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8,938,403 | 8 | 14 | 8. A system configured to compute token-dependent affective response baseline levels for a user, comprising: a database comprising first, second, and third affective response annotations corresponding to first, second, and third temporal windows of token instances, respectively; wherein, the user was exposed to the first, second, and third, temporal windows of token instances during first, second, and third time periods, respectively; and wherein the first time period precedes the second time period, and the second time period precedes the third time period; and a baseline calculator, implemented utilizing a processor, configured to receive a certain temporal window of token instances and to compute, using a distance function, a first metric, a second metric, and a third metric between the certain temporal window of token instances and of the first temporal window of token instances, the second temporal window of token instances, and the third temporal window of token instances respectively; wherein the first and third metrics are below a predefined threshold, while the second metric is not below the predefined threshold; the baseline calculator is further configured to receive, from the database, the first and third affective response annotations and to compute a first affective response baseline level, associated with the certain temporal window of token instances, based on data comprising the first and third affective response annotations; the baseline calculator is further configured to receive an additional temporal window of token instances; the baseline calculator is further configured to receive, from the database, the second affective response annotation; wherein a fourth metric between the additional temporal windows of token instances and the second temporal windows of token instances is below the predefined threshold; the baseline calculator is further configured to compute a second affective response baseline level associated with the additional temporal window of token instances based on data comprising the second affective response annotation; wherein the computed first affective response baseline level is different from the computed second affective response baseline level; wherein the first and second affective response baseline levels each represent a value comprising at least one of: an emotional response, and a value of a user measurement channel. | 8. A system configured to compute token-dependent affective response baseline levels for a user, comprising: a database comprising first, second, and third affective response annotations corresponding to first, second, and third temporal windows of token instances, respectively; wherein, the user was exposed to the first, second, and third, temporal windows of token instances during first, second, and third time periods, respectively; and wherein the first time period precedes the second time period, and the second time period precedes the third time period; and a baseline calculator, implemented utilizing a processor, configured to receive a certain temporal window of token instances and to compute, using a distance function, a first metric, a second metric, and a third metric between the certain temporal window of token instances and of the first temporal window of token instances, the second temporal window of token instances, and the third temporal window of token instances respectively; wherein the first and third metrics are below a predefined threshold, while the second metric is not below the predefined threshold; the baseline calculator is further configured to receive, from the database, the first and third affective response annotations and to compute a first affective response baseline level, associated with the certain temporal window of token instances, based on data comprising the first and third affective response annotations; the baseline calculator is further configured to receive an additional temporal window of token instances; the baseline calculator is further configured to receive, from the database, the second affective response annotation; wherein a fourth metric between the additional temporal windows of token instances and the second temporal windows of token instances is below the predefined threshold; the baseline calculator is further configured to compute a second affective response baseline level associated with the additional temporal window of token instances based on data comprising the second affective response annotation; wherein the computed first affective response baseline level is different from the computed second affective response baseline level; wherein the first and second affective response baseline levels each represent a value comprising at least one of: an emotional response, and a value of a user measurement channel. 14. The system of claim 8 , wherein for computing the first affective response baseline level the baseline calculator is further configured to perform at least one of the following to values comprising the first and third affective response annotations: averaging the values, applying low-pass filtering to the values, applying Fourier transform to the values, and performing wavelet transform analysis on the values. | 0.5 |
8,346,557 | 8 | 9 | 8. The method of claim 1 , further comprising: receiving by the computer, a user selection of the second, different voice model from one of a plurality of narration voice models to associate with the selected portion of words. | 8. The method of claim 1 , further comprising: receiving by the computer, a user selection of the second, different voice model from one of a plurality of narration voice models to associate with the selected portion of words. 9. The method of claim 8 wherein the narration voice models are user-modifiable. | 0.760479 |
9,437,186 | 16 | 18 | 16. A system, comprising: at least one processor coupled to a memory, the memory including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive audio input data including speech; to perform automatic speech recognition (ASR) processing on the audio input data to obtain a speech recognition output; to determine, based at least in part on the speech recognition output, a likelihood that the speech recognition output includes a complete user command; to determine, based at least in part on the likelihood, a threshold length of non-speech that is processed before indicating an ending of the speech; to determine an ending of an utterance in the audio input data after the threshold length of non-speech is detected in the audio input data; and to, after determining the ending, initiate an action to be executed on a first device based at least in part on the speech recognition output and the ending. | 16. A system, comprising: at least one processor coupled to a memory, the memory including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor: to receive audio input data including speech; to perform automatic speech recognition (ASR) processing on the audio input data to obtain a speech recognition output; to determine, based at least in part on the speech recognition output, a likelihood that the speech recognition output includes a complete user command; to determine, based at least in part on the likelihood, a threshold length of non-speech that is processed before indicating an ending of the speech; to determine an ending of an utterance in the audio input data after the threshold length of non-speech is detected in the audio input data; and to, after determining the ending, initiate an action to be executed on a first device based at least in part on the speech recognition output and the ending. 18. The system of claim 16 , wherein the at least one processor is further configured to perform natural language processing on the speech following the determining of the ending. | 0.871037 |
9,865,253 | 1 | 6 | 1. A computer-implemented method for reducing a security vulnerability of a speech-based user authentication process, the method comprising: storing executable instructions in memory of a server; receiving, by the server from a client device, a request to authenticate a user; receiving, by the server from the client device, a speech signal having one or more discriminating features; and executing, by a processor of the server, the instructions stored in memory of the server, wherein execution of the instructions causes the processor to: extract the one or more discriminating features from the received speech signal, wherein extracting the one or more discriminating features includes: segmenting the received speech signal into at least one of one or more utterances, one or more words, or one or more phonemes; computing one or more pitch patterns of the received speech signal; segmenting the pitch pattern to form a pitch pattern image, the pitch pattern image displaying a plurality of discrete data regions each forming a shape; and performing an image analysis of the pitch pattern image, wherein performing the image analysis includes: determining for each of at least a portion of the regions an upper line value associated with an upper edge of the shape displayed in the pitch pattern image and a lower line value associated a lower edge of the shape displayed in the pitch pattern image, and calculating one or more discriminating features based on the upper line value and the lower line value determined from the pitch pattern image to form a set of feature vectors; classify the received speech signal based on the extracted features as a synthetic speech signal configured to imitate a sequence of human vocal sounds, and decline the request to authenticate the user based on the classification of the received speech signal as the synthetic speech signal. | 1. A computer-implemented method for reducing a security vulnerability of a speech-based user authentication process, the method comprising: storing executable instructions in memory of a server; receiving, by the server from a client device, a request to authenticate a user; receiving, by the server from the client device, a speech signal having one or more discriminating features; and executing, by a processor of the server, the instructions stored in memory of the server, wherein execution of the instructions causes the processor to: extract the one or more discriminating features from the received speech signal, wherein extracting the one or more discriminating features includes: segmenting the received speech signal into at least one of one or more utterances, one or more words, or one or more phonemes; computing one or more pitch patterns of the received speech signal; segmenting the pitch pattern to form a pitch pattern image, the pitch pattern image displaying a plurality of discrete data regions each forming a shape; and performing an image analysis of the pitch pattern image, wherein performing the image analysis includes: determining for each of at least a portion of the regions an upper line value associated with an upper edge of the shape displayed in the pitch pattern image and a lower line value associated a lower edge of the shape displayed in the pitch pattern image, and calculating one or more discriminating features based on the upper line value and the lower line value determined from the pitch pattern image to form a set of feature vectors; classify the received speech signal based on the extracted features as a synthetic speech signal configured to imitate a sequence of human vocal sounds, and decline the request to authenticate the user based on the classification of the received speech signal as the synthetic speech signal. 6. The computer-implemented method of claim 1 , wherein no synthetic speech is required to train a classifier. | 0.929397 |
8,548,989 | 7 | 9 | 7. A computer program product to query a set of documents based on multiple relevance value types, the computer program product comprising: a computer-readable memory having computer-readable program code embodied therewith, the computer-readable memory including hardware, the computer-readable program code comprising: computer-readable program code configured to provide, for each document in the set, a summary representing the respective document, wherein providing the summary comprises, for each document, identifying content marked by hierarchical tags and generating the summary from the content marked by higher-order hierarchical tags; computer-readable program code configured to parse the set of documents using a received set of search terms in order to calculate, for each document in the set, a first relevance value based on the summary of the respective document and not based on the respective document itself; computer-readable program code configured to parse, from the set of documents and using the received set of search terms, only a subset of documents having the highest first relevance values in order to calculate, by operation of one or more computer processors when executing the computer-readable program code and for each document in the subset, a second relevance value based on the respective document itself and not based on the summary of the respective document, wherein the subset excludes at least one document in the set and for which a second relevance value is not calculated, thereby avoiding a processing cost associated with calculating the second relevance value for the at least one document in the set; and computer-readable program code configured to provide query results comprising documents from the subset that have the highest second relevance values, regardless of the first relevance value of any document in the set, wherein the query results exclude the at least one document in the set and at least one document in the subset. | 7. A computer program product to query a set of documents based on multiple relevance value types, the computer program product comprising: a computer-readable memory having computer-readable program code embodied therewith, the computer-readable memory including hardware, the computer-readable program code comprising: computer-readable program code configured to provide, for each document in the set, a summary representing the respective document, wherein providing the summary comprises, for each document, identifying content marked by hierarchical tags and generating the summary from the content marked by higher-order hierarchical tags; computer-readable program code configured to parse the set of documents using a received set of search terms in order to calculate, for each document in the set, a first relevance value based on the summary of the respective document and not based on the respective document itself; computer-readable program code configured to parse, from the set of documents and using the received set of search terms, only a subset of documents having the highest first relevance values in order to calculate, by operation of one or more computer processors when executing the computer-readable program code and for each document in the subset, a second relevance value based on the respective document itself and not based on the summary of the respective document, wherein the subset excludes at least one document in the set and for which a second relevance value is not calculated, thereby avoiding a processing cost associated with calculating the second relevance value for the at least one document in the set; and computer-readable program code configured to provide query results comprising documents from the subset that have the highest second relevance values, regardless of the first relevance value of any document in the set, wherein the query results exclude the at least one document in the set and at least one document in the subset. 9. The computer program product of claim 7 , wherein the summary is based on information embedded in the document by an author of the document. | 0.5 |
9,858,265 | 1 | 6 | 1. A method for determining a type of conversation continuity in a natural language conversation comprising a first query and a second query to refine search results in response to the first query and the second query based on the type of conversation continuity, the method comprising: receiving, via a user input device, the first query from a user; retrieving, from a database, a first search result for the first query; generating for display, using control circuitry, the first search result; receiving, via the user input device, the second query from the user; determining, using control circuitry, a first token in the first query; determining, using the control circuitry, a second token in the second query; identifying, using the control circuitry, first entity data for the first token, wherein the first entity data includes: a first entity type for the first token, a first probability that the first entity type corresponds to the first token, a second entity type for the first token, and a second probability that the second entity type corresponds to the first token; identifying, using the control circuitry, second entity data for the second token, wherein the second entity data includes: a third entity type for the second token, a third probability that the third entity type corresponds to the second token, a fourth entity type for the second token, and a fourth probability that the fourth entity type corresponds to the second token; transmitting a request including an indication of the first entity data and the second entity data for connections between the first entity data and the second entity data; in response to the transmitted request, receiving one or more graph connections between the first entity data and the second entity data obtained by a search of a knowledge graph, the search based on the indication of the first entity data and the second entity data; applying, using the control circuitry, the first token, the second token, the first entity data, the second entity data, and the one or more graph connections as inputs to an artificial neural network; determining, using the control circuitry, an output from the artificial neural network that indicates the type of conversation continuity between the first query and the second query; updating, using the control circuitry, the second query based on the type of conversation continuity; retrieving, from the database, a second search result for the updated second query; and generating for display, using control circuitry, the second search result. | 1. A method for determining a type of conversation continuity in a natural language conversation comprising a first query and a second query to refine search results in response to the first query and the second query based on the type of conversation continuity, the method comprising: receiving, via a user input device, the first query from a user; retrieving, from a database, a first search result for the first query; generating for display, using control circuitry, the first search result; receiving, via the user input device, the second query from the user; determining, using control circuitry, a first token in the first query; determining, using the control circuitry, a second token in the second query; identifying, using the control circuitry, first entity data for the first token, wherein the first entity data includes: a first entity type for the first token, a first probability that the first entity type corresponds to the first token, a second entity type for the first token, and a second probability that the second entity type corresponds to the first token; identifying, using the control circuitry, second entity data for the second token, wherein the second entity data includes: a third entity type for the second token, a third probability that the third entity type corresponds to the second token, a fourth entity type for the second token, and a fourth probability that the fourth entity type corresponds to the second token; transmitting a request including an indication of the first entity data and the second entity data for connections between the first entity data and the second entity data; in response to the transmitted request, receiving one or more graph connections between the first entity data and the second entity data obtained by a search of a knowledge graph, the search based on the indication of the first entity data and the second entity data; applying, using the control circuitry, the first token, the second token, the first entity data, the second entity data, and the one or more graph connections as inputs to an artificial neural network; determining, using the control circuitry, an output from the artificial neural network that indicates the type of conversation continuity between the first query and the second query; updating, using the control circuitry, the second query based on the type of conversation continuity; retrieving, from the database, a second search result for the updated second query; and generating for display, using control circuitry, the second search result. 6. The method of claim 1 , wherein updating the second query based on the type of conversation continuity comprises: identifying, using the control circuitry, the type of conversation continuity to be a merge type; merging, using the control circuitry, the second query with the first query based on identifying the type of conversation continuity to be the merge type. | 0.8207 |
8,000,991 | 14 | 16 | 14. A system comprising a computing device, and a workflow engine module for executing at least a portion of a workflow on the computing device, the workflow comprising one or more task activities comprising actions performed by devices participating in the workflow, routing activities used to transfer control and data between the devices and further comprising roles, the workflow engine module comprising: a receiving component configured to receive a message representing an incoming routing activity; a generating component, implemented using one or more processors, configured to generate from the workflow a local part to be executed on the computing device, wherein for generating the local part, the generating component is configured to: modify partner links in the workflow in order to specify coherent partner links; delete at least part or all task activities in the workflow that do not belong to the local part, while keeping dependencies specified by process control activities; and simplify the routing and process control activities in the workflow; an executing component configured to execute task activities comprised by the generated local part on the device; a performing component configured to perform a request to a discovery service in order to obtain one or more identifications of one or more next devices, the performing component including a matching component for matching a role to the capabilities of the one or more next devices, the role being a set of attributes of the next devices, the set of attributes being used to execute next task activities associated with a next local part on the one or more next devices; and a sending component configured to send one or more messages representing a next routing activity to the one or more next devices thus identified. | 14. A system comprising a computing device, and a workflow engine module for executing at least a portion of a workflow on the computing device, the workflow comprising one or more task activities comprising actions performed by devices participating in the workflow, routing activities used to transfer control and data between the devices and further comprising roles, the workflow engine module comprising: a receiving component configured to receive a message representing an incoming routing activity; a generating component, implemented using one or more processors, configured to generate from the workflow a local part to be executed on the computing device, wherein for generating the local part, the generating component is configured to: modify partner links in the workflow in order to specify coherent partner links; delete at least part or all task activities in the workflow that do not belong to the local part, while keeping dependencies specified by process control activities; and simplify the routing and process control activities in the workflow; an executing component configured to execute task activities comprised by the generated local part on the device; a performing component configured to perform a request to a discovery service in order to obtain one or more identifications of one or more next devices, the performing component including a matching component for matching a role to the capabilities of the one or more next devices, the role being a set of attributes of the next devices, the set of attributes being used to execute next task activities associated with a next local part on the one or more next devices; and a sending component configured to send one or more messages representing a next routing activity to the one or more next devices thus identified. 16. The system of claim 14 , wherein the executing component configured to execute the task activities is Business Process Execution Language (BPEL) enabled. | 0.734797 |
10,127,319 | 1 | 2 | 1. A computer-implemented method of processing a request for a document that is unavailable on a network comprising: processing a request for a previously accessed document from a corresponding link by: sending the request to a location on the network of a source storing the previously accessed document; receiving a response from the source including one of: an error message, and content accessed by the source based on the request; analyzing the response and determining that the previously accessed document is unavailable on the network when one of: the response includes the error message, and the response includes the accessed content and a number of different words between the accessed content and stored content of the previously accessed document from a prior access exceeds a predetermined value; and in response to the previously accessed document being unavailable on the network, generating a query and identifying a plurality of alternative documents on the network with content pertaining to content of the previously accessed document and relating to a network group of users, wherein the network group of users is associated with a subject matter, and wherein the query includes first keywords from metadata associated with the previously accessed document and second keywords pertaining to one or more interests of the network group of users in the subject matter; presenting the identified alternative documents as a result of the request for the previously accessed document when the analyzing indicates that the previously accessed document is unavailable on the network; and replacing the corresponding link, when the previously accessed document is unavailable on the network, with a link to a presented alternative document based on a degree of confidence in the presented alternative document determined from a quantity of user selections for the presented alternative document, wherein the presented alternative document is a most frequently selected alternative document of the identified alternative documents. | 1. A computer-implemented method of processing a request for a document that is unavailable on a network comprising: processing a request for a previously accessed document from a corresponding link by: sending the request to a location on the network of a source storing the previously accessed document; receiving a response from the source including one of: an error message, and content accessed by the source based on the request; analyzing the response and determining that the previously accessed document is unavailable on the network when one of: the response includes the error message, and the response includes the accessed content and a number of different words between the accessed content and stored content of the previously accessed document from a prior access exceeds a predetermined value; and in response to the previously accessed document being unavailable on the network, generating a query and identifying a plurality of alternative documents on the network with content pertaining to content of the previously accessed document and relating to a network group of users, wherein the network group of users is associated with a subject matter, and wherein the query includes first keywords from metadata associated with the previously accessed document and second keywords pertaining to one or more interests of the network group of users in the subject matter; presenting the identified alternative documents as a result of the request for the previously accessed document when the analyzing indicates that the previously accessed document is unavailable on the network; and replacing the corresponding link, when the previously accessed document is unavailable on the network, with a link to a presented alternative document based on a degree of confidence in the presented alternative document determined from a quantity of user selections for the presented alternative document, wherein the presented alternative document is a most frequently selected alternative document of the identified alternative documents. 2. The computer-implemented method of claim 1 , wherein identifying the plurality of alternative documents includes: extracting document information from the previously accessed document in response to one of a prior access of that document and entering that document on a list indicating prior accessed documents. | 0.5 |
9,852,374 | 8 | 9 | 8. The method of claim 7 , wherein: the first similarity result is based on a number of direct subsumers of the two concepts; and the second similarity result is based on (i) the number of direct subsumers of the two concepts, (ii) a common subsumer of the dissimilar semantics of the two concepts; and (iii) information content conveyed by the two concepts. | 8. The method of claim 7 , wherein: the first similarity result is based on a number of direct subsumers of the two concepts; and the second similarity result is based on (i) the number of direct subsumers of the two concepts, (ii) a common subsumer of the dissimilar semantics of the two concepts; and (iii) information content conveyed by the two concepts. 9. The method of claim 8 , wherein the similarity measure computation for the two concepts A and B is given by: sim ( A , B ) = 2 × n c ( A , B ) n t ( A , B ) + [ ( 1 - 2 × n c ( A , B ) n t ( A , B ) ) × ( 2 × I C ( R C S ( δ ( A , B ) , δ ( B , A ) ) ) I C ( δ ( A , B ) ) + I C ( δ ( B , A ) ) ) ] , where: n c (A, B) is a number of semantically equivalent concepts in S D (A) and S D (B); S D (A) is a direct subsumer set for concept A; S D (B) is a direct subsumer set for concept B; n t (A, B) is the number of direct subsumers of concepts A and B and is equal to | S D (A)|+| S D (B)|; IC is an information content function; RCS is the common subsumer of the dissimilar semantics of the two concepts; and δ(A, B) is a semantic function that characterizes different semantics between the two concepts. | 0.5 |
