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9,575,994 | 1 | 12 | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. 12. The method of claim 1 , wherein the storing of the at least one computed feature includes a storage of a bounding box that defines the region of interest in the at least one image, whereby the region of interest represents an image area that is used to generate the at least one feature, and a reference to the at least one image, whereby the at least one image is stored on an image database. | 0.693673 |
7,849,025 | 1 | 10 | 1. A method comprising the following computer-executable acts: receiving a computer-implemented relational model, wherein the computer-implemented relational model includes atoms and relationships between atoms; and modifying the relational model by selectively removing at least one of atoms or relationships from the relational model. | 1. A method comprising the following computer-executable acts: receiving a computer-implemented relational model, wherein the computer-implemented relational model includes atoms and relationships between atoms; and modifying the relational model by selectively removing at least one of atoms or relationships from the relational model. 10. The method of claim 1 , further comprising using the output value to determine a weight to be assigned to a clause in the relational model. | 0.864326 |
8,572,024 | 13 | 14 | 13. An apparatus for implementing a data extraction process, the apparatus comprising a workstation storage device, a workstation processor connected to the workstation storage device, the workstation storage device storing a workstation program for controlling the workstation processor, and the workstation processor operative with the workstation program to: receive one or more web sites selected by a user for data extraction; collect a plurality of co-occurring different HTML structured documents for each of the selected web sites; form a plurality of clusters comprising different subsets of a group of co-occurring Hyper Text Mark-up Language (HTML) structured documents for each of the selected web sites, wherein: each cluster comprises a different HTML structured document of the group of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the group of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, and an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures, display the centroid document of a particular cluster selected from a list of clusters; mark a data element on the centroid document of the particular cluster; and provide a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. | 13. An apparatus for implementing a data extraction process, the apparatus comprising a workstation storage device, a workstation processor connected to the workstation storage device, the workstation storage device storing a workstation program for controlling the workstation processor, and the workstation processor operative with the workstation program to: receive one or more web sites selected by a user for data extraction; collect a plurality of co-occurring different HTML structured documents for each of the selected web sites; form a plurality of clusters comprising different subsets of a group of co-occurring Hyper Text Mark-up Language (HTML) structured documents for each of the selected web sites, wherein: each cluster comprises a different HTML structured document of the group of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the group of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, and an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures, display the centroid document of a particular cluster selected from a list of clusters; mark a data element on the centroid document of the particular cluster; and provide a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. 14. The apparatus of claim 13 , further configured to collect a plurality of HTML structured documents from a merchant web site. | 0.824176 |
7,536,297 | 1 | 11 | 1. A system for matching one or more abbreviations and one or more definitions, comprising: a recognition process that examines character strings and determines which character strings to be abbreviated; an abbreviation pattern generation process that creates from said determined character strings one or more abbreviation patterns representing candidate abbreviations, each of the one or more abbreviation patterns being a template that indicates a number and a location of characters and numeric strings within a candidate abbreviation; and a definition pattern generation process that creates from said determined character strings one or more definition patterns representing candidate definitions, each of the one or more definition patterns being a template that indicates a number and a location of numeric strings, stopwords, prefix/headword combinations and base words within a candidate definition. | 1. A system for matching one or more abbreviations and one or more definitions, comprising: a recognition process that examines character strings and determines which character strings to be abbreviated; an abbreviation pattern generation process that creates from said determined character strings one or more abbreviation patterns representing candidate abbreviations, each of the one or more abbreviation patterns being a template that indicates a number and a location of characters and numeric strings within a candidate abbreviation; and a definition pattern generation process that creates from said determined character strings one or more definition patterns representing candidate definitions, each of the one or more definition patterns being a template that indicates a number and a location of numeric strings, stopwords, prefix/headword combinations and base words within a candidate definition. 11. A system, as in claim 1 , further comprising: a method for specifying pairs, each of which contains a candidate abbreviation and a candidate definition, for each pair generating an abbreviation patterns and a definition pattern. | 0.860911 |
7,729,594 | 6 | 17 | 6. The medium of claim 1 , wherein the PES packet comprises stream identification, PES packet length, and packet data. | 6. The medium of claim 1 , wherein the PES packet comprises stream identification, PES packet length, and packet data. 17. The medium of claim 6 , wherein the packet data comprises data as any one form of a style segment or a presentation segment. | 0.594937 |
9,967,159 | 16 | 27 | 16. A cloud brokerage device, comprising: at least one processor and an associated processor readable memory comprising instructions that, when executed by the at least one processor, cause the processor to: receive workload input data for a workload, wherein the workload input data comprises at least one workload pattern parameter, policy parameter, or cost attribute; determine resource optimization data based on the workload input data, wherein the determining the resource optimization data comprises determining, compliance of the workload with one or more audit and regulatory metrics, cost consumption of the workload, and non-functional context data associated with the workload, wherein the audit and regulatory metrics include at least one of an enterprise regulatory compliance metric, an industry standards body compliance metric or a governmental regulatory compliance metric and the cost consumption includes metering cost associated with deploying the workload based on a budget; apply one or more rules to the workload input data, wherein the one or more rules comprise at least one of an information technology, business, compliance, departmental, portfolio or enterprise context rule in a rules repository database; and deploy the workload across a cloud ecosystem according to deployment plan data generated based on the resource optimization data and the application of the one or more rules to the workload input data, wherein the deployment plan data comprises a deployment plan for optimally deploying the workload that is generated prior to deployment of the workload on any platform. | 16. A cloud brokerage device, comprising: at least one processor and an associated processor readable memory comprising instructions that, when executed by the at least one processor, cause the processor to: receive workload input data for a workload, wherein the workload input data comprises at least one workload pattern parameter, policy parameter, or cost attribute; determine resource optimization data based on the workload input data, wherein the determining the resource optimization data comprises determining, compliance of the workload with one or more audit and regulatory metrics, cost consumption of the workload, and non-functional context data associated with the workload, wherein the audit and regulatory metrics include at least one of an enterprise regulatory compliance metric, an industry standards body compliance metric or a governmental regulatory compliance metric and the cost consumption includes metering cost associated with deploying the workload based on a budget; apply one or more rules to the workload input data, wherein the one or more rules comprise at least one of an information technology, business, compliance, departmental, portfolio or enterprise context rule in a rules repository database; and deploy the workload across a cloud ecosystem according to deployment plan data generated based on the resource optimization data and the application of the one or more rules to the workload input data, wherein the deployment plan data comprises a deployment plan for optimally deploying the workload that is generated prior to deployment of the workload on any platform. 27. The device of claim 16 , wherein the processor readable memory further comprises one or more additional instructions that, when executed by the processor, further cause the processor to: meter computing resource consumption or cloud service consumption of the workload; compute charges associated with the workload on the basis of service subscription data retrieved from a service subscriptions repository database; validate charges associated with actual computing resource or cloud service consumption by the workload against budget data in a set of enterprise context data in the workload input data and the service usage context data; and create a consumption context pattern on the basis of the estimated workload resource cost and budget impact relative to the enterprise context data. | 0.506203 |
10,007,748 | 1 | 2 | 1. A tangible, non-transitory, and computer-readable media storing instructions that, when executed by one or more processors, cause one or more processors to: identify at least one programming language construct associated with a safety data type of an algorithmic description representation of a circuit design, wherein the algorithmic description representation is specified in a first language; and generate a second representation of the circuit design based on the algorithmic description representation and the safety data type, the second representation is specified in a second language and includes at least one safety feature that is based at least in part on the safety data type, wherein the second representation is used to configure a manufactured programmable logic device after manufacturing of the programmable logic device has been completed. | 1. A tangible, non-transitory, and computer-readable media storing instructions that, when executed by one or more processors, cause one or more processors to: identify at least one programming language construct associated with a safety data type of an algorithmic description representation of a circuit design, wherein the algorithmic description representation is specified in a first language; and generate a second representation of the circuit design based on the algorithmic description representation and the safety data type, the second representation is specified in a second language and includes at least one safety feature that is based at least in part on the safety data type, wherein the second representation is used to configure a manufactured programmable logic device after manufacturing of the programmable logic device has been completed. 2. The tangible, non-transitory, and computer-readable media of claim 1 , wherein the algorithmic description representation is a control-flow-based representation. | 0.641921 |
5,475,738 | 14 | 19 | 14. A method of communicating a voice message to a voice messaging system, the voice messaging system having a human operator interface associated therewith, the voice message based on a text message from a text messaging system, the text messaging system comprising one or more addressable nodes including a messaging system interface node, the text messaging system and the voice messaging system coupled by a telephone network, the method comprising the steps of: the messaging system interface node receiving the text message from the text messaging system based on an address of the messaging system interface node; the messaging system interface node generating interface signals for simulating human operation of the voice messaging system in accordance with the human operator interface associated therewith; the messaging system interface node generating a voice message responsive to the text message; and transmitting the interface signals and the voice message over the telephone network based on a recipient telephone number. | 14. A method of communicating a voice message to a voice messaging system, the voice messaging system having a human operator interface associated therewith, the voice message based on a text message from a text messaging system, the text messaging system comprising one or more addressable nodes including a messaging system interface node, the text messaging system and the voice messaging system coupled by a telephone network, the method comprising the steps of: the messaging system interface node receiving the text message from the text messaging system based on an address of the messaging system interface node; the messaging system interface node generating interface signals for simulating human operation of the voice messaging system in accordance with the human operator interface associated therewith; the messaging system interface node generating a voice message responsive to the text message; and transmitting the interface signals and the voice message over the telephone network based on a recipient telephone number. 19. The method according to claim 14 further comprising the step of determining the recipient telephone number based on a text messaging system address. | 0.62 |
