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8,352,467 | 16 | 17 | 16. The system of claim 15 , wherein the operations further comprise: annotating, with a name of the respective entity, indicia identifying each resource of the ranked search result set; and providing the indicia in a response to the search query. | 16. The system of claim 15 , wherein the operations further comprise: annotating, with a name of the respective entity, indicia identifying each resource of the ranked search result set; and providing the indicia in a response to the search query. 17. The system of claim 16 , wherein annotating further comprises: annotating, with the matching label term associated with each resource, the indicia identifying each resource of the ranked search result set. | 0.955475 |
8,214,387 | 10 | 12 | 10. A system in a mobile device for retrieving a media presentation associated with a rendered document, the system comprising: a data capture subsystem that optically or acoustically captures a first human-readable text-based portion of a rendered document and a second human-readable text-based portion of a rendered document; a digest subsystem that generates a digest of the first captured portion based at least in part on content of the text of the captured portion; an identification subsystem that locates a document identifier associated with an electronic counterpart to the rendered document based at least in part on the digest of the first captured portion; an enhancement subsystem that: sends an enhancement package request including the document identifier to a media server; and receives from the media server an enhancement package associated with the document identifier, wherein the enhancement package includes multiple media presentations associated with multiple words of the rendered document, wherein each word of the multiple words is associated with a respective media presentation of the multiple media presentations; a location subsystem that locates within the enhancement package media associated with one or more words identified within the second captured portion; and a presentation subsystem that presents the identified. | 10. A system in a mobile device for retrieving a media presentation associated with a rendered document, the system comprising: a data capture subsystem that optically or acoustically captures a first human-readable text-based portion of a rendered document and a second human-readable text-based portion of a rendered document; a digest subsystem that generates a digest of the first captured portion based at least in part on content of the text of the captured portion; an identification subsystem that locates a document identifier associated with an electronic counterpart to the rendered document based at least in part on the digest of the first captured portion; an enhancement subsystem that: sends an enhancement package request including the document identifier to a media server; and receives from the media server an enhancement package associated with the document identifier, wherein the enhancement package includes multiple media presentations associated with multiple words of the rendered document, wherein each word of the multiple words is associated with a respective media presentation of the multiple media presentations; a location subsystem that locates within the enhancement package media associated with one or more words identified within the second captured portion; and a presentation subsystem that presents the identified. 12. The system of claim 10 , wherein the presentation subsystem includes a display or speaker of the mobile device. | 0.889423 |
7,890,539 | 18 | 25 | 18. A method of processing text intervals, comprising: extracting a first proposition from a first text interval; generating a first proposition tree from the first proposition, wherein the first proposition tree comprises a set of nodes and a set of edges, and wherein each edge includes a semantic relationship between nodes of the first proposition tree; determining a first similarity value between the first text interval and a second text interval based on a comparison of the first proposition tree and a second proposition tree corresponding to the second text interval, wherein the second text interval is different from the first text interval; determining a second similarity value between the second text interval and the first text interval; finding the second text interval redundant to the first text interval in response to the first and second similarity values each exceeding respective thresholds; and selectively outputting, using a processor, the second text interval based on at least one of the first similarity value and the redundancy finding. | 18. A method of processing text intervals, comprising: extracting a first proposition from a first text interval; generating a first proposition tree from the first proposition, wherein the first proposition tree comprises a set of nodes and a set of edges, and wherein each edge includes a semantic relationship between nodes of the first proposition tree; determining a first similarity value between the first text interval and a second text interval based on a comparison of the first proposition tree and a second proposition tree corresponding to the second text interval, wherein the second text interval is different from the first text interval; determining a second similarity value between the second text interval and the first text interval; finding the second text interval redundant to the first text interval in response to the first and second similarity values each exceeding respective thresholds; and selectively outputting, using a processor, the second text interval based on at least one of the first similarity value and the redundancy finding. 25. The method of claim 18 , comprising: generating a first bag of nodes from the first proposition tree and a second bag of nodes from the second proposition tree; and determining the second similarity value by matching the first bag of nodes to the second bag of nodes. | 0.751832 |
8,335,687 | 1 | 9 | 1. A computer-implemented method comprising: receiving, by a speech recognition model training system and from a client device, a request to generate a new speech recognition model for the client device, wherein the request includes: (i) one or more features extracted from speech data by a feature extractor on the client device, and (ii) metadata regarding the speech recognition model to be generated; generating, by the speech recognition model training system and using the one or more features extracted from speech data by the feature extractor on the client device, the new speech recognition model according to the metadata; and transmitting, by the speech recognition model training system and to the client device, at least a portion of the new speech recognition model. | 1. A computer-implemented method comprising: receiving, by a speech recognition model training system and from a client device, a request to generate a new speech recognition model for the client device, wherein the request includes: (i) one or more features extracted from speech data by a feature extractor on the client device, and (ii) metadata regarding the speech recognition model to be generated; generating, by the speech recognition model training system and using the one or more features extracted from speech data by the feature extractor on the client device, the new speech recognition model according to the metadata; and transmitting, by the speech recognition model training system and to the client device, at least a portion of the new speech recognition model. 9. The method of claim 1 , wherein generating a new speech recognition model includes updating an existing speech recognition model. | 0.86747 |
9,747,347 | 18 | 20 | 18. The system of claim 15 , wherein the system is further configured to: retrieve a user relationship map of a user; determine other users that are more than one hop away from the user in the user relationship map; retrieve content by the other users as the extended content; determine quality of the extended content; and combine more extended content than engaging content to the combined list of content if the quality of the extended content is high. | 18. The system of claim 15 , wherein the system is further configured to: retrieve a user relationship map of a user; determine other users that are more than one hop away from the user in the user relationship map; retrieve content by the other users as the extended content; determine quality of the extended content; and combine more extended content than engaging content to the combined list of content if the quality of the extended content is high. 20. The system of claim 18 , wherein the determination of other users includes determining the other users that are k hops away from the user in the user relationship map, where k is a natural number 2 or greater. | 0.904399 |
10,152,966 | 6 | 8 | 6. A method comprising: receiving, at a device, an audio signal comprising a signal marker of a plurality of signal markers; processing the signal marker; and determining, based on the processing of the signal marker, not to cause execution of a voice command associated with the signal marker, wherein the plurality of signal markers comprises a first signal marker configured to cause the device not to cause execution of a voice command for a first time duration and a second signal marker configured to cause the device not to cause execution of a voice command for a second time duration. | 6. A method comprising: receiving, at a device, an audio signal comprising a signal marker of a plurality of signal markers; processing the signal marker; and determining, based on the processing of the signal marker, not to cause execution of a voice command associated with the signal marker, wherein the plurality of signal markers comprises a first signal marker configured to cause the device not to cause execution of a voice command for a first time duration and a second signal marker configured to cause the device not to cause execution of a voice command for a second time duration. 8. The method of claim 6 , wherein the device comprises a plurality of microphones, a given one of the microphones being configured for detection of the signal marker. | 0.796341 |
8,943,608 | 18 | 21 | 18. A method comprising: extracting content of a document, using a processor; dividing the extracted content into a plurality of document content sections based on metadata of the document; and generating a plurality of parallel data structures for the plurality of document content sections based on a viewing size, wherein: each parallel data structure of the plurality of parallel data structures corresponds to a document content section of the plurality of document content sections based; and each parallel data structure comprises pagination selectors associated with the corresponding document content section. | 18. A method comprising: extracting content of a document, using a processor; dividing the extracted content into a plurality of document content sections based on metadata of the document; and generating a plurality of parallel data structures for the plurality of document content sections based on a viewing size, wherein: each parallel data structure of the plurality of parallel data structures corresponds to a document content section of the plurality of document content sections based; and each parallel data structure comprises pagination selectors associated with the corresponding document content section. 21. The method of claim 18 , further comprising generating a table of contents for a document content section of the plurality of document content sections based on its corresponding parallel data structure. | 0.634276 |
9,152,735 | 1 | 7 | 1. A method for exporting at least a portion of a relational database to an XML document, comprising the steps of: obtaining an initial view query that defines an XML view on said relational database and an XSLT stylesheet specifying at least one transformation; modifying said initial view query to account for an effect of said at least one transformation specified in said XSLT stylesheet; applying said modified view query that accounts for said effect of said at least one transformation specified in said XSLT stylesheet to said relational database to obtain said XML document; generating a first graph representing processing done by said XSLT stylesheet; and combining said first graph with a second graph to produce a combined graph, wherein said second graph represents said initial view query by matching pairs of nodes from the first and second graphs and wherein said combined graph is a context transition graph for an XSLT stylesheet executed on said initial view query. | 1. A method for exporting at least a portion of a relational database to an XML document, comprising the steps of: obtaining an initial view query that defines an XML view on said relational database and an XSLT stylesheet specifying at least one transformation; modifying said initial view query to account for an effect of said at least one transformation specified in said XSLT stylesheet; applying said modified view query that accounts for said effect of said at least one transformation specified in said XSLT stylesheet to said relational database to obtain said XML document; generating a first graph representing processing done by said XSLT stylesheet; and combining said first graph with a second graph to produce a combined graph, wherein said second graph represents said initial view query by matching pairs of nodes from the first and second graphs and wherein said combined graph is a context transition graph for an XSLT stylesheet executed on said initial view query. 7. The method of claim 1 , wherein said obtained XML document is substantially similar to a second XML document produced by applying said XSLT stylesheet on said XML document produced by said initial view query. | 0.632404 |
5,513,311 | 6 | 11 | 6. A data processing system for efficiently creating a logical connection between a new graphic object and at least one of a plurality of existing graphic objects, wherein a number diverse types of logical connections may be created between graphic objects, said data processing system comprising: identification means, responsive to a placement of a new graphic object in a location, for identifying each existing graphic object within said plurality of existing graphic objects located within a predetermined distance from said new graphic object; and creation means for automatically creating a particular logical connection between said new graphic object and each identified existing graphic object based upon a position of each identified existing graphic object with respect to said new graphic object, wherein logical connections between graphic objects are efficiently created. | 6. A data processing system for efficiently creating a logical connection between a new graphic object and at least one of a plurality of existing graphic objects, wherein a number diverse types of logical connections may be created between graphic objects, said data processing system comprising: identification means, responsive to a placement of a new graphic object in a location, for identifying each existing graphic object within said plurality of existing graphic objects located within a predetermined distance from said new graphic object; and creation means for automatically creating a particular logical connection between said new graphic object and each identified existing graphic object based upon a position of each identified existing graphic object with respect to said new graphic object, wherein logical connections between graphic objects are efficiently created. 11. The data processing system of claim 6, wherein said new object and said plurality of existing graphic objects have the same shape and size. | 0.842163 |
7,552,452 | 1 | 2 | 1. A method of localization of a software product comprising: loading an application or an operating system wherein the application or operating system places a plurality of calls to a resource loader to load a plurality of resources; loading one of the plurality of resources in response to a call to load the one of the plurality of resources, wherein the application or operating system indicates a language for the one of the plurality of resources; intercepting the one of the plurality of resources in the resource loader after the one of the plurality of resources which is in the language has been received in the resource loader; comparing the one of the plurality of resources to a predetermined set of resource identifiers to determine whether the one of the plurality of resources is permitted to be translated, wherein the predetermined set of resource identifiers are in a data structure that cannot be modified without prior authorization; and when the one of the plurality of resources is permitted to be translated, loading a translation in a different language for the one of the plurality of resources; and transmitting the one of the plurality of resources to the application or operating system without translation when the one of the plurality of resources is not permitted to be translated. | 1. A method of localization of a software product comprising: loading an application or an operating system wherein the application or operating system places a plurality of calls to a resource loader to load a plurality of resources; loading one of the plurality of resources in response to a call to load the one of the plurality of resources, wherein the application or operating system indicates a language for the one of the plurality of resources; intercepting the one of the plurality of resources in the resource loader after the one of the plurality of resources which is in the language has been received in the resource loader; comparing the one of the plurality of resources to a predetermined set of resource identifiers to determine whether the one of the plurality of resources is permitted to be translated, wherein the predetermined set of resource identifiers are in a data structure that cannot be modified without prior authorization; and when the one of the plurality of resources is permitted to be translated, loading a translation in a different language for the one of the plurality of resources; and transmitting the one of the plurality of resources to the application or operating system without translation when the one of the plurality of resources is not permitted to be translated. 2. The method of claim 1 , further comprising comparing the translation for the one of the plurality of resources to one or more predetermined rules and transmitting the one of the plurality of resources to the application or the operating system without translation when the called resource does not match the one or more predetermined rules. | 0.603926 |
7,996,479 | 15 | 17 | 15. A method as claimed in claim 1 , further comprising the steps of: analysing the message to determine the recipient of the message; placing the message in a category based on the determined recipient; storing the category in one or more data stores; and wherein the category is associated with the sender of the message. | 15. A method as claimed in claim 1 , further comprising the steps of: analysing the message to determine the recipient of the message; placing the message in a category based on the determined recipient; storing the category in one or more data stores; and wherein the category is associated with the sender of the message. 17. A method as claimed in claim 15 , wherein the recipient is a group of known recipients. | 0.926375 |
7,792,838 | 10 | 11 | 10. The method of claim 9 , wherein the similarity between the instances i and j is based on statements where the instances i and j are the subjects and a predicate is the at least one given ontology property. | 10. The method of claim 9 , wherein the similarity between the instances i and j is based on statements where the instances i and j are the subjects and a predicate is the at least one given ontology property. 11. The method of claim 10 , wherein an instance is considered to belong to a virtual class of size one and a description for the instance is defined in terms of membership of the instance to the virtual class of size one. | 0.941946 |
10,061,773 | 17 | 18 | 17. The computer program product of claim 16 wherein if the data type of the first field comprising the nested document is associated with the first content type and is different than the second content type, the control application further configures the processing circuit to determine whether the first parser is able to identify a field and a corresponding data type for the field in the nested document. | 17. The computer program product of claim 16 wherein if the data type of the first field comprising the nested document is associated with the first content type and is different than the second content type, the control application further configures the processing circuit to determine whether the first parser is able to identify a field and a corresponding data type for the field in the nested document. 18. The computer program product of claim 17 wherein the control application further configures the processing circuit to: parse the nested document using the first parser if the first parser is able to identify the field and corresponding data type in the nested document; and parse the nested document using the second parser if the first parser is unable to identify the field and corresponding data type in the nested document. | 0.877278 |
8,706,680 | 12 | 15 | 12. A system for generating a report whereby a user selects a response from a plurality of lexeme responses in response to a lexeme query, said system comprising: a processor; an input interface configured to receive data input from the user and an output interface coupled to said processor; a memory; a lexicon comprising of a plurality of lexeme queries and associated responses stored in said memory which lexeme queries and associated responses are accessible by said processor; wherein said user interface is configured to receive context information from the user which is processed to determine which lexeme query to display on the output interface; wherein the user is able to select the desired response using the input interface; and wherein the system determines which lexeme query and associated responses to display based on context, predicance, and coherence; wherein the queries are displayed iteratively one-at-a-time in an order established by the system's coherence and predicance; and wherein the user is constrained to respond to the queries in the order they are presented by the system. | 12. A system for generating a report whereby a user selects a response from a plurality of lexeme responses in response to a lexeme query, said system comprising: a processor; an input interface configured to receive data input from the user and an output interface coupled to said processor; a memory; a lexicon comprising of a plurality of lexeme queries and associated responses stored in said memory which lexeme queries and associated responses are accessible by said processor; wherein said user interface is configured to receive context information from the user which is processed to determine which lexeme query to display on the output interface; wherein the user is able to select the desired response using the input interface; and wherein the system determines which lexeme query and associated responses to display based on context, predicance, and coherence; wherein the queries are displayed iteratively one-at-a-time in an order established by the system's coherence and predicance; and wherein the user is constrained to respond to the queries in the order they are presented by the system. 15. The system of claim 12 wherein the lexeme query is presented on the output interface in the form of a question. | 0.905428 |
10,055,397 | 18 | 19 | 18. The method of claim 16 , wherein the text data comprises a device delta language model trained on the text input by the user and incorporating the text data into one or more language models comprises merging the device delta language model into the one or more language models. | 18. The method of claim 16 , wherein the text data comprises a device delta language model trained on the text input by the user and incorporating the text data into one or more language models comprises merging the device delta language model into the one or more language models. 19. The method of claim 18 , wherein the one or more language models comprises a data structure associating sequences of terms with a frequency of occurrence for each sequence, and merging a first language model with a second language model comprises: adding the frequencies of occurrence for sequences in the data structure of the second language model to the frequencies of occurrence for corresponding sequences in the data structure of the first language model; and inserting a new sequence and its corresponding frequency of occurrence into the data structure of the first language model, if that sequence is in the data structure of the second language model but not in the data structure of the first language model. | 0.670765 |
4,860,213 | 21 | 23 | 21. A system, for practice on a computer, for reasoning with uncertainty system in a rule-based reasoning system comprising a plurality of rules each having a premise and a conclusion to be determined true upon finding a premise to be true, said premise comprising at least one clause including a variable to which a value can be assigned, said reasoning system comprising: means for associating a value certainty interval with each value assigned to one of said rule premise variables, said value certainty interval having a lower and an upper bound respectively representative of amounts of confirmation and failure of refutation of the assigned value; means for associating a sufficiency factor and a necessity factor with each said rule, said sufficiency factor representing a strength of belief that the rule conclusion is true given the rule premise is true, said necessity factor representing a strength of belief that the rule conclusion is false given the rule premise is false; means for computing a premise certainty interval from the value certainty intervals respectively associated with the values assigned to the premise variables, a lower bound of said premise certainty interval being a first predetermined function of the respective value certainty interval lower bounds, an upper bound of said premise certainty interval being said first function of the respective value certainty interval upper bounds; and means for firing each of said rules by computing a conclusion detachment certainty interval having a lower and upper bound, said conclusion detachment interval lower bound being a second predetermined function of both said rule sufficiency factor and said premise certainty interval lower bound, the conclusion detachment upper bound being a third predetermined function of both said rule necessity factor and said premise certainty interval upper bound, said conclusion detachment interval lower and upper bounds respectively representing the amounts of confirmation and failure of refutation of the rule conclusion, and wherein upon the same conclusion being provided by more than one rule in a predetermined group of said rules, said system additionally comprises: means for aggregating the same conclusions by computing a conclusion aggregation certainty interval having a lower bound that is a fourth predetermined function of the conclusion detachment interval lower bounds respectively computed for the rules reaching the same conclusion, an upper bound of said conclusion aggregation interval being said fourth predetermined function of the conclusion detachment interval upper bounds respectively computed for the rules reaching the same conclusion, said conclusion aggregation interval lower and upper bounds being respectively representative of the amount of confirmation and failure of refutation of the aggregated conclusion. | 21. A system, for practice on a computer, for reasoning with uncertainty system in a rule-based reasoning system comprising a plurality of rules each having a premise and a conclusion to be determined true upon finding a premise to be true, said premise comprising at least one clause including a variable to which a value can be assigned, said reasoning system comprising: means for associating a value certainty interval with each value assigned to one of said rule premise variables, said value certainty interval having a lower and an upper bound respectively representative of amounts of confirmation and failure of refutation of the assigned value; means for associating a sufficiency factor and a necessity factor with each said rule, said sufficiency factor representing a strength of belief that the rule conclusion is true given the rule premise is true, said necessity factor representing a strength of belief that the rule conclusion is false given the rule premise is false; means for computing a premise certainty interval from the value certainty intervals respectively associated with the values assigned to the premise variables, a lower bound of said premise certainty interval being a first predetermined function of the respective value certainty interval lower bounds, an upper bound of said premise certainty interval being said first function of the respective value certainty interval upper bounds; and means for firing each of said rules by computing a conclusion detachment certainty interval having a lower and upper bound, said conclusion detachment interval lower bound being a second predetermined function of both said rule sufficiency factor and said premise certainty interval lower bound, the conclusion detachment upper bound being a third predetermined function of both said rule necessity factor and said premise certainty interval upper bound, said conclusion detachment interval lower and upper bounds respectively representing the amounts of confirmation and failure of refutation of the rule conclusion, and wherein upon the same conclusion being provided by more than one rule in a predetermined group of said rules, said system additionally comprises: means for aggregating the same conclusions by computing a conclusion aggregation certainty interval having a lower bound that is a fourth predetermined function of the conclusion detachment interval lower bounds respectively computed for the rules reaching the same conclusion, an upper bound of said conclusion aggregation interval being said fourth predetermined function of the conclusion detachment interval upper bounds respectively computed for the rules reaching the same conclusion, said conclusion aggregation interval lower and upper bounds being respectively representative of the amount of confirmation and failure of refutation of the aggregated conclusion. 23. The reasoning with uncertainty system of claim 21 further comprising: means for excluding a selected conclusion from said aggregating step even though said selected conclusion is the same as the aggregated conclusions, said selected conclusion having an associated certainty interval; and means for computing a source consensus certainty interval by taking the intersection of the associated certainty interval of said selected conclusion with each said conclusion aggregation interval computed for the same conclusion. | 0.885508 |
