condition and outputs at least one of the results of the query containing the global backreference and information based on the results; and a processor which executes the instructions. | 13. A querying system comprising: memory which stores instructions for executing a query for retrieving results from an associated knowledge resource, the instructions including: a query engine which executes a query containing a global backreference and retrieves results from the knowledge resource responsive to the query, the query including a set of conditions, a first of the conditions including a regular expression that identifies strings in the knowledge resource that match the regular expression, the regular expression including a capturing group for capturing a substring of an identified matching string, the global backreference retrieving the substring captured by the capturing group and wherein the global backreference comprises a remote backreference which is outside the first condition and outputs at least one of the results of the query containing the global backreference and information based on the results; and a processor which executes the instructions. 15. The system of claim 13 , wherein each global backreference in the query is configured for retrieving a captured substring captured by a capturing group of the regular expression to which the global backreference refers when the regular expression matches a string in the knowledge source that includes the substring. | 0.6 |
7,789,665 | 1 | 7 | 1. An educational straw comprising: a) a shaped portion formed on the straw end and extending through a portion of the body forming a straw shaped portion; b) a body portion conjoined to the shaped portion and extending to an opposing end; and c) a descriptor appearing on the straw defining that portion of the straw having a preformed shape wherein said descriptor is at least one name defining the shaped portion. | 1. An educational straw comprising: a) a shaped portion formed on the straw end and extending through a portion of the body forming a straw shaped portion; b) a body portion conjoined to the shaped portion and extending to an opposing end; and c) a descriptor appearing on the straw defining that portion of the straw having a preformed shape wherein said descriptor is at least one name defining the shaped portion. 7. The educational straw as recited in claim 1 , wherein a plurality of educational straws are packaged as an educational tool. | 0.608025 |
9,026,442 | 1 | 4 | 1. A method comprising: identifying an acoustic model, wherein the acoustic model is trained on native speech in a target dialect; identifying a class of a speaker; and replacing a phoneme in the acoustic model with a modified phoneme, wherein the modified phoneme is a weighted sum of plausible phonemes in a lattice of plausible phonemes associated with the class of the speaker. | 1. A method comprising: identifying an acoustic model, wherein the acoustic model is trained on native speech in a target dialect; identifying a class of a speaker; and replacing a phoneme in the acoustic model with a modified phoneme, wherein the modified phoneme is a weighted sum of plausible phonemes in a lattice of plausible phonemes associated with the class of the speaker. 4. The method of claim 1 , wherein the target dialect comprises one of a regional dialect and a foreign accent. | 0.594891 |
10,013,467 | 2 | 5 | 2. The method of claim 1 , further comprising the steps of: selecting a target node among the nodes within the virtual n-dimensional array; comparing, using a chemical feature (“CF”) module which comprises code executing in the processor, at least one CF corresponding to the coded form contained within a first node adjacent to the target node to at least one CF corresponding to the coded form contained in at least a second node adjacent to the target node, the first and second nodes sharing a border with the target node in the virtual n-dimensional array; identifying common CFs between the target and second nodes using a commonality module which comprises code executing in the processor; generating at least one new coded form based on combinations of the identified, common CFs which, when inserted into the virtual n-dimensional array, results in a placement within the target node, using a coded form generator module which comprises code executing in the processor; and outputting a chemical identifier corresponding to the new coded form. | 2. The method of claim 1 , further comprising the steps of: selecting a target node among the nodes within the virtual n-dimensional array; comparing, using a chemical feature (“CF”) module which comprises code executing in the processor, at least one CF corresponding to the coded form contained within a first node adjacent to the target node to at least one CF corresponding to the coded form contained in at least a second node adjacent to the target node, the first and second nodes sharing a border with the target node in the virtual n-dimensional array; identifying common CFs between the target and second nodes using a commonality module which comprises code executing in the processor; generating at least one new coded form based on combinations of the identified, common CFs which, when inserted into the virtual n-dimensional array, results in a placement within the target node, using a coded form generator module which comprises code executing in the processor; and outputting a chemical identifier corresponding to the new coded form. 5. The method of claim 2 wherein the chemical identifier is at least one of a chemical formula, a chemical structure, or chemical name derived from chemical nomenclature. | 0.79064 |