8,528,043 | 1 | 6 | 1. A machine implemented method comprising: accessing data from a tangible machine readable medium representative of a model of a process, the model being in a format of a Business Process Modeling Notation (BPMN) choreography process that defines expected behavior among participating entities; identifying, from the model of the process, a set of participating entities; identifying a set of choreography tasks conducted between the set of participating entities; and for at least one choreography task in the set of choreography tasks: identifying an initiating participating entity and a corresponding participating entity for the choreography task; generating data indicating a trust relationship between the initiating participating entity and the corresponding participating entity based on the choreography task; storing data in a tangible computer readable medium indicating the trust relationship between the corresponding participating entity and the initiating participating entity; and accessing the data indicating the trust relationship to establish a security framework across a first enterprise domain of the initiating participating entity and a second enterprise domain of the corresponding participating entity. | 1. A machine implemented method comprising: accessing data from a tangible machine readable medium representative of a model of a process, the model being in a format of a Business Process Modeling Notation (BPMN) choreography process that defines expected behavior among participating entities; identifying, from the model of the process, a set of participating entities; identifying a set of choreography tasks conducted between the set of participating entities; and for at least one choreography task in the set of choreography tasks: identifying an initiating participating entity and a corresponding participating entity for the choreography task; generating data indicating a trust relationship between the initiating participating entity and the corresponding participating entity based on the choreography task; storing data in a tangible computer readable medium indicating the trust relationship between the corresponding participating entity and the initiating participating entity; and accessing the data indicating the trust relationship to establish a security framework across a first enterprise domain of the initiating participating entity and a second enterprise domain of the corresponding participating entity. 6. The machine implemented method of claim 1 , wherein the model of the process is represented by an XML formatted file, and identifying the set of tasks comprises parsing the XML formatted file to extract choreography task identifiers from the XML formatted file. | 0.647059 |
8,000,530 | 16 | 18 | 16. The system of claim 15 , further comprising tools and mechanisms to enable an expert to provide information concerning characteristics of the document type and goals of content understanding. | 16. The system of claim 15 , further comprising tools and mechanisms to enable an expert to provide information concerning characteristics of the document type and goals of content understanding. 18. The system of claim 16 , wherein the expert is provided with the document from said training management unit and the expert provides information concerning the characteristics of the document type and goals of content understanding. | 0.5 |
8,910,251 | 18 | 19 | 18. The method of claim 16 , further comprising: sending to the requestor a plurality of answers for the challenge question comprising at least a correct answer and one or more incorrect answers. | 18. The method of claim 16 , further comprising: sending to the requestor a plurality of answers for the challenge question comprising at least a correct answer and one or more incorrect answers. 19. The method of claim 18 , further comprising: receiving a suspiciousness score value from the requestor; and determining the number of answers in the plurality of answers based on the suspiciousness score value. | 0.5 |
9,613,144 | 20 | 21 | 20. The non-transitory computer readable medium of claim 19 , wherein the intercepted one or more search terms are modified by the remote computing system by adding one or more new search terms to the intercepted, one or more search terms at least partially based on the social network data associated with the user. | 20. The non-transitory computer readable medium of claim 19 , wherein the intercepted one or more search terms are modified by the remote computing system by adding one or more new search terms to the intercepted, one or more search terms at least partially based on the social network data associated with the user. 21. The non-transitory computer readable medium of claim 20 , wherein the social network data associated with the user comprises at least one characteristic associated with the user, wherein the at least one characteristic associated with the user is one or more characteristics selected from the group consisting of: (A) the gender of the user; (B) one or more products indicated by the user; (C) one or more companies indicated by the user; and (D) the occupation of the user. | 0.5 |
8,818,999 | 9 | 12 | 9. A tangibly embodied non-transitory computer-readable storage medium storing instructions, that, when executed by a processor, perform a ranking method comprising: sending, to a remote computer system via a network, a search query containing query terms; obtaining, at the remote computer system, documents resulting from performing the search query on a document database, the documents containing such terms that match the search query; determining base relevancy scores for the documents; adjusting the base relevancy scores by applying a lead boosting value calculated according to an influence function, the influence function promoting a particular word position in a document, the particular word position being a predetermined number of words from the beginning of the document; and ranking the documents according to the adjusted base relevancy scores. | 9. A tangibly embodied non-transitory computer-readable storage medium storing instructions, that, when executed by a processor, perform a ranking method comprising: sending, to a remote computer system via a network, a search query containing query terms; obtaining, at the remote computer system, documents resulting from performing the search query on a document database, the documents containing such terms that match the search query; determining base relevancy scores for the documents; adjusting the base relevancy scores by applying a lead boosting value calculated according to an influence function, the influence function promoting a particular word position in a document, the particular word position being a predetermined number of words from the beginning of the document; and ranking the documents according to the adjusted base relevancy scores. 12. The tangibly embodied non-transitory computer-readable storage medium of claim 9 , wherein the influence function is selected from one of a discontinuous, non-differential function, a heuristic function, a uniform function, a step-function, or a function that disregards deviation distance. | 0.795265 |
8,670,997 | 12 | 16 | 12. In a non-transitory computer readable storage medium having stored therein data representing instructions executable by a programmed processor for editing medical related quality metric information, the storage medium comprising instructions for: mining a patient record for patient treatment information related to a plurality of report values, the report values being metrics indicating quality of care related to a guideline or requirement; deriving the report values from the patient treatment information; displaying the report values for a patient at a given time; receiving edit information from a user, the edit information being for editing at least one of a plurality of supporting data values, a relationship between the supporting data values, or both for the at least one of the report values; changing the at least one of the data values, the relationship, or both based on the edit information, the data values and relationship between the supporting data values representing a state of the patient as indicated by the patient record such that the changing reflects a different state of the patient at the given time; and generating a report as a function of the changed at least one of the data values, the changed relationship, or both and the report values. | 12. In a non-transitory computer readable storage medium having stored therein data representing instructions executable by a programmed processor for editing medical related quality metric information, the storage medium comprising instructions for: mining a patient record for patient treatment information related to a plurality of report values, the report values being metrics indicating quality of care related to a guideline or requirement; deriving the report values from the patient treatment information; displaying the report values for a patient at a given time; receiving edit information from a user, the edit information being for editing at least one of a plurality of supporting data values, a relationship between the supporting data values, or both for the at least one of the report values; changing the at least one of the data values, the relationship, or both based on the edit information, the data values and relationship between the supporting data values representing a state of the patient as indicated by the patient record such that the changing reflects a different state of the patient at the given time; and generating a report as a function of the changed at least one of the data values, the changed relationship, or both and the report values. 16. The instructions of claim 12 further comprising: storing an annotation for the user edit information. | 0.89521 |
9,582,533 | 7 | 8 | 7. The content reproduction device according to claim 6 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: generate the use history data by counting, for each of the plurality of databases, the number of searches run by the search step. | 7. The content reproduction device according to claim 6 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: generate the use history data by counting, for each of the plurality of databases, the number of searches run by the search step. 8. The content reproduction device according to claim 7 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: transmit the use history data, generated by the use history data generating step, to a compilation device for compiling use history data; and (i) obtain, from the compilation device, integrated use history data generated by the compilation device calculating, for each of the plurality of databases, a sum of search counts included in each of the use history data received from the use history data generating step and use history data received from a device other than the content reproduction device and (ii) generate the priority data with reference to the integrated use history data. | 0.5 |
9,268,927 | 1 | 3 | 1. A computer implemented method for identifying a user as one from a series of authorized users from free typed text, comprising the steps of (1) retrieving with a processor stored typing profiles for a series of authorized users {U k } from a data storage device, each authorized user typing profile associated with a single authorized user and containing a set of trial values derived from feature measured values from said trial typing sample received from said associated authorized user, each of said trial values being associated with one feature from a set of predefined features {Z i }; (2) receiving a test typing sample of free text characters from a text input terminal, where said received test typing sample comprises a string of text characters that is not a fixed string of text characters; (3) extracting with a processor a subset of features Z from said received test typing sample, each extracted feature Z i in said subset Z having a set of non null test values derived from said extracted feature; (4) selecting one of said authorized user profiles U k , and for said selected authorized user profile, determining which features in said selected authorized user profile are common with said extracted subset of features Z, and comparing said common extracted feature test values to said common selected authorized user typing profiles feature trial values to derive a selected authorized user score associated with said selected authorized user, wherein said selected authorized user score, is related to either (a) a conditional probability estimate P ( U k / Z ) = P ( U k / Z 1 , Z 2 , … , Z n ) = P ( U k ) P ( Z 1 , Z 2 , … , Z n ) ∏ j = 1 n ( ∏ t = 1 m j P ( z j t / U k ) ) , that the selected authorized user U k generated the test values associated with said set of extracted subset of features Z=(Z 1 , . . . Z n ) where each Z j vector consists of feature values z j 1 , z j 2 , . . . z j m j , where (i) subscript j refers to a j th feature, (ii) superscript m j represents the total number of times feature value for the j th feature is recorded in the vector Z j , and (iii) z j t represents the extracted test value for the j th feature at the t th component position in the Z j vector; or (b) an estimated similarity S k of said extracted features Z to the corresponding selected authorized user profile, wherein said estimated similarity S k to said selected authorized user U k is related to the proportion of (i) the total of all extracted feature test values that lie in a predetermined neighborhood of the corresponding feature trial values in said selected authorized user U k authorized user profile, to (ii) the total of all extracted feature test values for said selected authorized user; and (5) associating said test typing sample with said selected authorized user if said selected authorized user score satisfies a predefined condition. | 1. A computer implemented method for identifying a user as one