9,754,593 | 5 | 6 | 5. The method of claim 1 , wherein the step of the computer mapping the one or more features of the sound construct further comprises the computer: sequencing out at least a portion of features of the one or more features to provide a feature sequence; and comparing the feature sequence to one or more defined sequences to identify one or more sound constructs of a selected language. | 5. The method of claim 1 , wherein the step of the computer mapping the one or more features of the sound construct further comprises the computer: sequencing out at least a portion of features of the one or more features to provide a feature sequence; and comparing the feature sequence to one or more defined sequences to identify one or more sound constructs of a selected language. 6. The method of claim 5 , further comprising the computer forming a word by sequencing the sound constructs. | 0.981809 |
8,127,336 | 23 | 27 | 23. A method for evaluating a request for a policy-based service management decision by a hardware-based policy management interface subsystem, comprising: receiving, using a processor, a request from a policy enforcement element for a service management decision associated with an access attempt to a network or a network resource by a subscriber device; retrieving, using a processor, one or more policy instances comprising of one or more rule definitions necessary to process the service management decision request, wherein the policy instance determines a set of actions, and wherein one or more rule definitions contain one or more rule definition variables wherein the rule definition variable is associated with a value selected from a user-defined value set; retrieving, using a processor, the user-defined value set for each variable defined in one or more retrieved rule definitions; substituting, using a processor, one or more values in the user-defined value set corresponding to each rule definition variable into the rule definitions in real-time as the rule is being evaluated; evaluating, using a processor, each of the retrieved policy instances to determine if the set of actions defined in the policy is to be performed by the policy enforcement element; and communicating a result of the evaluation to the policy enforcement element. | 23. A method for evaluating a request for a policy-based service management decision by a hardware-based policy management interface subsystem, comprising: receiving, using a processor, a request from a policy enforcement element for a service management decision associated with an access attempt to a network or a network resource by a subscriber device; retrieving, using a processor, one or more policy instances comprising of one or more rule definitions necessary to process the service management decision request, wherein the policy instance determines a set of actions, and wherein one or more rule definitions contain one or more rule definition variables wherein the rule definition variable is associated with a value selected from a user-defined value set; retrieving, using a processor, the user-defined value set for each variable defined in one or more retrieved rule definitions; substituting, using a processor, one or more values in the user-defined value set corresponding to each rule definition variable into the rule definitions in real-time as the rule is being evaluated; evaluating, using a processor, each of the retrieved policy instances to determine if the set of actions defined in the policy is to be performed by the policy enforcement element; and communicating a result of the evaluation to the policy enforcement element. 27. The method of claim 23 , wherein a first set of rule definitions is retrieved prior to receipt of the request and a second set of rule definitions is retrieved from a rule repository when the request is received. | 0.502304 |
8,171,450 | 1 | 5 | 1. A computer program product comprising a computer storage device having computer usable program code programmed to generate source code that defines a business rule condition, the operations of the computer program product comprising: displaying a business rule condition creation tool comprising at least one graphical expression function icon, at least one graphical business attribute icon, and a staging canvas having a result icon, the tool configured to operate within a build-time development environment and wherein the at least one graphical expression function icon comprises a description and an iconic symbol configured to convey the purpose of an associated atomic operator to a non-technical user without knowledge of business rule condition programming; positioning the at least one graphical expression function icon on the staging canvas; positioning the at least one graphical business attribute icon on the staging canvas; defining a graphical business rule condition by graphically relating the at least one positioned graphical expression function icon, the at least one positioned graphical business attribute icon, and the result icon in response to input from a user; translating the graphical business rule condition into a logical expression; and converting the logical expression to source code having a syntax compatible with a target source code language, the source code configured to operate as part of a business rule processing module in a run-time environment, the run-time environment configured to operate simultaneous to the operation of the build-time development environment and configured to operate with a previous version of the business rule processing module. | 1. A computer program product comprising a computer storage device having computer usable program code programmed to generate source code that defines a business rule condition, the operations of the computer program product comprising: displaying a business rule condition creation tool comprising at least one graphical expression function icon, at least one graphical business attribute icon, and a staging canvas having a result icon, the tool configured to operate within a build-time development environment and wherein the at least one graphical expression function icon comprises a description and an iconic symbol configured to convey the purpose of an associated atomic operator to a non-technical user without knowledge of business rule condition programming; positioning the at least one graphical expression function icon on the staging canvas; positioning the at least one graphical business attribute icon on the staging canvas; defining a graphical business rule condition by graphically relating the at least one positioned graphical expression function icon, the at least one positioned graphical business attribute icon, and the result icon in response to input from a user; translating the graphical business rule condition into a logical expression; and converting the logical expression to source code having a syntax compatible with a target source code language, the source code configured to operate as part of a business rule processing module in a run-time environment, the run-time environment configured to operate simultaneous to the operation of the build-time development environment and configured to operate with a previous version of the business rule processing module. 5. The computer program product of claim 1 , further comprising prompting the user for a target source code identifier that identifies the target source code language. | 0.878457 |
8,538,984 | 11 | 17 | 11. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: identifying a particular query term of an original search query; identifying a candidate synonym for the particular query term; accessing stored data that specifies, for a pair of terms that includes the particular query term and the candidate synonym of the particular query term, a confidence value for a non-adjacent query term of the original search query that is not adjacent to the particular query term in the original search query; determining that, in the stored data that specifies, for the pair of terms that includes the particular query term and the candidate synonym of the particular query term, the confidence value for the non-adjacent query term satisfies a threshold; and determining to revise the original search query to include the candidate synonym of the particular query term, based on determining that the confidence value for the non-adjacent query term satisfies the threshold. | 11. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: identifying a particular query term of an original search query; identifying a candidate synonym for the particular query term; accessing stored data that specifies, for a pair of terms that includes the particular query term and the candidate synonym of the particular query term, a confidence value for a non-adjacent query term of the original search query that is not adjacent to the particular query term in the original search query; determining that, in the stored data that specifies, for the pair of terms that includes the particular query term and the candidate synonym of the particular query term, the confidence value for the non-adjacent query term satisfies a threshold; and determining to revise the original search query to include the candidate synonym of the particular query term, based on determining that the confidence value for the non-adjacent query term satisfies the threshold. 17. The computer storage medium of claim 11 , the operations further comprising: determining two or more query terms comprise a compound phrase; and selecting a particular query term of the original search query that is not included in the compound phrase. | 0.781942 |
8,099,313 | 39 | 41 | 39. The system of claim 32 , wherein a task description includes a sequence of actions scripts that the controller uses to orchestrate the device actions. | 39. The system of claim 32 , wherein a task description includes a sequence of actions scripts that the controller uses to orchestrate the device actions. 41. The system of claim 39 , wherein device grounding information is specified on a functionality basis from the device descriptions. | 0.955429 |
8,849,659 | 11 | 22 | 11. A method comprising: capturing mobile device input, wherein the mobile device input includes a multimedia data stream; by a mobile device, transmitting the mobile device input over a wireless channel to a game engine; by the mobile device, transmitting location information indicating a location of the mobile device, wherein the location information corresponds to the location of a user providing verbal instruction input to the mobile device; receiving a result of an analysis of the location information and an analysis of an audio clip or video in the multimedia data stream; and by the mobile device, playing audio content or video content based at least in part on the analysis result in accordance with a game engine instruction. | 11. A method comprising: capturing mobile device input, wherein the mobile device input includes a multimedia data stream; by a mobile device, transmitting the mobile device input over a wireless channel to a game engine; by the mobile device, transmitting location information indicating a location of the mobile device, wherein the location information corresponds to the location of a user providing verbal instruction input to the mobile device; receiving a result of an analysis of the location information and an analysis of an audio clip or video in the multimedia data stream; and by the mobile device, playing audio content or video content based at least in part on the analysis result in accordance with a game engine instruction. 22. The method of claim 11 , further comprising: receiving a summary of the audio clip or video including relevant image, music, or video information. | 0.795082 |
8,224,641 | 6 | 10 | 6. The method of claim 1 wherein determining a final score S F (M) for one of the languages M includes: computing a non-default score component (S δ (M)) based on n-grams in the target document that have greater than a default probability of occurring in the language M; computing a default score component (S δ (M)) based on n-grams in the target document that do not have greater than the default probability of occurring in the language M; computing an alternative-language score component (S M ′(L)) for each language L in the set N(M), the alternative-language score component being based on the n-grams in the target document that do not have greater than the default probability of occurring in the language M; and determining the final score S F (M) based on the non-default score component S ε (M) and one or both of the default score component S δ (M) or one of the alternative-language score components S M ′(L). | 6. The method of claim 1 wherein determining a final score S F (M) for one of the languages M includes: computing a non-default score component (S δ (M)) based on n-grams in the target document that have greater than a default probability of occurring in the language M; computing a default score component (S δ (M)) based on n-grams in the target document that do not have greater than the default probability of occurring in the language M; computing an alternative-language score component (S M ′(L)) for each language L in the set N(M), the alternative-language score component being based on the n-grams in the target document that do not have greater than the default probability of occurring in the language M; and determining the final score S F (M) based on the non-default score component S ε (M) and one or both of the default score component S δ (M) or one of the alternative-language score components S M ′(L). 10. The method of claim 6 wherein determining the final score S F (M) includes: determining whether a frequency of occurrence in the target document of bigrams having no greater than the default probability of occurrence in the language M exceeds a threshold; in the event that the frequency exceeds the threshold, computing the final score S F (M) using the non default score component S ε (M) and the default score component S δ (M); and in the event that the frequency does not exceed the threshold, computing the final score S F (M) using the non default score component S ε (M) and the best one of the alternative language score components S M ′(L). | 0.748462 |
9,563,737 | 3 | 4 | 3. The computer implemented method of claim 1 , the process further comprising: identifying a shape; determining whether the shape corresponds to at least one track in multiple recognized or legal track patterns; and identifying the shape as a non-conforming shape when the shape is determined not to correspond to any tracks in the multiple recognized or legal track patterns. | 3. The computer implemented method of claim 1 , the process further comprising: identifying a shape; determining whether the shape corresponds to at least one track in multiple recognized or legal track patterns; and identifying the shape as a non-conforming shape when the shape is determined not to correspond to any tracks in the multiple recognized or legal track patterns. 4. The computer implemented method of claim 3 , the process further comprising: identifying a first shape in the region; determining whether the first shape changes the non-conforming shape into a conforming shape that corresponds to the at least one track in the multiple recognized or legal track patterns; and determining whether to flag the non-conforming shape as a violation based at least in part upon a result of determining whether the first shape changes the non-conforming shape into the conforming shape. | 0.790244 |
10,055,602 | 15 | 16 | 15. The computer program product of claim 14 , wherein the program instructions executable by a computing device further cause the computing device to: decrypt the final encrypted result, thereby generating a plain text result set. | 15. The computer program product of claim 14 , wherein the program instructions executable by a computing device further cause the computing device to: decrypt the final encrypted result, thereby generating a plain text result set. 16. The computer program product of claim 15 , wherein the program instructions executable by a computing device further cause the computing device to: output the plain text result set to a client that provided the range query. | 0.871461 |
6,067,552 | 17 | 19 | 17. The computer-readable medium recited in claim 13, further comprising the step of linking each electronic document in the hypertext database to a present position of the user in the hypertext database by an intermediate, dynamically generated tree link. | 17. The computer-readable medium recited in claim 13, further comprising the step of linking each electronic document in the hypertext database to a present position of the user in the hypertext database by an intermediate, dynamically generated tree link. 19. The method recited in claim 17, further including the step of computing relevance to the user of the document to which the tree link as a function of the set of index terms and the weighted relevancy ranking of the index terms. | 0.930085 |
7,986,842 | 1 | 4 | 1. A method for detecting two or more concepts in a source digital video which includes one or more digital video frames comprising: (a) segmenting the source digital video into a plurality of shots, wherein each shot includes one or more of the digital video frames; (b) identifying a keyframe within each shot, wherein the keyframe is one of the one or more of the digital video frames; (c) extracting low level features from the keyframe, wherein the low level features are representative of the two or more concepts, and are related in a graph of concepts, and wherein each concept is semi-automatically generated text associated with the one or more digital video frames, and wherein semi-automatically generated text is automatically generated text which has been manually revised; (d) training a discriminative classifier for each concept using a set of the low level features, wherein the discriminative classifier is a support vector machine; (e) building a collective annotation model combining each of the discriminative classifiers; (f) defining in the collective annotation model one or more interaction potential to model interdependence between related concepts; (g) receiving a second source digital video; (h) applying the discriminative classifiers to the second source digital video; and (i) determining a probability of a presence or absence of the two or more concepts in the low level features extracted from the second source digital video using the collective annotation model and the defined interaction potentials. | 1. A method for detecting two or more concepts in a source digital video which includes one or more digital video frames comprising: (a) segmenting the source digital video into a plurality of shots, wherein each shot includes one or more of the digital video frames; (b) identifying a keyframe within each shot, wherein the keyframe is one of the one or more of the digital video frames; (c) extracting low level features from the keyframe, wherein the low level features are representative of the two or more concepts, and are related in a graph of concepts, and wherein each concept is semi-automatically generated text associated with the one or more digital video frames, and wherein semi-automatically generated text is automatically generated text which has been manually revised; (d) training a discriminative classifier for each concept using a set of the low level features, wherein the discriminative classifier is a support vector machine; (e) building a collective annotation model combining each of the discriminative classifiers; (f) defining in the collective annotation model one or more interaction potential to model interdependence between related concepts; (g) receiving a second source digital video; (h) applying the discriminative classifiers to the second source digital video; and (i) determining a probability of a presence or absence of the two or more concepts in the low level features extracted from the second source digital video using the collective annotation model and the defined interaction potentials. 4. The method of claim 1 , wherein the output of the support vector machine is transformed to a probability using a logistic mapping. | 0.806686 |
7,499,850 | 6 | 7 | 6. The method of claim 1 wherein processing the mathematical function forms included in the packages comprises: if the first sentence form is not mapped to a mathematical function: gathering the first mathematical function form and synonyms including explicit synonyms of the first mathematical function form from each of the packages as mathematical function forms in a working set; computing identity of the first mathematical function form; if the identity maps to a mathematical function, obtaining the mathematical function to which the identity maps; else creating a mathematical function; mapping each of the mathematical function forms in the working set as a representer of the mathematical function; and processing placeholders of each of the mathematical function forms in the working set; obtaining function forms to which the mathematical function maps; and if one of the function forms is a sentence form representing a fact type: creating an association indicating that the mathematical function is defined by the fact type represented by the sentence form. | 6. The method of claim 1 wherein processing the mathematical function forms included in the packages comprises: if the first sentence form is not mapped to a mathematical function: gathering the first mathematical function form and synonyms including explicit synonyms of the first mathematical function form from each of the packages as mathematical function forms in a working set; computing identity of the first mathematical function form; if the identity maps to a mathematical function, obtaining the mathematical function to which the identity maps; else creating a mathematical function; mapping each of the mathematical function forms in the working set as a representer of the mathematical function; and processing placeholders of each of the mathematical function forms in the working set; obtaining function forms to which the mathematical function maps; and if one of the function forms is a sentence form representing a fact type: creating an association indicating that the mathematical function is defined by the fact type represented by the sentence form. 7. The method of claim 6 wherein processing placeholders of each of the mathematical function forms in the working set comprises: if the first placeholder is from the first mathematical function form: creating an argument represented by the first placeholder, and creating an association relating the argument to the mathematical function to which the first mathematical function form maps; else if the first placeholder is not from one of the explicit synonyms of the first mathematical function form: setting the first placeholder as a representer of a previously created argument in corresponding ordinal position; else obtaining all placeholders that are mapped to the first placeholder, one of the mapped placeholders representing a role; locating the represented role; and setting the first placeholder as a representer of the located role. | 0.775597 |
8,375,312 | 12 | 20 | 12. A medium bearing instructions to enable one or more machines to perform operations, the operations comprising: displaying one or more poster frames in a user interface, wherein a poster frame corresponds to an item of digital content; in response to receiving an input, displaying a plurality of first level classification panes adjacent to a poster frame corresponding to an item of digital content, wherein each of the first level classification panes is associated with a corresponding keyword; detecting a selection and positioning of the poster frame at an at least partially common location with a classification pane of the plurality of first level classification panes; and in response to the detecting, associating the item of digital content to which the selected poster frame corresponds with a keyword associated with the first level classification pane on which the selected poster frame that corresponds to the item of digital content is positioned. | 12. A medium bearing instructions to enable one or more machines to perform operations, the operations comprising: displaying one or more poster frames in a user interface, wherein a poster frame corresponds to an item of digital content; in response to receiving an input, displaying a plurality of first level classification panes adjacent to a poster frame corresponding to an item of digital content, wherein each of the first level classification panes is associated with a corresponding keyword; detecting a selection and positioning of the poster frame at an at least partially common location with a classification pane of the plurality of first level classification panes; and in response to the detecting, associating the item of digital content to which the selected poster frame corresponds with a keyword associated with the first level classification pane on which the selected poster frame that corresponds to the item of digital content is positioned. 20. The medium of claim 12 wherein associating the keyword with the item comprises including the keyword in metadata associated with the item. | 0.925577 |
9,563,741 | 3 | 4 | 3. The method of claim 2 , wherein the manual editing of the plurality of assertions automatically extracted from the plurality of publications is performed by one or more subject matter experts in the particular biological field. | 3. The method of claim 2 , wherein the manual editing of the plurality of assertions automatically extracted from the plurality of publications is performed by one or more subject matter experts in the particular biological field. 4. The method of claim 3 , wherein automatically extracting the plurality of assertions from the plurality of publications comprises utilizing natural language processing software to derive the plurality of assertions from the text of the plurality of publications. | 0.917548 |
8,280,823 | 264 | 266 | 264. The graphical user interface of claim 261 , wherein grouping characters enclose each said at least one search phrase. | 264. The graphical user interface of claim 261 , wherein grouping characters enclose each said at least one search phrase. 266. The graphical user interface of claim 264 , wherein, when the search string comprises at least two search phrases, a Boolean operator separates adjoining ones of said at least two search phrases. | 0.954107 |
9,336,299 | 15 | 16 | 15. The computing device of claim 14 , wherein the instructions, when executed by the at least one processing unit, cause the at least one processing unit to: obtain training data having labeled instances of the seed phrase, including first instances where the seed phrase is labeled as belonging to the first semantic class and second instances where the seed phrase is labeled as belonging to the second semantic class; determine a first number of times the seed phrase is labeled in the training data as belonging to the first semantic class; determine a second number of times the seed phrase is labeled in the training data as belonging to the second semantic class; calculate the first seed probability based at least on the first number of times the seed phrase is labeled in the training data as belonging to the first semantic class; and calculate the second seed probability based at least on the second number of times the seed phrase is labeled in the training data as belonging to the second semantic class. | 15. The computing device of claim 14 , wherein the instructions, when executed by the at least one processing unit, cause the at least one processing unit to: obtain training data having labeled instances of the seed phrase, including first instances where the seed phrase is labeled as belonging to the first semantic class and second instances where the seed phrase is labeled as belonging to the second semantic class; determine a first number of times the seed phrase is labeled in the training data as belonging to the first semantic class; determine a second number of times the seed phrase is labeled in the training data as belonging to the second semantic class; calculate the first seed probability based at least on the first number of times the seed phrase is labeled in the training data as belonging to the first semantic class; and calculate the second seed probability based at least on the second number of times the seed phrase is labeled in the training data as belonging to the second semantic class. 16. The computing device of claim 15 , wherein the other phrases lack corresponding seed probabilities derived from the training data. | 0.93514 |
8,321,841 | 5 | 6 | 5. A service oriented architecture (SOA) oriented application validation data processing system comprising: a computer system comprising at least one computer with memory and at least one processor; a model transformation module executing in the memory of the computer system and configured during execution to transform a business process model for an SOA oriented application into a directed and connected graph; a service group transformation module configured to further transform a plurality of service groupings for the business process model into corresponding directed and connected, acyclic graphs; a path discovery module configured to compute all paths from root node to leaf node in the graph for the business process model; and, model validation logic also executing in the computer system and comprising program code enabled to invalidate the business process model in response to either identifying a loop or cycle in the graph for the business process model, or identifying a shared vertex amongst the graphs for the service groupings. | 5. A service oriented architecture (SOA) oriented application validation data processing system comprising: a computer system comprising at least one computer with memory and at least one processor; a model transformation module executing in the memory of the computer system and configured during execution to transform a business process model for an SOA oriented application into a directed and connected graph; a service group transformation module configured to further transform a plurality of service groupings for the business process model into corresponding directed and connected, acyclic graphs; a path discovery module configured to compute all paths from root node to leaf node in the graph for the business process model; and, model validation logic also executing in the computer system and comprising program code enabled to invalidate the business process model in response to either identifying a loop or cycle in the graph for the business process model, or identifying a shared vertex amongst the graphs for the service groupings. 6. The system of claim 5 , wherein the program code is further enabled to determine that an individual one of the paths contains all vertices for a single one of the service groupings and to invalidate the single one of the service groupings if not all of the vertices contained in a single path are connected. | 0.525994 |
