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8,010,979 | 1 | 7 | 1. A method for allowing an operator to update a functionality characteristic of an interactive television program guide implemented on a user television equipment, the method comprising: allowing the operator to remotely supply a markup language document to the interactive television program guide implemented on the user television equipment; updating the functionality characteristic of the interactive television program guide based on the markup language document using the interactive television program guide; and generating a program guide display screen on the user television equipment having the functionality characteristic of the interactive television program guide as updated based on the markup language document. | 1. A method for allowing an operator to update a functionality characteristic of an interactive television program guide implemented on a user television equipment, the method comprising: allowing the operator to remotely supply a markup language document to the interactive television program guide implemented on the user television equipment; updating the functionality characteristic of the interactive television program guide based on the markup language document using the interactive television program guide; and generating a program guide display screen on the user television equipment having the functionality characteristic of the interactive television program guide as updated based on the markup language document. 7. The method of claim 1 , wherein the updated functionality characteristic causes, in response to user input, the program guide to display a program listings information screen, start a recording, set a favorite channel, or set a reminder. | 0.5 |
9,549,042 | 7 | 8 | 7. The method of claim 6 , wherein the record features comprise at least one of the count features, the entropy features and the semantic features, and the stability features comprise a measure of stability of neighboring information units from the multiple electronic devices based on at least one similarity metric. | 7. The method of claim 6 , wherein the record features comprise at least one of the count features, the entropy features and the semantic features, and the stability features comprise a measure of stability of neighboring information units from the multiple electronic devices based on at least one similarity metric. 8. The method of claim 7 , wherein inferring user context comprises at least one of segmenting the information units and smoothing the information units. | 0.5 |
8,250,145 | 21 | 26 | 21. A method for providing social information, the method comprising: receiving at a server of a social networking system a request for information based on an instruction in a markup language document, wherein the request for information comprises one or more parameters for selecting the requested information, and wherein the determined requested information is selected based on the parameters, wherein the request for information is responsive to a request for a web page of a third-party website that is within a domain of a third-party website that is different from a domain of the social networking system, and wherein the markup language document includes an instruction to create a frame within the web page that includes information obtained from the social networking system, the frame comprising an iframe that contains a web page in the domain of the social networking system; identifying a user associated with the request; determining the requested information based on social information associated with the user; and sending the requested information for display in the frame of the web page. | 21. A method for providing social information, the method comprising: receiving at a server of a social networking system a request for information based on an instruction in a markup language document, wherein the request for information comprises one or more parameters for selecting the requested information, and wherein the determined requested information is selected based on the parameters, wherein the request for information is responsive to a request for a web page of a third-party website that is within a domain of a third-party website that is different from a domain of the social networking system, and wherein the markup language document includes an instruction to create a frame within the web page that includes information obtained from the social networking system, the frame comprising an iframe that contains a web page in the domain of the social networking system; identifying a user associated with the request; determining the requested information based on social information associated with the user; and sending the requested information for display in the frame of the web page. 26. The method of claim 21 , further comprising: receiving an indication of whether the user has an existing session with the social networking system. | 0.756452 |
9,141,605 | 1 | 10 | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries, wherein the annotation that annotates one matched element of the matched elements is a domain term that expresses that the one matched element is a noun defining a particular domain; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request. | 1. A method for semantic attribution of a request, said method implemented by a processor of a computer system, said method comprising: said processor receiving source data statements for the request; said processor receiving a selection of a domain for the received source data statements; said processor semantically analyzing the received source data statements, said semantically analyzing comprising matching elements in the received source data statements to respective one or more entries in an ontology associated with the selected domain, wherein the ontology comprises items and relationships that define the selected domain, and wherein each element in the received source data statements is a word or a phrase; said processor assigning the one or more entries to the matched elements, respectively, to annotate each matched element with a respective annotation consisting of the respective one or more entries, wherein the annotation that annotates one matched element of the matched elements is a domain term that expresses that the one matched element is a noun defining a particular domain; said processor saving the annotated elements with the respective annotations; and said processor using the annotations to generate a search query for the request. 10. The method of claim 1 , wherein the annotation that annotates one matched element of the matched elements is a pillar which is a main structural element of the ontology, wherein the pillar expresses: an activity and refers to what changed, a product and an associated environment to identify main products of concern, a situation to identify symptoms associated with a specific situation or incident, or a component to define where a situation occurs. | 0.788372 |
7,617,078 | 13 | 38 | 13. The system of claim 1 , wherein the created structured clinical information is stored in a database. | 13. The system of claim 1 , wherein the created structured clinical information is stored in a database. 38. The system of claim 13 wherein the database comprises a healthcare provider database. | 0.5 |
9,805,020 | 2 | 3 | 2. The method of claim 1 , wherein setting the first context compartment as the current context compartment comprises identifying the first context compartment as a context compartment that comprises the identified first row. | 2. The method of claim 1 , wherein setting the first context compartment as the current context compartment comprises identifying the first context compartment as a context compartment that comprises the identified first row. 3. The method of claim 2 , the identification of the first context compartment as a context compartment that comprises the identified first row is based on a value in the outline field of the identified first row, and wherein only searching the current context compartment comprises restricting the search to only those of the plurality of rows in the at least one table that comprise outline fields having the same value as the value in the outline field of the identified first row. | 0.5 |
7,496,593 | 1 | 4 | 1. A computer-implemented system for creating one or more multi-relational ontologies having a predetermined structure, the system comprising: at least one processor and a memory having instructions causing the processor to: (i) create an upper ontology that includes: a set of predetermined concept types, a set of predetermined relationship types, a set of concept type pairs, and for each concept type pair, a set of relationships permitted to be used to connect the concept types of the concept type pair; (ii) receive raw data and arrange the raw data into a plurality of individual assertions according to the upper ontology, each assertion comprising a first concept, a second concept, and a relationship between the first and second concept, wherein the first and second concept of each assertion have a concept type from the set of predetermined concept types, wherein the relationship of each assertion has a relationship type from the set of predetermined relationship types, wherein the first and second concept of each assertion belong to a concept type pair of the set of concept type pairs and are connected by a relationship from the set of possible relationships permitted for the concept type pair, wherein at least one concept within the plurality of assertions is part of more than one assertion, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, wherein each concept within each assertion of the plurality of individual assertions is associated with a label, a concept type, and at least one property, and wherein the at least one property includes at least a version of a data source from which the concept was derived; and (iii) store on at least one data storage device: the plurality of individual assertions as one or more multi-relational ontologies, and one or more pieces of evidence supporting information contained in each assertion of the plurality of assertions, wherein each of the one or more pieces of evidence are linked to their corresponding assertion such that each of the one or more pieces of evidence are able to be accessed along with their corresponding assertion, and wherein the one or more pieces of evidence are each associated with at least a data source from which the evidence is derived. | 1. A computer-implemented system for creating one or more multi-relational ontologies having a predetermined structure, the system comprising: at least one processor and a memory having instructions causing the processor to: (i) create an upper ontology that includes: a set of predetermined concept types, a set of predetermined relationship types, a set of concept type pairs, and for each concept type pair, a set of relationships permitted to be used to connect the concept types of the concept type pair; (ii) receive raw data and arrange the raw data into a plurality of individual assertions according to the upper ontology, each assertion comprising a first concept, a second concept, and a relationship between the first and second concept, wherein the first and second concept of each assertion have a concept type from the set of predetermined concept types, wherein the relationship of each assertion has a relationship type from the set of predetermined relationship types, wherein the first and second concept of each assertion belong to a concept type pair of the set of concept type pairs and are connected by a relationship from the set of possible relationships permitted for the concept type pair, wherein at least one concept within the plurality of assertions is part of more than one assertion, wherein one or more relationships in the plurality of individual assertions comprise relationships unconstrained by any hierarchical arrangement of concepts, wherein each concept within each assertion of the plurality of individual assertions is associated with a label, a concept type, and at least one property, and wherein the at least one property includes at least a version of a data source from which the concept was derived; and (iii) store on at least one data storage device: the plurality of individual assertions as one or more multi-relational ontologies, and one or more pieces of evidence supporting information contained in each assertion of the plurality of assertions, wherein each of the one or more pieces of evidence are linked to their corresponding assertion such that each of the one or more pieces of evidence are able to be accessed along with their corresponding assertion, and wherein the one or more pieces of evidence are each associated with at least a data source from which the evidence is derived. 4. The system of claim 1 , wherein at least one concept from the plurality of individual assertions is associated with one or more quantitative values. | 0.802872 |
8,725,759 | 9 | 10 | 9. The data providing system of claim 8 , wherein the processor is configured to receive the data from the data repository by identifying a first data source according to a source key, identifying a record in the first data source containing the data according to a record key, and retrieving the data from the record. | 9. The data providing system of claim 8 , wherein the processor is configured to receive the data from the data repository by identifying a first data source according to a source key, identifying a record in the first data source containing the data according to a record key, and retrieving the data from the record. 10. The data providing system of claim 9 , wherein the first data source is a table, the source key identifying the table among the plurality of data sources. | 0.5 |
9,684,885 | 1 | 3 | 1. A method for creating OWL (Web Ontology Language) ontology from a UBL (Universal Business Language) process diagram, the method comprising: extracting, by a data converting computing device, at least one of one or more processes, one or more partitions, one or more activities, or one or more objects from the UBL process diagram; creating, by the data converting computing device, a first OWL class corresponding to the one or more processes assigned as instances to the first OWL class, a second OWL class corresponding to the one or more partitions assigned as instances to the second OWL class, a third OWL class corresponding to the one or more assigned as instances to the third OWL class, and one or more object properties, wherein the one or more object properties correspond to the one or more activities; assigning, by the data converting computing device, a domain and a range corresponding to each of the one or more object properties, wherein assigning the range to each of the one or more object properties comprises determining an object associated with each of the one or more object properties assigning the object as the range to each of the one or more object properties; generating, by the data converting computing device, an OWL ontology by adding the first OWL class, the second OWL class, the third OWL class, and the one or more object properties; and associating, by the data converting computing device, one or more rules with the one or more object properties, wherein the one or more rules capture the sequence of the one or more activities. | 1. A method for creating OWL (Web Ontology Language) ontology from a UBL (Universal Business Language) process diagram, the method comprising: extracting, by a data converting computing device, at least one of one or more processes, one or more partitions, one or more activities, or one or more objects from the UBL process diagram; creating, by the data converting computing device, a first OWL class corresponding to the one or more processes assigned as instances to the first OWL class, a second OWL class corresponding to the one or more partitions assigned as instances to the second OWL class, a third OWL class corresponding to the one or more assigned as instances to the third OWL class, and one or more object properties, wherein the one or more object properties correspond to the one or more activities; assigning, by the data converting computing device, a domain and a range corresponding to each of the one or more object properties, wherein assigning the range to each of the one or more object properties comprises determining an object associated with each of the one or more object properties assigning the object as the range to each of the one or more object properties; generating, by the data converting computing device, an OWL ontology by adding the first OWL class, the second OWL class, the third OWL class, and the one or more object properties; and associating, by the data converting computing device, one or more rules with the one or more object properties, wherein the one or more rules capture the sequence of the one or more activities. 3. The method of claim 1 , further comprising creating, by the data converting computing device, the one or more object properties for each of an initial node and a final node, wherein the initial node and the final node connect the one or more processes in the UBL process diagram. | 0.628947 |
7,769,235 | 7 | 8 | 7. The method as recited in claim 1 wherein said reliability value of said template rejected by context analysis means is decremented. | 7. The method as recited in claim 1 wherein said reliability value of said template rejected by context analysis means is decremented. 8. The method as recited in claim 7 wherein when the reliability value of said template decreases lower than the predefined minimal level, the said template is deleted from the template cache. | 0.5 |
9,400,772 | 1 | 5 | 1. A method performed by a handheld mobile communication terminal for offering a dictionary feature, the method comprising: displaying at least a portion of a text document on a display unit configured for the handheld mobile communication terminal; in response to at least one touch input for selecting a word, displaying an enlarged version of a part of the displayed text document and providing an indication of a selected word and a visual element for receiving a user request for dictionary information corresponding to the selected word among the part of the displayed text document, the visual element overlaying less than all of the displayed text document; in response to the user request for the dictionary information via the visual element, displaying a dictionary screen in place of the displayed text document so that the dictionary screen visually appears to be over the entire displayed text document, the dictionary screen showing the dictionary information corresponding to the selected word; and in response to a user request for termination of the dictionary screen, returning from the dictionary screen to a screen showing the displayed text document with the indication of the selected word remaining, wherein the enlarged version of the part of the displayed text document and the part of the displayed text document are both displayed at the same time. | 1. A method performed by a handheld mobile communication terminal for offering a dictionary feature, the method comprising: displaying at least a portion of a text document on a display unit configured for the handheld mobile communication terminal; in response to at least one touch input for selecting a word, displaying an enlarged version of a part of the displayed text document and providing an indication of a selected word and a visual element for receiving a user request for dictionary information corresponding to the selected word among the part of the displayed text document, the visual element overlaying less than all of the displayed text document; in response to the user request for the dictionary information via the visual element, displaying a dictionary screen in place of the displayed text document so that the dictionary screen visually appears to be over the entire displayed text document, the dictionary screen showing the dictionary information corresponding to the selected word; and in response to a user request for termination of the dictionary screen, returning from the dictionary screen to a screen showing the displayed text document with the indication of the selected word remaining, wherein the enlarged version of the part of the displayed text document and the part of the displayed text document are both displayed at the same time. 5. The method of claim 1 , further comprising editing the part of the displayed text document in response to an editing input. | 0.686567 |
9,582,539 | 13 | 15 | 13. A computer-implemented system for optimizing queries, the system comprising: a computer processor; and a non-transitory computer-readable storage medium storing computer program modules configured to execute on the computer processor, the computer program modules comprising: an optimizer module configured to: receive a database query for optimization, the database query comprising a first subquery and a second subquery, the first subquery specifying a first where clause comprising a first condition and the second subquery specifying a second where clause comprising a second condition, wherein the first where clause is distinct from the second where clause and wherein the first condition evaluates to true for a first set of input rows and the second condition evaluates to true for a second set of input rows; compare the first subquery and the second subquery based on input tables processed by each of the first and second subqueries; responsive to determining that the first subquery and the second subquery match based on the comparison: generate a first database query specifying a where clause comprising a condition that evaluates to true for a superset of the first set of input rows and the second set of input rows; generate a statement comprising the first database query, the statement storing result of execution of the first database query in a result table; generate a first expression equivalent to the first subquery and a second expression equivalent to the second subquery, the first and the second expressions based on the result table; modify the database query to use the result table, the modifying comprising, replacing the first subquery with the first expression and the second subquery with the second expression; and replace an execution of the database query with an execution of the statement followed by an execution of the modified database query. | 13. A computer-implemented system for optimizing queries, the system comprising: a computer processor; and a non-transitory computer-readable storage medium storing computer program modules configured to execute on the computer processor, the computer program modules comprising: an optimizer module configured to: receive a database query for optimization, the database query comprising a first subquery and a second subquery, the first subquery specifying a first where clause comprising a first condition and the second subquery specifying a second where clause comprising a second condition, wherein the first where clause is distinct from the second where clause and wherein the first condition evaluates to true for a first set of input rows and the second condition evaluates to true for a second set of input rows; compare the first subquery and the second subquery based on input tables processed by each of the first and second subqueries; responsive to determining that the first subquery and the second subquery match based on the comparison: generate a first database query specifying a where clause comprising a condition that evaluates to true for a superset of the first set of input rows and the second set of input rows; generate a statement comprising the first database query, the statement storing result of execution of the first database query in a result table; generate a first expression equivalent to the first subquery and a second expression equivalent to the second subquery, the first and the second expressions based on the result table; modify the database query to use the result table, the modifying comprising, replacing the first subquery with the first expression and the second subquery with the second expression; and replace an execution of the database query with an execution of the statement followed by an execution of the modified database query. 15. The computer-implemented system of claim 13 , wherein the first subquery includes a group by clause based on a first set of columns and the second subquery includes a group by clause based on a second set of columns, wherein generating the statement comprises: determining a union of the first set of columns and the second set of columns; and adding a group by clause to a query of the statement to group the result of the query by the union of the first and second set of columns. | 0.5 |
10,095,988 | 14 | 15 | 14. The system of claim 11 , further comprising displaying a ranked list of search results for the search query, the search results including social graph information associated with the search results. | 14. The system of claim 11 , further comprising displaying a ranked list of search results for the search query, the search results including social graph information associated with the search results. 15. The system of claim 14 , wherein the social graph information comprises likes or comments for the search results from friends of a user of the client device. | 0.5 |
10,097,490 | 1 | 6 | 1. A method for providing services over a secure forum accessible from within a controlled environment, comprising: receiving a first request to post a communication in a sub-forum of the secure forum, the first request including a first identifier associated with a resident of the controlled environment and a sub-forum identifier associated with the sub-forum; retrieving a rule associated with at least one of the first identifier and the sub-forum; posting, based on the rule, the communication in the sub-forum; transmitting, based on the rule, a notification of the posted communication to a destination identified by the rule; receiving a second request to access the sub-forum, the second request including a second identifier of another registered user in the controlled environment; determining to allow the access to the sub-forum based on at least one of the second identifier and the rule; performing a text-based analysis of the communication; and generating a service recommendation based on the text-based analysis of the communication and a recommendation rule, wherein the service recommendation identifies a service provider approved by the controlled environment to communicate in the secure forum; and transmitting the service recommendation to an account associated with the first identifier. | 1. A method for providing services over a secure forum accessible from within a controlled environment, comprising: receiving a first request to post a communication in a sub-forum of the secure forum, the first request including a first identifier associated with a resident of the controlled environment and a sub-forum identifier associated with the sub-forum; retrieving a rule associated with at least one of the first identifier and the sub-forum; posting, based on the rule, the communication in the sub-forum; transmitting, based on the rule, a notification of the posted communication to a destination identified by the rule; receiving a second request to access the sub-forum, the second request including a second identifier of another registered user in the controlled environment; determining to allow the access to the sub-forum based on at least one of the second identifier and the rule; performing a text-based analysis of the communication; and generating a service recommendation based on the text-based analysis of the communication and a recommendation rule, wherein the service recommendation identifies a service provider approved by the controlled environment to communicate in the secure forum; and transmitting the service recommendation to an account associated with the first identifier. 6. The method of claim 1 , wherein the second request is received in response to transmitting the notification. | 0.916163 |
9,805,172 | 1 | 3 | 1. A system for managing the separate control of resource usage and resource access for interoperability between and within open, distributed computing environments, comprising: a client computer comprising a processor including both a usage management mechanism and an enforcement mechanism, the usage management mechanism for managing resource usage according to a context, an event, and a license, the license including a set of actions and a policy specifying the conditions for whether or not the event may occur, and the enforcement mechanism for enforcing the license within the system according to how the license may be used; a server computer comprising a processor including a license generator managing resource access according to the policy using a license object and a context object, the license object identifying content usage policies and the context object identifying a structure and state of the computing environment, a model deployed within each of the open, distributed computing environments, the model using generic rights expression language lic, C, umm, iav, EM, for interoperability of the license within the computing environment, the license object represented by lic= Racv, ε, I with Racv representing restricted actions in the computing environment according to the license, ε representing the license that is subject to the restricted actions, and I representing a set of functions supported by the license capturing the dynamic usage history in the computing environment associated with the policy, the context object represented by C= E, S, R , with E representing a set of system environment properties, S representing a set of subject properties, and R representing a set of resource properties capturing the dynamic state of the computing environment through attributes of each entity within the computing environment; the usage management mechanism represented by umm= UI, Act, iC with UI representing functions used by the usage management mechanism to interact with the license, Act representing all actions enabled in the computing environments, and iC representing an instance of the context, wherein the usage management mechanism of the client computer queries the license object and the context object of the server computer for compatibility of the event with the policy and the client computer accepts the event and accesses content when the policy is compatible, wherein an activity by the client computer on the content generates an activity instance iav= acv, iC with acv representing the activity and iC representing the instance of the context; the enforcement mechanism represented by EM= A, iC, U with A representing the set of actions performed under the license, iC representing the instance of the context, and U representing functions of the license that are used by the enforcement mechanism to interact with the license, wherein the enforcement mechanism of the client computer prevents the activity on the content when the activity is not compatible with the set of actions of the license. | 1. A system for managing the separate control of resource usage and resource access for interoperability between and within open, distributed computing environments, comprising: a client computer comprising a processor including both a usage management mechanism and an enforcement mechanism, the usage management mechanism for managing resource usage according to a context, an event, and a license, the license including a set of actions and a policy specifying the conditions for whether or not the event may occur, and the enforcement mechanism for enforcing the license within the system according to how the license may be used; a server computer comprising a processor including a license generator managing resource access according to the policy using a license object and a context object, the license object identifying content usage policies and the context object identifying a structure and state of the computing environment, a model deployed within each of the open, distributed computing environments, the model using generic rights expression language lic, C, umm, iav, EM, for interoperability of the license within the computing environment, the license object represented by lic= Racv, ε, I with Racv representing restricted actions in the computing environment according to the license, ε representing the license that is subject to the restricted actions, and I representing a set of functions supported by the license capturing the dynamic usage history in the computing environment associated with the policy, the context object represented by C= E, S, R , with E representing a set of system environment properties, S representing a set of subject properties, and R representing a set of resource properties capturing the dynamic state of the computing environment through attributes of each entity within the computing environment; the usage management mechanism represented by umm= UI, Act, iC with UI representing functions used by the usage management mechanism to interact with the license, Act representing all actions enabled in the computing environments, and iC representing an instance of the context, wherein the usage management mechanism of the client computer queries the license object and the context object of the server computer for compatibility of the event with the policy and the client computer accepts the event and accesses content when the policy is compatible, wherein an activity by the client computer on the content generates an activity instance iav= acv, iC with acv representing the activity and iC representing the instance of the context; the enforcement mechanism represented by EM= A, iC, U with A representing the set of actions performed under the license, iC representing the instance of the context, and U representing functions of the license that are used by the enforcement mechanism to interact with the license, wherein the enforcement mechanism of the client computer prevents the activity on the content when the activity is not compatible with the set of actions of the license. 3. The system according to claim 1 , wherein the policy further comprises a policy state. | 0.87064 |