from a series of authorized users from free typed text, comprising the steps of (1) retrieving with a processor stored typing profiles for a series of authorized users {U k } from a data storage device, each authorized user typing profile associated with a single authorized user and containing a set of trial values derived from feature measured values from said trial typing sample received from said associated authorized user, each of said trial values being associated with one feature from a set of predefined features {Z i }; (2) receiving a test typing sample of free text characters from a text input terminal, where said received test typing sample comprises a string of text characters that is not a fixed string of text characters; (3) extracting with a processor a subset of features Z from said received test typing sample, each extracted feature Z i in said subset Z having a set of non null test values derived from said extracted feature; (4) selecting one of said authorized user profiles U k , and for said selected authorized user profile, determining which features in said selected authorized user profile are common with said extracted subset of features Z, and comparing said common extracted feature test values to said common selected authorized user typing profiles feature trial values to derive a selected authorized user score associated with said selected authorized user, wherein said selected authorized user score, is related to either (a) a conditional probability estimate P ( U k / Z ) = P ( U k / Z 1 , Z 2 , … , Z n ) = P ( U k ) P ( Z 1 , Z 2 , … , Z n ) ∏ j = 1 n ( ∏ t = 1 m j P ( z j t / U k ) ) , that the selected authorized user U k generated the test values associated with said set of extracted subset of features Z=(Z 1 , . . . Z n ) where each Z j vector consists of feature values z j 1 , z j 2 , . . . z j m j , where (i) subscript j refers to a j th feature, (ii) superscript m j represents the total number of times feature value for the j th feature is recorded in the vector Z j , and (iii) z j t represents the extracted test value for the j th feature at the t th component position in the Z j vector; or (b) an estimated similarity S k of said extracted features Z to the corresponding selected authorized user profile, wherein said estimated similarity S k to said selected authorized user U k is related to the proportion of (i) the total of all extracted feature test values that lie in a predetermined neighborhood of the corresponding feature trial values in said selected authorized user U k authorized user profile, to (ii) the total of all extracted feature test values for said selected authorized user; and (5) associating said test typing sample with said selected authorized user if said selected authorized user score satisfies a predefined condition. 3. The computer implemented method of claim 1 wherein, prior to receiving said test typing sample, a sample free text string is displayed at a display unit associated with said text input terminal for replication by a user, wherein said test typing sample received is the user's attempted replication of said sample free text string. | 0.74186 |
9,137,577 | 12 | 29 | 12. A television system for responding to user selection of an object in television programming, the television system operable to: determine an identity of a user-selected object in a television program being presented to a user, where the user-selected object is associated with a person, and where the identity is received from a remote server in response to a transmission, by a television controller of the television system, of a signal that indicates a location of the user-selected object on a television screen of the television system; determine, based at least in part on the determined object identity, one or more actions to perform in response to the selection of the user-selected object, the determined one or more actions comprise starting two-way video communication between the user and the person, the person being remote from the television system; and perform the determined one or more actions. | 12. A television system for responding to user selection of an object in television programming, the television system operable to: determine an identity of a user-selected object in a television program being presented to a user, where the user-selected object is associated with a person, and where the identity is received from a remote server in response to a transmission, by a television controller of the television system, of a signal that indicates a location of the user-selected object on a television screen of the television system; determine, based at least in part on the determined object identity, one or more actions to perform in response to the selection of the user-selected object, the determined one or more actions comprise starting two-way video communication between the user and the person, the person being remote from the television system; and perform the determined one or more actions. 29. The television system of claim 12 , wherein the determined one or more actions comprise searching, with search terms relating to the selected information element, one or more entities or system components. | 0.703125 |
7,720,804 | 10 | 11 | 10. The method as claimed in claim 1 , wherein the providing data management services comprises managing generation of a source framework model from one or more data source systems, the source framework model is a semantic layer containing a logical business representation of the source systems. | 10. The method as claimed in claim 1 , wherein the providing data management services comprises managing generation of a source framework model from one or more data source systems, the source framework model is a semantic layer containing a logical business representation of the source systems. 11. The method as claimed in claim 10 , wherein the managing generation of a source framework model comprises: accessing and reading the logical information of the source systems; and reflecting the logical information in the source framework model. | 0.5 |
8,144,838 | 18 | 21 | 18. The tangible computer-readable medium of claim 17 , the instructions further comprising applying a threshold to task objectives associated with the first input, wherein task objectives below the threshold are not implemented. | 18. The tangible computer-readable medium of claim 17 , the instructions further comprising applying a threshold to task objectives associated with the first input, wherein task objectives below the threshold are not implemented. 21. The tangible computer-readable medium of claim 18 , wherein if the task objectives below the threshold are not implemented, the instructions further comprising conducting a dialog with the user. | 0.5 |
8,661,339 | 7 | 8 | 7. A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display, cause the device to: display at least a portion of an electronic document at a first magnification level on the display; detect an input indicating a point within an object in the document; and in response to detecting the input: in accordance with a determination that the object includes respective editable text: select a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the respective text at a target text display size; and display the document at the second magnification level; and in accordance with a determination that the object does not include editable text: select a third magnification level different from the second magnification level, wherein the third magnification level is selected so as to display the object at a target object display size; and display the document at the third magnification level. | 7. A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device with a display, cause the device to: display at least a portion of an electronic document at a first magnification level on the display; detect an input indicating a point within an object in the document; and in response to detecting the input: in accordance with a determination that the object includes respective editable text: select a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the respective text at a target text display size; and display the document at the second magnification level; and in accordance with a determination that the object does not include editable text: select a third magnification level different from the second magnification level, wherein the third magnification level is selected so as to display the object at a target object display size; and display the document at the third magnification level. 8. The computer readable storage medium of claim 7 , wherein the second magnification level is selected without reference to a size of the object. | 0.668182 |
10,032,191 | 18 | 33 | 18. A method of a networked device comprising: associating with a client device executing a sandboxed application by way of a sandbox reachable service executing on the networked device using a communication provided by the networked device, the client device constraining an executable environment in a security sandbox and executing the sandboxed application in the constrained executable environment; applying an automatic content recognition algorithm to determine a content identifier of an audio-visual data; associating the content identifier with an advertisement data based on a semantic correlation between a metadata of the advertisement data provided by a content provider and the content identifier; targeting the advertisement data at the client device based on the association of the content identifier with the advertisement data and the association between the client device and the networked device; and improving targeting of the advertisement data in accordance with the association between the client device and the networked device based on embedding a script is in at least one of the client device, a supply-side platform, and a data provider integrated with the supply side platform to enable execution of arbitrary cross-site scripts in the sandboxed application of the client device. | 18. A method of a networked device comprising: associating with a client device executing a sandboxed application by way of a sandbox reachable service executing on the networked device using a communication provided by the networked device, the client device constraining an executable environment in a security sandbox and executing the sandboxed application in the constrained executable environment; applying an automatic content recognition algorithm to determine a content identifier of an audio-visual data; associating the content identifier with an advertisement data based on a semantic correlation between a metadata of the advertisement data provided by a content provider and the content identifier; targeting the advertisement data at the client device based on the association of the content identifier with the advertisement data and the association between the client device and the networked device; and improving targeting of the advertisement data in accordance with the association between the client device and the networked device based on embedding a script is in at least one of the client device, a supply-side platform, and a data provider integrated with the supply side platform to enable execution of arbitrary cross-site scripts in the sandboxed application of the client device. 33. The method of claim 18 , comprising: associating the content identifier with the advertisement data generated through an advertising exchange server based on the content identifier and a public IP address associated with an application requesting the advertisement data, wherein at least one of: a provider of the content identifier receives a compensation when the advertisement data is associated with the audio-visual data based on the public IP address associated with the application requesting the advertisement data, the provider of the content identifier appends at least one of a set of content identifiers from associated clients and a viewing history from the associated clients to a plurality of advertisements and resells the advertisement data back to an advertising exchange based on the appended content identifiers, a capture infrastructure annotates the audio-visual data with at least one of a brand name and a product name by comparing entries in a master database with at least one of a closed captioning data of the audio-visual data and through application of an optical character recognition algorithm to the audio-visual data, the sandboxed application of the client device requests access to at least one of a microphone and a camera on the client device to capture a raw audio/video data, the capture infrastructure processes the raw audio/video data with the at least one of the brand name and the product name by comparing the entries in the master database with at least one of the raw audio/video data and through application of a sensory recognition algorithm of the raw audio/video data, the content identifier is at least one of a music identification, an object identification, a facial identification, and a voice identification, wherein a minimal functionality comprising accessing at least one of a tuner and a stream decoder that identifies at least one of a channel and a content is found in the networked device, the method further comprises producing, through the networked device, at least one of an audio fingerprint and a video fingerprint that is communicated with the capture infrastructure, the capture infrastructure compares the at least one of the audio fingerprint and the video fingerprint with the master database, the capture infrastructure annotates the audio-visual data with a logo name by comparing the entries in the master database with a logo data of the audio-visual data identified using a logo detection algorithm, the capture infrastructure automatically divides the audio-visual data into a series of scenes based on a semantic grouping of actions in the audio-visual data, the audio-visual data is analyzed in advance of a broadcast to determine content identifiers associated with each commercial in the audio-visual data such that advertisements are pre-inserted into the audio-visual data prior to the broadcast, the capture infrastructure applies a time-order algorithm to automatically match the advertisements to the audio-visual data when a correlation pattern is identified by the capture infrastructure with other audio-visual content previously analyzed, the capture infrastructure includes a buffer that is saved to a persistent storage and for which a label is generated to facilitate identification of reoccurring sequences, a post processing operation is at least one of automated through a post-processing algorithm and a crowd-sourced operation using a plurality of users in which a turing test is applied to determine a veracity of an input, a device pairing algorithm is used in which a cookie data associated with a web page visited by a user stored on a browser on the client device is paired with the networked device when the client device is communicatively coupled with the networked device, a transitive public IP matching algorithm is utilized in which at least one of the client device and the networked device communicates each public IP address with any paired entity to the capture infrastructure, a tag that is unconstrained from a same-origin policy is used to automatically load an advertisement in the browser, and the tag is at least one of an image tag, a frame, a iframe, and a script tag. | 0.5 |