9,535,909 | 12 | 13 | 12. The computer implemented method of claim 1 , further comprising: distributing, by the rule manager system, jobs to the one or more job manager systems. | 12. The computer implemented method of claim 1 , further comprising: distributing, by the rule manager system, jobs to the one or more job manager systems. 13. The computer implemented method of claim 12 , further comprising: generating, by the one or more jobs manager system, a job responsive to the job request. | 0.967165 |
8,346,809 | 8 | 9 | 8. A computer implemented method for querying a markup language document having hierarchical information including a parent node and descendent nodes related to the parent node, comprising: storing, in a data source, a markup language document; retrieving the markup language document; identifying and extracting information from the retrieved markup language document in response to a query by consulting a mapping specification containing information for locating the parent node, and if the parent node satisfies the query, storing the parent node in a first table; and locating the descendent nodes by consulting the mapping specification if the parent node satisfies the query and storing said descendent nodes in a second table. | 8. A computer implemented method for querying a markup language document having hierarchical information including a parent node and descendent nodes related to the parent node, comprising: storing, in a data source, a markup language document; retrieving the markup language document; identifying and extracting information from the retrieved markup language document in response to a query by consulting a mapping specification containing information for locating the parent node, and if the parent node satisfies the query, storing the parent node in a first table; and locating the descendent nodes by consulting the mapping specification if the parent node satisfies the query and storing said descendent nodes in a second table. 9. The computer implemented method of claim 8 , wherein said consulting a mapping specification includes evaluating an expression for locating the parent node. | 0.560773 |
8,533,621 | 19 | 20 | 19. The means for claim 18 , wherein said plurality of distinct quadrants includes a first quadrant, a second quadrant, a third quadrant, a fourth quadrant, and a stop button disposed thereon. | 19. The means for claim 18 , wherein said plurality of distinct quadrants includes a first quadrant, a second quadrant, a third quadrant, a fourth quadrant, and a stop button disposed thereon. 20. The means for claim 19 , wherein each of said first quadrant, said second quadrant, said third quadrant, and said fourth quadrant is comprised of a top row and a bottom row wherein each said row includes at least three characters. | 0.96338 |
8,856,235 | 1 | 5 | 1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; identifying, by a computer, a plurality of interactions between the selected user and one or more of a set of users who are connected to the selected user in the social networking system; inferring, by the computer, a value of an attribute of the user profile for the selected user based on one or more of: topic analysis of the one or more identified interactions and sentiment analysis associated with one or more topics identified in the one or more identified interactions; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. | 1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; identifying, by a computer, a plurality of interactions between the selected user and one or more of a set of users who are connected to the selected user in the social networking system; inferring, by the computer, a value of an attribute of the user profile for the selected user based on one or more of: topic analysis of the one or more identified interactions and sentiment analysis associated with one or more topics identified in the one or more identified interactions; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. 5. The computer-implemented method of claim 1 , wherein inferring the value of the attribute of the user profile for the selected user comprises determining the inferred value of the attribute to be a median value of the attribute of the set of users. | 0.773466 |
8,330,760 | 13 | 14 | 13. The computer storage medium of claim 12 , where the received glyph outline is defined by hint coordinates in a hint data structure. | 13. The computer storage medium of claim 12 , where the received glyph outline is defined by hint coordinates in a hint data structure. 14. The computer storage medium of claim 13 , where modifying the horizontal stems includes modifying the hint data structure coordinates for edges of the horizontal stems to define modified hints. | 0.921887 |
8,060,458 | 1 | 3 | 1. A method of an engineering design, comprising the steps of: (a) constructing a plurality of knowledge components, wherein each knowledge component comprises one or more universal modules, each universal module comprising at least operations, procedures, rules and flows of a corresponding engineering design process, wherein each knowledge component is constructed to have: (i) a data interface having data input and output ports; (ii) a control interface having input and output ports, for defining a logical control relation between the knowledge component and its upstream and downstream knowledge components thereof; (iii) a human-computer interactive interface having input ports, for managing data input and data output through the data input and output ports of the data interface; (iv) a message interface having input ports, for receiving external messages and information; and (v) a third party tool interface having input ports, for accessing third party tools, wherein the logical control relation is automatically established in accordance with the sequences that a user uses the knowledge components to complete the engineering design process; (b) defining a data relation and an execution relation of the plurality of knowledge components so as to correlate the plurality of the knowledge components to each other to form a design process model dynamically and concurrently with the design process without programming, wherein when defining the data relation of the plurality of knowledge components, a data mapping relation between the input and output ports of the plurality of knowledge components is automatically established, wherein the execution relation of the plurality of knowledge components comprises logical relations, data driving relations, time characteristics, message triggering mechanisms and any combination thereof, and wherein data of the design process model is automatically modifiable by a computer that is operatively associated with the plurality of knowledge components, in accordance with the rules adapted for defining the design process model; (c) integrating a variety of software platforms via an uniform environment so as to call the plurality of knowledge components of the design process model to perform an engineering design; and (d) packing two or more knowledge components and the data relation and the execution relation thereof into a parent knowledge component without programming, such that the output ports of the data interface and the control interface of any one but the last knowledge component are respectively connected to the input ports of the data interface and the control interface of the immediate next knowledge component, wherein the parent knowledge component comprises: (I) a parent data interface having input ports connected the input ports of the data interface of the first knowledge component, and output ports connected the output ports of the data interface of the last knowledge component; (II) a parent control interface for defining a logical control relation between the parent knowledge component and the upstream and downstream parent knowledge components thereof, having input ports connected the input ports of the control interface of the first knowledge component, and output ports connected the output ports of the control interface of the last knowledge component; (III) a parent human-computer interactive interface having input ports, for managing data input and data output through the data input and output ports of the parent data interface; (IV) a parent message interface having input ports, for receiving external messages and information; (V) a parent third party tool interface having input ports, for accessing third party tools; (VI) a message registration center configured to establish and manage a variety of messages relating to the parent knowledge component, and send the messages to corresponding internal knowledge components to trigger desired activities thereof, wherein the message registration center is connected between the parent message interface and the message input ports of each internal knowledge component; (VII) a customizable human-computer interactive interface having a variety of types of human-computer interactive controls including a data control for modifying data of the parent knowledge component and a message control for binding desired messages in the message registration center for calling the corresponding internal knowledge components, wherein the customizable human-computer interactive interface is connected to the parent human-computer interactive interface, the message registration center and the first knowledge component; (VIII) a knowledge information index coupled to a knowledge information database and configured to record the index relations of a number of activities of the parent knowledge component and usage specifications, design instructions, experiences and knowledge stored in the knowledge information database, and automatically extract the relevant information from the knowledge information database when the parent knowledge component carries out a certain activity; (IX) a timer configured to send a time message to the message registration center on the basis of the time point set by the parent knowledge component; and (X) a tool registration center configured to record information of the third party tool connected into the parent knowledge component, wherein the information includes access interfaces, data interfaces, starting mechanisms of the third party tool, wherein in operation, modifying the data of the design process model triggers the design process model to be partially or fully executed dynamically and concurrently with the design process, whereby both the definition and execution of the design process model occurs concurrently. | 1. A method of an engineering design, comprising the steps of: (a) constructing a plurality of knowledge components, wherein each knowledge component comprises one or more universal modules, each universal module comprising at least operations, procedures, rules and flows of a corresponding engineering design process, wherein each knowledge component is constructed to have: (i) a data interface having data input and output ports; (ii) a control interface having input and output ports, for defining a logical control relation between the knowledge component and its upstream and downstream knowledge components thereof; (iii) a human-computer interactive interface having input ports, for managing data input and data output through the data input and output ports of the data interface; (iv) a message interface having input ports, for receiving external messages and information; and (v) a third party tool interface having input ports, for accessing third party tools, wherein the logical control relation is automatically established in accordance with the sequences that a user uses the knowledge components to complete the engineering design process; (b) defining a data relation and an execution relation of the plurality of knowledge components so as to correlate the plurality of the knowledge components to each other to form a design process model dynamically and concurrently with the design process without programming, wherein when defining the data relation of the plurality of knowledge components, a data mapping relation between the input and output ports of the plurality of knowledge components is automatically established, wherein the execution relation of the plurality of knowledge components comprises logical relations, data driving relations, time characteristics, message triggering mechanisms and any combination thereof, and wherein data of the design process model is automatically modifiable by a computer that is operatively associated with the plurality of knowledge components, in accordance with the rules adapted for defining the design process model; (c) integrating a variety of software platforms via an uniform environment so as to call the plurality of knowledge components of the design process model to perform an engineering design; and (d) packing two or more knowledge components and the data relation and the execution relation thereof into a parent knowledge component without programming, such that the output ports of the data interface and the control interface of any one but the last knowledge component are respectively connected to the input ports of the data interface and the control interface of the immediate next knowledge component, wherein the parent knowledge component comprises: (I) a parent data interface having input ports connected the input ports of the data interface of the first knowledge component, and output ports connected the output ports of the data interface of the last knowledge component; (II) a parent control interface for defining a logical control relation between the parent knowledge component and the upstream and downstream parent knowledge components thereof, having input ports connected the input ports of the control interface of the first knowledge component, and output ports connected the output ports of the control interface of the last knowledge component; (III) a parent human-computer interactive interface having input ports, for managing data input and data output through the data input and output ports of the parent data interface; (IV) a parent message interface having input ports, for receiving external messages and information; (V) a parent third party tool interface having input ports, for accessing third party tools; (VI) a message registration center configured to establish and manage a variety of messages relating to the parent knowledge component, and send the messages to corresponding internal knowledge components to trigger desired activities thereof, wherein the message registration center is connected between the parent message interface and the message input ports of each internal knowledge component; (VII) a customizable human-computer interactive interface having a variety of types of human-computer interactive controls including a data control for modifying data of the parent knowledge component and a message control for binding desired messages in the message registration center for calling the corresponding internal knowledge components, wherein the customizable human-computer interactive interface is connected to the parent human-computer interactive interface, the message registration center and the first knowledge component; (VIII) a knowledge information index coupled to a knowledge information database and configured to record the index relations of a number of activities of the parent knowledge component and usage specifications, design instructions, experiences and knowledge stored in the knowledge information database, and automatically extract the relevant information from the knowledge information database when the parent knowledge component carries out a certain activity; (IX) a timer configured to send a time message to the message registration center on the basis of the time point set by the parent knowledge component; and (X) a tool registration center configured to record information of the third party tool connected into the parent knowledge component, wherein the information includes access interfaces, data interfaces, starting mechanisms of the third party tool, wherein in operation, modifying the data of the design process model triggers the design process model to be partially or fully executed dynamically and concurrently with the design process, whereby both the definition and execution of the design process model occurs concurrently. 3. The method of claim 1 , wherein when calling the plurality of knowledge components, the data relation of the plurality of knowledge components is automatically established based on the rules. | 0.916952 |
8,949,773 | 3 | 4 | 3. The method of claim 1 , further including: automatically updating the in-memory model of the use case in response to the process model or the selected business process model or both being changed. | 3. The method of claim 1 , further including: automatically updating the in-memory model of the use case in response to the process model or the selected business process model or both being changed. 4. The method of claim 3 , wherein the automatically updating further includes automatically updating the natural language text describing the use case. | 0.964083 |
10,142,269 | 12 | 21 | 12. A system, comprising: a processing device; a network interface; non-transitory computer readable memory storing program code that when executed by the processing device is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; enable delivery of a voice message, directed to the user, to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the voice message to be played via a web browser of a second computing device associated with the user; enable the user to send a textual reply message, via the web browser of the second computing device associated with the user, to an originator of the voice message without the user entering an address of the originator of the voice message: receive, via the network interface, a user voice message deletion instruction from the web browser of the second computing device associated with the user; and in response to the user voice message deletion instruction received from the web browser of the second computing device associated with the user, enable, in cooperation with the software program on the first computing device associated with of the user, deletion of the voice message on the first computing device associated with the user. | 12. A system, comprising: a processing device; a network interface; non-transitory computer readable memory storing program code that when executed by the processing device is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; enable delivery of a voice message, directed to the user, to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the voice message to be played via a web browser of a second computing device associated with the user; enable the user to send a textual reply message, via the web browser of the second computing device associated with the user, to an originator of the voice message without the user entering an address of the originator of the voice message: receive, via the network interface, a user voice message deletion instruction from the web browser of the second computing device associated with the user; and in response to the user voice message deletion instruction received from the web browser of the second computing device associated with the user, enable, in cooperation with the software program on the first computing device associated with of the user, deletion of the voice message on the first computing device associated with the user. 21. The system as defined in claim 12 , wherein the system is further configured to: receive a verified phone address associated with the user, wherein a verification of the phone address comprises verification that a received set of digits is a valid phone address. | 0.749529 |
7,584,180 | 1 | 5 | 1. A computer-implemented method for enabling response to a query, the method comprising: receiving a query entered by a first user using a computer system; creating a selectable link that is representative of the query entered by the first user; causing a scrolling display of other selectable links that are representative of other received queries to be displayed by another computer system; causing the selectable link that is representative of the query entered by the first user to be added to the scrolling display displayed by the other computer system; receiving, from the other computer system, an indication of a selection, from within the scrolling display and by a second user, of the selectable link that is representative of the query entered by the first user; in response to receiving the indication of the selection of the selectable link that is representative of the query entered by the first user, providing a mechanism for responding to the query entered by the first user; and receiving, from the second user, a response to the query entered by the first user using the provided mechanism for responding. | 1. A computer-implemented method for enabling response to a query, the method comprising: receiving a query entered by a first user using a computer system; creating a selectable link that is representative of the query entered by the first user; causing a scrolling display of other selectable links that are representative of other received queries to be displayed by another computer system; causing the selectable link that is representative of the query entered by the first user to be added to the scrolling display displayed by the other computer system; receiving, from the other computer system, an indication of a selection, from within the scrolling display and by a second user, of the selectable link that is representative of the query entered by the first user; in response to receiving the indication of the selection of the selectable link that is representative of the query entered by the first user, providing a mechanism for responding to the query entered by the first user; and receiving, from the second user, a response to the query entered by the first user using the provided mechanism for responding. 5. The method of claim 1 , further comprising: receiving an indication of a request by the second user to strike a selectable link that is representative of a query from the scrolling display; and in response to receiving the indication of the request by the second user to strike the selectable link from the scrolling display, removing the requested selectable link from the scrolling display. | 0.807317 |
10,013,396 | 12 | 18 | 12. A method comprising: generating a preview document of a native document comprising a preview code including table elements corresponding to fields in the native document, the native document stored on a client device, the generating comprising: generating field dimensions for the fields in the native document; generating a field mapping of fields in the native document to table elements in the preview code; generating a formula listing designating, for each formula of a set of formulas in the native document, one or more fields associated with the formula in the native document; and displaying the preview document on a display by executing the preview code; generating an updated preview document in response to a change to the native document; swapping the updated preview document with the displayed preview document; and applying a current user interaction context to the swapped updated preview document. | 12. A method comprising: generating a preview document of a native document comprising a preview code including table elements corresponding to fields in the native document, the native document stored on a client device, the generating comprising: generating field dimensions for the fields in the native document; generating a field mapping of fields in the native document to table elements in the preview code; generating a formula listing designating, for each formula of a set of formulas in the native document, one or more fields associated with the formula in the native document; and displaying the preview document on a display by executing the preview code; generating an updated preview document in response to a change to the native document; swapping the updated preview document with the displayed preview document; and applying a current user interaction context to the swapped updated preview document. 18. The method of claim 12 , wherein generating the formula listing comprises expanding a formula that does not list a specific formula for each field in a range of fields. | 0.890724 |
7,610,546 | 1 | 11 | 1. A document processing apparatus comprising: an input device; a display device; a processor; a memory device which stores a plurality of instructions, which when executed by the processor, cause the processor to operate with the display device and the input device to: (a) detect video data designation information attached to electronic document data, the electronic document data including: (i) a first element having a first central activation value used to generate an index; (ii) a second element having a second central activation value used to generate said index; and (iii) read out audio attribute information; (b) generate a summary of said electronic document data, wherein said generation of said summary includes spreading said first central activation value to said second central activation value; (c) select video data in accordance with said detected video data designation information; (d) store a categorization model, the categorization model including a plurality of data categories; (e) create an automatic categorization based on any one of said video data and electronic document data in accordance with the categorization model; (f) update the categorization model with the automatic categorization; (g) control an output of said summary of said electronic document data such that said summary of said electronic data being output is automatically progressed based on at least one of a size of a display area and a length of time displayed; (h) control an output of said selected video data in correspondence with the output of said summary of said electronic document data such that said selected video data being output is output in synchronization with said progress of the said operation of outputting said summary of said electronic data; (i) control an output of a read out audio based on read out audio attribute information in said electronic document to synthesize said read out audio; and (j) automatically terminate the output of said video data upon completion of the outputting of said summary of said electronic document data regardless of whether an end of the video data has been reached. | 1. A document processing apparatus comprising: an input device; a display device; a processor; a memory device which stores a plurality of instructions, which when executed by the processor, cause the processor to operate with the display device and the input device to: (a) detect video data designation information attached to electronic document data, the electronic document data including: (i) a first element having a first central activation value used to generate an index; (ii) a second element having a second central activation value used to generate said index; and (iii) read out audio attribute information; (b) generate a summary of said electronic document data, wherein said generation of said summary includes spreading said first central activation value to said second central activation value; (c) select video data in accordance with said detected video data designation information; (d) store a categorization model, the categorization model including a plurality of data categories; (e) create an automatic categorization based on any one of said video data and electronic document data in accordance with the categorization model; (f) update the categorization model with the automatic categorization; (g) control an output of said summary of said electronic document data such that said summary of said electronic data being output is automatically progressed based on at least one of a size of a display area and a length of time displayed; (h) control an output of said selected video data in correspondence with the output of said summary of said electronic document data such that said selected video data being output is output in synchronization with said progress of the said operation of outputting said summary of said electronic data; (i) control an output of a read out audio based on read out audio attribute information in said electronic document to synthesize said read out audio; and (j) automatically terminate the output of said video data upon completion of the outputting of said summary of said electronic document data regardless of whether an end of the video data has been reached. 11. The document processing apparatus of claim 1 , wherein when executed by the processor, said plurality of instructions cause the processor to operate with the display device to create the automatic categorization using a word sense relevance value. | 0.7019 |
9,949,103 | 2 | 6 | 2. The method of claim 1 , further comprising: classifying the composed message into a category; and wherein the set of previous messages is limited to messages that share the category with the composed message. | 2. The method of claim 1 , further comprising: classifying the composed message into a category; and wherein the set of previous messages is limited to messages that share the category with the composed message. 6. The method of claim 2 , wherein the category is a communication-medium category. | 0.971161 |
8,126,984 | 2 | 3 | 2. The system of claim 1 , wherein the interface adaptation service adapts the user interface of the client device to select a sensory communication path for interaction of the user with the enterprise service suited to a context described by the context information. | 2. The system of claim 1 , wherein the interface adaptation service adapts the user interface of the client device to select a sensory communication path for interaction of the user with the enterprise service suited to a context described by the context information. 3. The system of claim 2 wherein the sensory communication path selected comprises at least one of a voice communication path, a text communication path, and a graphical communication path. | 0.960772 |