7,912,715 | 21 | 25 | 21. An apparatus comprising: a distortion computation module configured: to compare a first feature vector in a sequence of feature vectors formed from a digitized incoming signal to be recognized with a first number of templates from a set of templates representing candidate patterns, to select, based on said comparison, a second number of templates from said template set, the second number being smaller than the first number, to compare a second feature vector only with said selected templates so as to recognize a pattern of said digitized incoming signal; and to generate a signal corresponding to a recognized pattern of said digitized incoming signal as a result of said comparing said second feature vector only with said selected templates. | 21. An apparatus comprising: a distortion computation module configured: to compare a first feature vector in a sequence of feature vectors formed from a digitized incoming signal to be recognized with a first number of templates from a set of templates representing candidate patterns, to select, based on said comparison, a second number of templates from said template set, the second number being smaller than the first number, to compare a second feature vector only with said selected templates so as to recognize a pattern of said digitized incoming signal; and to generate a signal corresponding to a recognized pattern of said digitized incoming signal as a result of said comparing said second feature vector only with said selected templates. 25. The apparatus according to claim 21 , further comprising a control module, configured to detect the processor load and to adjust the number of successive feature vectors in response to a said load. | 0.56681 |
8,725,756 | 1 | 8 | 1. A method comprising: receiving, by one or more computers and from a user device, a first search query during a current search session, the first search query comprising one or more first query terms; receiving, by one or more computers and from the user device, an additional search query during the current search session, the additional search query comprising one or more additional query terms and the additional search query being received subsequent to search results for the first search query being provided in response to the first search query; identifying, by one or more computers and from a set of previous search sessions that each concluded prior to the current search session, a similar subset of previous search sessions, each individual previous search session of the similar subset being identified for inclusion in the similar subset based on the individual previous search session being a search session during which the first search query and the additional search query were both received, the similar subset lacking at least one previous search session of the set of previous search sessions; identifying, by one or more computers and from the similar subset of previous search sessions, a set of follow-up search queries, each follow-up search query being a search query that was received subsequent to receipt of the first search query and the additional search query in at least one of the previous search sessions of the similar subset; identifying, by one or more computers and for each follow-up search query, a frequency at which the follow-up search query was received in previous search sessions subsequent to receipt of the first search query and the additional search query; aggregating the set of follow-up search queries from the similar subset of previous search sessions; selecting from the aggregated follow-up search queries and based on the identified frequencies having the highest frequency of occurrence, a suggested search query for presentation in response to receipt of the additional search query during the current search session; and providing the suggested search query with search results for the additional search query. | 1. A method comprising: receiving, by one or more computers and from a user device, a first search query during a current search session, the first search query comprising one or more first query terms; receiving, by one or more computers and from the user device, an additional search query during the current search session, the additional search query comprising one or more additional query terms and the additional search query being received subsequent to search results for the first search query being provided in response to the first search query; identifying, by one or more computers and from a set of previous search sessions that each concluded prior to the current search session, a similar subset of previous search sessions, each individual previous search session of the similar subset being identified for inclusion in the similar subset based on the individual previous search session being a search session during which the first search query and the additional search query were both received, the similar subset lacking at least one previous search session of the set of previous search sessions; identifying, by one or more computers and from the similar subset of previous search sessions, a set of follow-up search queries, each follow-up search query being a search query that was received subsequent to receipt of the first search query and the additional search query in at least one of the previous search sessions of the similar subset; identifying, by one or more computers and for each follow-up search query, a frequency at which the follow-up search query was received in previous search sessions subsequent to receipt of the first search query and the additional search query; aggregating the set of follow-up search queries from the similar subset of previous search sessions; selecting from the aggregated follow-up search queries and based on the identified frequencies having the highest frequency of occurrence, a suggested search query for presentation in response to receipt of the additional search query during the current search session; and providing the suggested search query with search results for the additional search query. 8. The method of claim 1 , further comprising: providing the search results for the first search query in response to receiving the first search query; wherein: receiving the additional search query comprises receiving, prior to an end of the current search session and after providing the search results for the first search query, the additional search query; and identifying the similar subset of previous search sessions comprises identifying a particular search session that occurred prior to the current search session and that included both the first search query and the additional search query. | 0.598535 |