7,940,273 | 1 | 9 | 1. A method comprising: under control of one or more processors executing computer-executable instructions: receiving an indication of at least one command relating to text that contains at least one first glyph; determining that the at least one first glyph maps to multiple corresponding Unicode representations, the multiple corresponding Unicode representations defining a collision; resolving the collision such that the at least one first glyph maps to only a single Unicode representation of the multiple corresponding Unicode representations; converting the at least one first glyph to the single corresponding Unicode representation in response to the command; performing the command on the single Unicode representation of the at least one first glyph; creating at least one further glyph for the single Unicode representation of the at least one first glyph; and mapping the at least one further glyph element to the at least one first glyph via a glyph substitution table. | 1. A method comprising: under control of one or more processors executing computer-executable instructions: receiving an indication of at least one command relating to text that contains at least one first glyph; determining that the at least one first glyph maps to multiple corresponding Unicode representations, the multiple corresponding Unicode representations defining a collision; resolving the collision such that the at least one first glyph maps to only a single Unicode representation of the multiple corresponding Unicode representations; converting the at least one first glyph to the single corresponding Unicode representation in response to the command; performing the command on the single Unicode representation of the at least one first glyph; creating at least one further glyph for the single Unicode representation of the at least one first glyph; and mapping the at least one further glyph element to the at least one first glyph via a glyph substitution table. 9. The method of claim 1 , wherein receiving an indication of at least one command includes receiving an indication of at least one command related to editing text displayed to a user. | 0.523316 |
9,424,364 | 7 | 9 | 7. A non-transitory computer-readable medium having an integration software module stored thereon and configured for communication that when executed on a processor causes the processor to: use an integration software module to provide an integrated data connection between a webpage and a social network, the integrated data connection configured to automatically deliver data relevant to the webpage based on a portion of content of the webpage selected by a user, wherein the integration software module behaves at least in part according to a third-party custom software cartridge that modifies a behavior of the integration software module to take actions in addition to search, including at least two of changing search results font, downloading files, presenting a user interface on a target webpage, accessing a database, acquiring user input, and playing multimedia files; and display the delivered data on the webpage. | 7. A non-transitory computer-readable medium having an integration software module stored thereon and configured for communication that when executed on a processor causes the processor to: use an integration software module to provide an integrated data connection between a webpage and a social network, the integrated data connection configured to automatically deliver data relevant to the webpage based on a portion of content of the webpage selected by a user, wherein the integration software module behaves at least in part according to a third-party custom software cartridge that modifies a behavior of the integration software module to take actions in addition to search, including at least two of changing search results font, downloading files, presenting a user interface on a target webpage, accessing a database, acquiring user input, and playing multimedia files; and display the delivered data on the webpage. 9. The non-transitory computer-readable medium of claim 7 , wherein the integration software module is a browser plugin component. | 0.712389 |
8,145,621 | 13 | 16 | 13. A computer-usable storage device having computer program logic recorded thereon to cause a computing device to perform operations for generating a graphical representation of a query optimization process, the operations comprising: parsing a search space log, the log comprising an order in time in which one or more access plans were evaluated, a property for an object of one of the one or more evaluated access plans, and a best access plan selected from the one or more evaluated access plans; presenting the one or more evaluated access plans on a time axis and a cost axis of a timeline, organized on the timeline corresponding to the order in time in which the one or more evaluated access plans were evaluated; identifying the best access plan on the timeline; and displaying a graphical representation of the time axis and the cost axis. | 13. A computer-usable storage device having computer program logic recorded thereon to cause a computing device to perform operations for generating a graphical representation of a query optimization process, the operations comprising: parsing a search space log, the log comprising an order in time in which one or more access plans were evaluated, a property for an object of one of the one or more evaluated access plans, and a best access plan selected from the one or more evaluated access plans; presenting the one or more evaluated access plans on a time axis and a cost axis of a timeline, organized on the timeline corresponding to the order in time in which the one or more evaluated access plans were evaluated; identifying the best access plan on the timeline; and displaying a graphical representation of the time axis and the cost axis. 16. The computer-usable storage device of claim 13 , the operations further comprising: analyzing the graphical representation of the timeline; and refining the query optimization process. | 0.676976 |
8,538,386 | 25 | 26 | 25. A mobile wireless communications device comprising: a wireless transceiver and a controller cooperating therewith and configured to receive text messages from a wireless communications network, said controller configured to be switchable between a normal message mode and an audio message mode; a user interface device connected to said controller and configured to receive at least one audio mode filter parameter from a user; and an audio output connected to said controller; said controller configured to, when in the audio message mode, select received text messages based upon the at least one audio mode filter parameter, and output audio messages comprising speech generated from the selected text messages via said audio output; said controller configured to switch between the normal message mode and the audio message mode based upon a connection between said audio output and an audio device and an override mode setting, the override mode setting causing said controller to remain in the audio message mode. | 25. A mobile wireless communications device comprising: a wireless transceiver and a controller cooperating therewith and configured to receive text messages from a wireless communications network, said controller configured to be switchable between a normal message mode and an audio message mode; a user interface device connected to said controller and configured to receive at least one audio mode filter parameter from a user; and an audio output connected to said controller; said controller configured to, when in the audio message mode, select received text messages based upon the at least one audio mode filter parameter, and output audio messages comprising speech generated from the selected text messages via said audio output; said controller configured to switch between the normal message mode and the audio message mode based upon a connection between said audio output and an audio device and an override mode setting, the override mode setting causing said controller to remain in the audio message mode. 26. The mobile wireless communications device of claim 25 wherein the audio device comprises a wired headset, and wherein said audio output comprises a headset jack. | 0.677734 |
9,325,568 | 12 | 13 | 12. The method of claim 1 , further comprising: generating a correlation graph for the set of correlated events, the correlation graph comprising vertices and edges connecting the vertices, wherein each vertex represents a particular event and each edge represents a correlation between the events represented by the connected vertices, wherein an edge is added between two vertices if there is at least one identical context identifier associated with the two events; analysing the graph to determine at least one root vertex; and determining the at least one root event among the correlated events based on the at least one root vertex. | 12. The method of claim 1 , further comprising: generating a correlation graph for the set of correlated events, the correlation graph comprising vertices and edges connecting the vertices, wherein each vertex represents a particular event and each edge represents a correlation between the events represented by the connected vertices, wherein an edge is added between two vertices if there is at least one identical context identifier associated with the two events; analysing the graph to determine at least one root vertex; and determining the at least one root event among the correlated events based on the at least one root vertex. 13. The method of claim 12 , wherein the correlation graph has directed vertices. | 0.874613 |
9,477,658 | 9 | 12 | 9. A system for speech to speech translation, comprising: a processing element; an interface coupled to the processing element, wherein the interface is configured to receive at least one audio signal; and a memory communicatively connected to the processing element, wherein the memory contains instructions that, when executed by the processing element, configure the processing element to: identify a first concept in the received at least audio input; identify a first language based on the first concept identified for the received audio signal; identify a first plurality of concepts in the first language, wherein the first plurality of concepts is statistically proximate to the first concept and previously matched to a second plurality of concepts, wherein the second plurality of concepts is in the target language; and identify a second concept statistically proximate to the second plurality of concepts, wherein the statistical proximity is determined by use of a threshold in order to determine a match respective of the first concept and the second concept, wherein the second concept is respective of a target language. | 9. A system for speech to speech translation, comprising: a processing element; an interface coupled to the processing element, wherein the interface is configured to receive at least one audio signal; and a memory communicatively connected to the processing element, wherein the memory contains instructions that, when executed by the processing element, configure the processing element to: identify a first concept in the received at least audio input; identify a first language based on the first concept identified for the received audio signal; identify a first plurality of concepts in the first language, wherein the first plurality of concepts is statistically proximate to the first concept and previously matched to a second plurality of concepts, wherein the second plurality of concepts is in the target language; and identify a second concept statistically proximate to the second plurality of concepts, wherein the statistical proximity is determined by use of a threshold in order to determine a match respective of the first concept and the second concept, wherein the second concept is respective of a target language. 12. The system of claim 9 , wherein the received audio signal is at least one of: a digital representation of an audio signal, and a direct feed from at least one microphone device. | 0.635081 |
8,380,507 | 37 | 43 | 37. The Computer readable media for providing speech content, the computer readable media comprising computer readable instructions recorded thereon for: receiving a set of text strings for which speech content is requested; receiving a default language associated with the electronic device; identify a title text string from the received set of text strings, wherein the title text string is associated with a title text string language; identify an artist text string from the received set of text strings, wherein the artist text string is associated with an artist text string language; determine that at least two of the title text string language, album text string language, and default language are different; and select one of the title text string language, album text string language, and default language for generating speech content for the title text string and album text string. | 37. The Computer readable media for providing speech content, the computer readable media comprising computer readable instructions recorded thereon for: receiving a set of text strings for which speech content is requested; receiving a default language associated with the electronic device; identify a title text string from the received set of text strings, wherein the title text string is associated with a title text string language; identify an artist text string from the received set of text strings, wherein the artist text string is associated with an artist text string language; determine that at least two of the title text string language, album text string language, and default language are different; and select one of the title text string language, album text string language, and default language for generating speech content for the title text string and album text string. 43. The computer readable media of claim 37 , further comprising instructions for: determining that the artist text string language is not speakable in the title text string language; determining that speech content generated using the title text string language for the artist text string generates an audible output; and generating the speech content using the title text string language. | 0.5 |
9,798,975 | 1 | 2 | 1. A production rules engine comprising: a class loader configured to load a production rule ontology into a rules engine, wherein the production rule ontology provides a description and instances of a production rule, wherein the production rule comprises a condition part and an action part, wherein the condition part matches instances of the production rule to be grouped into a working memory, and wherein the action part updates the instances of the production rule in response to the instances of the production rule being grouped into the working memory; a class loader configured to load production rules into the rules engine, wherein the production rule comprises a rule and an action defined in the production rule ontology; a production instance creator configured to create instances of the production rules; a reasoner configured to: execute the production rules, locate an instance of a production rule having an inconsistency between an action to change the production rule ontology and an existing ontology, and execute the production rules after production rule inconsistencies have been fixed; a constraint engine configured to locate a solution to an inconsistent ontology; a fixer configured to update the inconsistent ontology with a located solution; and an ontology manager configured to: embed an Ontological Web Language (OWL) axiom in a single extended RETE axiom node, wherein the OWL axiom is a class expression, and wherein the single extended RETE axiom node is a stateless RETE subnode that has no local memory associated to it; embedding embed the OWL axiom into a RETE production rule engine; and define new language terms based on tight coupling between the RETE production rule engine and the OWL axiom. | 1. A production rules engine comprising: a class loader configured to load a production rule ontology into a rules engine, wherein the production rule ontology provides a description and instances of a production rule, wherein the production rule comprises a condition part and an action part, wherein the condition part matches instances of the production rule to be grouped into a working memory, and wherein the action part updates the instances of the production rule in response to the instances of the production rule being grouped into the working memory; a class loader configured to load production rules into the rules engine, wherein the production rule comprises a rule and an action defined in the production rule ontology; a production instance creator configured to create instances of the production rules; a reasoner configured to: execute the production rules, locate an instance of a production rule having an inconsistency between an action to change the production rule ontology and an existing ontology, and execute the production rules after production rule inconsistencies have been fixed; a constraint engine configured to locate a solution to an inconsistent ontology; a fixer configured to update the inconsistent ontology with a located solution; and an ontology manager configured to: embed an Ontological Web Language (OWL) axiom in a single extended RETE axiom node, wherein the OWL axiom is a class expression, and wherein the single extended RETE axiom node is a stateless RETE subnode that has no local memory associated to it; embedding embed the OWL axiom into a RETE production rule engine; and define new language terms based on tight coupling between the RETE production rule engine and the OWL axiom. 2. The production rules engine according to claim 1 , wherein the constraint engine generates more than one logical solution to the inconsistent ontology, and wherein the constraint engine chooses a logical solution to use when generating said more than one logical solution to the inconsistent ontology. | 0.5 |
8,296,354 | 24 | 25 | 24. A computer-implemented method for converting typed application data into a Simple Object Access Protocol (SOAP) format, the method comprising: an act of storing by a first computer system a typed data object, wherein the typed data object defines a method associated with a first portion of a distributed application, wherein the typed data object comprises: typed application data comprising at least one typed object parameter for invoking the method, wherein the at least one typed object parameter is in a format compatible with the first portion of the distributed application and with a second portion of the distributed application on a second computer system; and at least one message contract attribute of a message contract model, wherein the at least one message contract attribute annotates the typed data object such that the at least one message contract attribute is adjacent to the at least one typed object parameter, wherein the at least one message contract attribute defines a mapping between the at least one typed object parameter and a corresponding SOAP element, and wherein the at least one message contract attribute specifies a location within a SOAP envelope for inserting the corresponding SOAP element; an act of accessing the typed data object; an act of mapping the at least one typed object parameter to the corresponding SOAP element by referring to the at least one message contract attribute that annotates the accessed typed data object; an act of inserting the corresponding SOAP element into the location within the SOAP envelope in accordance with the at least one message contract attribute; and an act of transmitting the SOAP envelope to the second portion of the distributed application on the second computer system. | 24. A computer-implemented method for converting typed application data into a Simple Object Access Protocol (SOAP) format, the method comprising: an act of storing by a first computer system a typed data object, wherein the typed data object defines a method associated with a first portion of a distributed application, wherein the typed data object comprises: typed application data comprising at least one typed object parameter for invoking the method, wherein the at least one typed object parameter is in a format compatible with the first portion of the distributed application and with a second portion of the distributed application on a second computer system; and at least one message contract attribute of a message contract model, wherein the at least one message contract attribute annotates the typed data object such that the at least one message contract attribute is adjacent to the at least one typed object parameter, wherein the at least one message contract attribute defines a mapping between the at least one typed object parameter and a corresponding SOAP element, and wherein the at least one message contract attribute specifies a location within a SOAP envelope for inserting the corresponding SOAP element; an act of accessing the typed data object; an act of mapping the at least one typed object parameter to the corresponding SOAP element by referring to the at least one message contract attribute that annotates the accessed typed data object; an act of inserting the corresponding SOAP element into the location within the SOAP envelope in accordance with the at least one message contract attribute; and an act of transmitting the SOAP envelope to the second portion of the distributed application on the second computer system. 25. The computer-implemented method as recited in claim 24 , wherein the act of accessing the typed data object comprises accessing a public class that represents parameters to a Common Language Runtime method. | 0.768212 |
8,615,419 | 1 | 6 | 1. A method for calculating an interaction churn score in an organization with which the customer has an interaction, the method comprising: receiving a plurality of categories, each category characterized by an at least one parameter of a voiced expression; capturing or logging the interaction using a capturing or logging component; based on a determined relation of data of the interaction to churning, categorizing the interaction into at least one churning category out of a total number of categories according to an extent to which the data of the interaction belongs to the least one churning category, and determining a number of churning categories into which the interaction is categorized; and determining an interaction churn score for the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is categorized into and inversely related to the total number of churning categories based on a formula as:
A *(maximal score for a churning category)+ B *((the number of churning categories into which the interaction is categorized)/(the number of churning categories)*100), wherein A and B are coefficients that satisfy a condition of A+B=1; and wherein capturing or logging the interaction and determining an interaction churn score for the interaction are carried out using a computing platform provisioned with a memory device. | 1. A method for calculating an interaction churn score in an organization with which the customer has an interaction, the method comprising: receiving a plurality of categories, each category characterized by an at least one parameter of a voiced expression; capturing or logging the interaction using a capturing or logging component; based on a determined relation of data of the interaction to churning, categorizing the interaction into at least one churning category out of a total number of categories according to an extent to which the data of the interaction belongs to the least one churning category, and determining a number of churning categories into which the interaction is categorized; and determining an interaction churn score for the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is categorized into and inversely related to the total number of churning categories based on a formula as:
A *(maximal score for a churning category)+ B *((the number of churning categories into which the interaction is categorized)/(the number of churning categories)*100), wherein A and B are coefficients that satisfy a condition of A+B=1; and wherein capturing or logging the interaction and determining an interaction churn score for the interaction are carried out using a computing platform provisioned with a memory device. 6. The method of claim 1 wherein determining the interaction churn score comprises the steps of: categorizing the interaction into at least one category, by determining at least one category-interaction indication associating the interaction with the at least one category; and combining the at least one category-interaction indication into the interaction churn score. | 0.5 |
9,031,947 | 11 | 19 | 11. A system comprising at least one computer processor and at least one non-transitory computer storage device storing computer-executable instructions to implement a method for identifying elements of a system, the system comprising; a system element store comprising machine-readable representations of system models comprising system elements classified as a whole element of a whole-part relationship, an entity element of an entity-relation-entity relationship, a pair of entity elements of an entity-relation-entity relationship, or a relation element of an entity-relation-entity relationship; a query formulator configured to: electronically receive a graphical user interface input identifying a system model as a selected electronic representation of the system; extract corresponding system elements of the identified system model from the system element store in response to the graphical user interface input; automatically formulate a query from the extracted system elements, wherein the extracted system elements represent a set of system objectives; and a knowledge search engine configured to use the query to: search one or more merelogical and functional relationship databases containing one or more general document repositories that are semantically indexed and contain non-hierarchical database structures and additional one or more knowledge bases selected from the group consisting of: one or more locally accessible knowledge bases, one or more knowledge bases containing corporate knowledge, and one or more publicly accessible knowledge bases; retrieve component elements useful to form the extracted system elements and identify functional interactions between the component elements, wherein the component elements represent parts of entity-relationship-entity relationships represented in the identified system model; and output the retrieved component elements and identified functional interactions as search results in association with the extracted system elements, wherein the search results are represented as user-selectable options representing design alternatives to satisfy the set of system objectives of the system. | 11. A system comprising at least one computer processor and at least one non-transitory computer storage device storing computer-executable instructions to implement a method for identifying elements of a system, the system comprising; a system element store comprising machine-readable representations of system models comprising system elements classified as a whole element of a whole-part relationship, an entity element of an entity-relation-entity relationship, a pair of entity elements of an entity-relation-entity relationship, or a relation element of an entity-relation-entity relationship; a query formulator configured to: electronically receive a graphical user interface input identifying a system model as a selected electronic representation of the system; extract corresponding system elements of the identified system model from the system element store in response to the graphical user interface input; automatically formulate a query from the extracted system elements, wherein the extracted system elements represent a set of system objectives; and a knowledge search engine configured to use the query to: search one or more merelogical and functional relationship databases containing one or more general document repositories that are semantically indexed and contain non-hierarchical database structures and additional one or more knowledge bases selected from the group consisting of: one or more locally accessible knowledge bases, one or more knowledge bases containing corporate knowledge, and one or more publicly accessible knowledge bases; retrieve component elements useful to form the extracted system elements and identify functional interactions between the component elements, wherein the component elements represent parts of entity-relationship-entity relationships represented in the identified system model; and output the retrieved component elements and identified functional interactions as search results in association with the extracted system elements, wherein the search results are represented as user-selectable options representing design alternatives to satisfy the set of system objectives of the system. 19. The system according to claim 11 , further comprising: one or more computer processing elements; one or more display devices; one or more user input devices; and communication elements for communicating with the one or more merelogical and functional relationship databases. | 0.5 |
10,140,977 | 24 | 26 | 24. The computer-readable storage media of claim 23 , wherein determining, based on the training conversational turns in the first set of training data, that the natural language understanding engine is likely to generate inaccurate annotations of other conversational turns that are similar to the first input conversational turn comprises: identifying training conversational turns in the training data that are similar to the first input conversational turn according to a similarity measure. | 24. The computer-readable storage media of claim 23 , wherein determining, based on the training conversational turns in the first set of training data, that the natural language understanding engine is likely to generate inaccurate annotations of other conversational turns that are similar to the first input conversational turn comprises: identifying training conversational turns in the training data that are similar to the first input conversational turn according to a similarity measure. 26. The computer-readable storage media of claim 24 , wherein determining, based on the training conversational turns in the first set of training data, that the natural language understanding engine is likely to generate inaccurate annotations of other conversational turns that are similar to the first input conversational turn comprises: determining that the natural language understanding unit performs poorly on training conversational turns that are similar to the first input conversational turn according to the similarity measure. | 0.5 |
7,613,731 | 39 | 60 | 39. A method for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, comprising the steps of: assigning an emphasis value to each word in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word; processing the first tagged file in a computer system, including deriving emphasis values for recognizability and comprehensibility and pairing selected words as a cognitive cluster to be treated as one word, to generate a second tagged file of derived emphasis values; processing the second tagged file in the computer system, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; and presenting the electronic document to the viewer on an electronic display device or printer. | 39. A method for presenting an electronic document to a viewer to facilitate comprehension and control display and speed of delivery, comprising the steps of: assigning an emphasis value to each word in the electronic document using a knowledge database thereby generating a first tagged file of assigned emphasis values for each word; processing the first tagged file in a computer system, including deriving emphasis values for recognizability and comprehensibility and pairing selected words as a cognitive cluster to be treated as one word, to generate a second tagged file of derived emphasis values; processing the second tagged file in the computer system, including facilitating editing of properties of selected words and cognitive clusters in the electronic document, to generate a property deliverable file that dynamically controls the presentation of the electronic document to the viewer; and presenting the electronic document to the viewer on an electronic display device or printer. 60. The method for presenting an electronic document of claim 39 further comprising the step of changing an opacity of images in an image file associated with the electronic document. | 0.672043 |