8,700,612 | 15 | 26 | 15. A non-transitory computer-readable storage medium storing instructions that, when executed, cause a processing device to perform a method comprising: receiving a search input; selecting a first cell within a matrix of cells in response to the search input, wherein each cell within the matrix of cells includes searchable data, the first cell is selected based upon the first cell including searchable data related to the search input, and the first cell further includes a first link assigned a causal context relationship and providing a navigation link from the first cell to a causal context cell corresponding to the first cell, a second link assigned an inclusion contextual relationship and providing a navigation link from the first cell to an inclusion context cell corresponding to the first cell, a third link assigned a temporal contextual relationship and providing a navigation link from the first cell to a temporal context cell corresponding to the first cell, and fourth link assigned a spatial contextual relationship and providing a navigation link from the first cell to a spatial context cell corresponding to the first cell; displaying, in response to the search input, a portion of the searchable data of the first cell and first, second, third, and fourth selectable objects, the first selectable object corresponding to the first link, the second selectable object corresponding to the second link, the third selectable object corresponding to the third link, and the fourth selectable object corresponding to the fourth link; receiving selection of the first, second, third, or fourth of the plurality of selectable objects; and utilizing the corresponding link to display a context cell corresponding to the first cell, wherein selection of a first of the plurality of selectable objects results in the computer utilizing the first link to select and display the causal context cell corresponding to the first cell, the display of the causal context cell including displaying a subject of the first cell as causing or influencing one or more subjects of other cells or as being caused or influenced by one or more subjects of other cells, wherein selection of a second of the plurality of selectable objects results in the computer utilizing the second link to select and display the inclusion context cell corresponding to the first cell, the display of the inclusion context cell including displaying the subject of the first cell within a category along with subjects of other cells included within the category, wherein selection of a third of the plurality of selectable objects results in the computer utilizing the third link to select and display the temporal context cell corresponding to the first cell, the display of the temporal context cell including displaying the subject of the first cell within a timeline along with subjects of other cells of relevance within the timeline, wherein selection of a fourth of the plurality of selectable objects results in the computer utilizing the fourth link to select and display the spatial context cell corresponding to the first cell, the display of the spatial context cell including displaying a location corresponding to the subject of the first cell within a map, and when the received selection is of the first of the plurality of selectable objects, the method further comprising receiving a command to alter the zoom of the display of the corresponding portion of the data of the first cell and the first set of other data and, in response to the zoom command, adding or removing subjects that served as a cause of or influence upon the subject of the first cell, or adding or removing subjects that were caused or influenced by the subject of the first cell. | 15. A non-transitory computer-readable storage medium storing instructions that, when executed, cause a processing device to perform a method comprising: receiving a search input; selecting a first cell within a matrix of cells in response to the search input, wherein each cell within the matrix of cells includes searchable data, the first cell is selected based upon the first cell including searchable data related to the search input, and the first cell further includes a first link assigned a causal context relationship and providing a navigation link from the first cell to a causal context cell corresponding to the first cell, a second link assigned an inclusion contextual relationship and providing a navigation link from the first cell to an inclusion context cell corresponding to the first cell, a third link assigned a temporal contextual relationship and providing a navigation link from the first cell to a temporal context cell corresponding to the first cell, and fourth link assigned a spatial contextual relationship and providing a navigation link from the first cell to a spatial context cell corresponding to the first cell; displaying, in response to the search input, a portion of the searchable data of the first cell and first, second, third, and fourth selectable objects, the first selectable object corresponding to the first link, the second selectable object corresponding to the second link, the third selectable object corresponding to the third link, and the fourth selectable object corresponding to the fourth link; receiving selection of the first, second, third, or fourth of the plurality of selectable objects; and utilizing the corresponding link to display a context cell corresponding to the first cell, wherein selection of a first of the plurality of selectable objects results in the computer utilizing the first link to select and display the causal context cell corresponding to the first cell, the display of the causal context cell including displaying a subject of the first cell as causing or influencing one or more subjects of other cells or as being caused or influenced by one or more subjects of other cells, wherein selection of a second of the plurality of selectable objects results in the computer utilizing the second link to select and display the inclusion context cell corresponding to the first cell, the display of the inclusion context cell including displaying the subject of the first cell within a category along with subjects of other cells included within the category, wherein selection of a third of the plurality of selectable objects results in the computer utilizing the third link to select and display the temporal context cell corresponding to the first cell, the display of the temporal context cell including displaying the subject of the first cell within a timeline along with subjects of other cells of relevance within the timeline, wherein selection of a fourth of the plurality of selectable objects results in the computer utilizing the fourth link to select and display the spatial context cell corresponding to the first cell, the display of the spatial context cell including displaying a location corresponding to the subject of the first cell within a map, and when the received selection is of the first of the plurality of selectable objects, the method further comprising receiving a command to alter the zoom of the display of the corresponding portion of the data of the first cell and the first set of other data and, in response to the zoom command, adding or removing subjects that served as a cause of or influence upon the subject of the first cell, or adding or removing subjects that were caused or influenced by the subject of the first cell. 26. The non-transitory computer-readable medium of claim 15 , wherein the instructions, when executed, cause the processing device to perform a method further comprising: receiving user input to add a second cell within the matrix of cells or create a new link between two cells. | 0.727539 |
7,552,381 | 1 | 13 | 1. A computer-implemented method comprising: scanning a coversheet having an overview of a collection; receiving an image of the overview of the collection that comprises a first plurality of indication areas associated with a plurality of documents and a second plurality of indication areas associated with a plurality of actions, wherein the plurality of actions includes printing, faxing, sending by electronic mail, and grouping; identifying at least one action from the plurality of actions set forth in the image; identifying at least one document from the plurality of documents for the at least one action identified from the plurality of actions, wherein the identifying the at least one action from the plurality of actions set forth in the image is performed based on the second plurality of the indication areas in the image, the identifying the at least one document from the plurality of documents is performed based on the first plurality of the indication areas in the image, wherein the at least one action from the plurality of actions and the at least one document from the plurality of documents are identified by scanning the image; and performing the at least one action on the at least one document in response to the identifying the at least one action from the fourth plurality of actions set forth in the image and the identifying the at least one document from the third plurality of documents from the image. | 1. A computer-implemented method comprising: scanning a coversheet having an overview of a collection; receiving an image of the overview of the collection that comprises a first plurality of indication areas associated with a plurality of documents and a second plurality of indication areas associated with a plurality of actions, wherein the plurality of actions includes printing, faxing, sending by electronic mail, and grouping; identifying at least one action from the plurality of actions set forth in the image; identifying at least one document from the plurality of documents for the at least one action identified from the plurality of actions, wherein the identifying the at least one action from the plurality of actions set forth in the image is performed based on the second plurality of the indication areas in the image, the identifying the at least one document from the plurality of documents is performed based on the first plurality of the indication areas in the image, wherein the at least one action from the plurality of actions and the at least one document from the plurality of documents are identified by scanning the image; and performing the at least one action on the at least one document in response to the identifying the at least one action from the fourth plurality of actions set forth in the image and the identifying the at least one document from the third plurality of documents from the image. 13. The method defined in claim 1 wherein the plurality of actions comprise two or more of a group consisting of printing, faxing, sending by electronic mail, deleting, grouping, ungrouping, and playing. | 0.794534 |
8,200,651 | 10 | 11 | 10. A computer program product for facilitating user comprehension of digitally encoded texts, the computer program product comprising: a non-transitory computer-usable medium including: computer program instructions for accessing a plurality of dictionary databases; computer program instructions for associating at least one content category with each dictionary database; computer program instructions for associating at least one predetermined marking with each of the plurality of dictionary databases; computer program instructions for identifying at least one text portion marked by the user with a first marking; computer program instructions for identifying at least one additional text portion marked by the user with a second marking, the second marking being different from the first marking, the at least one text portion and the at least one additional text portion being part of a same digitally encoded text; computer program instructions for identifying one or more dictionary databases associated with the first marking; computer program instructions for determining a subset of dictionary database(s) from the one or more dictionary databases identified as being associated with the first marking, each dictionary database in the subset having a content category that corresponds to the at least one text portion; computer program instructions for identifying one or more dictionary databases associated with the second marking; computer program instructions for initiating a searching process comprising performing a first search of the at least one text portion within the subset of dictionary database(s) and performing a second search of the at least one additional text portion with the one or more dictionary databases associated with the second marking; computer program instructions for displaying the results of the first and second searches to the user in a consolidated format. | 10. A computer program product for facilitating user comprehension of digitally encoded texts, the computer program product comprising: a non-transitory computer-usable medium including: computer program instructions for accessing a plurality of dictionary databases; computer program instructions for associating at least one content category with each dictionary database; computer program instructions for associating at least one predetermined marking with each of the plurality of dictionary databases; computer program instructions for identifying at least one text portion marked by the user with a first marking; computer program instructions for identifying at least one additional text portion marked by the user with a second marking, the second marking being different from the first marking, the at least one text portion and the at least one additional text portion being part of a same digitally encoded text; computer program instructions for identifying one or more dictionary databases associated with the first marking; computer program instructions for determining a subset of dictionary database(s) from the one or more dictionary databases identified as being associated with the first marking, each dictionary database in the subset having a content category that corresponds to the at least one text portion; computer program instructions for identifying one or more dictionary databases associated with the second marking; computer program instructions for initiating a searching process comprising performing a first search of the at least one text portion within the subset of dictionary database(s) and performing a second search of the at least one additional text portion with the one or more dictionary databases associated with the second marking; computer program instructions for displaying the results of the first and second searches to the user in a consolidated format. 11. The computer program product of claim 10 further comprising computer program instructions for accessing at least one of the plurality of dictionary databases through a network. | 0.745042 |
8,156,459 | 11 | 12 | 11. The method of claim 10 , wherein the processor and the memory are further configured to: indentify blocks of text within the first and second text-based models which correspond to blocks of the high level block diagram-based model. | 11. The method of claim 10 , wherein the processor and the memory are further configured to: indentify blocks of text within the first and second text-based models which correspond to blocks of the high level block diagram-based model. 12. The method of claim 11 , wherein the processor and the memory are further configured to: identify each block that has been added, modified, or deleted; and store data indicating each block that has been added, modified, or deleted. | 0.823042 |
8,086,600 | 13 | 14 | 13. A system comprising: one or more computers; and a computer-readable storage device having stored thereon instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a plurality of first search results in a first presentation format, the first search results received from a first search engine, the first search results identified for a search query directed to the first search engine, the first search results having an associated order indicative of respective first quality scores that are used to rank the first search results; receiving one or more second search results in a second presentation format different from the first presentation format, the second search results received from a second search engine, the second search results identified for the search query directed to the second search engine, wherein the first search engine searches a first corpus of first resources, wherein the second search engine searches a second corpus of second resources, and wherein the first search engine and the second search engines are distinct from each other; obtaining a respective first quality score for a plurality of the first search results, the respective first quality score determined in relation to the corpus of first resources and obtaining a respective second quality score for each of the one or more second search results, each respective second quality score determined in relation to the corpus of second resources; and inserting one or more of the second search results into the order including decreasing one or more of the respective first quality scores by reducing a contribution of a scoring feature unique to the first search results and distinct from scoring features of the second search results so that the inserted second search results occur within a number of top- ranked search results in the order. | 13. A system comprising: one or more computers; and a computer-readable storage device having stored thereon instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a plurality of first search results in a first presentation format, the first search results received from a first search engine, the first search results identified for a search query directed to the first search engine, the first search results having an associated order indicative of respective first quality scores that are used to rank the first search results; receiving one or more second search results in a second presentation format different from the first presentation format, the second search results received from a second search engine, the second search results identified for the search query directed to the second search engine, wherein the first search engine searches a first corpus of first resources, wherein the second search engine searches a second corpus of second resources, and wherein the first search engine and the second search engines are distinct from each other; obtaining a respective first quality score for a plurality of the first search results, the respective first quality score determined in relation to the corpus of first resources and obtaining a respective second quality score for each of the one or more second search results, each respective second quality score determined in relation to the corpus of second resources; and inserting one or more of the second search results into the order including decreasing one or more of the respective first quality scores by reducing a contribution of a scoring feature unique to the first search results and distinct from scoring features of the second search results so that the inserted second search results occur within a number of top- ranked search results in the order. 14. The system of claim 13 , wherein the plurality of first search results comprises an ordered list of search results, and wherein the plurality of first search results is a number of highest-quality search results provided by the first search engine that are identified as responsive to the search query. | 0.612658 |
9,774,736 | 8 | 9 | 8. A non-transitory, computer-readable medium comprising computer-executable instructions for determining whether a call has reached a live party or a machine, that when executed, cause a call handler that is handling the call to: analyze a cadence of audio of the call; establish a call leg to a speech analytics system so that the speech analytics system can analyze the audio of the call over the call leg to detect one or more keywords; make a first determination that the call has reached the live party or the machine based on the cadence of the audio; receive an event from the speech analytics system as a result of the speech analytics system detecting a particular keyword in the audio of the call; upon receiving the event, make a second determination that the call has reached the live party or the machine based on the particular keyword detected in the audio of the call; and connect the call with a second live party so that the second live party can converse with the live party reached on the call in response to the first and second determinations indicating the call has reached the live party. | 8. A non-transitory, computer-readable medium comprising computer-executable instructions for determining whether a call has reached a live party or a machine, that when executed, cause a call handler that is handling the call to: analyze a cadence of audio of the call; establish a call leg to a speech analytics system so that the speech analytics system can analyze the audio of the call over the call leg to detect one or more keywords; make a first determination that the call has reached the live party or the machine based on the cadence of the audio; receive an event from the speech analytics system as a result of the speech analytics system detecting a particular keyword in the audio of the call; upon receiving the event, make a second determination that the call has reached the live party or the machine based on the particular keyword detected in the audio of the call; and connect the call with a second live party so that the second live party can converse with the live party reached on the call in response to the first and second determinations indicating the call has reached the live party. 9. The non-transitory, computer-readable medium of claim 8 , wherein the computer-executable instructions are configured to cause the call handler, in response to the first and second determinations indicating the call has reached the machine, to determine that the call has reached an auto attendant, has reached a voice mail, or has been placed on hold based on at least one additional event received from the speech analytics system. | 0.501144 |
9,646,166 | 8 | 9 | 8. The method of claim 1 , wherein the second entry is computed by applying a pseudorandom function to the attribute value to obtain an intermediate value, multiplying the intermediate value with the encrypted randomized index value to obtain a product, and performing an exponentiation of the product in an algebraic group. | 8. The method of claim 1 , wherein the second entry is computed by applying a pseudorandom function to the attribute value to obtain an intermediate value, multiplying the intermediate value with the encrypted randomized index value to obtain a product, and performing an exponentiation of the product in an algebraic group. 9. The method of claim 8 , wherein the algebraic group is a cyclic group. | 0.978504 |
8,543,949 | 12 | 13 | 12. A system comprising: an input interface operable to receive a code sequence, along with a hardware resource count specifying a number of hardware resources that are to be allocated for the code sequence, in a high-level language program, wherein the interface includes a processor; and a processor operable to generate hardware acceleration logic for implementing the code sequence using the number of hardware resources specified by the hardware resource count, wherein the number of hardware resources is associated with an amount of logic used to implement the code sequence on a device; wherein the hardware acceleration logic is implemented on the device. | 12. A system comprising: an input interface operable to receive a code sequence, along with a hardware resource count specifying a number of hardware resources that are to be allocated for the code sequence, in a high-level language program, wherein the interface includes a processor; and a processor operable to generate hardware acceleration logic for implementing the code sequence using the number of hardware resources specified by the hardware resource count, wherein the number of hardware resources is associated with an amount of logic used to implement the code sequence on a device; wherein the hardware acceleration logic is implemented on the device. 13. The system of claim 12 , wherein the high-level language program is used by both software simulation design flows and by hardware generation flows. | 0.503289 |
8,326,686 | 11 | 12 | 11. The computer-implemented method of claim 1 , wherein, in the index generated, the one of (A) advertiser document identifiers for the at least one advertiser document on which the extracted information is found, and (B) ad identifiers for ads generated from the at least one advertiser document on which the extracted information is found, includes weights. | 11. The computer-implemented method of claim 1 , wherein, in the index generated, the one of (A) advertiser document identifiers for the at least one advertiser document on which the extracted information is found, and (B) ad identifiers for ads generated from the at least one advertiser document on which the extracted information is found, includes weights. 12. The computer-implemented method of claim 11 , wherein the information from the at least one advertiser document includes terms, each of the terms including one of a word and a phrase, wherein the index generated maps terms extracted from the at least one advertiser document back to one of (A) advertiser document identifiers for the at least one advertiser document on which the extracted terms are found, and (B) ad identifiers for ads generated from the at least one advertiser document on which such terms are found, and wherein the weights are determined as a function of at least one of (A) font size, (B) font attributes, and (C) Meta information, of the terms in the at least one advertiser document. | 0.817623 |
8,705,706 | 17 | 18 | 17. The method of claim 12 further comprising: storing in the database an association between the file and a datum; receiving at the database a first signal that indicates the datum; and in response to the receipt of the first signal, retrieving from the database the files that are associated with the datum. | 17. The method of claim 12 further comprising: storing in the database an association between the file and a datum; receiving at the database a first signal that indicates the datum; and in response to the receipt of the first signal, retrieving from the database the files that are associated with the datum. 18. The method of claim 17 wherein the datum is the telephone number. | 0.965875 |
8,799,768 | 5 | 8 | 5. A computerized system comprising: a document of ambiguous data: a document type definition; a mapper of ambiguous data, operatively coupled to the document and operatively coupled to the document, yielding a mapping file from the document and the document type definition; a disambiguator operatively coupled to the mapping file and the document type definition, yielding an output file; and wherein the document type definition describes a markup syntax; wherein the output file complies with the syntax described by the document type definition; and wherein the disambiguator further comprising: a permutater of two or more candidate paths from the mapping file, operatively coupled to the mapping file, with each candidate path representing a possible path from one node in the mapping file to another node in the mapping file; a scorer of the two or more candidate paths, operatively coupled to the permutater, yielding a corresponding number of two or more scores. | 5. A computerized system comprising: a document of ambiguous data: a document type definition; a mapper of ambiguous data, operatively coupled to the document and operatively coupled to the document, yielding a mapping file from the document and the document type definition; a disambiguator operatively coupled to the mapping file and the document type definition, yielding an output file; and wherein the document type definition describes a markup syntax; wherein the output file complies with the syntax described by the document type definition; and wherein the disambiguator further comprising: a permutater of two or more candidate paths from the mapping file, operatively coupled to the mapping file, with each candidate path representing a possible path from one node in the mapping file to another node in the mapping file; a scorer of the two or more candidate paths, operatively coupled to the permutater, yielding a corresponding number of two or more scores. 8. The computerized system of claim 5 , the disambiguator comprising: a selector of two or more candidate paths, based on the two or more scores, operatively coupled to the scorer, yielding a selected path; and a convertor of the selected candidate path into language described by the document type definition, operatively coupled to the selector of two or more candidate paths and operatively coupled to the document type definition. | 0.62906 |
9,600,771 | 10 | 11 | 10. A non-transitory computer-readable medium storing instructions that, when executed, cause one or more processor to perform operations comprising: segmenting a textual message into a plurality of semantic sentences; analyzing the plurality of semantic sentences to generate a sequence of binary bits, wherein each bit of the sequence of binary bits corresponds to a respective one of the plurality of semantic sentences; determining that a number of the plurality of semantic sentences is suitable to carry a code, wherein the code includes one or more bits; determining that semantic richness of the textual message is sufficient to carry the code; selecting a subset of the plurality of semantic sentences to carry the code; marking the selected subset of the plurality of semantic sentences to carry the code in the textual message; and transmitting the textual message with the code embedded in the marked selected subset of the plurality of semantic sentences, wherein a pattern of the binary bits corresponding to the selected subset of the plurality of semantic sentences matches a pattern of the one or more bits of the code. | 10. A non-transitory computer-readable medium storing instructions that, when executed, cause one or more processor to perform operations comprising: segmenting a textual message into a plurality of semantic sentences; analyzing the plurality of semantic sentences to generate a sequence of binary bits, wherein each bit of the sequence of binary bits corresponds to a respective one of the plurality of semantic sentences; determining that a number of the plurality of semantic sentences is suitable to carry a code, wherein the code includes one or more bits; determining that semantic richness of the textual message is sufficient to carry the code; selecting a subset of the plurality of semantic sentences to carry the code; marking the selected subset of the plurality of semantic sentences to carry the code in the textual message; and transmitting the textual message with the code embedded in the marked selected subset of the plurality of semantic sentences, wherein a pattern of the binary bits corresponding to the selected subset of the plurality of semantic sentences matches a pattern of the one or more bits of the code. 11. The non-transitory computer-readable medium of claim 10 , wherein the determining that semantic richness of the textual message is sufficient to carry the code comprises: comparing the code to the sequence of binary bits; and determining that the one or more bits of the code can be represented by a corresponding number of binary bits of the sequence of binary bits. | 0.689799 |