9,484,033 | 1 | 3 | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: converting audible speech received by a microphone to text, wherein the audible speech is being delivered to a user; identifying an annotation candidate included in the text; combining a rarity score pertaining to the identified annotation candidate, a phrase matching score pertaining to the identified annotation candidate, and a signal strength score pertaining to a context of the identified annotation candidate into an overall score; in response to the overall score exceeding a threshold, retrieving an annotation reference relating to the identified annotation candidate; and presenting the annotation reference to the user. | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: converting audible speech received by a microphone to text, wherein the audible speech is being delivered to a user; identifying an annotation candidate included in the text; combining a rarity score pertaining to the identified annotation candidate, a phrase matching score pertaining to the identified annotation candidate, and a signal strength score pertaining to a context of the identified annotation candidate into an overall score; in response to the overall score exceeding a threshold, retrieving an annotation reference relating to the identified annotation candidate; and presenting the annotation reference to the user. 3. The method of claim 1 further comprising: parsing the text into a plurality of parts; identifying a locatable entity as one of the parts; and filtering the locatable entity, wherein the filtering results in the annotation candidate. | 0.764056 |
7,636,730 | 33 | 37 | 33. An article of manufacture comprising: a computer-readable storage medium comprising programming configured to cause processing circuitry to: select a cluster label for a cluster comprising a subset of a plurality of documents of a document set at least in part by co-occurrence of the cluster label and a plurality of terms of the documents of the cluster which are indicative of subject matter content of the documents of the cluster, wherein the subset comprises a plurality of the documents and wherein the cluster label comprises one of a plurality of terms common to at least one of the documents of the cluster and the cluster label comprises a plurality of word senses; determine, for individual ones of the word senses, a plurality of semantic similarity values for respective ones of the terms, wherein the semantic similarity values are individually indicative of a degree of semantic similarity between one of the word senses and one of the terms; analyze the semantic similarity values determined for respective ones of the word senses; and select one of the word senses using the analysis, wherein the one of the word senses has an increased relevancy with respect to the terms of the documents of the cluster compared with the relevancies of others of the word senses. | 33. An article of manufacture comprising: a computer-readable storage medium comprising programming configured to cause processing circuitry to: select a cluster label for a cluster comprising a subset of a plurality of documents of a document set at least in part by co-occurrence of the cluster label and a plurality of terms of the documents of the cluster which are indicative of subject matter content of the documents of the cluster, wherein the subset comprises a plurality of the documents and wherein the cluster label comprises one of a plurality of terms common to at least one of the documents of the cluster and the cluster label comprises a plurality of word senses; determine, for individual ones of the word senses, a plurality of semantic similarity values for respective ones of the terms, wherein the semantic similarity values are individually indicative of a degree of semantic similarity between one of the word senses and one of the terms; analyze the semantic similarity values determined for respective ones of the word senses; and select one of the word senses using the analysis, wherein the one of the word senses has an increased relevancy with respect to the terms of the documents of the cluster compared with the relevancies of others of the word senses. 37. The article of claim 33 wherein the terms comprise minor terms and major terms, and the cluster label comprises a major term. | 0.876908 |
10,140,017 | 1 | 11 | 1. A method comprising: outputting, by a first application executing at a computing device, a graphical user interface including a text edit region that includes uncommitted text input, and an output region that includes committed text input: invoking, by the first application, a keyboard application executing at the computing device to provide a graphical keyboard within the graphical user interface; outputting, by the keyboard application, for display adjacent to the text edit and output regions of the graphical user interface, the graphical keyboard, wherein the graphical keyboard includes a plurality of character keys, a word suggestion region and a search element, wherein the word suggestion region and the search element are each positioned above the plurality of character keys and below the text edit and output regions, wherein the word suggestion region includes a plurality of word suggestions based on the uncommitted text input displayed by the text edit region; receiving, by the keyboard application, an indication of a selection of the search element; responsive to receiving the indication of the selection of the search element, outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the word suggestion region, a query suggestion region including one or more suggested search queries; while outputting the query suggestion region for display, receiving, by the keyboard application, an indication of a selection of one or more character keys from the plurality of character keys; outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the query suggestion region, an updated query suggestion region including one or more characters selected in response to the selection of the one or more character keys; determining, by the keyboard application, based on the one or more characters, one or more updated suggested search queries; outputting, by the keyboard application, for display, the one or more updated suggested search queries in the updated query suggestion region; receiving, by the keyboard application, an indication of a selection of one of one or more updated suggested search queries, the one of the one or more updated suggested search queries being a selected search query; invoking, by the keyboard application and based on the selected search query, a search; responsive to invoking the search, receiving, by the keyboard application, search results; and outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of a portion, but not all, of the plurality of character keys, a graphical indication of at least a portion of the search results. | 1. A method comprising: outputting, by a first application executing at a computing device, a graphical user interface including a text edit region that includes uncommitted text input, and an output region that includes committed text input: invoking, by the first application, a keyboard application executing at the computing device to provide a graphical keyboard within the graphical user interface; outputting, by the keyboard application, for display adjacent to the text edit and output regions of the graphical user interface, the graphical keyboard, wherein the graphical keyboard includes a plurality of character keys, a word suggestion region and a search element, wherein the word suggestion region and the search element are each positioned above the plurality of character keys and below the text edit and output regions, wherein the word suggestion region includes a plurality of word suggestions based on the uncommitted text input displayed by the text edit region; receiving, by the keyboard application, an indication of a selection of the search element; responsive to receiving the indication of the selection of the search element, outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the word suggestion region, a query suggestion region including one or more suggested search queries; while outputting the query suggestion region for display, receiving, by the keyboard application, an indication of a selection of one or more character keys from the plurality of character keys; outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of the query suggestion region, an updated query suggestion region including one or more characters selected in response to the selection of the one or more character keys; determining, by the keyboard application, based on the one or more characters, one or more updated suggested search queries; outputting, by the keyboard application, for display, the one or more updated suggested search queries in the updated query suggestion region; receiving, by the keyboard application, an indication of a selection of one of one or more updated suggested search queries, the one of the one or more updated suggested search queries being a selected search query; invoking, by the keyboard application and based on the selected search query, a search; responsive to invoking the search, receiving, by the keyboard application, search results; and outputting, by the keyboard application, for display within the graphical keyboard, adjacent to the text edit and output regions of the graphical user interface, and in place of a portion, but not all, of the plurality of character keys, a graphical indication of at least a portion of the search results. 11. The method of claim 1 , further comprising: determining, by the keyboard application, the one or more suggested queries based on one or more of a search history of a user associated with the computing device, a current messaging conversation, or a current context of the computing device. | 0.735986 |
8,666,982 | 9 | 12 | 9. A system comprising: a non-transitory memory; and a processor to: receive a document; apply one or more tags to the document, each tag applied to a term, each tag representing a part of speech; extract one or more terms from the document based on the tag; determine a frequency parameter for each of the one or more extracted terms, wherein the frequency parameter is proportional to a logarithm of a total number of documents in the domain ontology divided by a number of documents in which the term appears; determine, based on the frequency parameter associated with each of the extracted terms, whether a domain ontology comprises the one or more extracted terms; and augment, if the domain ontology does not comprise the one or more extracted terms, such that the domain ontology comprises the one or more extracted terms. | 9. A system comprising: a non-transitory memory; and a processor to: receive a document; apply one or more tags to the document, each tag applied to a term, each tag representing a part of speech; extract one or more terms from the document based on the tag; determine a frequency parameter for each of the one or more extracted terms, wherein the frequency parameter is proportional to a logarithm of a total number of documents in the domain ontology divided by a number of documents in which the term appears; determine, based on the frequency parameter associated with each of the extracted terms, whether a domain ontology comprises the one or more extracted terms; and augment, if the domain ontology does not comprise the one or more extracted terms, such that the domain ontology comprises the one or more extracted terms. 12. The system of claim 9 , wherein to determine the frequency parameter for each of the one or more extracted terms the processor is to: generate a sorted list of extracted terms arranged according to frequencies. | 0.826016 |
9,348,815 | 8 | 17 | 8. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training, wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error from the knowledge graph representation, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. | 8. A system, comprising: one or more processors; a memory device coupled to the one or more processors and storing instructions which, when executed by the one or more processors, cause the system to perform functions that include: reading text data corresponding to one or more messages; creating one or more semantic annotations to the text data to generate one or more annotated messages, wherein creating the one or more semantic annotations comprises generating, at least in part by a trained statistical language model, one or more predictive labels as annotations corresponding to language patterns associated with the text data; aggregating the one or more annotated messages and storing information associated with the aggregated one or more annotated messages in a message store; and performing, based on information from the message store and associated with the one or more messages, global analytics functions that include: identifying an annotation error in the created semantic annotations, updating the respective semantic annotation to correct the annotation error, and back-propagating the updated semantic annotation into training data for further language model training, wherein aggregating the one or more annotated messages and storing the information associated with the aggregated one or more annotated messages comprises constructing a global knowledge graph representation corresponding to the aggregated one or more annotated messages, and wherein identifying the annotation error, updating the respective semantic annotation, and back-propagating the updated semantic annotation comprises: (a) identifying the annotation error from the knowledge graph representation, (b) updating the respective semantic annotation in the knowledge graph representation to correct the annotation error, (c) back-propagating the updated semantic annotation into the training data for the further language model training, and (d) performing steps (a)-(c) repeatedly until a predetermined level of accuracy of the annotations has been reached or a predetermined number of iterations have been performed. 17. The system of claim 8 , wherein the language patterns comprise at least one of part-of-speech, syntactic role, and sentiment associated with the text data. | 0.671488 |
7,536,297 | 2 | 3 | 2. A system, as in claim 1 , further comprising: a set of abbreviation rules that correlate abbreviation patterns to definition patterns using one or more formation rules that define how each character in an abbreviation is formed from a definition, the set of abbreviation rules including abbreviation rules that have been automatically generated based on candidate abbreviations and definition patterns that have previously been determined as matches by the system; a lookup process that selects one or more formation rules, being selected formation rules, corresponding to the abbreviation pattern of the candidate abbreviation and the definition pattern of the candidate definition; and a rule application process that applies the selected formation rules to determine which candidate definitions match the candidate abbreviation. | 2. A system, as in claim 1 , further comprising: a set of abbreviation rules that correlate abbreviation patterns to definition patterns using one or more formation rules that define how each character in an abbreviation is formed from a definition, the set of abbreviation rules including abbreviation rules that have been automatically generated based on candidate abbreviations and definition patterns that have previously been determined as matches by the system; a lookup process that selects one or more formation rules, being selected formation rules, corresponding to the abbreviation pattern of the candidate abbreviation and the definition pattern of the candidate definition; and a rule application process that applies the selected formation rules to determine which candidate definitions match the candidate abbreviation. 3. A system, as in claim 2 , further comprising: one or more matching algorithms that match one or more pairs of abbreviations and definitions based on the abbreviation patterns and the definition patterns. | 0.552174 |
10,055,397 | 1 | 5 | 1. A system comprising: a processor; memory storing instructions that, when executed by the processor, configure the processor to: receive text data representing text that has been input by a user into one or more of a plurality of devices associated with the user; incorporate the text data into one or more language models by accumulating frequencies of occurrence for sequences of the text data, wherein the frequencies are for occurrences in respective ones of the language models; and provide the one or more language models to one or more of the plurality of devices, the one or more language models being combined to merge the frequencies for occurrences in respective ones of the language models at each of the devices; wherein, in response to deployment of the one or more language models among the plurality of devices, the one or more language models enable synchronized text prediction for text inputs among the plurality of devices based on the merged frequencies for occurrences. | 1. A system comprising: a processor; memory storing instructions that, when executed by the processor, configure the processor to: receive text data representing text that has been input by a user into one or more of a plurality of devices associated with the user; incorporate the text data into one or more language models by accumulating frequencies of occurrence for sequences of the text data, wherein the frequencies are for occurrences in respective ones of the language models; and provide the one or more language models to one or more of the plurality of devices, the one or more language models being combined to merge the frequencies for occurrences in respective ones of the language models at each of the devices; wherein, in response to deployment of the one or more language models among the plurality of devices, the one or more language models enable synchronized text prediction for text inputs among the plurality of devices based on the merged frequencies for occurrences. 5. The system of claim 1 , wherein incorporating the text data into one or more language models comprises incorporating the text data into a single language model to generate a cumulative language model. | 0.655932 |
9,405,834 | 25 | 28 | 25. A non-transitory computer readable storage medium storing at least one program configured for execution by at least one processor of a computer system, the at least one program comprising instructions to: receive a search query from a user; identify a set of ranked search results satisfying the search query; identify, using historical search query data, at least one last related search query in at least one chain of related search queries that is related to the search query and that includes at least one search result that was selected by users who issued the search query, wherein the identifying includes querying a query database to identify the at least one last related search query in the at least one chain of related search queries that are related to the search query, wherein a respective chain of related search queries is a sequence of consecutive search queries that are issued by a respective user and that include an initial search query that is successively refined; the query database includes a plurality of records, wherein each respective record includes: a respective search query; a number of times the respective search query was issued; a respective search result that was selected by users who issued the respective search query and that corresponds to at least one respective related search query in at least one respective chain of related search queries that are related to the respective search query; the at least one respective related search query; and a number of times the respective search query led to a selection of the respective search result; and return the set of ranked search results and the at least one last related search query to the user. | 25. A non-transitory computer readable storage medium storing at least one program configured for execution by at least one processor of a computer system, the at least one program comprising instructions to: receive a search query from a user; identify a set of ranked search results satisfying the search query; identify, using historical search query data, at least one last related search query in at least one chain of related search queries that is related to the search query and that includes at least one search result that was selected by users who issued the search query, wherein the identifying includes querying a query database to identify the at least one last related search query in the at least one chain of related search queries that are related to the search query, wherein a respective chain of related search queries is a sequence of consecutive search queries that are issued by a respective user and that include an initial search query that is successively refined; the query database includes a plurality of records, wherein each respective record includes: a respective search query; a number of times the respective search query was issued; a respective search result that was selected by users who issued the respective search query and that corresponds to at least one respective related search query in at least one respective chain of related search queries that are related to the respective search query; the at least one respective related search query; and a number of times the respective search query led to a selection of the respective search result; and return the set of ranked search results and the at least one last related search query to the user. 28. The non-transitory computer readable storage medium of claim 25 , wherein each respective related search query in the at least one chain of related search queries, except for the at least one last related search query in the at least one chain of related search queries, violates a timing criterion with respect to user-selection of search results. | 0.649402 |
7,716,199 | 53 | 55 | 53. A computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause a computer to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each set of commands contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. | 53. A computer-readable medium encoded with a computer program comprising commands that, when executed, operate to cause a computer to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each set of commands contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. 55. The computer-readable medium of claim 53 , further comprising: selecting a first context file based on the search query input; and selecting a second context file based on an identity of a user who entered the search query input. | 0.69016 |
8,918,406 | 1 | 5 | 1. A method comprising: receiving a content file including audio data; employing processing circuitry to determine an identity score of a source of a portion of at least a portion the content file; employing processing circuitry to determine a word score based for the content file; employing processing circuitry to determine a metadata score for the content file; determining a composite priority score based on the identity score, the word score and the metadata score; and associating the composite priority score with the content file for electronic provision of the content file together with the composite priority score to a human analyst, wherein determining the identity score comprises comparing the audio data in the content file to speaker data in a library of known speakers to determine if an identity of a speaker is determinable based on a degree of matching of the audio data to the speaker data, and, in response to determining the identity of the speaker, assigning the identity score based on a weight value associated with the speaker. | 1. A method comprising: receiving a content file including audio data; employing processing circuitry to determine an identity score of a source of a portion of at least a portion the content file; employing processing circuitry to determine a word score based for the content file; employing processing circuitry to determine a metadata score for the content file; determining a composite priority score based on the identity score, the word score and the metadata score; and associating the composite priority score with the content file for electronic provision of the content file together with the composite priority score to a human analyst, wherein determining the identity score comprises comparing the audio data in the content file to speaker data in a library of known speakers to determine if an identity of a speaker is determinable based on a degree of matching of the audio data to the speaker data, and, in response to determining the identity of the speaker, assigning the identity score based on a weight value associated with the speaker. 5. The method of claim 1 , wherein a plurality of weighting tables are provided and each weighting table corresponds to a separate case, and wherein the metadata score, the word score and the identity score are generated based on a weighting table of an analyst selected case. | 0.585586 |
8,347,231 | 8 | 9 | 8. The data processing system of claim 6 , wherein the graphical user interface comprises an additional slider control displayed adjacent to the long tail tag word inventory curve, wherein the additional slider control is operably associated with the tag cloud and with the long tail tag word inventory curve and is responsive to user movement, and wherein movement of the additional slider control changes the number of the tag words displayed in the tag cloud. | 8. The data processing system of claim 6 , wherein the graphical user interface comprises an additional slider control displayed adjacent to the long tail tag word inventory curve, wherein the additional slider control is operably associated with the tag cloud and with the long tail tag word inventory curve and is responsive to user movement, and wherein movement of the additional slider control changes the number of the tag words displayed in the tag cloud. 9. The data processing system of claim 8 , wherein the two slider controls define a range of popularity on the long tail tag word inventory curve, and wherein only the tag words in the defined range of popularity are displayed within the tag cloud. | 0.5 |
8,886,652 | 1 | 12 | 1. A method for searching objects in a database by means of an index data structure which associates object attribute values to collections of spatial elements—for example tiles of a quadtree or cuboids of an octtree—defined to partition a space, especially a two-dimensional plane or a three-dimensional space, herein a predefined number of spatial elements being combinable to a next-level spatial element, the method comprising: searching the index data structure for a first input search pattern and, if the first input search pattern is associated to a first collection of spatial elements through the index data structure, including all spatial elements from the first collection into a first candidate set of spatial elements, wherein, if the number of spatial elements in the first candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; searching the index data structure for a second input search pattern and, if the second input search pattern is associated to a second collection of spatial elements through the index data structure, including all spatial elements from the second collection into a second candidate set of spatial elements, wherein, if the number of spatial elements in the second candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; forming, from the first candidate set and the second candidate set, a combined candidate set of spatial elements; searching, in the combined candidate set of spatial elements, for objects that match the first input search pattern and the input second search pattern to obtain a set of result objects wherein in the combined candidate set formed from the first candidate set and the second candidate set some or all of the spatial elements are combined to a reduced number of next-level spatial elements if the number of spatial elements in the combined candidate set exceeds a predefined threshold value. | 1. A method for searching objects in a database by means of an index data structure which associates object attribute values to collections of spatial elements—for example tiles of a quadtree or cuboids of an octtree—defined to partition a space, especially a two-dimensional plane or a three-dimensional space, herein a predefined number of spatial elements being combinable to a next-level spatial element, the method comprising: searching the index data structure for a first input search pattern and, if the first input search pattern is associated to a first collection of spatial elements through the index data structure, including all spatial elements from the first collection into a first candidate set of spatial elements, wherein, if the number of spatial elements in the first candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; searching the index data structure for a second input search pattern and, if the second input search pattern is associated to a second collection of spatial elements through the index data structure, including all spatial elements from the second collection into a second candidate set of spatial elements, wherein, if the number of spatial elements in the second candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; forming, from the first candidate set and the second candidate set, a combined candidate set of spatial elements; searching, in the combined candidate set of spatial elements, for objects that match the first input search pattern and the input second search pattern to obtain a set of result objects wherein in the combined candidate set formed from the first candidate set and the second candidate set some or all of the spatial elements are combined to a reduced number of next-level spatial elements if the number of spatial elements in the combined candidate set exceeds a predefined threshold value. 12. The method according to claim 1 , wherein the database contains map data of a navigation device, the objects corresponding to geographic objects of the map data and the two-dimensional plane corresponding to a geographical map to be displayed by the navigation device that is partitioned by the spatial elements, wherein in particular, when interactively inputting the first input search pattern and/or the second input search pattern, a geographical area corresponding to the combined set of spatial elements is output, especially in an incremental manner during the interactive input. | 0.59589 |
8,713,540 | 1 | 8 | 1. A non-transitory computer-accessible memory medium that stores program instructions executable by a computer system to perform: analyzing a graphical program, wherein the graphical program comprises a plurality of interconnected nodes that visually indicate functionality of the graphical program, and wherein the graphical program comprises an I/O interface comprising one or more ordered parameters for providing input to or receiving output from the graphical program; generating a function in a textual programming language based on said analyzing the graphical program, wherein the function implements the functionality of the graphical program, and wherein the function comprises a textual function I/O interface with the one or more ordered parameters of the I/O interface of the graphical program; displaying the textual function I/O interface; receiving user input specifying one or more changes to the textual function I/O interface to produce a modified textual function I/O interface; and in response to the user input, automatically generating a wrapper for the function in the textual programming language with the modified textual function I/O interface, wherein the wrapper is configured to invoke the function, and wherein during execution the wrapper receives one or more input values in accordance with the modified textual function I/O interface and provides the one or more input values to the function via the textual function I/O interface. | 1. A non-transitory computer-accessible memory medium that stores program instructions executable by a computer system to perform: analyzing a graphical program, wherein the graphical program comprises a plurality of interconnected nodes that visually indicate functionality of the graphical program, and wherein the graphical program comprises an I/O interface comprising one or more ordered parameters for providing input to or receiving output from the graphical program; generating a function in a textual programming language based on said analyzing the graphical program, wherein the function implements the functionality of the graphical program, and wherein the function comprises a textual function I/O interface with the one or more ordered parameters of the I/O interface of the graphical program; displaying the textual function I/O interface; receiving user input specifying one or more changes to the textual function I/O interface to produce a modified textual function I/O interface; and in response to the user input, automatically generating a wrapper for the function in the textual programming language with the modified textual function I/O interface, wherein the wrapper is configured to invoke the function, and wherein during execution the wrapper receives one or more input values in accordance with the modified textual function I/O interface and provides the one or more input values to the function via the textual function I/O interface. 8. The non-transitory computer-accessible memory medium of claim 1 , wherein said generating the function in a textual programming language comprises generating a first function prototype in accordance with the I/O interface of the graphical program; and wherein said generating the wrapper for the function in the textual programming language with the modified textual function I/O interface comprises generating a second function prototype in accordance with the modified textual function I/O interface. | 0.711429 |