9,965,502 | 15 | 20 | 15. A computer-readable storage medium storing a plurality of instructions for controlling a processor in an apparatus which manages a plurality of objects, each object including content data and metadata, the plurality of instructions comprising: generating an index for the objects, the index including a plurality of content properties including a first content property and a second content property, the first content property having a first name of the first content property and first expression information for extracting values from fields in the metadata of one or more of the objects, and the second content property having the first name and second expression information for extracting values from the fields in the metadata of one or more of the objects so that at least a portion of the index is deduplicated such that values for multiple relevant expressions are able to be returned for a single search request; and searching, upon receipt of a search request including the first name and a first value, the index for one or more objects that have at least one of: the first value in at least one of the fields identified based on the first expression information in the metadata, or the first value in at least one of the fields identified based on the second expression information in the metadata; and based on finding at least one match, returning an indication of at least one of the objects determined to include the first value in at least one of the fields identified in the metadata based on the first expression information or in at least one of the fields identified in the metadata based on the second expression information. | 15. A computer-readable storage medium storing a plurality of instructions for controlling a processor in an apparatus which manages a plurality of objects, each object including content data and metadata, the plurality of instructions comprising: generating an index for the objects, the index including a plurality of content properties including a first content property and a second content property, the first content property having a first name of the first content property and first expression information for extracting values from fields in the metadata of one or more of the objects, and the second content property having the first name and second expression information for extracting values from the fields in the metadata of one or more of the objects so that at least a portion of the index is deduplicated such that values for multiple relevant expressions are able to be returned for a single search request; and searching, upon receipt of a search request including the first name and a first value, the index for one or more objects that have at least one of: the first value in at least one of the fields identified based on the first expression information in the metadata, or the first value in at least one of the fields identified based on the second expression information in the metadata; and based on finding at least one match, returning an indication of at least one of the objects determined to include the first value in at least one of the fields identified in the metadata based on the first expression information or in at least one of the fields identified in the metadata based on the second expression information. 20. A computer-readable storage medium according to claim 15 , wherein the plurality of instructions further comprise managing a first access control list (ACL) which is used to control restriction of access to the object and a second ACL which is used to control restriction of access to the plurality of annotations. | 0.5 |
9,703,771 | 9 | 10 | 9. The article of manufacture of claim 8 , wherein the data defining computer operating context includes environmental data from a sensor. | 9. The article of manufacture of claim 8 , wherein the data defining computer operating context includes environmental data from a sensor. 10. The article of manufacture of claim 9 , wherein the environmental data includes at least ambient light. | 0.572 |
9,753,974 | 21 | 30 | 21. A processor readable non-transitive storage media that includes instructions wherein execution of the instructions by a processor device enables actions, comprising: providing a datastore comprising a plurality of time-stamped, searchable events, each event having a portion of raw data and a timestamp extracted from the portion of raw data, the portion of raw data produced by at least one hardware system; providing a data structure that contains a plurality of field names, each field name among the plurality of field names associated with a set of pointers to time-stamped, searchable events having a value for a field referred to by the field name; receiving an incoming search query that references one or more field names among the plurality of field names contained in the data structure and a time range criteria; and in response to the incoming search query, servicing the incoming search query by: (i) executing the incoming search query across the data structure, wherein one or more values from the data structure are used to create a search result; and (ii) supplementing the search result by executing a search comprising the time range criteria of the incoming search query across the time-stamped searchable events, independent of the data structure. | 21. A processor readable non-transitive storage media that includes instructions wherein execution of the instructions by a processor device enables actions, comprising: providing a datastore comprising a plurality of time-stamped, searchable events, each event having a portion of raw data and a timestamp extracted from the portion of raw data, the portion of raw data produced by at least one hardware system; providing a data structure that contains a plurality of field names, each field name among the plurality of field names associated with a set of pointers to time-stamped, searchable events having a value for a field referred to by the field name; receiving an incoming search query that references one or more field names among the plurality of field names contained in the data structure and a time range criteria; and in response to the incoming search query, servicing the incoming search query by: (i) executing the incoming search query across the data structure, wherein one or more values from the data structure are used to create a search result; and (ii) supplementing the search result by executing a search comprising the time range criteria of the incoming search query across the time-stamped searchable events, independent of the data structure. 30. The media of claim 21 , further comprising: while creating the data structure, searching the time-stamped searchable events for a value for a field using an extraction rule. | 0.74858 |
9,818,138 | 7 | 8 | 7. A system to provide controlled access to an electronic signature document for a plurality of users, comprising: one or more memory devices; one or more processors communicatively coupled to the one or more memory devices; and an electronic signature service (ESS) module, executable via the one or more processors using instructions stored by the one or more memory devices, the executable module when executed by the one or more processors, causes the one or more processors to perform operations comprising: identifying one or more documents associated with a document owner, the one or more documents including a document that comprise content including terms for an agreement between the plurality of users, the plurality of users including at least a signing user, the document being an individual file; receiving a request from a client device associated with the document owner via an application programming interface (API) over a network to pre-tag the document to indicate a location for signature and a signing role for the signing user; in response to receiving an instruction to link the document to a transaction room for signing, creating a non-editable copy of the document for signing on a storage device accessible to the transaction room for the agreement, the non-editable copy being an additional individual file in a non-editable format, the transaction room implemented as a web service accessible by the plurality of users remotely over the network, the non-editable copy of the document for signing viewable by the plurality of users remotely through a graphical user interface of the transaction room, the content of the non-editable copy of the document for signing not being editable by the plurality of users remotely through the graphical user interface of the transaction room; associating the signing user with the signing role; in response to receiving an instruction to transmit the document for signing to at least the signing user, tagging the non-editable copy of the document for signing with one or more tags based on the pre-tag to display data identifying the location for signature for the signing user to sign; and in response to receiving, from the signing user, input information for the document for signing, overlaying the input information on the non-editable copy of the document for signing without altering the terms for the agreement in the non-editable copy of the document for signing. | 7. A system to provide controlled access to an electronic signature document for a plurality of users, comprising: one or more memory devices; one or more processors communicatively coupled to the one or more memory devices; and an electronic signature service (ESS) module, executable via the one or more processors using instructions stored by the one or more memory devices, the executable module when executed by the one or more processors, causes the one or more processors to perform operations comprising: identifying one or more documents associated with a document owner, the one or more documents including a document that comprise content including terms for an agreement between the plurality of users, the plurality of users including at least a signing user, the document being an individual file; receiving a request from a client device associated with the document owner via an application programming interface (API) over a network to pre-tag the document to indicate a location for signature and a signing role for the signing user; in response to receiving an instruction to link the document to a transaction room for signing, creating a non-editable copy of the document for signing on a storage device accessible to the transaction room for the agreement, the non-editable copy being an additional individual file in a non-editable format, the transaction room implemented as a web service accessible by the plurality of users remotely over the network, the non-editable copy of the document for signing viewable by the plurality of users remotely through a graphical user interface of the transaction room, the content of the non-editable copy of the document for signing not being editable by the plurality of users remotely through the graphical user interface of the transaction room; associating the signing user with the signing role; in response to receiving an instruction to transmit the document for signing to at least the signing user, tagging the non-editable copy of the document for signing with one or more tags based on the pre-tag to display data identifying the location for signature for the signing user to sign; and in response to receiving, from the signing user, input information for the document for signing, overlaying the input information on the non-editable copy of the document for signing without altering the terms for the agreement in the non-editable copy of the document for signing. 8. The system of claim 7 , wherein the operations further comprise: determining whether the non-editable copy of the document for signing includes at least one pre-tagged signing role that is unassociated with any signing user; and generating a report identifying the non-editable copy of the document for signing based on the determination of an unassociated pre-tagged signing role. | 0.71471 |
8,909,926 | 1 | 14 | 1. A security analysis tool, comprising: a processor; and a memory communicatively coupled to the processor and having stored thereon computer-executable components configured to implement the security analysis tool, the computer-executable components comprising: a learning component that monitors communication of data associated with an I/O table of an industrial controller of an automation system during a training period and generates a learned pattern of communication, wherein the I/O table stores input data received by the industrial controller from a controlled device via an I/O device and output data provided by the industrial controller to the controlled device via the I/O device; and an analyzer component that monitors data traffic subsequent to the training period and generates one or more security outputs in response to a determination that a current pattern of the data traffic deviates from the learned pattern in excess of an acceptable deviation, the one or more security outputs comprising at least one output that alters the data traffic between the industrial controller and the I/O device. | 1. A security analysis tool, comprising: a processor; and a memory communicatively coupled to the processor and having stored thereon computer-executable components configured to implement the security analysis tool, the computer-executable components comprising: a learning component that monitors communication of data associated with an I/O table of an industrial controller of an automation system during a training period and generates a learned pattern of communication, wherein the I/O table stores input data received by the industrial controller from a controlled device via an I/O device and output data provided by the industrial controller to the controlled device via the I/O device; and an analyzer component that monitors data traffic subsequent to the training period and generates one or more security outputs in response to a determination that a current pattern of the data traffic deviates from the learned pattern in excess of an acceptable deviation, the one or more security outputs comprising at least one output that alters the data traffic between the industrial controller and the I/O device. 14. The security analysis tool of claim 1 , wherein the one or more security outputs alter the data traffic between the industrial controller and the I/O device to restore the learned pattern. | 0.69906 |
7,519,616 | 16 | 17 | 16. The method of claim 14 wherein the arranging is performed through a time container that defines the second set of one or more elements. | 16. The method of claim 14 wherein the arranging is performed through a time container that defines the second set of one or more elements. 17. The method of claim 16 wherein the time container is defined by SMIL conventions. | 0.752907 |
8,095,481 | 2 | 3 | 2. The method of claim 1 wherein said classification system comprises of a rules-based classification system and/or a semantic web-based classification system. | 2. The method of claim 1 wherein said classification system comprises of a rules-based classification system and/or a semantic web-based classification system. 3. The method of claim 2 wherein said predefined set of characteristics in said rules-based classification system comprises one or more pre-conditions for a plurality of classification rules. | 0.524876 |
9,063,974 | 1 | 11 | 1. A machine-implemented method for processing a query, comprising: determining, by a microprocessor, that execution of the query involves a scan operation; in response to determining that execution of the query involves a scan operation, generating, by the microprocessor, a scan operation command that includes, as parameters of the scan operation command, address data that is used to identify input data to be read by a coprocessor and one or more values that are used to compare against the input data; wherein the microprocessor is separate from the coprocessor; causing, by the microprocessor, the scan operation command to be stored in memory; processing, by the coprocessor, the scan operation command by: reading the scan operation command from the memory; causing the input data to be read from a location that is indicated by the address data; performing a comparison between the input data with the one or more values; generating a result data based on the comparison; causing the result data to be stored. | 1. A machine-implemented method for processing a query, comprising: determining, by a microprocessor, that execution of the query involves a scan operation; in response to determining that execution of the query involves a scan operation, generating, by the microprocessor, a scan operation command that includes, as parameters of the scan operation command, address data that is used to identify input data to be read by a coprocessor and one or more values that are used to compare against the input data; wherein the microprocessor is separate from the coprocessor; causing, by the microprocessor, the scan operation command to be stored in memory; processing, by the coprocessor, the scan operation command by: reading the scan operation command from the memory; causing the input data to be read from a location that is indicated by the address data; performing a comparison between the input data with the one or more values; generating a result data based on the comparison; causing the result data to be stored. 11. The method of claim 1 , wherein: the address data included in the scan operation command includes one or more virtual addresses; the method further comprising causing the one or more virtual addresses to be replaced with one or more physical addresses that the coprocessor uses to read the input data. | 0.757166 |
8,421,823 | 1 | 2 | 1. Audio video apparatus, comprising: video display; processor controlling the display to present video; computer readable storage medium accessible to the processor and bearing instructions executable by the processor to configure the processor to: present on the display an emotion presentation user interface (UI), the UI including a first selector element selectable to cause an actual image of a viewer of the display as captured by a camera to be overlaid onto video, the UI including a second selector element selectable by a user to cause an emoticon to be overlaid onto video, the emoticon being established by the processor responsive to selection of the second selector element to match closely as possible the actual image of the viewer as captured by the camera and processed by the processor executing a recognition engine; receive a viewer selection of the first selector element or the second selector element; responsive to a viewer selection of the first selector element, generate an actual image of a viewer of the display and overlay the image on the video; and responsive to a viewer selection of the second selector element, correlate the image to an emoticon and overlay the emoticon on the video. | 1. Audio video apparatus, comprising: video display; processor controlling the display to present video; computer readable storage medium accessible to the processor and bearing instructions executable by the processor to configure the processor to: present on the display an emotion presentation user interface (UI), the UI including a first selector element selectable to cause an actual image of a viewer of the display as captured by a camera to be overlaid onto video, the UI including a second selector element selectable by a user to cause an emoticon to be overlaid onto video, the emoticon being established by the processor responsive to selection of the second selector element to match closely as possible the actual image of the viewer as captured by the camera and processed by the processor executing a recognition engine; receive a viewer selection of the first selector element or the second selector element; responsive to a viewer selection of the first selector element, generate an actual image of a viewer of the display and overlay the image on the video; and responsive to a viewer selection of the second selector element, correlate the image to an emoticon and overlay the emoticon on the video. 2. The apparatus of claim 1 , wherein the instructions executable by the processor further configure the processor to: present, along with the image or emoticon, audio generated by a viewer and captured by a microphone communicating with the processor. | 0.671875 |
7,730,395 | 29 | 30 | 29. The system of claim 26 comprising: means for building a tree representation of said one or more instances of said electronic document; and means for determining a document scheme from said tree representation of said original electronic document and a tree structure of alternate versions of said original electronic document. | 29. The system of claim 26 comprising: means for building a tree representation of said one or more instances of said electronic document; and means for determining a document scheme from said tree representation of said original electronic document and a tree structure of alternate versions of said original electronic document. 30. The system of claim 29 further comprising: means for determining if a more recent version of said one or more instances of said electronic document has a document scheme similar to said determined document scheme; means for creating said virtual page from said retrieved one or more virtual tag objects and said most recent version of said one or more instances of said electronic document, if said more recent version of said original electronic document has a document scheme similar to said determined document scheme; or means for revising said virtual tags and said one or more transformation rules, if said more recent version of said one or more instances of said electronic document does not have a document scheme similar to said determined document scheme; and means for creating said virtual page from said most recent version of said original electronic document with said revised one or more virtual tags and said revised one or more transformation rules. | 0.5 |
9,384,282 | 1 | 4 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue of the plurality of fact check queues contains the segments to be fact checked in real-time, and a second fact check queue of the plurality of fact check queues contains the segments to be fact checked in non-real-time; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and then searching the source information located on a slower access time hardware device; wherein utilizing pattern matching begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information; b. automatically parsing the target information into segments and prioritizing the segments so a highest priority segment is fact checked first, wherein priority is based on the relatedness of the segment to a current topic being discussed and when the segment was presented, wherein if the segment is not fact checked before a timeout threshold, then the segment is removed from a fact check queue, wherein a plurality of fact check queues are implemented, wherein a first fact check queue of the plurality of fact check queues contains the segments to be fact checked in real-time, and a second fact check queue of the plurality of fact check queues contains the segments to be fact checked in non-real-time; c. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the exact match search result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; and d. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information, wherein searching for the exact match begins searching the source information located on a fastest access time hardware device and then searching the source information located on a slower access time hardware device; wherein utilizing pattern matching begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device; and wherein the natural language search begins searching the source information located on the fastest access time hardware device and then searching the source information located on the slower access time hardware device. 4. The method of claim 1 wherein searching for the exact match begins searching the source information classified by a plurality of keywords found in the target information, then using the source information classified by a single keyword found in the target information, and then using the source information classified by keywords related to the keywords found in the target information; wherein utilizing pattern matching begins utilizing the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information; and wherein the natural language search begins searching the source information classified by the plurality of keywords found in the target information, then using the source information classified by the single keyword found in the target information, and then using the source information classified by the keywords related to the keywords found in the target information. | 0.5 |
9,990,641 | 9 | 13 | 9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs. | 9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs. 13. The advertising server network of claim 9 , wherein aggregating the training model dataset includes aggregating a data structure including at least one of, a user cookie, a timestamp, a targeting category, a position, a property. | 0.605085 |
5,473,741 | 3 | 4 | 3. The method as recited in claim 1, wherein said test data file comprises at least one of: first graphical imaged data, first scanned image data, first computer generated image data, first contone image data, and first vector image data, and wherein said actual page description language file comprises at least one of: second graphical imaged data, second scanned image data, second computer generated image data, second contone image data, and second vector image data. | 3. The method as recited in claim 1, wherein said test data file comprises at least one of: first graphical imaged data, first scanned image data, first computer generated image data, first contone image data, and first vector image data, and wherein said actual page description language file comprises at least one of: second graphical imaged data, second scanned image data, second computer generated image data, second contone image data, and second vector image data. 4. The method as recited in claim 3, wherein said test data file and said page description language file each comprise an encapsulated PostScript file. | 0.5 |
8,589,392 | 7 | 8 | 7. The computer-implemented method of claim 6 , wherein the user interface enabling the user to define a plurality of search scopes includes devices for defining each search scope as including documents uploaded by the user, including documents available for searching by all users of the online document repository, and including all documents made available to the user for searching. | 7. The computer-implemented method of claim 6 , wherein the user interface enabling the user to define a plurality of search scopes includes devices for defining each search scope as including documents uploaded by the user, including documents available for searching by all users of the online document repository, and including all documents made available to the user for searching. 8. The computer-implemented method of claim 7 , wherein the ranking devices may be activated repetitively to specify a desired ranking of search results within each associated search scope. | 0.5 |
9,275,636 | 1 | 6 | 1. A computer-implemented method for estimating the accuracy of a transcription of a voice recording, comprising: transcribing the voice recording into the transcription of the voice recording; receiving the transcription of the voice recording; providing a customer specific dictionary; providing a dictionary of common language words; determining a number of inaccurate words in the transcription; determining a number of accurate words in the transcription; determining a total number of words in the transcription; calculating an accuracy number by dividing the number of accurate words by the total number of words; assigning a greater weight to at least one word exceeding a predefined number of characters as compared to at least one other word below the predetermined number of characters; retrieving, from a data structure, a set of axioms associated with at least one of the words in the transcription, wherein the set of axioms comprises a computer-parsable definition of a relationship of data to the at least one of the words; and assigning a confidence level to each axiom of the set of axioms based on an output of a Gaussian function applied to a result of the dividing and the assigning of weight. | 1. A computer-implemented method for estimating the accuracy of a transcription of a voice recording, comprising: transcribing the voice recording into the transcription of the voice recording; receiving the transcription of the voice recording; providing a customer specific dictionary; providing a dictionary of common language words; determining a number of inaccurate words in the transcription; determining a number of accurate words in the transcription; determining a total number of words in the transcription; calculating an accuracy number by dividing the number of accurate words by the total number of words; assigning a greater weight to at least one word exceeding a predefined number of characters as compared to at least one other word below the predetermined number of characters; retrieving, from a data structure, a set of axioms associated with at least one of the words in the transcription, wherein the set of axioms comprises a computer-parsable definition of a relationship of data to the at least one of the words; and assigning a confidence level to each axiom of the set of axioms based on an output of a Gaussian function applied to a result of the dividing and the assigning of weight. 6. The computer-implemented method of claim 1 , further comprising determining the length of each word in the transcription. | 0.748988 |
9,264,824 | 1 | 13 | 1. A method comprising: providing a graphical user interface in a user field of vision for a user to identify and select a speaker of interest from a plurality of speakers; recording a plurality of lip movement patterns of the speaker of interest; generating voice activity detection data from the plurality of lip movement patterns; recording voice audio data; and generating noise-reduced voice audio data, wherein generating the noise-reduced voice audio data uses the voice activity detection data to isolate voice audio within the recorded voice audio data corresponding to the speaker of interest. | 1. A method comprising: providing a graphical user interface in a user field of vision for a user to identify and select a speaker of interest from a plurality of speakers; recording a plurality of lip movement patterns of the speaker of interest; generating voice activity detection data from the plurality of lip movement patterns; recording voice audio data; and generating noise-reduced voice audio data, wherein generating the noise-reduced voice audio data uses the voice activity detection data to isolate voice audio within the recorded voice audio data corresponding to the speaker of interest. 13. The method of claim 1 , wherein providing a graphical user interface includes providing a gesture sensing input. | 0.726415 |