8,661,338 | 8 | 10 | 8. A method comprising: comparing one or more elements of at least a portion of an original document against the same types of elements in at least a portion each of a plurality of stored documents, wherein the portion of the original document is the portion that requires adjustment or re-layout; determining a particular stored document in the plurality of stored documents, with the portion which is closest to the portion of the original document based on the comparing; identifying a designated output device and output device characteristics; applying one or more mutators to the portion of the original document which were applied to mutate the portion of the determined particular stored document, to form a mutated portion in the original document, having obtained one or more mutators from a list of stored mutators which correspond to the determined particular stored document, wherein the applying further comprises determining which of the one or more stored mutators to apply based on one or more of the characteristics of the designated output device and the identified particular stored document that matches the portion of the original document; and wherein the applying further comprises determining an order for the applying of the determined one or more mutators to the portion of the original document, according to stored priority order. | 8. A method comprising: comparing one or more elements of at least a portion of an original document against the same types of elements in at least a portion each of a plurality of stored documents, wherein the portion of the original document is the portion that requires adjustment or re-layout; determining a particular stored document in the plurality of stored documents, with the portion which is closest to the portion of the original document based on the comparing; identifying a designated output device and output device characteristics; applying one or more mutators to the portion of the original document which were applied to mutate the portion of the determined particular stored document, to form a mutated portion in the original document, having obtained one or more mutators from a list of stored mutators which correspond to the determined particular stored document, wherein the applying further comprises determining which of the one or more stored mutators to apply based on one or more of the characteristics of the designated output device and the identified particular stored document that matches the portion of the original document; and wherein the applying further comprises determining an order for the applying of the determined one or more mutators to the portion of the original document, according to stored priority order. 10. The method as set forth in claim 8 further comprising selecting the portion of the original document for the comparing. | 0.931131 |
7,596,609 | 9 | 13 | 9. A method of WWW page retrieval from a web site, comprising: receiving information associated with content of a web site, wherein said received information is not a WWW address and comprises characters typed for entry by a user into a URL entry field in a browser operable on an electronic device having web browsing capabilities, in which a standard URL address would be entered; said information being received by a software not associated with said site; analyzing said information to correct spelling in said information to a spelling-corrected input; providing a page address of a page of said site, responsive to said spelling corrected input, by said software; sending the page address to the browser for retrieving said page responsive to said page address; and thereby causing said page to be directly displayed to the user using the browser, without any additional user intervention beyond the entry of said information, wherein said page address is determined using a database of associations, said database is at least logically associated with a particular user, and said database includes user information regarding a particular user, which user information is entered by said user, which page is selected for display responsive to said user information and wherein said database is stored at a location remote from where said information received by said software is entered by the user for display of said page. | 9. A method of WWW page retrieval from a web site, comprising: receiving information associated with content of a web site, wherein said received information is not a WWW address and comprises characters typed for entry by a user into a URL entry field in a browser operable on an electronic device having web browsing capabilities, in which a standard URL address would be entered; said information being received by a software not associated with said site; analyzing said information to correct spelling in said information to a spelling-corrected input; providing a page address of a page of said site, responsive to said spelling corrected input, by said software; sending the page address to the browser for retrieving said page responsive to said page address; and thereby causing said page to be directly displayed to the user using the browser, without any additional user intervention beyond the entry of said information, wherein said page address is determined using a database of associations, said database is at least logically associated with a particular user, and said database includes user information regarding a particular user, which user information is entered by said user, which page is selected for display responsive to said user information and wherein said database is stored at a location remote from where said information received by said software is entered by the user for display of said page. 13. A method according to claim 9 , wherein providing a page address comprises providing responsive to a popularity level of said page. | 0.681604 |
8,060,869 | 1 | 12 | 1. A method for providing a binary instrumentation using a binary instrumentation tool to detect memory problems in runtime application executing on a computer system, the method comprising: examining a source code of a runtime application to identify a function having an instruction that accesses memory on the computer system, wherein the source code includes a user provided executable code (UPE), the UPE including a function having an instruction that accesses memory; generating an annotation section when compiling the source code into an executable binary code by a compiler, the annotation section including one or more compiler annotations provided by the compiler for the identified function having one or more instructions, the compiler annotations defining essential functional characteristic data related to the identified function based on examination of the one or more instructions and providing guidelines for inserting checker codes, the generated annotation section associated with the executable binary code; defining and inserting a checker code into the original function code of the identified function to obtain a modified function code based on the guidelines provided by compiler annotations in the annotation section associated with the function, the checker code defined by the program error detector (PED); and generating a modified executable binary code of the runtime application by replacing the original function code of the identified function with the corresponding modified function code, the modified executable binary code generated by the PED based on the annotations associated with the identified function, the modified executable binary code invoking a checker upon execution of the appropriate function, the checker enabling efficient detection of program memory errors associated with the identified function, wherein the operations of examining, generating and defining are performed by a processor of a computer. | 1. A method for providing a binary instrumentation using a binary instrumentation tool to detect memory problems in runtime application executing on a computer system, the method comprising: examining a source code of a runtime application to identify a function having an instruction that accesses memory on the computer system, wherein the source code includes a user provided executable code (UPE), the UPE including a function having an instruction that accesses memory; generating an annotation section when compiling the source code into an executable binary code by a compiler, the annotation section including one or more compiler annotations provided by the compiler for the identified function having one or more instructions, the compiler annotations defining essential functional characteristic data related to the identified function based on examination of the one or more instructions and providing guidelines for inserting checker codes, the generated annotation section associated with the executable binary code; defining and inserting a checker code into the original function code of the identified function to obtain a modified function code based on the guidelines provided by compiler annotations in the annotation section associated with the function, the checker code defined by the program error detector (PED); and generating a modified executable binary code of the runtime application by replacing the original function code of the identified function with the corresponding modified function code, the modified executable binary code generated by the PED based on the annotations associated with the identified function, the modified executable binary code invoking a checker upon execution of the appropriate function, the checker enabling efficient detection of program memory errors associated with the identified function, wherein the operations of examining, generating and defining are performed by a processor of a computer. 12. The method for providing a binary instrumentation using a binary instrumentation tool to detect memory problems in runtime application executing on a computer system of claim 1 , wherein the program memory errors that may be detected include any one of uninitialized variable usage, memory leaks along with the corresponding location, array access violation, stack access violation, access beyond stack bounds, access beyond array bounds, incorrect parameter for function calls, unallocated memory read, double free memory, free memory read, partially initialized data access. | 0.51586 |
7,827,210 | 6 | 10 | 6. A computer system for translating data from a hierarchical data structure to a relational data structure, the computer system comprising: a converter for: defining at least one shredding tree that each translate a hierarchical data structure into a relational data structure, each of the at least one shredding tree defining a hierarchical data structure comprising at least one cursor node and at least one data node, wherein each of the at least one cursor node defines, in conjunction with parent cursor nodes, a column within the relational data structure, and each of the at least one data node being an immediate child of a respective parent cursor node within the at least one cursor nodes, each of the at least one data node comprising a respective data element to be inserted at the column defined by the respective parent cursor node; reading at least one data element from a subset of the at least one data node of a first part of a hierarchical data structure instance using a tree traversal algorithm defined by the at least one shredding tree; maintaining: a set of tree commit counter, each tree commit counter being associated with a respective shredding tree within the at least one shredding tree; and a global commit counter; decrementing, in response to the storing, a current tree commit counter within the set of tree commit counters, the current tree commit counter being associated with the current shredding tree; and decrementing, in response to the storing, the global commit counter; a first storage for storing the at least one data element in a first storage according to the relational data structure defined by a current shredding tree comprising the at least one data node containing the at least one data element; and a relational database controller for determining, in response to the storing, that the first storage stores a quantity of data that is greater than a threshold and that at least one of a tree commit counter within the set of tree commit counters and the global commit counter has been decremented to zero, and for, in response to the determining, transferring data stored in the first storage to a relational data structure according to the mapping. | 6. A computer system for translating data from a hierarchical data structure to a relational data structure, the computer system comprising: a converter for: defining at least one shredding tree that each translate a hierarchical data structure into a relational data structure, each of the at least one shredding tree defining a hierarchical data structure comprising at least one cursor node and at least one data node, wherein each of the at least one cursor node defines, in conjunction with parent cursor nodes, a column within the relational data structure, and each of the at least one data node being an immediate child of a respective parent cursor node within the at least one cursor nodes, each of the at least one data node comprising a respective data element to be inserted at the column defined by the respective parent cursor node; reading at least one data element from a subset of the at least one data node of a first part of a hierarchical data structure instance using a tree traversal algorithm defined by the at least one shredding tree; maintaining: a set of tree commit counter, each tree commit counter being associated with a respective shredding tree within the at least one shredding tree; and a global commit counter; decrementing, in response to the storing, a current tree commit counter within the set of tree commit counters, the current tree commit counter being associated with the current shredding tree; and decrementing, in response to the storing, the global commit counter; a first storage for storing the at least one data element in a first storage according to the relational data structure defined by a current shredding tree comprising the at least one data node containing the at least one data element; and a relational database controller for determining, in response to the storing, that the first storage stores a quantity of data that is greater than a threshold and that at least one of a tree commit counter within the set of tree commit counters and the global commit counter has been decremented to zero, and for, in response to the determining, transferring data stored in the first storage to a relational data structure according to the mapping. 10. The computer system of claim 6 , wherein the shredding tree is defined by one of an annotated XML schema an annotated document type definition document, the one of the annotated XML schema and annotated document type definition document defining a hierarchical data structure definition with annotations, wherein the annotations comprise a first set of annotations for at least one leaf node of the hierarchical data structure definition that define a respective binding between a data element of the respective at least one leaf node and a column of the hierarchical data structure. | 0.50085 |
10,049,293 | 8 | 9 | 8. A system, comprising: a video input receiver configured to receive a plurality of video frames of a video scene; at least one processor; and a memory having processor-executable instructions and in communication with the at least one processor, the instructions in the memory comprising instructions for the at least one processor to: determine at least one pixel-level characteristic for a foreground patch in a first video frame from the plurality of video frames of a video scene received by the video input receiver, the foreground patch including a set of pixels containing a portion of scene foreground in the first video frame of the video scene, determine kinematics of an object in the video scene based at least in part on the at least one pixel-level characteristic, generate a micro-feature vector based at least in part on at least on the kinematics of the object, the micro-feature vector corresponding to at least one micro-feature value; update a neural network based at least in part on the micro-feature vector, the neural network including a plurality of clusters, each cluster in the plurality of clusters representing an object type, classify the object in the first video frame of the video scene as a first object type based on the updated neural network, the first object type being represented by a first cluster in the plurality of clusters, and track the object in the video scene based on the micro-feature vector and the first object type. | 8. A system, comprising: a video input receiver configured to receive a plurality of video frames of a video scene; at least one processor; and a memory having processor-executable instructions and in communication with the at least one processor, the instructions in the memory comprising instructions for the at least one processor to: determine at least one pixel-level characteristic for a foreground patch in a first video frame from the plurality of video frames of a video scene received by the video input receiver, the foreground patch including a set of pixels containing a portion of scene foreground in the first video frame of the video scene, determine kinematics of an object in the video scene based at least in part on the at least one pixel-level characteristic, generate a micro-feature vector based at least in part on at least on the kinematics of the object, the micro-feature vector corresponding to at least one micro-feature value; update a neural network based at least in part on the micro-feature vector, the neural network including a plurality of clusters, each cluster in the plurality of clusters representing an object type, classify the object in the first video frame of the video scene as a first object type based on the updated neural network, the first object type being represented by a first cluster in the plurality of clusters, and track the object in the video scene based on the micro-feature vector and the first object type. 9. The system of claim 8 , wherein the instructions for the at least one processor to update the neural network include instructions to: (1) create the first cluster representing the first object type, and/or (2) update the first cluster in the plurality of clusters representing the first object type based on the micro-feature vector. | 0.61991 |
9,180,778 | 1 | 4 | 1. A display system for a vehicle, comprising: a monitor having a display and a plurality of operational selectors in the vehicle, the monitor being configured to display a plurality of language choices in their native text when at least one of the operational selectors is activated for a predetermined length of time; and a controller in communication with the monitor, the controller being configured to direct the monitor to display vehicle information in one of the languages when a corresponding one of the plurality of language choices is selected by activating at least one of the plurality of operational selectors; wherein the monitor displays the plurality of language choices in their native text without the need for another activation or combination of activations before or after the activation of the operational selector for the predetermined length of time. | 1. A display system for a vehicle, comprising: a monitor having a display and a plurality of operational selectors in the vehicle, the monitor being configured to display a plurality of language choices in their native text when at least one of the operational selectors is activated for a predetermined length of time; and a controller in communication with the monitor, the controller being configured to direct the monitor to display vehicle information in one of the languages when a corresponding one of the plurality of language choices is selected by activating at least one of the plurality of operational selectors; wherein the monitor displays the plurality of language choices in their native text without the need for another activation or combination of activations before or after the activation of the operational selector for the predetermined length of time. 4. The display system of claim 1 , wherein the plurality of operational selectors comprise a plurality of selection switches. | 0.771062 |
8,724,890 | 1 | 2 | 1. A method for training and using an object classifier to identify a class object from a captured image, the method comprising the steps of: (a) obtaining a plurality of still images from training data; (b) applying a feature generation technique to the plurality of still images of the training data for identifying candidate features from each respective image, wherein applying the feature generation technique further comprises the steps of: identifying a comparative image of a known object; randomly extracting a fragment from the comparative image; comparing the extracted fragment to each of the plurality of still images, wherein each still image is partitioned into a plurality of image sections that are identified by an image position, wherein the fragment and each image position are compared using a feature descriptor technique; determining a similarity score between the fragment and each image position in each image; identifying the respective image position having a highest similarity score in each respective image; compiling a group of fragments that have the highest similarity score from each respective image; (c) selecting a subset of features from the candidate features using a similarity comparison technique; (d) iteratively repeating steps (a) through (c) a predetermined number of times as a function of the selected subset of features identified in step (c); (e) generating a trained object classifier; (f) capturing an image from an image capture device; (g) classifying features in the captured image using the trained object classifier; and (h) determining whether the captured image contains a class object based on the trained object classifier associating an identified feature in the image with the class object. | 1. A method for training and using an object classifier to identify a class object from a captured image, the method comprising the steps of: (a) obtaining a plurality of still images from training data; (b) applying a feature generation technique to the plurality of still images of the training data for identifying candidate features from each respective image, wherein applying the feature generation technique further comprises the steps of: identifying a comparative image of a known object; randomly extracting a fragment from the comparative image; comparing the extracted fragment to each of the plurality of still images, wherein each still image is partitioned into a plurality of image sections that are identified by an image position, wherein the fragment and each image position are compared using a feature descriptor technique; determining a similarity score between the fragment and each image position in each image; identifying the respective image position having a highest similarity score in each respective image; compiling a group of fragments that have the highest similarity score from each respective image; (c) selecting a subset of features from the candidate features using a similarity comparison technique; (d) iteratively repeating steps (a) through (c) a predetermined number of times as a function of the selected subset of features identified in step (c); (e) generating a trained object classifier; (f) capturing an image from an image capture device; (g) classifying features in the captured image using the trained object classifier; and (h) determining whether the captured image contains a class object based on the trained object classifier associating an identified feature in the image with the class object. 2. The method of claim 1 wherein determining the similarity score comprises the steps of: computing an appearance descriptor for the extracted fragment; computing an appearance descriptor for each image position in each image; comparing the appearance descriptor of the extracted fragment to the appearance descriptor of a respective image position; determining a similarity score in response to the comparison between the appearance descriptors of the extracted fragment and the respective image position. | 0.500986 |
9,814,879 | 1 | 15 | 1. A method comprising: receiving audio input into a hearing prosthesis that is operable to stimulate a physiological system of a recipient in accordance with the received audio input, the received audio input representing an audio environment of the recipient; determining by the hearing prosthesis, based on the received audio input, linguistic characteristics of the audio environment, wherein the linguistic characteristics comprise (i) a measure of quantity of speech by the recipient and (ii) a measure of quantity of speech by one or more people other than the recipient; generating by the hearing prosthesis data representing the determined linguistic characteristics; and outputting the data from the hearing prosthesis. | 1. A method comprising: receiving audio input into a hearing prosthesis that is operable to stimulate a physiological system of a recipient in accordance with the received audio input, the received audio input representing an audio environment of the recipient; determining by the hearing prosthesis, based on the received audio input, linguistic characteristics of the audio environment, wherein the linguistic characteristics comprise (i) a measure of quantity of speech by the recipient and (ii) a measure of quantity of speech by one or more people other than the recipient; generating by the hearing prosthesis data representing the determined linguistic characteristics; and outputting the data from the hearing prosthesis. 15. The method of claim 1 , wherein at times the hearing prosthesis operates in a stimulation-on mode in which the hearing prosthesis is set to stimulate the physiological system of the recipient in accordance with audio input being received by the hearing prosthesis, and at other times the hearing prosthesis operates in a stimulation-off mode in which the hearing prosthesis is set to not stimulate the physiological system of the recipient in accordance with the audio input being received by the hearing prosthesis, the hearing prosthesis basing the determining of the linguistic characteristics on the audio input received while the hearing prosthesis is in the stimulation-on mode but not on the audio input received while the hearing prosthesis is in the stimulation-off mode. | 0.560538 |
9,015,263 | 6 | 14 | 6. A method, comprising: receiving, by at least one server communicatively coupled to a network, a request to identify a plurality of candidate domain names for registration from a requester; identifying, by the at least one server, the plurality of candidate domain names relevant to the request; calculating, by the at least one server, a reputation rating for each one of the plurality of candidate domain names, wherein the reputation rating is calculated based on historical data associated with each one of the plurality of candidate domain names and the historical data is accumulated by at least one of determining a length of time that the each one of the plurality of candidate domain names has been registered; determining an amount of spam, viruses, or phishing email messages that originated from email accounts or websites of the each one of the plurality of candidate domain names; determining a number of complaints about the each one of the plurality of candidate domain names; determining whether website content of the each one of the plurality of candidate domain names relates to illegal content; determining whether the each one of the plurality of candidate domain names has been issued a certified security certificate; and determining whether a registering entity has validated contact information of a registrant of the each one of the plurality of candidate domain names; and displaying, by the at least one server, a user interface depicting the plurality of candidate domain names and an indication of the reputation rating of the each one of the plurality of candidate domain names. | 6. A method, comprising: receiving, by at least one server communicatively coupled to a network, a request to identify a plurality of candidate domain names for registration from a requester; identifying, by the at least one server, the plurality of candidate domain names relevant to the request; calculating, by the at least one server, a reputation rating for each one of the plurality of candidate domain names, wherein the reputation rating is calculated based on historical data associated with each one of the plurality of candidate domain names and the historical data is accumulated by at least one of determining a length of time that the each one of the plurality of candidate domain names has been registered; determining an amount of spam, viruses, or phishing email messages that originated from email accounts or websites of the each one of the plurality of candidate domain names; determining a number of complaints about the each one of the plurality of candidate domain names; determining whether website content of the each one of the plurality of candidate domain names relates to illegal content; determining whether the each one of the plurality of candidate domain names has been issued a certified security certificate; and determining whether a registering entity has validated contact information of a registrant of the each one of the plurality of candidate domain names; and displaying, by the at least one server, a user interface depicting the plurality of candidate domain names and an indication of the reputation rating of the each one of the plurality of candidate domain names. 14. The method of claim 6 , wherein the request for the domain name includes keywords. | 0.835249 |
9,762,549 | 1 | 2 | 1. A method comprising: transmitting a first data stream, the transmitting comprising: parsing unstructured text content within a first message to identify, from the text content, a first set of sensitive data; encrypting the first set of sensitive data using an encryption type identified by a first name and value pair; transmitting the first message in the first data stream with a first set of private tags surrounding the first set of sensitive data, the first set of private tags identifying the first name and value pair; receiving a second data stream, the receiving comprising: parsing the second data stream to identify a second set of private tags surrounding a second set of sensitive data in a second message; and decrypting the second set of sensitive data using a decryption type identified by a second name and value pair identified by the second set of private tags. | 1. A method comprising: transmitting a first data stream, the transmitting comprising: parsing unstructured text content within a first message to identify, from the text content, a first set of sensitive data; encrypting the first set of sensitive data using an encryption type identified by a first name and value pair; transmitting the first message in the first data stream with a first set of private tags surrounding the first set of sensitive data, the first set of private tags identifying the first name and value pair; receiving a second data stream, the receiving comprising: parsing the second data stream to identify a second set of private tags surrounding a second set of sensitive data in a second message; and decrypting the second set of sensitive data using a decryption type identified by a second name and value pair identified by the second set of private tags. 2. The method of claim 1 , further comprising: removing the second set of private tags surrounding the second set of sensitive data in the second message to generate an original second message. | 0.76348 |
