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9,390,197 | 1 | 16 | 1. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; in the social graph, updating a value of the first edge between the first and second nodes; when the sender sends the message to the first recipient and a second recipient, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a first amount; and when the sender sends the message to only the first recipient and no other recipients, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a second amount, wherein the second amount is greater than the first amount. | 1. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; in the social graph, updating a value of the first edge between the first and second nodes; when the sender sends the message to the first recipient and a second recipient, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a first amount; and when the sender sends the message to only the first recipient and no other recipients, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a second amount, wherein the second amount is greater than the first amount. 16. The method of claim 1 further comprising: storing in the social graph the second activity information. | 0.889813 |
9,629,663 | 17 | 20 | 17. A method for spinal stabilization, comprising: implanting a first bone anchor on a first side of a first vertebra, the first bone anchor having a spinal fixation element receiving portion disposed between opposed arms; disposing a spinal fixation element in the spinal fixation element receiving portion of the first bone anchor; mating a subassembly to the first bone anchor to secure the spinal fixation element within the spinal fixation element receiving portion; inserting one end of a cross connector into a rod-receiving portion of a clamp, the rod-receiving portion being disposed proximal of the spinal fixation element receiving portion; and fixing a location of the cross connector rod with respect to the bone anchor. | 17. A method for spinal stabilization, comprising: implanting a first bone anchor on a first side of a first vertebra, the first bone anchor having a spinal fixation element receiving portion disposed between opposed arms; disposing a spinal fixation element in the spinal fixation element receiving portion of the first bone anchor; mating a subassembly to the first bone anchor to secure the spinal fixation element within the spinal fixation element receiving portion; inserting one end of a cross connector into a rod-receiving portion of a clamp, the rod-receiving portion being disposed proximal of the spinal fixation element receiving portion; and fixing a location of the cross connector rod with respect to the bone anchor. 20. The method of claim 17 , wherein fixing a location of the cross connector rod with respect to the bone anchor further comprises matting the subassembly with the clamp such that the subassembly operates the clamp to fix the location of the cross connector rod with respect to the bone anchor. | 0.514803 |
8,751,484 | 18 | 21 | 18. A non-transitory computer readable storage medium having stored therein instructions, which when executed by a computer system cause the computer system to: receive a search request from a user of the computer, the search request including a plurality of search keywords; and in response to the search request: identify multiple resource identifiers in accordance with a first set of predefined criteria for selecting a respective document that satisfies user-specified search keywords from a user, each resource identifier corresponding to a document at a respective data source; retrieve a document from the respective document source for at least one of the resource identifiers; identify within the retrieved document a chunk by applying a second set of predefined criteria to one or more candidate chunks within the retrieved document; and provide the identified chunk and a link to the identified chunk within the document for display to the user, wherein the first set of predefined criteria requires that at least a first subset of the search keywords be found within an identified respective document, and the second set of predefined criteria requires that at least a second subset of the search keywords be found within an identified chunk. | 18. A non-transitory computer readable storage medium having stored therein instructions, which when executed by a computer system cause the computer system to: receive a search request from a user of the computer, the search request including a plurality of search keywords; and in response to the search request: identify multiple resource identifiers in accordance with a first set of predefined criteria for selecting a respective document that satisfies user-specified search keywords from a user, each resource identifier corresponding to a document at a respective data source; retrieve a document from the respective document source for at least one of the resource identifiers; identify within the retrieved document a chunk by applying a second set of predefined criteria to one or more candidate chunks within the retrieved document; and provide the identified chunk and a link to the identified chunk within the document for display to the user, wherein the first set of predefined criteria requires that at least a first subset of the search keywords be found within an identified respective document, and the second set of predefined criteria requires that at least a second subset of the search keywords be found within an identified chunk. 21. The computer readable storage medium of claim 18 , further comprising: instructions for identifying multiple chunks within the retrieved document, wherein each chunk satisfies the search keywords; and instructions for displaying the multiple chunks and a link to each of the multiple chunks within the document. | 0.730769 |
9,189,467 | 1 | 7 | 1. A method, comprising: opening a first electronic document; creating a second electronic document superimposed over the first electronic document to receive annotations in reference to the first electronic document; creating, in response to creating the second electronic document to receive annotations, an association between the first electronic document and the second electronic document; saving the second document as a separate document independent of the first document; in response to a second opening of the first electronic document, and based upon the association between the first electronic document and the second electronic document that was annotated during a previous viewing of the first electronic document, automatically opening the second electronic document without user intervention; superimposing the second electronic document with the annotations over the first electronic document; and receiving additional annotations in reference to the first electronic document within the second electronic document concurrently while viewing the first electronic document beneath the second electronic document. | 1. A method, comprising: opening a first electronic document; creating a second electronic document superimposed over the first electronic document to receive annotations in reference to the first electronic document; creating, in response to creating the second electronic document to receive annotations, an association between the first electronic document and the second electronic document; saving the second document as a separate document independent of the first document; in response to a second opening of the first electronic document, and based upon the association between the first electronic document and the second electronic document that was annotated during a previous viewing of the first electronic document, automatically opening the second electronic document without user intervention; superimposing the second electronic document with the annotations over the first electronic document; and receiving additional annotations in reference to the first electronic document within the second electronic document concurrently while viewing the first electronic document beneath the second electronic document. 7. The method of claim 1 , wherein the first electronic document is a spreadsheet file. | 0.862776 |
8,145,660 | 1 | 10 | 1. A computer-implemented method, comprising: receiving, by one or more processors, a search query generated by a user; determining, by the one or more processors, a type of expansion to apply to the search query; automatically generating, by the one or more processors, a plurality of different expanded search queries according to the determined expansion type without intervention from the user; executing, by the one or more processors, a separate search on each one of the plurality of different expanded search queries to retrieve search results; and providing, by the one or more processors, the search results of the separate searches on each of the plurality of different expanded search queries for presentation to the user in a plurality of different modules, wherein each module comprises search results for one of the expanded search queries. | 1. A computer-implemented method, comprising: receiving, by one or more processors, a search query generated by a user; determining, by the one or more processors, a type of expansion to apply to the search query; automatically generating, by the one or more processors, a plurality of different expanded search queries according to the determined expansion type without intervention from the user; executing, by the one or more processors, a separate search on each one of the plurality of different expanded search queries to retrieve search results; and providing, by the one or more processors, the search results of the separate searches on each of the plurality of different expanded search queries for presentation to the user in a plurality of different modules, wherein each module comprises search results for one of the expanded search queries. 10. The method of claim 1 , further comprising: determining a refinement to apply to the search query; and wherein generating expanded search queries comprises generating expanded search queries according to the determined expansion type and the determined refinement. | 0.5 |
9,594,742 | 5 | 6 | 5. The computer-implemented method of claim 4 , wherein a second placeholder symbol is used to represent a missing vowel in each two-set token comprising zero vowels. | 5. The computer-implemented method of claim 4 , wherein a second placeholder symbol is used to represent a missing vowel in each two-set token comprising zero vowels. 6. The computer-implemented method of claim 5 , wherein if the first tokenized set comprises a different number of tokens as the second tokenized set, further comprising the step of performing three-step tokenization. | 0.5 |
9,947,119 | 11 | 16 | 11. A system comprising: one or more processors and executable instructions accessible on a computer-readable medium that, when executed, configure the one or more processors to at least: obtain graph data including information related to a plurality of nodes, the plurality of nodes corresponding to search queries performed on a host site; construct sub-graph of additional nodes that represent search results of the search queries, the constructing of the sub-graph including generating links between the additional nodes based on an amount of overlap among the search results produced from the search queries that correspond to the one or more of the plurality of nodes, the additional nodes included in the sub-graph being clusters of the search results; render a graph by displaying each node at a respective absolute position within the graph and generating a plurality of tiles that depict images of the sub-graph at each of a plurality of zoom levels; and display a sub-graph image corresponding to a selected position and zoom level. | 11. A system comprising: one or more processors and executable instructions accessible on a computer-readable medium that, when executed, configure the one or more processors to at least: obtain graph data including information related to a plurality of nodes, the plurality of nodes corresponding to search queries performed on a host site; construct sub-graph of additional nodes that represent search results of the search queries, the constructing of the sub-graph including generating links between the additional nodes based on an amount of overlap among the search results produced from the search queries that correspond to the one or more of the plurality of nodes, the additional nodes included in the sub-graph being clusters of the search results; render a graph by displaying each node at a respective absolute position within the graph and generating a plurality of tiles that depict images of the sub-graph at each of a plurality of zoom levels; and display a sub-graph image corresponding to a selected position and zoom level. 16. The system of claim 11 , wherein the search queries are top search queries identified based on a number of instances in which the search queries are performed by users of the host site. | 0.72449 |
9,445,209 | 2 | 3 | 2. The computing device of claim 1 wherein the low-power engine is to cause the computing device to transition from a second low-power state to a second active state after recognizing the wake phrase in a second audio input provided by a second user to the microphone while the computing device is in the second low-power state and after verifying the second user based at least in part on a portion of the second audio input comprising the wake phrase while the computing device is in the second low-power state. | 2. The computing device of claim 1 wherein the low-power engine is to cause the computing device to transition from a second low-power state to a second active state after recognizing the wake phrase in a second audio input provided by a second user to the microphone while the computing device is in the second low-power state and after verifying the second user based at least in part on a portion of the second audio input comprising the wake phrase while the computing device is in the second low-power state. 3. The computing device of claim 2 , wherein the command interpretation module is to interpret the portion of the second audio input comprising the wake phrase as a second command to be performed by the computing device. | 0.5 |
8,756,561 | 9 | 10 | 9. A computer software product comprising machine executable instructions stored in a non-transitory storage medium, wherein the machine executable instructions, when executed by a processor of a computer, perform: deriving a meta-model, the meta-model being independent of a particular software application, the derivation comprising identifying a subset of common structures and functions from a plurality of enterprise resource planning applications; deriving a plurality of software models from a specific enterprise resource planning application by executing at least one query on a repository associated with the specific enterprise resource planning application, wherein each of the plurality of software models is compliant with the meta-model by sharing the subset of common structures and functions; and deriving a customer specific software application from the specific enterprise resource planning application and the plurality of software models to enable interacting with the specific enterprise resource planning application using the plurality of software models. | 9. A computer software product comprising machine executable instructions stored in a non-transitory storage medium, wherein the machine executable instructions, when executed by a processor of a computer, perform: deriving a meta-model, the meta-model being independent of a particular software application, the derivation comprising identifying a subset of common structures and functions from a plurality of enterprise resource planning applications; deriving a plurality of software models from a specific enterprise resource planning application by executing at least one query on a repository associated with the specific enterprise resource planning application, wherein each of the plurality of software models is compliant with the meta-model by sharing the subset of common structures and functions; and deriving a customer specific software application from the specific enterprise resource planning application and the plurality of software models to enable interacting with the specific enterprise resource planning application using the plurality of software models. 10. The computer software product of claim 9 , wherein the meta-model is derived using Universal Modeling Language or Eclipse Modeling Framework. | 0.810705 |
8,429,225 | 14 | 15 | 14. The system of claim 12 , wherein said transmission module configured to transmit the congruence data indicative of the extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user comprises: a transmission module configured to transmit the congruence data indicative of the extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user via a network communication interface. | 14. The system of claim 12 , wherein said transmission module configured to transmit the congruence data indicative of the extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user comprises: a transmission module configured to transmit the congruence data indicative of the extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user via a network communication interface. 15. The system of claim 14 , wherein said transmission module configured to transmit the congruence data indicative of the extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user via a network communication interface comprises: a transmission module configured to transmit the congruence data indicative of the extent of congruity between the inferred mental state of the first authoring user and the inferred mental state of the second authoring user to at least one of the first authoring user or the second authoring user via a communication network interface. | 0.5 |
8,370,761 | 19 | 20 | 19. The system of claim 13 , wherein a visual effect circuit provides a spatial or hierarchical overview of a workspace that includes the similarity metric. | 19. The system of claim 13 , wherein a visual effect circuit provides a spatial or hierarchical overview of a workspace that includes the similarity metric. 20. The system of claim 19 , wherein the visual indication is one or more of making the similarity terms bold or highlighted or superimposed over a display of the similar clusters or groups using a different color font. | 0.5 |
8,170,881 | 7 | 13 | 7. A system for call processing using a distributed voice browser, the system comprising: a computing device and a memory encoded with instructions that, when executed by the computing device, are configured to: partition a voice browser into separate components, including a parser, a service processor and a session manager, the components of the voice browser located and executing on separate computing machines, wherein the components of the voice browser, located on separate computing machines, are replicated as needed to support increased call volume; instantiate a plurality of Voice Extensible Markup Language (VXML) parsers, each of the VXML parsers being configured to retrieve and parse VXML script representing a telephone service, and wherein the VXML parsers are instantiated in a first computing machine; instantiate a plurality of service processors, each of the service processors being configured to interpret VXML data parsed by the VXML parsers, and wherein the service processors are instantiated in a second computing machine; instantiate a plurality of session managers, wherein the session managers are instantiated in a third computing machine; receive a call by telephone switch, wherein the telephone switch selects a free channel processor of a media gateway having a plurality of channel processors, queries the media gateway to accept the call, and applies the call to the selected channel processor; identify call processing VXML scripts associated with the received call; identify a service processor and transmitting the identified VXML scripts to the identified service processor; implement the telephone service by the service processor by executing the identified VXML scripts; determine a change in call volume during run time; and vary, at run time to support increased call volume, a number of service processors, a number of VXML parsers, and a number of session managers independently in response to determining a change in call volume detected during run time. | 7. A system for call processing using a distributed voice browser, the system comprising: a computing device and a memory encoded with instructions that, when executed by the computing device, are configured to: partition a voice browser into separate components, including a parser, a service processor and a session manager, the components of the voice browser located and executing on separate computing machines, wherein the components of the voice browser, located on separate computing machines, are replicated as needed to support increased call volume; instantiate a plurality of Voice Extensible Markup Language (VXML) parsers, each of the VXML parsers being configured to retrieve and parse VXML script representing a telephone service, and wherein the VXML parsers are instantiated in a first computing machine; instantiate a plurality of service processors, each of the service processors being configured to interpret VXML data parsed by the VXML parsers, and wherein the service processors are instantiated in a second computing machine; instantiate a plurality of session managers, wherein the session managers are instantiated in a third computing machine; receive a call by telephone switch, wherein the telephone switch selects a free channel processor of a media gateway having a plurality of channel processors, queries the media gateway to accept the call, and applies the call to the selected channel processor; identify call processing VXML scripts associated with the received call; identify a service processor and transmitting the identified VXML scripts to the identified service processor; implement the telephone service by the service processor by executing the identified VXML scripts; determine a change in call volume during run time; and vary, at run time to support increased call volume, a number of service processors, a number of VXML parsers, and a number of session managers independently in response to determining a change in call volume detected during run time. 13. The system of claim 7 , wherein said VXML parsers are configured to execute within at least one virtual machine. | 0.804714 |
7,603,330 | 1 | 8 | 1. A computer-implemented method for automatically classifying a first question, the method comprising: receiving unlabeled audio or digital text data from an input module, said unlabeled audio or digital text data comprising data that is not previously associated with an expected answer; automatically labeling said unlabeled audio or digital text data using a processor to produce first labeled audio or digital text data associating a first answer with the unlabeled audio or digital text data using a first artificial neural network, said first artificial neural network comprising a first set of weights, said first artificial neural network producing the first labeled audio or digital text data by performing one or more auxiliary tasks analyzing characteristics of said unlabeled audio or digital text data; transferring said first set of weights to a second artificial neural network; receiving second labeled audio or digital text data comprising a second question and a corresponding answer; training said second artificial neural network with the processor using said second labeled audio or digital text data by modifying a second set of weights associated with the second artificial neural network responsive to the second labeled audio or digital text data and freezing the first set of weights; receiving the first question from the input module; and associating a question category with the first question using said second artificial neural network, said question category identifying a source for retrieving text data or audio data describing an answer corresponding to the first question. | 1. A computer-implemented method for automatically classifying a first question, the method comprising: receiving unlabeled audio or digital text data from an input module, said unlabeled audio or digital text data comprising data that is not previously associated with an expected answer; automatically labeling said unlabeled audio or digital text data using a processor to produce first labeled audio or digital text data associating a first answer with the unlabeled audio or digital text data using a first artificial neural network, said first artificial neural network comprising a first set of weights, said first artificial neural network producing the first labeled audio or digital text data by performing one or more auxiliary tasks analyzing characteristics of said unlabeled audio or digital text data; transferring said first set of weights to a second artificial neural network; receiving second labeled audio or digital text data comprising a second question and a corresponding answer; training said second artificial neural network with the processor using said second labeled audio or digital text data by modifying a second set of weights associated with the second artificial neural network responsive to the second labeled audio or digital text data and freezing the first set of weights; receiving the first question from the input module; and associating a question category with the first question using said second artificial neural network, said question category identifying a source for retrieving text data or audio data describing an answer corresponding to the first question. 8. The method of claim 1 , wherein said first and second artificial neural networks each comprise an input layer, a hidden layer and an output layer. | 0.83944 |
8,494,983 | 2 | 5 | 2. The computer-implemented method of claim 1 , wherein the quality comprises a calculated size of a region comprising the common pattern. | 2. The computer-implemented method of claim 1 , wherein the quality comprises a calculated size of a region comprising the common pattern. 5. The computer-implemented method of claim 2 , wherein the ranking comprises ranking an image from the query results having a largest calculated region that comprises the common pattern as a highest-ranking image of the query results. | 0.5 |