8,411,086 | 22 | 24 | 22. The method of claim 17 , wherein the associated semantic information associated with the predefined marker includes at least one of joint constraints, motion properties, material properties and insertion of dynamic elements. | 22. The method of claim 17 , wherein the associated semantic information associated with the predefined marker includes at least one of joint constraints, motion properties, material properties and insertion of dynamic elements. 24. The method of claim 22 , wherein motion properties include at least one of motion type, speed and direction. | 0.763713 |
8,798,519 | 15 | 16 | 15. The online education system of claim 14 wherein the plurality of roles includes a teacher role and a student role. | 15. The online education system of claim 14 wherein the plurality of roles includes a teacher role and a student role. 16. The online education system of claim 15 wherein the plurality of roles includes a mentor role. | 0.5 |
8,670,618 | 1 | 5 | 1. A computer-implemented method for extracting personal information from a family history document, comprising: applying optical character recognition (OCR) to a digital image of a family history document to create an OCR copy; identifying a person's name in the digital image; extracting name data from the OCR copy representing the name; confirming accuracy of the extracted name data; publishing the extracted name data in a searchable format; identifying a family relationship indicator corresponding to the identified person's name in the digital image, and extracting relationship data from the OCR copy representing the family relationship indicator. | 1. A computer-implemented method for extracting personal information from a family history document, comprising: applying optical character recognition (OCR) to a digital image of a family history document to create an OCR copy; identifying a person's name in the digital image; extracting name data from the OCR copy representing the name; confirming accuracy of the extracted name data; publishing the extracted name data in a searchable format; identifying a family relationship indicator corresponding to the identified person's name in the digital image, and extracting relationship data from the OCR copy representing the family relationship indicator. 5. The method of claim 1 , wherein extracting name data includes highlighting the identified name, manually selecting the highlighted name, and mapping to data in the OCR copy representing the identified name. | 0.648148 |
9,552,055 | 10 | 11 | 10. The method of claim 1 , wherein the second set of user nodes comprises approximately 100% of the user nodes of the plurality of user nodes minus the first set of user nodes. | 10. The method of claim 1 , wherein the second set of user nodes comprises approximately 100% of the user nodes of the plurality of user nodes minus the first set of user nodes. 11. The method of claim 10 , wherein the second set of user nodes is divided into a plurality of discrete sets of users. | 0.5 |
9,785,850 | 44 | 46 | 44. The method of claim 43 , wherein thresholding includes using histogram segmentation. | 44. The method of claim 43 , wherein thresholding includes using histogram segmentation. 46. The method of claim 44 , wherein thresholding includes using a block size smaller than an average size of the characters. | 0.5 |
9,740,735 | 1 | 9 | 1. A computer system, comprising: a distributed computer cluster; one or more processors; and one or more computer readable storage media having stored thereon computer-executable instructions that are executable by the one or more processors to cause the computer system to generate parallel-processing queries, the computer-executable instructions including instructions that are executable to cause the computer system to perform at least the following: create a structured query according to a structured query language, the structured query being created for execution in parallel across the distributed computer cluster; and; receive programming language syntax that comprises a functions; insert the received programming language syntax into the structured query of the structured query language such that a resulting query includes a structured query language statement in combination with programming language code that specifies both an aggregation and an operation; insert a keyword into the resulting query that defines an object type in the programming language code; compile the programming language code, wherein compiling the programming language code is performed based on the object type defined by the inserted keyword; and execute the resulting query, including both the structured query language and the programming language code, in a distributed manner on the distributed computer cluster. | 1. A computer system, comprising: a distributed computer cluster; one or more processors; and one or more computer readable storage media having stored thereon computer-executable instructions that are executable by the one or more processors to cause the computer system to generate parallel-processing queries, the computer-executable instructions including instructions that are executable to cause the computer system to perform at least the following: create a structured query according to a structured query language, the structured query being created for execution in parallel across the distributed computer cluster; and; receive programming language syntax that comprises a functions; insert the received programming language syntax into the structured query of the structured query language such that a resulting query includes a structured query language statement in combination with programming language code that specifies both an aggregation and an operation; insert a keyword into the resulting query that defines an object type in the programming language code; compile the programming language code, wherein compiling the programming language code is performed based on the object type defined by the inserted keyword; and execute the resulting query, including both the structured query language and the programming language code, in a distributed manner on the distributed computer cluster. 9. The system of claim 1 , wherein the programming language code is checked for errors at compile time. | 0.637324 |