7,536,374 | 29 | 32 | 29. A computer usable storage medium comprising program instructions, wherein the program instructions are executable to implement: determining one or more semantic efficiency values of a semantic network, wherein the semantic network includes a plurality of context nodes defining a stored natural language context, and wherein the semantic network is represented by data stored in a memory of a computer system; rearranging a topology of the semantic network to improve at least one of the one or more semantic efficiency values; receiving a voice input at the computer system, wherein the voice input includes a plurality of words; analyzing one or more of the plurality of words of the voice input using the rearranged semantic network; determining a contextual meaning for the voice input using one or more of the analyzed words, wherein the contextual meaning for the voice input is based on the plurality of context nodes in the rearranged semantic network; and in response to determining the contextual meaning for the voice input, causing a device to perform a function corresponding to the determined contextual meaning. | 29. A computer usable storage medium comprising program instructions, wherein the program instructions are executable to implement: determining one or more semantic efficiency values of a semantic network, wherein the semantic network includes a plurality of context nodes defining a stored natural language context, and wherein the semantic network is represented by data stored in a memory of a computer system; rearranging a topology of the semantic network to improve at least one of the one or more semantic efficiency values; receiving a voice input at the computer system, wherein the voice input includes a plurality of words; analyzing one or more of the plurality of words of the voice input using the rearranged semantic network; determining a contextual meaning for the voice input using one or more of the analyzed words, wherein the contextual meaning for the voice input is based on the plurality of context nodes in the rearranged semantic network; and in response to determining the contextual meaning for the voice input, causing a device to perform a function corresponding to the determined contextual meaning. 32. The computer usable storage medium of claim 29 , wherein the received voice input is received at the computer system from the device. | 0.641361 |
9,251,221 | 1 | 22 | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. 22. The method of claim 1 , wherein the numerical contribution is proportional to a number of occurrences of the triggering condition. | 0.896605 |
8,543,380 | 1 | 7 | 1. A method comprising: accessing a record stored in one or more tangible media, the record recording a plurality of clusters of a plurality of documents, a document comprising a plurality of words, a cluster comprising a plurality of satisfactorily affine words of the plurality of words, a cluster indicating a theme; establishing a number of themes of each document of at least a subset of the plurality of documents; determining a specificity of the each document according to the number of themes by: determining that the each document is more specific if the each document has a lower number of themes; and determining that the each document is less specific if the each document has a higher number of themes; receiving a search query comprising a document specificity request, the document specificity indicated using a slider; and retrieving one or more documents of the plurality of documents that satisfy the search query and the document specificity request. | 1. A method comprising: accessing a record stored in one or more tangible media, the record recording a plurality of clusters of a plurality of documents, a document comprising a plurality of words, a cluster comprising a plurality of satisfactorily affine words of the plurality of words, a cluster indicating a theme; establishing a number of themes of each document of at least a subset of the plurality of documents; determining a specificity of the each document according to the number of themes by: determining that the each document is more specific if the each document has a lower number of themes; and determining that the each document is less specific if the each document has a higher number of themes; receiving a search query comprising a document specificity request, the document specificity indicated using a slider; and retrieving one or more documents of the plurality of documents that satisfy the search query and the document specificity request. 7. The method of claim 1 : the plurality of documents associated with one or more users; and the determining the specificity of the each document according to the number of themes further comprising determining a user specificity of the one or more users from the plurality of documents. | 0.723507 |
8,423,370 | 9 | 10 | 9. The method of claim 1 , further comprising classifying, at the data processing device, the language-based content as having a durable importance beyond a temporal scope of a medical encounter. | 9. The method of claim 1 , further comprising classifying, at the data processing device, the language-based content as having a durable importance beyond a temporal scope of a medical encounter. 10. The method of claim 9 , further comprising storing in an electronic health record a representation of the received language-based content classified as having a durable importance. | 0.856474 |
8,959,429 | 1 | 17 | 1. A computer-network system implemented by an online stationery/card service for a user to personalize and send stationery/cards using a client device, the system comprising: a computer server configured to communicate with a client device and enable a user to personalize and send non-electronic stationery/cards using the client device, wherein the computer server is configured to enable a reminder list displayed on the client device, wherein the reminder list comprises a plurality of reminder entries each identifying an upcoming event associated with one or more contacts of the user stored in a contacts database, wherein the reminder list is organized based on a prioritization scheme with a highest priority event selected within the reminder list, wherein the computer server is configured to enable a recommendation region displayed on the client device, wherein the computer server is configured to populate the recommendation region with one or more recommended stationery/card designs for the highest priority event in the reminder list; and a stationery/card personalization engine configured to receive, from the user, a selection of one of the one or more recommended stationery/card designs in the recommendation region using the client device, to provide the user with a set of personalization options related to the selected stationery/card design, and to generate a personalized stationery/card based on the selected stationery/card design and the user's input. | 1. A computer-network system implemented by an online stationery/card service for a user to personalize and send stationery/cards using a client device, the system comprising: a computer server configured to communicate with a client device and enable a user to personalize and send non-electronic stationery/cards using the client device, wherein the computer server is configured to enable a reminder list displayed on the client device, wherein the reminder list comprises a plurality of reminder entries each identifying an upcoming event associated with one or more contacts of the user stored in a contacts database, wherein the reminder list is organized based on a prioritization scheme with a highest priority event selected within the reminder list, wherein the computer server is configured to enable a recommendation region displayed on the client device, wherein the computer server is configured to populate the recommendation region with one or more recommended stationery/card designs for the highest priority event in the reminder list; and a stationery/card personalization engine configured to receive, from the user, a selection of one of the one or more recommended stationery/card designs in the recommendation region using the client device, to provide the user with a set of personalization options related to the selected stationery/card design, and to generate a personalized stationery/card based on the selected stationery/card design and the user's input. 17. The computer-network system as in claim 1 , wherein the computer server is configured to enable a schedule calendar displayed on the client device to allow the user to select a delivery date for the personalized stationery/card. | 0.820155 |
10,002,128 | 1 | 9 | 1. A computerized system for transforming an input text string, the input text string being an ordered set of characters, the system comprising: a dictionary data store configured to store a plurality of tokens, wherein each token is associated with a score, and wherein each token is a string of one or more characters; a chart parser configured to generate a chart parse of the input text string, wherein: the chart parse includes a plurality of entries, each entry includes (i) an indication of a start character of the entry within the input text string and (ii) an indication of an end character of the entry within the input text string, and the chart parser is configured to, for each position within the input text string, (i) identify a string of at least one consecutive character in the input text string that begins at that position and matches one of the plurality of tokens and (ii) unless the identified string is a single character matching the start character for another entry in the chart parse, create an entry corresponding to the identified string; a partition selection module configured to determine a selected partition of the input text string based on the entries of the chart parse, wherein: the selected partition includes an array of tokens such that a concatenation of the array of tokens matches the ordered set of characters of the input text string, each of the array of tokens is selected from the chart parse, a score of the selected partition is based on a sum of, for each token of the array of tokens, the score specified by the dictionary data store, and the selected partition is a minimum score partition; a data store storing application state records; a set generation module configured to, in response to a set of tokens, select records from the data store to form a consideration set of records; and a results generation module configured to respond to the user device with a subset of the consideration set of records, wherein the subset identifies application states of applications that are relevant to a search query from the user device, wherein the input text string is based on the search query from the user device. | 1. A computerized system for transforming an input text string, the input text string being an ordered set of characters, the system comprising: a dictionary data store configured to store a plurality of tokens, wherein each token is associated with a score, and wherein each token is a string of one or more characters; a chart parser configured to generate a chart parse of the input text string, wherein: the chart parse includes a plurality of entries, each entry includes (i) an indication of a start character of the entry within the input text string and (ii) an indication of an end character of the entry within the input text string, and the chart parser is configured to, for each position within the input text string, (i) identify a string of at least one consecutive character in the input text string that begins at that position and matches one of the plurality of tokens and (ii) unless the identified string is a single character matching the start character for another entry in the chart parse, create an entry corresponding to the identified string; a partition selection module configured to determine a selected partition of the input text string based on the entries of the chart parse, wherein: the selected partition includes an array of tokens such that a concatenation of the array of tokens matches the ordered set of characters of the input text string, each of the array of tokens is selected from the chart parse, a score of the selected partition is based on a sum of, for each token of the array of tokens, the score specified by the dictionary data store, and the selected partition is a minimum score partition; a data store storing application state records; a set generation module configured to, in response to a set of tokens, select records from the data store to form a consideration set of records; and a results generation module configured to respond to the user device with a subset of the consideration set of records, wherein the subset identifies application states of applications that are relevant to a search query from the user device, wherein the input text string is based on the search query from the user device. 9. The system of claim 1 wherein the score of the selected partition is equal to the sum of, for each token of the array of tokens, the score specified by the dictionary data store. | 0.825962 |
8,694,490 | 1 | 2 | 1. A method of representing data comprising: in a processing system, collecting pieces of communication data from a plurality of sources; normalizing the pieces of communication data from the plurality of sources such that each piece of communication data includes multiple common fields; identifying one or more communication threads of the communication data, wherein each communication thread includes two or more pieces of the communication data that are related, regardless of the source, by having similar information in one or more of the common fields; and displaying a representation of multiple pieces of the communication data as a three dimensional collection of cubes, where each cube represents a subset of the multiple pieces of communication data, and wherein a first axis for each cube represents communication threads, a second axis represents a first common field of the common fields and a third axis represents a second common field of the common fields, wherein a portal view is a three dimensional representation of a selected subset, wherein a first portal view axis represents communication threads and a second portal view axis represents time, and wherein the portal view displays communication data in a higher resolution than the three dimensional collection of cubes such that communication data is visible, wherein the cubes are color-coded according to the communication threads. | 1. A method of representing data comprising: in a processing system, collecting pieces of communication data from a plurality of sources; normalizing the pieces of communication data from the plurality of sources such that each piece of communication data includes multiple common fields; identifying one or more communication threads of the communication data, wherein each communication thread includes two or more pieces of the communication data that are related, regardless of the source, by having similar information in one or more of the common fields; and displaying a representation of multiple pieces of the communication data as a three dimensional collection of cubes, where each cube represents a subset of the multiple pieces of communication data, and wherein a first axis for each cube represents communication threads, a second axis represents a first common field of the common fields and a third axis represents a second common field of the common fields, wherein a portal view is a three dimensional representation of a selected subset, wherein a first portal view axis represents communication threads and a second portal view axis represents time, and wherein the portal view displays communication data in a higher resolution than the three dimensional collection of cubes such that communication data is visible, wherein the cubes are color-coded according to the communication threads. 2. The method of claim 1 wherein the two or more pieces of communication data in each of the communication threads are related by being associated with two or more common participants. | 0.710692 |
8,010,364 | 8 | 13 | 8. A system for troubleshooting based on a probability distribution model, the system comprising: a processor; a first module configured to control the processor to establish a speech-based conversation with the user; a second module configured to control the processor to establish at least one non-speech-based channel of interaction for obtaining behavioral information associated with the product during the speech-based conversation; a third module configured to control the processor to maintain a probability distribution over time for each of a plurality of component variables describing a state of the product based on a state of a conversation over time and a state of the behavioral information over time; and a fourth module configured to control the processor to troubleshoot the product by responding based on the probability distribution. | 8. A system for troubleshooting based on a probability distribution model, the system comprising: a processor; a first module configured to control the processor to establish a speech-based conversation with the user; a second module configured to control the processor to establish at least one non-speech-based channel of interaction for obtaining behavioral information associated with the product during the speech-based conversation; a third module configured to control the processor to maintain a probability distribution over time for each of a plurality of component variables describing a state of the product based on a state of a conversation over time and a state of the behavioral information over time; and a fourth module configured to control the processor to troubleshoot the product by responding based on the probability distribution. 13. The system of claim 8 , wherein partially observable Markov decision processes (POMDPs) are used to select troubleshooting responses. | 0.76936 |
8,274,520 | 28 | 29 | 28. The computer-readable storage medium of claim 25 , wherein the resources are identifiers for images, wherein the identifiers include: addresses of a location in a memory or on a disk where the images are stored; MD5 tags, a size value, and/or an age value. | 28. The computer-readable storage medium of claim 25 , wherein the resources are identifiers for images, wherein the identifiers include: addresses of a location in a memory or on a disk where the images are stored; MD5 tags, a size value, and/or an age value. 29. The computer-readable storage medium of claim 28 , wherein receiving the resource query or the filtering query involves receiving a request for a list of addresses of images, wherein the images have at least one property in common, and wherein the property in common can be determined by comparing one or more MD 5 tags. | 0.866447 |
10,007,720 | 1 | 11 | 1. A method comprising: receiving, over a network by a networked system, a communication that is a part of a conversation involving one or more users, the networked system being a participant in the conversation; analyzing, by one or more hardware processors of the networked system, the communication, the analyzing including parsing key terms from the communication; identifying, by the networked system, a sentiment of a user among the one or more users based on the parsed key terms, the identified sentiment of the user identifying a level of commitment readiness among at least two sequentially increasing levels of commitment readiness, the at least two sequentially increasing levels including a penultimate level that indicates readiness to consider multiple options and including an ultimate level that indicates readiness to commit to one option among the multiple options; based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness, determining whether the networked system is to respond to the communication; and in response to a determination to respond, generating, by the networked system, a customized response based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness and transmitting the customized response, over the network, to a device of the user. | 1. A method comprising: receiving, over a network by a networked system, a communication that is a part of a conversation involving one or more users, the networked system being a participant in the conversation; analyzing, by one or more hardware processors of the networked system, the communication, the analyzing including parsing key terms from the communication; identifying, by the networked system, a sentiment of a user among the one or more users based on the parsed key terms, the identified sentiment of the user identifying a level of commitment readiness among at least two sequentially increasing levels of commitment readiness, the at least two sequentially increasing levels including a penultimate level that indicates readiness to consider multiple options and including an ultimate level that indicates readiness to commit to one option among the multiple options; based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness, determining whether the networked system is to respond to the communication; and in response to a determination to respond, generating, by the networked system, a customized response based on the identified level of commitment readiness among the at least two sequentially increasing levels of commitment readiness and transmitting the customized response, over the network, to a device of the user. 11. The method of claim 1 , further comprising training a machine, using a plurality of samples, to identify a question or location in the communication. | 0.789835 |
8,739,019 | 27 | 28 | 27. A computer program product for presenting an electronic document, wherein said electronic document is defined as at least one of a news story, an informational article, and an electronic book, wherein a choosing by a user of select text within said electronic document is synchronized through a scrolling-oriented multimedia control with a related media content presentation, including at least one visual image configured primarily to illustrate at least part of a primary body of text in said electronic document, wherein said scrolling-oriented multimedia control automatically commences displaying each successive presentation of visual imagery no later than effectively simultaneous to a reading of each associated text segment by said user, and wherein a rate of speed reviewing select text by said user modifies the presentation of said at least one visual image, said computer program product comprising: a computer processor having a computer output device; a non-transitory computer-useable storage medium having a computer-readable program embedded therein, said computer-readable program being executable by said computer processor, said computer-readable program including at least part of said scrolling-oriented multimedia control; said computer program arranged to cause said computer processor to store on said non-transitory computer-useable storage medium and display on said computer output device a current presentation of said electronic document, wherein said current presentation includes at least part of said primary body of text and at least one associated visual image; said computer program then arranged to cause said computer processor to detect an activating of said scrolling-oriented multimedia control to select a next segment of text within said primary body of text; said computer program then arranged to cause said computer processor to retrieve from said non-transitory computer-useable storage medium and display on said computer output device a next presentation of said electronic document, wherein said next presentation includes displaying one or more changed components of related media content, wherein at least one of the changed components includes a continued, modified presentation of said at least one associated visual image, with said continued, modified presentation configured primarily to help illustrate said next segment of text chosen within said primary body of text, wherein said at least one associated visual image is at least one of a video and a digital photograph, wherein said at least one associated visual image is modified based on said rate of speed reviewing said next segment of text by said user, and wherein alteration of said at least one associated visual image includes at least one of a zooming-in on at least one depicted subject, a zooming-out on at least one depicted subject, and a panning across at least one depicted subject; said computer program then arranged to cause said computer processor to detect a new activating of said scrolling-oriented multimedia control to select a new next segment of text within said primary body of text; said computer program then arranged to cause said computer processor to retrieve from said non-transitory computer-useable storage medium and display on said computer output device a new next presentation of said electronic document, wherein said new next presentation includes displaying one or more changed components of related media content to help illustrate said new next segment of text chosen within said primary body of text. | 27. A computer program product for presenting an electronic document, wherein said electronic document is defined as at least one of a news story, an informational article, and an electronic book, wherein a choosing by a user of select text within said electronic document is synchronized through a scrolling-oriented multimedia control with a related media content presentation, including at least one visual image configured primarily to illustrate at least part of a primary body of text in said electronic document, wherein said scrolling-oriented multimedia control automatically commences displaying each successive presentation of visual imagery no later than effectively simultaneous to a reading of each associated text segment by said user, and wherein a rate of speed reviewing select text by said user modifies the presentation of said at least one visual image, said computer program product comprising: a computer processor having a computer output device; a non-transitory computer-useable storage medium having a computer-readable program embedded therein, said computer-readable program being executable by said computer processor, said computer-readable program including at least part of said scrolling-oriented multimedia control; said computer program arranged to cause said computer processor to store on said non-transitory computer-useable storage medium and display on said computer output device a current presentation of said electronic document, wherein said current presentation includes at least part of said primary body of text and at least one associated visual image; said computer program then arranged to cause said computer processor to detect an activating of said scrolling-oriented multimedia control to select a next segment of text within said primary body of text; said computer program then arranged to cause said computer processor to retrieve from said non-transitory computer-useable storage medium and display on said computer output device a next presentation of said electronic document, wherein said next presentation includes displaying one or more changed components of related media content, wherein at least one of the changed components includes a continued, modified presentation of said at least one associated visual image, with said continued, modified presentation configured primarily to help illustrate said next segment of text chosen within said primary body of text, wherein said at least one associated visual image is at least one of a video and a digital photograph, wherein said at least one associated visual image is modified based on said rate of speed reviewing said next segment of text by said user, and wherein alteration of said at least one associated visual image includes at least one of a zooming-in on at least one depicted subject, a zooming-out on at least one depicted subject, and a panning across at least one depicted subject; said computer program then arranged to cause said computer processor to detect a new activating of said scrolling-oriented multimedia control to select a new next segment of text within said primary body of text; said computer program then arranged to cause said computer processor to retrieve from said non-transitory computer-useable storage medium and display on said computer output device a new next presentation of said electronic document, wherein said new next presentation includes displaying one or more changed components of related media content to help illustrate said new next segment of text chosen within said primary body of text. 28. The computer program product of claim 27 , wherein at least one of a speed and an extent of at least one of said zooming-in on at least one depicted subject and said zooming-out on at least one depicted subject changes based on the rate of speed by said user to read at least one associated text segment. | 0.824401 |
7,962,507 | 12 | 13 | 12. The method as recited in claim 10 wherein the filtering the snippet set comprises dividing up text in at least one snippet of the snippet set into sentences based on punctuation. | 12. The method as recited in claim 10 wherein the filtering the snippet set comprises dividing up text in at least one snippet of the snippet set into sentences based on punctuation. 13. The method as recited in claim 12 wherein the sentences are grouped in pairs to form sentence pairs. | 0.950096 |