10,148,961 | 1 | 2 | 1. A method for entropy coding of video data, the method comprising: determining a window size of a plurality of window sizes for a first context of a plurality of contexts used in a context-adaptive binary arithmetic coding (CABAC) process; CABAC coding, based on a probability state of the first context, a bin of a value for a first syntax element of the video data; updating the probability state of the first context based on the window size for the first context and the coded bin of the value for the first syntax element; determining a window size of the plurality of window sizes for a second context of the plurality of contexts, wherein the window size for the second context is different than the window size for the first context, and wherein the window size for the second context is not used to update the probability state of the first context; CABAC coding, based on a probability state of the second context, a bin of a value for a second syntax element of the video data; and updating the probability state of the second context based on the window size for the second context and the coded bin for the second syntax element. | 1. A method for entropy coding of video data, the method comprising: determining a window size of a plurality of window sizes for a first context of a plurality of contexts used in a context-adaptive binary arithmetic coding (CABAC) process; CABAC coding, based on a probability state of the first context, a bin of a value for a first syntax element of the video data; updating the probability state of the first context based on the window size for the first context and the coded bin of the value for the first syntax element; determining a window size of the plurality of window sizes for a second context of the plurality of contexts, wherein the window size for the second context is different than the window size for the first context, and wherein the window size for the second context is not used to update the probability state of the first context; CABAC coding, based on a probability state of the second context, a bin of a value for a second syntax element of the video data; and updating the probability state of the second context based on the window size for the second context and the coded bin for the second syntax element. 2. The method of claim 1 , further comprising: CABAC coding another bin associated with the first context based on the updated probability state of the first context. | 0.632743 |
8,156,429 | 1 | 5 | 1. A server communicatively coupled to an Internet Protocol “IP” network and configured to transfer markup language based content that represents a web page to a client computer within the network, the server comprising: a dispatcher module that: interfaces to a content source and receives a markup language content from the content source, wherein the received markup language content is targeted toward a browser application at a requesting client computer and includes one or more browser links; provides at least a portion of the received markup language content to a markup language object module; receives modified markup language content from the markup language object module; and sends the modified markup language content toward the browser application at the requesting client computer; and the markup language object module that: receives the provided markup language content from the dispatcher module; parses the provided markup language content; identifies a browser link within the provided markup language content; traverses the browser link to obtain the corresponding object; replaces the browser link in the provided markup language content with the corresponding object to modify the provided markup language content; and provides the modified markup language content to the dispatcher module; wherein the server operates in an intermediate node communicatively positioned between the content source and the requesting client; wherein the modified markup language content that is sent toward the browser application has a reduced number of browser links than the markup language content received from the content server; and wherein the modification is transparent to the browser application at the client computer. | 1. A server communicatively coupled to an Internet Protocol “IP” network and configured to transfer markup language based content that represents a web page to a client computer within the network, the server comprising: a dispatcher module that: interfaces to a content source and receives a markup language content from the content source, wherein the received markup language content is targeted toward a browser application at a requesting client computer and includes one or more browser links; provides at least a portion of the received markup language content to a markup language object module; receives modified markup language content from the markup language object module; and sends the modified markup language content toward the browser application at the requesting client computer; and the markup language object module that: receives the provided markup language content from the dispatcher module; parses the provided markup language content; identifies a browser link within the provided markup language content; traverses the browser link to obtain the corresponding object; replaces the browser link in the provided markup language content with the corresponding object to modify the provided markup language content; and provides the modified markup language content to the dispatcher module; wherein the server operates in an intermediate node communicatively positioned between the content source and the requesting client; wherein the modified markup language content that is sent toward the browser application has a reduced number of browser links than the markup language content received from the content server; and wherein the modification is transparent to the browser application at the client computer. 5. The server of claim 1 , further comprising an object deliverer thread that: receives a browser link from the markup language object module; fetches the object associated with the browser link; and provide the fetched object to the markup language object module; and the markup language object module further to traverses the browser link by providing the browser link to the object deliverer thread and receiving the fetched object from the object deliverer thread. | 0.5 |
9,626,685 | 14 | 15 | 14. A system comprising: a plurality of processors; a physical entity request engine implemented by at least one of said plurality of processors comprising: a request sub-module that receives one or more requests to display information related to first a physical entity; a transform sub-module that transforms the request into search data; a subset generation and matching sub-module that dynamically applies the search data to descriptive information related to a set of other physical entities known to a network, said application comprising deriving a subset of other physical entities matching the search data from the descriptive information related to the set of other known physical entities, the descriptive information corresponding to the other physical entities is analyzed as part of said deriving the subset of other physical entities that match the search data; and an attention rank engine for ranking the subset of other physical entities to form a ranked subset of physical entities after having generated entity rank, attention rank, and personal rank, the ranked subset based upon the applied search data, the ranked subset comprising the descriptive information corresponding to the other physical entities of the subset; and a mapping manager module implemented by at least one of said plurality of processors for presenting information related to the ranked subset of physical entities to a first user, the presenting of the ranked physical entities information being dependent upon user information stored in the network, the user information comprising data generated by the user, data associated with the user, and data associated with the request. | 14. A system comprising: a plurality of processors; a physical entity request engine implemented by at least one of said plurality of processors comprising: a request sub-module that receives one or more requests to display information related to first a physical entity; a transform sub-module that transforms the request into search data; a subset generation and matching sub-module that dynamically applies the search data to descriptive information related to a set of other physical entities known to a network, said application comprising deriving a subset of other physical entities matching the search data from the descriptive information related to the set of other known physical entities, the descriptive information corresponding to the other physical entities is analyzed as part of said deriving the subset of other physical entities that match the search data; and an attention rank engine for ranking the subset of other physical entities to form a ranked subset of physical entities after having generated entity rank, attention rank, and personal rank, the ranked subset based upon the applied search data, the ranked subset comprising the descriptive information corresponding to the other physical entities of the subset; and a mapping manager module implemented by at least one of said plurality of processors for presenting information related to the ranked subset of physical entities to a first user, the presenting of the ranked physical entities information being dependent upon user information stored in the network, the user information comprising data generated by the user, data associated with the user, and data associated with the request. 15. The system of claim 14 further comprising: a web rank module that collects web data produced by user interactions with web pages; a world rank module that generates an entity rank for each physical entity in the set of other physical entities; and a request initiation module that initiates a request to display information related to the one or more physical entities. | 0.665171 |
8,989,438 | 23 | 33 | 23. A non-transitory computer-readable storage medium implementing a mobile body track identification method comprising: generating track-coupling candidates corresponding to combinations of tracks of mobile bodies detected in a predetermined time in the past; generating sets of track-coupling candidate/identification pairs combining track-coupling candidates and identifications of mobile bodies detected in the predetermined time in the past, thus generating hypotheses corresponding to sets of track-coupling candidate/identification pairs satisfying a predetermined condition; selecting individual hypotheses so as to calculate identification likelihoods representing likelihoods of detecting identifications with respect to tracks indicated by track-coupling candidates included in each of track-coupling candidate/identification pairs ascribed to each of the selected hypotheses; integrating identification likelihoods for each track-coupling candidate/identification pair so as to calculate an identification likelihood for each of the selected hypotheses; and estimating a most-probable hypothesis based on identification likelihoods of hypotheses. | 23. A non-transitory computer-readable storage medium implementing a mobile body track identification method comprising: generating track-coupling candidates corresponding to combinations of tracks of mobile bodies detected in a predetermined time in the past; generating sets of track-coupling candidate/identification pairs combining track-coupling candidates and identifications of mobile bodies detected in the predetermined time in the past, thus generating hypotheses corresponding to sets of track-coupling candidate/identification pairs satisfying a predetermined condition; selecting individual hypotheses so as to calculate identification likelihoods representing likelihoods of detecting identifications with respect to tracks indicated by track-coupling candidates included in each of track-coupling candidate/identification pairs ascribed to each of the selected hypotheses; integrating identification likelihoods for each track-coupling candidate/identification pair so as to calculate an identification likelihood for each of the selected hypotheses; and estimating a most-probable hypothesis based on identification likelihoods of hypotheses. 33. The non-transitory computer-readable storage medium implementing a mobile body track identification method according to claim 23 further comprising: storing environmental information representing a transient time of a mobile body along a passable path in a tracking area; calculating a real transient time from a track disappearance detection time to a next track appearance detection time with respect to each track-coupling candidate; estimating a transient time of a mobile body from a track disappearance time to a next track appearance time based on the environmental information; and precluding track-coupling candidates each having the estimated transient time longer than the real transient time from track-coupling candidates for use in generation of hypotheses. | 0.617095 |
9,146,908 | 13 | 14 | 13. The system according to claim 10 , further comprising: an execution context generating module configured to generate the execution context for the at least one rule object of the extracted part of the rule objects, and register the execution context to the context registry. | 13. The system according to claim 10 , further comprising: an execution context generating module configured to generate the execution context for the at least one rule object of the extracted part of the rule objects, and register the execution context to the context registry. 14. The system according to claim 13 , where the execution context generating module is configured to generate the execution context for the at least one rule object of the extracted part of the rule objects according to a predefined function. | 0.5 |
9,892,159 | 8 | 12 | 8. A method for generating an execution plan for a query in a relational database system, comprising: generating one or more initial logical representations of the query, each initial logical representation including a plurality of operators; performing a bounded exploration process comprising: (a) adding the operators of the one or more initial logical representations to a data structure; (b) identifying zero or more patterns of operators within the data structure that are eligible for the application of a transformation rule, a pattern of operators being eligible for the application of a transformation rule if (i) the pattern of operators matches a pattern associated with the transformation rule and (ii) a search distance associated with one or more of the operators in the pattern of operators, and that is a numerical value, is less than a maximum allowable search distance that is a numerical value corresponding to an upper bound of the search distance associated with the one or more of the operators in the pattern of operators to enable bounding of the exploration process; (c) applying a transformation rule to each eligible pattern of operators identified in step (b) to generate a logically-equivalent pattern of operators within the data structure, thereby generating one or more additional logical representations of the query within the data structure; (d) assigning a search distance to each operator within each logically-equivalent pattern of operators generated during step (c), the assigned search distance being a function of a search distance of one or more operators within the eligible pattern of operators to which the logically-equivalent pattern of operators corresponds; and (e) repeatedly performing steps (b), (c) and (d) until no further patterns of operators that are eligible for the application of a transformation rule can be identified within the data structure; obtaining one or more physical implementation alternatives for each of the logical representations of the query included in the data structure; and selecting one of the physical implementation alternatives as the execution plan. | 8. A method for generating an execution plan for a query in a relational database system, comprising: generating one or more initial logical representations of the query, each initial logical representation including a plurality of operators; performing a bounded exploration process comprising: (a) adding the operators of the one or more initial logical representations to a data structure; (b) identifying zero or more patterns of operators within the data structure that are eligible for the application of a transformation rule, a pattern of operators being eligible for the application of a transformation rule if (i) the pattern of operators matches a pattern associated with the transformation rule and (ii) a search distance associated with one or more of the operators in the pattern of operators, and that is a numerical value, is less than a maximum allowable search distance that is a numerical value corresponding to an upper bound of the search distance associated with the one or more of the operators in the pattern of operators to enable bounding of the exploration process; (c) applying a transformation rule to each eligible pattern of operators identified in step (b) to generate a logically-equivalent pattern of operators within the data structure, thereby generating one or more additional logical representations of the query within the data structure; (d) assigning a search distance to each operator within each logically-equivalent pattern of operators generated during step (c), the assigned search distance being a function of a search distance of one or more operators within the eligible pattern of operators to which the logically-equivalent pattern of operators corresponds; and (e) repeatedly performing steps (b), (c) and (d) until no further patterns of operators that are eligible for the application of a transformation rule can be identified within the data structure; obtaining one or more physical implementation alternatives for each of the logical representations of the query included in the data structure; and selecting one of the physical implementation alternatives as the execution plan. 12. The method of claim 8 , wherein obtaining the one or more physical implementation alternatives for each of the logical representations of the query included in the data structure comprises: converting one or more logical operators in the data structure to physical operators. | 0.675581 |
9,258,351 | 1 | 3 | 1. A computerized message routing system comprising: a plurality of disparate messaging subsystems having different transaction management protocols, wherein the disparate messaging subsystems include a publisher configured to publish messages under general subjects using different transports; a router configured to run (i) a consumer process that includes multiple consumer threads, (ii) a publisher process that includes multiple publisher threads configured to publish messages from the router, and (iii) an application configured to execute multiple routing rules on inbound messages received from the publisher, wherein the application is also configured to determine a set of specific subjects for each of the inbound messages, the router configured to publish outbound messages to consumers in accordance with one or more subscriptions based on the specific subjects and the general subjects; and a library having multiple introspection routines configured to be dynamically loaded by the router; wherein the application is further configured to determine a message type. | 1. A computerized message routing system comprising: a plurality of disparate messaging subsystems having different transaction management protocols, wherein the disparate messaging subsystems include a publisher configured to publish messages under general subjects using different transports; a router configured to run (i) a consumer process that includes multiple consumer threads, (ii) a publisher process that includes multiple publisher threads configured to publish messages from the router, and (iii) an application configured to execute multiple routing rules on inbound messages received from the publisher, wherein the application is also configured to determine a set of specific subjects for each of the inbound messages, the router configured to publish outbound messages to consumers in accordance with one or more subscriptions based on the specific subjects and the general subjects; and a library having multiple introspection routines configured to be dynamically loaded by the router; wherein the application is further configured to determine a message type. 3. The computerized message routing system of claim 1 , wherein the routing system is configured to add additional consumer threads to the multiple consumer threads based on a performance of the router. | 0.547085 |
9,582,610 | 5 | 6 | 5. The computer-implemented method of claim 1 , further comprising increasing a number of the rectangles of the grid in response to a further user-selected search result. | 5. The computer-implemented method of claim 1 , further comprising increasing a number of the rectangles of the grid in response to a further user-selected search result. 6. The computer-implemented method of claim 5 , further comprising increasing the number of the rectangles of the grid rather than repositioning previously selected search results based at least in part on another aspect ratio of the further user-selected search result. | 0.5 |
8,959,477 | 16 | 19 | 16. A system, comprising: memory operable to store scripting language files; one or more processors operable to: provide a scripting language editor for generating software components for a business application, the scripting language editor configured to receive input associated with a scripting language and save the input and software components into a scripting language file on a repository on a backend server system; provide a scripting language compiler for identifying a scripting language file and retrieving and cross-compiling the software components of the scripting language file saved by the scripting language editor, wherein the cross-compiling comprises: retrieve metadata from a backend server system, the metadata associated with at least one of a business object or a data type of a platform of the business application; create one or more metadata-driven context libraries associated with the scripting language, the one or more metadata-driven context libraries providing access to context information for the at least one business object or data type at runtime; and generate, by a computer, a business application language file comprising only reusable software components based on a translation of the software components of the scripting language file and the metadata; and execute the business application language file at runtime, the business application language file comprising only code that accesses context information at runtime based on the metadata, wherein the code within the business application language file when executed drives the one or more metadata-driven context libraries to produce context-specific source code corresponding to the reusable software components. | 16. A system, comprising: memory operable to store scripting language files; one or more processors operable to: provide a scripting language editor for generating software components for a business application, the scripting language editor configured to receive input associated with a scripting language and save the input and software components into a scripting language file on a repository on a backend server system; provide a scripting language compiler for identifying a scripting language file and retrieving and cross-compiling the software components of the scripting language file saved by the scripting language editor, wherein the cross-compiling comprises: retrieve metadata from a backend server system, the metadata associated with at least one of a business object or a data type of a platform of the business application; create one or more metadata-driven context libraries associated with the scripting language, the one or more metadata-driven context libraries providing access to context information for the at least one business object or data type at runtime; and generate, by a computer, a business application language file comprising only reusable software components based on a translation of the software components of the scripting language file and the metadata; and execute the business application language file at runtime, the business application language file comprising only code that accesses context information at runtime based on the metadata, wherein the code within the business application language file when executed drives the one or more metadata-driven context libraries to produce context-specific source code corresponding to the reusable software components. 19. The system of claim 16 , wherein the scripting language editor includes a visual programming shell providing core source code editing features. | 0.695021 |