8,024,195 | 4 | 5 | 4. The apparatus of claim 1 further comprising a network interface for coupling the kiosk to a network. | 4. The apparatus of claim 1 further comprising a network interface for coupling the kiosk to a network. 5. The apparatus of claim 4 wherein the network comprises the Internet. | 0.704167 |
9,430,453 | 16 | 23 | 16. A document capture system, comprising: a communication or other interface configured to receive a stream of document page images; and a processor coupled to the interface and configured to: obtain the stream of document page images; determine that a sequence of pages in the stream of document page images comprise a single multi-page document; extract data from two or more different pages included in the sequence; determine a document type based at least in part on the extracted data and a data entry forms library; create an instance of a type-specific data entry form based at least in part on the document type; populate the data entry form associated with the multi-page document based at least in part on the data extracted from two or more different pages included in the sequence of pages and the document type; identify, according to one or more validation rules, one or more form fields for which validation of the corresponding data by a user is required, wherein identifying of the one or more form fields for which validation of the corresponding data by a user is required comprises validating a dependent data value according to one or more data values on which the dependent data value depends, wherein the one or more data values on which the dependent data value depends are extracted from a page of the multi-page document that is different from a page of the multi-page document from which the dependent data value is extracted; and provide, to the user, the one or more form fields for which validation of the corresponding data is required. | 16. A document capture system, comprising: a communication or other interface configured to receive a stream of document page images; and a processor coupled to the interface and configured to: obtain the stream of document page images; determine that a sequence of pages in the stream of document page images comprise a single multi-page document; extract data from two or more different pages included in the sequence; determine a document type based at least in part on the extracted data and a data entry forms library; create an instance of a type-specific data entry form based at least in part on the document type; populate the data entry form associated with the multi-page document based at least in part on the data extracted from two or more different pages included in the sequence of pages and the document type; identify, according to one or more validation rules, one or more form fields for which validation of the corresponding data by a user is required, wherein identifying of the one or more form fields for which validation of the corresponding data by a user is required comprises validating a dependent data value according to one or more data values on which the dependent data value depends, wherein the one or more data values on which the dependent data value depends are extracted from a page of the multi-page document that is different from a page of the multi-page document from which the dependent data value is extracted; and provide, to the user, the one or more form fields for which validation of the corresponding data is required. 23. The system of claim 16 , wherein for each extracted value a corresponding location on the page from which the value was extracted is saved. | 0.787834 |
8,234,704 | 1 | 4 | 1. A system comprising: a plurality of security sensors distributed throughout a plurality of sites, each sensor configured to generate a sensor signal in response to a defined event, wherein the sensor signal is provided in a native format proprietary to a manufacturer of the respective sensor; a central security management processor coupled to the plurality of security sensors, configured to receive sensor signals from each of the plurality of security sensors and configured to manage individual user profiles and their respective access privileges and credentials in the system; a normalization module configured to normalize the sensor signal data in accordance with a defined data mapping scheme by mapping the sensor signal data from each security sensor in the native format of each manufacturer to a common format, the common format including a data object and processing information for the sensor signal, the normalization module further configured to generate unique physical access privileges and credentials to exclusively map a user's profile to a spatial hierarchy of physical sites along with security devices of the system, wherein the unique physical access credentials maintain a common representation of the user's identity across the plurality of sites and to associate specific user identities with respective actionable events; a visual policy manager having a rules definition component configured to define, at design time, physical security policies in the context of user profiles at all sites through actionable representations of physical, network and information technology resources of the sites, wherein the security policies define standardized rule definitions through visual rules depicted by live objects that contain attributes to define their spatial relationship to the actionable representations, and that are applied to the actionable events normalized to the common format to produce normalized event data; and a signal processing component applying, at run time, the defined standardized rules comprising condition-action sequences including relevant transformation and routing rules to the normalized signal data and to invoke the defined responses to the actionable events in order to maintain user profiles and physical security states across the plurality of sites and to resolve the actionable events through the associated specific user identities. | 1. A system comprising: a plurality of security sensors distributed throughout a plurality of sites, each sensor configured to generate a sensor signal in response to a defined event, wherein the sensor signal is provided in a native format proprietary to a manufacturer of the respective sensor; a central security management processor coupled to the plurality of security sensors, configured to receive sensor signals from each of the plurality of security sensors and configured to manage individual user profiles and their respective access privileges and credentials in the system; a normalization module configured to normalize the sensor signal data in accordance with a defined data mapping scheme by mapping the sensor signal data from each security sensor in the native format of each manufacturer to a common format, the common format including a data object and processing information for the sensor signal, the normalization module further configured to generate unique physical access privileges and credentials to exclusively map a user's profile to a spatial hierarchy of physical sites along with security devices of the system, wherein the unique physical access credentials maintain a common representation of the user's identity across the plurality of sites and to associate specific user identities with respective actionable events; a visual policy manager having a rules definition component configured to define, at design time, physical security policies in the context of user profiles at all sites through actionable representations of physical, network and information technology resources of the sites, wherein the security policies define standardized rule definitions through visual rules depicted by live objects that contain attributes to define their spatial relationship to the actionable representations, and that are applied to the actionable events normalized to the common format to produce normalized event data; and a signal processing component applying, at run time, the defined standardized rules comprising condition-action sequences including relevant transformation and routing rules to the normalized signal data and to invoke the defined responses to the actionable events in order to maintain user profiles and physical security states across the plurality of sites and to resolve the actionable events through the associated specific user identities. 4. The system of claim 1 wherein the physical security policies comprise rules consisting of virtual objects representing personnel and physical assets of the site and events involving the personnel and physical assets, wherein each rule has an associated action and one rule is applied at a time to the normalized event data in a sequential order dictated by one of a defined rule execution order or a top to bottom order based on event time. | 0.5 |
9,898,580 | 1 | 2 | 1. A method comprising: extracting, from a text documenting a clinician's encounter with a single patient, a set of one or more clinical facts representing one or more abstract semantic concepts, wherein the extracting comprises analyzing the text, via a natural language understanding engine, to identify a set of one or more features of at least a portion of the text, and correlating the set of features to the one or more abstract semantic concepts; wherein the one or more abstract semantic concepts comprise a first diagnosis that the clinician, in the text, indicated that the patient exhibited; wherein the first diagnosis is a generic diagnosis representing a class of a plurality of more specific subdiagnoses of the first diagnosis; wherein the method further comprises: analyzing a history record comprising data indicative of the patient's history to determine an additional fact without needing to request input of the additional fact; analyzing the set of one or more clinical facts and the additional fact, using at least one processor, to generate one or more hypotheses for a second diagnosis, exhibited by the patient and not documented in the text, the second diagnosis being a particular one of the plurality of more specific subdiagnoses of the first diagnosis that the clinician indicated that the patient exhibited; and presenting, to a user, the generated at least one of the one or more hypotheses. | 1. A method comprising: extracting, from a text documenting a clinician's encounter with a single patient, a set of one or more clinical facts representing one or more abstract semantic concepts, wherein the extracting comprises analyzing the text, via a natural language understanding engine, to identify a set of one or more features of at least a portion of the text, and correlating the set of features to the one or more abstract semantic concepts; wherein the one or more abstract semantic concepts comprise a first diagnosis that the clinician, in the text, indicated that the patient exhibited; wherein the first diagnosis is a generic diagnosis representing a class of a plurality of more specific subdiagnoses of the first diagnosis; wherein the method further comprises: analyzing a history record comprising data indicative of the patient's history to determine an additional fact without needing to request input of the additional fact; analyzing the set of one or more clinical facts and the additional fact, using at least one processor, to generate one or more hypotheses for a second diagnosis, exhibited by the patient and not documented in the text, the second diagnosis being a particular one of the plurality of more specific subdiagnoses of the first diagnosis that the clinician indicated that the patient exhibited; and presenting, to a user, the generated at least one of the one or more hypotheses. 2. The method of claim 1 , wherein the text comprises a free-form narration of the patient encounter provided by the clinician. | 0.781034 |
10,002,130 | 12 | 14 | 12. The method of claim 1 , wherein converting, utilizing one or more processors, the first utterance to first text is performed at a first server remote from the electronic device. | 12. The method of claim 1 , wherein converting, utilizing one or more processors, the first utterance to first text is performed at a first server remote from the electronic device. 14. The method of claim 12 , wherein encapsulating, utilizing one or more processors, the converted first text in a first rheme object is performed at a second server. | 0.502976 |
8,571,872 | 14 | 15 | 14. The non-transitory computer-readable storage medium of claim 13 , further comprising instructions that, when executed, provide content to the user based at least in part upon the additional processing function. | 14. The non-transitory computer-readable storage medium of claim 13 , further comprising instructions that, when executed, provide content to the user based at least in part upon the additional processing function. 15. The non-transitory computer-readable storage medium of claim 14 , wherein the content comprises an advertisement. | 0.5 |