10,089,553 | 5 | 6 | 5. A device for automatically extracting a validity period of a driving license, the device comprising a storage device and a processor, wherein the storage device is configured for storing a system for automatically extracting a validity period of a driving license; the processor is configured for executing the system to perform the following operations: receiving an image file of a vehicle driving license; extracting candidate contour regions from within the image file according to a contour extraction rule, and selecting from among the extracted candidate contour regions at least one candidate contour region containing an annual inspection validity period; extracting all character contours from within each selected candidate contour region; acquiring a smallest circumscribed rectangle of each character contour in the selected candidate contour region, and dividing image blocks bound by the acquired smallest circumscribed rectangles one by one into individual single-character blocks; sorting these single-character blocks according to their respective positions in the selected candidate contour region; recognizing a corresponding character of each single-character block; generating a character string representing the annual inspection validity period using the recognized characters based on the sorting; and extracting time data in the character string and taking the time data as the annual inspection validity period of the selected candidate contour region. | 5. A device for automatically extracting a validity period of a driving license, the device comprising a storage device and a processor, wherein the storage device is configured for storing a system for automatically extracting a validity period of a driving license; the processor is configured for executing the system to perform the following operations: receiving an image file of a vehicle driving license; extracting candidate contour regions from within the image file according to a contour extraction rule, and selecting from among the extracted candidate contour regions at least one candidate contour region containing an annual inspection validity period; extracting all character contours from within each selected candidate contour region; acquiring a smallest circumscribed rectangle of each character contour in the selected candidate contour region, and dividing image blocks bound by the acquired smallest circumscribed rectangles one by one into individual single-character blocks; sorting these single-character blocks according to their respective positions in the selected candidate contour region; recognizing a corresponding character of each single-character block; generating a character string representing the annual inspection validity period using the recognized characters based on the sorting; and extracting time data in the character string and taking the time data as the annual inspection validity period of the selected candidate contour region. 6. The device of claim 5 , wherein the contour extraction rule comprises: extracting contour regions containing various types of information from within the image file using maximum stable extremal region (MSER) scheme; and extracting, from among the extracted contour regions, the contour regions each having an aspect ratio lying within a predetermined range, as the candidate contour regions. | 0.758557 |
6,122,593 | 9 | 10 | 9. The invention of claim 8 wherein said indication is a reference to one of said data entities of said second type. | 9. The invention of claim 8 wherein said indication is a reference to one of said data entities of said second type. 10. The invention of claim 9 wherein the data record of said second type to which said reference in said data entity of said first type refers contains that name by which the road segment represented by the data entity of said first type is referred to by a road sign located along the road of which the represented road segment is a part. | 0.864508 |
10,074,108 | 22 | 25 | 22. The method of claim 19 , wherein the communication session is established between the sandboxed application and the sandbox reachable service in accordance with the client device: extending the security sandbox with a discovery algorithm and a relay algorithm through a discovery module and a relay module added to the security sandbox; and bypassing the pairing server having the discovery algorithm and the relay algorithm when establishing the communication session between the sandboxed application and the sandbox reachable service when the security sandbox is extended with the discovery algorithm and the relay algorithm through the discovery module and the relay module added to the security sandbox. | 22. The method of claim 19 , wherein the communication session is established between the sandboxed application and the sandbox reachable service in accordance with the client device: extending the security sandbox with a discovery algorithm and a relay algorithm through a discovery module and a relay module added to the security sandbox; and bypassing the pairing server having the discovery algorithm and the relay algorithm when establishing the communication session between the sandboxed application and the sandbox reachable service when the security sandbox is extended with the discovery algorithm and the relay algorithm through the discovery module and the relay module added to the security sandbox. 25. The method of claim 22 , wherein the communication session is established between the sandboxed application and the sandbox reachable service in accordance with the client device: applying the discovery algorithm of the security sandbox to determine that the networked device having the sandbox reachable service communicates in a shared network common to the client device and the networked device; and applying the relay algorithm of the security sandbox to establish the communication session between the sandboxed application and the sandbox reachable service of the networked device. | 0.923097 |
7,809,708 | 1 | 7 | 1. A method for searching a corpus of documents, comprising: defining a knowledge domain; identifying a set of reference documents in the corpus pertinent to the domain; inputting a first query; searching the corpus using the set of reference documents to find one or more of the documents in the corpus that contain information in the domain relevant to the first query; and adding at least one of the found documents to the set of reference documents for use in searching the corpus for information in the domain relevant to a second, subsequent query, which is substantially different from the first query, wherein searching the corpus comprises searching the corpus to find the documents that contain the information relevant to the query and ranking the found documents by comparing them to the set of reference documents, and wherein ranking the found documents comprises assessing links between the found documents and the reference documents. | 1. A method for searching a corpus of documents, comprising: defining a knowledge domain; identifying a set of reference documents in the corpus pertinent to the domain; inputting a first query; searching the corpus using the set of reference documents to find one or more of the documents in the corpus that contain information in the domain relevant to the first query; and adding at least one of the found documents to the set of reference documents for use in searching the corpus for information in the domain relevant to a second, subsequent query, which is substantially different from the first query, wherein searching the corpus comprises searching the corpus to find the documents that contain the information relevant to the query and ranking the found documents by comparing them to the set of reference documents, and wherein ranking the found documents comprises assessing links between the found documents and the reference documents. 7. The method according to claim 1 , wherein adding the at least one of the found documents comprises removing one of the documents from the set responsive to adding the at least one of the found documents. | 0.723861 |
7,689,703 | 1 | 16 | 1. A network data transfer system comprising a memory having stored therein computer executable components and a processor that executes the computer executable components, wherein the computer executable components include: an Extensible Markup Language for Analysis (XMLA) protocol component that employs a computerized mark-up language to facilitate data interactions between network components, wherein the data interactions are based on, at least in part; (1) of an execute method having a statement command, (2) a discover method having at least one discover, and (3) at least one property of the mark-up language; and an XMLA extension component that operates with the protocol component to support the data interactions, wherein the extension component: (1) extends the statement method by utilizing the statement command to supply at least one other command to facilitate the data interactions, and wherein the at least one other command comprises at least one of a create command, an alter command, or a delete command; (2) extends the discover method by supplying at least one other discover type for discovering the state of objects on a server; (3) supplies at least one other property to further extend server object management capabilities; (4) supplies a parameter specification component that enables the statement command to be parameterized, and that enables one or more parameters to be sent with the at least one other command; and (5) supplies a binary markup-language extension for communications that facilitates communications between client and server components using a binary representation of the markup-language and that includes an interface enabling use of internal server identifiers of mark-up language elements directly in the binary representation. | 1. A network data transfer system comprising a memory having stored therein computer executable components and a processor that executes the computer executable components, wherein the computer executable components include: an Extensible Markup Language for Analysis (XMLA) protocol component that employs a computerized mark-up language to facilitate data interactions between network components, wherein the data interactions are based on, at least in part; (1) of an execute method having a statement command, (2) a discover method having at least one discover, and (3) at least one property of the mark-up language; and an XMLA extension component that operates with the protocol component to support the data interactions, wherein the extension component: (1) extends the statement method by utilizing the statement command to supply at least one other command to facilitate the data interactions, and wherein the at least one other command comprises at least one of a create command, an alter command, or a delete command; (2) extends the discover method by supplying at least one other discover type for discovering the state of objects on a server; (3) supplies at least one other property to further extend server object management capabilities; (4) supplies a parameter specification component that enables the statement command to be parameterized, and that enables one or more parameters to be sent with the at least one other command; and (5) supplies a binary markup-language extension for communications that facilitates communications between client and server components using a binary representation of the markup-language and that includes an interface enabling use of internal server identifiers of mark-up language elements directly in the binary representation. 16. The system of claim 1 , wherein the mark-up language comprises XMLA and Wireless Markup Language (WML). | 0.887368 |
8,560,466 | 8 | 10 | 8. A method for handling a received document, said received document having been transmitted electronically and involving an encoding scheme, the method comprising: ascertaining, using identification rules, whether a charset employed to encode said target document belongs to an excluded charset group, said excluded charset group having at least two charsets, each charset in said excluded charset group selected based on charset inherent characteristics; if said charset employed to encode said target document does not belong to said excluded charset group, performing processing of said received document by performing the steps below; receiving a plurality of text document samples, said plurality of text document samples being encoded with different encoding schemes and selected for training purposes, said different encoding schemes pertaining to charset encoding; training, using said plurality of text document samples, to obtain a set of machine learning models, said training including generating fundamental units from said plurality of text document samples for charsets of said plurality of text document samples, extracting a subset of said fundamental units as feature lists, said extracting said subset of said fundamental units including filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences between said different encoding schemes, converting said feature lists into a set of feature vectors, said feature vectors are grouped by charsets, and generating said set of machine learning models from said set of feature vectors using a SVM (Support Vector Machine) technique; applying said set of machine learning models against a set of target document feature vectors converted from said received document, said applying including analyzing said set of received document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of received document feature vectors; and decoding said received document to obtain decoded content of said received document based on at least said first encoding scheme. | 8. A method for handling a received document, said received document having been transmitted electronically and involving an encoding scheme, the method comprising: ascertaining, using identification rules, whether a charset employed to encode said target document belongs to an excluded charset group, said excluded charset group having at least two charsets, each charset in said excluded charset group selected based on charset inherent characteristics; if said charset employed to encode said target document does not belong to said excluded charset group, performing processing of said received document by performing the steps below; receiving a plurality of text document samples, said plurality of text document samples being encoded with different encoding schemes and selected for training purposes, said different encoding schemes pertaining to charset encoding; training, using said plurality of text document samples, to obtain a set of machine learning models, said training including generating fundamental units from said plurality of text document samples for charsets of said plurality of text document samples, extracting a subset of said fundamental units as feature lists, said extracting said subset of said fundamental units including filtering said fundamental units to obtain fundamental units that are more discriminatory in describing differences between said different encoding schemes, converting said feature lists into a set of feature vectors, said feature vectors are grouped by charsets, and generating said set of machine learning models from said set of feature vectors using a SVM (Support Vector Machine) technique; applying said set of machine learning models against a set of target document feature vectors converted from said received document, said applying including analyzing said set of received document feature vectors using said set of machine learning models to compute similarity indicia between said set of target document feature vectors and said set of machine learning models associated with said different encoding schemes, wherein a first encoding scheme associated with said set of machine learning models is designated as said encoding scheme if characteristics of said first encoding scheme as represented by said set of machine learning models are computed to be most similar, relative to other encoding schemes of said different encoding schemes, to said set of received document feature vectors; and decoding said received document to obtain decoded content of said received document based on at least said first encoding scheme. 10. the method of claim 8 wherein said set of feature vectors are converted using a statistical representation technique. | 0.891964 |
9,037,654 | 1 | 2 | 1. A method for transmitting a sharing document containing only text and pictures over a network, comprising the steps of: converting, by a virtual printer module in a first client device, GDI (Graph Device Interface) functions corresponding to a sharing document to be transmitted into GDI instructions, forming a GDI document by synthesizing the GDI instructions, and sending the GDI document to a document sender in the first client device; receiving, by a document receiver in a second client device, the GDI document sent from the document sender through a network; and restoring, by the document receiver, the received GDI document, and contents of the restored GDI document being the same as that of the sharing document; the method for said converting the GDI functions corresponding to the sharing document into GDI instruction, wherein forming the GDI document by synthesizing the GDI instructions comprises the steps of: opening, by an application of the sharing document on the document sender, the interface for interacting with the virtual printer module and starting to perform virtual printing of the sharing document; determining, by the application of the sharing document, whether the virtual printing should be terminated, if the virtual printing should be terminated, terminating the virtual printing of the sharing document by sending a GDI function indicating the end of the sharing document to the virtual printer module and terminating current procedure for generating the GDI document; if the virtual printing should not be terminated, sending, by the application of the sharing document, based on the contents of the sharing document and by calling print driver GDI transfer interface function, a GDI function to the virtual printer module, and converting, by the virtual printer module, the received GDI function into a GDI instruction and returning the result of the conversion to the application of the sharing document; and determining, by the application of the sharing document, based on the result of the conversion returned by the virtual printer module, whether the conversion is successful, and if the conversion is successful, starting, by the application of the sharing document, to deal with the next GDI function and cycling back to the step of determining whether the virtual print should be terminated; if the conversion is unsuccessful, terminating, by the application of the sharing document, the virtual printing of the sharing document by sending a GDI function indicating the end of the sharing document to the virtual printer module and terminating the procedure for generating the GDI document; the GDI instruction comprises at least: the name of GDI function, number of GDI function and serial number of GDI performance; the method for converting, by the virtual printer module, the received GDI function into the GDI instruction and retuning the result of the conversion to the application of the sharing document, comprising the steps of: calling, by the application of sharing document, the print driver GDI transfer interface function, determining, by the virtual printer module, whether the received GDI function is a GDI function indicating start of virtual printing of the sharing document, if the received GDI function is a GDI function indicating start of virtual printing of the sharing document, acquiring, by the virtual printed module, a corresponding table of names and numbers of GDI functions from a GDI subsystem, initializing the variable of the serial number of GDI performance to 0, establishing and opening an empty GDI document, and generating an initialization variable indicating the completion situation of the initialization; if the received GDI function is nota GDI function indicating start of virtual printing of the sharing document, determining, based on the initialization variable, whether the initialization has been completed, and if the initialization has been completed, determining whether the received GDI function is a GDI function indicating end of the virtual printing of the sharing document, if the received GDI function is a GDI function indicating end of the virtual printing of the sharing document, closing the GDI document, and returning, by the virtual printer module, the result of the conversion to the application of the sharing document; if the received GDI function is not a GDI function indicating end of the virtual print of the sharing document, determining whether the number of GDI function corresponding to the current GDI function is found, and if the number of GDI function corresponding to the current GDI function is found, adding 1 to the variable of the serial number of GDI performance, encoding the name of GDI function, the variable of the serial number of GDI performance and the GDI function based on the format of GDI instruction stream so as to generate GDI instruction, and writing the GDI instruction into the GDI document; and if the number of GDI function corresponding to the current GDI function is not found, returning, by the virtual printer module, the result of the conversion to the application of the sharing document; and if initialization has not been completed, cycling back to the step of acquiring, by the virtual printer module, a corresponding table of names and numbers of GDI functions from a GDI subsystem, initializing the variable of the serial number of GDI performance to 0, establishing and opening an empty GDI document, and generating an initialization variable indicating the completion situation of the initialization. | 1. A method for transmitting a sharing document containing only text and pictures over a network, comprising the steps of: converting, by a virtual printer module in a first client device, GDI (Graph Device Interface) functions corresponding to a sharing document to be transmitted into GDI instructions, forming a GDI document by synthesizing the GDI instructions, and sending the GDI document to a document sender in the first client device; receiving, by a document receiver in a second client device, the GDI document sent from the document sender through a network; and restoring, by the document receiver, the received GDI document, and contents of the restored GDI document being the same as that of the sharing document; the method for said converting the GDI functions corresponding to the sharing document into GDI instruction, wherein forming the GDI document by synthesizing the GDI instructions comprises the steps of: opening, by an application of the sharing document on the document sender, the interface for interacting with the virtual printer module and starting to perform virtual printing of the sharing document; determining, by the application of the sharing document, whether the virtual printing should be terminated, if the virtual printing should be terminated, terminating the virtual printing of the sharing document by sending a GDI function indicating the end of the sharing document to the virtual printer module and terminating current procedure for generating the GDI document; if the virtual printing should not be terminated, sending, by the application of the sharing document, based on the contents of the sharing document and by calling print driver GDI transfer interface function, a GDI function to the virtual printer module, and converting, by the virtual printer module, the received GDI function into a GDI instruction and returning the result of the conversion to the application of the sharing document; and determining, by the application of the sharing document, based on the result of the conversion returned by the virtual printer module, whether the conversion is successful, and if the conversion is successful, starting, by the application of the sharing document, to deal with the next GDI function and cycling back to the step of determining whether the virtual print should be terminated; if the conversion is unsuccessful, terminating, by the application of the sharing document, the virtual printing of the sharing document by sending a GDI function indicating the end of the sharing document to the virtual printer module and terminating the procedure for generating the GDI document; the GDI instruction comprises at least: the name of GDI function, number of GDI function and serial number of GDI performance; the method for converting, by the virtual printer module, the received GDI function into the GDI instruction and retuning the result of the conversion to the application of the sharing document, comprising the steps of: calling, by the application of sharing document, the print driver GDI transfer interface function, determining, by the virtual printer module, whether the received GDI function is a GDI function indicating start of virtual printing of the sharing document, if the received GDI function is a GDI function indicating start of virtual printing of the sharing document, acquiring, by the virtual printed module, a corresponding table of names and numbers of GDI functions from a GDI subsystem, initializing the variable of the serial number of GDI performance to 0, establishing and opening an empty GDI document, and generating an initialization variable indicating the completion situation of the initialization; if the received GDI function is nota GDI function indicating start of virtual printing of the sharing document, determining, based on the initialization variable, whether the initialization has been completed, and if the initialization has been completed, determining whether the received GDI function is a GDI function indicating end of the virtual printing of the sharing document, if the received GDI function is a GDI function indicating end of the virtual printing of the sharing document, closing the GDI document, and returning, by the virtual printer module, the result of the conversion to the application of the sharing document; if the received GDI function is not a GDI function indicating end of the virtual print of the sharing document, determining whether the number of GDI function corresponding to the current GDI function is found, and if the number of GDI function corresponding to the current GDI function is found, adding 1 to the variable of the serial number of GDI performance, encoding the name of GDI function, the variable of the serial number of GDI performance and the GDI function based on the format of GDI instruction stream so as to generate GDI instruction, and writing the GDI instruction into the GDI document; and if the number of GDI function corresponding to the current GDI function is not found, returning, by the virtual printer module, the result of the conversion to the application of the sharing document; and if initialization has not been completed, cycling back to the step of acquiring, by the virtual printer module, a corresponding table of names and numbers of GDI functions from a GDI subsystem, initializing the variable of the serial number of GDI performance to 0, establishing and opening an empty GDI document, and generating an initialization variable indicating the completion situation of the initialization. 2. The method of claim 1 , further comprising the steps of: compressing, by the document sender, the GDI document; and decompressing, by the document receiver, the received GDI document. | 0.832734 |
7,668,407 | 10 | 12 | 10. An article comprising a machine-readable medium storing instructions adapted to cause one or more machines to perform operations comprising: receiving a plurality of proposed character assignments for at least one instance of a character in an image on which optical character recognition is being performed, each of the character assignments representing a character determined from a character set for the at least one instance of the character by the optical character recognition, the at least one instance of the character residing in one or more character strings of multiple characters, at least one of the character strings of multiple characters known to exclude a subset of at least one character from the character set based at least in part on the at least one character string of multiple characters' location in the image; and eliminating at least one of the proposed character assignments by comparing the at least one of the proposed character assignments to the subset of at least one character excluded from the at least one character string of multiple characters. | 10. An article comprising a machine-readable medium storing instructions adapted to cause one or more machines to perform operations comprising: receiving a plurality of proposed character assignments for at least one instance of a character in an image on which optical character recognition is being performed, each of the character assignments representing a character determined from a character set for the at least one instance of the character by the optical character recognition, the at least one instance of the character residing in one or more character strings of multiple characters, at least one of the character strings of multiple characters known to exclude a subset of at least one character from the character set based at least in part on the at least one character string of multiple characters' location in the image; and eliminating at least one of the proposed character assignments by comparing the at least one of the proposed character assignments to the subset of at least one character excluded from the at least one character string of multiple characters. 12. The article of claim 10 wherein the instructions are further adapted to cause one or more machines to perform operations comprising: determining the subset of at least one character excluded by a character string of multiple characters at least in part from information conveyed by the character string of multiple characters. | 0.843305 |
9,542,820 | 13 | 23 | 13. A non-transitory computer readable storage medium storing executable code, the code when executed causes a processor at a computing device with a tactile output generator to perform the following steps: detecting an occurrence of a first event; and in response to detecting the occurrence of the first event: in accordance with a determination that the first event is a first type of event of a plurality of types of events that are affected by the alert-salience setting, providing a first alert with the tactile output generator that includes a first haptic output selected based at least in part on an alert-salience setting of the device; and in accordance with a determination that the first event is a second type of event of a plurality of types of events that are not affected by the alert-salience setting, providing a second alert with the tactile output generator that includes a second haptic output selected without regard to the alert-salience setting of the device. | 13. A non-transitory computer readable storage medium storing executable code, the code when executed causes a processor at a computing device with a tactile output generator to perform the following steps: detecting an occurrence of a first event; and in response to detecting the occurrence of the first event: in accordance with a determination that the first event is a first type of event of a plurality of types of events that are affected by the alert-salience setting, providing a first alert with the tactile output generator that includes a first haptic output selected based at least in part on an alert-salience setting of the device; and in accordance with a determination that the first event is a second type of event of a plurality of types of events that are not affected by the alert-salience setting, providing a second alert with the tactile output generator that includes a second haptic output selected without regard to the alert-salience setting of the device. 23. The non-transitory computer readable storage medium of claim 13 , wherein when the alert-salience setting has a first value, a plurality of different events in the first type of events are augmented in the same respective manner and when the alert-salience setting has a second value that is different from the first value, a plurality of different events in the first type of events are not augmented in the respective manner. | 0.803555 |