7,620,622 | 8 | 11 | 8. A system for providing at least one search result responsive to a search query comprising at least one search query term, the system comprising: a parse module for parsing the at least one record for text and non-text indexable elements and assigning a location identifier to one or more of the plurality of text and non-text indexable elements, the location identifier corresponding to a location of a given text and non-text indexable element in the at least one record; an indexing module for indexing the text and non-text indexable elements and the corresponding location identifier for the one or more of the plurality of text and non-text indexable elements, the location identifier is a pointer to the location of the given text and non-text indexable element; a query module for receiving the search query, the search query requesting at least one text and non-text indexable element in the world wide web, the search query received from a user across a networked connection; a search module for locating corresponding text and non-text indexable element relating to the search query; and a transmitter for transmitting a representation of the non-text indexable element and a text representation corresponding to the search query result to the user across the networked connection. | 8. A system for providing at least one search result responsive to a search query comprising at least one search query term, the system comprising: a parse module for parsing the at least one record for text and non-text indexable elements and assigning a location identifier to one or more of the plurality of text and non-text indexable elements, the location identifier corresponding to a location of a given text and non-text indexable element in the at least one record; an indexing module for indexing the text and non-text indexable elements and the corresponding location identifier for the one or more of the plurality of text and non-text indexable elements, the location identifier is a pointer to the location of the given text and non-text indexable element; a query module for receiving the search query, the search query requesting at least one text and non-text indexable element in the world wide web, the search query received from a user across a networked connection; a search module for locating corresponding text and non-text indexable element relating to the search query; and a transmitter for transmitting a representation of the non-text indexable element and a text representation corresponding to the search query result to the user across the networked connection. 11. The system of claim 8 , wherein the object comprises a hyperlink to a sound file. | 0.5 |
8,560,468 | 1 | 6 | 1. A method performed by data processing apparatus, the method comprising: receiving a collection of facts, each fact represented as an entity-attribute-value tuple; identifying expected values for one or more individual attributes, where the identifying expected values includes, for each particular attribute: identifying facts having the attribute, calculating a value score for facts of the collection of facts having the particular attribute for each particular value, calculating a global score for all facts of the collection having the attribute, and comparing the value score to the global score such that a value is identified as an expected value if the comparison satisfies a specified threshold. | 1. A method performed by data processing apparatus, the method comprising: receiving a collection of facts, each fact represented as an entity-attribute-value tuple; identifying expected values for one or more individual attributes, where the identifying expected values includes, for each particular attribute: identifying facts having the attribute, calculating a value score for facts of the collection of facts having the particular attribute for each particular value, calculating a global score for all facts of the collection having the attribute, and comparing the value score to the global score such that a value is identified as an expected value if the comparison satisfies a specified threshold. 6. The method of claim 1 , further comprising determining whether an expected value is a list. | 0.916667 |
8,010,358 | 1 | 12 | 1. A method for voice recognition, the method comprising: obtaining a voice signal; performing two or more voice recognition analyses in parallel on the voice signal, wherein each voice recognition analysis uses a filter bank defined by a different maximum frequency and a different minimum frequency and wherein each voice recognition analysis produces a recognition probability r i of recognition of one or more speech units, whereby there are two or more recognition probabilities r i , wherein each recognition probability r i represents a probability that the voice signal matches a recognized unit of speech, wherein performing the two or more voice recognition analyses in parallel includes performing a first voice recognition analysis on the voice signal based on a first maximum frequency f max and a first minimum frequency f min ; wherein f min and f max are adjusted dynamically during the first voice recognition; and performing one or more additional voice recognition analyses on the voice signal based on a different maximum frequency given by f max ±Δf max and a different minimum frequency given by f min ±Δf min ,where Δf max <f max and Δf min <f min ; and determining a final recognition probability P f based on the two or more recognition probabilities r i ; determining a confidence measure based on the final recognition probability and the two or more recognition probabilities r i ; and using the confidence measure as an acceptance criterion for the final recognition probability P f after determining the final recognition probability P f . | 1. A method for voice recognition, the method comprising: obtaining a voice signal; performing two or more voice recognition analyses in parallel on the voice signal, wherein each voice recognition analysis uses a filter bank defined by a different maximum frequency and a different minimum frequency and wherein each voice recognition analysis produces a recognition probability r i of recognition of one or more speech units, whereby there are two or more recognition probabilities r i , wherein each recognition probability r i represents a probability that the voice signal matches a recognized unit of speech, wherein performing the two or more voice recognition analyses in parallel includes performing a first voice recognition analysis on the voice signal based on a first maximum frequency f max and a first minimum frequency f min ; wherein f min and f max are adjusted dynamically during the first voice recognition; and performing one or more additional voice recognition analyses on the voice signal based on a different maximum frequency given by f max ±Δf max and a different minimum frequency given by f min ±Δf min ,where Δf max <f max and Δf min <f min ; and determining a final recognition probability P f based on the two or more recognition probabilities r i ; determining a confidence measure based on the final recognition probability and the two or more recognition probabilities r i ; and using the confidence measure as an acceptance criterion for the final recognition probability P f after determining the final recognition probability P f . 12. The method of claim 1 wherein performing two or more voice recognition analyses on the voice signal includes performing two or more voice recognition analyses having different speaker category assumptions. | 0.850714 |
9,836,985 | 1 | 3 | 1. A computer-implemented method of measuring a user's English language proficiency, the method comprising: receiving a constructed response generated by a user, the constructed response being based on a picture; parsing the constructed response with a processing system to generate a set of individual words associated with the constructed response; processing the constructed response with the processing system to identify in the constructed response a plurality of multi-word sequences, each multi-word sequence comprising a sequence of two or more adjacent words in the constructed response; processing the constructed response with the processing system to determine a first numerical measure indicative of a presence of one or more grammar errors in the constructed response; processing the set of individual words and a reference corpus with the processing system to determine a second numerical measure indicative of a degree to which the constructed response describes a subject matter of the picture, each word of the set of individual words being compared to individual words of the reference corpus to determine the second numerical measure, the reference corpus having been designated as representative of the subject matter; processing the plurality of multi-word sequences of the constructed response and an n-gram dataset comprising a plurality of entries with the processing system to determine a third numerical measure indicative of a degree of awkward word usage in the constructed response, each of the multi-word sequences of the constructed response being searched across the entries of the n-gram dataset to determine the third numerical measure, wherein each entry of the n-gram dataset includes an English word n-gram and an associated statistical association score, the searching of each multi-word sequence comprising comparing the multi-word sequence of the constructed response to English word n-grams of the n-gram dataset to determine a matching entry of the n-gram dataset, the statistical association score for the matching entry indicating a probability of the multi-word sequence appearing in a well-formed text; and applying a numerical, computer-based scoring model to the first numerical measure, the second numerical measure, and the third numerical measure to automatically determine a score for the constructed response indicative of the user's English language proficiency, the numerical, computer-based scoring model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the second variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. | 1. A computer-implemented method of measuring a user's English language proficiency, the method comprising: receiving a constructed response generated by a user, the constructed response being based on a picture; parsing the constructed response with a processing system to generate a set of individual words associated with the constructed response; processing the constructed response with the processing system to identify in the constructed response a plurality of multi-word sequences, each multi-word sequence comprising a sequence of two or more adjacent words in the constructed response; processing the constructed response with the processing system to determine a first numerical measure indicative of a presence of one or more grammar errors in the constructed response; processing the set of individual words and a reference corpus with the processing system to determine a second numerical measure indicative of a degree to which the constructed response describes a subject matter of the picture, each word of the set of individual words being compared to individual words of the reference corpus to determine the second numerical measure, the reference corpus having been designated as representative of the subject matter; processing the plurality of multi-word sequences of the constructed response and an n-gram dataset comprising a plurality of entries with the processing system to determine a third numerical measure indicative of a degree of awkward word usage in the constructed response, each of the multi-word sequences of the constructed response being searched across the entries of the n-gram dataset to determine the third numerical measure, wherein each entry of the n-gram dataset includes an English word n-gram and an associated statistical association score, the searching of each multi-word sequence comprising comparing the multi-word sequence of the constructed response to English word n-grams of the n-gram dataset to determine a matching entry of the n-gram dataset, the statistical association score for the matching entry indicating a probability of the multi-word sequence appearing in a well-formed text; and applying a numerical, computer-based scoring model to the first numerical measure, the second numerical measure, and the third numerical measure to automatically determine a score for the constructed response indicative of the user's English language proficiency, the numerical, computer-based scoring model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the second variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. 3. The computer-implemented method of claim 1 , wherein the plurality of multiword sequences include adjacent word pairs and adjacent word triples, and wherein the determining of the third numerical measure comprises: determining a Pointwise Mutual Information (PMI) value for each adjacent word pair of the plurality of multi-word sequences, the determining of the PMI value for an adjacent word pair comprising: determining a probability p(AB) of the adjacent word pair appearing in a well-formed text based on the n-gram dataset, determining probabilities p(A) and p(B) of first and second words, respectively, of the adjacent word pair appearing in a well-formed text based on the n-gram dataset, and determining the PMI value for the adjacent word pair based on log 2 p ( AB ) p ( A ) · p ( B ) ; determining a PMI value for each adjacent word triple of the plurality of multi-word sequences, the determining of the PMI value for an adjacent word triple comprising: determining a probability p(A′B′C′) of the adjacent word triple appearing in a wellformed text based on the n-gram dataset, determining probabilities p(A′), p(B′), and p(C′) of first, second, and third words, respectively, of the adjacent word triple appearing in a well-formed text based on the n-gram dataset, and determining the PMI value for the adjacent word triple based on log 2 p ( A ′ B ′ C ′ ) p ( A ′ ) · p ( B ′ ) · p ( C ′ ) ; and processing the PMI values for the adjacent word pairs and the adjacent word triples with the processing system to determine the third numerical measure. | 0.5 |
9,883,136 | 1 | 18 | 1. A method of outputting audio, comprising: progressively downloading a plurality of main audio data sets from a first server and a plurality of associated audio data sets from a second server, wherein the plurality of main audio data sets and the plurality of associated audio data sets are not interleaved on the first server and the second server; storing a multimedia container, wherein the multimedia container includes: the plurality of main audio data sets and the plurality of associated audio data sets, wherein the plurality of main audio data sets and the plurality of associated audio data sets are in a plurality of languages and data elements of the plurality of main audio data sets are interleaved with data elements of the plurality of associated audio data sets in the multimedia container; and synchronization information that synchronizes one of the plurality of main audio data sets and one of the plurality of associated audio data sets; receiving first selection information, wherein the first selection information corresponds to a first language of the plurality of languages; outputting a first audio data stream from the multimedia container after a defined amount of the multimedia container has been progressively downloaded and as the multimedia container is being progressively downloaded, wherein the first audio data stream corresponds to a first main audio data set of the plurality of main audio data sets in the first language; and outputting a second audio data stream from the multimedia container concurrently with outputting the first audio data stream according to the synchronization information, wherein the second audio data stream corresponds to a first associated audio data set of the plurality of associated audio data sets in the first language. | 1. A method of outputting audio, comprising: progressively downloading a plurality of main audio data sets from a first server and a plurality of associated audio data sets from a second server, wherein the plurality of main audio data sets and the plurality of associated audio data sets are not interleaved on the first server and the second server; storing a multimedia container, wherein the multimedia container includes: the plurality of main audio data sets and the plurality of associated audio data sets, wherein the plurality of main audio data sets and the plurality of associated audio data sets are in a plurality of languages and data elements of the plurality of main audio data sets are interleaved with data elements of the plurality of associated audio data sets in the multimedia container; and synchronization information that synchronizes one of the plurality of main audio data sets and one of the plurality of associated audio data sets; receiving first selection information, wherein the first selection information corresponds to a first language of the plurality of languages; outputting a first audio data stream from the multimedia container after a defined amount of the multimedia container has been progressively downloaded and as the multimedia container is being progressively downloaded, wherein the first audio data stream corresponds to a first main audio data set of the plurality of main audio data sets in the first language; and outputting a second audio data stream from the multimedia container concurrently with outputting the first audio data stream according to the synchronization information, wherein the second audio data stream corresponds to a first associated audio data set of the plurality of associated audio data sets in the first language. 18. The method of claim 1 , wherein the data elements of the plurality of main audio data sets and the data elements of the plurality of associated audio data sets are interleaved in the multimedia container according to a physical arrangement wherein a portion of the data elements of the plurality of main audio data sets and a corresponding portion of the data elements of the plurality of associated audio data sets that are to be output synchronously are interleaved before a next portion of video data. | 0.717778 |
8,666,962 | 13 | 20 | 13. One or more non-transitory computer-readable media storing instructions for providing speculative search results, wherein the instructions, when executed by one or more processors, causes: receiving, at a search engine, over a network from a client node, a not-yet-submitted search query provided by a user; in response to receiving at the search engine, from the client node, the not-yet-submitted search query, determining, at the search engine, whether the not-yet-submitted search query meets a criterion for initiating a speculative search for items that satisfy the not-yet-submitted search query; in response to determining, at the search engine, that the not-yet-submitted search query does not meet the criterion, waiting for additional input from the client node without initiating the speculative search for items that satisfy the not-yet-submitted search query; receiving, at the search engine, over the network, from the client node, an updated not-yet-submitted search query that comprises the not-yet-submitted search query and one or more additional characters; in response to receiving, at the search engine, from the client node, the updated not-yet-submitted search query, determining, at the search engine, whether the updated not-yet-submitted search query meets the criterion for initiating a speculative search for items that satisfy the updated not-yet-submitted search query; in response to determining, at the search engine, that the updated not-yet-submitted search query meets the criterion, performing, at the search engine, the speculative search for items that satisfy said updated not-yet-submitted search query prior to receiving, from said client node, an indication that said updated not-yet-submitted search query is completely formed; providing, from the search engine, to said client node, information about to at least one item, found by the speculative search, that satisfies said updated not-yet submitted search query; wherein the at least one item, found by the speculative search, includes at least one of (a) a web page, (b) a graphic, or (c) textual information. | 13. One or more non-transitory computer-readable media storing instructions for providing speculative search results, wherein the instructions, when executed by one or more processors, causes: receiving, at a search engine, over a network from a client node, a not-yet-submitted search query provided by a user; in response to receiving at the search engine, from the client node, the not-yet-submitted search query, determining, at the search engine, whether the not-yet-submitted search query meets a criterion for initiating a speculative search for items that satisfy the not-yet-submitted search query; in response to determining, at the search engine, that the not-yet-submitted search query does not meet the criterion, waiting for additional input from the client node without initiating the speculative search for items that satisfy the not-yet-submitted search query; receiving, at the search engine, over the network, from the client node, an updated not-yet-submitted search query that comprises the not-yet-submitted search query and one or more additional characters; in response to receiving, at the search engine, from the client node, the updated not-yet-submitted search query, determining, at the search engine, whether the updated not-yet-submitted search query meets the criterion for initiating a speculative search for items that satisfy the updated not-yet-submitted search query; in response to determining, at the search engine, that the updated not-yet-submitted search query meets the criterion, performing, at the search engine, the speculative search for items that satisfy said updated not-yet-submitted search query prior to receiving, from said client node, an indication that said updated not-yet-submitted search query is completely formed; providing, from the search engine, to said client node, information about to at least one item, found by the speculative search, that satisfies said updated not-yet submitted search query; wherein the at least one item, found by the speculative search, includes at least one of (a) a web page, (b) a graphic, or (c) textual information. 20. The one or more non-transitory computer-readable media of claim 13 , wherein the instructions, when executed by the one or more processors, further cause: receiving a further portion of said updated not-yet-submitted search query from said client node; determining an updated speculative search result for said further portion prior to receiving an indication from said client node that said updated not-yet-submitted search query is completely formed; and providing said updated speculative search result to said client node, wherein said updated speculative search result identifies at least one item that satisfies said updated not-yet submitted search query. | 0.5 |
8,566,708 | 1 | 6 | 1. A method comprising: displaying, with an online document editing system, a visual representation of an electronic document; receiving an input to affect a modification of the electronic document, the modification comprising two or more document change operations; causing each of the two or more document change operations to be applied to the electronic document; determining, using the online document editing system, a redraw approach for redrawing a portion of the visual representation of the electronic document based on the two or more document change operations, the redraw approach comprising fewer redraws than document change operations; performing a first redraw of the portion of the visual representation of the electronic document based on the redraw approach; tracking all document change operations including the two or more document change operations; receiving undo commands to undo a portion of all of the document change operations after the performing a first redraw, wherein the portion of all of the document change operations is less than all of the document change operations; and performing a second redraw of a portion of the visual representation of the electronic document to implement the undo commands by applying merging rules to reverse a portion of the document change operations, wherein the merging rules provide fewer redraws than the number of undo commands. | 1. A method comprising: displaying, with an online document editing system, a visual representation of an electronic document; receiving an input to affect a modification of the electronic document, the modification comprising two or more document change operations; causing each of the two or more document change operations to be applied to the electronic document; determining, using the online document editing system, a redraw approach for redrawing a portion of the visual representation of the electronic document based on the two or more document change operations, the redraw approach comprising fewer redraws than document change operations; performing a first redraw of the portion of the visual representation of the electronic document based on the redraw approach; tracking all document change operations including the two or more document change operations; receiving undo commands to undo a portion of all of the document change operations after the performing a first redraw, wherein the portion of all of the document change operations is less than all of the document change operations; and performing a second redraw of a portion of the visual representation of the electronic document to implement the undo commands by applying merging rules to reverse a portion of the document change operations, wherein the merging rules provide fewer redraws than the number of undo commands. 6. The method of claim 1 , wherein determining the redraw approach comprises identifying a minimum number of redraws to visually represent the modification of the electronic document. | 0.87751 |
7,559,022 | 15 | 16 | 15. The method according to claim 13 , wherein the rules include giving full access to the file to all by creating a published work. | 15. The method according to claim 13 , wherein the rules include giving full access to the file to all by creating a published work. 16. The method according to claim 15 , wherein upon publishing, the authored work is available via a web page for viewing over the internet. | 0.5 |
10,146,749 | 13 | 16 | 13. An apparatus for dynamically tracking of JavaScript actions in different document object models, the apparatus comprising: a communications fabric; a memory connected to the communications fabric, wherein the memory contains computer executable program code; a communications unit connected to the communications fabric; an input/output unit connected to the communications fabric; a display connected to the communications fabric; and a processor unit connected to the communications fabric, wherein the processor unit executes the computer executable program code to direct the apparatus to: receive a document object model (DOM) representative of a particular page of an application at a particular time; analyze the DOM received to identify each JavaScript action on the particular page; calculate, for each JavaScript action identified, a JavaScript action characteristics ID based on one or more JavaScript action attribute names and one or more respective computed node characteristics identifiers; store to memory, the JavaScript action characteristics ID and associated JavaScript action; determine whether multiple instances of a same JavaScript action exist, using the JavaScript action characteristics ID; responsive to a determination of multiple instances of the same JavaScript action exist, for each of the JavaScript action characteristics ID corresponding to a multiple JavaScript action, collecting a list of the JavaScript actions corresponding to a current JavaScript action characteristics ID; remove from memory, JavaScript action entries for the multiple instances of the same JavaScript action characteristics ID and a same neighbor influence; compute the neighbor influence, for members of the list of JavaScript actions to uniquely distinguish between the JavaScript actions comprising the list of JavaScript actions, wherein the processor unit executes the computer executable program code to compute the neighbor influence for a member of the list of JavaScript actions remaining further directs the apparatus to: identify a node as being the node to which is initiated searching for a closest neighbor that will distinguish between the JavaScript actions; construct a search tree rooted in the node identified using a current DOM tree; use the search tree to perform a breadth first search, until locating a correct element, wherein each time an element is selected, a same path is traversed as in the current DOM tree for all of the JavaScript action entries that are identical to determine whether the element selected uniquely identifies all of the JavaScript action entries that have a same JavaScript action characteristics ID and wherein a stop condition for the breadth first search is one of: completion of traversing the search tree and not locating an element to uniquely identify the JavaScript action entries in which case the JavaScript action entries are considered to be the same; a predefined depth threshold in the search tree is reached in which case the JavaScript action entries are considered to be the same in which case the breadth first search does not proceed; and an element that helps distinguish the JavaScript action entries from each other is located; store to memory, the JavaScript action characteristics ID and the associated JavaScript action wherein the JavaScript action characteristics ID is calculated for the members of the list of JavaScript actions remaining; determine whether there are more multiple JavaScript actions; and responsive to a determination there are no more multiple JavaScript actions, return all of the JavaScript action characteristics ID and the associated JavaScript action stored; receive a second DOM representative of a second particular page of the application at a second particular time; and compare the returned JavaScript action characteristics IDs and the associated JavaScript actions of the first DOM with the JavaScript action characteristics IDs and the associated JavaScript actions of the second DOM and outputting matching JavaScript actions based on the comparison. | 13. An apparatus for dynamically tracking of JavaScript actions in different document object models, the apparatus comprising: a communications fabric; a memory connected to the communications fabric, wherein the memory contains computer executable program code; a communications unit connected to the communications fabric; an input/output unit connected to the communications fabric; a display connected to the communications fabric; and a processor unit connected to the communications fabric, wherein the processor unit executes the computer executable program code to direct the apparatus to: receive a document object model (DOM) representative of a particular page of an application at a particular time; analyze the DOM received to identify each JavaScript action on the particular page; calculate, for each JavaScript action identified, a JavaScript action characteristics ID based on one or more JavaScript action attribute names and one or more respective computed node characteristics identifiers; store to memory, the JavaScript action characteristics ID and associated JavaScript action; determine whether multiple instances of a same JavaScript action exist, using the JavaScript action characteristics ID; responsive to a determination of multiple instances of the same JavaScript action exist, for each of the JavaScript action characteristics ID corresponding to a multiple JavaScript action, collecting a list of the JavaScript actions corresponding to a current JavaScript action characteristics ID; remove from memory, JavaScript action entries for the multiple instances of the same JavaScript action characteristics ID and a same neighbor influence; compute the neighbor influence, for members of the list of JavaScript actions to uniquely distinguish between the JavaScript actions comprising the list of JavaScript actions, wherein the processor unit executes the computer executable program code to compute the neighbor influence for a member of the list of JavaScript actions remaining further directs the apparatus to: identify a node as being the node to which is initiated searching for a closest neighbor that will distinguish between the JavaScript actions; construct a search tree rooted in the node identified using a current DOM tree; use the search tree to perform a breadth first search, until locating a correct element, wherein each time an element is selected, a same path is traversed as in the current DOM tree for all of the JavaScript action entries that are identical to determine whether the element selected uniquely identifies all of the JavaScript action entries that have a same JavaScript action characteristics ID and wherein a stop condition for the breadth first search is one of: completion of traversing the search tree and not locating an element to uniquely identify the JavaScript action entries in which case the JavaScript action entries are considered to be the same; a predefined depth threshold in the search tree is reached in which case the JavaScript action entries are considered to be the same in which case the breadth first search does not proceed; and an element that helps distinguish the JavaScript action entries from each other is located; store to memory, the JavaScript action characteristics ID and the associated JavaScript action wherein the JavaScript action characteristics ID is calculated for the members of the list of JavaScript actions remaining; determine whether there are more multiple JavaScript actions; and responsive to a determination there are no more multiple JavaScript actions, return all of the JavaScript action characteristics ID and the associated JavaScript action stored; receive a second DOM representative of a second particular page of the application at a second particular time; and compare the returned JavaScript action characteristics IDs and the associated JavaScript actions of the first DOM with the JavaScript action characteristics IDs and the associated JavaScript actions of the second DOM and outputting matching JavaScript actions based on the comparison. 16. The apparatus of claim 13 wherein the processor unit executes the computer executable program code to construct a search tree rooted in the node identified using a current DOM tree further directs the apparatus to: generate a binary tree data structure suitable for searching, wherein the binary tree data structure stores data values from an ordered set of data values, derived from the current DOM; and perform an in-order traversal of the tree to visit each of the nodes in ascending order of the stored values. | 0.694935 |