7,565,013 | 1 | 3 | 1. A character recognition method performed by a character recognition device, comprising the steps of: receiving information in which a device identifier, character image data, and a corrected character code are associated with one another, storing the received information as a new entry in a correction history table, deciding whether or not information of each entry included in the correction history table satisfies a predetermined condition, extracting a plurality of character image data pieces from the entries included in the correction history table according to a result of the decision, producing new character image data by performing difference detection on the extracted character image data, and storing, in an additional table, information in which the new character image data, a character code, and a device identifier are associated with one another, deciding whether or not the additional table has a device identifier received with a character recognition instruction when receiving information in which the device identifier and character image data are associated with each other as well as the character recognition instruction, performing character recognition based on the additional table when it is decided that the additional table has the device identifier received with the character recognition instruction, and performing character recognition, when it is decided that the additional table does not have the device identifier received with the character recognition instruction, based on a basic table storing an entry in which predetermined character image data and a character code are associated with each other. | 1. A character recognition method performed by a character recognition device, comprising the steps of: receiving information in which a device identifier, character image data, and a corrected character code are associated with one another, storing the received information as a new entry in a correction history table, deciding whether or not information of each entry included in the correction history table satisfies a predetermined condition, extracting a plurality of character image data pieces from the entries included in the correction history table according to a result of the decision, producing new character image data by performing difference detection on the extracted character image data, and storing, in an additional table, information in which the new character image data, a character code, and a device identifier are associated with one another, deciding whether or not the additional table has a device identifier received with a character recognition instruction when receiving information in which the device identifier and character image data are associated with each other as well as the character recognition instruction, performing character recognition based on the additional table when it is decided that the additional table has the device identifier received with the character recognition instruction, and performing character recognition, when it is decided that the additional table does not have the device identifier received with the character recognition instruction, based on a basic table storing an entry in which predetermined character image data and a character code are associated with each other. 3. The character recognition method according to claim 1 , wherein in the difference detection, a difference is determined between coordinate data on character image data included in the basic table storing an entry in which predetermined character image data and a character code are associated with each other and coordinate data on a plurality of character image data pieces extracted from the correction history table, coordinate data is determined for an average value of coordinate data on the determined difference, and the determined coordinate data on the average value and the coordinate data on the character image data included in the basic table are combined. | 0.5 |
8,493,229 | 1 | 9 | 1. A product container, the container comprising: a body having an opening associated with an interior portion; a product disposed within the interior portion; an enclosure member positioned proximate to the opening and movable between a first position in which the product is retained in the interior portion and a second position in which the product can exit the interior portion via the opening; a sensor operably coupled to at least one of the body and the enclosure member; and an audible warning system carried by the container and operably coupled to the sensor, wherein the audible warning system is configured to audibly output a spoken warning regarding the product in response to receiving an indication from the sensor associated with movement of the enclosure member from the first position toward the second position. | 1. A product container, the container comprising: a body having an opening associated with an interior portion; a product disposed within the interior portion; an enclosure member positioned proximate to the opening and movable between a first position in which the product is retained in the interior portion and a second position in which the product can exit the interior portion via the opening; a sensor operably coupled to at least one of the body and the enclosure member; and an audible warning system carried by the container and operably coupled to the sensor, wherein the audible warning system is configured to audibly output a spoken warning regarding the product in response to receiving an indication from the sensor associated with movement of the enclosure member from the first position toward the second position. 9. The container of claim 1 wherein the sensor is a temperature sensor, and the indication from the sensor is associated with a detected temperature outside of a predetermined temperature range. | 0.792291 |
7,987,416 | 13 | 14 | 13. A computer-implemented method of extracting information comprising: defining a plurality of reusable operators, wherein each operator performs a predefined information extraction task different from the other operators; specifying a composition of said reusable operators to form a composite annotator, wherein each operator receives a searchable item and generates one or more output annotations; and storing the output annotations for use during a search, wherein the plurality of reusable operators include an composition operator, the searchable items comprising text, and wherein the composition operator receives an input annotation and two reference annotations and generates one or more output annotations comprising text between the two reference annotations. | 13. A computer-implemented method of extracting information comprising: defining a plurality of reusable operators, wherein each operator performs a predefined information extraction task different from the other operators; specifying a composition of said reusable operators to form a composite annotator, wherein each operator receives a searchable item and generates one or more output annotations; and storing the output annotations for use during a search, wherein the plurality of reusable operators include an composition operator, the searchable items comprising text, and wherein the composition operator receives an input annotation and two reference annotations and generates one or more output annotations comprising text between the two reference annotations. 14. The method of claim 13 wherein the composition operator receives a specification of an output annotation type. | 0.5 |
10,033,775 | 3 | 5 | 3. The method of claim 2 further comprising: determining, by the processor, the frequency of the user's consumption of information based on a number of content items consumed by the user in each of the content categories. | 3. The method of claim 2 further comprising: determining, by the processor, the frequency of the user's consumption of information based on a number of content items consumed by the user in each of the content categories. 5. The method of claim 3 , further comprising: indicating, by the processor, in the dashboard, one or more of the content categories in which the user infrequently consumes content. | 0.5 |
7,702,574 | 1 | 10 | 1. A computerized apparatus for managing risk associated with earnings estimates for a company, the apparatus comprising: a computer server comprising a processor and a digital storage and accessible with a system access device via a communications network; and executable software stored on the computer server and executable on demand, the executable software operative with the processor to cause the computer server to: receive into the digital storage data descriptive of multiple earnings estimates, each earnings estimate generated by a respective bank; receive into the digital storage data indicative of one or more business relationships comprising a bank and the company; generate a first consensus estimate excluding earnings estimates received from the bank with the data indicative of one or more business relationships with the company; transmit, to the bank, data comprising a message that the bank's earnings estimate is excluded from the first consensus estimate; and generate a suggested action based upon the first consensus estimate. | 1. A computerized apparatus for managing risk associated with earnings estimates for a company, the apparatus comprising: a computer server comprising a processor and a digital storage and accessible with a system access device via a communications network; and executable software stored on the computer server and executable on demand, the executable software operative with the processor to cause the computer server to: receive into the digital storage data descriptive of multiple earnings estimates, each earnings estimate generated by a respective bank; receive into the digital storage data indicative of one or more business relationships comprising a bank and the company; generate a first consensus estimate excluding earnings estimates received from the bank with the data indicative of one or more business relationships with the company; transmit, to the bank, data comprising a message that the bank's earnings estimate is excluded from the first consensus estimate; and generate a suggested action based upon the first consensus estimate. 10. The computerized apparatus of claim 1 wherein the executable software is additionally operative with the processor to cause the computer server to transmit data comprising a reason for the exclusion of the earnings estimate from the consensus estimate. | 0.731656 |
5,434,953 | 10 | 12 | 10. A processor-based method for reducing a binary input image to produce a reduced image wherein the input image is divided into M.times.N tiles, each tile has M pixels down and N pixels across, and each tile is mapped to a single pixel in the reduced image, comprising the steps, carried out once for each tile, of: applying a convolution window defined by a plurality of active pixel positions when registered to the tile, the number of active pixel positions in the tile being less than the number of pixels in the tile; determining, on the basis of pixel values at the active pixel positions, whether at least a predetermined number of subconditions are met, each subcondition having an associated threshold and an associated subset of the active pixel positions, each subcondition requiring that at least the associated threshold number of pixels at the active pixel positions in the associated subset be ON; and turning ON the pixel in the reduced image if and only if the result of said determining step is affirmative. | 10. A processor-based method for reducing a binary input image to produce a reduced image wherein the input image is divided into M.times.N tiles, each tile has M pixels down and N pixels across, and each tile is mapped to a single pixel in the reduced image, comprising the steps, carried out once for each tile, of: applying a convolution window defined by a plurality of active pixel positions when registered to the tile, the number of active pixel positions in the tile being less than the number of pixels in the tile; determining, on the basis of pixel values at the active pixel positions, whether at least a predetermined number of subconditions are met, each subcondition having an associated threshold and an associated subset of the active pixel positions, each subcondition requiring that at least the associated threshold number of pixels at the active pixel positions in the associated subset be ON; and turning ON the pixel in the reduced image if and only if the result of said determining step is affirmative. 12. The method of claim 10 wherein the convolution window fits entirely within the tile. | 0.842857 |
4,744,050 | 6 | 7 | 6. A method for automatically registering frequently used phrases according to claim 1, wherein said registering step is carried out each time the total number of phrases generated in said first or second conversion reaches a predetermined value. | 6. A method for automatically registering frequently used phrases according to claim 1, wherein said registering step is carried out each time the total number of phrases generated in said first or second conversion reaches a predetermined value. 7. A method for automatically registering frequently used phrases according to claim 6, wherein said registering step includes a step of selecting a phrase from among the phrases already stored in the phrase table which is not yet registered in the macro table and having the highest frequency of occurrence among the phrases registered in the phrase table as the phrase to be additionally registered in the macro table. | 0.5 |
9,092,490 | 16 | 21 | 16. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprises a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query. | 16. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query; obtaining search results including publication search results responsive to the query, wherein each publication search result refers to a respective book; determining that a score for a highest-ranked publication search result satisfies a threshold relative to respective scores of one or more other publication search results to be provided in response to the query, wherein the highest-ranked publication search result refers to a book; in response to determining that the score for the highest-ranked publication search result satisfies the threshold relative to respective scores of the other publication search results, wherein the score for the highest ranked publication search result satisfies the threshold if the score is at least a threshold multiple of a second score for a second publication search result ranked second in a ranked order of the publication search results, generating a rich result for the highest-ranked publication search result, wherein the rich result for the highest-ranked publication search result comprises more elements of data than any of the other publication search results to be provided in response to the query, wherein the rich result for the highest-ranked publication search result comprises data from one or more web resources that refer to the book, and wherein the elements of data for the rich result comprises a title of the book, an author of the book, and a link to a website related to the book; and providing the rich result and the one or more other publication search results in response to the query. 21. The computer program product of claim 16 , wherein the operations further comprise: obtaining data for a plurality of book resources, wherein a book resource is a web resource that includes information about the book; and generating a metadata representation for the book using overlapping data from the plurality of book resources, wherein generating the rich result for the highest-ranked publication search result comprises obtaining the elements of data for the rich result from the metadata representation for the book. | 0.5 |
7,610,281 | 9 | 10 | 9. A computer-readable medium having stored thereon instructions that when executed by a processor cause the processor to perform a method, the method comprising: identifying a set of candidate documents from a set of indexed documents by comparing a first set of grams to a second set of grams, the first set of grams being related to a query for documents, the second set of grams being related to indexed documents; selecting a subset of the set of candidate documents to partially reconstruct based on a similarity score; selectively producing a partially reconstructed document from the subset of candidate documents; selectively computing an edit distance between a first string related to the first set of grams and a second string related to the partially reconstructed document; and providing data corresponding to the edit distance. | 9. A computer-readable medium having stored thereon instructions that when executed by a processor cause the processor to perform a method, the method comprising: identifying a set of candidate documents from a set of indexed documents by comparing a first set of grams to a second set of grams, the first set of grams being related to a query for documents, the second set of grams being related to indexed documents; selecting a subset of the set of candidate documents to partially reconstruct based on a similarity score; selectively producing a partially reconstructed document from the subset of candidate documents; selectively computing an edit distance between a first string related to the first set of grams and a second string related to the partially reconstructed document; and providing data corresponding to the edit distance. 10. The computer-readable medium of claim 9 , where a gram may include one or more of, a skipping character, a substitution character, and a delimiter character; and where identifying a set of candidate documents includes: selecting one of a plurality of overlapping matching grams for grams appearing in both the first set of grams and the second set of grams; finding one or more matches for the selected query gram in an inverted index; and retrieving a document identifier from the inverted index based on the one or more matches for the selected query gram. | 0.831737 |
9,324,034 | 2 | 3 | 2. The method of claim 1 , further comprising: applying the factors to the corpus of behavior vectors to generate a second family of classifier models that identify fewer data points as being relevant for enabling the mobile device to conclusively determine whether the mobile device behavior is not benign; and generating a mobile device classifier based on the second family of classifier models. | 2. The method of claim 1 , further comprising: applying the factors to the corpus of behavior vectors to generate a second family of classifier models that identify fewer data points as being relevant for enabling the mobile device to conclusively determine whether the mobile device behavior is not benign; and generating a mobile device classifier based on the second family of classifier models. 3. The method of claim 2 , further comprising: sending the mobile device classifier to a mobile computing device. | 0.5 |
9,324,338 | 1 | 16 | 1. A method for enhancing an input noisy signal, wherein the input noisy signal is a mixture of a clean speech signal and a noise signal, comprising: determining from the input noisy signal, using a model of the clean speech signal and a model of the noise signal, sequences of hidden variables including at least one sequence of hidden variables representing an excitation component of the clean speech signal, at least one sequence of hidden variables representing a filter component of the clean speech signal, and at least one sequence of hidden variables representing the noise signal, wherein the model of the clean speech signal includes a non-negative source-filter dynamical system (NSFDS) constraining the hidden variables representing the excitation component to be statistically dependent over time and constraining the hidden variables representing the filter component to be statistically dependent over time, and wherein the sequences of hidden variables include hidden variables determined as a non-negative linear combination of non-negative basis functions; and generating an output signal using a product of corresponding hidden variables representing the excitation and the filter components, wherein steps of the method are performed by a processor. | 1. A method for enhancing an input noisy signal, wherein the input noisy signal is a mixture of a clean speech signal and a noise signal, comprising: determining from the input noisy signal, using a model of the clean speech signal and a model of the noise signal, sequences of hidden variables including at least one sequence of hidden variables representing an excitation component of the clean speech signal, at least one sequence of hidden variables representing a filter component of the clean speech signal, and at least one sequence of hidden variables representing the noise signal, wherein the model of the clean speech signal includes a non-negative source-filter dynamical system (NSFDS) constraining the hidden variables representing the excitation component to be statistically dependent over time and constraining the hidden variables representing the filter component to be statistically dependent over time, and wherein the sequences of hidden variables include hidden variables determined as a non-negative linear combination of non-negative basis functions; and generating an output signal using a product of corresponding hidden variables representing the excitation and the filter components, wherein steps of the method are performed by a processor. 16. The method of claim 1 , wherein parameters of the model of clean speech signals are estimated from a database of training clean speech signals. | 0.758224 |
9,443,169 | 6 | 7 | 6. The computer implemented method of classifying a digital image according to claim 1 , wherein the MI-SVM classifier is formulated as min { w ( v ) , C ( v ) } ∑ v = 1 V ( 1 2 w ( v ) 2 + C ( v ) ∑ I ( v ) ξ I ( v ) ) s.t. (subject to)
Y I ·( w (v) ·x I S I +b v )≧1−ξ I(v) where W represents a hyperplane slope of a hyperplane associated with the MI-SVM, C is a cross validated selective constant, b represents an offset of the hyperplane, I represents a bag of image regions associated with a training image, S I represents an image region selected for bag I; v represents a view point, V represents a total number of viewpoints v, x I S I represents an image region selected from bag I, Y I represents the object type label associated with bag I, and ξ I(v) represents a fixed value. | 6. The computer implemented method of classifying a digital image according to claim 1 , wherein the MI-SVM classifier is formulated as min { w ( v ) , C ( v ) } ∑ v = 1 V ( 1 2 w ( v ) 2 + C ( v ) ∑ I ( v ) ξ I ( v ) ) s.t. (subject to)
Y I ·( w (v) ·x I S I +b v )≧1−ξ I(v) where W represents a hyperplane slope of a hyperplane associated with the MI-SVM, C is a cross validated selective constant, b represents an offset of the hyperplane, I represents a bag of image regions associated with a training image, S I represents an image region selected for bag I; v represents a view point, V represents a total number of viewpoints v, x I S I represents an image region selected from bag I, Y I represents the object type label associated with bag I, and ξ I(v) represents a fixed value. 7. The computer implemented method of classifying a digital image according to claim 6 , wherein an iterative process is used between training of the w (v) and reasoning about image region selection based on positive bags including at least one discriminative image region including a CRF (Conditional Random Field), where E ( { L I } | { v i } ) = ∑ I φ ( L I | v I ) + ∑ I ∑ J δ ( L I , L J | v I , v J ) where
φ( L I |v I )=−( w (v I ) ·x I L I +b (v I ) ), and the pairwise terms (L I ,L J |v I ,v J ) account for geometry and appearance constraints relative to a plurality of viewpoints, L I and L J represents a variable based on indices of an image region selected within bag I, E represents an energy function which is minimized, δ is an energy term, and φ is an energy term. | 0.5 |
7,966,341 | 6 | 20 | 6. The method of claim 1 , further comprising: receiving a second query that includes a second date-qualified query term; inspecting the second query to determine that the second query includes a date; and in response to determining that the second query includes a date, establishing the second query as not being a date-qualified query. | 6. The method of claim 1 , further comprising: receiving a second query that includes a second date-qualified query term; inspecting the second query to determine that the second query includes a date; and in response to determining that the second query includes a date, establishing the second query as not being a date-qualified query. 20. A computer-readable storage storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 6 . | 0.568376 |
9,779,388 | 1 | 6 | 1. A computer-implemented method of disambiguating organization names, the method comprising: selecting multiple names of organizations; and using the computer to: extract a first name identified in an electronic content item, wherein multiple different organizations have the first name; for each of the multiple organizations, assemble a corresponding feature vector comprising: a set of name features reflecting use of the first name in the electronic content item; and a set of affiliation features reflecting one or more affiliations of the organization also identified in the electronic content item; execute a model to identify, among the multiple organizations, only one organization to which the electronic content item refers; and make the electronic content item available to a user interested in content items that reference the one organization. | 1. A computer-implemented method of disambiguating organization names, the method comprising: selecting multiple names of organizations; and using the computer to: extract a first name identified in an electronic content item, wherein multiple different organizations have the first name; for each of the multiple organizations, assemble a corresponding feature vector comprising: a set of name features reflecting use of the first name in the electronic content item; and a set of affiliation features reflecting one or more affiliations of the organization also identified in the electronic content item; execute a model to identify, among the multiple organizations, only one organization to which the electronic content item refers; and make the electronic content item available to a user interested in content items that reference the one organization. 6. The method of claim 1 , wherein each organization's corresponding feature vector further comprises: a set of wrongness features derived from correlation of the electronic content item with one or more other content items known to not reference the organization. | 0.636364 |
8,954,463 | 3 | 4 | 3. The computer program product according to claim 1 , wherein said computer readable program code configured to consult historical search queries from previous browsing sessions. | 3. The computer program product according to claim 1 , wherein said computer readable program code configured to consult historical search queries from previous browsing sessions. 4. The computer program product according to claim 3 , wherein said computer readable program code is further configured to determine n-grams of search queries from previous browsing sessions. | 0.5 |