8,077,984 | 19 | 20 | 19. The method of claim 1 , wherein the second sequence comprises a set of second sequences and the method comprises, for each of the second sequences, computing of the similarity measure between the first sequence of symbols and the second sequence of symbols as a function of the occurrences of optionally noncontiguous subsequences of symbols shared by the two sequences of symbols, the method further comprising evaluating a fluency of the first text span in a natural language shared by the text sequences based on the computed similarity measures. | 19. The method of claim 1 , wherein the second sequence comprises a set of second sequences and the method comprises, for each of the second sequences, computing of the similarity measure between the first sequence of symbols and the second sequence of symbols as a function of the occurrences of optionally noncontiguous subsequences of symbols shared by the two sequences of symbols, the method further comprising evaluating a fluency of the first text span in a natural language shared by the text sequences based on the computed similarity measures. 20. The method of claim 19 , wherein the set of second sequences comprises a set of good sequences determined to have good fluency and a set of bad sequences determined to have a poor fluency. | 0.897106 |
8,004,495 | 3 | 5 | 3. The method of claim 2 wherein the multiple-axis input device is rotatable to provide input, and further comprising detecting as the input from the multiple-axis input device a rotation of the multiple-axis input device a rotational distance equal to a number of times a predetermined rotational distance. | 3. The method of claim 2 wherein the multiple-axis input device is rotatable to provide input, and further comprising detecting as the input from the multiple-axis input device a rotation of the multiple-axis input device a rotational distance equal to a number of times a predetermined rotational distance. 5. The method of claim 3 , further comprising detecting as the rotation of the multiple-axis input device an initial rotation of the multiple-axis input device in a first rotational direction a rotational distance equal to a first number of times the predetermined rotational distance and a subsequent rotation of the multiple-axis input device in a second rotational direction a rotational distance equal to a second number of times the predetermined rotational distance, each successive disambiguated interpretation being the next sequentially disposed disambiguated interpretation in the direction of rotation of the multiple-axis input device. | 0.813759 |
10,095,488 | 11 | 12 | 11. The non-transitory computer-readable medium of claim 9 , wherein the model can be further enriched with attributes that describe the specified business entities in greater detail. | 11. The non-transitory computer-readable medium of claim 9 , wherein the model can be further enriched with attributes that describe the specified business entities in greater detail. 12. The non-transitory computer-readable medium of claim 11 , wherein the attributes are manually entered by the user via the integrated graphical modeler. | 0.95614 |
9,152,714 | 11 | 20 | 11. A system comprising: a processor; and a non-transitory computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: obtaining search query data, the search query data including a plurality of search queries submitted by users, each search query being associated with one or more responsive search results and user selection data for the one or more search results, wherein the user selection data identifies which search results were selected by users; obtaining a plurality of score improvement lists, each score improvement list being associated with a point value, each score improvement list being an ordered list of adjusters, wherein the adjusters are serially applied in order of the adjusters in the ordered list to initial scores of a group of search results to determine a final scoring of the search results; iteratively selecting pairs of score improvement lists from a pool of score improvement lists, the pool of score improvement lists including the plurality of score improvement lists; automatically for each selected pair: separately applying the ordered list of adjusters for each score improvement list included in the selected pair to one or more search results associated with a search query from the search query data, in response to the applying, identifying, for each score improvement list in the selected pair, respective ordered search results responsive to the search query, determining a winning and losing score improvement list in the selected pair from the respective ordered search results and the user selection data associated with the search query, increasing the point value associated with the winning score improvement list, and decreasing the point value associated with the losing score improvement list; repeating testing for respective pairs of score improvement lists until ending criteria are reached; and selecting one or more score improvement lists based on the respective point values after the repeated testing. | 11. A system comprising: a processor; and a non-transitory computer-readable medium coupled to the processor and having instructions stored thereon, which, when executed by the processor, cause the processor to perform operations comprising: obtaining search query data, the search query data including a plurality of search queries submitted by users, each search query being associated with one or more responsive search results and user selection data for the one or more search results, wherein the user selection data identifies which search results were selected by users; obtaining a plurality of score improvement lists, each score improvement list being associated with a point value, each score improvement list being an ordered list of adjusters, wherein the adjusters are serially applied in order of the adjusters in the ordered list to initial scores of a group of search results to determine a final scoring of the search results; iteratively selecting pairs of score improvement lists from a pool of score improvement lists, the pool of score improvement lists including the plurality of score improvement lists; automatically for each selected pair: separately applying the ordered list of adjusters for each score improvement list included in the selected pair to one or more search results associated with a search query from the search query data, in response to the applying, identifying, for each score improvement list in the selected pair, respective ordered search results responsive to the search query, determining a winning and losing score improvement list in the selected pair from the respective ordered search results and the user selection data associated with the search query, increasing the point value associated with the winning score improvement list, and decreasing the point value associated with the losing score improvement list; repeating testing for respective pairs of score improvement lists until ending criteria are reached; and selecting one or more score improvement lists based on the respective point values after the repeated testing. 20. The system of claim 11 , wherein the user selection data includes, for each search result, a length of user time spent at a particular resource associated with the search result. | 0.866959 |
9,368,107 | 14 | 15 | 14. A computing system for discovering speech recognition commands comprising a processor, a memory, and a bus linking the processor and memory, wherein said processor is able execute instructions of at least one computer program product that is stored in a non-transitory storage medium, wherein execution of the instructions causes the computing system to: automatically respond to a manually initiated action with voice command discovery by presenting speech command data configured to facilitate initiation of the action via speech, such that the presentation of the speech command data directs the user to use the speech command to initiate the action without manual intervention, wherein the computing system in communication with a discovery server through an application server, and wherein the automatically responding with voice command discovery causing the computing system to: receive at an application an input from a manually initiated action, wherein the computing system is associated with a speech component, wherein the input is associated with a computing system function, and wherein the computing system function is an operation within the computing system and is linked to a function identifier, the function identifier being associated with the manually initiated action in the context of the application; transmit a request containing the function identifier through the application server to the discovery server, the discovery server configured with a mapping of function identifiers linked to respective speech command data, wherein the discovery server determines the application based on an application identifier derived from the manually initiated action, and wherein the discovery server translates the function identifier contained in the request to the speech command data by using the function identifier contained in the request associated with the application to find in the mapping a corresponding function identifier linked to the speech command data; receive from the discovery server through the application server the speech command data, wherein the command data is associated with a command identifier and a command, and wherein the speech command data is a speech command registered within the speech component; and present the received speech command data within a speech interface of the speech component responsive to the translating. | 14. A computing system for discovering speech recognition commands comprising a processor, a memory, and a bus linking the processor and memory, wherein said processor is able execute instructions of at least one computer program product that is stored in a non-transitory storage medium, wherein execution of the instructions causes the computing system to: automatically respond to a manually initiated action with voice command discovery by presenting speech command data configured to facilitate initiation of the action via speech, such that the presentation of the speech command data directs the user to use the speech command to initiate the action without manual intervention, wherein the computing system in communication with a discovery server through an application server, and wherein the automatically responding with voice command discovery causing the computing system to: receive at an application an input from a manually initiated action, wherein the computing system is associated with a speech component, wherein the input is associated with a computing system function, and wherein the computing system function is an operation within the computing system and is linked to a function identifier, the function identifier being associated with the manually initiated action in the context of the application; transmit a request containing the function identifier through the application server to the discovery server, the discovery server configured with a mapping of function identifiers linked to respective speech command data, wherein the discovery server determines the application based on an application identifier derived from the manually initiated action, and wherein the discovery server translates the function identifier contained in the request to the speech command data by using the function identifier contained in the request associated with the application to find in the mapping a corresponding function identifier linked to the speech command data; receive from the discovery server through the application server the speech command data, wherein the command data is associated with a command identifier and a command, and wherein the speech command data is a speech command registered within the speech component; and present the received speech command data within a speech interface of the speech component responsive to the translating. 15. The system of claim 14 , wherein the presenting comprises enunciating the command associated with the command data, wherein the command is at least one of a word and a phrase. | 0.886565 |
7,929,767 | 11 | 12 | 11. A method performed by a computing system for analyzing a handwritten mathematical expression, the method comprising steps of: providing a mapping of dominant symbols to their corresponding characters and locations of any sub-expressions relative to the dominant symbol; identifying by the computing system potential dominant symbols within the handwritten mathematical expression, each potential dominant symbol having shape information; for each potential dominant symbol that is identified, identifying by the computing system sub-expressions of the potential dominant symbol; determining by the computing system the location of each identified sub-expression relative to the potential dominant symbol; and recognizing by the computing system a character the potential dominant symbol of the handwritten expression represents from the provided mapping based on the determined location of the identified sub-expressions relative to the potential dominant symbol and from shape information of the potential dominant symbol such that the potential dominant symbol cannot be correctly recognized based on the shape information alone; receiving from the user a selection of a potential dominant symbol; displaying to the user a list of characters as potentially representing the selected potential dominant symbol and receiving from the user a selection of a character from the list; displaying to the user the selected character to replace the potential dominant symbol in the handwritten mathematical expression along with a placeholder corresponding to a sub-expression of the selected character; and receiving from the user a symbol to be inserted in the placeholder by dragging and dropping a previously handwritten symbol into the placeholder, the symbol representing a sub-expression of the selected character. | 11. A method performed by a computing system for analyzing a handwritten mathematical expression, the method comprising steps of: providing a mapping of dominant symbols to their corresponding characters and locations of any sub-expressions relative to the dominant symbol; identifying by the computing system potential dominant symbols within the handwritten mathematical expression, each potential dominant symbol having shape information; for each potential dominant symbol that is identified, identifying by the computing system sub-expressions of the potential dominant symbol; determining by the computing system the location of each identified sub-expression relative to the potential dominant symbol; and recognizing by the computing system a character the potential dominant symbol of the handwritten expression represents from the provided mapping based on the determined location of the identified sub-expressions relative to the potential dominant symbol and from shape information of the potential dominant symbol such that the potential dominant symbol cannot be correctly recognized based on the shape information alone; receiving from the user a selection of a potential dominant symbol; displaying to the user a list of characters as potentially representing the selected potential dominant symbol and receiving from the user a selection of a character from the list; displaying to the user the selected character to replace the potential dominant symbol in the handwritten mathematical expression along with a placeholder corresponding to a sub-expression of the selected character; and receiving from the user a symbol to be inserted in the placeholder by dragging and dropping a previously handwritten symbol into the placeholder, the symbol representing a sub-expression of the selected character. 12. The method of claim 11 , further comprising steps of: determining whether an expression structure candidate is valid; storing information of the valid expression structure candidate in a parse tree. | 0.813996 |
10,055,874 | 7 | 12 | 7. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 1 wherein synchronizing lip movement of the creature with lip movement from the first animation model comprises: determining a jaw opening of the first animation model; determining a jaw opening for the second animation model; and determining if the jaw opening of the second animation model matches the jaw opening of the first animation model, and if not, adjusting the jaw opening of the second animation model to more closely match the jaw opening of the first animation model. | 7. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 1 wherein synchronizing lip movement of the creature with lip movement from the first animation model comprises: determining a jaw opening of the first animation model; determining a jaw opening for the second animation model; and determining if the jaw opening of the second animation model matches the jaw opening of the first animation model, and if not, adjusting the jaw opening of the second animation model to more closely match the jaw opening of the first animation model. 12. The method of transferring facial expressions from a subject to a computer-generated character set forth in claim 7 wherein a match between the jaw opening of the second animation model and the jaw opening of the first animation model occurs when the openings are within a predetermined amount of each other. | 0.93543 |
8,233,671 | 16 | 17 | 16. A reading device, comprising: a camera configured to scan at least a portion of a document having text; at least one processor configured to identify text blocks and to characterize a first text block of the text blocks into a hierarchical level based at least on a format attribute in the first text block and on a format attribute in a second text block proximal to the first text block; and a user interface to allow a user to hierarchically navigate the text blocks when read to the user, wherein the at least one processor is configured to characterize the first text block into a hierarchical level based at least on whether a character dimension of the first text block is bigger than a character dimension in a different text block by about ten percent or more. | 16. A reading device, comprising: a camera configured to scan at least a portion of a document having text; at least one processor configured to identify text blocks and to characterize a first text block of the text blocks into a hierarchical level based at least on a format attribute in the first text block and on a format attribute in a second text block proximal to the first text block; and a user interface to allow a user to hierarchically navigate the text blocks when read to the user, wherein the at least one processor is configured to characterize the first text block into a hierarchical level based at least on whether a character dimension of the first text block is bigger than a character dimension in a different text block by about ten percent or more. 17. The device of claim 16 , wherein the at least one processor is configured to perform optical character recognition to process the raster file. | 0.690678 |
9,081,816 | 1 | 6 | 1. A method of implementing a universal framework for searching across multiple search platforms in a secure federated search, the method comprising: receiving, at a federated broker, a query from an authenticated user; obtaining, by the federated broker, a plurality of user credentials associated with the authenticated user, wherein each of the plurality of user credentials is used to access at least one source of a plurality of sources; obtaining, by the federated broker, a plurality of security attributes associated with the authenticated user, wherein: the plurality of security attributes are distinct from the plurality of user credentials; and the plurality of user credentials are first used to access the plurality of sources, and then the plurality of security attributes are compared to security attributes of individual documents within the plurality of sources to determine if the authenticated user can access the individual documents; determining, by the federated broker, a required query format for each of the plurality of sources; translating, by the federated broker, the query into a plurality of queries formatted according to the required query format of each of the plurality of sources; propagating, by the federated broker, the plurality of translated queries, the plurality of security attributes, and the plurality of user credentials to each corresponding source to appear to each corresponding source to be the authenticated user; receiving, at the federated broker, results of each of the plurality of queries from each source of the plurality of sources; and consolidating, by the federated broker, the results of each of the plurality of queries to be displayed in a uniform manner. | 1. A method of implementing a universal framework for searching across multiple search platforms in a secure federated search, the method comprising: receiving, at a federated broker, a query from an authenticated user; obtaining, by the federated broker, a plurality of user credentials associated with the authenticated user, wherein each of the plurality of user credentials is used to access at least one source of a plurality of sources; obtaining, by the federated broker, a plurality of security attributes associated with the authenticated user, wherein: the plurality of security attributes are distinct from the plurality of user credentials; and the plurality of user credentials are first used to access the plurality of sources, and then the plurality of security attributes are compared to security attributes of individual documents within the plurality of sources to determine if the authenticated user can access the individual documents; determining, by the federated broker, a required query format for each of the plurality of sources; translating, by the federated broker, the query into a plurality of queries formatted according to the required query format of each of the plurality of sources; propagating, by the federated broker, the plurality of translated queries, the plurality of security attributes, and the plurality of user credentials to each corresponding source to appear to each corresponding source to be the authenticated user; receiving, at the federated broker, results of each of the plurality of queries from each source of the plurality of sources; and consolidating, by the federated broker, the results of each of the plurality of queries to be displayed in a uniform manner. 6. The method for implementing a universal framework for searching across multiple search platforms in a secure federated search as in claim 1 , wherein propagating, by the federated broker, the plurality of translated queries and the plurality of user credentials to each corresponding source to appear to each corresponding source to be the authorized user is implemented in a single sign-on (SSO) federation environment. | 0.670047 |
10,002,167 | 1 | 5 | 1. A method, executed on a suitably programmed computing device, for managing data, the method comprising: extracting, by a search engine, a plurality of data field descriptors from at least one database from each of a plurality of disparate data sources, comprising the search engine: performing a preliminary database access function to determine access to each of the at least one database, wherein for each database: determining a schema of the database, and determining available data fields of the database; using the plurality of data field descriptors from each of the at least one database, developing a data field result list upon which a query may be run, by: providing a display of the plurality of data field descriptors and control data from the at least one database, the control data comprising one or more of constraints, fields, keywords, and truncations used for extracting the plurality of data field descriptors from the at least one database, and saving the plurality of data field descriptors and the control data as the data field result list for each of the at least one database; receiving, from a graphical user interface, a user search request directed to the data field result list; transforming the user search request into a dataset query based on the data field result list by combining the user search request with an API request; communicating the dataset query to the at least one database; searching the at least one database using the dataset query; and managing, based on the data field result list, data from the at least one database comprising providing a response to the dataset query of the at least one database. | 1. A method, executed on a suitably programmed computing device, for managing data, the method comprising: extracting, by a search engine, a plurality of data field descriptors from at least one database from each of a plurality of disparate data sources, comprising the search engine: performing a preliminary database access function to determine access to each of the at least one database, wherein for each database: determining a schema of the database, and determining available data fields of the database; using the plurality of data field descriptors from each of the at least one database, developing a data field result list upon which a query may be run, by: providing a display of the plurality of data field descriptors and control data from the at least one database, the control data comprising one or more of constraints, fields, keywords, and truncations used for extracting the plurality of data field descriptors from the at least one database, and saving the plurality of data field descriptors and the control data as the data field result list for each of the at least one database; receiving, from a graphical user interface, a user search request directed to the data field result list; transforming the user search request into a dataset query based on the data field result list by combining the user search request with an API request; communicating the dataset query to the at least one database; searching the at least one database using the dataset query; and managing, based on the data field result list, data from the at least one database comprising providing a response to the dataset query of the at least one database. 5. The method of claim 1 , wherein developing the data field result list comprises developing a dataset tree. | 0.928944 |
8,806,432 | 1 | 3 | 1. A computer implemented method for virtually executing a program having property declarations of classes in a first programming language that is a dynamic scripting language on an execution system of a second programming language, the method comprising the steps of: generating an interface class that is uniquely determined from a property name in the program in the first programming language; loading the interface class; and preparing, for a first class of the first programming language occurring during execution of the program in the first programming language, when the first class of the first programming language directly inherits a second class of the first programming language, a class hierarchy on the execution system of the second programming language so that the class hierarchy corresponds to a dynamically created class hierarchy on the program in the first programming language by caching a second class of the second programming language inheriting a first class of the second programming language, with the first class of the second programming language corresponding to the first class of the first programming language being a key; determining whether a second object of the second programming language, corresponding to a first object of the first programming language, is an instance of an interface class of the second programming language; and converting an operator of the first programming language for obtaining a property of the first object of the first programming language to a conditional operator of the second programming language and a function that returns a corresponding property of the second object of the second programming language in response to determining that the second object of the second programming language, corresponding to the first object, is the instance of the interface class of the second programming language, wherein the converting obviates a use of a hash table; wherein fields are prepared in the first and second classes of the second programming language corresponding to the respective property declarations of the first and second classes of the program in the first programming language, wherein a processor connected to a memory device is configured to perform: the generating, the loading, the preparing, the determining and the converting. | 1. A computer implemented method for virtually executing a program having property declarations of classes in a first programming language that is a dynamic scripting language on an execution system of a second programming language, the method comprising the steps of: generating an interface class that is uniquely determined from a property name in the program in the first programming language; loading the interface class; and preparing, for a first class of the first programming language occurring during execution of the program in the first programming language, when the first class of the first programming language directly inherits a second class of the first programming language, a class hierarchy on the execution system of the second programming language so that the class hierarchy corresponds to a dynamically created class hierarchy on the program in the first programming language by caching a second class of the second programming language inheriting a first class of the second programming language, with the first class of the second programming language corresponding to the first class of the first programming language being a key; determining whether a second object of the second programming language, corresponding to a first object of the first programming language, is an instance of an interface class of the second programming language; and converting an operator of the first programming language for obtaining a property of the first object of the first programming language to a conditional operator of the second programming language and a function that returns a corresponding property of the second object of the second programming language in response to determining that the second object of the second programming language, corresponding to the first object, is the instance of the interface class of the second programming language, wherein the converting obviates a use of a hash table; wherein fields are prepared in the first and second classes of the second programming language corresponding to the respective property declarations of the first and second classes of the program in the first programming language, wherein a processor connected to a memory device is configured to perform: the generating, the loading, the preparing, the determining and the converting. 3. The method according to claim 1 , wherein the first programming language is PHP, and the second programming language is Java®. | 0.766304 |
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