7,584,192 | 1 | 5 | 1. A computer implemented method for processing data in an electronic marketplace, the method comprising: receiving documents sent through the electronic marketplace; extracting data from the documents, wherein the extracted data relates to a predetermined statistical category of transactions conducted through the electronic marketplace and the extracted data for each document includes information identifying a document type; storing the extracted data for each document; aggregating the stored data according to the predetermined statistical category, wherein aggregating the stored data includes aggregating the stored data by document type to identify a quantity of documents for the predetermined statistical category; receiving a query for a statistical category of data; and presenting information from the appreciated data in response to the received query, wherein the presented information includes a number of documents sent through the electronic marketplace by an entity, a time period, and a document type associated with the documents. | 1. A computer implemented method for processing data in an electronic marketplace, the method comprising: receiving documents sent through the electronic marketplace; extracting data from the documents, wherein the extracted data relates to a predetermined statistical category of transactions conducted through the electronic marketplace and the extracted data for each document includes information identifying a document type; storing the extracted data for each document; aggregating the stored data according to the predetermined statistical category, wherein aggregating the stored data includes aggregating the stored data by document type to identify a quantity of documents for the predetermined statistical category; receiving a query for a statistical category of data; and presenting information from the appreciated data in response to the received query, wherein the presented information includes a number of documents sent through the electronic marketplace by an entity, a time period, and a document type associated with the documents. 5. The method of claim 1 wherein storing the extracted data for each document comprises: identifying a transaction with which each document is associated; and linking data from documents that are associated with the same transaction. | 0.666189 |
10,042,923 | 5 | 6 | 5. The method of claim 1 , further comprising: identifying a set of synonymous topics within the set of topics; and merging the synonymous topics under a representative topic. | 5. The method of claim 1 , further comprising: identifying a set of synonymous topics within the set of topics; and merging the synonymous topics under a representative topic. 6. The method of claim 5 , wherein identifying the set of synonymous topics within the set of topics comprises: obtaining a first set of attributes associated with a first topic in the set of topics and a second set of attributes associated with a second topic in the set of topics; determining a similarity between the first and second set of attributes; and identifying the first and second topics as synonymous when the similarity exceeds a threshold. | 0.5 |
9,613,621 | 10 | 16 | 10. An electronic apparatus, comprising: an input unit, receiving a speech signal; a storage unit, storing a plurality of program code segments; and a processing unit, coupled to the input unit and the storage unit, the processing unit executing a plurality of commands through the program code segments, and the commands comprising: obtaining a phonetic transcription sequence of the speech signal according to an acoustic model; obtaining a plurality of syllable sequences and a plurality of corresponding phonetic spelling matching probabilities according to the phonetic transcription sequence and a syllable acoustic lexicon; obtaining an intonation information corresponding to each of the syllable sequences according to a tone of the phonetic transcription sequence; obtaining a plurality of phonetic spelling sequences and a plurality of phonetic spelling sequence probabilities, from the language model, according to each phonetic spelling of phonetic spelling sequences and the intonation information; obtaining, from the language model, a plurality of text sequences corresponding to the phonetic transcription sequence, and a plurality of spelling sequence probabilities; generating a plurality of associated probabilities by multiplying each of the phonetic spelling matching probabilities and each of the spelling sequence probabilities; and selecting the text sequence corresponding to a largest one among the associated probabilities to be used as a recognition result of the speech signal, wherein different intonation information in the language model is divided into different semantemes, and the semantemes are corresponding to different phonetic spelling sequences. | 10. An electronic apparatus, comprising: an input unit, receiving a speech signal; a storage unit, storing a plurality of program code segments; and a processing unit, coupled to the input unit and the storage unit, the processing unit executing a plurality of commands through the program code segments, and the commands comprising: obtaining a phonetic transcription sequence of the speech signal according to an acoustic model; obtaining a plurality of syllable sequences and a plurality of corresponding phonetic spelling matching probabilities according to the phonetic transcription sequence and a syllable acoustic lexicon; obtaining an intonation information corresponding to each of the syllable sequences according to a tone of the phonetic transcription sequence; obtaining a plurality of phonetic spelling sequences and a plurality of phonetic spelling sequence probabilities, from the language model, according to each phonetic spelling of phonetic spelling sequences and the intonation information; obtaining, from the language model, a plurality of text sequences corresponding to the phonetic transcription sequence, and a plurality of spelling sequence probabilities; generating a plurality of associated probabilities by multiplying each of the phonetic spelling matching probabilities and each of the spelling sequence probabilities; and selecting the text sequence corresponding to a largest one among the associated probabilities to be used as a recognition result of the speech signal, wherein different intonation information in the language model is divided into different semantemes, and the semantemes are corresponding to different phonetic spelling sequences. 16. The electronic apparatus of claim 10 , wherein the commands further comprise: obtaining the language model through training with a plurality of corpus data based on different languages, dialects or different pronunciation habits. | 0.818818 |
8,660,372 | 1 | 3 | 1. An apparatus, comprising: a processor; and a storage device having instructions stored thereon that are executable by the processor to cause the apparatus to perform operations including: predicting one or more distortion categories from a plurality of distortion categories as having been previously applied to a first one or more image frames, wherein the predicting is based on a comparison of a plurality of image feature scores for the first one or more image frames with a plurality of image feature score ranges that correspond to one or more known distortion categories, wherein the plurality of image feature scores for the first one or more image frames are derived from a natural scene statistics model; and determining a quality of the first one or more image frames based on the predicted one or more distortion categories, wherein the determining is based on a plurality of human-measured quality scores for a plurality of second one or more image frames, wherein each of the plurality of second one or more image frames are classified as being in at least one of the predicted one or more distortion categories, and wherein the determining includes a comparison of one or more the plurality of image feature scores for the first one or more image frames with other feature scores for the plurality of second one or more image frames. | 1. An apparatus, comprising: a processor; and a storage device having instructions stored thereon that are executable by the processor to cause the apparatus to perform operations including: predicting one or more distortion categories from a plurality of distortion categories as having been previously applied to a first one or more image frames, wherein the predicting is based on a comparison of a plurality of image feature scores for the first one or more image frames with a plurality of image feature score ranges that correspond to one or more known distortion categories, wherein the plurality of image feature scores for the first one or more image frames are derived from a natural scene statistics model; and determining a quality of the first one or more image frames based on the predicted one or more distortion categories, wherein the determining is based on a plurality of human-measured quality scores for a plurality of second one or more image frames, wherein each of the plurality of second one or more image frames are classified as being in at least one of the predicted one or more distortion categories, and wherein the determining includes a comparison of one or more the plurality of image feature scores for the first one or more image frames with other feature scores for the plurality of second one or more image frames. 3. The apparatus of claim 1 , wherein reference image frames for the first one or more image frames are not available to the apparatus in performing the predicting identifying and the determining. | 0.623077 |
4,592,086 | 2 | 19 | 2. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector comprising a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern comprising a feature vector in the same format as said input pattern for each of a plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th word at a time point n at every time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern V from the first word to end word V for each time point to end point M; an asymptotic calculating means to calculate a similarity measure D(l, v, n) given by the cumulative sum of said distances on the l-th digit at said time points n and a path information F(l, v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(l, v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v, while changing digit number l from one to L, and while changing the reference pattern v from the first word to the end word V for each time point m of the input pattern, said time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of the reference patterns of all the words on the l-th digit obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(l, m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(l, m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(l, m) on said digit l at said time point m while changing digit number l from one to L for each time point m of the input pattern, said each time point m changing from the start point to end point M; an initializing means to give said digit similarity measure DB (l-1, m-1) as an initial value of said similarity measure at a time point (m-1) and to give time point (m-1) as an initial value of said path information at a time point m while changing the line point m of the input pattern from the start point to end point M; a decision means to obtain a final digit from said similarity measure DB(l, m), to obtain a recognized result at said final digit from said digit recognition category W(l, M), at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result of the digit prior to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern. | 2. A continuous speech recognition system for recognizing an input speech composed of a plurality of continuously spoken words comprising: a speech analyzing means for analyzing an input signal at every given frame time point m and outputting an input pattern expressed in a time series of a feature vector comprising a predetermined number of feature parameters; an input pattern memory to store said input pattern; a reference pattern memory to store a reference pattern comprising a feature vector in the same format as said input pattern for each of a plurality (V) of predetermined words to be recognized; a distance calculating means to calculate the distance between the feature vector of said input pattern at a time point m and the feature vector of the reference pattern of the v-th word at a time point n at every time point n under a predetermined distance formula by changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v while changing the reference pattern V from the first word to end word V for each time point to end point M; an asymptotic calculating means to calculate a similarity measure D(l, v, n) given by the cumulative sum of said distances on the l-th digit at said time points n and a path information F(l, v, n) indicating a time point of the input pattern at the start point of said v-th reference pattern on a path through which said similarity measure D(l, v, n) has been obtained by a predetermined asymptotic expression according to a dynamic programming process while changing the time point n of the reference pattern of the v-th word in an arbitrary order from the start point to end point N.sup.v, while changing digit number l from one to L, and while changing the reference pattern v from the first word to the end word V for each time point m of the input pattern, said time point m changing from the start point to end point M; a digit similarity measure and digit path information calculating means to select a minimum similarity measure from among the similarity measures at the end time points of the reference patterns of all the words on the l-th digit obtained through said asymptotic calculating means, and to provide said minimum similarity measure as a digit similarity measure DB(l, m), a category to which the word corresponding to said minimum similarity measure belongs as a digit recognition category W(l, m)=v, and path information corresponding to said minimum similarity measure as a digit path information FB(l, m) on said digit l at said time point m while changing digit number l from one to L for each time point m of the input pattern, said each time point m changing from the start point to end point M; an initializing means to give said digit similarity measure DB (l-1, m-1) as an initial value of said similarity measure at a time point (m-1) and to give time point (m-1) as an initial value of said path information at a time point m while changing the line point m of the input pattern from the start point to end point M; a decision means to obtain a final digit from said similarity measure DB(l, m), to obtain a recognized result at said final digit from said digit recognition category W(l, M), at the end point M of said input pattern, to obtain an end point of said input pattern on the digit previous to the final digit by one from said digit path information at the end point M, to obtain a recognized result of the digit prior to said final digit by one from said digit recognition category at the end point, and to obtain a recognized result at each digit sequentially toward the start point of said input pattern. 19. A continuous speech recognition system according to claim 2, wherein said asymptotic expression is ##EQU14## | 0.952703 |
9,792,357 | 19 | 20 | 19. A non-transitory computer readable medium for storing computer instructions that, when executed by at least one processor, causes the at least one processor to perform steps of displaying results, the steps comprising: receiving a search query for searching an attribute within a document; providing, for display within a graphical user interface, a plurality of search results matching the attribute in a plurality of snippets, wherein each snippet of the plurality of snippets displays a portion of content from the document, and wherein each portion of content comprises at least one result from the plurality of search results matching the attribute; receiving, based on a user interaction with the graphical user interface, a first user input with respect to a first snippet of the plurality of snippets, wherein the first snippet comprises a first portion of content from the document, and wherein the first portion of content comprises multiple result instances from the plurality of search results; based on receiving the first user input with respect to the first snippet: determining a proximity within the document between two adjacent result instances of the multiple result instances within the first snippet; and further determining a required display space within the graphical user interface for splitting the first snippet into one or more additional snippets, wherein a given size of a display space is based at least in part on a number of result instances comprised in a given snippet; determining that the proximity between the two adjacent result instances is outside a proximity threshold; determining that the required display space within the graphical user interface is within an acceptable range; based on determining that the proximity between the two adjacent result instances is outside the proximity threshold and further based on determining that the required display space within the graphical user interface is within an acceptable range, splitting the first snippet into one or more additional snippets; and providing, for display within the graphical user interface, the one or more additional snippets, wherein each of the one or more additional snippets comprises one or more result instances from among the multiple result instances within the first snippet. | 19. A non-transitory computer readable medium for storing computer instructions that, when executed by at least one processor, causes the at least one processor to perform steps of displaying results, the steps comprising: receiving a search query for searching an attribute within a document; providing, for display within a graphical user interface, a plurality of search results matching the attribute in a plurality of snippets, wherein each snippet of the plurality of snippets displays a portion of content from the document, and wherein each portion of content comprises at least one result from the plurality of search results matching the attribute; receiving, based on a user interaction with the graphical user interface, a first user input with respect to a first snippet of the plurality of snippets, wherein the first snippet comprises a first portion of content from the document, and wherein the first portion of content comprises multiple result instances from the plurality of search results; based on receiving the first user input with respect to the first snippet: determining a proximity within the document between two adjacent result instances of the multiple result instances within the first snippet; and further determining a required display space within the graphical user interface for splitting the first snippet into one or more additional snippets, wherein a given size of a display space is based at least in part on a number of result instances comprised in a given snippet; determining that the proximity between the two adjacent result instances is outside a proximity threshold; determining that the required display space within the graphical user interface is within an acceptable range; based on determining that the proximity between the two adjacent result instances is outside the proximity threshold and further based on determining that the required display space within the graphical user interface is within an acceptable range, splitting the first snippet into one or more additional snippets; and providing, for display within the graphical user interface, the one or more additional snippets, wherein each of the one or more additional snippets comprises one or more result instances from among the multiple result instances within the first snippet. 20. The non-transitory computer readable medium as claimed in claim 19 , wherein providing for display the plurality of search results comprises: grouping the plurality of search results into the plurality of snippets based on at least one of: a proximity of the plurality of search results with each other within the document, or a location of the plurality of search results in the document. | 0.644665 |
7,958,129 | 6 | 8 | 6. A method as defined in claim 1 , wherein at least one quality parameter takes into account at least one of the following quantities: a number of changes required for converting the value of the data field to be identical to a synonym candidate; a proportion of identical characters in the value of the data field and in a synonym candidate; and a difference between the length of the value of the data field and the length of a synonym candidate. | 6. A method as defined in claim 1 , wherein at least one quality parameter takes into account at least one of the following quantities: a number of changes required for converting the value of the data field to be identical to a synonym candidate; a proportion of identical characters in the value of the data field and in a synonym candidate; and a difference between the length of the value of the data field and the length of a synonym candidate. 8. A method as defined in claim 6 , wherein the proportion of identical characters takes into account the order of the characters. | 0.678218 |
9,275,023 | 1 | 6 | 1. A method for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations, the method comprising: identifying, by a web computing device, a plurality of rules matching one or more elements in an HTML document; identifying, by the web computing device, a plurality of actions associated with each of the identified plurality of rules; grouping, by the web computing device, each of the matching identified plurality of actions together into one or more corresponding groups; filtering, by the web computing device, the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing, by the web computing device, one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying, by the web computing device, the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing, by the web computing device, the transformed HTML document. | 1. A method for further adapting eXtensible Stylesheet Language (XSL) to HyperText Markup Language (HTML) document transformations, the method comprising: identifying, by a web computing device, a plurality of rules matching one or more elements in an HTML document; identifying, by the web computing device, a plurality of actions associated with each of the identified plurality of rules; grouping, by the web computing device, each of the matching identified plurality of actions together into one or more corresponding groups; filtering, by the web computing device, the grouped plurality of actions based on one or more filtering rules when two or more of the grouped plurality of actions match; removing, by the web computing device, one or more of the plurality of actions in each of the one or more corresponding groups based on the one or more filtering rules; applying, by the web computing device, the remaining grouped plurality of actions that match after the filtering to transform the matching one or more elements in the HTML document; and providing, by the web computing device, the transformed HTML document. 6. The method as set forth in claim 1 , wherein the one or more filtering rules comprises removing remove-element or set-meta-category when the identified plurality of actions in the one or more corresponding groups comprises set-meta-category. | 0.738758 |
8,661,065 | 13 | 23 | 13. A system, comprising: one or more processors; one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: storing data in a computerized data storage system that facilitates collaborative data management, wherein collaborative data management includes performance of multiple data management tasks, each data management task associated with a different one of multiple classes of data management tasks, wherein each one of the classes of data management tasks is associated with a unique group of users having permission to perform the data management tasks of the one class; activating a definition interface for defining terms used to manage the data, wherein a term is applicable to the data, and wherein a term includes a definition or a requirement; activating an instruction interface for effectuating terms, wherein the instruction interface facilitates an input of instructions into a data management system such that the inputted instructions effectuate a defined term within the data storage system, and wherein the inputted instructions cause the data storage system to associate the data with the defined term effectuated by the inputted instructions; processing the data according to the defined term effectuated by the inputted instructions; and displaying the inputted instructions, the defined term effectuated by the inputted instructions, and the processed data, wherein displaying includes using a monitoring interface that facilitates monitoring the data stored in the data storage system. | 13. A system, comprising: one or more processors; one or more non-transitory computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: storing data in a computerized data storage system that facilitates collaborative data management, wherein collaborative data management includes performance of multiple data management tasks, each data management task associated with a different one of multiple classes of data management tasks, wherein each one of the classes of data management tasks is associated with a unique group of users having permission to perform the data management tasks of the one class; activating a definition interface for defining terms used to manage the data, wherein a term is applicable to the data, and wherein a term includes a definition or a requirement; activating an instruction interface for effectuating terms, wherein the instruction interface facilitates an input of instructions into a data management system such that the inputted instructions effectuate a defined term within the data storage system, and wherein the inputted instructions cause the data storage system to associate the data with the defined term effectuated by the inputted instructions; processing the data according to the defined term effectuated by the inputted instructions; and displaying the inputted instructions, the defined term effectuated by the inputted instructions, and the processed data, wherein displaying includes using a monitoring interface that facilitates monitoring the data stored in the data storage system. 23. The system of claim 13 , wherein a term further includes an attribute, and wherein an attribute includes a related documents attribute. | 0.732692 |
10,061,753 | 5 | 6 | 5. The method of claim 1 , wherein computing the first identifier comprises computing, for each of a plurality of words in a predetermined set of words, a frequency of each word in the markup language text and the search result. | 5. The method of claim 1 , wherein computing the first identifier comprises computing, for each of a plurality of words in a predetermined set of words, a frequency of each word in the markup language text and the search result. 6. The method of claim 5 , wherein the predetermined set of words are generated by: (a) retrieving markup language text from an Internet domain; (b) retrieving search results associated with the Internet domain from one or more search engines; (c) computing a frequency for each of a plurality of words in the search results and the markup language text; and (d) adding to the predetermined set of words each of the plurality of words whose frequency is greater than a threshold. | 0.5 |
9,613,374 | 1 | 2 | 1. A method of displaying candidate domain names for registration by a user, the method comprising: presenting, by a computer server in electronic communication with a computer network to a user via a user device in electronic communication with the computer network, a user interface; the user interface comprising a carousel comprising a plurality of bundles, each bundle comprising a plurality of the candidate domain names, the plurality of bundles comprising a first bundle related to a characteristic of the user comprising a name of the user, a name of a business of the user, an address of the business, a location of the user, a location of the business, a purchase history of the user or an ownership of other domain names and a second bundle, different from the first bundle, related to input data specified by the user, and the carousel enabling the user to paginate through the bundles; and the user interface further comprising a selection mechanism to permit the selection of at least one relevant bundle from the plurality of bundles, to thereby enable the user to formulate a request to register the candidate domain names in the relevant bundle. | 1. A method of displaying candidate domain names for registration by a user, the method comprising: presenting, by a computer server in electronic communication with a computer network to a user via a user device in electronic communication with the computer network, a user interface; the user interface comprising a carousel comprising a plurality of bundles, each bundle comprising a plurality of the candidate domain names, the plurality of bundles comprising a first bundle related to a characteristic of the user comprising a name of the user, a name of a business of the user, an address of the business, a location of the user, a location of the business, a purchase history of the user or an ownership of other domain names and a second bundle, different from the first bundle, related to input data specified by the user, and the carousel enabling the user to paginate through the bundles; and the user interface further comprising a selection mechanism to permit the selection of at least one relevant bundle from the plurality of bundles, to thereby enable the user to formulate a request to register the candidate domain names in the relevant bundle. 2. The method of claim 1 , wherein each candidate domain name is derived from the input data specified by the user combined with one of multiple TLD extensions. | 0.62963 |