9,990,679 | 5 | 6 | 5. The method of claim 4 , wherein the social graph includes an explicit social graph connection that indicates the third social network object as a page item of the second social network object, and wherein the second social network object is a social network page and the page item is a content item, a widget, or interactive multimedia. | 5. The method of claim 4 , wherein the social graph includes an explicit social graph connection that indicates the third social network object as a page item of the second social network object, and wherein the second social network object is a social network page and the page item is a content item, a widget, or interactive multimedia. 6. The method of claim 5 , wherein the user interaction is an activation action or a reference action; and wherein the activation action indicates the first social network object activating a function of the page item and the reference action indicates the first social network object publishing content to the social network system that references the third social network object. | 0.5 |
7,685,155 | 1 | 6 | 1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema. | 1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema. 6. The method of claim 1 , wherein the plurality of attributes describing the one or more classes further comprises one or more of name, base class, persistence service assembly, and paths. | 0.664894 |
9,983,869 | 6 | 7 | 6. The medium of claim 1 , wherein the attribute of the execution context comprises at least one of: a programming language, a target architecture, a host platform, and an execution model. | 6. The medium of claim 1 , wherein the attribute of the execution context comprises at least one of: a programming language, a target architecture, a host platform, and an execution model. 7. The medium of claim 6 , wherein the wrapper is a host-platform-specific wrapper that calls execution context independent code, the execution context independent code implementing the requested component. | 0.5 |
9,788,055 | 1 | 11 | 1. A computer-implemented method, comprising: at an electronic device that includes a processor and memory, automatically and without user interaction at the electronic device: streaming a media program to a first client device for display on the first client device; receiving a content search request associated with the media program displayed on the first client device, wherein the content search request is received from a second client device that is communicatively coupled to the first client device; obtaining an image of what is being displayed on the first client device by capturing screen display data associated with the media program displayed on the first client device; in response to the content search request: after obtaining the image of what is being displayed on the first client device: analyzing the obtained image for one or more predefined indicators of a program information overlay including information about the media program, wherein the program information overlay is distinct from the media program; in response to the analysis, determining whether the one or more predefined indicators are present in the obtained image; and in response to determining that the obtained image includes the one or more predefined indicators, extracting text displayed on the program information overlay in the obtained image, wherein the extracted text is associated with the media program; generating search terms from the extracted text; performing an Internet search based on at least some of the generated search terms to identify content associated with the media program; and transmitting the results of the Internet search to the second screen client device for concurrent display thereon when the media program is displayed on the first client device. | 1. A computer-implemented method, comprising: at an electronic device that includes a processor and memory, automatically and without user interaction at the electronic device: streaming a media program to a first client device for display on the first client device; receiving a content search request associated with the media program displayed on the first client device, wherein the content search request is received from a second client device that is communicatively coupled to the first client device; obtaining an image of what is being displayed on the first client device by capturing screen display data associated with the media program displayed on the first client device; in response to the content search request: after obtaining the image of what is being displayed on the first client device: analyzing the obtained image for one or more predefined indicators of a program information overlay including information about the media program, wherein the program information overlay is distinct from the media program; in response to the analysis, determining whether the one or more predefined indicators are present in the obtained image; and in response to determining that the obtained image includes the one or more predefined indicators, extracting text displayed on the program information overlay in the obtained image, wherein the extracted text is associated with the media program; generating search terms from the extracted text; performing an Internet search based on at least some of the generated search terms to identify content associated with the media program; and transmitting the results of the Internet search to the second screen client device for concurrent display thereon when the media program is displayed on the first client device. 11. The method of claim 1 , wherein generating search terms comprises: identifying noun phrases in the extracted text; and selecting a threshold number of the noun phrases to be search terms. | 0.780963 |
9,959,356 | 10 | 11 | 10. The non-transitory, computer accessible memory medium of claim 8 , wherein the program instructions are further executable to: receive further user input from the user for a second ranking function, wherein the ranking functions are usable for a plurality of different search contexts. | 10. The non-transitory, computer accessible memory medium of claim 8 , wherein the program instructions are further executable to: receive further user input from the user for a second ranking function, wherein the ranking functions are usable for a plurality of different search contexts. 11. The non-transitory, computer accessible memory medium of claim 10 , wherein the different search contexts comprise an autocomplete search context or a full text search context. | 0.5 |
5,587,918 | 1 | 21 | 1. A circuit pattern comparison apparatus for extracting portions matched to a designated predetermined search pattern from an object of comparison represented by a circuit network having a set of nodes and node-to-node arcs or links, comprising: search pattern editing means for schematically describing said designated predetermined search pattern having a plurality of nodes; comparison order designating means for designating a comparison order of the nodes contained in the designated predetermined search pattern; search code synthesizing means for synthesizing at least one search code by subjecting, to code conversion, said designated predetermined search pattern schematically described by said search pattern editing means; comparing means for comparing the designated predetermined search pattern to the object of comparison utilizing the at least one search code; and extracting means for extracting at least one portion of the object of comparison matched to said designated predetermined search pattern. | 1. A circuit pattern comparison apparatus for extracting portions matched to a designated predetermined search pattern from an object of comparison represented by a circuit network having a set of nodes and node-to-node arcs or links, comprising: search pattern editing means for schematically describing said designated predetermined search pattern having a plurality of nodes; comparison order designating means for designating a comparison order of the nodes contained in the designated predetermined search pattern; search code synthesizing means for synthesizing at least one search code by subjecting, to code conversion, said designated predetermined search pattern schematically described by said search pattern editing means; comparing means for comparing the designated predetermined search pattern to the object of comparison utilizing the at least one search code; and extracting means for extracting at least one portion of the object of comparison matched to said designated predetermined search pattern. 21. A circuit pattern comparison apparatus according to claim 1, further comprising: normal comparison order knowledge input means for inputting normal comparison order knowledge independent of an individual pattern for the comparison order; and comparison order synthesizing means for combining the normal comparison order knowledge input from the normal comparison order knowledge input means and the comparison order designated by said comparison order designating means and for synthesizing a new comparison order, wherein said comparing means includes means for comparing said designated predetermined comparison pattern from the object of comparison in accordance with the new comparison order synthesized by said comparison order synthesizing means. | 0.5 |
9,219,746 | 1 | 4 | 1. A method, comprising: receiving, by a risk identification system including at least one computing device having at least one processor and at least one memory coupled to the processor, a string of terms; determining, by the at least one computing device of the risk identification system, whether the string of terms includes at least one word matching a keyword of a keyword listing; responsive to determining that the string of terms includes at least one word matching the keyword, identifying, by the risk identification system, at least a noun and a verb in the string of terms; identifying, by the at least one computing device of the risk identification system, a category of risk associated with the identified noun and a category of risk associated with the identified verb; determining, by the at least one computing device of the risk identification system, whether the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are a same category of risk; responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are the same category, determining, by the risk identification system, a first risk rating of the received string of terms including the identified noun and the identified verb, the first risk rating being based on the identified noun, the identified verb and the same category; and responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are different categories, determining, by the risk identification system, a second risk rating of the received string of terms including the identified noun and the identified verb, the second risk rating being based on the identified noun, the identified verb, the identified category of risk associated with the noun and the identified category of risk associated with the verb, the second risk rating being different from the first risk rating. | 1. A method, comprising: receiving, by a risk identification system including at least one computing device having at least one processor and at least one memory coupled to the processor, a string of terms; determining, by the at least one computing device of the risk identification system, whether the string of terms includes at least one word matching a keyword of a keyword listing; responsive to determining that the string of terms includes at least one word matching the keyword, identifying, by the risk identification system, at least a noun and a verb in the string of terms; identifying, by the at least one computing device of the risk identification system, a category of risk associated with the identified noun and a category of risk associated with the identified verb; determining, by the at least one computing device of the risk identification system, whether the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are a same category of risk; responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are the same category, determining, by the risk identification system, a first risk rating of the received string of terms including the identified noun and the identified verb, the first risk rating being based on the identified noun, the identified verb and the same category; and responsive to determining that the identified category of risk associated with the identified noun and the identified category of risk associated with the identified verb are different categories, determining, by the risk identification system, a second risk rating of the received string of terms including the identified noun and the identified verb, the second risk rating being based on the identified noun, the identified verb, the identified category of risk associated with the noun and the identified category of risk associated with the verb, the second risk rating being different from the first risk rating. 4. The method of claim 1 , further including identifying, by the at least one computing device of the risk identification system, an additional action to implement based on the identified risk rating. | 0.822695 |
8,640,110 | 14 | 15 | 14. A system as in claim 11 , wherein the operations further comprise executing, based on the response of the plurality of pseudo-functional entities, changes to at least one of the plurality of pseudo-structural entities. | 14. A system as in claim 11 , wherein the operations further comprise executing, based on the response of the plurality of pseudo-functional entities, changes to at least one of the plurality of pseudo-structural entities. 15. A system as in claim 14 , wherein the operations further comprise: generating a call of the plurality of pseudo-functional entities; and logging information concerning the call of the plurality of pseudo-functional entities. | 0.5 |