9,699,129 | 1 | 4 | 1. An electronic mail apparatus, comprising: a computing device capable of being connected to a network; and an email productivity module, executed by the computing device, and configured to interact with an existing email application executed by the computing device that sends and receives email messages over the network, wherein the email productivity module includes: a content analysis engine, executed by the computing device, configured to analyze a received email message to generate content information representative of a content of the received email message; a prioritization module, executed by the computing device, having at least one prioritization knowledge base implemented on the computing device, the prioritization module being configured to apply the content information to the at least one prioritization knowledge base to determine at least one priority score for the received email message that reflects a relative priority of the received email message as a legitimate email message and to assign at least one priority level to the received email message based on the priority score that reflects a range of priority scores; a message sorting module, executed by the computing device, having at least one sorting knowledge base implemented on the computing device, the message sorting module being configured to apply the content information to the at least one sorting knowledge base to determine a set of suggested folders for the received email message that represent one or more folders in which are stored other emails having similar content and in which a user would be most likely to store the received email message; and a junkmail module, executed by the computing device, having at least one junkmail knowledge base implemented on the computing device, the junkmail module being configured to apply the content information to the at least one junkmail knowledge base to determine a junkmail score for the received email message that represents a probability that the received email message is junkmail, and the junkmail module being configured to cause a user interface of the existing email application to modify a presentation of the received email message in accordance with the junkmail score; the email productivity module being configured to attach fields for the priority score, priority level, set of suggested folders, and junkmail score to the received email message for display by the existing email application; the email productivity module being configured to receive user feedback to the existing email application indicative of a user action taken with respect to the received email message, and to cause the computing device to adapt the at least one prioritization knowledge base, the at least one sorting database, or the at least one junkmail database, in accordance with the user feedback; wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with explicit user feedback in an event that the user modifies the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display; and wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with implicit user feedback in an event that the user does not modify the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display. | 1. An electronic mail apparatus, comprising: a computing device capable of being connected to a network; and an email productivity module, executed by the computing device, and configured to interact with an existing email application executed by the computing device that sends and receives email messages over the network, wherein the email productivity module includes: a content analysis engine, executed by the computing device, configured to analyze a received email message to generate content information representative of a content of the received email message; a prioritization module, executed by the computing device, having at least one prioritization knowledge base implemented on the computing device, the prioritization module being configured to apply the content information to the at least one prioritization knowledge base to determine at least one priority score for the received email message that reflects a relative priority of the received email message as a legitimate email message and to assign at least one priority level to the received email message based on the priority score that reflects a range of priority scores; a message sorting module, executed by the computing device, having at least one sorting knowledge base implemented on the computing device, the message sorting module being configured to apply the content information to the at least one sorting knowledge base to determine a set of suggested folders for the received email message that represent one or more folders in which are stored other emails having similar content and in which a user would be most likely to store the received email message; and a junkmail module, executed by the computing device, having at least one junkmail knowledge base implemented on the computing device, the junkmail module being configured to apply the content information to the at least one junkmail knowledge base to determine a junkmail score for the received email message that represents a probability that the received email message is junkmail, and the junkmail module being configured to cause a user interface of the existing email application to modify a presentation of the received email message in accordance with the junkmail score; the email productivity module being configured to attach fields for the priority score, priority level, set of suggested folders, and junkmail score to the received email message for display by the existing email application; the email productivity module being configured to receive user feedback to the existing email application indicative of a user action taken with respect to the received email message, and to cause the computing device to adapt the at least one prioritization knowledge base, the at least one sorting database, or the at least one junkmail database, in accordance with the user feedback; wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with explicit user feedback in an event that the user modifies the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display; and wherein the at least one prioritization knowledge base is adapted by the computing device in accordance with implicit user feedback in an event that the user does not modify the at least one priority level or the at least one priority score produced by the prioritization module and attached to the received email message for display. 4. The apparatus of claim 1 , the message sorting module being configured to cause the user interface of the email application to modify the presentation of the received email message to display the suggested folders. | 0.652244 |
7,996,222 | 17 | 20 | 17. A device, comprising: at least one processor; and at least one memory storing machine executable instructions, the machine-executable instructions configured to, with the at least one processor, cause the device to (a) receive data for a plurality of segments of a passage in a source voice, wherein the data for each segment of the plurality models a prosodic component of the source voice for that segment, (b) identify a target voice entry in a codebook for each of the source voice passage segments, wherein each of the identified target voice entries models a prosodic component of a target voice for a different segment of codebook training material, and (c) generate a target voice version of the plurality of passage segments by altering the modeled source voice prosodic component for each segment to replicate the target voice prosodic component modeled by the target voice entry identified for that segment in (b), and wherein the codebook includes multiple source voice entries, each of the multiple source voice entries models a prosodic component of the source voice for a different segment of the codebook training material, each of the multiple source voice entries corresponds to a target voice entry modeling a prosodic component of the target voice for the segment of the codebook training material for which the corresponding source voice entry models the prosodic component of the source voice, operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing data for the source voice passage segment to one or more of the multiple source voice entries, each of the multiple source voice entries and its corresponding target voice entry includes a plurality of transform coefficients representing a contour for the modeled prosodic component, and operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing transform coefficients representing a contour for the prosodic component of the source voice passage segment to the transform coefficients for one or more of the multiple source voice entries. | 17. A device, comprising: at least one processor; and at least one memory storing machine executable instructions, the machine-executable instructions configured to, with the at least one processor, cause the device to (a) receive data for a plurality of segments of a passage in a source voice, wherein the data for each segment of the plurality models a prosodic component of the source voice for that segment, (b) identify a target voice entry in a codebook for each of the source voice passage segments, wherein each of the identified target voice entries models a prosodic component of a target voice for a different segment of codebook training material, and (c) generate a target voice version of the plurality of passage segments by altering the modeled source voice prosodic component for each segment to replicate the target voice prosodic component modeled by the target voice entry identified for that segment in (b), and wherein the codebook includes multiple source voice entries, each of the multiple source voice entries models a prosodic component of the source voice for a different segment of the codebook training material, each of the multiple source voice entries corresponds to a target voice entry modeling a prosodic component of the target voice for the segment of the codebook training material for which the corresponding source voice entry models the prosodic component of the source voice, operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing data for the source voice passage segment to one or more of the multiple source voice entries, each of the multiple source voice entries and its corresponding target voice entry includes a plurality of transform coefficients representing a contour for the modeled prosodic component, and operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing transform coefficients representing a contour for the prosodic component of the source voice passage segment to the transform coefficients for one or more of the multiple source voice entries. 20. The device of claim 17 , wherein the modeled prosodic components are pitch contours. | 0.95884 |
8,812,531 | 8 | 12 | 8. A method comprising: by one or more computing devices, deriving a concept matrix from a plurality of sample documents using singular value decomposition of a term-document matrix, the concept matrix identifying a latent pattern of word usage in the plurality of sample documents around a concept; by the one or more computing devices, deriving concept terms by extracting significant terms from search text and inferring relevant terms from said significant terms in accordance with the concept matrix; and by the one or more computing devices, generating a query comprising a search expression having at least one of the derived concept terms. | 8. A method comprising: by one or more computing devices, deriving a concept matrix from a plurality of sample documents using singular value decomposition of a term-document matrix, the concept matrix identifying a latent pattern of word usage in the plurality of sample documents around a concept; by the one or more computing devices, deriving concept terms by extracting significant terms from search text and inferring relevant terms from said significant terms in accordance with the concept matrix; and by the one or more computing devices, generating a query comprising a search expression having at least one of the derived concept terms. 12. The method as recited in claim 8 wherein said query conforms to a Boolean expression. | 0.701342 |
7,734,622 | 1 | 6 | 1. A machine-implemented browsing method, comprising: performing a context search based on information associated with at least one media object, wherein the performing of the context search comprises searching a first database of indexed references to web pages and other documents based on search criteria derived from information extracted from the at least one media object, wherein the performing of the context search further comprises generating a context search query from information associated with the at least one media object, transmitting the context search query to a first search engine operable to query the first database in response to receipt of the context search query, and receiving a first search response from the first search engine; performing a context-sensitive search based on results of the context search, wherein the performing of the context-sensitive search comprises searching a second database of indexed references to web pages and other documents based on search criteria derived from the results of the context search, wherein the performing of the context-sensitive search further comprises generating a context-sensitive search query from the first search response, transmitting the context-sensitive search query to a second search engine operable to query the second database in response to receipt of the context-sensitive search query, and receiving a second search response from the second search engine; and presenting information derived from results of the context-sensitive search. | 1. A machine-implemented browsing method, comprising: performing a context search based on information associated with at least one media object, wherein the performing of the context search comprises searching a first database of indexed references to web pages and other documents based on search criteria derived from information extracted from the at least one media object, wherein the performing of the context search further comprises generating a context search query from information associated with the at least one media object, transmitting the context search query to a first search engine operable to query the first database in response to receipt of the context search query, and receiving a first search response from the first search engine; performing a context-sensitive search based on results of the context search, wherein the performing of the context-sensitive search comprises searching a second database of indexed references to web pages and other documents based on search criteria derived from the results of the context search, wherein the performing of the context-sensitive search further comprises generating a context-sensitive search query from the first search response, transmitting the context-sensitive search query to a second search engine operable to query the second database in response to receipt of the context-sensitive search query, and receiving a second search response from the second search engine; and presenting information derived from results of the context-sensitive search. 6. The method of claim 1 , wherein generating the context-sensitive search query comprises extracting one or more search criteria of the context-sensitive search query from the first search response. | 0.5 |
7,904,461 | 1 | 2 | 1. A method implemented by a computer system, the method comprising: generating, by the computer system, a set of content-based keywords based on content generated by users of a social network, wherein users are represented by nodes in a graph that represents the social network; labeling, by the computer system, nodes comprising the user nodes with advertising labels comprising content-based keywords from the set of content-based keywords that coincide with advertiser-selected keywords, wherein the advertiser-selected keywords are based on one or more terms specified by an advertiser; and outputting, by the computer system for each respective node, weights for the advertising labels which are determined from weights of the advertising labels associated with neighboring nodes that are related to the respective node by a relationship, each weight expressing a magnitude of a contribution of an associated advertising label to a characterization of the respective node. | 1. A method implemented by a computer system, the method comprising: generating, by the computer system, a set of content-based keywords based on content generated by users of a social network, wherein users are represented by nodes in a graph that represents the social network; labeling, by the computer system, nodes comprising the user nodes with advertising labels comprising content-based keywords from the set of content-based keywords that coincide with advertiser-selected keywords, wherein the advertiser-selected keywords are based on one or more terms specified by an advertiser; and outputting, by the computer system for each respective node, weights for the advertising labels which are determined from weights of the advertising labels associated with neighboring nodes that are related to the respective node by a relationship, each weight expressing a magnitude of a contribution of an associated advertising label to a characterization of the respective node. 2. The method of claim 1 , wherein the relationship is a social relationship. | 0.885075 |
5,465,304 | 9 | 11 | 9. A method for reducing an amount of data needed for segmenting the features of a document image, said document image having a bit mapped representation, said method comprising the steps of: a) accessing said bit mapped representation, said bit mapped representation having a plurality of scanlines; b) examining a set of corresponding bytes of a set of N scanlines of said plurality of scanlines; c) assigning a first value to a corresponding bit in a temporary compressed scanline, if any bits of said set of corresponding bytes has said first value; d) assigning a second value to said corresponding bit, if none of said bits of said set of corresponding bytes has said first value; and e) generating a set of compressed scanlines by assigning said first value or said second value to each bit of a corresponding byte of a corresponding compressed scanline according to the following rules: assigning all bits in a corresponding byte of a compressed scanline to said first value if any bits in a corresponding byte in said temporary compressed scanline have said first value; and assigning all bits in a corresponding byte of a compressed scanline to said second value if no bits in said corresponding byte in said temporary compressed scanline have said first value; f) extracting a plurality of run lengths from said set of compressed scanlines; and g) constructing a plurality of rectangles from said plurality of run lengths, said plurality of rectangles representing features of said document image. | 9. A method for reducing an amount of data needed for segmenting the features of a document image, said document image having a bit mapped representation, said method comprising the steps of: a) accessing said bit mapped representation, said bit mapped representation having a plurality of scanlines; b) examining a set of corresponding bytes of a set of N scanlines of said plurality of scanlines; c) assigning a first value to a corresponding bit in a temporary compressed scanline, if any bits of said set of corresponding bytes has said first value; d) assigning a second value to said corresponding bit, if none of said bits of said set of corresponding bytes has said first value; and e) generating a set of compressed scanlines by assigning said first value or said second value to each bit of a corresponding byte of a corresponding compressed scanline according to the following rules: assigning all bits in a corresponding byte of a compressed scanline to said first value if any bits in a corresponding byte in said temporary compressed scanline have said first value; and assigning all bits in a corresponding byte of a compressed scanline to said second value if no bits in said corresponding byte in said temporary compressed scanline have said first value; f) extracting a plurality of run lengths from said set of compressed scanlines; and g) constructing a plurality of rectangles from said plurality of run lengths, said plurality of rectangles representing features of said document image. 11. The method of claim 9 wherein said first value is a non-zero value and said second value is a zero value. | 0.942021 |
7,729,595 | 12 | 14 | 12. An apparatus for recording a data structure for managing reproduction of text data on a recording medium, comprising: a pickup configured to record data on the recording medium; and a controller configured to control the pickup to record at least one main audio-visual (AV) data and at least one subtitle information segment on the recording medium, each subtitle information segment being represented by each PES packet of transport packets and having a one-to-one correspondence with the PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein the at least one subtitle information segment includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment of the at least one subtitle information segment identified as the text data includes a palette identifier identifying palette information for controlling color attributes of the text data, and wherein a second subtitle information segment of the at least one subtitle information segment identified as the text data includes at most two text subtitle regions, and each text subtitle region is linked to at least one first style information defined in the first subtitle information segment using identifier, wherein the second subtitle information segment of the at least one subtitle information segment identified as the text data includes second style information for managing reproduction of the text data by the reproducing device, and wherein a third subtitle information segment of the at least one subtitle information segment identified as the graphic data is multiplexed with the at least one main AV data into a file. | 12. An apparatus for recording a data structure for managing reproduction of text data on a recording medium, comprising: a pickup configured to record data on the recording medium; and a controller configured to control the pickup to record at least one main audio-visual (AV) data and at least one subtitle information segment on the recording medium, each subtitle information segment being represented by each PES packet of transport packets and having a one-to-one correspondence with the PES packet, the PES packet including a packet identifier for identifying a type of the packet, wherein the at least one subtitle information segment includes a segment identifier identifying the subtitle information segment as one of text data and graphic data, wherein a first subtitle information segment of the at least one subtitle information segment identified as the text data includes a palette identifier identifying palette information for controlling color attributes of the text data, and wherein a second subtitle information segment of the at least one subtitle information segment identified as the text data includes at most two text subtitle regions, and each text subtitle region is linked to at least one first style information defined in the first subtitle information segment using identifier, wherein the second subtitle information segment of the at least one subtitle information segment identified as the text data includes second style information for managing reproduction of the text data by the reproducing device, and wherein a third subtitle information segment of the at least one subtitle information segment identified as the graphic data is multiplexed with the at least one main AV data into a file. 14. The apparatus of claim 12 , wherein the controller is configured to control the pickup to record the style information indicating at least one of font size, font style and font set for the text data. | 0.686728 |
10,095,683 | 29 | 30 | 29. The system of claim 20 , wherein the instructions to calculate the relevance-score for each unique combination based at least in part on the contextual speller model further comprise instructions to: modify the calculated relevance-score of each unique combination comprising an n-gram having a frequency of use in the personal language model different from a frequency of use in the standard language model greater than a threshold frequency of use. | 29. The system of claim 20 , wherein the instructions to calculate the relevance-score for each unique combination based at least in part on the contextual speller model further comprise instructions to: modify the calculated relevance-score of each unique combination comprising an n-gram having a frequency of use in the personal language model different from a frequency of use in the standard language model greater than a threshold frequency of use. 30. The system of claim 29 , wherein the instructions to modify the calculated relevance-score of each unique combination comprising the n-gram having the frequency of use in the personal language model different from the frequency of use in the standard language model greater than the threshold frequency of use further comprise instructions to: increase a probability of the n-gram appearing in the search query, the n-gram having the frequency of use in the personal language model different from the frequency of use in the standard language model greater than or equal to the threshold frequency of use; or decrease the probability of the n-gram appearing in the search query, the n-gram having the frequency of use in the personal language model different from the frequency of use in the standard language model less than the threshold frequency of use. | 0.5 |
8,001,106 | 3 | 4 | 3. The method of claim 1 , wherein step (d) comprises using heuristic rules to group the set of deep tokens appearing in the set of current tokens. | 3. The method of claim 1 , wherein step (d) comprises using heuristic rules to group the set of deep tokens appearing in the set of current tokens. 4. The method of claim 3 , wherein using the heuristic rules comprises considering a type of deep token. | 0.723404 |