8,762,398 | 1 | 13 | 1. A method of integrating data of an Extensible Markup Language (XML) document with a database (DB) on a web, comprising: designing an XML document provided with user-defined tags; designing an Extensible Stylesheet Language (XSL) format document for normal data mapping, which is used when mapping normal text among structural data of the XML document, and an XSL format document for repetitive data mapping, which is used when mapping repetitive text; creating mapping information required to map the normal text and the repetitive text of the XML document to the XSL format document for normal data mapping and the XSL format document for repetitive data mapping, respectively; designing an XSL document for normal data mapping to which the normal text is mapped and an XSL document for repetitive data mapping to which the repetitive text is mapped, by mapping the normal text and the repetitive text of the XML document to the XSL format document for normal data mapping and the XSL format document for repetitive data mapping, respectively, using the mapping information; generating a Structured Query Language (SQL) query statement required to integrate the normal text and the repetitive text of the XML document with a DB associated with the XML document on the web by performing Extensible Stylesheet Language Transformation (XSLT) on the XML document and the XSL documents for mapping using an XSL transformer; and integrating data of the XML document with the DB by executing the SQL query statement on the DB; wherein the designing the XSL format document for mapping comprises: designing the XSL format document for normal data mapping; and designing the XSL format document for repetitive data mapping, wherein the XSL format document for normal data mapping comprises a mapping XSL format document for normal data storage and a mapping XSL format document for normal data revision, and wherein the XSL format document for repetitive data mapping comprises a mapping XSL format document for repetitive data storage and a mapping XSL format document for repetitive data revision. | 1. A method of integrating data of an Extensible Markup Language (XML) document with a database (DB) on a web, comprising: designing an XML document provided with user-defined tags; designing an Extensible Stylesheet Language (XSL) format document for normal data mapping, which is used when mapping normal text among structural data of the XML document, and an XSL format document for repetitive data mapping, which is used when mapping repetitive text; creating mapping information required to map the normal text and the repetitive text of the XML document to the XSL format document for normal data mapping and the XSL format document for repetitive data mapping, respectively; designing an XSL document for normal data mapping to which the normal text is mapped and an XSL document for repetitive data mapping to which the repetitive text is mapped, by mapping the normal text and the repetitive text of the XML document to the XSL format document for normal data mapping and the XSL format document for repetitive data mapping, respectively, using the mapping information; generating a Structured Query Language (SQL) query statement required to integrate the normal text and the repetitive text of the XML document with a DB associated with the XML document on the web by performing Extensible Stylesheet Language Transformation (XSLT) on the XML document and the XSL documents for mapping using an XSL transformer; and integrating data of the XML document with the DB by executing the SQL query statement on the DB; wherein the designing the XSL format document for mapping comprises: designing the XSL format document for normal data mapping; and designing the XSL format document for repetitive data mapping, wherein the XSL format document for normal data mapping comprises a mapping XSL format document for normal data storage and a mapping XSL format document for normal data revision, and wherein the XSL format document for repetitive data mapping comprises a mapping XSL format document for repetitive data storage and a mapping XSL format document for repetitive data revision. 13. The method according to claim 1 , wherein the generating the SQL query statement comprises: generating a storage SQL query statement required to store the normal text of the XML document in the DB, wherein the storage SQL query statement required to store the normal text comprises an INSERT INTO TABLE command comprising DB column values according to the normal data mapping; generating a storage SQL statement required to store the repetitive text of the XML document in the DB, wherein the storage SQL statement required to store the repetitive text comprises a for-each statement and a nested INSERT INTO TABLE command comprising DB column values according to the repetitive data mapping; generating a revision SQL query statement required to revise the DB using the normal text of the XML document, wherein the revision SQL query statement required to revise the DB using the normal text comprises an UPDATE command comprising DB column values according to the normal data mapping; and generating a revision SQL query statement required to revise the DB using the repetitive text of the XML document, wherein the revision SQL query statement required to revise the DB using the repetitive text comprises a for-each statement and a nested UPDATE command comprising DB column values according to the repetitive data mapping. | 0.5 |
10,146,939 | 2 | 3 | 2. The method of claim 1 , wherein the anomaly detection score is determined by applying a content anomaly detection model to the received input dataset. | 2. The method of claim 1 , wherein the anomaly detection score is determined by applying a content anomaly detection model to the received input dataset. 3. The method of claim 2 , wherein the content anomaly detection model is a frequency distribution-based detection model that determines a plurality of appearance frequencies, and wherein each of the plurality of appearance frequencies corresponds to one of the training n-grams. | 0.5 |
9,208,213 | 1 | 9 | 1. A system for presenting reports processed by an on-line analytical processing (OLAP) system over a network, the system comprising: at least one physical processing device that executes one or more computer program modules that: receive, from a user system through a web browser, a request for a workbook comprising a plurality of reports and a selection of one or more specified templates or filter combinations to format one or more of the plurality of reports; return control of the web browser to enable a user to use the web browser to perform one or more other tasks while the workbook request is being processed, wherein the one or more other tasks includes requesting an additional workbook; receive the workbook comprising the plurality of reports processed by the OLAP system in response to the workbook request; format one or more of the plurality of reports in the workbook in accordance with the selected one or more specified template or filter combinations received from the user system through the web browser in communication with the OLAP system over the network; build an interactive spreadsheet application for presenting the workbook at the web browser of the user system, wherein the interactive spreadsheet application configures an arrangement of the plurality of formatted reports in the workbook; and transmit the workbook including the plurality of formatted reports within a page over the network to the web browser of the user system through which the request was received, wherein the transmitted workbook is presented at the user system using the interactive spreadsheet application displayed within the web browser. | 1. A system for presenting reports processed by an on-line analytical processing (OLAP) system over a network, the system comprising: at least one physical processing device that executes one or more computer program modules that: receive, from a user system through a web browser, a request for a workbook comprising a plurality of reports and a selection of one or more specified templates or filter combinations to format one or more of the plurality of reports; return control of the web browser to enable a user to use the web browser to perform one or more other tasks while the workbook request is being processed, wherein the one or more other tasks includes requesting an additional workbook; receive the workbook comprising the plurality of reports processed by the OLAP system in response to the workbook request; format one or more of the plurality of reports in the workbook in accordance with the selected one or more specified template or filter combinations received from the user system through the web browser in communication with the OLAP system over the network; build an interactive spreadsheet application for presenting the workbook at the web browser of the user system, wherein the interactive spreadsheet application configures an arrangement of the plurality of formatted reports in the workbook; and transmit the workbook including the plurality of formatted reports within a page over the network to the web browser of the user system through which the request was received, wherein the transmitted workbook is presented at the user system using the interactive spreadsheet application displayed within the web browser. 9. The system of claim 1 , wherein the one or more template or filter combinations specify one or more scripts used to format the plurality of reports in the workbook, wherein the one or more scripts are created at the user system and specified through the web browser. | 0.571656 |
7,970,759 | 1 | 14 | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. | 1. A computer implemented method for inferring a probability of a first inference relating to a drug, the computer implemented method comprising: importing additional data into the plurality of data, wherein the additional data initially is not associated with metadata and the additional data does not conform to the dimensions of the database; conforming the additional data to the dimensions of the database; associating metadata and a key with each datum of the additional data; receiving a query at a database regarding a fact related to the drug, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the database is conformed to the dimensions of the database, wherein each datum of the plurality of data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; determining an I th set of rules using a J th set of rules, wherein the J th set of rules, wherein J=1 is the first iteration of a recursion process and I-1 is the J th iteration of the recursion process, wherein the I th set of rules is a first set of rules, and wherein the J th set of rules is a second set of rules; applying the first set of rules to the query, wherein the first set of rules are determined for the query according to the second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of data according to the first set of rules, wherein the probability of the first inference is based on factors selected from the group consisting of: a timing of the plurality of data according to the first set of rules, a source of the plurality of data according to the first set of rules, a trustworthiness of the plurality of data according to the first set of rules, a relevance of the plurality of data according to the first set of rules the plurality of data according to the first set of rules, a reliability of the plurality of data according to the first set of rules, an importance of the plurality of data according to the first set of rules, a data integrity of the plurality of data according to the first set of rules, and cohort information of the plurality of data according to the first set of rules, wherein a combination of the factors has a synergistic effect on the probability of the first inference; and storing the probability of the first inference, wherein subsequently viewing the first inference is accessible to individuals having one of a set of different security access clearances based on the probability of the first inference having a higher or lower threshold of certainty probabilities of inferences when the inference implicates medical privacy laws, wherein first ones the individuals having a first one of the set of different security access clearances are permitted to viewing the first inference, and, wherein second ones the individuals having a second one of the set of different security access clearances are not permitted to viewing the first inference. 14. The computer implemented method of claim 1 wherein the set of rules includes rules for adjusting the probability of the inference based on background data. | 0.880988 |
8,103,547 | 5 | 6 | 5. The media of claim 4 , wherein providing the email comprises at least one of providing a preview email to a sender of the email or providing the email to a recipient. | 5. The media of claim 4 , wherein providing the email comprises at least one of providing a preview email to a sender of the email or providing the email to a recipient. 6. The media of claim 5 , further comprising receiving an indication from the recipient of the email to not allow a display of the one or more logocons. | 0.5 |
7,962,469 | 24 | 25 | 24. The system of claim 23 , where the means for obtaining the set of one or more URLs includes: means for identifying the set of one or more URLs from a preferences list created by a user, the means for identifying including: means for permitting the user to add URLs corresponding to on-topic documents to a positive preferences list, and means for permitting the user to add URLs corresponding to off-topic documents to a negative preferences list. | 24. The system of claim 23 , where the means for obtaining the set of one or more URLs includes: means for identifying the set of one or more URLs from a preferences list created by a user, the means for identifying including: means for permitting the user to add URLs corresponding to on-topic documents to a positive preferences list, and means for permitting the user to add URLs corresponding to off-topic documents to a negative preferences list. 25. The system of claim 24 , where the means for filtering the set of links further includes: means for including, in the subset of the links, one of the links corresponding to one of the URLs within the positive preferences list, and means for excluding, from the subset of the links, one of the links corresponding to one of the URLs within the negative preferences list. | 0.5 |
7,970,796 | 7 | 11 | 7. A computing device for importing data into a repository, comprising: a document loaded in a document application comprising data; and a map file stored in a directory and configured to map data from the document to a plurality of fields in the repository, wherein the map file and the plurality of fields correspond to a document type of the document, wherein the map file is used to dynamically create a context menu in the document by a macro specific to the document application, wherein the macro is dynamically inserted into the document application when the document is loaded and executes in response to selection of data to be imported from the document, and is configured to: access the map file at the directory location stored in the repository, determine the plurality of fields corresponding to the document type of the document from which data is imported from the map file, and create the context menu in response to selection of data in the document, wherein the context menu is a user interface comprising the plurality of fields corresponding to the repository, and wherein the selected data in the document is associated with one of the plurality of fields by selecting the one of the plurality of fields in the context menu, resulting in the importation of the selected data to the selected one of the plurality of fields in the repository, wherein the selected data is copied to the map file, which acts as an intermediary storage file between the document and the repository, until the stored selected data is loaded from the map file into the repository at a later time, and wherein a comment is inserted into the document by a user after importation to indicate that the selected data is imported into the repository. | 7. A computing device for importing data into a repository, comprising: a document loaded in a document application comprising data; and a map file stored in a directory and configured to map data from the document to a plurality of fields in the repository, wherein the map file and the plurality of fields correspond to a document type of the document, wherein the map file is used to dynamically create a context menu in the document by a macro specific to the document application, wherein the macro is dynamically inserted into the document application when the document is loaded and executes in response to selection of data to be imported from the document, and is configured to: access the map file at the directory location stored in the repository, determine the plurality of fields corresponding to the document type of the document from which data is imported from the map file, and create the context menu in response to selection of data in the document, wherein the context menu is a user interface comprising the plurality of fields corresponding to the repository, and wherein the selected data in the document is associated with one of the plurality of fields by selecting the one of the plurality of fields in the context menu, resulting in the importation of the selected data to the selected one of the plurality of fields in the repository, wherein the selected data is copied to the map file, which acts as an intermediary storage file between the document and the repository, until the stored selected data is loaded from the map file into the repository at a later time, and wherein a comment is inserted into the document by a user after importation to indicate that the selected data is imported into the repository. 11. The computing device of claim 7 , wherein the dynamically created context menu is accessed by right-clicking on the selected data. | 0.737255 |
9,880,999 | 15 | 18 | 15. A computer-implemented method of processing text, the computer-implemented method comprising: using one or more processors configured to execute a natural language processing application, including: the one or more processors receiving, via a user interface, a candidate term comprising one or more natural language terms; the one or more processors discovering, using one or more semantic analysis techniques, an initial subset of concepts of a digital corpus that are at least one of explicitly or implicitly associated with the candidate term, the digital corpus comprising natural language; the one or more processors mining the digital corpus for a set of concept association rules of the digital corpus, the set of concept association rules determined based on record-links included in a plurality of records of the digital corpus, and the mining of the digital corpus including: for each candidate rule corresponding to the set of concept association rules, (i) determining a respective measure of support based on a number of occurrences, in a transaction dictionary of the digital corpus, of a set of antecedent concepts of the each candidate rule together with a set of consequence concepts of the each candidate rule; and (ii) determining a respective measure of confidence based on the respective measure of support and a number of occurrences, in the transaction dictionary of the digital corpus, of the set of antecedent concepts of the each candidate rule; determining a set of candidate rules as the set of concept association rules; and limiting a size of the set of concept association rules based on a set of rule-limiting parameters, the set of rule-limiting parameters including at least one of: a number of concepts included in the set of consequence concepts, a minimum strength of the respective measure of support, or a minimum strength of the respective measure of confidence; the one or more processors discovering, based on the mined set of concept association rules and the discovered initial subset of concepts of the digital corpus that are at least one of explicitly or implicitly associated with the candidate term, an expansion subset of concepts of the digital corpus that are latently associated with the candidate term; the one or more processors generating a concept space of the candidate term from at least a portion of the initial subset of concepts and at least a portion of the expansion subset of concepts, wherein each concept included in the concept space comprises a respective one or more natural language terms; the one or more processors searching, using the generated concept space, the digital corpus for a first set of records corresponding to the at least the portion of the initial subset of concepts of the generated concept space and a second set of records corresponding to the at least the portion of the expansion subset of concepts of the generated concept space; the one or more processors retrieving, from the digital corpus, at least a portion of each record included in the second set of records corresponding to the at least the portion of the expansion subset of concepts of the generated concept space; and the one or more processors displaying, at the user interface, the retrieved at least the portion of the each record included in the second set of records corresponding to the at least the portion of the expansion subset of concepts of the generated concept space. | 15. A computer-implemented method of processing text, the computer-implemented method comprising: using one or more processors configured to execute a natural language processing application, including: the one or more processors receiving, via a user interface, a candidate term comprising one or more natural language terms; the one or more processors discovering, using one or more semantic analysis techniques, an initial subset of concepts of a digital corpus that are at least one of explicitly or implicitly associated with the candidate term, the digital corpus comprising natural language; the one or more processors mining the digital corpus for a set of concept association rules of the digital corpus, the set of concept association rules determined based on record-links included in a plurality of records of the digital corpus, and the mining of the digital corpus including: for each candidate rule corresponding to the set of concept association rules, (i) determining a respective measure of support based on a number of occurrences, in a transaction dictionary of the digital corpus, of a set of antecedent concepts of the each candidate rule together with a set of consequence concepts of the each candidate rule; and (ii) determining a respective measure of confidence based on the respective measure of support and a number of occurrences, in the transaction dictionary of the digital corpus, of the set of antecedent concepts of the each candidate rule; determining a set of candidate rules as the set of concept association rules; and limiting a size of the set of concept association rules based on a set of rule-limiting parameters, the set of rule-limiting parameters including at least one of: a number of concepts included in the set of consequence concepts, a minimum strength of the respective measure of support, or a minimum strength of the respective measure of confidence; the one or more processors discovering, based on the mined set of concept association rules and the discovered initial subset of concepts of the digital corpus that are at least one of explicitly or implicitly associated with the candidate term, an expansion subset of concepts of the digital corpus that are latently associated with the candidate term; the one or more processors generating a concept space of the candidate term from at least a portion of the initial subset of concepts and at least a portion of the expansion subset of concepts, wherein each concept included in the concept space comprises a respective one or more natural language terms; the one or more processors searching, using the generated concept space, the digital corpus for a first set of records corresponding to the at least the portion of the initial subset of concepts of the generated concept space and a second set of records corresponding to the at least the portion of the expansion subset of concepts of the generated concept space; the one or more processors retrieving, from the digital corpus, at least a portion of each record included in the second set of records corresponding to the at least the portion of the expansion subset of concepts of the generated concept space; and the one or more processors displaying, at the user interface, the retrieved at least the portion of the each record included in the second set of records corresponding to the at least the portion of the expansion subset of concepts of the generated concept space. 18. The computer-implemented method of claim 15 , wherein the one or more processors discovering the expansion subset of concepts that are latently associated with the candidate term based on the set of concept association rules and the initial subset of concepts comprises, for each concept included in the initial subset of concepts, the one or more processors mining the set of concept association rules to determine a set of concepts that are latently associated with the each concept included in the initial subset of concepts. | 0.5 |
9,946,800 | 10 | 16 | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive an input graph comprising a plurality of first nodes, where subsets of first nodes in the plurality of first nodes are coupled to one another via one or more first edges and each first edge in the one or more first edges has an associated weight value; generate a blinking graph model based on the graph, wherein the blinking graph model comprises blink rate values associated with second edges of the blinking graph model calculated based on weights of corresponding first edges in the input graph, wherein the blink rate value specifies a fraction of time a corresponding second edge is determined to be present in the blinking graph model; receive a request for performance of a cognitive operation, wherein the request comprises an identification of a node of interest; calculate a relatedness metric for a target node in the blinking graph model relative to the node of interest based on the blink rate values of the second edges, wherein the relatedness metric indicates a degree of relatedness of the target node to the node of interest, wherein the relatedness metric is calculated for the target node at least by calculating the relatedness metric for each path from the node of interest to a plurality of target nodes in the blinking graph model; and perform a cognitive operation based on the relatedness metric. | 10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive an input graph comprising a plurality of first nodes, where subsets of first nodes in the plurality of first nodes are coupled to one another via one or more first edges and each first edge in the one or more first edges has an associated weight value; generate a blinking graph model based on the graph, wherein the blinking graph model comprises blink rate values associated with second edges of the blinking graph model calculated based on weights of corresponding first edges in the input graph, wherein the blink rate value specifies a fraction of time a corresponding second edge is determined to be present in the blinking graph model; receive a request for performance of a cognitive operation, wherein the request comprises an identification of a node of interest; calculate a relatedness metric for a target node in the blinking graph model relative to the node of interest based on the blink rate values of the second edges, wherein the relatedness metric indicates a degree of relatedness of the target node to the node of interest, wherein the relatedness metric is calculated for the target node at least by calculating the relatedness metric for each path from the node of interest to a plurality of target nodes in the blinking graph model; and perform a cognitive operation based on the relatedness metric. 16. The computer program product of claim 10 , wherein blink rate values associated with second edges of the blinking graph model are specified as either an individual blink rate values associated with a corresponding second edge such that the corresponding second edge has a blink rate value independent of other second, or as a joint function of a plurality of blink rate values associated with different types of evidence supporting a relationship modeled by the corresponding second edge such that the corresponding second edge has a blink rate value based on a combination of the plurality of blink rate values. | 0.558106 |
8,234,561 | 1 | 9 | 1. A method comprising: observing values entered in form field objects; generating likelihood assessments for possible values to be entered in a current form field object based on the observed values, the likelihood assessments indicating relative probability of the possible values being entered in the current form field object; and predicting a value for the current form field object based on the generated likelihood assessments, wherein generating likelihood assessments comprises: determining a semantic similarity between the current form field object and a form field for which values have been observed; and generating a likelihood assessment for a possible value based on the observed values for the form field and the determined semantic similarity. | 1. A method comprising: observing values entered in form field objects; generating likelihood assessments for possible values to be entered in a current form field object based on the observed values, the likelihood assessments indicating relative probability of the possible values being entered in the current form field object; and predicting a value for the current form field object based on the generated likelihood assessments, wherein generating likelihood assessments comprises: determining a semantic similarity between the current form field object and a form field for which values have been observed; and generating a likelihood assessment for a possible value based on the observed values for the form field and the determined semantic similarity. 9. The method of claim 1 , wherein observing values entered in form field objects comprises storing order information for the observed values, and wherein generating likelihood assessments for possible values comprises comparing order information for values entered in a current form instance with the stored order information for the observed values. | 0.603837 |
8,856,098 | 14 | 15 | 14. A system for ranking search results, comprising: one or more processors configured to: receive a query string; retrieve a plurality of search results that include a corresponding plurality of target strings that relate to the query string; segment the query string and each of the plurality of target strings; pair segments in the query string with respective segments in the target strings to form a plurality of word pairs, wherein one word pair of the plurality of the word pairs comprises a segment from the segmented query string and a segment from one of the segmented target strings; retrieve a plurality of weights that correspond to the plurality of word pairs based on a mapping of word pairs and their respective weights, wherein a weight measures semantic correlation between words in a word pair; and determine a weighted word length based on the weights corresponding to each of the plurality of target strings, wherein determining a weighted word length for a first target string of the plurality of target strings includes determining a minimum weight corresponding to each segment of the first target string with respect to segmented words in the query string, wherein the minimum weight corresponding to a first segment of the first target string comprises a minimum weight selected from a plurality of weights corresponding to respective ones of a subset of the plurality of word pairs associated with the first segment and the segmented words in the query string; and rank the plurality of target strings based on their respective weighted word lengths; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. | 14. A system for ranking search results, comprising: one or more processors configured to: receive a query string; retrieve a plurality of search results that include a corresponding plurality of target strings that relate to the query string; segment the query string and each of the plurality of target strings; pair segments in the query string with respective segments in the target strings to form a plurality of word pairs, wherein one word pair of the plurality of the word pairs comprises a segment from the segmented query string and a segment from one of the segmented target strings; retrieve a plurality of weights that correspond to the plurality of word pairs based on a mapping of word pairs and their respective weights, wherein a weight measures semantic correlation between words in a word pair; and determine a weighted word length based on the weights corresponding to each of the plurality of target strings, wherein determining a weighted word length for a first target string of the plurality of target strings includes determining a minimum weight corresponding to each segment of the first target string with respect to segmented words in the query string, wherein the minimum weight corresponding to a first segment of the first target string comprises a minimum weight selected from a plurality of weights corresponding to respective ones of a subset of the plurality of word pairs associated with the first segment and the segmented words in the query string; and rank the plurality of target strings based on their respective weighted word lengths; and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions. 15. The system of claim 14 , wherein the mapping of word pairs and their respective weights is determined by: acquiring a set of statistical samples; selecting a first word and a second word from the set of statistical samples, and counting the number of times that both the first and second words occur in the statistical samples as C (the first word, the second word); counting the number of times that the second word occurs in the statistical samples as ΣC (Y i , the second word), wherein Y i denotes the respective words occurring together with the second word; calculating a probability of occurrence P of the first word given a condition that the second word occurs as based on the number of times both the first and second words occur in the statistical samples and the number of times that the second word occurs in the statistical samples; determining a weight that measures semantic correlation between the first and second words by W=1−P during a search for the second word, wherein W is the weight, and P is the probability of the first word on the condition that the second word occurs; repeating selecting, counting, calculating, and determining steps above to determine the weights measuring semantic correlations between word pairs in the statistical samples; and storing the mapping of the word pairs and their respective weights. | 0.5 |