8,782,071 | 9 | 17 | 9. A method comprising: periodically analyzing one or more data sources to identify a plurality of prior queries as fresh queries, wherein each of the prior queries was submitted as a search query a number of times during a recent time period and satisfies a criterion, wherein the criterion is a rate of change in query frequency during the time period, a deviation from an expected query frequency during the time period, or a threshold number of occurrences of the query during the time period; in response to receiving a user query from a user, selecting from the fresh queries a plurality of queries that match the user query; ranking the selected plurality of queries, wherein the selected plurality of queries are ranked based on one or more of the data source of each selected query, a quality of results associated with each of the selected queries, or a profile of the user; and providing one or more of the selected queries as related search suggestions for the user query based on the ranking. | 9. A method comprising: periodically analyzing one or more data sources to identify a plurality of prior queries as fresh queries, wherein each of the prior queries was submitted as a search query a number of times during a recent time period and satisfies a criterion, wherein the criterion is a rate of change in query frequency during the time period, a deviation from an expected query frequency during the time period, or a threshold number of occurrences of the query during the time period; in response to receiving a user query from a user, selecting from the fresh queries a plurality of queries that match the user query; ranking the selected plurality of queries, wherein the selected plurality of queries are ranked based on one or more of the data source of each selected query, a quality of results associated with each of the selected queries, or a profile of the user; and providing one or more of the selected queries as related search suggestions for the user query based on the ranking. 17. The method of claim 9 , comprising filtering the plurality of prior queries wherein filtering the prior queries includes filtering the prior queries based on the one or more data sources. | 0.676271 |
5,493,678 | 15 | 16 | 15. The method of claim 14, wherein each of said data elements in said subtrees is classified into a type category and wherein the method further comprises the step of specifying permitted connections between data elements, said permitted connections defining the types of data elements that may be connected and the type of relationships permitted between types of data elements. | 15. The method of claim 14, wherein each of said data elements in said subtrees is classified into a type category and wherein the method further comprises the step of specifying permitted connections between data elements, said permitted connections defining the types of data elements that may be connected and the type of relationships permitted between types of data elements. 16. The method of claim 15, wherein the connecting steps of steps (b)-(d) are performed only if a permitted relationship is established. | 0.5 |
8,365,139 | 10 | 18 | 10. A storage for holding computer-executable instructions, the instructions comprising instructions for: providing a coding standard in a graphical modeling environment; applying the coding standard to at least a portion of a graphical model in the graphical modeling environment to detect a violating segment of the graphical model that violates the coding standard; displaying the violating segment of the graphical model differently than a non-violating segment of the graphical model; displaying information on violation of the coding standard associated with the violating segment of the graphical model automatically generating a coding standard compliant intermediate representation of the graphical model; compiling the graphical model for execution using the coding standard compliant intermediate representation of the graphical model; and generating code for the compiled graphical model. | 10. A storage for holding computer-executable instructions, the instructions comprising instructions for: providing a coding standard in a graphical modeling environment; applying the coding standard to at least a portion of a graphical model in the graphical modeling environment to detect a violating segment of the graphical model that violates the coding standard; displaying the violating segment of the graphical model differently than a non-violating segment of the graphical model; displaying information on violation of the coding standard associated with the violating segment of the graphical model automatically generating a coding standard compliant intermediate representation of the graphical model; compiling the graphical model for execution using the coding standard compliant intermediate representation of the graphical model; and generating code for the compiled graphical model. 18. The storage of claim 10 , wherein the compiled graphical model is free of violations of the coding standard. | 0.753304 |
9,438,947 | 19 | 21 | 19. The method of claim 17 , wherein the audio component is selected from the group consisting of: a song, a soundtrack, a voice, and a sound effect. | 19. The method of claim 17 , wherein the audio component is selected from the group consisting of: a song, a soundtrack, a voice, and a sound effect. 21. The method of claim 19 , wherein the visual component is selected from the group consisting of: a scene break, a geographic location, a face, a person, an object, a physical object, and a text. | 0.5 |
9,378,460 | 2 | 7 | 2. The method of claim 1 , wherein producing the set of facts further includes: generating, as a fact of the set of facts, a text string conforming to the provisioning target fact template. | 2. The method of claim 1 , wherein producing the set of facts further includes: generating, as a fact of the set of facts, a text string conforming to the provisioning target fact template. 7. The method of claim 2 , wherein the parameters that specify provisioning operation requirements for the provisioning target include an application identifier identifying an application and lower and upper bounds of a storage utilization of the application, and wherein generating the text string conforming to the provisioning target fact template includes obtaining the application identifier, the lower bound, and the upper bound. | 0.5 |
8,767,825 | 11 | 12 | 11. The system of claim 1 , wherein the resolution transcoding sub-system comprises: a resolution determination module configured to: receive the source video having a first video format and a first resolution; obtain a video coding complexity score of the source video; determine a second resolution of the source video based on the video coding complexity; and an adaptive video encoder configured to encode the source video into an output video having the second resolution and a predetermined video output format. | 11. The system of claim 1 , wherein the resolution transcoding sub-system comprises: a resolution determination module configured to: receive the source video having a first video format and a first resolution; obtain a video coding complexity score of the source video; determine a second resolution of the source video based on the video coding complexity; and an adaptive video encoder configured to encode the source video into an output video having the second resolution and a predetermined video output format. 12. The system of claim 11 , wherein the adaptive video encoder is further configured to encode the source video into an intermediate video having an intermediate video format. | 0.534392 |
8,301,622 | 1 | 6 | 1. An identity analysis and correlation service system, comprising: a tangible, non-transitory, machine-readable medium storing a summary manager service operable to generate a plurality of identity correlation summaries pertaining to a persona, wherein the generated plurality of identity correlation summaries are based at least in part on discovered content corresponding to the persona and analyzed content corresponding to the discovered content, the persona having a semantic position; a semantic analysis service operable to generate the analyzed content, wherein the semantic analysis service is operable to generate the analyzed content based at least in part on a plurality of semantic abstracts, wherein the plurality of semantic abstracts are based at least in part on the discovered content and at least one of persona content corresponding to the persona and community content corresponding to the persona, wherein the community content comprises information pertaining to the persona's involvement with an online community; a data store operable to store the generated plurality of identity correlation summaries; and a dashboard utility configured to graphically display information pertaining to at least some of the generated identity correlation summaries by displaying on a display a plurality of status arrows that show how the discovered content relates to the semantic position of the persona. | 1. An identity analysis and correlation service system, comprising: a tangible, non-transitory, machine-readable medium storing a summary manager service operable to generate a plurality of identity correlation summaries pertaining to a persona, wherein the generated plurality of identity correlation summaries are based at least in part on discovered content corresponding to the persona and analyzed content corresponding to the discovered content, the persona having a semantic position; a semantic analysis service operable to generate the analyzed content, wherein the semantic analysis service is operable to generate the analyzed content based at least in part on a plurality of semantic abstracts, wherein the plurality of semantic abstracts are based at least in part on the discovered content and at least one of persona content corresponding to the persona and community content corresponding to the persona, wherein the community content comprises information pertaining to the persona's involvement with an online community; a data store operable to store the generated plurality of identity correlation summaries; and a dashboard utility configured to graphically display information pertaining to at least some of the generated identity correlation summaries by displaying on a display a plurality of status arrows that show how the discovered content relates to the semantic position of the persona. 6. The identity analysis and correlation service system of claim 1 , further comprising a notification service operable to provide a notification based on the generated plurality of identity correlation summaries. | 0.52027 |
8,738,567 | 15 | 16 | 15. The system as recited in claim 11 , wherein the network file system is accessible as a network service in which the group folder is mounted as a drive or a folder on the client computing devices. | 15. The system as recited in claim 11 , wherein the network file system is accessible as a network service in which the group folder is mounted as a drive or a folder on the client computing devices. 16. The system as recited in claim 15 , wherein to mount the group folder includes initiating executing of a group application as dictated by a semantically defined auto start document. | 0.5 |
9,716,686 | 1 | 2 | 1. A method for obtaining device information comprising: sending a device description request message to a plurality of remote devices, wherein the device description request message comprises indications of criteria for a responding device that is at least one of the plurality of remote devices, wherein the indications of criteria for the responding device comprises: a fabric identifier that identifies a fabric to which the responding device is connected; a device mode that indicates a mode for the responding device; a vendor identifier that identifies a vendor for the responding device; and a product identifier that identifies a product type for the responding device; and receiving a response message from only the responding device using a wireless communication protocol capable of utilizing more than a single frequency band in response to the device description request message that satisfy all criteria indicated in the indications of criteria, wherein the response message includes device description data about the responding device, and the device description data in the response message is encoded in a tag-length-value format. | 1. A method for obtaining device information comprising: sending a device description request message to a plurality of remote devices, wherein the device description request message comprises indications of criteria for a responding device that is at least one of the plurality of remote devices, wherein the indications of criteria for the responding device comprises: a fabric identifier that identifies a fabric to which the responding device is connected; a device mode that indicates a mode for the responding device; a vendor identifier that identifies a vendor for the responding device; and a product identifier that identifies a product type for the responding device; and receiving a response message from only the responding device using a wireless communication protocol capable of utilizing more than a single frequency band in response to the device description request message that satisfy all criteria indicated in the indications of criteria, wherein the response message includes device description data about the responding device, and the device description data in the response message is encoded in a tag-length-value format. 2. The method of claim 1 , wherein the response message comprises information about the responding device, wherein the information indicates whether the responding device can connect to a home alarm panel, a power type for the responding device, the fabric identifier, a device identifier, device features, product revision, manufacture date, a MAC address, or a combination thereof. | 0.571588 |
7,596,568 | 15 | 17 | 15. The method of claim 7 , further comprising receiving a set of parameters. | 15. The method of claim 7 , further comprising receiving a set of parameters. 17. The method of claim 15 , wherein the set of parameters comprises an interpretation generation policy. | 0.5 |