8,620,686 | 1 | 8 | 1. A computer assisted method for accelerated planning and dynamic graphical mapping of a contextual awareness and creating an integrated composite decision plan using a plurality of client devices, an administrative processor and an administrative data storage connected to a network, and a plurality of computer instructions, the computer assisted method comprising: a. using an administrative data storage connected to an administrative processor and a network, and a plurality of client devices wherein the client devices are selected from the group: a cell phone, a laptop, a computer, and a tablet, to provide input when connected to the network to enable the administrative processor to perform a computer assisted geospatial analysis and create an integrated composite decision plan; b. using computer instructions in the administrative data storage to instruct the administrative processor to create a system interface; wherein the computer instructions simultaneously connect together the plurality of client devices, and a third party provider via the network to computer instructions in the administrative data storage using the administrative processor to register a client device and provide a system interface to request and store data from the third party provider; c. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the system interface to instruct the administrative processor to identify a contextual awareness; wherein the computer instructions identify the contextual awareness using key words, classification codes, and priority codes, and computer instructions that list situational awareness linked to the key word, classification code, and priority codes using a library of contextual awareness stored in the administrative data storage; d. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the client devices to instruct the administrative processor to collect raw data on the contextual awareness; wherein the computer instructions to collect the raw data comprise information from a member of the group: transportation facilities, health care facilities, first responder facilities, educational facilities, and combinations thereof; e. using computer instructions in the administrative data storage to instruct the administrative processor to store the collected raw data in the administrative data storage linked to the identified contextual awareness using the plurality of client devices in a plurality of client device protocols simultaneously; and f. using computer instructions in the administrative data storage to instruct the administrative processor to perform geospatial analysis on the collected raw data for the identified contextual awareness using the library of contextual awareness; wherein the computer instructions to perform the geospatial analysis consist of: (i) computer instructions to instruct the administrative processor to request compliance standards from a third party provider via the network for the identified contextual awareness, wherein the compliance standards from the third party provider are in a dynamic electronic library of searchable fields including best practices for a contextual awareness, materials specification standards for the contextual awareness, government standards for the contextual awareness from codes of federal regulation, government standards for the contextual awareness from other state, municipal, regulations, and community promulgated standards for the contextual awareness; (ii) computer instructions to instruct the administrative processor to form data specifications to achieve contextual awareness compliance for the identified contextual awareness wherein the computer instructions provide a projection of need for a geographic area for over a defined period of time for the identified contextual awareness using a projected use for facilities, equipment, disposable materials, personnel, transportation and related resources related to the identified contextual awareness; (iii) computer instructions to instruct the administrative processor to match the collected raw data to the data specifications for compliance enabling the identification of a location specific to existing facilities, existing equipment, existing disposable materials, existing personnel, existing transportation, and existing other related resources related to the identified contextual awareness for use in achieving contextual awareness compliance with the data specifications; (iv) computer instructions to instruct the administrative processor to perform data standardization, data checking, and data correction on the collected raw data to form cleaned data; and (v) computer instructions to instruct the administrative processor to use the cleaned data with the data specifications for compliance to calculate quantity of facilities needed and type of facilities needed, for the geographic area given the identified contextual awareness, quantity of equipment needed, quantity of disposable materials needed, quantity of personnel needed, and transportation needed for the geographic area, to meet data specifications for compliance for the identified contextual awareness; wherein the calculations are determined using computer instructions that calculate predictive dynamic decision plan modeling for the identified contextual awareness consisting of: a. computer instructions to instruct the administrative processor to identify single data points from the cleaned data for the geographic area; b. computer instructions to instruct the administrative processor to identify multiple internal data points from the cleaned data, wherein the multiple data points include geo-demographic zones, geographic zones, and zones formed using geographic spatial relationships; c. computer instructions to instruct the administrative processor to identify patterns of contextual awareness from the cleaned data wherein the patterns consist of concentrations of different contextual awareness, quantities of contextual awareness, and prevalence of contextual awareness by the geographic area; d. computer instructions to instruct the administrative processor to identify recurrences over time of the patterns of contextual awareness, wherein the recurrences of contextual awareness over time consist of: (a) frequency of contextual awareness, (b) duration of contextual awareness, and (c) past, present or future direction of events related to contextual awareness; e. computer instructions to instruct the administrative processor to perform issue disassembly and reassembly over time analysis; f. computer instructions to instruct the administrative processor to identify stakeholders which interact with one of the identified contextual awareness; g. computer instructions to instruct the administrative processor to sort contextual awarenesses chronologically to identify external issues related to contextual awareness compliance, using the library of contextual awareness in the administrative data storage; h. computer instructions to instruct the administrative processor to produce visual outputs from the administrative data storage to display predictive trends and patterns for the contextual awareness compliance using the cleaned data; i. computer instructions to instruct the administrative processor to transmit to stakeholders for collaborative decision making: tasks to reach contextual awareness compliance for each contextual awareness; and to identify resources required for tasks to reach contextual awareness compliance for each contextual awareness; and j. computer instructions to instruct the administrative processor to enable the stakeholders to create an integrated, composite decision plan with geographically sorted and prioritized actions identified by task, by quantity of the stakeholders needed, and by the resources needed to achieve contextual awareness compliance creating an integrated composite decision plan for: geographically defined facilities, equipment, disposable materials, personnel, and transportation. | 1. A computer assisted method for accelerated planning and dynamic graphical mapping of a contextual awareness and creating an integrated composite decision plan using a plurality of client devices, an administrative processor and an administrative data storage connected to a network, and a plurality of computer instructions, the computer assisted method comprising: a. using an administrative data storage connected to an administrative processor and a network, and a plurality of client devices wherein the client devices are selected from the group: a cell phone, a laptop, a computer, and a tablet, to provide input when connected to the network to enable the administrative processor to perform a computer assisted geospatial analysis and create an integrated composite decision plan; b. using computer instructions in the administrative data storage to instruct the administrative processor to create a system interface; wherein the computer instructions simultaneously connect together the plurality of client devices, and a third party provider via the network to computer instructions in the administrative data storage using the administrative processor to register a client device and provide a system interface to request and store data from the third party provider; c. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the system interface to instruct the administrative processor to identify a contextual awareness; wherein the computer instructions identify the contextual awareness using key words, classification codes, and priority codes, and computer instructions that list situational awareness linked to the key word, classification code, and priority codes using a library of contextual awareness stored in the administrative data storage; d. using computer instructions in the administrative data storage to instruct the administrative processor and computer instructions in the client devices to instruct the administrative processor to collect raw data on the contextual awareness; wherein the computer instructions to collect the raw data comprise information from a member of the group: transportation facilities, health care facilities, first responder facilities, educational facilities, and combinations thereof; e. using computer instructions in the administrative data storage to instruct the administrative processor to store the collected raw data in the administrative data storage linked to the identified contextual awareness using the plurality of client devices in a plurality of client device protocols simultaneously; and f. using computer instructions in the administrative data storage to instruct the administrative processor to perform geospatial analysis on the collected raw data for the identified contextual awareness using the library of contextual awareness; wherein the computer instructions to perform the geospatial analysis consist of: (i) computer instructions to instruct the administrative processor to request compliance standards from a third party provider via the network for the identified contextual awareness, wherein the compliance standards from the third party provider are in a dynamic electronic library of searchable fields including best practices for a contextual awareness, materials specification standards for the contextual awareness, government standards for the contextual awareness from codes of federal regulation, government standards for the contextual awareness from other state, municipal, regulations, and community promulgated standards for the contextual awareness; (ii) computer instructions to instruct the administrative processor to form data specifications to achieve contextual awareness compliance for the identified contextual awareness wherein the computer instructions provide a projection of need for a geographic area for over a defined period of time for the identified contextual awareness using a projected use for facilities, equipment, disposable materials, personnel, transportation and related resources related to the identified contextual awareness; (iii) computer instructions to instruct the administrative processor to match the collected raw data to the data specifications for compliance enabling the identification of a location specific to existing facilities, existing equipment, existing disposable materials, existing personnel, existing transportation, and existing other related resources related to the identified contextual awareness for use in achieving contextual awareness compliance with the data specifications; (iv) computer instructions to instruct the administrative processor to perform data standardization, data checking, and data correction on the collected raw data to form cleaned data; and (v) computer instructions to instruct the administrative processor to use the cleaned data with the data specifications for compliance to calculate quantity of facilities needed and type of facilities needed, for the geographic area given the identified contextual awareness, quantity of equipment needed, quantity of disposable materials needed, quantity of personnel needed, and transportation needed for the geographic area, to meet data specifications for compliance for the identified contextual awareness; wherein the calculations are determined using computer instructions that calculate predictive dynamic decision plan modeling for the identified contextual awareness consisting of: a. computer instructions to instruct the administrative processor to identify single data points from the cleaned data for the geographic area; b. computer instructions to instruct the administrative processor to identify multiple internal data points from the cleaned data, wherein the multiple data points include geo-demographic zones, geographic zones, and zones formed using geographic spatial relationships; c. computer instructions to instruct the administrative processor to identify patterns of contextual awareness from the cleaned data wherein the patterns consist of concentrations of different contextual awareness, quantities of contextual awareness, and prevalence of contextual awareness by the geographic area; d. computer instructions to instruct the administrative processor to identify recurrences over time of the patterns of contextual awareness, wherein the recurrences of contextual awareness over time consist of: (a) frequency of contextual awareness, (b) duration of contextual awareness, and (c) past, present or future direction of events related to contextual awareness; e. computer instructions to instruct the administrative processor to perform issue disassembly and reassembly over time analysis; f. computer instructions to instruct the administrative processor to identify stakeholders which interact with one of the identified contextual awareness; g. computer instructions to instruct the administrative processor to sort contextual awarenesses chronologically to identify external issues related to contextual awareness compliance, using the library of contextual awareness in the administrative data storage; h. computer instructions to instruct the administrative processor to produce visual outputs from the administrative data storage to display predictive trends and patterns for the contextual awareness compliance using the cleaned data; i. computer instructions to instruct the administrative processor to transmit to stakeholders for collaborative decision making: tasks to reach contextual awareness compliance for each contextual awareness; and to identify resources required for tasks to reach contextual awareness compliance for each contextual awareness; and j. computer instructions to instruct the administrative processor to enable the stakeholders to create an integrated, composite decision plan with geographically sorted and prioritized actions identified by task, by quantity of the stakeholders needed, and by the resources needed to achieve contextual awareness compliance creating an integrated composite decision plan for: geographically defined facilities, equipment, disposable materials, personnel, and transportation. 8. The method of claim 1 , wherein the computer instructions that list situational awareness use situational awarenesses from the library of contextual awareness which are economic awarenesses. | 0.779176 |
9,239,710 | 19 | 21 | 19. The method of claim 11 , wherein the transforming includes subjecting the at least one rule of the rules set to a condition. | 19. The method of claim 11 , wherein the transforming includes subjecting the at least one rule of the rules set to a condition. 21. The method of claim 19 , wherein the condition is any one of a set of: selection of a rule of the rules set by a user; and selection of a rule from a state of the abstract syntax tree. | 0.5 |
8,645,248 | 1 | 21 | 1. An integrated customer communications computer system, comprising: at least one computer database; and a communications computer system, in communication with said at least one database and at least one component of an account opening system, and configured to provide outbound customer communications, wherein the communications computer system generates documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from said at least one component of the account opening system, and static content for the templates received from a content repository, and wherein the communications computer system includes: a communication manager, comprising: a communication controller receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; a document manager managing documents associated with the communications; and a communication history component maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; a plurality of transmission channels for transmitting the communications; an interface for managing the templates and the content; and a document repository storing, retrieving, and managing storage of the documents wherein the interface for managing the templates is configured to provide a user functionality to create, preview, edit, maintain and delete communication templates for different channels, define what data items are included in the communication, insert dynamic variables that vary by at least one of channel and communication type, define a source of the dynamic data for the communication, and make deployments to various environments for validation. | 1. An integrated customer communications computer system, comprising: at least one computer database; and a communications computer system, in communication with said at least one database and at least one component of an account opening system, and configured to provide outbound customer communications, wherein the communications computer system generates documents associated with the communications in a predefined format, in real-time or in batch, by merging templates comprising static data received from a template repository, dynamic data received from said at least one component of the account opening system, and static content for the templates received from a content repository, and wherein the communications computer system includes: a communication manager, comprising: a communication controller receiving, recording, sending, and processing at least one of communication requests and history requests from the at least one component of the account opening system, and transmitting communications responsive thereto; a document manager managing documents associated with the communications; and a communication history component maintaining a record of the communications transmitted, including at least one of date, time, channel, and content, and saving the record to a communication history database; a plurality of transmission channels for transmitting the communications; an interface for managing the templates and the content; and a document repository storing, retrieving, and managing storage of the documents wherein the interface for managing the templates is configured to provide a user functionality to create, preview, edit, maintain and delete communication templates for different channels, define what data items are included in the communication, insert dynamic variables that vary by at least one of channel and communication type, define a source of the dynamic data for the communication, and make deployments to various environments for validation. 21. The integrated customer communications computer system of claim 1 , wherein the communication requests comprise information regarding what documents are to be sent, the dynamic data required to generate the documents, the document formats, the delivery channels, and the data required by the delivery channels. | 0.823991 |
8,862,250 | 8 | 9 | 8. The method of claim 1 , wherein the step of applying the rule-based expert system comprises evaluating the set of rules in a sequence such that rules whose conditional premises are fully known are evaluated before the rules whose conditional premises are not fully known. | 8. The method of claim 1 , wherein the step of applying the rule-based expert system comprises evaluating the set of rules in a sequence such that rules whose conditional premises are fully known are evaluated before the rules whose conditional premises are not fully known. 9. The method of claim 8 , wherein the set of rules includes a first rule and a second rule that relies on a conclusion of the first rule, and wherein the first rule is evaluated before the second rule. | 0.5 |
8,645,815 | 6 | 8 | 6. A GUI evaluation method, implemented by a processor, comprising: grouping prerecorded headings included in each evaluation target screen by expression used for the headings in accordance with the GUI information including information indicative of a heading expression which is the expression used for the heading; and evaluating a consistency of the heading expressions between a plurality of evaluation target screens by comparing heading groups that are grouped according to the expressions and included in all possible combinations of two of the plurality of evaluation target screens. | 6. A GUI evaluation method, implemented by a processor, comprising: grouping prerecorded headings included in each evaluation target screen by expression used for the headings in accordance with the GUI information including information indicative of a heading expression which is the expression used for the heading; and evaluating a consistency of the heading expressions between a plurality of evaluation target screens by comparing heading groups that are grouped according to the expressions and included in all possible combinations of two of the plurality of evaluation target screens. 8. The GUI evaluation method according to claim 6 , implemented by a processor, further comprising: achieving grouping by specifying headings that are included in an evaluation target screen and agree with each other in the employed expression and in either the vertical or horizontal on-screen position, as members of the same heading group, in accordance with GUI information that concerns the heading included in the evaluation target screen and includes information indicative of a heading expression for the heading and information indicative of an on-screen position of the heading. | 0.640587 |
8,908,970 | 1 | 5 | 1. A method for extracting textual information from a document containing text characters using a digital image capture device, comprising: capturing a plurality of digital images of the document using the digital image capture device, wherein all of the digital images include a same document region of the document; automatically analyzing each of the captured digital images using an optical character recognition process to determine extracted textual data for the same document region in each captured digital image; merging the extracted textual data from the plurality of captured digital images to determine the textual information for the document, wherein differences between the extracted textual data for the same document region in the plurality of captured digital images are analyzed to determine the textual information for the document region; wherein the merging of the extracted textual data for the captured digital images includes: analyzing the extracted textual data for the captured digital images to determine corresponding portions of the textual data for the captured digital images, wherein the corresponding portions correspond to the same text characters in the document; analyzing the extracted textual data to identify portions of the textual data for the plurality of captured digital images where the textual data extracted from at least one of the captured digital images is different from the textual data extracted from the corresponding portion of another one of the captured digital images; analyzing the differences between extracted textual data for the captured digital images to determine a corresponding portion of the textual information for the document; and wherein the method is performed, at least in part, using a data processor. | 1. A method for extracting textual information from a document containing text characters using a digital image capture device, comprising: capturing a plurality of digital images of the document using the digital image capture device, wherein all of the digital images include a same document region of the document; automatically analyzing each of the captured digital images using an optical character recognition process to determine extracted textual data for the same document region in each captured digital image; merging the extracted textual data from the plurality of captured digital images to determine the textual information for the document, wherein differences between the extracted textual data for the same document region in the plurality of captured digital images are analyzed to determine the textual information for the document region; wherein the merging of the extracted textual data for the captured digital images includes: analyzing the extracted textual data for the captured digital images to determine corresponding portions of the textual data for the captured digital images, wherein the corresponding portions correspond to the same text characters in the document; analyzing the extracted textual data to identify portions of the textual data for the plurality of captured digital images where the textual data extracted from at least one of the captured digital images is different from the textual data extracted from the corresponding portion of another one of the captured digital images; analyzing the differences between extracted textual data for the captured digital images to determine a corresponding portion of the textual information for the document; and wherein the method is performed, at least in part, using a data processor. 5. The method of claim 1 , wherein the analysis to determine the textual information for the document region includes comparing the extracted textual data for the captured digital images to a dictionary. | 0.684783 |
8,731,819 | 1 | 6 | 1. A method of identifying and associating individuals comprising: providing a first set of records associated with one or more individuals at a defined geographic location and a defined period of time; providing a second set of records associated with one or more individuals across multiple geographic locations and defined time periods; a user selecting both a desired demarcated area of the Earth and a desired date range on a computing device; on the computing device, identifying a set of individuals corresponding to the selected demarcated area of the Earth and the desired date range, and associating relationships among the set of identified individuals who previously had no identified relationships in the first and second sets of records corresponding to the demarcated area of the Earth and the desired date range; and outputting to the user by displaying on a monitor of the computing device results of the associated relationships among the set of identified individuals to provide the user with results of known and probable relationships in the defined geographic location over the defined period of time. | 1. A method of identifying and associating individuals comprising: providing a first set of records associated with one or more individuals at a defined geographic location and a defined period of time; providing a second set of records associated with one or more individuals across multiple geographic locations and defined time periods; a user selecting both a desired demarcated area of the Earth and a desired date range on a computing device; on the computing device, identifying a set of individuals corresponding to the selected demarcated area of the Earth and the desired date range, and associating relationships among the set of identified individuals who previously had no identified relationships in the first and second sets of records corresponding to the demarcated area of the Earth and the desired date range; and outputting to the user by displaying on a monitor of the computing device results of the associated relationships among the set of identified individuals to provide the user with results of known and probable relationships in the defined geographic location over the defined period of time. 6. The method of claim 1 wherein the first or second set of records includes identification of location of origin of an individual and wherein the returned, identified set of individuals are in contemporaneous geospatial proximity, and further including identifying the preponderance of the location of origin of the returned, identified set of individuals, and using the preponderance of the location of origin of the returned, identified set of individuals to associate the location of origin relationships among the set of returned individuals who previously had no identified location of origin relationships in the first and second sets of records. | 0.810285 |
9,910,567 | 11 | 14 | 11. The non-transitory computer-readable medium of claim 8 , wherein the first user interface gadget contains a reference to a respective behavior definition that defines the first trigger event condition and a script to perform the first action on the first user interface gadget. | 11. The non-transitory computer-readable medium of claim 8 , wherein the first user interface gadget contains a reference to a respective behavior definition that defines the first trigger event condition and a script to perform the first action on the first user interface gadget. 14. The non-transitory computer-readable medium of claim 11 , wherein initiating further comprises: detecting conflicting behavior definitions of the first user interface gadget; and in response to the conflicting behavior definitions including a reference to a tag associated with a behavior definition, initiating an action based on the behavior definition associated with the tag. | 0.5 |
8,838,562 | 18 | 19 | 18. The apparatus of claim 17 , wherein the query creation unit comprises: a conversion unit to convert the search data into the textual search data; and a text unit to convert the textual search data into the created query. | 18. The apparatus of claim 17 , wherein the query creation unit comprises: a conversion unit to convert the search data into the textual search data; and a text unit to convert the textual search data into the created query. 19. The apparatus of claim 18 , wherein the conversion unit uses optical character recognition to convert the search data into the textual search data. | 0.5 |
10,074,361 | 27 | 38 | 27. A speech recognition apparatus, the apparatus comprising: a processor configured to: identify select frames from all frames of a first speech of a user; calculate respective acoustic scores of the identified select frames by providing information of the identified select frames, less than all frames of the first speech, to an acoustic model as combined speech to calculate the respective acoustic scores of the identified select frames; calculate respective acoustic scores of frames, of the first speech, other than the identified select frames based on one or more of the calculated respective scores of the identified select frames; and recognize the first speech based on the calculated respective acoustic scores of the identified select frames and the calculated respective acoustic scores of the frames other than the identified select frames. | 27. A speech recognition apparatus, the apparatus comprising: a processor configured to: identify select frames from all frames of a first speech of a user; calculate respective acoustic scores of the identified select frames by providing information of the identified select frames, less than all frames of the first speech, to an acoustic model as combined speech to calculate the respective acoustic scores of the identified select frames; calculate respective acoustic scores of frames, of the first speech, other than the identified select frames based on one or more of the calculated respective scores of the identified select frames; and recognize the first speech based on the calculated respective acoustic scores of the identified select frames and the calculated respective acoustic scores of the frames other than the identified select frames. 38. The speech recognition apparatus of claim 27 , further comprising a memory configured to store instructions, wherein the processor is further configured to execute the instructions to configure the processor to perform the identifying of the select frames, calculating of the respective acoustic scores of the identified select frames, and calculating of the respective acoustic score of the frames other than the identified select frames. | 0.502247 |
6,119,114 | 25 | 26 | 25. The system of claim 23 further comprising: means for determining, on the basis of said absolute-relevance score of said newly-received document and said first collective absolute relevance, whether to replace said first set of training data by a second set of training data formed by adding said newly-received document to said first set of training data. | 25. The system of claim 23 further comprising: means for determining, on the basis of said absolute-relevance score of said newly-received document and said first collective absolute relevance, whether to replace said first set of training data by a second set of training data formed by adding said newly-received document to said first set of training data. 26. The system of claim 25 wherein said means for determining whether to replace said first set of training data comprises means for including said newly-received document in said first set of training data to create a second set of training data having a second collective absolute relevance higher than said first collective absolute relevance. | 0.819415 |
10,114,862 | 1 | 5 | 1. A system, comprising: a processor; and a non-transitory computer memory storing a program, which, when executed on the processor, performs an operation for suggesting a search query based on terms, the operation comprising: receiving a search query having at least a first term; identifying a plurality of related terms having a relationship to the first term, based on prior search queries; determining to ignore a first related term of the plurality of related terms, based on the first related term having not been observed with the first term over a specified time interval; and generating a plurality of predictive suggestions for completing the search query, wherein none of the plurality of predictive suggestions includes the ignored first related term, wherein a first of the plurality of predictive suggestions includes at least the first term, and wherein a second of the plurality of predictive suggestions includes an identified semantic equivalent of the first term and a second related term of the plurality of related terms, wherein the identified semantic equivalent is synonymous with the first term. | 1. A system, comprising: a processor; and a non-transitory computer memory storing a program, which, when executed on the processor, performs an operation for suggesting a search query based on terms, the operation comprising: receiving a search query having at least a first term; identifying a plurality of related terms having a relationship to the first term, based on prior search queries; determining to ignore a first related term of the plurality of related terms, based on the first related term having not been observed with the first term over a specified time interval; and generating a plurality of predictive suggestions for completing the search query, wherein none of the plurality of predictive suggestions includes the ignored first related term, wherein a first of the plurality of predictive suggestions includes at least the first term, and wherein a second of the plurality of predictive suggestions includes an identified semantic equivalent of the first term and a second related term of the plurality of related terms, wherein the identified semantic equivalent is synonymous with the first term. 5. The system of claim 1 , wherein the relationship is identified by determining that an entity containing the first term also contains the at least one of the plurality of related terms. | 0.822581 |