9,099,081 | 14 | 15 | 14. The device of claim 10 , wherein the memory further stores a dictionary comprising all recognized words of a set of recognized words and the processor is further configured to determine the pronunciation of the other level domain by: searching the dictionary to determining whether the other level domain matches one of the recognized words of the set of recognized words; and, in response to determining that the other level domain does not match one of the recognized words of the set of recognized words, then one or more of: generating a respective phonetic representation of each respective character in the other level domain pronounced individually and generating speech from the respective phonetic representation of each respective character in the other level domain pronounced individually utilizing the audio waveform generator; and, generating a respective tokenized representation of each respective individual character of the other level domain suitable for interpretation by the text-to-speech engine. | 14. The device of claim 10 , wherein the memory further stores a dictionary comprising all recognized words of a set of recognized words and the processor is further configured to determine the pronunciation of the other level domain by: searching the dictionary to determining whether the other level domain matches one of the recognized words of the set of recognized words; and, in response to determining that the other level domain does not match one of the recognized words of the set of recognized words, then one or more of: generating a respective phonetic representation of each respective character in the other level domain pronounced individually and generating speech from the respective phonetic representation of each respective character in the other level domain pronounced individually utilizing the audio waveform generator; and, generating a respective tokenized representation of each respective individual character of the other level domain suitable for interpretation by the text-to-speech engine. 15. The device of claim 14 , wherein the set of recognized words comprises one or more of a dictionary, a corpus, names of organizations, and abbreviations of organization names. | 0.5 |
9,785,625 | 3 | 5 | 3. The method of claim 2 , wherein determining the subject matter of the content page comprises performing sentiment analysis or semantic analysis on the online content. | 3. The method of claim 2 , wherein determining the subject matter of the content page comprises performing sentiment analysis or semantic analysis on the online content. 5. The method of claim 3 , wherein determining the subject matter of the content page based on the sentiment analysis comprises determining the subject matter to be a negative sentiment, the method further comprising selecting the comment based on the negative sentiment. | 0.5 |
8,521,718 | 7 | 11 | 7. A system, comprising: one or more computers coupled to a database of web page impressions and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying a first query having first criteria, wherein the first criteria specifies one or more attributes of web page impressions; obtaining a set of web page impressions that satisfy the first query; storing, as a pre-computed response to the first query, an identifier for each web page impression in the set; after storing the pre-computed response to the first query, receiving from a client device a second query having second criteria, wherein the second criteria specifies one or more attributes of web page impressions and wherein a number of second criteria is greater than a number of first criteria; generating a plurality of sub-queries from the second query, the plurality of sub-queries comprising (i) a first sub-query having the first criteria, and (ii) one or more other sub-queries, wherein each of the second criteria is represented in at least one of the plurality of sub-queries; obtaining a response for each of the one or more other sub-queries, from the database of web page impressions, wherein each response comprises identifiers of web page impressions satisfying criteria of the associated sub-query; comparing the pre-computed response to the first query and the responses to the one or more other sub-queries; and providing an answer to the client device based at least in part on comparing the pre-computed response to the first query and the responses to the one or more other sub-queries. | 7. A system, comprising: one or more computers coupled to a database of web page impressions and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying a first query having first criteria, wherein the first criteria specifies one or more attributes of web page impressions; obtaining a set of web page impressions that satisfy the first query; storing, as a pre-computed response to the first query, an identifier for each web page impression in the set; after storing the pre-computed response to the first query, receiving from a client device a second query having second criteria, wherein the second criteria specifies one or more attributes of web page impressions and wherein a number of second criteria is greater than a number of first criteria; generating a plurality of sub-queries from the second query, the plurality of sub-queries comprising (i) a first sub-query having the first criteria, and (ii) one or more other sub-queries, wherein each of the second criteria is represented in at least one of the plurality of sub-queries; obtaining a response for each of the one or more other sub-queries, from the database of web page impressions, wherein each response comprises identifiers of web page impressions satisfying criteria of the associated sub-query; comparing the pre-computed response to the first query and the responses to the one or more other sub-queries; and providing an answer to the client device based at least in part on comparing the pre-computed response to the first query and the responses to the one or more other sub-queries. 11. The system of claim 7 , wherein at least one of the responses to the one or more other sub-queries is a pre-computed response. | 0.5 |
9,271,050 | 10 | 11 | 10. A method comprising: authenticating a user login for a localized process system; presenting a user with a project, comprising an asset, wherein the project is a movie, and wherein the asset is created for an original geographical territory; presenting a user with a display to order a localized version of the asset, wherein the localized version of the asset is a version of the asset that is customized for a second geographical territory that is different than the original geographical territory; receiving user input to create subtitles for the localized version of the asset, wherein the user selects himself to enter the subtitles presenting the user with a display of a timed-text script that displays a time of the asset, and the dialogue of the asset receiving user input of a new subtitle that the user entered on the display generating a new timed-text script with the new subtitle receiving an order to create the localized version of the asset, wherein the localized version of the asset is created using the new timed-text script. | 10. A method comprising: authenticating a user login for a localized process system; presenting a user with a project, comprising an asset, wherein the project is a movie, and wherein the asset is created for an original geographical territory; presenting a user with a display to order a localized version of the asset, wherein the localized version of the asset is a version of the asset that is customized for a second geographical territory that is different than the original geographical territory; receiving user input to create subtitles for the localized version of the asset, wherein the user selects himself to enter the subtitles presenting the user with a display of a timed-text script that displays a time of the asset, and the dialogue of the asset receiving user input of a new subtitle that the user entered on the display generating a new timed-text script with the new subtitle receiving an order to create the localized version of the asset, wherein the localized version of the asset is created using the new timed-text script. 11. The method of claim 10 wherein the asset is an international trailer for the movie. | 0.729814 |
8,412,749 | 1 | 15 | 1. A machine-implemented method comprising: transmitting description data describing a preexisting structured presentation, a visual presentation of the preexisting structured presentation visually presenting information in a systematic arrangement that conforms with a structured design, the preexisting structured presentation denoting characterization of attributes of a particular instance by values that characterize the attributes of the particular instance by virtue of an arrangement of an identifier of the particular instance and the values in the visual presentation of the preexisting structured presentation; receiving data describing user interaction with the visual presentation of the preexisting structured presentation, the user interaction identifying a fraction of the visual presentation of the preexisting structured presentation for population with attribute values; and in response to the receipt of the data describing the user interaction, comparing characteristics of the identified fraction of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new value that characterizes an instance characterized in the identified fraction of the preexisting structured presentation, adding the new value to the preexisting structured presentation to form a new structured presentation having at least the fraction of the visual presentation identified by the user interaction populated with new attribute values, and outputting instructions for visually presenting the new structured presentation. | 1. A machine-implemented method comprising: transmitting description data describing a preexisting structured presentation, a visual presentation of the preexisting structured presentation visually presenting information in a systematic arrangement that conforms with a structured design, the preexisting structured presentation denoting characterization of attributes of a particular instance by values that characterize the attributes of the particular instance by virtue of an arrangement of an identifier of the particular instance and the values in the visual presentation of the preexisting structured presentation; receiving data describing user interaction with the visual presentation of the preexisting structured presentation, the user interaction identifying a fraction of the visual presentation of the preexisting structured presentation for population with attribute values; and in response to the receipt of the data describing the user interaction, comparing characteristics of the identified fraction of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new value that characterizes an instance characterized in the identified fraction of the preexisting structured presentation, adding the new value to the preexisting structured presentation to form a new structured presentation having at least the fraction of the visual presentation identified by the user interaction populated with new attribute values, and outputting instructions for visually presenting the new structured presentation. 15. The method of claim 1 , wherein the user interaction identifies a new instance that is to be added to the preexisting structured presentation. | 0.849174 |
9,229,934 | 1 | 3 | 1. A method for integrating a document from a first document repository to another document repository in a cloud computing environment, the method comprising: receiving by a server a configuration setup file including information identifying a source document repository, a destination document repository located in a cloud computing environment, and at least one web portal; receiving by the server an indication to upload a document from the source document repository to the destination document repository; in response to receiving the indication, retrieving automatically by the server the document from the source document repository, wherein the document is formatted in a first format; converting automatically by the server the document from the first format to a second format; identifying automatically by the server at least one static object in the converted document; transmitting the at least one static object associated with the converted document to the at least one web portal; transmitting the converted document to the destination document repository, the converted document being accessible via the at least one web portal; removing, from the destination document repository, an obsolete version of the document from the destination document repository; and removing, from the at least one web portal, a static object associated with the obsolete version of the document. | 1. A method for integrating a document from a first document repository to another document repository in a cloud computing environment, the method comprising: receiving by a server a configuration setup file including information identifying a source document repository, a destination document repository located in a cloud computing environment, and at least one web portal; receiving by the server an indication to upload a document from the source document repository to the destination document repository; in response to receiving the indication, retrieving automatically by the server the document from the source document repository, wherein the document is formatted in a first format; converting automatically by the server the document from the first format to a second format; identifying automatically by the server at least one static object in the converted document; transmitting the at least one static object associated with the converted document to the at least one web portal; transmitting the converted document to the destination document repository, the converted document being accessible via the at least one web portal; removing, from the destination document repository, an obsolete version of the document from the destination document repository; and removing, from the at least one web portal, a static object associated with the obsolete version of the document. 3. The method of claim 1 wherein the destination document repository is included in a multi-tenant on-demand database system. | 0.902648 |
8,713,445 | 1 | 8 | 1. A computer-implemented method of generating a customized user interface representing a contract, comprising: receiving, over an electronic network, a contract description message including description information corresponding to a computer device being used to display the contract to a user; retrieving, by using a processor, the description information from the contract description message; comparing the description information with information stored in a template library and adaptor library to identify a generic user interface and a corresponding adaptor module; ranking the identified generic user interface and the identified adaptor module, wherein: the identified generic user interface is ranked when the comparison provides a plurality of potential generic user interfaces for generation of the customized user interface; and the identified adaptor module is ranked when the comparison provides a plurality of potential adaptor modules for generation of the customized user interface; and generating a contract response message based on a result of the comparison and the ranking, the response message including an instruction to generate, on the computer device, the customized user interface based on the identified generic user interface and corresponding adaptor module when the generic user interface and the corresponding adaptor module are identified. | 1. A computer-implemented method of generating a customized user interface representing a contract, comprising: receiving, over an electronic network, a contract description message including description information corresponding to a computer device being used to display the contract to a user; retrieving, by using a processor, the description information from the contract description message; comparing the description information with information stored in a template library and adaptor library to identify a generic user interface and a corresponding adaptor module; ranking the identified generic user interface and the identified adaptor module, wherein: the identified generic user interface is ranked when the comparison provides a plurality of potential generic user interfaces for generation of the customized user interface; and the identified adaptor module is ranked when the comparison provides a plurality of potential adaptor modules for generation of the customized user interface; and generating a contract response message based on a result of the comparison and the ranking, the response message including an instruction to generate, on the computer device, the customized user interface based on the identified generic user interface and corresponding adaptor module when the generic user interface and the corresponding adaptor module are identified. 8. The method of claim 1 , wherein the identified generic user interface is ranked highest from the plurality of potential generic user interfaces. | 0.876678 |
6,016,380 | 36 | 38 | 36. A computer implemented method for generating a representation of a video program as a sequence of edit events to be used by a digital video editor for editing the video program, the method comprising the steps of: receiving a video edit decision list in a first syntax for a first machine wherein the video edit decision list comprises a formatted list of computer instructions for an edit controller for assembling the video program, wherein each instruction defines source material and a destination of an edit event; selecting a format specifier from a plurality of format specifiers, wherein each format specifier specifies a syntax for a video edit decision list for a different machine; generating, according to the video edit decision list and the selected format specifier corresponding to the first syntax, the sequence of edit events which corresponds to the video edit decision list. | 36. A computer implemented method for generating a representation of a video program as a sequence of edit events to be used by a digital video editor for editing the video program, the method comprising the steps of: receiving a video edit decision list in a first syntax for a first machine wherein the video edit decision list comprises a formatted list of computer instructions for an edit controller for assembling the video program, wherein each instruction defines source material and a destination of an edit event; selecting a format specifier from a plurality of format specifiers, wherein each format specifier specifies a syntax for a video edit decision list for a different machine; generating, according to the video edit decision list and the selected format specifier corresponding to the first syntax, the sequence of edit events which corresponds to the video edit decision list. 38. The computer-implemented method of claim 36, wherein a format specifier includes a control section defining global variables and flags indicating semantic choices for the format, and a list of entries, wherein each entry corresponds to one edit event. | 0.5 |
7,869,989 | 20 | 21 | 20. The method of claim 19 wherein the at least one definition element further comprises a plurality of definition elements, each of the definition elements corresponding to a mask indicative of significant fields in the definition elements, further comprising: a primary definition element indicative of a deterministic usage of the word; and at least one secondary definition element indicative of particular contextual usages of the word applicable to the primary definition. | 20. The method of claim 19 wherein the at least one definition element further comprises a plurality of definition elements, each of the definition elements corresponding to a mask indicative of significant fields in the definition elements, further comprising: a primary definition element indicative of a deterministic usage of the word; and at least one secondary definition element indicative of particular contextual usages of the word applicable to the primary definition. 21. The method of claim 20 wherein the mapped dictionary term further maps to at least one definition section, each definition section corresponding to a primary definition of the word having at least one definition element. | 0.5 |
8,583,415 | 10 | 14 | 10. One or more computer-storage devices having computer-executable instructions embodied thereon that, when executed, perform a method for performing a phonetic search, the method comprising: obtaining a query native string associated with a query based on an Indian writing system; obtaining one or more search content native strings associated with search content to be searched; generating a query normalized string based on the query native string input by a user using an optimization attribute that takes into account size of one or more character-sets within the query native string, the query normalized string being generated based on one or more largest character-set sizes that correspond with phonetic correlations to the query native string input by the user; generating one or more search content normalized strings based on each of the one or more search content native strings associated with search content to be searched, the one or more search content normalized strings being generated in accordance with phonetic correlations to the one or more search content native strings; determining if the query normalized string generated in accordance with phonetic correlations to the query native string input by the user matches any of the one or more search content normalized strings generated in accordance with phonetic correlations to the one or more search content native strings; and if so, indexing the query normalized string in association with the search content having the one or more search content normalized strings that match the query normalized string such that the index may be accessed at a later time. | 10. One or more computer-storage devices having computer-executable instructions embodied thereon that, when executed, perform a method for performing a phonetic search, the method comprising: obtaining a query native string associated with a query based on an Indian writing system; obtaining one or more search content native strings associated with search content to be searched; generating a query normalized string based on the query native string input by a user using an optimization attribute that takes into account size of one or more character-sets within the query native string, the query normalized string being generated based on one or more largest character-set sizes that correspond with phonetic correlations to the query native string input by the user; generating one or more search content normalized strings based on each of the one or more search content native strings associated with search content to be searched, the one or more search content normalized strings being generated in accordance with phonetic correlations to the one or more search content native strings; determining if the query normalized string generated in accordance with phonetic correlations to the query native string input by the user matches any of the one or more search content normalized strings generated in accordance with phonetic correlations to the one or more search content native strings; and if so, indexing the query normalized string in association with the search content having the one or more search content normalized strings that match the query normalized string such that the index may be accessed at a later time. 14. The computer-storage device of claim 10 , wherein generating the query normalized string comprises replacing at least one native character-set with at least one normalized character-set. | 0.697452 |
8,417,854 | 10 | 16 | 10. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component, instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer, instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class, instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class, identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters, instantiating the identified specific adaptor, communicator, and converter classes, adding the identified specific adaptor, communicator class, and converter classes to an instance list, and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes. | 10. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving, at an integration layer, a connection request from an auto-id component to be connected to an auto-id node, the connection request specifying one or more communication parameters of the auto-id component, instantiating a generic adaptor class for effecting communication between the auto-id node and the auto-id component, the generic adaptor implementing functionality common to multiple different, specific adaptor classes stored in a class repository of the integration layer, instantiating a generic communicator class for effecting a data transport aspect of the communication between the auto-id node and the auto-id component, the generic communicator class implementing functionality common to multiple different, specific communicator classes stored in the class repository, and the generic communicator class being a component of the generic adaptor class, instantiating a generic converter class for effecting a data conversion aspect of the communication between the auto-id node and the auto-id component, the generic converter class implementing functionality common to multiple different, specific converter classes stored in the class repository, and the generic converter class being a component of the generic adaptor class, identifying, from among the multiple different adaptor, communicator, and converter classes stored in the class repository, a specific adaptor, a specific communicator class, and a specific converter class, respectively, based on the specified communication parameters, instantiating the identified specific adaptor, communicator, and converter classes, adding the identified specific adaptor, communicator class, and converter classes to an instance list, and effecting the communication between the auto-id component and the auto-id node using the instantiated generic adaptor, communicator, and converter classes and the instantiated specific adaptor, communicator, and converter classes. 16. The system of claim 10 , wherein the specific adaptor class further comprises a SOAP (Simple Object Access Protocol) or a JSP (Java Server Pages) adaptor class. | 0.721088 |