8,477,611 | 10 | 11 | 10. An apparatus for packet classification comprising: a memory for storing a hash table provided with rules for the packet classification; a tuple generator for determining a matching length of how long each field value of one or more fields in an input packet coincides with a field value of a corresponding field stored in a rule set by performing a field-by-field search on the fields in the input packet, generating a tuple list made up of a combination of one or more of the matching length for the respective fields, and selecting particular tuples existing in the rule set from the tuple list; and a packet classifying control for filtering each of the particular tuples selected by the tuple generator by using a Bloom filter to produce positive tuples, and searching for a best matching rule for the input packet by accessing the hash table based on a search pool including exclusively the positive tuples resulting from the filtering. | 10. An apparatus for packet classification comprising: a memory for storing a hash table provided with rules for the packet classification; a tuple generator for determining a matching length of how long each field value of one or more fields in an input packet coincides with a field value of a corresponding field stored in a rule set by performing a field-by-field search on the fields in the input packet, generating a tuple list made up of a combination of one or more of the matching length for the respective fields, and selecting particular tuples existing in the rule set from the tuple list; and a packet classifying control for filtering each of the particular tuples selected by the tuple generator by using a Bloom filter to produce positive tuples, and searching for a best matching rule for the input packet by accessing the hash table based on a search pool including exclusively the positive tuples resulting from the filtering. 11. The apparatus for packet classification in claim 10 , wherein the packet classifying control includes: a hash unit for generating one or more hashing indices for each of the selected tuples, wherein the Bloom filter identifies bit values of entries indicated by the one or more hashing indices to determine the search pool including only the positive tuples resulting from the search; and a rule determiner for accessing hash table entries by using at least one of the one or more hashing indices corresponding to each of the tuples within the search pool to search for the rules stored in the hash table entries and determining the best matching rule from among the rules. | 0.534388 |
9,269,346 | 10 | 14 | 10. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: storing, in a database, voice data, wherein the voice data is associated with a plurality of voices, wherein the plurality of voices are stored within libraries according to emotions; identifying, using user speech exhibited by a user, a user emotion; identifying, according to the user emotion, a first text-to-speech voice of the plurality of voices which are in the database, wherein the first text-to-speech voice has a first emotional content from a first speaker; identifying, according to the user emotion, a second text-to-speech voice of the plurality of voices which are in the database, wherein the second text-to-speech voice has a second emotional content from a second speaker, and wherein the second emotional content is distinct from the first emotional content; and synthesizing synthesized speech using the first text-to-speech voice and the second text-to-speech voice, wherein the synthesized speech mimics the user emotion. | 10. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: storing, in a database, voice data, wherein the voice data is associated with a plurality of voices, wherein the plurality of voices are stored within libraries according to emotions; identifying, using user speech exhibited by a user, a user emotion; identifying, according to the user emotion, a first text-to-speech voice of the plurality of voices which are in the database, wherein the first text-to-speech voice has a first emotional content from a first speaker; identifying, according to the user emotion, a second text-to-speech voice of the plurality of voices which are in the database, wherein the second text-to-speech voice has a second emotional content from a second speaker, and wherein the second emotional content is distinct from the first emotional content; and synthesizing synthesized speech using the first text-to-speech voice and the second text-to-speech voice, wherein the synthesized speech mimics the user emotion. 14. The system of claim 10 , wherein the synthesized speech is synthesized using selected voice units from the database, wherein the selected voice units comprise a first voice unit from the first text-to-speech voice, and comprise a second voice unit from the second text-to-speech voice. | 0.597493 |
8,880,529 | 12 | 16 | 12. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors perform the steps of: maintaining, at a server, a set of tags that have been approved for use in associating tags with content; receiving, at the server, a particular tag associated with a particular item of multimedia content, the particular tag among a plurality of tags from a plurality of users, the plurality of tags associated with particular items of multimedia content; determining, by the server, that the particular tag is not in the set of tags; submitting, by the server, the particular tag to an automated approval process; upon a determination by the automated approval process that the particular tag has not been approved for adding to the set of tags, the server discarding the particular tag; and upon a determination by the automated approval process that the particular tag has been approved for adding to the set of tags, the server updating the set of tags to include the particular tag; providing the set of tags to devices for use in user interfaces for selecting tags. | 12. A non-transitory computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors perform the steps of: maintaining, at a server, a set of tags that have been approved for use in associating tags with content; receiving, at the server, a particular tag associated with a particular item of multimedia content, the particular tag among a plurality of tags from a plurality of users, the plurality of tags associated with particular items of multimedia content; determining, by the server, that the particular tag is not in the set of tags; submitting, by the server, the particular tag to an automated approval process; upon a determination by the automated approval process that the particular tag has not been approved for adding to the set of tags, the server discarding the particular tag; and upon a determination by the automated approval process that the particular tag has been approved for adding to the set of tags, the server updating the set of tags to include the particular tag; providing the set of tags to devices for use in user interfaces for selecting tags. 16. The non-transitory computer-readable storage medium of claim 12 , wherein updating the set of tags to include the particular tag further comprises associating the particular tag with an identification of one or more users who submitted the particular tag. | 0.800769 |
8,756,239 | 4 | 8 | 4. The method of claim 1 , wherein the selected partition of the user-term index comprises a plurality of database shards organized by time, and indexing the term of the post and the post identifier into the selected partition of the user-term index comprises: selecting a record in a most recent database shard of the plurality of database shards, the record comprising the user identifier, the term identifier, and a list of post identifiers; and adding the post identifier into the list of post identifiers of the selected record in the most recent database shard. | 4. The method of claim 1 , wherein the selected partition of the user-term index comprises a plurality of database shards organized by time, and indexing the term of the post and the post identifier into the selected partition of the user-term index comprises: selecting a record in a most recent database shard of the plurality of database shards, the record comprising the user identifier, the term identifier, and a list of post identifiers; and adding the post identifier into the list of post identifiers of the selected record in the most recent database shard. 8. The method of claim 4 , further comprising: determining that all of the shards are filled to capacity; and creating a new shard, and setting the new shard as the most recent database shard. | 0.5 |
7,478,192 | 44 | 48 | 44. An associative memory computer program product according to claim 43 wherein the computer-readable program code that is configured to provide a observer system comprises: computer-readable program code that is configured to provide an entity observer that is configured to observe into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; and computer-readable program code that is configured to provide a document observer that is configured to observe into the network of document associative memory networks, the associations among observed entities in a respective observer input document. | 44. An associative memory computer program product according to claim 43 wherein the computer-readable program code that is configured to provide a observer system comprises: computer-readable program code that is configured to provide an entity observer that is configured to observe into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; and computer-readable program code that is configured to provide a document observer that is configured to observe into the network of document associative memory networks, the associations among observed entities in a respective observer input document. 48. An associative memory computer program product according to claim 44 wherein the computer-readable program code that is configured to provide a processing system further comprises: computer-readable program code that is configured to provide a reader system that is responsive to the input documents and is configured to produce document IDs and document data therefrom; computer-readable program code that is configured to provide a parser that is responsive to the document data and is configured to extract entities from the document data; and computer-readable program code that is configured to provide a context generator that is responsive to the parser and is configured to identify observer entities and observed entities from the entities that are extracted and to provide the observer entities and observed entities to the entity observer and the document observer. | 0.5 |
7,880,730 | 1 | 4 | 1. A text entry system comprising: (a) a user input device comprising an auto-correcting keyboard region comprising a plurality of the members of a character set, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, wherein user interaction with the user input device within the auto-correcting keyboard region determines a location associated with the user interaction and wherein the determined interaction location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined interaction location in the input sequence of interactions, calculates a set of distance values between the interaction locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies any candidate objects in memory, and for each of the identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks the evaluated candidate objects based on the calculated matching metric values if more than one object is identified; and (iii) a selection component for identifying one or more candidate objects according to an evaluated ranking, presenting at least one identified object to the user, and enabling the user to select from amongst said at least one presented object for output to the text display area on the output device. | 1. A text entry system comprising: (a) a user input device comprising an auto-correcting keyboard region comprising a plurality of the members of a character set, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, wherein user interaction with the user input device within the auto-correcting keyboard region determines a location associated with the user interaction and wherein the determined interaction location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined interaction location in the input sequence of interactions, calculates a set of distance values between the interaction locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies any candidate objects in memory, and for each of the identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks the evaluated candidate objects based on the calculated matching metric values if more than one object is identified; and (iii) a selection component for identifying one or more candidate objects according to an evaluated ranking, presenting at least one identified object to the user, and enabling the user to select from amongst said at least one presented object for output to the text display area on the output device. 4. The system of claim 1 , wherein when a key activation event is detected comprising substantially simultaneous activation of a plurality of adjacent discrete keys in the auto-correcting region, a location corresponding to said key activation event is determined as a function of the locations of the simultaneously activated keys, and said determined location is appended to a current input sequence of the locations of the key activation events. | 0.5 |
8,719,519 | 33 | 40 | 33. A non-transitory machine-readable medium having stored thereon data, which if performed by at least one machine, causes the at least one machine to fabricate at least one integrated circuit to perform a method comprising: reading a portion of a data word by a computer processor, wherein the data word includes a plurality of syllables and the reading of the portion of the data word includes: reading a first syllable of the plurality of syllables from a first memory; and reading a second syllable of the plurality of syllables from a second memory, wherein bits of the second syllable are less critical than bits of the first syllable, and the second memory is distinct from the first memory based on at least a physical attribute. | 33. A non-transitory machine-readable medium having stored thereon data, which if performed by at least one machine, causes the at least one machine to fabricate at least one integrated circuit to perform a method comprising: reading a portion of a data word by a computer processor, wherein the data word includes a plurality of syllables and the reading of the portion of the data word includes: reading a first syllable of the plurality of syllables from a first memory; and reading a second syllable of the plurality of syllables from a second memory, wherein bits of the second syllable are less critical than bits of the first syllable, and the second memory is distinct from the first memory based on at least a physical attribute. 40. The machine-readable medium of claim 33 , wherein the less critical bits of the second syllable are processed after processing the bits of the first syllable. | 0.687259 |