7,676,358 | 29 | 31 | 29. A system comprising a at least one computer, said system comprising a first unit for partitioning document text separated by spaces into a plurality of tokens based on the spaces; a second unit, operable for identifying tokens to be ignored and not considered; a third unit, operable for determining that a first token considered of the plurality of tokens comprises a chemical name fragment, wherein determining comprises: examining syntax of the first token, examining context of the first token with respect to at least one adjacent token of the plurality of tokens, and taking into account the syntax and the context, applying a plurality of regular expressions, rules, and a plurality of dictionaries comprised of a prefix dictionary and a syntax dictionary to recognize the chemical name fragment; a fourth unit, operable to add the recognized chemical name fragment to a vector of chemical name fragments, where the chemical name fragment is identified by a vector index variable; a fifth unit, operable to combine the recognized chemical name fragment with at least one of the adjacent tokens that are determined to be a chemical name fragment into a complete chemical name, where combining comprises: the fifth unit is operable to initialize the chemical name fragment vector index variable, the fifth unit is operable to increment the chemical name fragment vector index variable, where the incrementing continues at least until no chemical name fragments remain; the fifth unit is operable to set a string combination to include the chemical name fragments identified by the initialized and incremented chemical name fragment vector index variables, and the fifth unit is operable to add the string combination to a vector c as the complete chemical name; a sixth unit, operable to assign the complete chemical name with one part of speech; and a seventh unit, operable for storing in a memory information the complete chemical name with the one part of speech. | 29. A system comprising a at least one computer, said system comprising a first unit for partitioning document text separated by spaces into a plurality of tokens based on the spaces; a second unit, operable for identifying tokens to be ignored and not considered; a third unit, operable for determining that a first token considered of the plurality of tokens comprises a chemical name fragment, wherein determining comprises: examining syntax of the first token, examining context of the first token with respect to at least one adjacent token of the plurality of tokens, and taking into account the syntax and the context, applying a plurality of regular expressions, rules, and a plurality of dictionaries comprised of a prefix dictionary and a syntax dictionary to recognize the chemical name fragment; a fourth unit, operable to add the recognized chemical name fragment to a vector of chemical name fragments, where the chemical name fragment is identified by a vector index variable; a fifth unit, operable to combine the recognized chemical name fragment with at least one of the adjacent tokens that are determined to be a chemical name fragment into a complete chemical name, where combining comprises: the fifth unit is operable to initialize the chemical name fragment vector index variable, the fifth unit is operable to increment the chemical name fragment vector index variable, where the incrementing continues at least until no chemical name fragments remain; the fifth unit is operable to set a string combination to include the chemical name fragments identified by the initialized and incremented chemical name fragment vector index variables, and the fifth unit is operable to add the string combination to a vector c as the complete chemical name; a sixth unit, operable to assign the complete chemical name with one part of speech; and a seventh unit, operable for storing in a memory information the complete chemical name with the one part of speech. 31. A system as in claim 29 , where a user of the system accesses the system through a data communications network. | 0.846257 |
9,589,012 | 1 | 6 | 1. A computer-implemented method, comprising: receiving from a user a selection of an object among one or more objects included in a data model, the selection made through an object-selection interface; retrieving from computer memory a previously stored object definition that corresponds to the selected object, the previously stored object definition includes: an object query that, when executed, retrieves a set of time stamped events from a data store on a computing device, each event including a portion of raw machine data reflecting activity in an information technology environment; and an object schema identifying a set of one or more fields, each field defined by an extraction rule or regular expression that locates the field in the raw machine data and can be used to extract a field value from the field location from the raw machine data in each event in a subset of the set of time stamped events, each extraction rule or regular expression operating on the raw machine data in an event without modifying the event's raw machine data; and executing, against events in the data store that meet filtering criteria of the object query, a search query that references only field values that are extracted using the object schema and that produces a result based at least in part on the data reflecting the activity of the information technology environment. | 1. A computer-implemented method, comprising: receiving from a user a selection of an object among one or more objects included in a data model, the selection made through an object-selection interface; retrieving from computer memory a previously stored object definition that corresponds to the selected object, the previously stored object definition includes: an object query that, when executed, retrieves a set of time stamped events from a data store on a computing device, each event including a portion of raw machine data reflecting activity in an information technology environment; and an object schema identifying a set of one or more fields, each field defined by an extraction rule or regular expression that locates the field in the raw machine data and can be used to extract a field value from the field location from the raw machine data in each event in a subset of the set of time stamped events, each extraction rule or regular expression operating on the raw machine data in an event without modifying the event's raw machine data; and executing, against events in the data store that meet filtering criteria of the object query, a search query that references only field values that are extracted using the object schema and that produces a result based at least in part on the data reflecting the activity of the information technology environment. 6. The method of claim 1 , further comprising causing display of the result in a table. | 0.956673 |
10,133,765 | 1 | 10 | 1. A system comprising: one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising: storing a plurality of items, each item comprising digital content; for each item of the plurality of items, generating a quality score to provide a plurality of quality scores, each quality score indicating a quality of a respective item and being based on at least one of a status score and a content score, the status score being associated with an author user of the respective item and the content score being associated with digital content provided in the respective item; identifying occurrences of events associated with the plurality of items, each event having an event type selected from a group comprising a comment event, an endorsement event, a mute event, and a share event; for each identified occurrence of an event associated with a respective item from the plurality of items, incrementing an item weight of the respective item by an amount that is based on the event type for the event; identifying a first proper subset of the plurality of items that have item weights that meet a threshold and, in response, updating respective timestamps for the items in the first proper subset; determining an order of items based on respective quality scores and timestamps; and transmitting instructions to display items to a user based on the order, wherein updating the respective timestamp for a particular item in the first proper subset comprises assigning a timestamp to the particular item that represents a time of occurrence of a particular event associated with the particular item, and wherein the operations comprise: identifying the occurrence of the particular event associated with the particular item, incrementing the item weight of the particular item by an amount that is based on the event type for the particular event, determining that the incremented item weight of the particular item meets the threshold, and in response to determining that the incremented item weight of the particular item meets the threshold, assigning the timestamp to the particular item that represents the time of occurrence of the particular event. | 1. A system comprising: one or more processors; and a non-transitory computer-readable medium coupled to the one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations comprising: storing a plurality of items, each item comprising digital content; for each item of the plurality of items, generating a quality score to provide a plurality of quality scores, each quality score indicating a quality of a respective item and being based on at least one of a status score and a content score, the status score being associated with an author user of the respective item and the content score being associated with digital content provided in the respective item; identifying occurrences of events associated with the plurality of items, each event having an event type selected from a group comprising a comment event, an endorsement event, a mute event, and a share event; for each identified occurrence of an event associated with a respective item from the plurality of items, incrementing an item weight of the respective item by an amount that is based on the event type for the event; identifying a first proper subset of the plurality of items that have item weights that meet a threshold and, in response, updating respective timestamps for the items in the first proper subset; determining an order of items based on respective quality scores and timestamps; and transmitting instructions to display items to a user based on the order, wherein updating the respective timestamp for a particular item in the first proper subset comprises assigning a timestamp to the particular item that represents a time of occurrence of a particular event associated with the particular item, and wherein the operations comprise: identifying the occurrence of the particular event associated with the particular item, incrementing the item weight of the particular item by an amount that is based on the event type for the particular event, determining that the incremented item weight of the particular item meets the threshold, and in response to determining that the incremented item weight of the particular item meets the threshold, assigning the timestamp to the particular item that represents the time of occurrence of the particular event. 10. The system of claim 1 , wherein the operations further comprise filtering the plurality of items based on their respective item weights to select a second proper subset of the plurality of items to provide for display, the second proper subset selected to exclusion of a third proper subset of the plurality of items; wherein determining the order of items comprises determining an order of items from the second proper subset based on respective quality scores and timestamps, wherein transmitting instructions comprises transmitting instructions to display items from the second proper subset to the user based on the order. | 0.5 |
8,296,279 | 1 | 26 | 1. A computer-implemented method, comprising: identifying a search query comprising one or more search terms; identifying an index for a word, wherein the word or a substring of the word matches one of the one or more search terms of the search query, and wherein the index comprises: one or more substrings of the word, wherein each substring includes one or more but not all characters included in the word; one or more inclusive strings corresponding to the one or more substrings, each of the one or more inclusive strings comprising the corresponding substring and at least one more character included in the word; and two or more word objects, wherein each of the one or more substrings correspond to at least one of the two or more word objects, and the two or more word objects identify content that includes at least one substring of the word; and using the index to identify one or more search results for the search query based on the two or more word objects; wherein the word object is a location of a web page in which the word occurs. | 1. A computer-implemented method, comprising: identifying a search query comprising one or more search terms; identifying an index for a word, wherein the word or a substring of the word matches one of the one or more search terms of the search query, and wherein the index comprises: one or more substrings of the word, wherein each substring includes one or more but not all characters included in the word; one or more inclusive strings corresponding to the one or more substrings, each of the one or more inclusive strings comprising the corresponding substring and at least one more character included in the word; and two or more word objects, wherein each of the one or more substrings correspond to at least one of the two or more word objects, and the two or more word objects identify content that includes at least one substring of the word; and using the index to identify one or more search results for the search query based on the two or more word objects; wherein the word object is a location of a web page in which the word occurs. 26. The method of claim 1 , wherein: the one or more substrings comprises a plurality of substrings and the two or more word objects comprise a plurality of word objects; the one search term matches a first substring of the plurality of substrings of the word; and the one or more search results include content identified by one or more word objects of the plurality of word objects, and the one or more word objects correspond to the first substring and one or more substrings that match the one or more inclusive strings that correspond to the first substring. | 0.5 |
9,443,324 | 4 | 6 | 4. A method for rendering annotations associated with an electronic image comprising: displaying on a display the electronic image, the electronic image having a plurality of pixels, with one or more pixels annotated at a plurality of levels in ascending magnitude of descriptive characteristics, with each level containing one or more descriptive characteristics of the pixel, such that the descriptive characteristics at a subsequent level in the ascending magnitude is with reference to descriptive characteristics of one or more pixel surrounding the pixel; receiving pixel and level selection details through a user interface; retrieving and rendering the selected level annotation for the selected pixel; wherein a level selected by default is a lowest level available, wherein at a lowest level the descriptive characteristic of the pixel is a caption of the electronic image and at a highest level the descriptive characteristic of the pixel is a color of the pixel; storing a plurality of annotations in a file separate from the electronic image, wherein the annotations at the plurality of levels for the annotated pixels is collectively stored in the file separate from the electronic image; and displaying the electronic image, wherein the displayed electronic image is determined based on a cursor location relative to a plurality of pixel coordinates within a user interface. | 4. A method for rendering annotations associated with an electronic image comprising: displaying on a display the electronic image, the electronic image having a plurality of pixels, with one or more pixels annotated at a plurality of levels in ascending magnitude of descriptive characteristics, with each level containing one or more descriptive characteristics of the pixel, such that the descriptive characteristics at a subsequent level in the ascending magnitude is with reference to descriptive characteristics of one or more pixel surrounding the pixel; receiving pixel and level selection details through a user interface; retrieving and rendering the selected level annotation for the selected pixel; wherein a level selected by default is a lowest level available, wherein at a lowest level the descriptive characteristic of the pixel is a caption of the electronic image and at a highest level the descriptive characteristic of the pixel is a color of the pixel; storing a plurality of annotations in a file separate from the electronic image, wherein the annotations at the plurality of levels for the annotated pixels is collectively stored in the file separate from the electronic image; and displaying the electronic image, wherein the displayed electronic image is determined based on a cursor location relative to a plurality of pixel coordinates within a user interface. 6. The method as claimed in claim 4 , further comprising retaining the pixel selected on receiving new level selection details. | 0.706019 |
8,738,608 | 28 | 30 | 28. The data storage and/or retrieval system of claim 1 , wherein the plurality of data tunnels and respective operators relate to —instances of entities of arbitrary structure. | 28. The data storage and/or retrieval system of claim 1 , wherein the plurality of data tunnels and respective operators relate to —instances of entities of arbitrary structure. 30. The data storage and/or retrieval system of claim 28 , wherein a plurality of the data tunnels are combinative data tunnels, and the plurality of combinative data tunnels and respective operators relate to instances of entities of arbitrary structure. | 0.511494 |
8,180,721 | 14 | 17 | 14. The system of claim 11 , wherein the memory further stores computer usable program code executed by the processor to: analyze the content of the companion guides and to build an organizer of companion guide rules where each companion guide is associated with one of the plurality of entities; and employ the organizer of companion guide rules to update companion guide rules to the inventory of rules. | 14. The system of claim 11 , wherein the memory further stores computer usable program code executed by the processor to: analyze the content of the companion guides and to build an organizer of companion guide rules where each companion guide is associated with one of the plurality of entities; and employ the organizer of companion guide rules to update companion guide rules to the inventory of rules. 17. The system of claim 14 , wherein the memory further stores computer usable program code executed by the processor to: create human-readable hierarchies of rules from companion guides. | 0.733618 |
8,307,073 | 1 | 2 | 1. A computer-implemented method for repairing URL (Uniform Resource Locator) request messages from user computing devices, the method comprising: receiving a URL request from a user computing device, the URL request specifying a URL that includes a name of a domain followed by a character string, the character string including a first product identifier; determining that the URL is invalid; at least partly in response to receiving the invalid URL, processing the invalid URL into a repaired URL using one or more computing devices, the repaired URL being different from the invalid URL, the processing comprising: identifying a non-URL escape sequence in the character string through a comparison with known escape sequences, the escape sequence corresponding to a special character; replacing the non-URL escape sequence in the character string with the corresponding special character; and decoding the URL a second time by replacing a URL escape sequence in the character string with a corresponding special character, wherein the URL was previously decoded a first time; and in response to determining whether the repaired URL resolves to valid content, (1) providing the valid content associated with the repaired URL to the user computing device when the repaired URL is valid or (2) identifying, using the first product identifier extracted from the invalid URL, a substitute URL and providing content associated with the substitute URL when the repaired URL is invalid. | 1. A computer-implemented method for repairing URL (Uniform Resource Locator) request messages from user computing devices, the method comprising: receiving a URL request from a user computing device, the URL request specifying a URL that includes a name of a domain followed by a character string, the character string including a first product identifier; determining that the URL is invalid; at least partly in response to receiving the invalid URL, processing the invalid URL into a repaired URL using one or more computing devices, the repaired URL being different from the invalid URL, the processing comprising: identifying a non-URL escape sequence in the character string through a comparison with known escape sequences, the escape sequence corresponding to a special character; replacing the non-URL escape sequence in the character string with the corresponding special character; and decoding the URL a second time by replacing a URL escape sequence in the character string with a corresponding special character, wherein the URL was previously decoded a first time; and in response to determining whether the repaired URL resolves to valid content, (1) providing the valid content associated with the repaired URL to the user computing device when the repaired URL is valid or (2) identifying, using the first product identifier extracted from the invalid URL, a substitute URL and providing content associated with the substitute URL when the repaired URL is invalid. 2. The method of claim 1 , wherein the non-URL escape sequence comprises XML encoded escape sequences. | 0.789256 |
9,424,516 | 14 | 16 | 14. A method comprising: ordering, by a computing device, answers according to their frequency of occurrence; determining a relative difference for each neighboring pair of the ordered answers, the relative distance based on the frequency of occurrence of each ordered answer of the each neighboring pair; and designating as final answers any of the ordered answers that have a frequency of occurrence that is greater than a frequency of occurrence of an ordered answer of a neighboring pair that has a greatest relative distance of the neighboring pairs. | 14. A method comprising: ordering, by a computing device, answers according to their frequency of occurrence; determining a relative difference for each neighboring pair of the ordered answers, the relative distance based on the frequency of occurrence of each ordered answer of the each neighboring pair; and designating as final answers any of the ordered answers that have a frequency of occurrence that is greater than a frequency of occurrence of an ordered answer of a neighboring pair that has a greatest relative distance of the neighboring pairs. 16. The method of claim 14 where the answers are directed to labeling an image. | 0.608911 |
8,867,838 | 9 | 10 | 9. The computer implementable method of claim 1 , wherein the labeling comprises one or more of a security based labeling, a rejection based labeling, and a dependency based labeling. | 9. The computer implementable method of claim 1 , wherein the labeling comprises one or more of a security based labeling, a rejection based labeling, and a dependency based labeling. 10. The computer implementable method of claim 9 , wherein the security based labeling is performed for the at least one group of the plurality of groups requiring confidential or restricted access. | 0.642599 |
7,594,172 | 1 | 20 | 1. A method of storing descriptive metatag-value pairs for parametized information regarding first and second items having differing classifications, comprising: providing a first electronic interface through which a first human user identifies the first item in a first document to a computer system; prompting the first user to select a first classification for the first item, wherein the first user selects the first classification for the first item; providing the first user with a first set of metatag choices determined at least in part by the first user's selection of the first classification; presenting the first user with: (a) the first set of metatag choices for possible association with the first item, and (b) candidate values for at least one of the metatag choices that allows the first user to define a first metatag-value pair; providing a second electronic interface through which the first user creates a new metatag for the first set of metatag choices which based on an analysis of a second document that includes the second item, is subsequently displayed in the first set of metatag choices to a second human user for the second user to utilize in entering a second metatag-value pair for possible association with the second item in the second document; and storing an association of the first item and the new metatag in a data structure. | 1. A method of storing descriptive metatag-value pairs for parametized information regarding first and second items having differing classifications, comprising: providing a first electronic interface through which a first human user identifies the first item in a first document to a computer system; prompting the first user to select a first classification for the first item, wherein the first user selects the first classification for the first item; providing the first user with a first set of metatag choices determined at least in part by the first user's selection of the first classification; presenting the first user with: (a) the first set of metatag choices for possible association with the first item, and (b) candidate values for at least one of the metatag choices that allows the first user to define a first metatag-value pair; providing a second electronic interface through which the first user creates a new metatag for the first set of metatag choices which based on an analysis of a second document that includes the second item, is subsequently displayed in the first set of metatag choices to a second human user for the second user to utilize in entering a second metatag-value pair for possible association with the second item in the second document; and storing an association of the first item and the new metatag in a data structure. 20. A computer having a processor and a memory, and running software that executes a method according to claim 1 . | 0.658683 |
8,717,299 | 1 | 5 | 1. A computer-implemented method of translating user input into at least one word having multiple characters, the method comprising: displaying a keyboard on a display, wherein the keyboard comprises multiple keys, and wherein each key in the keyboard has a relative position with respect to every other key in the keyboard, receiving a sequence of user inputs; translating the sequence of user inputs into a pattern of one or more relative directions, wherein each relative direction in the pattern corresponds to the relative position of a key in the keyboard with respect to a previous key; and using the pattern of one or more relative directions to identify the at least one word in a stored dictionary, wherein the stored dictionary associates the word with a pattern of relative directions that reflects relative positions of the keys associated with the multiple characters that form the word. | 1. A computer-implemented method of translating user input into at least one word having multiple characters, the method comprising: displaying a keyboard on a display, wherein the keyboard comprises multiple keys, and wherein each key in the keyboard has a relative position with respect to every other key in the keyboard, receiving a sequence of user inputs; translating the sequence of user inputs into a pattern of one or more relative directions, wherein each relative direction in the pattern corresponds to the relative position of a key in the keyboard with respect to a previous key; and using the pattern of one or more relative directions to identify the at least one word in a stored dictionary, wherein the stored dictionary associates the word with a pattern of relative directions that reflects relative positions of the keys associated with the multiple characters that form the word. 5. The computer-implemented method of claim 1 , wherein the sequence of user inputs is received via a virtual keyboard. | 0.816923 |