9,910,554 | 9 | 13 | 9. A program product, comprising: a data storage device; and program code stored within the data storage device that, when executed by a computer, causes the computer to perform: extracting first and second interface elements from a first graphical user interface (GUI) associated with a first cultural background, wherein the first and second interface elements are both of a first interface element type; in a rule repository including a plurality of transformation rules each specifying an interface element type and associated action to be taken on user interface elements of the specified interface element type, locating a first transformation rule that specifies the first interface element type and an associated first action; in response to locating the first transaction rule and utilizing the first action specified by the first transformation rule, transforming the first and second interface elements into third and fourth interface elements, respectively, wherein the third and fourth interface elements are associated with a second cultural background; and providing a second GUI including at least the third and fourth interface elements. | 9. A program product, comprising: a data storage device; and program code stored within the data storage device that, when executed by a computer, causes the computer to perform: extracting first and second interface elements from a first graphical user interface (GUI) associated with a first cultural background, wherein the first and second interface elements are both of a first interface element type; in a rule repository including a plurality of transformation rules each specifying an interface element type and associated action to be taken on user interface elements of the specified interface element type, locating a first transformation rule that specifies the first interface element type and an associated first action; in response to locating the first transaction rule and utilizing the first action specified by the first transformation rule, transforming the first and second interface elements into third and fourth interface elements, respectively, wherein the third and fourth interface elements are associated with a second cultural background; and providing a second GUI including at least the third and fourth interface elements. 13. The program product according to claim 9 , wherein the first cultural background and the second cultural background include at least one of: writing language, writing direction, date format, time format, currency format, display order, calendar type and unit format. | 0.781553 |
9,646,512 | 2 | 3 | 2. The method of claim 1 , wherein parsing, by the hardware processor, the text content into the one or more sentences further comprises one or more of: removing extensible markup language (XML) associated with each token from the received text content; and determining a part of speech tag to correspond to each token of each sentence. | 2. The method of claim 1 , wherein parsing, by the hardware processor, the text content into the one or more sentences further comprises one or more of: removing extensible markup language (XML) associated with each token from the received text content; and determining a part of speech tag to correspond to each token of each sentence. 3. The method of claim 2 , wherein each token comprises metadata indicating the part of speech tag, the lemma, and the position of each token in each sentence. | 0.687008 |
9,398,460 | 1 | 2 | 1. A mobile phone-based system for providing on-demand security to a requester primarily via non-voice communication, the system comprising: a. a database having i. requester data, ii. security escort data, iii. engagement data, iv. review data, and v. at least one request factor; b. at least one requester mobile phone having i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. request security escorts for at least one time period in at least one location, B. select at least one request factor and send a request to an engagement engine, C. receive a response from the engagement engine, D. enable the requester to meet and identify an escort, E. declare an emergency, F. terminate security escort for one time period in one location, and G. close an engagement; c. a screening facility adapted to— i. qualify at least one selected from security escort, requester, and ii. review qualifications of at least are selected from escort and requestor; d. at least one security escort mobile phone having— i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. receive a proposed security engagement, B. respond to the proposed engagement, C. receive security escort details, D. enable an escort to meet and identify a requester, E. declare an emergency, and F. close an engagement; e. an engagement engine having— i. a query generator interactively facilitating each request and generating a query most closely related to the requester's needs in view of each applicable request factor, and ii. a response generator receiving the query and applying request factors to generate a response including confirmation of request, expected cost, and escort identification; f. a meeting engine adapted to— i. transmit location and identification data to the requester and escort, ii. facilitate a meeting between the requester and the escort, iii. receive verification of an agreeable meeting, iv. close each engagement upon notification from at least one selected from requester and escort database, and v. pay the escorts whereby the security escorts required for a particular engagement are determined based on requester-provided data as a function of a requester requirements, security escort provider abilities, and application of request factors. | 1. A mobile phone-based system for providing on-demand security to a requester primarily via non-voice communication, the system comprising: a. a database having i. requester data, ii. security escort data, iii. engagement data, iv. review data, and v. at least one request factor; b. at least one requester mobile phone having i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. request security escorts for at least one time period in at least one location, B. select at least one request factor and send a request to an engagement engine, C. receive a response from the engagement engine, D. enable the requester to meet and identify an escort, E. declare an emergency, F. terminate security escort for one time period in one location, and G. close an engagement; c. a screening facility adapted to— i. qualify at least one selected from security escort, requester, and ii. review qualifications of at least are selected from escort and requestor; d. at least one security escort mobile phone having— i. at least one non-voice communication channel, ii. at least one voice communication channel, iii. an interface adapted to— A. receive a proposed security engagement, B. respond to the proposed engagement, C. receive security escort details, D. enable an escort to meet and identify a requester, E. declare an emergency, and F. close an engagement; e. an engagement engine having— i. a query generator interactively facilitating each request and generating a query most closely related to the requester's needs in view of each applicable request factor, and ii. a response generator receiving the query and applying request factors to generate a response including confirmation of request, expected cost, and escort identification; f. a meeting engine adapted to— i. transmit location and identification data to the requester and escort, ii. facilitate a meeting between the requester and the escort, iii. receive verification of an agreeable meeting, iv. close each engagement upon notification from at least one selected from requester and escort database, and v. pay the escorts whereby the security escorts required for a particular engagement are determined based on requester-provided data as a function of a requester requirements, security escort provider abilities, and application of request factors. 2. The system of claim 1 , where the database includes a set of security escort data for at least one security escort for at least one engagement. | 0.715953 |
8,140,515 | 1 | 6 | 1. A computer-implemented method for building a user profile of a user, the method comprising: labeling and storing user registration information in a database as a set of demographic nouns; analyzing, with a computing device, author-generated classification information regarding at least one document of a set of documents and assigning a set of first taxonomic nouns to characterize the user based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer and characterizing the user of at least one document of the set of documents and assigning a set of second taxonomic nouns to characterize the user based upon the user-generated tag characterization; identifying, with a computing device, a method by which the user accessed at least one document of the set of documents from a content provider and assigning a set of third taxonomic nouns to characterize the user based upon the method of access; evaluating, with a computing device, attributes that are related to the method of access and assigning a set of fourth taxonomic nouns to characterize the user based upon the attributes related to the method of access; processing, with a computing device, at least one document of the set of documents to extract a set of fifth taxonomic nouns to characterize the user; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; building, with a computing device, a user profile based upon the composite set of taxonomic nouns, the author-generated classification information, and at least one of the demographic nouns; comparing, with a computing device, the composite set of taxonomic nouns with taxonomic nouns associated with a plurality of other user profiles corresponding to a plurality of other users; and modifying, with a computing device, the user profile based on the comparison. | 1. A computer-implemented method for building a user profile of a user, the method comprising: labeling and storing user registration information in a database as a set of demographic nouns; analyzing, with a computing device, author-generated classification information regarding at least one document of a set of documents and assigning a set of first taxonomic nouns to characterize the user based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer and characterizing the user of at least one document of the set of documents and assigning a set of second taxonomic nouns to characterize the user based upon the user-generated tag characterization; identifying, with a computing device, a method by which the user accessed at least one document of the set of documents from a content provider and assigning a set of third taxonomic nouns to characterize the user based upon the method of access; evaluating, with a computing device, attributes that are related to the method of access and assigning a set of fourth taxonomic nouns to characterize the user based upon the attributes related to the method of access; processing, with a computing device, at least one document of the set of documents to extract a set of fifth taxonomic nouns to characterize the user; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; building, with a computing device, a user profile based upon the composite set of taxonomic nouns, the author-generated classification information, and at least one of the demographic nouns; comparing, with a computing device, the composite set of taxonomic nouns with taxonomic nouns associated with a plurality of other user profiles corresponding to a plurality of other users; and modifying, with a computing device, the user profile based on the comparison. 6. The computer-implemented method for building a user profile of claim 1 , wherein building the user profile includes deriving a user cluster of related users. | 0.835729 |
8,074,168 | 1 | 2 | 1. A method for automated rendering of context-compensated text in a graphical environment that is displayed in a display of a computing device, comprising: receiving a specification of items to be graphically displayed in the graphical environment, wherein the specification includes text to be graphically displayed in the graphical environment, and wherein the text is associated with an enhanced type-font for the text; determining a set of graphical items that will be displayed in proximity to a graphical representation of the text; determining that graphical aspects of the proximate graphical items will interfere with a user's ability to view the graphical representation of the text; and modifying the graphical representation of the text to more clearly display the text in the graphical environment, wherein modifying the graphical representation of the text comprises using rules associated with the enhanced type-font to change the complexity and detail displayed for the graphical representation of the text based on the size of the displayed text. | 1. A method for automated rendering of context-compensated text in a graphical environment that is displayed in a display of a computing device, comprising: receiving a specification of items to be graphically displayed in the graphical environment, wherein the specification includes text to be graphically displayed in the graphical environment, and wherein the text is associated with an enhanced type-font for the text; determining a set of graphical items that will be displayed in proximity to a graphical representation of the text; determining that graphical aspects of the proximate graphical items will interfere with a user's ability to view the graphical representation of the text; and modifying the graphical representation of the text to more clearly display the text in the graphical environment, wherein modifying the graphical representation of the text comprises using rules associated with the enhanced type-font to change the complexity and detail displayed for the graphical representation of the text based on the size of the displayed text. 2. The method of claim 1 , wherein determining that graphical aspects of the proximate graphical items will interfere with a user's view of the text includes analyzing one or more of the following: a size, a resolution, or a level-of-detail associated with the graphical representation of the text; a size, a resolution, or a level-of-detail associated with a proximate graphical item in the graphical environment; perspective magnification, tilting, or fog effects related to distance and viewpoint for the proximate graphical item and the graphical representation of the text; variations in brightness, color, hue, saturation, virtual lighting, or virtual reflectivity related to the proximate graphical item, the graphical representation of the text , and virtual lighting in the graphical environment; and shadows, texture, scattering, absorption, reflections, or other effects related to interactions among the proximate graphical item, the graphical representation of the text, and virtual lighting in the graphical environment. | 0.5 |
8,122,399 | 9 | 10 | 9. The apparatus of claim 1 , wherein the first, second, and third generators comprise a 1×N compiler. | 9. The apparatus of claim 1 , wherein the first, second, and third generators comprise a 1×N compiler. 10. The apparatus of claim 9 , wherein the 1×N compiler is arranged to determine reuse of said one of the 1×N arrays of cells via an analysis of a netlist, wherein the netlist comprises one of the behavioral representation, the logical representation, and the physical design representation. | 0.5 |
9,256,694 | 9 | 11 | 9. The device of claim 8 , wherein the operations comprise: classifying a specific search result as very relevant to the search query based on an observed historical click through rate associated with the specific search result, the specific search result being one of the one or more search results that are each classified as very relevant to the search query. | 9. The device of claim 8 , wherein the operations comprise: classifying a specific search result as very relevant to the search query based on an observed historical click through rate associated with the specific search result, the specific search result being one of the one or more search results that are each classified as very relevant to the search query. 11. The device of claim 9 , wherein the operations comprise: calculating the observed historical click through rate as a ratio representing a total number of times users have selected the specific search result in response to a particular search query to a total number of times users have selected other search results in response to the particular search query, the other search results being different from the specific search result. | 0.5 |
8,688,727 | 31 | 32 | 31. The system of claim 24 , wherein selecting one or more candidate refinement queries comprises: selecting as candidate refinement queries one or more sibling queries of the search query, wherein sibling queries are queries that have one or more shared parent queries in common, and wherein each of the sibling queries was submitted during a second search session following submission of a shared parent query during the first search session. | 31. The system of claim 24 , wherein selecting one or more candidate refinement queries comprises: selecting as candidate refinement queries one or more sibling queries of the search query, wherein sibling queries are queries that have one or more shared parent queries in common, and wherein each of the sibling queries was submitted during a second search session following submission of a shared parent query during the first search session. 32. The system of claim 31 , wherein the search query is textually distinct from each of the selected sibling queries and all the substrings of the selected sibling queries. | 0.5 |
9,268,668 | 8 | 10 | 8. A computer-implemented method, comprising: executing an application under test in a layout engine module, wherein the application under test comprises one or more instructions in one scripting language, wherein a selected scripting language engine is configured to interpret the one or more instructions in the one scripting language, and wherein the selected scripting language engine is selected using a user interface of testing options; initializing, in the layout engine module, a debugging session for the application under test, wherein the debugging session is configured to generate output data for the application under test, wherein the debugging session is based on a testing option that selects the selected scripting language engine from among a plurality of scripting language engines, and wherein each scripting language engine of the plurality of scripting language engines is configured to interpret the one scripting language; executing a communication module configured to receive at least packed command data associated with the debugging session; and executing an unpack module configured to establish communication between the communication module and the layout engine module at least to provide unpacked command data based on the packed command data to the layout engine module. | 8. A computer-implemented method, comprising: executing an application under test in a layout engine module, wherein the application under test comprises one or more instructions in one scripting language, wherein a selected scripting language engine is configured to interpret the one or more instructions in the one scripting language, and wherein the selected scripting language engine is selected using a user interface of testing options; initializing, in the layout engine module, a debugging session for the application under test, wherein the debugging session is configured to generate output data for the application under test, wherein the debugging session is based on a testing option that selects the selected scripting language engine from among a plurality of scripting language engines, and wherein each scripting language engine of the plurality of scripting language engines is configured to interpret the one scripting language; executing a communication module configured to receive at least packed command data associated with the debugging session; and executing an unpack module configured to establish communication between the communication module and the layout engine module at least to provide unpacked command data based on the packed command data to the layout engine module. 10. The method of claim 8 , wherein the layout engine module comprises one or more test tools, and wherein the one or more test tools comprise at least one of: a runtime editing tool, a memory allocation information tool, and a platform resource usage information tool. | 0.685012 |
9,792,038 | 1 | 7 | 1. A method for providing feedback via an input device, the method comprising: receiving a first input on an input surface via an input device, wherein the first input is received at a location corresponding to a margin of an electronic document; based on the location of the received first input on the input surface being in the margin of the electronic document and a length of time associated with drawing the received first input, determining if the received first input is associated with a scribble input intended to test pen attributes; in response to determining that the received first input is associated with the scribble input intended to test pen attributes, making a determination whether to erase the scribble input, wherein making the determination to erase the scribble input comprises: receiving a second input via the input device; determining that the second input is not in the margin of the electronic document; evaluating a size of the second input relative to the scribble input; and determining, based on the second input not being in the margin and the size of the second input, that the second input is not a continuation of the scribble input; and in response to making the determination to erase the scribble input, providing feedback via the input device that the scribble input is about to be erased. | 1. A method for providing feedback via an input device, the method comprising: receiving a first input on an input surface via an input device, wherein the first input is received at a location corresponding to a margin of an electronic document; based on the location of the received first input on the input surface being in the margin of the electronic document and a length of time associated with drawing the received first input, determining if the received first input is associated with a scribble input intended to test pen attributes; in response to determining that the received first input is associated with the scribble input intended to test pen attributes, making a determination whether to erase the scribble input, wherein making the determination to erase the scribble input comprises: receiving a second input via the input device; determining that the second input is not in the margin of the electronic document; evaluating a size of the second input relative to the scribble input; and determining, based on the second input not being in the margin and the size of the second input, that the second input is not a continuation of the scribble input; and in response to making the determination to erase the scribble input, providing feedback via the input device that the scribble input is about to be erased. 7. The method of claim 1 , wherein no portion of the second input overlaps the received first input. | 0.772727 |
9,311,301 | 21 | 24 | 21. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause a computer to perform functions that comprise: ingesting text data from a plurality of documents containing a plurality of mentions; locating, from the text data, for each of a selected plurality of chains of coreferent mentions, a particular context-based name from the respective chain, wherein the coreferent mentions correspond to entities and the context-based name is a longest name in the respective chain, a last name in the respective chain, or a most frequently occurring name in the respective chain; determining an entity category for each respective one of the plurality of chains; determining one or more entity attributes from structured data and unstructured data; based on the located particular context-based name, the entity category, and the one or more attributes, assigning high-probability coreferent chains to high-confidence buckets, such as to produce a power law probability distribution having a head region and a tail region; and resolving, based at least in part on the power law probability distribution, the coreferent mentions to identify corresponding real-world entities. | 21. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause a computer to perform functions that comprise: ingesting text data from a plurality of documents containing a plurality of mentions; locating, from the text data, for each of a selected plurality of chains of coreferent mentions, a particular context-based name from the respective chain, wherein the coreferent mentions correspond to entities and the context-based name is a longest name in the respective chain, a last name in the respective chain, or a most frequently occurring name in the respective chain; determining an entity category for each respective one of the plurality of chains; determining one or more entity attributes from structured data and unstructured data; based on the located particular context-based name, the entity category, and the one or more attributes, assigning high-probability coreferent chains to high-confidence buckets, such as to produce a power law probability distribution having a head region and a tail region; and resolving, based at least in part on the power law probability distribution, the coreferent mentions to identify corresponding real-world entities. 24. The non-transitory computer-readable medium of claim 21 , wherein the stored instructions, when executed by the one or more processors, further cause the computer to perform functions that comprise: assigning one or more low-frequency sub-entities into the head region; and assigning one or more high-frequency sub-entities into the tail region, wherein the low-frequency sub-entities correspond to mentions that occur less frequently across a document corpus than the mentions corresponding to the high-frequency sub-entities. | 0.684304 |
9,262,485 | 8 | 9 | 8. A computer program product for identifying a sketching matrix used by a linear sketch, the computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: receiving an initial output of the linear sketch; generating a query vector; inputting the query vector into the linear sketch; receiving an revised output of the linear sketch based on inputting the query vector; iteratively repeating the steps of generating the query vector, inputting the query vector into the linear sketch, and receiving an revised output of the linear sketch based on inputting the query vector until the sketching matrix used by the linear sketch can be identified. | 8. A computer program product for identifying a sketching matrix used by a linear sketch, the computer program product comprising: a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by a processor to: receiving an initial output of the linear sketch; generating a query vector; inputting the query vector into the linear sketch; receiving an revised output of the linear sketch based on inputting the query vector; iteratively repeating the steps of generating the query vector, inputting the query vector into the linear sketch, and receiving an revised output of the linear sketch based on inputting the query vector until the sketching matrix used by the linear sketch can be identified. 9. The computer program product of claim 8 , wherein inputting the query vector into the linear sketch is based on the revised output of the linear sketch received during a prior iteration. | 0.574324 |
10,025,487 | 10 | 14 | 10. An electronic device comprising: a display; at least one processor operable when executed to perform the following operations: detect a location of a text selection icon on the display; detect a touch input representing a selection of text displayed on the display using the text selection icon; determine a movement of the text selection icon while the touch input is maintained during the movement, wherein the movement is continuous and drags the text selection icon into a zone adjacent an edge of the display; in response to the determination, enable a row by row selection mode; and during the movement of the text selection icon while the touch input is maintained and the row by row selection mode is enabled, dynamically increase a width of said zone based on at least one of a number of rows of displayed text selected by the continuous movement of the text selection icon or a speed of the movement; wherein: if the detected location of the text selection icon is maintained within said zone during the movement while the touch input is maintained, the displayed text is selected on a row by row basis; and, if the detected location of the text selection icon moves outside said zone and moves into the displayed text during the movement while the touch input is maintained, the row by row selection mode is switched to a letter by letter selection mode, wherein in the letter by letter selection mode the displayed text is selected on a letter by letter basis. | 10. An electronic device comprising: a display; at least one processor operable when executed to perform the following operations: detect a location of a text selection icon on the display; detect a touch input representing a selection of text displayed on the display using the text selection icon; determine a movement of the text selection icon while the touch input is maintained during the movement, wherein the movement is continuous and drags the text selection icon into a zone adjacent an edge of the display; in response to the determination, enable a row by row selection mode; and during the movement of the text selection icon while the touch input is maintained and the row by row selection mode is enabled, dynamically increase a width of said zone based on at least one of a number of rows of displayed text selected by the continuous movement of the text selection icon or a speed of the movement; wherein: if the detected location of the text selection icon is maintained within said zone during the movement while the touch input is maintained, the displayed text is selected on a row by row basis; and, if the detected location of the text selection icon moves outside said zone and moves into the displayed text during the movement while the touch input is maintained, the row by row selection mode is switched to a letter by letter selection mode, wherein in the letter by letter selection mode the displayed text is selected on a letter by letter basis. 14. The electronic device according to claim 10 , wherein the selected text is highlighted on the display. | 0.53913 |
9,477,755 | 14 | 15 | 14. The computer program product of claim 5 , wherein the computer usable code, if executed, further causes a computer to apply a threshold to determine one or more of the user-question affinity value, the user-community affinity value, and the question-community affinity value. | 14. The computer program product of claim 5 , wherein the computer usable code, if executed, further causes a computer to apply a threshold to determine one or more of the user-question affinity value, the user-community affinity value, and the question-community affinity value. 15. The computer program product of claim 14 , wherein the threshold includes one or more of a predetermined frequency of occurrence with respect to user activity, a number of votes, and a number of candidate members in a candidate social community. | 0.5 |
8,135,800 | 13 | 21 | 13. A computer-implemented method of profiling a target user having a social network including a plurality of users, the method comprising: selecting a user from the plurality of users in the social network of the target user; scanning metadata associated with content items shared by the selected user; determining a list of keywords associated with the content items based on the metadata; accessing social network data associated with the selected user, the social network data including a relationship classifier that classifies a relationship between the selected user and the target user and a social network distance between the target user and the selected user, and a trust classifier that classifies a trust level between the selected user and the target user; determining a plurality of keyword scores based on the social network data, each of the plurality of keyword scores corresponding to one of the keywords on the list of keywords, wherein each of the plurality of scores is weighted by the trust classifier and an adjustment factor inversely proportional to the social network distance; normalizing individual keyword scores of the plurality of keywords scores based on a number of the content items shared by the selected user in comparison to a number of content items shared by other selected users of the plurality of users when the number of the content items shared by the selected user is greater than the number of content items shared by other selected users of the plurality of users; and generating a profile for the target user, the profile having the list of keywords and the corresponding plurality of keyword scores based on the scoring of each keyword. | 13. A computer-implemented method of profiling a target user having a social network including a plurality of users, the method comprising: selecting a user from the plurality of users in the social network of the target user; scanning metadata associated with content items shared by the selected user; determining a list of keywords associated with the content items based on the metadata; accessing social network data associated with the selected user, the social network data including a relationship classifier that classifies a relationship between the selected user and the target user and a social network distance between the target user and the selected user, and a trust classifier that classifies a trust level between the selected user and the target user; determining a plurality of keyword scores based on the social network data, each of the plurality of keyword scores corresponding to one of the keywords on the list of keywords, wherein each of the plurality of scores is weighted by the trust classifier and an adjustment factor inversely proportional to the social network distance; normalizing individual keyword scores of the plurality of keywords scores based on a number of the content items shared by the selected user in comparison to a number of content items shared by other selected users of the plurality of users when the number of the content items shared by the selected user is greater than the number of content items shared by other selected users of the plurality of users; and generating a profile for the target user, the profile having the list of keywords and the corresponding plurality of keyword scores based on the scoring of each keyword. 21. The computer-implemented method as set forth in claim 13 , further comprising: prior to scanning the metadata associated with the content items, determining whether to access the metadata based on one or more access parameters. | 0.716216 |