7,900,208 | 1 | 5 | 1. A system for translating a received message, said system comprising: a first non-transitory computer-readable storage medium storing a plurality of extensible exchange protocol plug-ins for identifying and decoding an exchange protocol of said received message; a second non-transitory computer-readable storage medium storing a plurality of extensible document format protocol plug-ins for identifying and translating a document format protocol associated with said received message; a standard communication interface; and a processor coupled to said first and second non-transitory computer-readable storage media and said communication interface, said processor configured to: invoke each one of the plurality of extensible exchange protocol plug-ins to identify a particular exchange protocol associated with the received message; identify, by a particular one of said plurality of extensible exchange protocol plug-ins, the particular exchange protocol associated with the received message; upon successful identification of the particular exchange protocol, decode said received message with said particular one of the plurality of extensible exchange protocol plug-ins to produce a decoded message; invoke each one of the plurality of extensible document format protocol plug-ins to identify a particular document format protocol associated with the decoded message; identify, by a particular one of said plurality of extensible document format protocol plug-ins, the particular document format protocol associated with the decoded message; and upon successful identification of the particular document format protocol, translate said decoded message with said particular one of the plurality of extensible document format protocol plug-ins to produce an output message of a native format. | 1. A system for translating a received message, said system comprising: a first non-transitory computer-readable storage medium storing a plurality of extensible exchange protocol plug-ins for identifying and decoding an exchange protocol of said received message; a second non-transitory computer-readable storage medium storing a plurality of extensible document format protocol plug-ins for identifying and translating a document format protocol associated with said received message; a standard communication interface; and a processor coupled to said first and second non-transitory computer-readable storage media and said communication interface, said processor configured to: invoke each one of the plurality of extensible exchange protocol plug-ins to identify a particular exchange protocol associated with the received message; identify, by a particular one of said plurality of extensible exchange protocol plug-ins, the particular exchange protocol associated with the received message; upon successful identification of the particular exchange protocol, decode said received message with said particular one of the plurality of extensible exchange protocol plug-ins to produce a decoded message; invoke each one of the plurality of extensible document format protocol plug-ins to identify a particular document format protocol associated with the decoded message; identify, by a particular one of said plurality of extensible document format protocol plug-ins, the particular document format protocol associated with the decoded message; and upon successful identification of the particular document format protocol, translate said decoded message with said particular one of the plurality of extensible document format protocol plug-ins to produce an output message of a native format. 5. A system as described in claim 1 wherein said processor is configured to perform message de-batching. | 0.820069 |
8,041,694 | 16 | 22 | 16. A method of identifying pairs of similar vectors in a set of vectors, the method comprising: identifying a similarity threshold; identifying a comparison vector x having processed features and non-processed features; based on the comparison vector x, identifying a first set of vectors, each vector in the first set of vectors having processed features and non-processed features corresponding to the processed features and non-processed features of the comparison vector x; identifying, using one or more computers, a candidate vector y from the first set of vectors based on a maximum similarity between the non--processed features of x and the non--processed features of y, and removing y from the first set of vectors. | 16. A method of identifying pairs of similar vectors in a set of vectors, the method comprising: identifying a similarity threshold; identifying a comparison vector x having processed features and non-processed features; based on the comparison vector x, identifying a first set of vectors, each vector in the first set of vectors having processed features and non-processed features corresponding to the processed features and non-processed features of the comparison vector x; identifying, using one or more computers, a candidate vector y from the first set of vectors based on a maximum similarity between the non--processed features of x and the non--processed features of y, and removing y from the first set of vectors. 22. The method of claim 16 in which the maximum similarity between the non-processed features of x and the non-processed features of y is determined based on a similarity between the non-processed features of x and a bounding vector having an ith coordinate equal to a largest feature in an ith coordinate among all vectors in a second set of vectors. | 0.74602 |
7,809,697 | 1 | 8 | 1. A computer-implemented method comprising: accessing, by a computer system, a plurality of documents that each include a plurality of hyperlinks; identifying, for one document of the plurality of documents, portions of the plurality of hyperlinks of the one document; adding, for the one document, the identified portions of the plurality of hyperlinks as entries to a dictionary along with an associated reference for each of the added entries, wherein the dictionary and associated references for the one document are different than dictionaries and associated references for other documents of the plurality of documents, and wherein each associated reference defines a shortened representation for an entry in the dictionary that corresponds to the reference; compressing, by the computer system, each of the plurality of hyperlinks of the one document by replacing portions of the plurality of hyperlinks of the one document that are provided by entries in the dictionary for the one document with corresponding references to the entries in the dictionary; modifying the one document to include the dictionary and the associated references for the one document as a base hyperlink and replacing the plurality of hyperlinks of the one document with corresponding compressed hyperlinks; and providing the modified one document to a computing device for presentation to a user of the computing device. | 1. A computer-implemented method comprising: accessing, by a computer system, a plurality of documents that each include a plurality of hyperlinks; identifying, for one document of the plurality of documents, portions of the plurality of hyperlinks of the one document; adding, for the one document, the identified portions of the plurality of hyperlinks as entries to a dictionary along with an associated reference for each of the added entries, wherein the dictionary and associated references for the one document are different than dictionaries and associated references for other documents of the plurality of documents, and wherein each associated reference defines a shortened representation for an entry in the dictionary that corresponds to the reference; compressing, by the computer system, each of the plurality of hyperlinks of the one document by replacing portions of the plurality of hyperlinks of the one document that are provided by entries in the dictionary for the one document with corresponding references to the entries in the dictionary; modifying the one document to include the dictionary and the associated references for the one document as a base hyperlink and replacing the plurality of hyperlinks of the one document with corresponding compressed hyperlinks; and providing the modified one document to a computing device for presentation to a user of the computing device. 8. The computer-implemented method of claim 1 , wherein each of the entries in the dictionary for the one document comprises a plurality of characters. | 0.781159 |
9,436,768 | 1 | 7 | 1. A method for pushing content items, comprising: obtaining a target text and analyzing lexically the target text; extracting features, comprising traffic feature, from the target text; classifying hierarchically, the features extracted from the target text, based on a pre-trained hierarchical classification model considering traffic feature to obtain a hierarchical classification of the target text; selecting one or more among a plurality of content items based on the hierarchical classification of the target text; obtaining the selected content items; and pushing the obtained content items to a terminal; wherein the target text comprises a webpage text which comprises a traffic feature identifying source of the webpage text; wherein the plurality of content items comprise a plurality of promotion texts; wherein for each of the plurality of promotion texts: obtaining the promotion text and analyzing lexically the promotion text; extracting features, comprising traffic feature, from the promotion text; classifying hierarchically, the features extracted from the promotion text, based on a pre-trained hierarchical classification model considering traffic feature to obtain a hierarchical classification of the promotion text; and calculating similarity between the webpage text and the promotion text based on the hierarchical classification of the promotion text and the hierarchical classification of the webpage text, wherein the selecting one or more among the plurality of promotion texts is based on the similarity between the webpage text and each of the plurality of promotion texts. | 1. A method for pushing content items, comprising: obtaining a target text and analyzing lexically the target text; extracting features, comprising traffic feature, from the target text; classifying hierarchically, the features extracted from the target text, based on a pre-trained hierarchical classification model considering traffic feature to obtain a hierarchical classification of the target text; selecting one or more among a plurality of content items based on the hierarchical classification of the target text; obtaining the selected content items; and pushing the obtained content items to a terminal; wherein the target text comprises a webpage text which comprises a traffic feature identifying source of the webpage text; wherein the plurality of content items comprise a plurality of promotion texts; wherein for each of the plurality of promotion texts: obtaining the promotion text and analyzing lexically the promotion text; extracting features, comprising traffic feature, from the promotion text; classifying hierarchically, the features extracted from the promotion text, based on a pre-trained hierarchical classification model considering traffic feature to obtain a hierarchical classification of the promotion text; and calculating similarity between the webpage text and the promotion text based on the hierarchical classification of the promotion text and the hierarchical classification of the webpage text, wherein the selecting one or more among the plurality of promotion texts is based on the similarity between the webpage text and each of the plurality of promotion texts. 7. The method of claim 1 , in which the target text further comprises a user text. | 0.834677 |
9,152,719 | 1 | 7 | 1. A method of prioritizing items comprising: procuring a task to be performed; obtaining a reference associated with the task; selecting, by a processor, a group of items associated with the reference; notifying a member of the group in an order based on a ranking of the group for the reference; and adding objects to the group when all members of the group have been notified and the task is incomplete. | 1. A method of prioritizing items comprising: procuring a task to be performed; obtaining a reference associated with the task; selecting, by a processor, a group of items associated with the reference; notifying a member of the group in an order based on a ranking of the group for the reference; and adding objects to the group when all members of the group have been notified and the task is incomplete. 7. The method of claim 1 wherein the items are users and the task comprises an action indicating an opinion. | 0.649351 |
9,092,778 | 2 | 14 | 2. The method of claim 1 wherein said intermediary algorithm system provides all communications to all parties without any required human interaction; wherein said results transfer of step “15” is undertaken without the need for any input or disclosure of any personal information of said financial account holder to said financial institution and/or said optional third party; and wherein no financial account information is shared with nor stored within said intermediary algorithm system. | 2. The method of claim 1 wherein said intermediary algorithm system provides all communications to all parties without any required human interaction; wherein said results transfer of step “15” is undertaken without the need for any input or disclosure of any personal information of said financial account holder to said financial institution and/or said optional third party; and wherein no financial account information is shared with nor stored within said intermediary algorithm system. 14. The method of claim 2 wherein said optional third party is present and is selected from the group consisting of an individual other than said financial account holder, a corporate entity other than said financial account holder, a merchant, and the same or a different financial institution than that servicing said financial account holder account. | 0.5 |
8,375,048 | 31 | 32 | 31. The computer readable storage device of claim 30 , the respective weight values and confidence levels used for ranking the search results and for federation, the federation comprising: evaluating, based at least in part on at least one of the algorithmic intent determination or the list-match intent determination, one or more search queries using two or more data sources in parallel; and determining whether to send at least one of the one or more evaluated search queries to at least one of an encyclopedic provider, a news provider, a travel provider, a document serving provider, or a phone directory provider. | 31. The computer readable storage device of claim 30 , the respective weight values and confidence levels used for ranking the search results and for federation, the federation comprising: evaluating, based at least in part on at least one of the algorithmic intent determination or the list-match intent determination, one or more search queries using two or more data sources in parallel; and determining whether to send at least one of the one or more evaluated search queries to at least one of an encyclopedic provider, a news provider, a travel provider, a document serving provider, or a phone directory provider. 32. The computer readable storage device of claim 31 , at least one of a first weight value or a first confidence level assigned to a first keyword term not comprising an attached query augmentation term, at least one of a second weight value or a second confidence level assigned to a second keyword term comprising an attached query augmentation term, at least one of the first weight value or the first confidence level indicative of a first level of importance of the first keyword term, at least one of the second weight value or the second confidence level indicative of a second level of importance of the second keyword term, the first level of importance one of less than or greater than the second level of importance. | 0.5 |
8,775,161 | 6 | 7 | 6. The method of claim 3 wherein the evaluation indicator comprises a story generation request, the story generation request indicating that the narrative story is to be generated. | 6. The method of claim 3 wherein the evaluation indicator comprises a story generation request, the story generation request indicating that the narrative story is to be generated. 7. The method of claim 6 wherein the story generation request comprises data that is indicative of at least one story angle from the angle set data structure. | 0.5 |
7,783,528 | 1 | 5 | 1. A method implemented by a computer, the computer comprising in a computer readable storage medium including one or more computer readable instructions stored thereon that, when executed by a computer, cause the computer to perform the method to automatically generate a naturally reading narrative product summary including assertions about a specific product selected by a user, said method comprising: receiving the selection of the specific product from the user, the specific product associated with a plurality of attributes; determining at least one attribute of the plurality of attributes for comparison for the specific product selected by the user; selecting a comparable product based on the at least one attribute, the comparable product being the product having a high value rating for the at least one attribute; and generating the naturally reading narrative product summary including assertions about the specific product selected by the user and a recommendation of the comparable product. | 1. A method implemented by a computer, the computer comprising in a computer readable storage medium including one or more computer readable instructions stored thereon that, when executed by a computer, cause the computer to perform the method to automatically generate a naturally reading narrative product summary including assertions about a specific product selected by a user, said method comprising: receiving the selection of the specific product from the user, the specific product associated with a plurality of attributes; determining at least one attribute of the plurality of attributes for comparison for the specific product selected by the user; selecting a comparable product based on the at least one attribute, the comparable product being the product having a high value rating for the at least one attribute; and generating the naturally reading narrative product summary including assertions about the specific product selected by the user and a recommendation of the comparable product. 5. The method of claim 1 , wherein said user selected product has a primary scenario that is the same as a primary scenario of said selected comparable product. | 0.73064 |
7,770,136 | 1 | 12 | 1. At a gesture recognition tutorial system including a motion-sensitive display surface capable of recognizing various forms of user interaction with the surface, a method of suggesting recognized application gesture commands based on the user interaction with the surface in order to give the user various options and/or instructions on how to appropriately use the application for the motion-sensitive display surface, the method comprising: receiving at a motion-sensitive display surface a user-performed gesture, which includes user movement of an object over the surface that recognizes such user interaction therewith; determining that the received user-performed gesture is an unrecognized command, the gesture not corresponding to gesture commands recognized by one or more programs running on the gesture recognition tutorial system's motion-sensitive display surface; based on the determination, identifying one or more gesture commands that are similar to the received user-performed gesture that are recognizable by the one or more programs of the motion-sensitive display surface, wherein the one or more gesture commands recognized by the program represent actual commands of the program; and displaying one or more exemplary gesture commands recognized by the one or more programs in order to aid the user in understanding appropriate various defined gestures representing actual program commands, the exemplary gesture commands comprising one or more graphical, non-textual images that depict a series of one or more object motions or movements performable by the user that form a recognized command, recognizable by the motion-sensitive display surface. | 1. At a gesture recognition tutorial system including a motion-sensitive display surface capable of recognizing various forms of user interaction with the surface, a method of suggesting recognized application gesture commands based on the user interaction with the surface in order to give the user various options and/or instructions on how to appropriately use the application for the motion-sensitive display surface, the method comprising: receiving at a motion-sensitive display surface a user-performed gesture, which includes user movement of an object over the surface that recognizes such user interaction therewith; determining that the received user-performed gesture is an unrecognized command, the gesture not corresponding to gesture commands recognized by one or more programs running on the gesture recognition tutorial system's motion-sensitive display surface; based on the determination, identifying one or more gesture commands that are similar to the received user-performed gesture that are recognizable by the one or more programs of the motion-sensitive display surface, wherein the one or more gesture commands recognized by the program represent actual commands of the program; and displaying one or more exemplary gesture commands recognized by the one or more programs in order to aid the user in understanding appropriate various defined gestures representing actual program commands, the exemplary gesture commands comprising one or more graphical, non-textual images that depict a series of one or more object motions or movements performable by the user that form a recognized command, recognizable by the motion-sensitive display surface. 12. The method of claim 1 , further comprising allowing the user to create a gesture that is recognized by one or more programs as a program command. | 0.670354 |
9,576,577 | 10 | 11 | 10. A method for transcription transfer, comprising: receiving text data in an electronic format; determining a header in the text data; in response to determining the header in the text data, determining a segment associated with the header; providing a dialog box associated with the text data, wherein the dialog box includes a first option for inserting the segment into a user interface provided by a destination application; receiving a user selection of the first option; and inserting the segment into a predetermined portion of the user interface provided by the destination application. | 10. A method for transcription transfer, comprising: receiving text data in an electronic format; determining a header in the text data; in response to determining the header in the text data, determining a segment associated with the header; providing a dialog box associated with the text data, wherein the dialog box includes a first option for inserting the segment into a user interface provided by a destination application; receiving a user selection of the first option; and inserting the segment into a predetermined portion of the user interface provided by the destination application. 11. The method of claim 10 , further comprising: determining whether the text data includes a sub-header associated with the header; determining a sub-segment of the text data that corresponds to the sub-header; and including a second option for inserting the sub-segment into the user interface provided by the destination application. | 0.660606 |
9,055,074 | 1 | 3 | 1. A method for aggregating social media content items that are relevant to geographically definable locations, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: obtaining, by the one or more physical processors, at least a first parameter that specifies one or more geographically definable locations; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicating, by the one or more physical processors, at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. | 1. A method for aggregating social media content items that are relevant to geographically definable locations, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: obtaining, by the one or more physical processors, at least a first parameter that specifies one or more geographically definable locations; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; and communicating, by the one or more physical processors, at least a portion of the first set of social media content items and at least a portion of the second set of social media content items. 3. The method of claim 1 , the method further comprising: normalizing, by the one or more processors, at least one of: the first set of social media content items or the second set of social media content items. | 0.793945 |