7,818,340 | 1 | 5 | 1. A computer-implemented method comprising: interfacing with a search engine, the search engine to produce search results from one or more content datastores by matching a search query with content items stored in the one or more content datastores; receiving a sponsored concept from a sponsoring company at a server computer via a data network; receiving a first search query corresponding to a search by a first user, the first search query being used by the search engine to match with content items stored in the one or more content datastores, the first search query also being used to determine if the sponsored concept and the first search query fit within match criteria; determining, by use of a data processor, if the sponsored concept and the first search query fit within match criteria; generating for the first user, by use of the data processor, if the sponsored concept and the first search query fit within match criteria, a first link enabling the first user to initiate a conversation between the first user and an agent of the sponsoring company, the first link being a user interface element that can be activated by the first user; initiating a conversation between the first user and the agent of the sponsoring company upon activation of the first link; receiving a second search query corresponding to a search by a second user, the second search query being used by the search engine to match with content items stored in the one or more content datastores; determining if the first search query and the second search query fit within match criteria; generating for the first user, if the first search query and the second search query fit within match criteria, a second link enabling the first user to initiate a conversation between the first user and the second user, the second link being a user interface element that can be activated by the first user, the second link including at least a portion of the second search query from the second user; and initiating a conversation between the first user and the second user upon activation of the second link. | 1. A computer-implemented method comprising: interfacing with a search engine, the search engine to produce search results from one or more content datastores by matching a search query with content items stored in the one or more content datastores; receiving a sponsored concept from a sponsoring company at a server computer via a data network; receiving a first search query corresponding to a search by a first user, the first search query being used by the search engine to match with content items stored in the one or more content datastores, the first search query also being used to determine if the sponsored concept and the first search query fit within match criteria; determining, by use of a data processor, if the sponsored concept and the first search query fit within match criteria; generating for the first user, by use of the data processor, if the sponsored concept and the first search query fit within match criteria, a first link enabling the first user to initiate a conversation between the first user and an agent of the sponsoring company, the first link being a user interface element that can be activated by the first user; initiating a conversation between the first user and the agent of the sponsoring company upon activation of the first link; receiving a second search query corresponding to a search by a second user, the second search query being used by the search engine to match with content items stored in the one or more content datastores; determining if the first search query and the second search query fit within match criteria; generating for the first user, if the first search query and the second search query fit within match criteria, a second link enabling the first user to initiate a conversation between the first user and the second user, the second link being a user interface element that can be activated by the first user, the second link including at least a portion of the second search query from the second user; and initiating a conversation between the first user and the second user upon activation of the second link. 5. The computer-implemented method as claimed in claim 1 wherein the conversation initiated upon activation of the first link enables text communication. | 0.745 |
8,375,308 | 16 | 17 | 16. The method of claim 1 , wherein the conversation topic is changed when at least one of the plurality of users affirmatively acts to change the conversation topic in response to the at least one indication of support for the request to change the conversation topic. | 16. The method of claim 1 , wherein the conversation topic is changed when at least one of the plurality of users affirmatively acts to change the conversation topic in response to the at least one indication of support for the request to change the conversation topic. 17. The method of claim 16 , wherein the at least one of the plurality of users affirmatively acting to change the conversation topic comprises the at least one of the plurality of users selecting a new conversation topic. | 0.5 |
8,571,857 | 16 | 20 | 16. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving, from a separate entity, of a request to generate a model, input data and a seed model; receiving a cost function associated with generation of the model, the cost function indicating accuracy and one of speed and memory usage, wherein the cost function is formulated as:
Accscore( ASR ( Xi ))= f ( Xi )→word accuracy and speed where the following definitions apply:
f min( Xi )=−1* (word accuracy−β*speed),
speed=(CPU time)/(audio time), β=a weighting factor to speed that provides a tradeoff between accuracy and speed, Xi=a set of parameters that affect accuracy and speed, such as beam width, LM scale, MAP multiplier, maximum active arcs, duration scale; processing the input data based on the seed model and based on parameters that modify the accuracy and the one of speed and memory usage of the cost function, to yield an updated model; and outputting the updated model. | 16. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving, from a separate entity, of a request to generate a model, input data and a seed model; receiving a cost function associated with generation of the model, the cost function indicating accuracy and one of speed and memory usage, wherein the cost function is formulated as:
Accscore( ASR ( Xi ))= f ( Xi )→word accuracy and speed where the following definitions apply:
f min( Xi )=−1* (word accuracy−β*speed),
speed=(CPU time)/(audio time), β=a weighting factor to speed that provides a tradeoff between accuracy and speed, Xi=a set of parameters that affect accuracy and speed, such as beam width, LM scale, MAP multiplier, maximum active arcs, duration scale; processing the input data based on the seed model and based on parameters that modify the accuracy and the one of speed and memory usage of the cost function, to yield an updated model; and outputting the updated model. 20. The computer-readable storage device of claim 16 , wherein processing the input data comprises a first pass for retraining, a second pass for vocal-tract length normalization, and a third pass for constrained model adaptation. | 0.514768 |
9,589,561 | 8 | 9 | 8. The method as claimed in claim 1 , wherein, in response to the plurality of similar words which are similar to the uttered voice being determined, grouping the plurality of determined similar words into a similar word group. | 8. The method as claimed in claim 1 , wherein, in response to the plurality of similar words which are similar to the uttered voice being determined, grouping the plurality of determined similar words into a similar word group. 9. The method as claimed in claim 8 , wherein, in response to the similar words being grouped into a similar word group, determining all words in the similar word group as a similar word related to the uttered voice. | 0.5 |
8,849,870 | 1 | 2 | 1. A method comprising: receiving current context information related to a first device; accessing a context profile and a security profile associated with the first device; developing a composite context tree based on at least a portion of the current context information related to the first device and context information related to at least one other device based at least in part on the context profile defining, for a current context of the first device, aspects of the current context information to be utilized for the developing of the composite context tree, wherein developing the composite context tree comprises generating a schema based on the security profile and the context profile in which the schema defines the portion of the current context information and applying the schema to a context tree including the current context information such that only a portion of the context tree defined by the schema is visible to an entity developing the composite context tree; determining a context change has occurred with respect to the first device; determining whether the context change to the composite context tree is allowed based on the security profile and the context profile; wherein in an instance in which the context change is determined to be allowed, the context tree is updated for the context change; and wherein in an instance in which the context change is determined to not be allowed, the context tree is not updated for the context change. | 1. A method comprising: receiving current context information related to a first device; accessing a context profile and a security profile associated with the first device; developing a composite context tree based on at least a portion of the current context information related to the first device and context information related to at least one other device based at least in part on the context profile defining, for a current context of the first device, aspects of the current context information to be utilized for the developing of the composite context tree, wherein developing the composite context tree comprises generating a schema based on the security profile and the context profile in which the schema defines the portion of the current context information and applying the schema to a context tree including the current context information such that only a portion of the context tree defined by the schema is visible to an entity developing the composite context tree; determining a context change has occurred with respect to the first device; determining whether the context change to the composite context tree is allowed based on the security profile and the context profile; wherein in an instance in which the context change is determined to be allowed, the context tree is updated for the context change; and wherein in an instance in which the context change is determined to not be allowed, the context tree is not updated for the context change. 2. The method of claim 1 , wherein developing the composite context tree comprises applying the security profile and the context profile to a context tree including the current context information to define a node list providing the portion of the current context information to be used for composite context tree development. | 0.5 |
9,213,911 | 1 | 6 | 1. An apparatus for recognizing text on a surface, the apparatus comprising: an image sensor configured to capture images from an environment of a user; and at least one processor device configured to: identify the surface is a curved surface based on at least one of the images; determine that text is found on the identified curved surface; receive a first image of a first perspective of text on the curved surface, wherein the first image includes a first portion of text on the curved surface, the first portion of text including skewed characters that are unrecognizable in an optical character recognition process due to a curvature of the first portion of text on the curved surface viewed from the first perspective, and wherein the first image includes a second portion of text recognizable in the optical character recognition process; receive a second image of a second perspective of the text on the curved surface, wherein the second image includes the first portion of text in a form capable of recognition in the optical character recognition process; perform optical character recognition on the second portion of text in the first image and the first portion of text in the second image; combine results of the optical character recognition on the second portion of text in the first image and on the first portion of text in the second image; and provide the user with a recognized representation of the text, including a recognized representation of the second portion of text in the first image and the first portion of text in the second image. | 1. An apparatus for recognizing text on a surface, the apparatus comprising: an image sensor configured to capture images from an environment of a user; and at least one processor device configured to: identify the surface is a curved surface based on at least one of the images; determine that text is found on the identified curved surface; receive a first image of a first perspective of text on the curved surface, wherein the first image includes a first portion of text on the curved surface, the first portion of text including skewed characters that are unrecognizable in an optical character recognition process due to a curvature of the first portion of text on the curved surface viewed from the first perspective, and wherein the first image includes a second portion of text recognizable in the optical character recognition process; receive a second image of a second perspective of the text on the curved surface, wherein the second image includes the first portion of text in a form capable of recognition in the optical character recognition process; perform optical character recognition on the second portion of text in the first image and the first portion of text in the second image; combine results of the optical character recognition on the second portion of text in the first image and on the first portion of text in the second image; and provide the user with a recognized representation of the text, including a recognized representation of the second portion of text in the first image and the first portion of text in the second image. 6. The apparatus of claim 1 , wherein the optical character recognition is performed separately on the first image and the second image. | 0.803468 |
8,332,206 | 1 | 8 | 1. A computer-implemented method for providing a definition or a translation, comprising: receiving an input indicating a word selected by a user; determining a user's language; communicating the determined user's language to a definition server and a translation server; sending, simultaneously, a definition request for the word to the definition server along with sending a translation request for the word to the translation server; receiving a response to the definition request from the definition server, wherein the response to the definition request indicates whether there is at least one definition of the word in the user's language; receiving a response to the translation request from the translation server, wherein the response to the translation request indicates whether there is at least one translation of the word in the user's language, wherein the response to the definition request and the response to the translation request are received simultaneously; determining whether to provide the user with a definition or a translation of the word based on the responses from the definition server and the translation server, wherein the determination comprises: determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language; and determining to provide the user with the translation of the word when the response to the definition request indicates that there is no definition of the word in the user's language and the response to the translation request includes at least one translation of the word in the user's language; and providing the user with the definition or the translation of the word based on the determination of whether to provide the user with a definition or a translation of the word, wherein the providing comprises a bubble showing the at least one definition or the at least one translation of the selected word. | 1. A computer-implemented method for providing a definition or a translation, comprising: receiving an input indicating a word selected by a user; determining a user's language; communicating the determined user's language to a definition server and a translation server; sending, simultaneously, a definition request for the word to the definition server along with sending a translation request for the word to the translation server; receiving a response to the definition request from the definition server, wherein the response to the definition request indicates whether there is at least one definition of the word in the user's language; receiving a response to the translation request from the translation server, wherein the response to the translation request indicates whether there is at least one translation of the word in the user's language, wherein the response to the definition request and the response to the translation request are received simultaneously; determining whether to provide the user with a definition or a translation of the word based on the responses from the definition server and the translation server, wherein the determination comprises: determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language; and determining to provide the user with the translation of the word when the response to the definition request indicates that there is no definition of the word in the user's language and the response to the translation request includes at least one translation of the word in the user's language; and providing the user with the definition or the translation of the word based on the determination of whether to provide the user with a definition or a translation of the word, wherein the providing comprises a bubble showing the at least one definition or the at least one translation of the selected word. 8. The method of claim 1 , wherein providing the user with the definition or the translation of the word comprises displaying the definition or the translation of the word to the user. | 0.864106 |
6,067,282 | 1 | 4 | 1. An information recording medium having a management information area and recording information area, the recording information area including a plurality of record information pieces constituting a hierarchical structure comprising a plurality of hierarchical layers; the management information area including: a layer information piece for specifying one of the plurality of hierarchical layers; a kind information piece for indicating a kind of information relating to one of the record information pieces; a text group including a plurality of text information comprising a plurality of layer related texts and a plurality of record information related texts, at least one of the plurality of layer related texts describing information related to the layer specified by the layer information piece, and at least one of the plurality of record information related texts describing information related to the kind of information indicated by the kind information piece; and a text arrangement information piece, arranged in pair with one of the layer information piece and the kind information piece, indicating a position of a text information corresponding to the paired one of the layer information piece and the kind information piece. | 1. An information recording medium having a management information area and recording information area, the recording information area including a plurality of record information pieces constituting a hierarchical structure comprising a plurality of hierarchical layers; the management information area including: a layer information piece for specifying one of the plurality of hierarchical layers; a kind information piece for indicating a kind of information relating to one of the record information pieces; a text group including a plurality of text information comprising a plurality of layer related texts and a plurality of record information related texts, at least one of the plurality of layer related texts describing information related to the layer specified by the layer information piece, and at least one of the plurality of record information related texts describing information related to the kind of information indicated by the kind information piece; and a text arrangement information piece, arranged in pair with one of the layer information piece and the kind information piece, indicating a position of a text information corresponding to the paired one of the layer information piece and the kind information piece. 4. The medium according to claim 1, further comprising an uppermost layer information piece indicating a recording position of the layer information piece corresponding to the highest layer out of the plurality of hierarchical layers. | 0.737079 |
8,315,850 | 13 | 14 | 13. The system of claim 8 , further comprising: receiving a request from a client, the request including the document address; retrieving the translated text data in the second language from the document translation database based on the document address; sending the translated text data in the second language to the client wherein the client renders the translated text data in the second language. | 13. The system of claim 8 , further comprising: receiving a request from a client, the request including the document address; retrieving the translated text data in the second language from the document translation database based on the document address; sending the translated text data in the second language to the client wherein the client renders the translated text data in the second language. 14. The system of claim 13 , wherein the client renders the translated text data in the second language in a browser executing on the client, and wherein the document address is an URL. | 0.5 |
8,396,701 | 12 | 13 | 12. The system of claim 9 , wherein the specification file is used in a different specification file associated with the larger assembly. | 12. The system of claim 9 , wherein the specification file is used in a different specification file associated with the larger assembly. 13. The system of claim 12 , wherein the different specification file that is associated with the larger assembly is stored in a software library. | 0.5 |
8,949,878 | 15 | 16 | 15. A parental control system for an electronic device to filter objectionable material from a multimedia program including plural segments, comprising: a learning module to generate filter criteria learned based on user instructions by examples of objectionable content; a splitting mechanism that splits the multimedia program into plural components; a transcript analysis module that extracts first audible features and text from a transcript analysis component within the plural components; a visual analysis module that extracts video features from a visual analysis component within the plural components; an audio analysis module that extracts second audible features from an audio analysis component within the plural components; an analyzer which processes each segment amongst the segments, according to the learned filter criteria generated by the learning module and the extracted features, and generates a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to the segment, and which generates a respective control signal when the numeric ranking exceeds a threshold; and a filter, which processes one of the segments of the multimedia program in response to a received respective control signal. | 15. A parental control system for an electronic device to filter objectionable material from a multimedia program including plural segments, comprising: a learning module to generate filter criteria learned based on user instructions by examples of objectionable content; a splitting mechanism that splits the multimedia program into plural components; a transcript analysis module that extracts first audible features and text from a transcript analysis component within the plural components; a visual analysis module that extracts video features from a visual analysis component within the plural components; an audio analysis module that extracts second audible features from an audio analysis component within the plural components; an analyzer which processes each segment amongst the segments, according to the learned filter criteria generated by the learning module and the extracted features, and generates a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to the segment, and which generates a respective control signal when the numeric ranking exceeds a threshold; and a filter, which processes one of the segments of the multimedia program in response to a received respective control signal. 16. The parental control system as recited in claim 15 , wherein the filter modifies one of the first and second audible features of the respective segment. | 0.820276 |
8,566,783 | 13 | 15 | 13. An information processing system for determining a navigation path for a constraint language editor, the information processing system comprising: a memory; a processor communicatively coupled to the memory; and a navigation helper coupled to the memory and the processor, the navigation helper being configured for: accessing at least one software model of at least one software application; parsing, with a computer, the software model to determine if there is at least one occurrence of a class inheritance, an association, and an association inheritance is in the software model; based upon the occurrence of the class inheritance, accessing a data list from a class inheritance database and performing type conversion on the data list which has been accessed; based upon the occurrence of the association, accessing a data list from an association database; and based upon the occurrence of the association inheritance, accessing a data list from an association inheritance database; loading the data list based upon the occurrence of the class inheritance, the association, and the association inheritance in the software model into a navigation path calculator; receiving user input into the navigation path calculator, the user input including a navigation starting point, a navigation ending point; and calculating, with the navigation path calculator, a navigation path with model or instance information including attributes of objects, operations of objects, associations between objects, and generations between objects. | 13. An information processing system for determining a navigation path for a constraint language editor, the information processing system comprising: a memory; a processor communicatively coupled to the memory; and a navigation helper coupled to the memory and the processor, the navigation helper being configured for: accessing at least one software model of at least one software application; parsing, with a computer, the software model to determine if there is at least one occurrence of a class inheritance, an association, and an association inheritance is in the software model; based upon the occurrence of the class inheritance, accessing a data list from a class inheritance database and performing type conversion on the data list which has been accessed; based upon the occurrence of the association, accessing a data list from an association database; and based upon the occurrence of the association inheritance, accessing a data list from an association inheritance database; loading the data list based upon the occurrence of the class inheritance, the association, and the association inheritance in the software model into a navigation path calculator; receiving user input into the navigation path calculator, the user input including a navigation starting point, a navigation ending point; and calculating, with the navigation path calculator, a navigation path with model or instance information including attributes of objects, operations of objects, associations between objects, and generations between objects. 15. The information processing system of claim 13 , wherein prior to calculating the navigation path, further comprising: receiving user input into the navigation calculator, the user input including a navigation ending point, and a maximum step of navigation. | 0.726891 |
7,512,878 | 8 | 10 | 8. The method of claim 1 , wherein at least one of the drivers is further associated with different communication protocols. | 8. The method of claim 1 , wherein at least one of the drivers is further associated with different communication protocols. 10. The method of claim 8 , wherein the plurality of drivers allow the multiple applications to access the package regardless of a file format associated with each of the multiple applications. | 0.5199 |
9,779,072 | 9 | 16 | 9. A system comprising one or more computers and one or more non-transitory computer-readable 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 plurality of different document versions of a particular document; identifying a first type of metadata that is associated with each document version of the plurality of different document versions, wherein the first type of metadata includes data that describes a source that provides each document version of the plurality of different document versions; identifying, by the computer system, a second type of metadata that is associated with each document version of the plurality of different document versions, wherein the second type of metadata describes a feature of each document version of the plurality of different document versions other than the source of the document version; for each document version of the plurality of different document versions, applying a priority rule to the first type of metadata and the second type of metadata, to generate a priority value; selecting a particular document version, of the plurality of different document versions, based on the priority values generated for each document version of the plurality of different document versions; and providing the particular document version for presentation. | 9. A system comprising one or more computers and one or more non-transitory computer-readable 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 plurality of different document versions of a particular document; identifying a first type of metadata that is associated with each document version of the plurality of different document versions, wherein the first type of metadata includes data that describes a source that provides each document version of the plurality of different document versions; identifying, by the computer system, a second type of metadata that is associated with each document version of the plurality of different document versions, wherein the second type of metadata describes a feature of each document version of the plurality of different document versions other than the source of the document version; for each document version of the plurality of different document versions, applying a priority rule to the first type of metadata and the second type of metadata, to generate a priority value; selecting a particular document version, of the plurality of different document versions, based on the priority values generated for each document version of the plurality of different document versions; and providing the particular document version for presentation. 16. The system of claim 9 , wherein the first type of metadata includes an address of a server that provides each document version of the plurality of different versions. | 0.813596 |
8,391,618 | 1 | 6 | 1. A non-transitory computer-readable storage medium that stores program instructions computer-executable to implement: determining a plurality of semantic category scores for a digital image via application of a corresponding plurality of classifiers; automatically determining a semantic category profile for the image based on the plurality of semantic category scores, wherein the semantic category profile characterizes semantic content of the image, and is useable to perform semantic based operations with respect to the image; and performing a semantic based operation wherein the semantic based operation comprises: a search operation based on a semantic similarity measure for a plurality of semantic category profiles for a plurality of digital images, wherein the plurality of semantic category profiles includes the semantic category profile for the image; or a keyword operation based on a semantic similarity measure for a plurality of semantic category profiles for a plurality of digital images, wherein the plurality of semantic category profiles includes the semantic category profile for the image. | 1. A non-transitory computer-readable storage medium that stores program instructions computer-executable to implement: determining a plurality of semantic category scores for a digital image via application of a corresponding plurality of classifiers; automatically determining a semantic category profile for the image based on the plurality of semantic category scores, wherein the semantic category profile characterizes semantic content of the image, and is useable to perform semantic based operations with respect to the image; and performing a semantic based operation wherein the semantic based operation comprises: a search operation based on a semantic similarity measure for a plurality of semantic category profiles for a plurality of digital images, wherein the plurality of semantic category profiles includes the semantic category profile for the image; or a keyword operation based on a semantic similarity measure for a plurality of semantic category profiles for a plurality of digital images, wherein the plurality of semantic category profiles includes the semantic category profile for the image. 6. The non-transitory computer-readable storage medium of claim 1 , wherein the semantic category profile for the image comprises the plurality of semantic category scores. | 0.916828 |