8,712,792 | 6 | 7 | 6. The method of claim 1 further comprising obtaining from each of the plurality of receiving users and the transmitting user corresponding personal health-related information, the health-related information including one or more health-related terms that each corresponds to a health-related concept; and correlating with a health terminology thesaurus each of the one or more health-related terms with a single concept unique identifier that uniquely identifies a corresponding health-related concept, each concept unique identifier having associated with it one or more terms corresponding to a common health-related concept, at least one of the terms being a lay medical term and not a clinical medical term. | 6. The method of claim 1 further comprising obtaining from each of the plurality of receiving users and the transmitting user corresponding personal health-related information, the health-related information including one or more health-related terms that each corresponds to a health-related concept; and correlating with a health terminology thesaurus each of the one or more health-related terms with a single concept unique identifier that uniquely identifies a corresponding health-related concept, each concept unique identifier having associated with it one or more terms corresponding to a common health-related concept, at least one of the terms being a lay medical term and not a clinical medical term. 7. The method of claim 6 in which computer implementation of the method employs a client computer and a server computer that are interconnected by a computer network, the method further comprising: transmitting at least some of the corresponding personal health-related information over the computer network from the client computer to the server computer, the server computer storing the health terminology thesaurus; and correlating, by the server computer, each of the one or more health-related terms with a single concept unique identifier. | 0.5 |
8,266,163 | 1 | 3 | 1. A method for utilizing reference/identification (ID) linking in extensible markup language (XML) wrapper code generation in a data processing system, said method comprising: receiving a type document and reference/ID constraints document; and accessing said reference/ID constraints document to translate between XML structures and object structures, wherein said accessing includes: creating a directed constraint graph from said reference/ID constraints document, wherein said directed constraint graph comprises at least one root XML structure that is not referenced by other XML structures and at least one leaf XML structure that does not reference other XML structures; generating a first set of deserialization code for at least one XML structure not in said directed constraint graph, wherein said first set of deserialization code translates said at least one XML structure not in said directed constraint graph into at least one object structure not in said directed constraint graph; creating a second set of deserialization code for said at least one XML leaf structure in said directed constraint graph, wherein said second set of deserialization code translates said at least one leaf XML structure into at least one leaf object structure; generating a third set of deserialization code for at least one next highest XML structure in said directed constraint graph, wherein said third set of deserialization code translates said at least one next highest XML structure into at least one next highest object structure; storing at least one intermediate object structure in at least one temporary hash table, wherein said at least one intermediate object structure is not a root object structure or a leaf object structure; and creating cleanup functions within said first, second, and third sets of deserialization code, wherein said cleanup functions remove all temporary hash tables utilized in object serialization. | 1. A method for utilizing reference/identification (ID) linking in extensible markup language (XML) wrapper code generation in a data processing system, said method comprising: receiving a type document and reference/ID constraints document; and accessing said reference/ID constraints document to translate between XML structures and object structures, wherein said accessing includes: creating a directed constraint graph from said reference/ID constraints document, wherein said directed constraint graph comprises at least one root XML structure that is not referenced by other XML structures and at least one leaf XML structure that does not reference other XML structures; generating a first set of deserialization code for at least one XML structure not in said directed constraint graph, wherein said first set of deserialization code translates said at least one XML structure not in said directed constraint graph into at least one object structure not in said directed constraint graph; creating a second set of deserialization code for said at least one XML leaf structure in said directed constraint graph, wherein said second set of deserialization code translates said at least one leaf XML structure into at least one leaf object structure; generating a third set of deserialization code for at least one next highest XML structure in said directed constraint graph, wherein said third set of deserialization code translates said at least one next highest XML structure into at least one next highest object structure; storing at least one intermediate object structure in at least one temporary hash table, wherein said at least one intermediate object structure is not a root object structure or a leaf object structure; and creating cleanup functions within said first, second, and third sets of deserialization code, wherein said cleanup functions remove all temporary hash tables utilized in object serialization. 3. The method according to claim 1 , wherein said accessing further comprises: for at least a first object structure to be serialized, generating a first serialization code for at least one child object structure, wherein only an identifying attribute of said at least one child object structure is serialized into an XML structure of said at least first object structure; and creating a second serialization code for at least one non-referenced child object. | 0.5 |
8,386,264 | 1 | 2 | 1. A speech data retrieval apparatus comprising: a speech database including plural pieces of speech data therein; a speech recognition unit configured to read speech data from the speech database, carry out a speech recognition process with respect to the read speech data, and output a result of speech recognition process as a lattice in which a phoneme, a syllable, or a word is a base unit; a confusion network creation unit configured to create a confusion network based on the lattice from the speech recognition unit and output the result of speech recognition process as the confusion network; an inverted index table creation unit configured to create an inverted index table based on the confusion network from the confusion network creation unit; a query input unit configured to receive a query input by a user, carry out a speech recognition process with respect to the received query, and output a result of speech recognition process as a character string; a query conversion unit configured to convert the character string from the query input unit into a label string in which a phoneme, a syllable, or a word is a base unit; and a label string check unit configured to check the label string from the query conversion unit against the inverted index table from the inverted index table creation unit, retrieve speech data which is included in both of the label string and the speech database, and output a list of pointer which indicates an address in the speech database in which the retrieved speech data is stored. | 1. A speech data retrieval apparatus comprising: a speech database including plural pieces of speech data therein; a speech recognition unit configured to read speech data from the speech database, carry out a speech recognition process with respect to the read speech data, and output a result of speech recognition process as a lattice in which a phoneme, a syllable, or a word is a base unit; a confusion network creation unit configured to create a confusion network based on the lattice from the speech recognition unit and output the result of speech recognition process as the confusion network; an inverted index table creation unit configured to create an inverted index table based on the confusion network from the confusion network creation unit; a query input unit configured to receive a query input by a user, carry out a speech recognition process with respect to the received query, and output a result of speech recognition process as a character string; a query conversion unit configured to convert the character string from the query input unit into a label string in which a phoneme, a syllable, or a word is a base unit; and a label string check unit configured to check the label string from the query conversion unit against the inverted index table from the inverted index table creation unit, retrieve speech data which is included in both of the label string and the speech database, and output a list of pointer which indicates an address in the speech database in which the retrieved speech data is stored. 2. The speech data retrieval apparatus according to claim 1 , wherein the label string check unit creates a partial confusion network formed by one or more arcs assigned to one or more labels included in the label string, with reference to the inverted index table, represents the label string by one-dimensional array graph and then assigns to each node in the one-dimensional array graph an arc returning to the each node to create a graph of query, and calculates an intersection between the partial confusion network and the graph of query. | 0.5 |
9,154,816 | 1 | 8 | 1. A system to detect garbled closed captioning data, comprising: a closed captioning data detector to detect closed captioning data in a video data stream; a data extractor to extract individual data elements from the closed captioning data; a data counter to count a total number of data elements in the closed captioning data and store the total data element count in a memory, and to count a total number of data elements having a particular characteristic in the closed captioning data and to store the data element characteristic count in the memory; a percentage threshold detector to determine a percentage of data elements having the particular data element characteristic in the closed captioning data as a ratio of the count of the number of data elements in the closed captioning data having the particular data element characteristic to the count of the total number of data elements in the closed captioning data; and an alert that is provided when the determined percentage exceeds a predetermined threshold. | 1. A system to detect garbled closed captioning data, comprising: a closed captioning data detector to detect closed captioning data in a video data stream; a data extractor to extract individual data elements from the closed captioning data; a data counter to count a total number of data elements in the closed captioning data and store the total data element count in a memory, and to count a total number of data elements having a particular characteristic in the closed captioning data and to store the data element characteristic count in the memory; a percentage threshold detector to determine a percentage of data elements having the particular data element characteristic in the closed captioning data as a ratio of the count of the number of data elements in the closed captioning data having the particular data element characteristic to the count of the total number of data elements in the closed captioning data; and an alert that is provided when the determined percentage exceeds a predetermined threshold. 8. The system recited in claim 1 , wherein the data counter uses a data delimiter to identify unique data elements within the closed captioning data for determining total data element and data element characteristic counts. | 0.614187 |
8,185,379 | 9 | 10 | 9. An electronic device comprising: a processor apparatus including a memory having a plurality of objects and at least one message stored therein, an output apparatus; and an input apparatus having a plurality of input members, at least some of the input members having a plurality of characters assigned thereto; the processor apparatus being adapted to: generate a new message in response to receiving one of a replying or forwarding command with respect to the at least one message, provide a dictionary comprising language objects associated with the at least one message, the first dictionary being stored in the memory, detect an ambiguous input comprising actuations of a number of the input members of the plurality of input members, determine that the ambiguous input is a portion of a salutation, identify one of the language objects stored in the dictionary that corresponds with the ambiguous input, and cause the output apparatus to output at least a portion of the identified language object as a proposed disambiguation of the ambiguous input. | 9. An electronic device comprising: a processor apparatus including a memory having a plurality of objects and at least one message stored therein, an output apparatus; and an input apparatus having a plurality of input members, at least some of the input members having a plurality of characters assigned thereto; the processor apparatus being adapted to: generate a new message in response to receiving one of a replying or forwarding command with respect to the at least one message, provide a dictionary comprising language objects associated with the at least one message, the first dictionary being stored in the memory, detect an ambiguous input comprising actuations of a number of the input members of the plurality of input members, determine that the ambiguous input is a portion of a salutation, identify one of the language objects stored in the dictionary that corresponds with the ambiguous input, and cause the output apparatus to output at least a portion of the identified language object as a proposed disambiguation of the ambiguous input. 10. The electronic device according to claim 9 , wherein the dictionary further comprises frequency objects. | 0.869565 |
8,019,857 | 1 | 7 | 1. A computer-implemented method for remediating one or more non-compliant computer systems in a network, the method comprising: receiving one or more compliance rules, wherein the rules include conditions for detecting whether a computer system violates the rule and remediation steps associated with each rule for restoring compliance of the computer system when it violates the rule; identifying the computer system; determining the compliance of the computer system with the compliance rules by checking the included conditions; when the computer system is determined to violate a compliance rule, performing the remediation steps associated with the violated compliance rule on the computer system; and after performing any remediation steps on the computer system, removing the received compliance rules from the computer system. | 1. A computer-implemented method for remediating one or more non-compliant computer systems in a network, the method comprising: receiving one or more compliance rules, wherein the rules include conditions for detecting whether a computer system violates the rule and remediation steps associated with each rule for restoring compliance of the computer system when it violates the rule; identifying the computer system; determining the compliance of the computer system with the compliance rules by checking the included conditions; when the computer system is determined to violate a compliance rule, performing the remediation steps associated with the violated compliance rule on the computer system; and after performing any remediation steps on the computer system, removing the received compliance rules from the computer system. 7. The method of claim 1 wherein the received compliance rule conditions identify one or more file versions that indicate compliance of the computer system with the rule. | 0.636752 |
9,436,726 | 1 | 17 | 1. A computer-implemented method comprising: translating official sector action non-quantitative text-based data into at least one quantitative risk management tool that electronically anticipates at least one trajectory of at least one official sector cross-border public policy data comprising: receiving electronically, by at least one computer processor, said official sector action non-quantitative text-based data relating to the at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, at least one tag or code relating to said official sector action non quantitative text-based data, comprising: tagging at least one concept electronically, by the at least one computer processor, of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: identifying electronically, by the at least one computer processor, occurrence of a group of words appearing together indicative of a specific concept in said at least one official sector action activity; associating electronically, by the at least one computer processor, said official sector action non-quantitative text-based data with said at least one tag or code, and storing in an electronic computer database; processing electronically, by the at least one computer processor, an algorithmic calculation to obtain the at least one anticipated official sector cross-border public policy data, wherein said algorithmic calculation comprises: linking electronically, by the at least one computer processor, the at least one anticipated official sector cross-border public policy data with said official sector action non-quantitative text-based data and said electronic database; enabling electronically, by the at least one computer processor, a semantic search of said electronic database; extracting electronically, by the at least one computer processor, quantitative data of at least one official sector action activity of the at least one official sector cross-border public policy data from said electronic database, wherein said extracting electronically said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data comprises: identifying electronically, by the at least one computer processor, correlations or covariances between a plurality of said at least one official sector action activity of said at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, said at least one tag or code, and said at least one concept; weighting electronically, by the at least one computer processor, said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: said at least one tag or code, and said at least one concept; a proximity of said at least one official sector action activity to a decision point; and a relative importance of an activity level of said at least one official sector action activity; and anticipating electronically, by the at least one computer processor, the at least one trajectory of the at least one official sector cross-border public policy data of said at least one official sector cross-border public policy based on: said at least one tag or code, and said at least one concept; said identifying electronically of said correlations or covariances, and said weighting electronically based on: said proximity to the deadline, and said relative importance of said activity level; and generating, by the at least one computer processor, at least one graphical representation of said quantitative data and the anticipated at least one trajectory of the at least one official sector cross-border public policy. | 1. A computer-implemented method comprising: translating official sector action non-quantitative text-based data into at least one quantitative risk management tool that electronically anticipates at least one trajectory of at least one official sector cross-border public policy data comprising: receiving electronically, by at least one computer processor, said official sector action non-quantitative text-based data relating to the at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, at least one tag or code relating to said official sector action non quantitative text-based data, comprising: tagging at least one concept electronically, by the at least one computer processor, of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: identifying electronically, by the at least one computer processor, occurrence of a group of words appearing together indicative of a specific concept in said at least one official sector action activity; associating electronically, by the at least one computer processor, said official sector action non-quantitative text-based data with said at least one tag or code, and storing in an electronic computer database; processing electronically, by the at least one computer processor, an algorithmic calculation to obtain the at least one anticipated official sector cross-border public policy data, wherein said algorithmic calculation comprises: linking electronically, by the at least one computer processor, the at least one anticipated official sector cross-border public policy data with said official sector action non-quantitative text-based data and said electronic database; enabling electronically, by the at least one computer processor, a semantic search of said electronic database; extracting electronically, by the at least one computer processor, quantitative data of at least one official sector action activity of the at least one official sector cross-border public policy data from said electronic database, wherein said extracting electronically said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data comprises: identifying electronically, by the at least one computer processor, correlations or covariances between a plurality of said at least one official sector action activity of said at least one official sector cross-border public policy data; receiving electronically, by the at least one computer processor, said at least one tag or code, and said at least one concept; weighting electronically, by the at least one computer processor, said quantitative data of said at least one official sector action activity of the at least one official sector cross-border public policy data, based on: said at least one tag or code, and said at least one concept; a proximity of said at least one official sector action activity to a decision point; and a relative importance of an activity level of said at least one official sector action activity; and anticipating electronically, by the at least one computer processor, the at least one trajectory of the at least one official sector cross-border public policy data of said at least one official sector cross-border public policy based on: said at least one tag or code, and said at least one concept; said identifying electronically of said correlations or covariances, and said weighting electronically based on: said proximity to the deadline, and said relative importance of said activity level; and generating, by the at least one computer processor, at least one graphical representation of said quantitative data and the anticipated at least one trajectory of the at least one official sector cross-border public policy. 17. The method according to claim 1 , further comprising at least one of: capturing at least one cross-border correlation between at least two of said at least one activities; or capturing at least one cross-border policy covariance of at least two of said at least one activities. | 0.929995 |
7,873,586 | 14 | 15 | 14. A computing system comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the processor implement a risk assessment method, said method comprising: receiving, by an inference engine within said computing system, first sensor cohort data associated with a first cohort, said first cohort located within a gate area within an airport; receiving, by said inference engine, first group technology inferences associated with said first cohort; generating, by said inference engine, first risk cohort inferences, said generating said first risk cohort inferences based on said first group technology inferences and said first sensor cohort data; receiving, by said inference engine, first inference data generated by said inference engine, said first inference data comprising a first plurality of inferences associated with said first cohort and a security perimeter area surrounding said airport; receiving, by said inference engine, second inference data generated by said inference engine, said second inference data comprising a second of plurality of inferences associated with said first cohort and a pre/post security area within said airport; receiving, by said inference engine, third inference data generated by said inference engine, said third inference data comprising a third of plurality of inferences associated with said first cohort and said gate area within said airport; generating, by said inference engine, fourth inference data, said fourth inference data comprising a fourth plurality of inferences associated with said first cohort and said gate area within said airport, wherein said generating said fourth inference data is based on said first risk cohort inferences, said first inference data, said second inference data, and said third inference data; generating, by said inference engine based on said fourth inference data, a first associated risk level score for said first cohort; and storing, by said computing system, said fourth inference data and said first associated risk level score. | 14. A computing system comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the processor implement a risk assessment method, said method comprising: receiving, by an inference engine within said computing system, first sensor cohort data associated with a first cohort, said first cohort located within a gate area within an airport; receiving, by said inference engine, first group technology inferences associated with said first cohort; generating, by said inference engine, first risk cohort inferences, said generating said first risk cohort inferences based on said first group technology inferences and said first sensor cohort data; receiving, by said inference engine, first inference data generated by said inference engine, said first inference data comprising a first plurality of inferences associated with said first cohort and a security perimeter area surrounding said airport; receiving, by said inference engine, second inference data generated by said inference engine, said second inference data comprising a second of plurality of inferences associated with said first cohort and a pre/post security area within said airport; receiving, by said inference engine, third inference data generated by said inference engine, said third inference data comprising a third of plurality of inferences associated with said first cohort and said gate area within said airport; generating, by said inference engine, fourth inference data, said fourth inference data comprising a fourth plurality of inferences associated with said first cohort and said gate area within said airport, wherein said generating said fourth inference data is based on said first risk cohort inferences, said first inference data, said second inference data, and said third inference data; generating, by said inference engine based on said fourth inference data, a first associated risk level score for said first cohort; and storing, by said computing system, said fourth inference data and said first associated risk level score. 15. The computing system of claim 14 , wherein said method further comprises: receiving, by said inference engine, second sensor cohort data associated with a second cohort, said second cohort located within said gate area within said airport; receiving, by said inference engine, second group technology inferences associated with said second cohort; generating, by said inference engine, second risk cohort inferences, said generating said second risk cohort inferences based on said second group technology inferences and said second sensor cohort data; receiving, by said inference engine, fifth inference data generated by said inference engine, said fifth inference data comprising a fifth plurality of inferences associated with said second cohort and said security perimeter area surrounding said airport; receiving, by said inference engine, sixth inference data generated by said inference engine, said sixth inference data comprising a sixth plurality of inferences associated with said second cohort and said pre/post security area within said airport; generating, by said inference engine, seventh inference data, said seventh inference data comprising a seventh plurality of inferences associated with said second cohort, wherein said generating said seventh inference data is based on second risk cohort inferences, said fifth inference data, and said sixth inference data; generating, by said inference engine based on said seventh inference data, a second associated risk level score for said second cohort; and storing, by said computing system, said seventh inference data and said second associated risk level score. | 0.5 |
10,108,700 | 1 | 4 | 1. A computer implemented method comprising the following operations performed by one or more processors: identifying, by one or more of the processors, an entity reference in a knowledge graph, wherein the entity reference corresponds to an entity type; identifying, by one or more of the processors, a missing data element associated with the entity reference, the missing data element reflecting a property of the entity reference for which no property value is currently assigned; generating, automatically by one or more of the processors in response to identifying the missing data element associated with the entity reference, a query based at least in part on the missing data element and the entity type; providing, by one or more of the processors, the query to a query processing engine; receiving information from the query processing engine in response to the query; and updating, by one or more of the processors in response to receiving information from the query processing engine, the knowledge graph based at least in part on the received information. | 1. A computer implemented method comprising the following operations performed by one or more processors: identifying, by one or more of the processors, an entity reference in a knowledge graph, wherein the entity reference corresponds to an entity type; identifying, by one or more of the processors, a missing data element associated with the entity reference, the missing data element reflecting a property of the entity reference for which no property value is currently assigned; generating, automatically by one or more of the processors in response to identifying the missing data element associated with the entity reference, a query based at least in part on the missing data element and the entity type; providing, by one or more of the processors, the query to a query processing engine; receiving information from the query processing engine in response to the query; and updating, by one or more of the processors in response to receiving information from the query processing engine, the knowledge graph based at least in part on the received information. 4. The method of claim 1 , wherein generating the query comprises selecting, from the knowledge graph, disambiguation query terms associated with the entity reference, wherein the disambiguation query terms comprise property values associated with the entity reference, and wherein the query includes the disambiguation query terms and one or more terms associated with the missing data element. | 0.5 |
9,250,706 | 8 | 9 | 8. The system for creating a unique signature as described in claim 7 , wherein the at least one segment has a color different from a color of the second segment. | 8. The system for creating a unique signature as described in claim 7 , wherein the at least one segment has a color different from a color of the second segment. 9. The system for creating a unique signature as described in claim 8 , wherein the signature includes an indicator, the indicator at the line beginning, designating where the line begins. | 0.5 |