6,094,506 | 22 | 25 | 22. The method of claim 20 wherein the probability table is a shape feature probability matrix. | 22. The method of claim 20 wherein the probability table is a shape feature probability matrix. 25. The method of claim 22 wherein each characteristic has a place within the set and wherein a comparison value is calculated by adding together the squared distance between the starting points and the squared distance between the ending points of two characteristics, the two characteristics being selected from the same place within the sets of characteristics representing the pair of sample patterns. | 0.5 |
9,460,080 | 1 | 6 | 1. A method comprising: identifying, in a profile of an entity in a social network, a name of the entity; automatically generating, based on the name of the entity, one or more sentences; based on the one or more sentences, training a tokenizer that is configured to identify tokens within a text string; wherein the method is performed by one or more computing devices. | 1. A method comprising: identifying, in a profile of an entity in a social network, a name of the entity; automatically generating, based on the name of the entity, one or more sentences; based on the one or more sentences, training a tokenizer that is configured to identify tokens within a text string; wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein automatically generating the one or more sentences comprises automatically generating the one or more sentences based on context data. | 0.803944 |
9,075,983 | 7 | 9 | 7. A method for authorizing access, comprising the step of: generating for display at least one distorted string of alphanumeric characters, in combination with at least one of a glyph, picture or symbol, the glyph, picture or symbol being foreign to a target audience, the generating step including: generating a random background; separating the at least one distorted string of alphanumeric characters into two or more strings, and adding at least one of the glyph, picture or symbol to one or more ends of the two or more strings to form at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol; and combining the random background with the at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol, using a random template; and comparing a response of a user entered in reaction to the distorted string of alphanumeric characters to a reference string of characters to determine whether to grant access. | 7. A method for authorizing access, comprising the step of: generating for display at least one distorted string of alphanumeric characters, in combination with at least one of a glyph, picture or symbol, the glyph, picture or symbol being foreign to a target audience, the generating step including: generating a random background; separating the at least one distorted string of alphanumeric characters into two or more strings, and adding at least one of the glyph, picture or symbol to one or more ends of the two or more strings to form at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol; and combining the random background with the at least one string of random alphanumeric characters that includes at least one of the glyph, picture or symbol, using a random template; and comparing a response of a user entered in reaction to the distorted string of alphanumeric characters to a reference string of characters to determine whether to grant access. 9. The method according to claim 7 wherein the random background has one or more randomly selected colors, shapes, features and/or textures. | 0.681818 |
8,185,455 | 1 | 3 | 1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results. | 1. An apparatus comprising: a processor to: receive a user selection of an audit data set including a plurality of exceptions, wherein each exception of the plurality of exceptions represents an instance of misbilling associated with the audit data set, wherein the audit data set is selected from a plurality of billing data sets, each billing data set of the plurality billing data sets including corresponding billing data that has been extracted by the processor from a database; apply a first audit rule to audit the audit data set and produce first audit rule results, wherein the first audit rule results identify a first subset of exceptions of the plurality of exceptions within the audit data set; apply a second audit rule, distinct from the first audit rule, to audit the audit data set and produce second audit rule results, wherein the second audit rule results identify a second subset of exceptions of the plurality of exceptions within the audit data set; present the first subset of exceptions and the second subset of exceptions to a user via a results user interface; and receive a selection of a particular audit rule, wherein the particular audit rule is one of the first audit rule and the second audit rule, and wherein the particular audit rule is selected based on the first audit rule results and the second audit rule results. 3. The apparatus of claim 1 , wherein the second audit rule results include an indication of one or more second false positives that are associated with the audit data set. | 0.782278 |