10,089,295 | 1 | 5 | 1. A method for generating a digital magazine, the method comprising: storing a plurality of page templates, each page template including one or more regions, each region configured to present one or more content items, one or more of the plurality of page templates including one or more regions, each region associated with a height that is based on a width of a display area; receiving a request from a client device to present one or more content items from one or more sources in the digital magazine to a user; retrieving information describing content items associated with the digital magazine; retrieving information describing user interaction with one or more content items associated with the digital magazine; identifying one or more page templates previously associated with the digital magazine from the one or more page templates; determining weights associated with characteristics of page templates based at least in part on characteristics of the identified one or more page templates previously associated with the digital magazine; selecting one or more candidate page templates by applying the determined weights to one or more selected from a group consisting of: the identified one or more page templates previously associated with the digital magazine, one or more characteristics of the content items associated with the digital magazine, the user interaction with the one or more content items associated with the digital magazine, and any combination thereof; generating a score associated with each of the one or more candidate page templates, where a score associated with a candidate page template is based on a number of the content items, characteristics of the one or more content items, and a number of regions in the page template; selecting a display page template based on the scores associated with the one or more candidate page templates; and generating a section of the digital magazine for presentation via the client device, the section including one or more regions each presenting one or more content items placed in positions specified by the one or more regions of the display page template. | 1. A method for generating a digital magazine, the method comprising: storing a plurality of page templates, each page template including one or more regions, each region configured to present one or more content items, one or more of the plurality of page templates including one or more regions, each region associated with a height that is based on a width of a display area; receiving a request from a client device to present one or more content items from one or more sources in the digital magazine to a user; retrieving information describing content items associated with the digital magazine; retrieving information describing user interaction with one or more content items associated with the digital magazine; identifying one or more page templates previously associated with the digital magazine from the one or more page templates; determining weights associated with characteristics of page templates based at least in part on characteristics of the identified one or more page templates previously associated with the digital magazine; selecting one or more candidate page templates by applying the determined weights to one or more selected from a group consisting of: the identified one or more page templates previously associated with the digital magazine, one or more characteristics of the content items associated with the digital magazine, the user interaction with the one or more content items associated with the digital magazine, and any combination thereof; generating a score associated with each of the one or more candidate page templates, where a score associated with a candidate page template is based on a number of the content items, characteristics of the one or more content items, and a number of regions in the page template; selecting a display page template based on the scores associated with the one or more candidate page templates; and generating a section of the digital magazine for presentation via the client device, the section including one or more regions each presenting one or more content items placed in positions specified by the one or more regions of the display page template. 5. The method of claim 1 , wherein the user interaction with the one or more content items associated with the digital magazine includes a length of time to interact with a content item based at least in part on prior interactions between the user and content items associated with the digital magazine previously presented to the user. | 0.809308 |
7,653,545 | 7 | 8 | 7. A method as claimed in claim 1 , wherein said grammar is hierarchical and said rules include terminal and/or non-terminal symbols, whereby said rules refer to lower level rules to resolve non-terminal symbols. | 7. A method as claimed in claim 1 , wherein said grammar is hierarchical and said rules include terminal and/or non-terminal symbols, whereby said rules refer to lower level rules to resolve non-terminal symbols. 8. A method as claimed in claim 7 , wherein said rule creating step includes generating a non-terminal symbol rule from correlated symbols and slot specification rules. | 0.5 |
9,020,824 | 18 | 19 | 18. A method comprising: initiating contact with a customer of an entity; receiving a natural language input sequence from the customer responsive to a natural language query; identifying keywords from the natural language input sequence; contextualizing the identified keywords to identify a scenario from a plurality of scenarios in a memory, each of the scenarios representing a category of customer messages; accessing a database in a memory to select a plurality of variable length video clips based on the keywords and the scenario; retrieving the selected video clips from the database; and combining the retrieved video clips to generate on-the-fly a video presentation. | 18. A method comprising: initiating contact with a customer of an entity; receiving a natural language input sequence from the customer responsive to a natural language query; identifying keywords from the natural language input sequence; contextualizing the identified keywords to identify a scenario from a plurality of scenarios in a memory, each of the scenarios representing a category of customer messages; accessing a database in a memory to select a plurality of variable length video clips based on the keywords and the scenario; retrieving the selected video clips from the database; and combining the retrieved video clips to generate on-the-fly a video presentation. 19. The method of claim 18 , further comprising receiving a standard language input sequence from the customer responsive to a standard language query, wherein the keywords are identified from both the natural language input sequence and the standard language input sequence. | 0.5 |
8,812,645 | 1 | 2 | 1. A computer apparatus comprising: a plurality of nodes each having a memory and at least one processor; a database residing in the memory accessible by a query from a node of the plurality of nodes; a plurality of independent networks connecting the node of the plurality of nodes to the database; and a query optimizer residing in the memory and executed by the at least one processor, wherein the query optimizer creates an optimized query that splits the query to use multiple independent networks of the plurality of independent networks in executing the optimized query to access the database, and wherein the query optimizer uses plan cache statistics from previously executed queries to determine whether to use the multiple independent networks to optimize the query; wherein the plan cache statistics comprises: query identification (ID), execution time, nodes involved, and estimated number of bytes for the query; and wherein the query optimizer uses a network file containing network file information for the multiple independent networks comprising: network ID, a timestamp; current utilization, availability, latency, and retransmits. | 1. A computer apparatus comprising: a plurality of nodes each having a memory and at least one processor; a database residing in the memory accessible by a query from a node of the plurality of nodes; a plurality of independent networks connecting the node of the plurality of nodes to the database; and a query optimizer residing in the memory and executed by the at least one processor, wherein the query optimizer creates an optimized query that splits the query to use multiple independent networks of the plurality of independent networks in executing the optimized query to access the database, and wherein the query optimizer uses plan cache statistics from previously executed queries to determine whether to use the multiple independent networks to optimize the query; wherein the plan cache statistics comprises: query identification (ID), execution time, nodes involved, and estimated number of bytes for the query; and wherein the query optimizer uses a network file containing network file information for the multiple independent networks comprising: network ID, a timestamp; current utilization, availability, latency, and retransmits. 2. The computer apparatus of claim 1 wherein the optimized query utilizes additional networks to increase communication speed to allow the query to execute faster. | 0.672691 |
9,928,476 | 1 | 4 | 1. A system for transforming a database of products, the system comprising: a first data storage medium storing a raw product database that describes a plurality of products, wherein the raw product database includes, for each of the plurality of products, attributes associated with the products, wherein each attribute has a value that includes a word; one or more processors; a second data storage medium bearing instructions that, when executed on the one or more processors, cause the one or more processors to process the raw product database to provide a standardized data structure that contains standardized values for the attributes of the products for improved analytics by performing the steps of: identify a dictionary comprising each word that appears as a value of at least one attribute of at least one product in the raw product database; partition the dictionary into synonym classes of words, each synonym class forming an equivalence class of mutually equivalent terms for a product attribute, wherein when one of the values appears in two or more synonym classes, the value is stored with a context for differentiating between the two or more synonym classes; select a representative word from each of the synonym classes, thereby associating each word in the dictionary with a corresponding representative word; identify a collection of replacement rules, each of which replaces a target word from one of the synonym classes with the corresponding representative word, wherein the replacement rules comprise global rules, multi-word phrase rules, attribute constant rules, and single-word replacement rules; and for each product in the raw product database, apply the replacement rules to one or more attributes of the product, thereby producing a standardized product database, wherein the global rules are applied before the multi-word phrase rules, the multi-word phrase rules are applied before the attribute constant rules, and the attribute constant rules are applied before the single-word replacement rules, wherein the replacement rules include at least one replacement rule for numerical values that is applied sequentially and repeatedly until a predetermined stopping condition is reached. | 1. A system for transforming a database of products, the system comprising: a first data storage medium storing a raw product database that describes a plurality of products, wherein the raw product database includes, for each of the plurality of products, attributes associated with the products, wherein each attribute has a value that includes a word; one or more processors; a second data storage medium bearing instructions that, when executed on the one or more processors, cause the one or more processors to process the raw product database to provide a standardized data structure that contains standardized values for the attributes of the products for improved analytics by performing the steps of: identify a dictionary comprising each word that appears as a value of at least one attribute of at least one product in the raw product database; partition the dictionary into synonym classes of words, each synonym class forming an equivalence class of mutually equivalent terms for a product attribute, wherein when one of the values appears in two or more synonym classes, the value is stored with a context for differentiating between the two or more synonym classes; select a representative word from each of the synonym classes, thereby associating each word in the dictionary with a corresponding representative word; identify a collection of replacement rules, each of which replaces a target word from one of the synonym classes with the corresponding representative word, wherein the replacement rules comprise global rules, multi-word phrase rules, attribute constant rules, and single-word replacement rules; and for each product in the raw product database, apply the replacement rules to one or more attributes of the product, thereby producing a standardized product database, wherein the global rules are applied before the multi-word phrase rules, the multi-word phrase rules are applied before the attribute constant rules, and the attribute constant rules are applied before the single-word replacement rules, wherein the replacement rules include at least one replacement rule for numerical values that is applied sequentially and repeatedly until a predetermined stopping condition is reached. 4. The system of claim 1 , in which the rules are applied repeatedly until a pre-determined condition is met. | 0.882035 |
9,468,852 | 7 | 23 | 7. The method of claim 1 wherein: capturing information about the user includes monitoring actions of the user; and automatically determining is based, at least in part, on the actions of the user. | 7. The method of claim 1 wherein: capturing information about the user includes monitoring actions of the user; and automatically determining is based, at least in part, on the actions of the user. 23. The method of claim 7 further comprising randomly inserting questions that relate to play personality or intrinsic motivators with other questions presented to the user within the online game environment. | 0.551724 |
9,575,994 | 1 | 4 | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. 4. The method as of claim 1 , wherein the mapping of the detected structures includes comparing the known structures of the knowledge database with the detected structures, selecting one of the known structures that shows a relatively highest similarity to the detected structures compared to the other known structures, and assigning the first URI to the detected structures. | 0.709877 |
9,542,386 | 1 | 6 | 1. An entailment evaluation device comprising: a generation unit configured to generate first information indicating at least an order of occurrence of events of first and second simple sentences included in a hypothesis text and generates second information indicating at least an order of occurrence of events of third and fourth simple sentences included in a target text, the third simple sentence being related to the first simple sentence, the fourth simple sentence being related to the second simple sentence; a calculation unit configured to obtain a calculation result by comparing, based on the first and second information, the order of occurrence of events of first and second simple sentences and the order of occurrence of events of third and fourth simple sentences; and a determination unit configured to determine, based on at least the calculation result, whether or not the target text entails the hypothesis text. | 1. An entailment evaluation device comprising: a generation unit configured to generate first information indicating at least an order of occurrence of events of first and second simple sentences included in a hypothesis text and generates second information indicating at least an order of occurrence of events of third and fourth simple sentences included in a target text, the third simple sentence being related to the first simple sentence, the fourth simple sentence being related to the second simple sentence; a calculation unit configured to obtain a calculation result by comparing, based on the first and second information, the order of occurrence of events of first and second simple sentences and the order of occurrence of events of third and fourth simple sentences; and a determination unit configured to determine, based on at least the calculation result, whether or not the target text entails the hypothesis text. 6. The entailment evaluation device according to claim 1 , wherein the extraction unit identifies a first simple sentence distance between the first and third simple sentences and a second simple sentence distance between the second and fourth simple sentences, and the determination unit determines, based on at least the calculation result and first and second simple sentence distances, whether or not the target text entails the hypothesis text. | 0.729192 |
9,679,561 | 16 | 18 | 16. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving speech from a user as part of a speech dialog between the user and a speech recognition service; identifying, based on the speech, a speech pattern of the user; identifying, based on the speech pattern of the user, a plurality of speech recognition models stored in a cloud computing storage environment, each speech recognition model of the plurality of speech recognition models being from a respective speech recognition domain; combining the plurality of speech recognition models, to yield a multi-domain combined speech recognition model; identifying in the speech a specific speech recognition domain, wherein the specific speech recognition domain does not match a specific speech recognition model in the plurality of speech recognition models; receiving sample data associated with the specific speech recognition domain, wherein the sample data is independent of the speech dialog between the user and the speech recognition service; when the sample data is more than a minimum threshold generating a new domain-specific speech recognition model for the specific speech recognition domain; and when the sample data is less than the minimum threshold, modifying the multi-domain combined speech recognition model specifically to the specific speech recognition domain by weighting components of the multi-domain combined speech recognition model associated with the specific speech recognition domain to have more influence in recognition of the speech from the user. | 16. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving speech from a user as part of a speech dialog between the user and a speech recognition service; identifying, based on the speech, a speech pattern of the user; identifying, based on the speech pattern of the user, a plurality of speech recognition models stored in a cloud computing storage environment, each speech recognition model of the plurality of speech recognition models being from a respective speech recognition domain; combining the plurality of speech recognition models, to yield a multi-domain combined speech recognition model; identifying in the speech a specific speech recognition domain, wherein the specific speech recognition domain does not match a specific speech recognition model in the plurality of speech recognition models; receiving sample data associated with the specific speech recognition domain, wherein the sample data is independent of the speech dialog between the user and the speech recognition service; when the sample data is more than a minimum threshold generating a new domain-specific speech recognition model for the specific speech recognition domain; and when the sample data is less than the minimum threshold, modifying the multi-domain combined speech recognition model specifically to the specific speech recognition domain by weighting components of the multi-domain combined speech recognition model associated with the specific speech recognition domain to have more influence in recognition of the speech from the user. 18. The computer-readable storage device of claim 16 , wherein the modifying of the multi-domain combined speech recognition model further comprises sampling the speech. | 0.692727 |
7,668,340 | 1 | 6 | 1. A control method, comprising the steps of: storing, in a memory, information relating to a plurality of gestures, the stored information including a plurality of geometric templates associated with static gestures and a plurality of dynamic models associated with dynamic gestures; receiving information from an image sensor about the position, orientation or x-y movement of a gesture-making target; and providing at least one processor to perform the following operations: a) identify the gesture as a static gesture or no gesture if the x-y movement is below a threshold amount, or identify the gesture as a dynamic gesture if the x-y movement is above the threshold amount; b) compare the position or orientation information of the gesture-making target to the geometric templates to determine if a particular static gesture is being made or, if the gesture is identified as a dynamic gesture, compare the position, orientation or x-y movement information to the stored dynamic models to determine if a particular dynamic gesture is being made; and c) output a control signal if a particular static or dynamic gesture is determined to control a computer or machine. | 1. A control method, comprising the steps of: storing, in a memory, information relating to a plurality of gestures, the stored information including a plurality of geometric templates associated with static gestures and a plurality of dynamic models associated with dynamic gestures; receiving information from an image sensor about the position, orientation or x-y movement of a gesture-making target; and providing at least one processor to perform the following operations: a) identify the gesture as a static gesture or no gesture if the x-y movement is below a threshold amount, or identify the gesture as a dynamic gesture if the x-y movement is above the threshold amount; b) compare the position or orientation information of the gesture-making target to the geometric templates to determine if a particular static gesture is being made or, if the gesture is identified as a dynamic gesture, compare the position, orientation or x-y movement information to the stored dynamic models to determine if a particular dynamic gesture is being made; and c) output a control signal if a particular static or dynamic gesture is determined to control a computer or machine. 6. The method of claim 1 , wherein at least a portion of the information received about the position, orientation or x-y movement of the gesture-making target is delved through an accelerometer. | 0.538095 |
8,667,051 | 1 | 2 | 1. A method for communication processing, the method comprising: storing, by a client device, information records comprising a table of one or more keywords and associated operative functions, the table having at least one keyword programmed by a user of the client device; determining, by the client device, whether audio or text data of a broadcast includes one or more broadcasted keywords; and performing, by the client device, a series of the associated operative functions based on said one or more broadcasted keywords in response to determining that the one or more broadcasted keywords match one or more of the keywords in the table, while concurrently presenting output corresponding to said audio or text data during said broadcast, wherein the series of said associated operative functions comprises at least four of: placing a call using the one or more broadcasted keywords; comparing a performance history associated with the one or more broadcasted keywords; storing contact information derived from the one or more broadcasted keywords; determining a domain name having the one or more broadcasted keywords at least partially therein and generating a hyperlink from the domain name; searching a database device for advertising associated with the one or more broadcasted keywords; and performing an Internet search with the one or more broadcasted keywords. | 1. A method for communication processing, the method comprising: storing, by a client device, information records comprising a table of one or more keywords and associated operative functions, the table having at least one keyword programmed by a user of the client device; determining, by the client device, whether audio or text data of a broadcast includes one or more broadcasted keywords; and performing, by the client device, a series of the associated operative functions based on said one or more broadcasted keywords in response to determining that the one or more broadcasted keywords match one or more of the keywords in the table, while concurrently presenting output corresponding to said audio or text data during said broadcast, wherein the series of said associated operative functions comprises at least four of: placing a call using the one or more broadcasted keywords; comparing a performance history associated with the one or more broadcasted keywords; storing contact information derived from the one or more broadcasted keywords; determining a domain name having the one or more broadcasted keywords at least partially therein and generating a hyperlink from the domain name; searching a database device for advertising associated with the one or more broadcasted keywords; and performing an Internet search with the one or more broadcasted keywords. 2. The method, as set forth in claim 1 , wherein performing, by the client device, the series of the associated operative functions comprises automatically performing the series of the associated operative functions with said one or more broadcasted keywords. | 0.71663 |
10,013,978 | 16 | 19 | 16. A method to invoke actions for sequence dependent operations in a voice activated data packet based computer network environment, comprising: receiving, by a natural language processor component executed by a data processing system data packets comprising an input audio signal detected by a sensor of a client computing device; identifying, by the natural language processor component, based on the input audio signal, a request and a trigger keyword corresponding to the request; determining, by a prediction component, a thread based on the trigger keyword and the request, the thread comprising a first action, a second action subsequent to the first action, and a third action subsequent to the second action; providing, by the prediction component, to a content selector component of the data processing system, an indication of the third action prior to occurrence of at least one of the first action and the second action; selecting, by the content selector component, based on the third action and the trigger keyword identified by the natural language processor, a content item via a real-time content selection process; obtaining, by an audio signal generator component executed by the data processing system, an output signal comprising the content item; and transmitting, via an interface of the data processing system, data packets comprising the output signal obtained by the audio signal generator component to cause an audio driver component executed by the client computing device to drive a speaker of at least one of the client computing device and a second client computing device to generate an acoustic wave corresponding to the output signal prior to occurrence of at least one of the first action and the second action. | 16. A method to invoke actions for sequence dependent operations in a voice activated data packet based computer network environment, comprising: receiving, by a natural language processor component executed by a data processing system data packets comprising an input audio signal detected by a sensor of a client computing device; identifying, by the natural language processor component, based on the input audio signal, a request and a trigger keyword corresponding to the request; determining, by a prediction component, a thread based on the trigger keyword and the request, the thread comprising a first action, a second action subsequent to the first action, and a third action subsequent to the second action; providing, by the prediction component, to a content selector component of the data processing system, an indication of the third action prior to occurrence of at least one of the first action and the second action; selecting, by the content selector component, based on the third action and the trigger keyword identified by the natural language processor, a content item via a real-time content selection process; obtaining, by an audio signal generator component executed by the data processing system, an output signal comprising the content item; and transmitting, via an interface of the data processing system, data packets comprising the output signal obtained by the audio signal generator component to cause an audio driver component executed by the client computing device to drive a speaker of at least one of the client computing device and a second client computing device to generate an acoustic wave corresponding to the output signal prior to occurrence of at least one of the first action and the second action. 19. The method of claim 16 , comprising: receiving, by the data processing system, from the client computing device, a data message that includes a response to the content item prior to occurrence of at least one of the first action and the second action. | 0.569257 |
7,729,899 | 1 | 2 | 1. An automated method for debugging training data used to train an automated language identifier, said method comprising: (a) collecting a text written in a predetermined language; (b) generating an occurrence count for each of a plurality of words, by counting the number of times each of said words is found within the text; (c) generating an occurrence ratio (OR) of each of said words by dividing the occurrence count by substantially the total number of words in each text; (d) repeating said (a), (b), and (c) to generate ORs for a plurality of texts; and (e) filtering, by a computer, words from one of said texts which have an occurrence ratio that is substantially distinct from corresponding occurrence ratios of an other of said texts, to generate a clean text. | 1. An automated method for debugging training data used to train an automated language identifier, said method comprising: (a) collecting a text written in a predetermined language; (b) generating an occurrence count for each of a plurality of words, by counting the number of times each of said words is found within the text; (c) generating an occurrence ratio (OR) of each of said words by dividing the occurrence count by substantially the total number of words in each text; (d) repeating said (a), (b), and (c) to generate ORs for a plurality of texts; and (e) filtering, by a computer, words from one of said texts which have an occurrence ratio that is substantially distinct from corresponding occurrence ratios of an other of said texts, to generate a clean text. 2. The method of claim 1 , wherein said repeating (d) is effected for a plurality of texts written in said predetermined language. | 0.701835 |
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