8,990,189 | 6 | 7 | 6. A computer program product to determine knowledgeable and available contacts in an instant messaging system, the computer program product comprising: one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions comprising: program instructions to receive a keyword related to an area of expertise; program instructions to search for the keyword in correspondence of users of an instant messaging system, the correspondence including real-time and historical information associated with each user of the instant messaging system; program instructions to identify, based on results of the search, a plurality of users having used the keyword in the correspondence; program instructions to determine an availability of each of the identified plurality of users; and program instructions to rank the identified plurality of users based on predefined criteria, the predefined criteria including at least one of the determined availability of each of the identified plurality of users and an incidence of the keyword in correspondence of each of the identified plurality of users, the incidence including both a number and a location of the keyword in the correspondence, wherein the keyword located near a beginning of the correspondence indicates a greater expertise in the area of expertise than the keyword located near an end of the correspondence. | 6. A computer program product to determine knowledgeable and available contacts in an instant messaging system, the computer program product comprising: one or more computer-readable storage devices and program instructions stored on at least one of the one or more tangible storage devices, the program instructions comprising: program instructions to receive a keyword related to an area of expertise; program instructions to search for the keyword in correspondence of users of an instant messaging system, the correspondence including real-time and historical information associated with each user of the instant messaging system; program instructions to identify, based on results of the search, a plurality of users having used the keyword in the correspondence; program instructions to determine an availability of each of the identified plurality of users; and program instructions to rank the identified plurality of users based on predefined criteria, the predefined criteria including at least one of the determined availability of each of the identified plurality of users and an incidence of the keyword in correspondence of each of the identified plurality of users, the incidence including both a number and a location of the keyword in the correspondence, wherein the keyword located near a beginning of the correspondence indicates a greater expertise in the area of expertise than the keyword located near an end of the correspondence. 7. The computer program product of claim 6 , wherein the program instructions to determine an availability further comprise program instructions to determine an availability of each of the identified plurality of users based on information associated with one or more of each of the user's electronic calendars, current and previous instant messaging status messages, and previous availability history. | 0.5 |
9,880,815 | 1 | 13 | 1. A structured query language (SQL) Visualizer, comprising: a processor of a computer system, wherein the processor is arranged to cause the computer system to transform a textual SQL statement into a graphical diagram which represents said textual SQL statement; said SQL Visualizer being arranged: a) to cause the computer system to transform a textual SQL procedure into a graphical diagram which represents said textual SQL procedure such that the structure of the SQL procedure is visually represented in said graphical diagram; and b) to transform a textual data manipulation language (DML) statement into a graphical diagram which represents the logic of said textual DML statement; wherein said textual DML statement includes an insert, update or delete, statement; wherein said graphical diagram which represents the logic of said textual DML statement includes at least an insert, update or delete icon; and wherein the SQL Visualizer further comprises a user interface, wherein said user interface comprises a dictionary selection control which allows a user to select a database used in said textual SQL statement, and to thereby provide a definition for said database for use in transforming said textual SQL statement into said graphical diagram which represents said textual SQL statement. | 1. A structured query language (SQL) Visualizer, comprising: a processor of a computer system, wherein the processor is arranged to cause the computer system to transform a textual SQL statement into a graphical diagram which represents said textual SQL statement; said SQL Visualizer being arranged: a) to cause the computer system to transform a textual SQL procedure into a graphical diagram which represents said textual SQL procedure such that the structure of the SQL procedure is visually represented in said graphical diagram; and b) to transform a textual data manipulation language (DML) statement into a graphical diagram which represents the logic of said textual DML statement; wherein said textual DML statement includes an insert, update or delete, statement; wherein said graphical diagram which represents the logic of said textual DML statement includes at least an insert, update or delete icon; and wherein the SQL Visualizer further comprises a user interface, wherein said user interface comprises a dictionary selection control which allows a user to select a database used in said textual SQL statement, and to thereby provide a definition for said database for use in transforming said textual SQL statement into said graphical diagram which represents said textual SQL statement. 13. A SQL Visualizer as claimed in claim 1 , which also allows a user to create textual SQL statements and SQL procedures from graphical SQL Rules and SQL Procedures. | 0.787724 |
8,832,132 | 1 | 5 | 1. A computer-implemented method of providing a search result set relevant to a search query, the method comprising: hosting a social network comprising a plurality of communities, each community having a plurality of users; storing a user profile for each user including a first user and a second user, the user profile identifying the user's membership in at least one of the communities; receiving the search query directed to a content index that is independent of the social network from the first user who is a member of at least one of the communities; determining personalization information including a first search term and a second search term, the first search term being determined from the first user's user profile and data from the second user's user profile, the second user's user profile having a degree of separation from the first user's user profile in the social network, and the second search term being based at least in part on the first user's membership in the at least one of the communities and a level of personalization selected by the first user for personalizing the search query received from the first user, wherein the level of personalization indicates a total number of the communities from which the second search term is retrieved; combining the search query received from the first user and the first and second search terms to form a personalized search query; and searching the content index using the personalized search query to produce the search result set comprising documents relevant to the personalized search query. | 1. A computer-implemented method of providing a search result set relevant to a search query, the method comprising: hosting a social network comprising a plurality of communities, each community having a plurality of users; storing a user profile for each user including a first user and a second user, the user profile identifying the user's membership in at least one of the communities; receiving the search query directed to a content index that is independent of the social network from the first user who is a member of at least one of the communities; determining personalization information including a first search term and a second search term, the first search term being determined from the first user's user profile and data from the second user's user profile, the second user's user profile having a degree of separation from the first user's user profile in the social network, and the second search term being based at least in part on the first user's membership in the at least one of the communities and a level of personalization selected by the first user for personalizing the search query received from the first user, wherein the level of personalization indicates a total number of the communities from which the second search term is retrieved; combining the search query received from the first user and the first and second search terms to form a personalized search query; and searching the content index using the personalized search query to produce the search result set comprising documents relevant to the personalized search query. 5. The method of claim 1 , wherein determining personalization information including the first search term further comprises identifying a history of user web page access. | 0.625 |
9,502,024 | 11 | 12 | 11. At least one computer-readable device having recorded thereon program code that, when executed, performs a method for use with an automatic speech recognition (ASR) system, the ASR system comprising at least one model having a plurality of representations of phones, the method comprising acts of: receiving an audio signal comprising a first user input; analyzing the audio signal to identify at least one first phone as having a selected recognition performance characteristic, wherein the act of analyzing comprises comparing one or more sounds in the audio signal with a representation of the at least one first phone in the at least one model; subsequent to receiving and analyzing the audio signal comprising the first user input, selecting a user prompt to be presented to a user of a speech-responsive application to elicit a second user input, wherein the speech-responsive application is programmed to perform at least one action based on the second user input, and wherein the user prompt is selected based on a determination of whether the user is expected to speak, in response to the user prompt, the at least one first phone which is identified as having the selected recognition performance characteristic; causing the user prompt to be presented to the user of the speech-responsive application, wherein: the at least one first phone comprises at least one first phone that is associated with a first confidence score, the first confidence score being lower than a selected confidence threshold, and the user prompt is selected to invite the user to speak an input phrase that combines a first word with one or more second words, wherein the first word comprises the at least one first phone associated with the first confidence score that is lower than the selected confidence threshold, and the one or more second words comprise at least one second phone that is associated with a second confidence score, the second confidence score being higher than the selected confidence threshold; and performing, by the speech-responsive application, the at least one action based on the second user input. | 11. At least one computer-readable device having recorded thereon program code that, when executed, performs a method for use with an automatic speech recognition (ASR) system, the ASR system comprising at least one model having a plurality of representations of phones, the method comprising acts of: receiving an audio signal comprising a first user input; analyzing the audio signal to identify at least one first phone as having a selected recognition performance characteristic, wherein the act of analyzing comprises comparing one or more sounds in the audio signal with a representation of the at least one first phone in the at least one model; subsequent to receiving and analyzing the audio signal comprising the first user input, selecting a user prompt to be presented to a user of a speech-responsive application to elicit a second user input, wherein the speech-responsive application is programmed to perform at least one action based on the second user input, and wherein the user prompt is selected based on a determination of whether the user is expected to speak, in response to the user prompt, the at least one first phone which is identified as having the selected recognition performance characteristic; causing the user prompt to be presented to the user of the speech-responsive application, wherein: the at least one first phone comprises at least one first phone that is associated with a first confidence score, the first confidence score being lower than a selected confidence threshold, and the user prompt is selected to invite the user to speak an input phrase that combines a first word with one or more second words, wherein the first word comprises the at least one first phone associated with the first confidence score that is lower than the selected confidence threshold, and the one or more second words comprise at least one second phone that is associated with a second confidence score, the second confidence score being higher than the selected confidence threshold; and performing, by the speech-responsive application, the at least one action based on the second user input. 12. The at least one computer-readable device of claim 11 , further comprising: receiving speech from the user in response to the user prompt; and using the speech to train the at least one model. | 0.744125 |
8,359,584 | 1 | 3 | 1. A computer-based method of debugging a debuggee computer program after an execution of at least a portion of the debuggee program, comprising: a) receiving a call graph having a plurality of nodes, each node representing a corresponding event that occurred during the debuggee program execution, the nodes ordered based on the debuggee program execution, including a first node representing a first event corresponding to a first machine address and corresponding to a source language statement and a second node representing a second event corresponding to a second machine address and corresponding to the source language statement; b) selectively clustering together the first node and the second node based on a comparison of the first machine address and the second machine address; and c) in response to a command to perform a step operation, selectively performing the step operation to include the first node and the second node, based on whether the first node and the second node are clustered. | 1. A computer-based method of debugging a debuggee computer program after an execution of at least a portion of the debuggee program, comprising: a) receiving a call graph having a plurality of nodes, each node representing a corresponding event that occurred during the debuggee program execution, the nodes ordered based on the debuggee program execution, including a first node representing a first event corresponding to a first machine address and corresponding to a source language statement and a second node representing a second event corresponding to a second machine address and corresponding to the source language statement; b) selectively clustering together the first node and the second node based on a comparison of the first machine address and the second machine address; and c) in response to a command to perform a step operation, selectively performing the step operation to include the first node and the second node, based on whether the first node and the second node are clustered. 3. The computer-based method of claim 1 , selectively clustering comprises: a) if the second node is ordered after the first node and the second machine address is less than the first machine address, determining not to cluster; and b) if the second node is ordered after the first node and the second machine address is greater than the first machine address, determining to cluster. | 0.6 |
8,934,652 | 1 | 18 | 1. A method for ability enhancement, the method comprising: receiving data representing a speech signal obtained at a hearing device associated with a user, the speech signal representing an utterance of a speaker who is distinct from the user; identifying the speaker based on the data representing the speech signal, wherein identifying the speaker includes: performing speech recognition to convert the received data into text data; and identifying the speaker based on the text data, by finding a document that references the speaker and that includes one or more words of the text data, thereby inferring that the speaker is the author of the document, a recipient of the document, or a person described in the document; determining speaker-related information associated with the identified speaker; and visually presenting the speaker-related information to the user. | 1. A method for ability enhancement, the method comprising: receiving data representing a speech signal obtained at a hearing device associated with a user, the speech signal representing an utterance of a speaker who is distinct from the user; identifying the speaker based on the data representing the speech signal, wherein identifying the speaker includes: performing speech recognition to convert the received data into text data; and identifying the speaker based on the text data, by finding a document that references the speaker and that includes one or more words of the text data, thereby inferring that the speaker is the author of the document, a recipient of the document, or a person described in the document; determining speaker-related information associated with the identified speaker; and visually presenting the speaker-related information to the user. 18. The method of claim 1 , wherein the determining speaker-related information includes: accessing information items associated with the speaker. | 0.819307 |
9,639,509 | 3 | 4 | 3. The method of claim 1 , wherein the threshold value is a threshold value for the set of networks. | 3. The method of claim 1 , wherein the threshold value is a threshold value for the set of networks. 4. The method of claim 3 , wherein the set of one or more networks excludes one or more networks providing automated requests for provision of the first document. | 0.5 |
7,617,448 | 1 | 2 | 1. A method for validation of structured documents, the method comprising parsing a first instance of a first structured document by using a generic parser; generating a fast parser for the first structured document, the fast parser being faster than the generic parser, the fast parser being generated based on the structure of the first structured document; parsing a second instance of the first structured document using the fast parser; identifying a subset of fast parsers from a group of fast parsers consisting of fast parsers used most recently and fast parsers used most frequently; searching a corresponding fast parser for an instance of a second structured document from the identified subset of the fast parsers; and if the corresponding fast parser is available in the identified subset of the fast parsers, parsing the instance of the second structured document by using the corresponding fast parser; else, parsing the instance of the second structured document by using the generic parser. | 1. A method for validation of structured documents, the method comprising parsing a first instance of a first structured document by using a generic parser; generating a fast parser for the first structured document, the fast parser being faster than the generic parser, the fast parser being generated based on the structure of the first structured document; parsing a second instance of the first structured document using the fast parser; identifying a subset of fast parsers from a group of fast parsers consisting of fast parsers used most recently and fast parsers used most frequently; searching a corresponding fast parser for an instance of a second structured document from the identified subset of the fast parsers; and if the corresponding fast parser is available in the identified subset of the fast parsers, parsing the instance of the second structured document by using the corresponding fast parser; else, parsing the instance of the second structured document by using the generic parser. 2. The method of claim 1 , wherein each structured document being represented by a Context Free Grammar (CFG). | 0.62585 |
8,924,212 | 18 | 19 | 18. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: instructions for performing, via a processor, a first pass of entries in a database to generate a shortlist of the entries, the first pass comprising: utilizing a phonotactic grammar to perform speech recognition on received speech and to generate a phoneme lattice, wherein the utilizing ignores inter-field constraints of the phonotactic grammar; removing silence and filler words from the phoneme lattice to yield a revised phoneme lattice; normalizing costs in the revised phoneme lattice, to yield a normalized phoneme lattice with a best path having a cost of zero; identifying N-best lowest cost indices of an index for the database based on the normalized phoneme lattice; and generating the shortlist of the entries in the database based on the N-best lowest cost indices; and instructions for performing a second pass on the shortlist of the entries in the database to obtain a final result, the second pass comprising: generating a grammar from the shortlist of the entries in the database to yield a generated grammar, having inter-field constraints; and identifying data from the database for each of the input field based on the received speech, the generated grammar, and the inter-field constraints; and populating an input field of a form using the final result. | 18. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: instructions for performing, via a processor, a first pass of entries in a database to generate a shortlist of the entries, the first pass comprising: utilizing a phonotactic grammar to perform speech recognition on received speech and to generate a phoneme lattice, wherein the utilizing ignores inter-field constraints of the phonotactic grammar; removing silence and filler words from the phoneme lattice to yield a revised phoneme lattice; normalizing costs in the revised phoneme lattice, to yield a normalized phoneme lattice with a best path having a cost of zero; identifying N-best lowest cost indices of an index for the database based on the normalized phoneme lattice; and generating the shortlist of the entries in the database based on the N-best lowest cost indices; and instructions for performing a second pass on the shortlist of the entries in the database to obtain a final result, the second pass comprising: generating a grammar from the shortlist of the entries in the database to yield a generated grammar, having inter-field constraints; and identifying data from the database for each of the input field based on the received speech, the generated grammar, and the inter-field constraints; and populating an input field of a form using the final result. 19. The computer-readable storage device of claim 18 , wherein the index is previously generated based on a plurality of training phoneme lattices and factors of interest from valid entries in the database, the factors of interest comprising trigrams, and wherein the database is a name/address database. | 0.608247 |
8,713,696 | 8 | 10 | 8. The method of claim 1 wherein the determined at least one content portion is a dynamically generated content portion that is based at least in part on the request. | 8. The method of claim 1 wherein the determined at least one content portion is a dynamically generated content portion that is based at least in part on the request. 10. The method of claim 8 wherein the dynamically generated content portion is at least one of a travel itinerary, booking information, flight availability information, flight reservation details, a web log entry, a user-submitted review, a user-submitted rating, a user-submitted photo, or a restaurant guide. | 0.5 |
9,002,877 | 1 | 11 | 1. A method for determining a suitable font for displaying text, comprising: generating a two-dimensional link matrix to link a plurality of available fonts for displaying text each identified in the matrix with one or more font attributes identified in the matrix via one or more attribute values identified in the matrix; receiving a font match query to determine a suitable font for text to be displayed from the plurality of available fonts including one or more specified attribute-attribute value pairs; and determining one or more fonts satisfying the received font match query from the available fonts based on a match between the one or more specified attribute-attribute value pairs and the one or more attribute values of the two-dimensional link matrix to determine which font can correctly display the text wherein determining the one or more fonts satisfying the received font match query further comprises: retrieving the two-dimensional link matrix for one or more of the attribute-attribute value pairs in the font match query to generate a set of fonts returned results, wherein the set of fonts returned results includes a list of fonts that can correctly display the text corresponding to the font match query. | 1. A method for determining a suitable font for displaying text, comprising: generating a two-dimensional link matrix to link a plurality of available fonts for displaying text each identified in the matrix with one or more font attributes identified in the matrix via one or more attribute values identified in the matrix; receiving a font match query to determine a suitable font for text to be displayed from the plurality of available fonts including one or more specified attribute-attribute value pairs; and determining one or more fonts satisfying the received font match query from the available fonts based on a match between the one or more specified attribute-attribute value pairs and the one or more attribute values of the two-dimensional link matrix to determine which font can correctly display the text wherein determining the one or more fonts satisfying the received font match query further comprises: retrieving the two-dimensional link matrix for one or more of the attribute-attribute value pairs in the font match query to generate a set of fonts returned results, wherein the set of fonts returned results includes a list of fonts that can correctly display the text corresponding to the font match query. 11. The method according to claim 1 , wherein the two-dimensional matrix comprises the plurality of available fonts in one dimension and the one or more font attributes in another dimension. | 0.826325 |