8,949,247 | 11 | 12 | 11. The disk memory according to claim 10 , further comprising: grouping updates of the database log together at specified intervals moving the grouped updates to the posting file; and storing each keyword respectively in an occurrence list in the form of occurrences of the keyword older than a determined update generation and in a delta list in the form of a set of smaller updates more recent than the same update generation, such that the dictionary contains one entry for each keyword in the posting file and a reference to the occurrence list and the delta list. | 11. The disk memory according to claim 10 , further comprising: grouping updates of the database log together at specified intervals moving the grouped updates to the posting file; and storing each keyword respectively in an occurrence list in the form of occurrences of the keyword older than a determined update generation and in a delta list in the form of a set of smaller updates more recent than the same update generation, such that the dictionary contains one entry for each keyword in the posting file and a reference to the occurrence list and the delta list. 12. The disk memory according to claim 11 , wherein the dictionary is implemented as a B-tree and storing the occurrence list and the delta list in the B-tree when the occurrence list and the delta list are below a specific size. | 0.691375 |
10,152,968 | 1 | 20 | 1. A computer-implemented method comprising: inferring, based on data indicating locations of a plurality of automation devices and on a location associated with a user, that first speech of the user is directed to a particular automation device of a particular type, wherein the particular automation device is installed and operating at one of the indicated locations, and wherein the location of the particular automation device is proximate to the location associated with the user while the user is uttering the first speech; selecting a topic-specific speech recognition model adapted to recognize speech related to the determined type of automation device; using the topic-specific speech recognition model to recognize second speech provided at the location, wherein recognizing the second speech comprises identifying a query or command relating to the type of automation device and represented by the second speech; and issuing the query or command represented by the second speech to the particular automation device of the particular type, thereby prompting the particular automation device to perform an act responsive to the command or query, wherein the type of automation device is a manufacturing process control type, an industrial process control type, an energy-production process control type, a water treatment process control type, an environmental regulation process control type, and/or a utility process control type. | 1. A computer-implemented method comprising: inferring, based on data indicating locations of a plurality of automation devices and on a location associated with a user, that first speech of the user is directed to a particular automation device of a particular type, wherein the particular automation device is installed and operating at one of the indicated locations, and wherein the location of the particular automation device is proximate to the location associated with the user while the user is uttering the first speech; selecting a topic-specific speech recognition model adapted to recognize speech related to the determined type of automation device; using the topic-specific speech recognition model to recognize second speech provided at the location, wherein recognizing the second speech comprises identifying a query or command relating to the type of automation device and represented by the second speech; and issuing the query or command represented by the second speech to the particular automation device of the particular type, thereby prompting the particular automation device to perform an act responsive to the command or query, wherein the type of automation device is a manufacturing process control type, an industrial process control type, an energy-production process control type, a water treatment process control type, an environmental regulation process control type, and/or a utility process control type. 20. The method of claim 1 , wherein the plurality of automation devices includes two or more proximate automation devices installed and operating at locations proximate to the location associated with the user, and wherein inferring that first speech of the user is directed to the particular automation device includes: inferring, independent of content of the second speech, that the first speech is directed to an unknown one of the two or more proximate automation devices; and based on the content of the first speech, selecting, from the two or more proximate automation devices, the particular automation device to which the first speech is directed. | 0.528694 |
9,098,533 | 11 | 12 | 11. A system that performs a visual search, comprising: a processor; and a memory that comprises a plurality of components that are executed by the processor, the plurality of components comprising: an object detection component that detects an object from visual content rendered on a display based on a search word recognized from a voice directed query related to the visual content, wherein the visual content is one of a frame from a video stream, a two-dimensional image, or a three-dimensional image; an algorithm selection component that selects an edge detection algorithm from a set of edge detection algorithms based on at least one of the visual content, the search word from the voice directed query, or contextual information; an extraction component that extracts an image of the object from the visual content using the edge detection algorithm selected from the set of edge detection algorithms, wherein the image of the object is a portion of the visual content and is extracted from a remainder of the visual content; and a search component that uses the image of the object extracted from the visual content as an input for a reverse visual search, wherein the reverse visual search is performed based upon the