8,938,390 | 1 | 14 | 1. A method for detecting autism in a natural language environment using a microphone, sound recorder, and a computer programmed with software for the specialized purpose of processing recordings captured by the microphone and sound recorder combination, the computer programmed to execute a method comprising: (a) segmenting an audio signal captured by the microphone and sound recorder combination using the computer programmed for the specialized purpose into a plurality of recording segments; (b) determining which of the plurality of recording segments correspond to a key child; (c) determining which of the plurality of recording segments that correspond to the key child are classified as key child recordings; (d) extracting phone-based features of the key child recordings; (e) comparing the phone-based features of the key child recordings to known phone-based features for children, the phone-based features corresponding to predetermined clusters of child speech resembling phones wherein the predetermined clusters of child speech resembling phones are clustered according to an unsupervised clustering method; (f) determining a likelihood of autism based on the comparing of (e); (g) extracting acoustic parameters of the key child recordings; and (h) comparing the acoustic parameters of the key child recordings to known acoustic parameters for children, wherein the determining of (f) also is based on the comparing of (h). | 1. A method for detecting autism in a natural language environment using a microphone, sound recorder, and a computer programmed with software for the specialized purpose of processing recordings captured by the microphone and sound recorder combination, the computer programmed to execute a method comprising: (a) segmenting an audio signal captured by the microphone and sound recorder combination using the computer programmed for the specialized purpose into a plurality of recording segments; (b) determining which of the plurality of recording segments correspond to a key child; (c) determining which of the plurality of recording segments that correspond to the key child are classified as key child recordings; (d) extracting phone-based features of the key child recordings; (e) comparing the phone-based features of the key child recordings to known phone-based features for children, the phone-based features corresponding to predetermined clusters of child speech resembling phones wherein the predetermined clusters of child speech resembling phones are clustered according to an unsupervised clustering method; (f) determining a likelihood of autism based on the comparing of (e); (g) extracting acoustic parameters of the key child recordings; and (h) comparing the acoustic parameters of the key child recordings to known acoustic parameters for children, wherein the determining of (f) also is based on the comparing of (h). 14. The method of claim 1 wherein unsupervised means that the clustering is based on the statistical characteristics of data gathered for determining the predetermined clusters of child speech. | 0.726629 |
8,560,575 | 1 | 10 | 1. A method comprising: accessing one or more updates associated with a data record, the one or more updates stored in a database, the data record being a parent record, the one or more updates related to one or more child records associated with the parent record, the parent record being at a first level of a hierarchy of records, the child records being at a second level of the hierarchy of records; providing the one or more updates as one or more candidates for publication on an information feed associated with the data record, the information feed capable of being displayed on a display device; and selecting a number of the candidates for publication on the information feed based on one or more criteria. | 1. A method comprising: accessing one or more updates associated with a data record, the one or more updates stored in a database, the data record being a parent record, the one or more updates related to one or more child records associated with the parent record, the parent record being at a first level of a hierarchy of records, the child records being at a second level of the hierarchy of records; providing the one or more updates as one or more candidates for publication on an information feed associated with the data record, the information feed capable of being displayed on a display device; and selecting a number of the candidates for publication on the information feed based on one or more criteria. 10. The method of claim 1 , further comprising: displaying the information feed to include the selected number of candidates. | 0.874749 |
8,056,050 | 1 | 2 | 1. A method for guided resolution of inter-model inconsistencies, comprising: grouping inconsistencies, detected as a result of a model-driven software development process, into model partitions within a list by analyzing relationships between the underlying models and identifying model partitions that are capable of being processed independently from one another during a resolution process; assigning priorities to models that contribute to the detected inconsistencies and inconsistency types, the priorities determining an order in which corresponding inconsistencies are presented to a user during the resolution process; reordering the list of inconsistencies to minimize the number of context switches during the resolution process, comprising: grouping the inconsistencies for a selected model partition by a corresponding abstract model context to produce groups A 1 , . . . , Am; ordering the groups A 1 , . . . , Am by average model priority; grouping the inconsistencies within each of the ordered groups Ai by abstract model element context, resulting in groups B 1 A1 , . . . , Bn Am ; ordering the groups B 1 A1 , . . . , Bn Am by one of a partial order ( amec) defined for corresponding abstract model element contexts and a total order derived from the amec; grouping inconsistencies inside each of the groups Bj Ai by inconsistency type to produce groups C 1 B1A1 , . . . , Co BnAm ; and ordering the groups C 1 B1A1 , . . . , Co BnAm by inconsistency type priority; and presenting, via a user interface screen, a listing of the inconsistencies and associated resolutions resulting from the reordering to the user at a client system; wherein the user applies a selected resolution for each of the inconsistencies presented via the user interface screen. | 1. A method for guided resolution of inter-model inconsistencies, comprising: grouping inconsistencies, detected as a result of a model-driven software development process, into model partitions within a list by analyzing relationships between the underlying models and identifying model partitions that are capable of being processed independently from one another during a resolution process; assigning priorities to models that contribute to the detected inconsistencies and inconsistency types, the priorities determining an order in which corresponding inconsistencies are presented to a user during the resolution process; reordering the list of inconsistencies to minimize the number of context switches during the resolution process, comprising: grouping the inconsistencies for a selected model partition by a corresponding abstract model context to produce groups A 1 , . . . , Am; ordering the groups A 1 , . . . , Am by average model priority; grouping the inconsistencies within each of the ordered groups Ai by abstract model element context, resulting in groups B 1 A1 , . . . , Bn Am ; ordering the groups B 1 A1 , . . . , Bn Am by one of a partial order ( amec) defined for corresponding abstract model element contexts and a total order derived from the amec; grouping inconsistencies inside each of the groups Bj Ai by inconsistency type to produce groups C 1 B1A1 , . . . , Co BnAm ; and ordering the groups C 1 B1A1 , . . . , Co BnAm by inconsistency type priority; and presenting, via a user interface screen, a listing of the inconsistencies and associated resolutions resulting from the reordering to the user at a client system; wherein the user applies a selected resolution for each of the inconsistencies presented via the user interface screen. 2. The method of claim 1 , wherein, for a given inconsistency i, the abstract model element context of the inconsistency i is a subset of its model element context comprising only the main elements for visualizing the inconsistency i. | 0.66087 |
10,102,295 | 1 | 15 | 1. A method comprising, by one or more computing devices: receiving, from a first client system of a first user, a first query inputted by the first user at the first client system, the first query comprising one or more n-grams; identifying one or more ideograms, each ideogram being associated with one or more tags, each identified ideogram being associated with at least one tag matching at least one of the n-grams of the received first query; calculating, for each identified ideogram, a use-probability for the ideogram given the received first query, wherein the use-probability is based at least in part on a frequency of use associated with the ideogram; sending, to the first client system, instructions for presenting a first set of ideograms comprising one or more of the identified ideograms, the first set being determined based on the calculated use-probabilities associated with the ideograms; receiving a second query from a second client system of a second user, the second query inputted by the second user at the second client system, the second query comprising one or more n-grams; and identifying one or more ideograms, each identified ideogram associated with at least one tag matching at least one of the n-grams of the received second query. | 1. A method comprising, by one or more computing devices: receiving, from a first client system of a first user, a first query inputted by the first user at the first client system, the first query comprising one or more n-grams; identifying one or more ideograms, each ideogram being associated with one or more tags, each identified ideogram being associated with at least one tag matching at least one of the n-grams of the received first query; calculating, for each identified ideogram, a use-probability for the ideogram given the received first query, wherein the use-probability is based at least in part on a frequency of use associated with the ideogram; sending, to the first client system, instructions for presenting a first set of ideograms comprising one or more of the identified ideograms, the first set being determined based on the calculated use-probabilities associated with the ideograms; receiving a second query from a second client system of a second user, the second query inputted by the second user at the second client system, the second query comprising one or more n-grams; and identifying one or more ideograms, each identified ideogram associated with at least one tag matching at least one of the n-grams of the received second query. 15. The method of claim 1 , further comprising: receiving a request from the first client system to access one or more restricted ideograms, wherein the first user is not authorized to access the restricted ideograms; and sending instructions for purchasing access to the one or more restricted ideograms to the first client system for display to the first user. | 0.65458 |
8,996,513 | 1 | 7 | 1. A computer memory device storing computer-executable instructions that, when executed, perform a method of constructing a search-result snippet of a website, the method comprising: receiving by a search engine a search query; determining that the website is relevant to the search query, wherein the website provides a website tool that converts a document from a first format to a second format; constructing the search-result snippet to include an interface by including an input field in the search-result snippet programmed to receive the document in the first format and by including a service-call instruction that, when executed, sends a service call to a website server requesting that the website tool convert the document from the first format to the second format; and providing the search-result snippet, which includes the input field and the service call, together with a plurality of other search-result snippets describing other pages in response to the search query. | 1. A computer memory device storing computer-executable instructions that, when executed, perform a method of constructing a search-result snippet of a website, the method comprising: receiving by a search engine a search query; determining that the website is relevant to the search query, wherein the website provides a website tool that converts a document from a first format to a second format; constructing the search-result snippet to include an interface by including an input field in the search-result snippet programmed to receive the document in the first format and by including a service-call instruction that, when executed, sends a service call to a website server requesting that the website tool convert the document from the first format to the second format; and providing the search-result snippet, which includes the input field and the service call, together with a plurality of other search-result snippets describing other pages in response to the search query. 7. The computer-memory device of claim 1 , wherein the interface includes a selectable link that is built to include the service-call instruction. | 0.779456 |
9,548,951 | 6 | 7 | 6. The method of claim 1 , wherein providing the additional information includes providing a notification to the sender and wherein the sender is the creator of the message. | 6. The method of claim 1 , wherein providing the additional information includes providing a notification to the sender and wherein the sender is the creator of the message. 7. The method of claim 6 , wherein the notification includes a prompt for the sender to grant permission to allow the providing of the additional information. | 0.5 |
7,533,019 | 1 | 3 | 1. A method for reducing the transcription effort for training an automatic speech recognition module, the method comprising: (1) training acoustic and language models using a first set of transcribed data; (2) recognizing utterances in a set of candidates for transcription using the acoustic and language models; (3) computing by a processor confidence scores of the utterances; (4) selecting k utterances that have the smallest confidence scores from the set of candidates and transcribing them into a first additional transcribed set; (5) adding the first additional transcribed set to the first set of transcribed data to produce a second set of transcribed data; (6) removing the first additional transcribed set from the set of candidates; (7) retrieving a set of un-transcribed data from the set of candidates; (8) training the acoustic and language models using the second set of transcribed data and speech recognition and word confidence scores for the retrieved set of un-transcribed data; and (9) returning to step (1) if word accuracy has not converged. | 1. A method for reducing the transcription effort for training an automatic speech recognition module, the method comprising: (1) training acoustic and language models using a first set of transcribed data; (2) recognizing utterances in a set of candidates for transcription using the acoustic and language models; (3) computing by a processor confidence scores of the utterances; (4) selecting k utterances that have the smallest confidence scores from the set of candidates and transcribing them into a first additional transcribed set; (5) adding the first additional transcribed set to the first set of transcribed data to produce a second set of transcribed data; (6) removing the first additional transcribed set from the set of candidates; (7) retrieving a set of un-transcribed data from the set of candidates; (8) training the acoustic and language models using the second set of transcribed data and speech recognition and word confidence scores for the retrieved set of un-transcribed data; and (9) returning to step (1) if word accuracy has not converged. 3. The method of claim 1 , wherein step (4) comprises leaving out utterances with confidence scores indicating that the utterances were correctly recognized. | 0.5 |
8,280,838 | 12 | 13 | 12. A system for an evidence evaluation method based on question answering, comprising: an editor operable to allow entering of information; an editor plug-in operable to automatically convert the information into a collection of questions; question answering processing module operable to determine answers for the collection of questions; said editor plug-in further operable to mark a fact in the information as being supported if one or more of the answers for the collection of questions support the fact and marking a fact in the information as being refuted if one or more of the answers for the collection of questions refute the fact, said editor plug-in further operable to collect the answers as evidence and add the evidence to the model of information to create an updated model of information. | 12. A system for an evidence evaluation method based on question answering, comprising: an editor operable to allow entering of information; an editor plug-in operable to automatically convert the information into a collection of questions; question answering processing module operable to determine answers for the collection of questions; said editor plug-in further operable to mark a fact in the information as being supported if one or more of the answers for the collection of questions support the fact and marking a fact in the information as being refuted if one or more of the answers for the collection of questions refute the fact, said editor plug-in further operable to collect the answers as evidence and add the evidence to the model of information to create an updated model of information. 13. The system of claim 12 , wherein the information includes a report. | 0.875439 |
9,891,792 | 12 | 22 | 12. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the interactive software system and obtaining user interaction activity data indicating the users' interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the interactive software system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data associated with the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the interactive software system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the interactive software system and obtaining current user interaction activity data indicating the current user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the interactive software system; correlating the biometric data associated with the current user with the current user's interaction activity data; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the current user; and presenting the customized interactive software system user experience to the current user. | 12. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the interactive software system and obtaining user interaction activity data indicating the users' interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the interactive software system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data associated with the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the interactive software system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the interactive software system and obtaining current user interaction activity data indicating the current user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the interactive software system; correlating the biometric data associated with the current user with the current user's interaction activity data; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the current user; and presenting the customized interactive software system user experience to the current user. 22. The method for building and utilizing interactive software system predictive models using biometric data of claim 12 , wherein the customized interactive software system user experience is presented to the user via at least one computing system selected from the group of computing systems consisting of: a server computing system; a workstation; a desktop computing system; a user wearable computing system; and a mobile computing system. | 0.855794 |
10,003,492 | 20 | 26 | 20. The method of claim 19 , wherein the auditing further comprises: determining a set of audit rules to execute, each audit rule targeting one or more attributes of network entities of the network model; for each audit rule, retrieving data values from the networking database correlated to the one or more target attributes; for each audit rule, executing the audit rule on the retrieved data values to determine whether an inconsistency exists; and in the event that an inconsistency exists, writing an entry comprising the inconsistent data values and associated network elements to a results repository. | 20. The method of claim 19 , wherein the auditing further comprises: determining a set of audit rules to execute, each audit rule targeting one or more attributes of network entities of the network model; for each audit rule, retrieving data values from the networking database correlated to the one or more target attributes; for each audit rule, executing the audit rule on the retrieved data values to determine whether an inconsistency exists; and in the event that an inconsistency exists, writing an entry comprising the inconsistent data values and associated network elements to a results repository. 26. The method of claim 20 , further comprising authorizing a source provider to access data in the results repository via an application programming interface (API). | 0.563158 |
8,375,021 | 18 | 19 | 18. A system comprising: an indexer that identifies words within a first document and determines a term identifier for said words, said first document having a document identifier; a term processor that identifies terms within said first document and determines a term identifier for said terms, at least a portion of said terms being derived from tags in said first document; a plurality of segment managers, each of said segment managers that manage as set of documents and create a plurality of search matrices from said set of documents; a distributor that identifies a first segment manager from said plurality of segment managers based on said document identifier and transmits at least said document identifier to said first segment manager; an aggregator that creates a set of consolidated matrices from a plurality of said search matrices; and a search engine that receives a search query, searches said set of consolidated matrices to identify a search result, and returns said search result. | 18. A system comprising: an indexer that identifies words within a first document and determines a term identifier for said words, said first document having a document identifier; a term processor that identifies terms within said first document and determines a term identifier for said terms, at least a portion of said terms being derived from tags in said first document; a plurality of segment managers, each of said segment managers that manage as set of documents and create a plurality of search matrices from said set of documents; a distributor that identifies a first segment manager from said plurality of segment managers based on said document identifier and transmits at least said document identifier to said first segment manager; an aggregator that creates a set of consolidated matrices from a plurality of said search matrices; and a search engine that receives a search query, searches said set of consolidated matrices to identify a search result, and returns said search result. 19. The system of claim 18 , said segment managers that further receive a modification for a document and updates said set of search matrices with said modification. | 0.5 |
8,650,177 | 14 | 15 | 14. The system of claim 9 , wherein the disambiguation module is further configured to calculate attributes about the plurality of disambiguated skill seed phrases and store the attributes in association with the plurality of disambiguated skill seed phrases. | 14. The system of claim 9 , wherein the disambiguation module is further configured to calculate attributes about the plurality of disambiguated skill seed phrases and store the attributes in association with the plurality of disambiguated skill seed phrases. 15. The system of claim 14 , wherein the attributes about the plurality of disambiguated skill seed phrases includes a top industry of at least one of the plurality of disambiguated skill phrases computed based upon an industry listed in the member profiles in which the at least one of the plurality of disambiguated skill seed phrases was found. | 0.5 |
9,087,396 | 1 | 5 | 1. A method comprising: determining, with a processing unit that has received a digital image, a brightness of an area of the digital image, the area being designated as an area upon which text is to be added to the digital image; selecting, with the processing unit, a color of the text based upon the determined brightness; adding, with the processing unit, a semi-transparent mask layer to the digital image, wherein a colored portion of the semi-transparent mask layer follows an outline of individual characters of the text being added to the digital image; and adding the text, to be outlined by the coloration of the semi-transparent mask layer, to the digital image with the processing unit. | 1. A method comprising: determining, with a processing unit that has received a digital image, a brightness of an area of the digital image, the area being designated as an area upon which text is to be added to the digital image; selecting, with the processing unit, a color of the text based upon the determined brightness; adding, with the processing unit, a semi-transparent mask layer to the digital image, wherein a colored portion of the semi-transparent mask layer follows an outline of individual characters of the text being added to the digital image; and adding the text, to be outlined by the coloration of the semi-transparent mask layer, to the digital image with the processing unit. 5. The method of claim 1 , wherein the colored portion of the mask layer comprises at least two differently colored areas corresponding to different portions of the text being added. | 0.665441 |
9,189,473 | 1 | 17 | 1. A method for coreference resolution comprising: receiving a set of document clusters, each cluster in the set of document clusters comprising a set of text documents; identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; for each of the candidate named entities, generating an event profile, the event profile comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; with a processor, computing a similarity between a pair of the candidate named entities based on their respective event profiles; and providing a decision for merging of the candidate named entities into a common real named entity, based on the computed similarity. | 1. A method for coreference resolution comprising: receiving a set of document clusters, each cluster in the set of document clusters comprising a set of text documents; identifying instances of each of a set of candidate named entities in the document clusters, the instances of a respective candidate named entity being text elements; for each of the candidate named entities, generating an event profile, the event profile comprising an optionally normalized vector of size k, where k is the number of document clusters in the set, in which each index of the vector is based on the occurrences of the identified instances of the candidate named entity in a respective one of the k clusters; with a processor, computing a similarity between a pair of the candidate named entities based on their respective event profiles; and providing a decision for merging of the candidate named entities into a common real named entity, based on the computed similarity. 17. The method of claim 1 , wherein the documents in the clusters are assigned to the clusters by a method which comprises: assigning each of a set of data points to a respective cluster, each of the data points representing a respective one of the documents; for a plurality of iterations: computing a comparison measure between each data point and each of a plurality of the clusters; and assigning each data point to at least one of the clusters based on the comparison measure and a threshold of the comparison measure; and outputting an assignment of the documents to the clusters, based on the clustering of the data points in one of the iterations. | 0.5 |
9,542,291 | 13 | 14 | 13. The event-based system of claim 12 , wherein the adjusting of the pre-defined waiting time is based on performance statistics of the CEP engine. | 13. The event-based system of claim 12 , wherein the adjusting of the pre-defined waiting time is based on performance statistics of the CEP engine. 14. The event-based system of claim 13 , wherein the performance statistics of the CEP engine include the number of queries presently executing. | 0.5 |
8,086,594 | 1 | 2 | 1. A computer implemented method for bifurcated document relevance scoring of documents in a document collection, the method comprising: indexing a plurality of documents in the document collection by: providing a set of phrases; for a plurality of documents in the document collection: identifying a plurality of phrases from the set of phrases that occurs in the document; for each phrase in a plurality of the identified phrases, scoring the phrase to produce a phrase relevance score for the phrase with respect to the document, and storing the phrase relevance score for the document in a phrase posting list for the phrase; receiving a search query of three or more words; determining a set of valid phrases in the search query by: decomposing, by at least one processor of a computer system, the query into a plurality of candidate phrasifications, including different groupings of words of the query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the query; scoring, by at least one of the processors of the computer system, at least two candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases in a corpus of documents and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; comparing, by at least one of the processors of the computer system, a score for each scored candidate phrasification to a threshold value; and selecting, by at least one of the processors of the computer system, at least one candidate phrasification, wherein the scores of each selected candidate phrasification exceed a threshold value and identifying the component phrase(s) of the selected candidate phrasification(s) as valid phrases for the search query; for each valid phrase for the search query, obtaining from the phrase posting list for the valid phrase the phrase relevance score for documents in which the valid phrase occurs; and for documents in which a valid phrase of the query occurs, scoring the document to produce a final relevance score using the phrase relevance scores for the document and based on the valid phrases of the search query. | 1. A computer implemented method for bifurcated document relevance scoring of documents in a document collection, the method comprising: indexing a plurality of documents in the document collection by: providing a set of phrases; for a plurality of documents in the document collection: identifying a plurality of phrases from the set of phrases that occurs in the document; for each phrase in a plurality of the identified phrases, scoring the phrase to produce a phrase relevance score for the phrase with respect to the document, and storing the phrase relevance score for the document in a phrase posting list for the phrase; receiving a search query of three or more words; determining a set of valid phrases in the search query by: decomposing, by at least one processor of a computer system, the query into a plurality of candidate phrasifications, including different groupings of words of the query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the query; scoring, by at least one of the processors of the computer system, at least two candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases in a corpus of documents and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; comparing, by at least one of the processors of the computer system, a score for each scored candidate phrasification to a threshold value; and selecting, by at least one of the processors of the computer system, at least one candidate phrasification, wherein the scores of each selected candidate phrasification exceed a threshold value and identifying the component phrase(s) of the selected candidate phrasification(s) as valid phrases for the search query; for each valid phrase for the search query, obtaining from the phrase posting list for the valid phrase the phrase relevance score for documents in which the valid phrase occurs; and for documents in which a valid phrase of the query occurs, scoring the document to produce a final relevance score using the phrase relevance scores for the document and based on the valid phrases of the search query. 2. The method of claim 1 , wherein: scoring the phrase to produce a phrase relevance score for the phrase with respect to the document comprises scoring the phrase and the document using a first scoring function; and scoring the document to produce a final relevance score using the phrase relevance scores for the document comprises scoring the document using a second scoring function. | 0.5 |
7,702,633 | 11 | 12 | 11. The media of claim 10 , wherein the rules reduce a total number of previews that a client device can request during a search session that corresponds to the protected electronic document. | 11. The media of claim 10 , wherein the rules reduce a total number of previews that a client device can request during a search session that corresponds to the protected electronic document. 12. The media of claim 11 , wherein the rules specify a maximum number of additional previews that can be requested for the protected electronic document. | 0.5 |
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