7,912,868 | 1 | 4 | 1. A machine-readable non-transitory medium having instructions stored thereon, where the instructions, when read by the machine, cause the machine to perform the steps of: accessing a semantic representation associated with a first dataset and a semantic representation associated with a second dataset, wherein at least one of the semantic representation associated with the first dataset and the semantic representation associated with the second dataset is a trainable semantic vector generated based on at least one data point included in a respective dataset and known relationships between predetermined data points and predetermined categories to which the predetermined data points may relate; determining a similarity between the semantic representation associated with the first dataset and the semantic representation associated with the second dataset; and selectively relating the first dataset to the second dataset based on a result of the determining step; wherein each attribute in a trainable semantic vector indicates how likely a dataset represented by the trainable semantic vector belongs to one of the predetermined categories, and the trainable semantic vector has a dimension equal to the number of the predetermined categories. | 1. A machine-readable non-transitory medium having instructions stored thereon, where the instructions, when read by the machine, cause the machine to perform the steps of: accessing a semantic representation associated with a first dataset and a semantic representation associated with a second dataset, wherein at least one of the semantic representation associated with the first dataset and the semantic representation associated with the second dataset is a trainable semantic vector generated based on at least one data point included in a respective dataset and known relationships between predetermined data points and predetermined categories to which the predetermined data points may relate; determining a similarity between the semantic representation associated with the first dataset and the semantic representation associated with the second dataset; and selectively relating the first dataset to the second dataset based on a result of the determining step; wherein each attribute in a trainable semantic vector indicates how likely a dataset represented by the trainable semantic vector belongs to one of the predetermined categories, and the trainable semantic vector has a dimension equal to the number of the predetermined categories. 4. The machine-readable medium of claim 1 further comprising the step of selectively conveying the first dataset along with the second dataset based on a result of the selectively relating step. | 0.885882 |
9,519,703 | 2 | 3 | 2. The method of claim 1 , further comprising: displaying, separately from any other search results, the set of results from the search of the compound search query. | 2. The method of claim 1 , further comprising: displaying, separately from any other search results, the set of results from the search of the compound search query. 3. The method of claim 2 , further comprising: displaying the set of results received from performing the search using the compound search query in a browser tab; and displaying each set of results received from performing the search for each sub-query in separate browser tabs. | 0.5 |
9,325,568 | 7 | 9 | 7. The method of claim 6 , wherein the event message reported by the network element includes at least one first context identifier relating to a first communication entity of the reporting network element and at least one second context identifier relating to a second communication entity of the network element on the peer side. | 7. The method of claim 6 , wherein the event message reported by the network element includes at least one first context identifier relating to a first communication entity of the reporting network element and at least one second context identifier relating to a second communication entity of the network element on the peer side. 9. The method of claim 7 , wherein information regarding the second context identifier relating to the peer side has been obtained by the reporting network element during a context exchange process from the network element on the peer side. | 0.571429 |
7,580,908 | 8 | 11 | 8. The system of claim 7 , wherein a plurality of candidate utterances are defined for each intention. | 8. The system of claim 7 , wherein a plurality of candidate utterances are defined for each intention. 11. The system of claim 8 , wherein the plurality of candidate utterances are analyzed according to a Bayesian network model, the model is determined over different instances of time to probabilistically infer a communicators intent. | 0.5 |
8,131,714 | 1 | 7 | 1. A method for determining a linguistic preference between two or more phrases each of the two or more phrases including a plurality of words, comprising: submitting each of the two or more phrases simultaneously, and one or more linguistic categories, as a search string to at least one search engine, wherein a search performed by the at least one search engine is restricted to the one or more linguistic categories; receiving search results from each instance of the at least one search engine for each submitted search string; comparing total hit values of each search result with each other; and displaying, to a user, one of the phrases associated with a greatest total hit value as a preferred phrase, wherein the step of displaying comprises displaying, to the user, two or more of display phrases where a difference between the total hit values of the two or more phrases is less than a predefined percentage. | 1. A method for determining a linguistic preference between two or more phrases each of the two or more phrases including a plurality of words, comprising: submitting each of the two or more phrases simultaneously, and one or more linguistic categories, as a search string to at least one search engine, wherein a search performed by the at least one search engine is restricted to the one or more linguistic categories; receiving search results from each instance of the at least one search engine for each submitted search string; comparing total hit values of each search result with each other; and displaying, to a user, one of the phrases associated with a greatest total hit value as a preferred phrase, wherein the step of displaying comprises displaying, to the user, two or more of display phrases where a difference between the total hit values of the two or more phrases is less than a predefined percentage. 7. The method of claim 1 , the step of comparing being performed by the at least one search engine. | 0.672185 |
9,350,753 | 1 | 22 | 1. A method of computer vulnerability discovery comprising: determining a plurality of researcher computers that are to be provided access to control logic, wherein a researcher computer of the plurality of researcher computers is a computer operated by, or to be operated by, an invited researcher, wherein an invited researcher is a person or organization selected to participate in one or more computer vulnerability research projects directed to researching and/or identifying computer vulnerabilities of one or more target systems comprising one or more network component and/or one or more computer component, wherein the control logic is logically interposed between the researcher computer and the one or more target systems; providing the plurality of researcher computers with access credentials for a management computer associated with the control logic to allow access to the control logic by particular ones of the plurality of researcher computers; tracking assignment of a particular computer vulnerability research project of the one or more computer vulnerability research projects to the researcher computer or to the invited researcher, wherein the particular computer vulnerability research project relates to a particular target system; establishing a communications path between the control logic and the particular target system; monitoring, using the control logic, networked data communications between the researcher computer and the particular target system, wherein the networked data communications include communications that are usable to identify a candidate vulnerability of the particular target system; determining a candidate vulnerability of the particular target system based on a report received from the invited researcher resulting from the invited researcher's use of the researcher computer to interact with the particular target system via the control logic; validating the report of the candidate vulnerability of the particular target system, wherein validating comprises attempting duplication of the candidate vulnerability after receiving the report; and triggering one or more remediation operations on the particular target system based at least in part upon the report. | 1. A method of computer vulnerability discovery comprising: determining a plurality of researcher computers that are to be provided access to control logic, wherein a researcher computer of the plurality of researcher computers is a computer operated by, or to be operated by, an invited researcher, wherein an invited researcher is a person or organization selected to participate in one or more computer vulnerability research projects directed to researching and/or identifying computer vulnerabilities of one or more target systems comprising one or more network component and/or one or more computer component, wherein the control logic is logically interposed between the researcher computer and the one or more target systems; providing the plurality of researcher computers with access credentials for a management computer associated with the control logic to allow access to the control logic by particular ones of the plurality of researcher computers; tracking assignment of a particular computer vulnerability research project of the one or more computer vulnerability research projects to the researcher computer or to the invited researcher, wherein the particular computer vulnerability research project relates to a particular target system; establishing a communications path between the control logic and the particular target system; monitoring, using the control logic, networked data communications between the researcher computer and the particular target system, wherein the networked data communications include communications that are usable to identify a candidate vulnerability of the particular target system; determining a candidate vulnerability of the particular target system based on a report received from the invited researcher resulting from the invited researcher's use of the researcher computer to interact with the particular target system via the control logic; validating the report of the candidate vulnerability of the particular target system, wherein validating comprises attempting duplication of the candidate vulnerability after receiving the report; and triggering one or more remediation operations on the particular target system based at least in part upon the report. 22. The method of claim 1 , further comprising: storing flow records based upon packet flow identifiers; and storing packets, segments, messages or request-response pairs based upon 5-tuple identifying data. | 0.892746 |
7,650,353 | 14 | 18 | 14. One or more computer storage media having computer-executable components for transforming electronic data interchange (EDI) transactions, said computer-executable components comprising: an interface component for receiving EDI data in a batch from a transmitting source and transmitting the received EDI data to a recipient, said batch of EDI data including a plurality of EDI documents, each having at least one EDI transaction corresponding to a transaction type; an identification component for identifying the EDI transactions included in the plurality of EDI documents by decoding the received EDI data according to EDI standards, each of the identified EDI transactions having transaction values associated therewith, said identification component farther identifies multiple instances of the identified EDI transactions belonging to the same transaction type; wherein the identification component identifies repeated EDI transaction structural elements in the identified multiple instances of the EDI transactions in the EDI documents belonging to the same transaction type, wherein the identification component also reduces a number of lines of multiple instances of the identified EDI transactions belonging to the same transaction type so that only one instance of the identified repeated EDI transaction structural elements remains, and the transaction values associated with the multiple instances of the identified EDI transactions are enclosed in a nested structure of the one instance of the repeated EDI transaction structural elements, said nested structure of the transaction values in the one instance of the repeated EDI transaction structural elements representing the same information as the repeated EDI transactions of the multiple instances of the identified EDI transactions; and a transformation component for defining a consolidated EDI document from the plurality of EDI documents in the batch of EDI data, said consolidated EDI document including the identified EDI transactions organized according to the transaction type and including the nested structure with the one instance of the identified repeated EDI transaction structural elements such that a loop-like logic can be used to create copies thereof during processing. | 14. One or more computer storage media having computer-executable components for transforming electronic data interchange (EDI) transactions, said computer-executable components comprising: an interface component for receiving EDI data in a batch from a transmitting source and transmitting the received EDI data to a recipient, said batch of EDI data including a plurality of EDI documents, each having at least one EDI transaction corresponding to a transaction type; an identification component for identifying the EDI transactions included in the plurality of EDI documents by decoding the received EDI data according to EDI standards, each of the identified EDI transactions having transaction values associated therewith, said identification component farther identifies multiple instances of the identified EDI transactions belonging to the same transaction type; wherein the identification component identifies repeated EDI transaction structural elements in the identified multiple instances of the EDI transactions in the EDI documents belonging to the same transaction type, wherein the identification component also reduces a number of lines of multiple instances of the identified EDI transactions belonging to the same transaction type so that only one instance of the identified repeated EDI transaction structural elements remains, and the transaction values associated with the multiple instances of the identified EDI transactions are enclosed in a nested structure of the one instance of the repeated EDI transaction structural elements, said nested structure of the transaction values in the one instance of the repeated EDI transaction structural elements representing the same information as the repeated EDI transactions of the multiple instances of the identified EDI transactions; and a transformation component for defining a consolidated EDI document from the plurality of EDI documents in the batch of EDI data, said consolidated EDI document including the identified EDI transactions organized according to the transaction type and including the nested structure with the one instance of the identified repeated EDI transaction structural elements such that a loop-like logic can be used to create copies thereof during processing. 18. The computer storage media of claim 14 , wherein the consolidated EDI document includes an uber-schema, said uber-schema representing a plurality of schemas referenced by the EDI transactions. | 0.512438 |
7,571,106 | 8 | 9 | 8. The method of claim 1 , further comprising obtaining additional data representing updates of the first data for publication on the publication site by action of a human digger not associated with either of the data providers. | 8. The method of claim 1 , further comprising obtaining additional data representing updates of the first data for publication on the publication site by action of a human digger not associated with either of the data providers. 9. The method of claim 8 , wherein the additional data comprises a correction to the first data. | 0.5 |
8,959,483 | 21 | 25 | 21. A computing system comprising: one or more computing devices configured to: create an intermediate representation of an electronic document page, the page being defined by a page description implemented in a markup language, the page description referring to data accessible via a data model, the intermediate representation including at least a portion of the data accessible via the data model, the intermediate representation being renderable to create a rendered page, the rendered page being displayable on a display device; initiate an action in the intermediate representation, the action simulating user input that can be provided via a rendered representation of the page, the action capable of causing a change in the portion of the data accessible via the data model; determine an expected value for the portion of the data model based on the initiated action in the intermediate representation; identify an actual value for the portion of the data model; determine whether the actual value matches the expected value; and when the actual value does not match the expected value, store an indication of an error. | 21. A computing system comprising: one or more computing devices configured to: create an intermediate representation of an electronic document page, the page being defined by a page description implemented in a markup language, the page description referring to data accessible via a data model, the intermediate representation including at least a portion of the data accessible via the data model, the intermediate representation being renderable to create a rendered page, the rendered page being displayable on a display device; initiate an action in the intermediate representation, the action simulating user input that can be provided via a rendered representation of the page, the action capable of causing a change in the portion of the data accessible via the data model; determine an expected value for the portion of the data model based on the initiated action in the intermediate representation; identify an actual value for the portion of the data model; determine whether the actual value matches the expected value; and when the actual value does not match the expected value, store an indication of an error. 25. The computing system recited in claim 21 , the one or more computing devices configured to: compile test procedure computer programming language instructions describing a test procedure for testing the page to create an executable test procedure. | 0.770221 |
9,507,826 | 19 | 20 | 19. A computer program product encoded on one or more non-transitory computer readable media, the computer program product comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: sending, to a client, client software that, when executed on the client, causes the client to: receive real-time search results for a first search query and a time token, wherein the time token is data that identifies a most-recent time that any resource identified by any of the received real-time search results was updated, present the real-time search results for the first search query, re-submit the first search query with the time token, obtain additional real-time search results that are more recent than the most-recent time identified by the time token, wherein an additional real-time search result is more recent than the most-recent time identified by the time token when a resource identified by the additional real-time search result was last updated more recently than the most-recent time identified by the time token, and present the additional real-time search results. | 19. A computer program product encoded on one or more non-transitory computer readable media, the computer program product comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: sending, to a client, client software that, when executed on the client, causes the client to: receive real-time search results for a first search query and a time token, wherein the time token is data that identifies a most-recent time that any resource identified by any of the received real-time search results was updated, present the real-time search results for the first search query, re-submit the first search query with the time token, obtain additional real-time search results that are more recent than the most-recent time identified by the time token, wherein an additional real-time search result is more recent than the most-recent time identified by the time token when a resource identified by the additional real-time search result was last updated more recently than the most-recent time identified by the time token, and present the additional real-time search results. 20. The computer program product of claim 19 , the operations further comprising: receiving the first search query from the client; determining that the first search query is a search query for which real-time search results should be returned; and sending to the client a user interface document that contains the client software as a response to the first search query. | 0.5 |
8,230,343 | 15 | 16 | 15. The apparatus of claim 9 , wherein the metadata generator further for incorporating manual adjustments to the start and end of at least one of the video program segments comprises the metadata generator further for: incorporating first manual adjustments to the start and end of a video portion of the at least one of the video program segments; incorporating second manual adjustments to the start and end of an audio portion of the at least one of the video program segments, wherein the first and second manual adjustments result in the video portion being a different length than the audio portion; and further modifying content of the at least one of the video program segments so that the video portion and the audio portion have the same length. | 15. The apparatus of claim 9 , wherein the metadata generator further for incorporating manual adjustments to the start and end of at least one of the video program segments comprises the metadata generator further for: incorporating first manual adjustments to the start and end of a video portion of the at least one of the video program segments; incorporating second manual adjustments to the start and end of an audio portion of the at least one of the video program segments, wherein the first and second manual adjustments result in the video portion being a different length than the audio portion; and further modifying content of the at least one of the video program segments so that the video portion and the audio portion have the same length. 16. The apparatus of claim 15 , wherein the metadata generator further for further modifying content of the at least one of the video program segments so that the video portion and the audio portion have the same length comprises the metadata generator further for lengthening the video portion by performing an action selected from a group consisting of: adding filler content to the video portion; adding one or more freeze-frame displays to the video portion; and altering at least a part of the video portion to be in slow motion. | 0.5 |
8,631,350 | 1 | 6 | 1. A method for displaying a graphical context menu on a display screen of a communication device, the method comprising: receiving a menu request; selecting, based on a context of the menu request, a subset of menu items from a complete set of menu items available for the context; determining a number of slots for a graphical context menu based on a number of menu items selected in the subset of menu items; comparing the number of slots for the graphical context menu to the number of menu items: obtaining at least one filler menu item from the complete set of menu items, the at least one filler menu item not being included in the subset of menu items; inserting the subset of menu items and the at least one filler menu item into selected slots in the graphical context menu; and rendering the graphical context menu on the display screen with the menu items and the at least one filler menu item. | 1. A method for displaying a graphical context menu on a display screen of a communication device, the method comprising: receiving a menu request; selecting, based on a context of the menu request, a subset of menu items from a complete set of menu items available for the context; determining a number of slots for a graphical context menu based on a number of menu items selected in the subset of menu items; comparing the number of slots for the graphical context menu to the number of menu items: obtaining at least one filler menu item from the complete set of menu items, the at least one filler menu item not being included in the subset of menu items; inserting the subset of menu items and the at least one filler menu item into selected slots in the graphical context menu; and rendering the graphical context menu on the display screen with the menu items and the at least one filler menu item. 6. The method of claim 1 wherein determining the number of slots for the graphical context menu includes generating a grid in accordance with the number of slots, the grid being one of: a three column by three row grid, a three column by two row grid, and a three column by one row grid. | 0.5 |
8,503,797 | 3 | 7 | 3. The method of claim 2 , wherein extracting the physical attributes of the scanned document comprises cropping and/or rotating the scanned document as needed to create a processed scanned document for feature extraction. | 3. The method of claim 2 , wherein extracting the physical attributes of the scanned document comprises cropping and/or rotating the scanned document as needed to create a processed scanned document for feature extraction. 7. The method of claim 3 , wherein the extracting of physical attributes of the scanned document comprises detecting the colorfulness of the scanned document. | 0.584211 |