image of the object extracted from the visual content, and wherein the reverse visual search returns a result. | 11. A system that performs a visual search, comprising: a processor; and a memory that comprises a plurality of components that are executed by the processor, the plurality of components comprising: an object detection component that detects an object from visual content rendered on a display based on a search word recognized from a voice directed query related to the visual content, wherein the visual content is one of a frame from a video stream, a two-dimensional image, or a three-dimensional image; an algorithm selection component that selects an edge detection algorithm from a set of edge detection algorithms based on at least one of the visual content, the search word from the voice directed query, or contextual information; an extraction component that extracts an image of the object from the visual content using the edge detection algorithm selected from the set of edge detection algorithms, wherein the image of the object is a portion of the visual content and is extracted from a remainder of the visual content; and a search component that uses the image of the object extracted from the visual content as an input for a reverse visual search, wherein the reverse visual search is performed based upon the image of the object extracted from the visual content, and wherein the reverse visual search returns a result. 12. The system of claim 11 , wherein the search component uses the search word recognized from the voice directed query as an input for a disparate search, and the object detection component detects the object from the visual content based on a result from the disparate search, wherein the result from the disparate search includes a set of images used by the object detection component to guide and refine detection of the object from the visual content. | 0.5 |
8,954,479 | 17 | 20 | 17. A method for end-to-end interoperability and workflows from building architecture design to one or more simulations, comprising: interacting with a data model via a user interface or an application programming interface or combinations of both integrated on a building information management enablement platform, wherein the data model comprises at least a user data entity, a user role data entity, a project data entity, an external information data entity, a format mapping data entity, an XML schema data entity, a none XML schema data entity, a model view definition template data entity and a repository data entity, the interacting comprising at least: creating a user data entity instance and populating one or more fields associated with the user data entity in the user data entity instance; creating a project data entity instance of the defined data model and populating one or more fields associated with the project data entity instance; adding external information data for simulation runs into an external information data entity instance; adding user role information to a user role data entity instance; creating one or more links to a file format and schema by populating a format mapping data entity instance and a schema data entity instance; creating a model view definition template data entity instance for translation of a building architecture design output format to a simulation input format, and populating the model view definition template data entity instance; creating an input file by populating a repository data entity instance to identify the input file and the model view definition template data entity instance; and running a simulation code associated with said one or more simulations with the data of the external information data entity instance and a transformed input file that is transformed using the populated model view definition template data entity instance, wherein the model view definition template data entity instance stores at least data associated with performing a format translation function comprising at least how data is to be extracted from one or more source files and mapped, wherein a user is allowed to populate the model view definition template data entity instance and the format mapping data entity instance, wherein responsive to the user invoking a code specified in the external information data entity instance, the method further comprises automatically transforming, via at least the model view definition template data entity instance and the format mapping data entity instance, an output of the building design to one or more formats of one or more of the plurality of simulations based on the data populated in the model view definition template data entity instance and the format mapping data entity instance, wherein responsive to a user command, the method further comprises automatically performing said running a simulation code. | 17. A method for end-to-end interoperability and workflows from building architecture design to one or more simulations, comprising: interacting with a data model via a user interface or an application programming interface or combinations of both integrated on a building information management enablement platform, wherein the data model comprises at least a user data entity, a user role data entity, a project data entity, an external information data entity, a format mapping data entity, an XML schema data entity, a none XML schema data entity, a model view definition template data entity and a repository data entity, the interacting comprising at least: creating a user data entity instance and populating one or more fields associated with the user data entity in the user data entity instance; creating a project data entity instance of the defined data model and populating one or more fields associated with the project data entity instance; adding external information data for simulation runs into an external information data entity instance; adding user role information to a user role data entity instance; creating one or more links to a file format and schema by populating a format mapping data entity instance and a schema data entity instance; creating a model view definition template data entity instance for translation of a building architecture design output format to a simulation input format, and populating the model view definition template data entity instance; creating an input file by populating a repository data entity instance to identify the input file and the model view definition template data entity instance; and running a simulation code associated with said one or more simulations with the data of the external information data entity instance and a transformed input file that is transformed using the populated model view definition template data entity instance, wherein the model view definition template data entity instance stores at least data associated with performing a format translation function comprising at least how data is to be extracted from one or more source files and mapped, wherein a user is allowed to populate the model view definition template data entity instance and the format mapping data entity instance, wherein responsive to the user invoking a code specified in the external information data entity instance, the method further comprises automatically transforming, via at least the model view definition template data entity instance and the format mapping data entity instance, an output of the building design to one or more formats of one or more of the plurality of simulations based on the data populated in the model view definition template data entity instance and the format mapping data entity instance, wherein responsive to a user command, the method further comprises automatically performing said running a simulation code. 20. The method of claim 17 , wherein the input file is an IFC file and the transformed input file is in Radiance format. | 0.508197 |
9,262,517 | 3 | 6 | 3. The method of claim 1 , further comprising: determining, using the processor, that an influencing condition exists based upon an analysis of the plurality of social media posts, wherein each of the plurality of social media posts relates to the topic and comprises a negative sentiment relating to the topic; and in response to determining that the influencing condition exists, posting, using the processor, social media to the social media website, wherein the social media is directed to the topic and is responsive to the plurality of social media posts. | 3. The method of claim 1 , further comprising: determining, using the processor, that an influencing condition exists based upon an analysis of the plurality of social media posts, wherein each of the plurality of social media posts relates to the topic and comprises a negative sentiment relating to the topic; and in response to determining that the influencing condition exists, posting, using the processor, social media to the social media website, wherein the social media is directed to the topic and is responsive to the plurality of social media posts. 6. The method of claim 3 , wherein determining that the influencing condition exists comprises: measuring, using the processor, an influence of a second plurality of social media posts archived to the database; and predicting, using the processor, the influence of each of the plurality of social media posts using the influence of the second plurality of social media posts. | 0.5 |
4,829,572 | 25 | 26 | 25. The method of claim 13 and additionally comprising the step of averaging the energy and sweep spectra of separate utterances of the same phoneme to derive profiles indicative of the phoneme. | 25. The method of claim 13 and additionally comprising the step of averaging the energy and sweep spectra of separate utterances of the same phoneme to derive profiles indicative of the phoneme. 26. The method of claim 25 and additionally comprising the steps of generating a difference profile for substantially each pair of phonemes by subtracting each profile of one phoneme from the equivalent profile of each pair phoneme, identifying adjacent sections of each difference profile which exceed positive and negative thresholds respectively, and computing the likelihood that an unknown phoneme will be one or the other of a phoneme pair based on the relative areas in the identified sections of the difference profiles. | 0.500945 |
10,127,212 | 20 | 21 | 20. A computing system comprising: at least one processor; and a non-transitory computer-readable storage medium comprising instructions stored thereon that, when executed by the at least one processor, are configured to cause the computing system to at least: monitor changes to text copied into multiple documents, the copied text having been copied from a previous document; determine that a same deletion and different insertions have been made to the copied text in at least a threshold number of documents, the threshold number being greater than one; and prompt the same deletion and a new insertion to be made to the copied text in a subsequent document based on the determination that the same deletion and different insertions have been made to the copied text in at least the threshold number of documents. | 20. A computing system comprising: at least one processor; and a non-transitory computer-readable storage medium comprising instructions stored thereon that, when executed by the at least one processor, are configured to cause the computing system to at least: monitor changes to text copied into multiple documents, the copied text having been copied from a previous document; determine that a same deletion and different insertions have been made to the copied text in at least a threshold number of documents, the threshold number being greater than one; and prompt the same deletion and a new insertion to be made to the copied text in a subsequent document based on the determination that the same deletion and different insertions have been made to the copied text in at least the threshold number of documents. 21. The computing system of claim 20 , wherein the copied text is presented in an email interface. | 0.873057 |