9,609,127 | 2 | 3 | 2. The method of claim 1 , wherein the device participating in the interactive communication initiates the interactive communication and further comprising: assigning scores to multiple instances of the incompatible input, and aggregating the scores. | 2. The method of claim 1 , wherein the device participating in the interactive communication initiates the interactive communication and further comprising: assigning scores to multiple instances of the incompatible input, and aggregating the scores. 3. The method of claim 2 , wherein the scores are aggregated until a threshold is reached, and wherein the original script is not modified until the threshold is reached. | 0.5 |
8,751,214 | 6 | 12 | 6. A non-transitory computer readable medium storing a program causing a computer to execute a process for performing an information processing, the process comprising: receiving an image including a non-character region; specifying a candidate region in the image; recognizing characters in the candidate region; obtaining as a recognized character feature, a quantity of predetermined characters contained in the characters recognized in the candidate region; deciding whether or not the recognized characters are to be translated in accordance with the obtained recognized character feature; translating the recognized characters in a case where it is decided that the recognized characters are to be translated; obtaining a feature from a translated result; deciding whether or not the translated result is to be outputted in accordance with the feature obtained from the translated result; and outputting, in a case where the output deciding unit decides that the translated result is to be outputted, the translated result in accordance with a structure of the image, wherein the recognizing of the characters recognizes characters in the character image of the received image in the receiving of the image, the obtaining of the recognized character feature of the recognized characters, in a case where a picture image other than the characters are recognized, obtains a feature related to characters included in the picture image, and the predetermined characters are characters frequently appearing in characters obtained by performing character recognition in a region which does not include characters. | 6. A non-transitory computer readable medium storing a program causing a computer to execute a process for performing an information processing, the process comprising: receiving an image including a non-character region; specifying a candidate region in the image; recognizing characters in the candidate region; obtaining as a recognized character feature, a quantity of predetermined characters contained in the characters recognized in the candidate region; deciding whether or not the recognized characters are to be translated in accordance with the obtained recognized character feature; translating the recognized characters in a case where it is decided that the recognized characters are to be translated; obtaining a feature from a translated result; deciding whether or not the translated result is to be outputted in accordance with the feature obtained from the translated result; and outputting, in a case where the output deciding unit decides that the translated result is to be outputted, the translated result in accordance with a structure of the image, wherein the recognizing of the characters recognizes characters in the character image of the received image in the receiving of the image, the obtaining of the recognized character feature of the recognized characters, in a case where a picture image other than the characters are recognized, obtains a feature related to characters included in the picture image, and the predetermined characters are characters frequently appearing in characters obtained by performing character recognition in a region which does not include characters. 12. The non-transitory computer readable medium as claimed in claim 6 , wherein the predetermined characters correspond to non-character image features appearing similar to recognized characters. | 0.5 |
9,766,805 | 2 | 3 | 2. The system of claim 1 , wherein said at least one processor is further configured to assign a second rank to each complex conjunct character among a plurality of complex conjunct characters based on a second frequency of occurrence of said each complex conjunct character in said dictionary, wherein said each complex conjunct character corresponds to at least one of said plurality of conjunct characters. | 2. The system of claim 1 , wherein said at least one processor is further configured to assign a second rank to each complex conjunct character among a plurality of complex conjunct characters based on a second frequency of occurrence of said each complex conjunct character in said dictionary, wherein said each complex conjunct character corresponds to at least one of said plurality of conjunct characters. 3. The system of claim 2 , wherein each of said plurality of base characters is a single code point of a character encoding method, each of said plurality of conjunct characters is a combination of two code points of said character encoding method, and each of said plurality of complex conjunct characters is a combination of at least three code points of said character encoding method. | 0.5 |
8,560,562 | 14 | 15 | 14. The client device of claim 12 , wherein: the client device receives a search results resource in response to a query received from the client device, the search results resource including: third instructions that cause the client device to generate a search results page that displays search results referencing resources determined to be responsive to the query; additional query suggestions; and fourth instructions that cause the client device to store the additional query suggestions in the suggestion store on the client device. | 14. The client device of claim 12 , wherein: the client device receives a search results resource in response to a query received from the client device, the search results resource including: third instructions that cause the client device to generate a search results page that displays search results referencing resources determined to be responsive to the query; additional query suggestions; and fourth instructions that cause the client device to store the additional query suggestions in the suggestion store on the client device. 15. The client device of claim 14 , wherein: the search results page includes a second query input field; and the fourth instructions cause the client device to: compare query characters input in the second query input field to the query suggestions stored in the suggestion store; select query suggestions that match the query characters input in the second query input field based on the comparison; and display the selected query suggestions as query suggestions for the query characters input into the second query input field. | 0.5 |
7,542,029 | 27 | 28 | 27. The apparatus of claim 24 , wherein said processor further comprises: a seventh component for automatically generating one or more spaces between one or more output textual objects. | 27. The apparatus of claim 24 , wherein said processor further comprises: a seventh component for automatically generating one or more spaces between one or more output textual objects. 28. The apparatus of claim 27 , wherein said processor further comprises: an eighth component for identifying two or more textual objects as belonging to two or more classes of textual objects, wherein each of said two or more classes of textual objects differs from other said classes in the manner in which one or more spaces are automatically generated at least one of preceding or following the output of a textual object belonging to said class. | 0.5 |
8,565,526 | 1 | 5 | 1. A method of searching optical character recognition results of image text documents comprising: linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results; creating reflection files corresponding to the image text documents from the edited text results; storing the reflection files in a reflection repository; searching the reflection files; and displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. | 1. A method of searching optical character recognition results of image text documents comprising: linguistically analyzing the optical character recognition results within a context of multiple lexicons to form edited text results; creating reflection files corresponding to the image text documents from the edited text results; storing the reflection files in a reflection repository; searching the reflection files; and displaying a first reflection file from the reflection files or a first image text document from the image text documents in response to searching. 5. A method as recited in claim 1 further comprising grammatically analyzing the optical character recognition results to form the edited text results. | 0.640476 |
7,993,372 | 14 | 17 | 14. A spinal implant system that is adapted to be mounted to a spine comprising: first and second anchors that are adapted to be secured to a spine; a first horizontal rod that is secured to the first and second anchors; a deflection rod system; a mount to mount the deflection rod system to said first horizontal rod; said deflection rod system including an inner rod and an outer shell; wherein said inner rod is elongated and said outer shell is elongated along the elongated inner rod; said deflection rod system including a shield that is elongated and is provided along and about the outer shell which shielded limits the deflection of said inner rod and said outer shell; said deflection rod system includes at least one first section that is moveable relative to a second section in order to accommodate movement of a spine; at least one joint connection located at an end of the deflection rod system; a first vertical rod that is secured by said joint connection to said first horizontal rod. | 14. A spinal implant system that is adapted to be mounted to a spine comprising: first and second anchors that are adapted to be secured to a spine; a first horizontal rod that is secured to the first and second anchors; a deflection rod system; a mount to mount the deflection rod system to said first horizontal rod; said deflection rod system including an inner rod and an outer shell; wherein said inner rod is elongated and said outer shell is elongated along the elongated inner rod; said deflection rod system including a shield that is elongated and is provided along and about the outer shell which shielded limits the deflection of said inner rod and said outer shell; said deflection rod system includes at least one first section that is moveable relative to a second section in order to accommodate movement of a spine; at least one joint connection located at an end of the deflection rod system; a first vertical rod that is secured by said joint connection to said first horizontal rod. 17. The spinal implant system of claim 14 wherein the joint connection includes a cylindrical surface joint. | 0.865672 |
9,575,947 | 2 | 3 | 2. The method of claim 1 , further comprising: identifying, using a computer or hardware component, a suitable expression of the subject annotation on a per document basis. | 2. The method of claim 1 , further comprising: identifying, using a computer or hardware component, a suitable expression of the subject annotation on a per document basis. 3. The method of claim 2 , further comprising: mapping an identified suitable expression to an aggregate of said plurality of annotators. | 0.5 |
9,430,531 | 1 | 19 | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information of the sender comprises an e-mail address of the sender; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information of the sender comprises an e-mail address of the sender; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. 19. The method of claim 1 wherein the receiving first activity information for the sender comprises: sending of an e-mail including the first link by the sender via a nonmobile device. | 0.816 |
9,852,655 | 11 | 20 | 11. A computing system comprising: a keyword store hosted on one or more server computers comprising non-transitory machine-readable storage media, the keyword store configured to store one or more words of text of one or more resources; and at least one processor of at least one computer configured to: determine a level score of a learner based upon a plurality of responsive inputs received from a client device associated with the learner via one or more networks; determine a pedagogical value threshold based upon a level score of the learner and a resource difficulty score of a resource; identify in the text of the resource each word having a word difficulty score satisfying the pedagogical value threshold; store into the keyword store each word satisfying the pedagogical value threshold; select from a resource store the resource comprising content associated with one or more learner attributes of the learner using each word satisfying the pedagogical value threshold; identify a type of learning activity that exercises a language skill for improvement of the learner and corresponds to a goal of the learner; identify one or more records in a distractor store containing a set of one or more distractors of a type suited to the identified type of learning activity; and generate a learning activity of the identified type of learning activity utilizing at least one of the set of one or more distractors extracted from the selected resource. | 11. A computing system comprising: a keyword store hosted on one or more server computers comprising non-transitory machine-readable storage media, the keyword store configured to store one or more words of text of one or more resources; and at least one processor of at least one computer configured to: determine a level score of a learner based upon a plurality of responsive inputs received from a client device associated with the learner via one or more networks; determine a pedagogical value threshold based upon a level score of the learner and a resource difficulty score of a resource; identify in the text of the resource each word having a word difficulty score satisfying the pedagogical value threshold; store into the keyword store each word satisfying the pedagogical value threshold; select from a resource store the resource comprising content associated with one or more learner attributes of the learner using each word satisfying the pedagogical value threshold; identify a type of learning activity that exercises a language skill for improvement of the learner and corresponds to a goal of the learner; identify one or more records in a distractor store containing a set of one or more distractors of a type suited to the identified type of learning activity; and generate a learning activity of the identified type of learning activity utilizing at least one of the set of one or more distractors extracted from the selected resource. 20. The system according to claim 11 , wherein the at least one processor is further configured to parse from the text of the resource a word of the one or more words of the text upon determining that the word matches a whitelist word in a computer file containing one or more whitelist words. | 0.672991 |
10,067,918 | 1 | 2 | 1. A method, comprising: identifying, by at least one computing device, a series of characters within a text block, the series of characters being a subset of the text block; binding, by the at least one computing device, the series of characters to generate a text unit; encoding, by the at least one computing device, the text block to generate an encoded text block, wherein the encoded text block comprises a first signal indicating that an entirety of the series of characters in the text unit is to be selected in response to a subset of the series of characters being selected; selecting, by the at least one computing device, in response to the first signal and at least a portion of the subset of the series of characters being selected, the entirety of the series of characters in the text unit; and encoding, by the at least one computing device, in response to an instruction to treat the series of characters as being unbound, the text block to generate a modified encoded text block, wherein the modified encoded text block comprises a second signal indicating that a portion of the series of characters is to be selected in response to the portion of the series of characters being selected. | 1. A method, comprising: identifying, by at least one computing device, a series of characters within a text block, the series of characters being a subset of the text block; binding, by the at least one computing device, the series of characters to generate a text unit; encoding, by the at least one computing device, the text block to generate an encoded text block, wherein the encoded text block comprises a first signal indicating that an entirety of the series of characters in the text unit is to be selected in response to a subset of the series of characters being selected; selecting, by the at least one computing device, in response to the first signal and at least a portion of the subset of the series of characters being selected, the entirety of the series of characters in the text unit; and encoding, by the at least one computing device, in response to an instruction to treat the series of characters as being unbound, the text block to generate a modified encoded text block, wherein the modified encoded text block comprises a second signal indicating that a portion of the series of characters is to be selected in response to the portion of the series of characters being selected. 2. The method of claim 1 , wherein the text unit comprises a cryptographic signature. | 0.833984 |
8,065,286 | 1 | 32 | 1. A method of performing a search, comprising: receiving a query from a query source; selectively including a keyword among a plurality of keywords based on a predetermined frequency of the keyword in a corpus; registering, by a searcher, for the keyword; selecting the searcher based on a ranking of the searcher among searchers registered for the keyword when determining that the keyword is a highest ranking keyword of the query; selecting the searcher based on a generalist ranking of the searcher when determining that the query does not indicate a keyword registered by at least one searcher; conducting the search by the searcher using a resource ranked highest by the searcher for conducting searches; presenting search results to the searcher from a plurality of resources selected based on the searcher, the searcher reviewing the search results from the resource ranked highest and the plurality of resources and selecting a result considered optimal for the query; and supplying the result to the query source subsequent to said reviewing by the searcher. | 1. A method of performing a search, comprising: receiving a query from a query source; selectively including a keyword among a plurality of keywords based on a predetermined frequency of the keyword in a corpus; registering, by a searcher, for the keyword; selecting the searcher based on a ranking of the searcher among searchers registered for the keyword when determining that the keyword is a highest ranking keyword of the query; selecting the searcher based on a generalist ranking of the searcher when determining that the query does not indicate a keyword registered by at least one searcher; conducting the search by the searcher using a resource ranked highest by the searcher for conducting searches; presenting search results to the searcher from a plurality of resources selected based on the searcher, the searcher reviewing the search results from the resource ranked highest and the plurality of resources and selecting a result considered optimal for the query; and supplying the result to the query source subsequent to said reviewing by the searcher. 32. The method as recited in claim 1 , further comprising presenting an advertisement to a user during the receiving, selecting, presenting and supplying. | 0.677824 |
9,298,276 | 11 | 13 | 11. The computing device of claim 10 , wherein the computing device is configured to: compare the plurality of respective characters associated with the plurality of respective keys to at least one string pattern that includes the at least one metacharacter, wherein the at least one string pattern is associated with the category; and identify the category based on determining that the plurality of respective characters matches the at least one string pattern. | 11. The computing device of claim 10 , wherein the computing device is configured to: compare the plurality of respective characters associated with the plurality of respective keys to at least one string pattern that includes the at least one metacharacter, wherein the at least one string pattern is associated with the category; and identify the category based on determining that the plurality of respective characters matches the at least one string pattern. 13. The computing device of claim 11 , wherein the at least one string pattern is a regular expression. | 0.920647 |
7,912,828 | 8 | 10 | 8. An apparatus for identifying patterns in text using structures defining types of patterns which are to be identified, wherein a structure comprises one or more definition items, the apparatus comprising: a processing system coupled to memory; means for assigning a fixed weighting to each structure and each definition item in each structure, each fixed weighting being an integer multiple of the same integer; means for searching the text for a pattern to be identified on the basis of a particular structure, a pattern being provisionally identified if it matches the definition given by said particular structure; in a provisionally identified pattern, means for determining definition items making up said particular structure that have been identified in the provisionally identified pattern; means for combining the fixed weightings of the determined definition items and the fixed weighting of the particular structure to a single quantity; means for assessing whether the single quantity fulfils a given condition; and depending on the result of said assessment, means for rejecting or confirming the provisionally identified pattern. | 8. An apparatus for identifying patterns in text using structures defining types of patterns which are to be identified, wherein a structure comprises one or more definition items, the apparatus comprising: a processing system coupled to memory; means for assigning a fixed weighting to each structure and each definition item in each structure, each fixed weighting being an integer multiple of the same integer; means for searching the text for a pattern to be identified on the basis of a particular structure, a pattern being provisionally identified if it matches the definition given by said particular structure; in a provisionally identified pattern, means for determining definition items making up said particular structure that have been identified in the provisionally identified pattern; means for combining the fixed weightings of the determined definition items and the fixed weighting of the particular structure to a single quantity; means for assessing whether the single quantity fulfils a given condition; and depending on the result of said assessment, means for rejecting or confirming the provisionally identified pattern. 10. The apparatus of claim 8 , wherein the single quantity is obtained by the means for combining the fixed weightings using one or more arithmetic operations. | 0.521084 |
9,740,881 | 7 | 10 | 7. A computer system, comprising: one or more processors; and memory including instructions that, when executed by the one or more processors, cause the computer system to at least: analyze a query response, corresponding to a query that has been submitted by a user, to obtain an advertisement targeted at the user, the advertisement being part of the query response; provide the query and the query response to a noise engine configured to generate noise information for the computer system based at least in part on the advertisement, the query comprising information that identifies at least one of the user or the query; receive the noise information from the noise engine, the noise information generated by the noise engine based at least in part on the query and the advertisement, and the noise information comprising a noise schedule with respective query execution times; cause one or more additional queries to be generated based at least in part on the noise information; and cause the one or more additional queries to be transmitted to the search engine according to the respective query execution times of the noise schedule. | 7. A computer system, comprising: one or more processors; and memory including instructions that, when executed by the one or more processors, cause the computer system to at least: analyze a query response, corresponding to a query that has been submitted by a user, to obtain an advertisement targeted at the user, the advertisement being part of the query response; provide the query and the query response to a noise engine configured to generate noise information for the computer system based at least in part on the advertisement, the query comprising information that identifies at least one of the user or the query; receive the noise information from the noise engine, the noise information generated by the noise engine based at least in part on the query and the advertisement, and the noise information comprising a noise schedule with respective query execution times; cause one or more additional queries to be generated based at least in part on the noise information; and cause the one or more additional queries to be transmitted to the search engine according to the respective query execution times of the noise schedule. 10. The computer system of claim 7 , wherein: the query response includes search result information from responses to the query submitted by the user; and the instructions further cause the computer system to generate search terms based at least in part on the search result information. | 0.5 |
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