9,262,745 | 1 | 6 | 1. A computer-implemented method that uses metadata from an existing structure of user roles to assign application programs to another structure of user roles, comprising: identifying, by a computer system, a set of first user roles that are used to control access to a set of first application programs, wherein: (i) the first application programs are implemented on a first computer platform in which user access to the first application programs is provided through a laptop or personal computer, and (ii) each user role in the set of first user roles is assigned (a) multiple respective users, and (b) one or more of the first application programs to which the multiple respective users have access due to their user role assignment; generating, by the computer system, a set of second user roles that are to be used to control access to a set of second application programs, by generating a corresponding second user role for each user role in the set of first user roles, wherein: (i) the second application programs are implemented on a second computer platform that is a mobile device platform in which user access to the second application programs is provided through use of a particular type of mobile device, and the second application programs are each a mobile application for the mobile device platform, (ii) each user role in the set of second user roles will be assigned multiple respective users, and (iii) each user role in the set of second user roles corresponds to a corresponding user role in the set of first user roles, wherein when the set of second user roles are generated, assignments do not exist between the set of second user roles and the second application programs; accessing, by the computer system, first metadata that is assigned to the set of first user roles; accessing, by the computer system, second metadata that is assigned to the second application programs; comparing, by the computer system, the first metadata that is assigned to the set of first user roles to the second metadata that is assigned to the second application programs to identify a matching portion of the first metadata that matches a matching portion of the second metadata; assigning, by the computer system, a second matching application program from the set of second application programs to a second matching user role from the set of second user roles, due to the computer system having identified that: (a) the matching portion of the first metadata matches the matching portion of the second metadata, (b) the matching portion of the first metadata is assigned to a first matching user role from among the set of first user roles, (c) the first matching user role corresponds to the second matching user role, and (d) the matching portion of the second metadata is assigned to the second matching application program. | 1. A computer-implemented method that uses metadata from an existing structure of user roles to assign application programs to another structure of user roles, comprising: identifying, by a computer system, a set of first user roles that are used to control access to a set of first application programs, wherein: (i) the first application programs are implemented on a first computer platform in which user access to the first application programs is provided through a laptop or personal computer, and (ii) each user role in the set of first user roles is assigned (a) multiple respective users, and (b) one or more of the first application programs to which the multiple respective users have access due to their user role assignment; generating, by the computer system, a set of second user roles that are to be used to control access to a set of second application programs, by generating a corresponding second user role for each user role in the set of first user roles, wherein: (i) the second application programs are implemented on a second computer platform that is a mobile device platform in which user access to the second application programs is provided through use of a particular type of mobile device, and the second application programs are each a mobile application for the mobile device platform, (ii) each user role in the set of second user roles will be assigned multiple respective users, and (iii) each user role in the set of second user roles corresponds to a corresponding user role in the set of first user roles, wherein when the set of second user roles are generated, assignments do not exist between the set of second user roles and the second application programs; accessing, by the computer system, first metadata that is assigned to the set of first user roles; accessing, by the computer system, second metadata that is assigned to the second application programs; comparing, by the computer system, the first metadata that is assigned to the set of first user roles to the second metadata that is assigned to the second application programs to identify a matching portion of the first metadata that matches a matching portion of the second metadata; assigning, by the computer system, a second matching application program from the set of second application programs to a second matching user role from the set of second user roles, due to the computer system having identified that: (a) the matching portion of the first metadata matches the matching portion of the second metadata, (b) the matching portion of the first metadata is assigned to a first matching user role from among the set of first user roles, (c) the first matching user role corresponds to the second matching user role, and (d) the matching portion of the second metadata is assigned to the second matching application program. 6. The computer-implemented method of claim 1 , further comprising receiving, by the computer system, user input from an administrator that assigns the first application programs to the set of first user roles. | 0.659091 |
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