8,959,480 | 11 | 19 | 11. A method of unifying one or more declarative rules and a plurality of procedural instructions in a procedural computational system, the method comprising: upon execution, within said procedural computational system, of a procedural instruction that changes one or more variables, detecting said changes to said one or more variables and notifying a declarative computational system that is in communicative coupling with said procedural computational system using a change tracking system that is in communicative coupling with said procedural computational system and said declarative computational system, and updating, within said change tracking system, one or more other variables participating in one or more declarative rules so as to maintain relationships imposed by said one or more rules among said variables, wherein said updating of said one or more other variables is performed prior to execution of other procedural instructions, and wherein said updating of said one or more other variables includes identifying, within said declarative computational system, one or more other declarative rules in which said one or more other variables participate, and propagating, within said declarative computational system, said updating of said one or more other variables to said one or more other declarative rules so as to maintain relationships imposed by said one or more other declarative rules among said variables. | 11. A method of unifying one or more declarative rules and a plurality of procedural instructions in a procedural computational system, the method comprising: upon execution, within said procedural computational system, of a procedural instruction that changes one or more variables, detecting said changes to said one or more variables and notifying a declarative computational system that is in communicative coupling with said procedural computational system using a change tracking system that is in communicative coupling with said procedural computational system and said declarative computational system, and updating, within said change tracking system, one or more other variables participating in one or more declarative rules so as to maintain relationships imposed by said one or more rules among said variables, wherein said updating of said one or more other variables is performed prior to execution of other procedural instructions, and wherein said updating of said one or more other variables includes identifying, within said declarative computational system, one or more other declarative rules in which said one or more other variables participate, and propagating, within said declarative computational system, said updating of said one or more other variables to said one or more other declarative rules so as to maintain relationships imposed by said one or more other declarative rules among said variables. 19. The method of claim 11 , wherein said one or more declarative rules specify patterns of objects related by said rules. | 0.69802 |
4,858,170 | 7 | 9 | 7. A method for rapidly recording vocalized speech comprising spoken words and transcribing said spoken words into commonly readable, text comprising the steps of: assigned an alphabetic shorthand code to said spoken words, said code being derived by a. omitting all silent letters appearing in each said spoken word of said vocalized speech; b. omitting a consonant where two of the same said consonants appear consecutively in the same said spoken word; c. omitting a vowel where two of the same said vowels appear consecutively in the same said spoken word; d. omitting all unaccented vowels from each said spoken word; e. omitting the letter combinations "la" and "ta" in each said spoken word where said spoken word has more than one syllable; f. omitting the letter "d" in each said spoken word where said letter "d" appears after the letter "n" and occurs in the same syllable; g. writing the letter "y" in each said spoken word wherever the "y" sound is heard; h. omitting the letters "t" in each said spoken word where said letter "t" occurs after the letter "s"; i. omitting the letter "t" in each said spoken word where said letter "t" occurs after the letter "x"; j. replacing the letter combination "ct" with the letter "k" in each said spoken word where said letter combination "ct" occurs; and entering into an appropriately programmed data processing system said alphabetic shorthand code to produced said spoken words in typed or printed form. | 7. A method for rapidly recording vocalized speech comprising spoken words and transcribing said spoken words into commonly readable, text comprising the steps of: assigned an alphabetic shorthand code to said spoken words, said code being derived by a. omitting all silent letters appearing in each said spoken word of said vocalized speech; b. omitting a consonant where two of the same said consonants appear consecutively in the same said spoken word; c. omitting a vowel where two of the same said vowels appear consecutively in the same said spoken word; d. omitting all unaccented vowels from each said spoken word; e. omitting the letter combinations "la" and "ta" in each said spoken word where said spoken word has more than one syllable; f. omitting the letter "d" in each said spoken word where said letter "d" appears after the letter "n" and occurs in the same syllable; g. writing the letter "y" in each said spoken word wherever the "y" sound is heard; h. omitting the letters "t" in each said spoken word where said letter "t" occurs after the letter "s"; i. omitting the letter "t" in each said spoken word where said letter "t" occurs after the letter "x"; j. replacing the letter combination "ct" with the letter "k" in each said spoken word where said letter combination "ct" occurs; and entering into an appropriately programmed data processing system said alphabetic shorthand code to produced said spoken words in typed or printed form. 9. The method for recording and transcribing of claim 7 wherein all said spoken words defining days of the week, months of the year, and measurements are replaced with abbreviations utilized in commonly readable text. | 0.5 |
8,332,415 | 19 | 26 | 19. A system comprising: data processing apparatus comprising one or more processors; and a computer-readable medium storing computer software instructions executable by the data processing apparatus to perform operations comprising: determining a first frequency of occurrence of a phrase in a plurality of first text items describing business entities, wherein the first text items are received from a trusted source; determining a first ratio of the first frequency of occurrence to a count of the plurality of first text items by dividing the first frequency by the count of the plurality of first items; determining a second frequency of occurrence of the phrase in a plurality of second text items describing business entities, wherein the second text items are received from an untrusted source; determining a second ratio of the second frequency of occurrence to a count of the plurality of second text items by dividing the second frequency by the count of the plurality of second items; determining a likelihood that text items received from the untrusted source include spam; determining a likelihood that the phrase is spam based at least partially on the first ratio, the second ratio, and the likelihood that text items received from the untrusted source include spam; and determining a likelihood that a different text item received from the untrusted source and that includes the phrase is spam based at least in part on the likelihood that the phrase is spam. | 19. A system comprising: data processing apparatus comprising one or more processors; and a computer-readable medium storing computer software instructions executable by the data processing apparatus to perform operations comprising: determining a first frequency of occurrence of a phrase in a plurality of first text items describing business entities, wherein the first text items are received from a trusted source; determining a first ratio of the first frequency of occurrence to a count of the plurality of first text items by dividing the first frequency by the count of the plurality of first items; determining a second frequency of occurrence of the phrase in a plurality of second text items describing business entities, wherein the second text items are received from an untrusted source; determining a second ratio of the second frequency of occurrence to a count of the plurality of second text items by dividing the second frequency by the count of the plurality of second items; determining a likelihood that text items received from the untrusted source include spam; determining a likelihood that the phrase is spam based at least partially on the first ratio, the second ratio, and the likelihood that text items received from the untrusted source include spam; and determining a likelihood that a different text item received from the untrusted source and that includes the phrase is spam based at least in part on the likelihood that the phrase is spam. 26. The system of claim 19 , wherein the plurality of first text items and the plurality of second text items represent titles of business entities. | 0.865455 |
8,775,465 | 12 | 13 | 12. The system of claim 9 , wherein the document content updater is configured to provide the determined update one or more updates to a document editor that displays the electronic document. | 12. The system of claim 9 , wherein the document content updater is configured to provide the determined update one or more updates to a document editor that displays the electronic document. 13. The system of claim 12 , wherein the document editor is configured to display the section of content in the electronic document with the determined one or more updates made to the section of content. | 0.671521 |
8,676,588 | 1 | 5 | 1. A system for use in processing a plurality of calls coming into a contact center, each of the plurality of calls comprising a streaming voice signal, the system comprising: an interceptor operable to receive the plurality of calls; a recognizer, operably coupled to the interceptor, operable to continuously analyze a call between a caller and a human agent of the plurality of calls to detect, within the streaming voice signal, occurrence of an unprompted predetermined utterance having response-determinative significance to provide a detected utterance; and a treatment processor, operably coupled to the recognizer, operable to determine a responsive action based on the response-determinative significance corresponding to the detected utterance and at least one of historical data and a configuration of the contact center, and further operable to perform the responsive action for the caller without action from the human agent; and wherein the detected utterance indicates that assistance from a third-party, other than the human agent, is needed. | 1. A system for use in processing a plurality of calls coming into a contact center, each of the plurality of calls comprising a streaming voice signal, the system comprising: an interceptor operable to receive the plurality of calls; a recognizer, operably coupled to the interceptor, operable to continuously analyze a call between a caller and a human agent of the plurality of calls to detect, within the streaming voice signal, occurrence of an unprompted predetermined utterance having response-determinative significance to provide a detected utterance; and a treatment processor, operably coupled to the recognizer, operable to determine a responsive action based on the response-determinative significance corresponding to the detected utterance and at least one of historical data and a configuration of the contact center, and further operable to perform the responsive action for the caller without action from the human agent; and wherein the detected utterance indicates that assistance from a third-party, other than the human agent, is needed. 5. The system of claim 1 , wherein the recognizer is further operable to: provide, to the treatment processor, the response-determinative significance corresponding to the detected utterance. | 0.787778 |
9,009,292 | 8 | 9 | 8. The method of claim 1 , wherein the context model is shared by multiple applications executing on one or more computational devices. | 8. The method of claim 1 , wherein the context model is shared by multiple applications executing on one or more computational devices. 9. The method of claim 8 , wherein the one or more computational devices include one or more mobile devices. | 0.642384 |
9,401,153 | 14 | 15 | 14. A method of detecting a watermark in an electronic audio signal, the method comprising: with a programmed processor, classifying the audio signal according to audio type, the classifying including analyzing the audio signal to detect a voiced and an unvoiced sound; based on the audio type, determining with a programmed processor an audio watermark type and insertion method; and with a programmed processor, detecting a watermark of the selected audio watermark type in the audio signal according to the selected insertion method, the detecting including transforming the audio signal into a state or domain from which message symbols are extracted. | 14. A method of detecting a watermark in an electronic audio signal, the method comprising: with a programmed processor, classifying the audio signal according to audio type, the classifying including analyzing the audio signal to detect a voiced and an unvoiced sound; based on the audio type, determining with a programmed processor an audio watermark type and insertion method; and with a programmed processor, detecting a watermark of the selected audio watermark type in the audio signal according to the selected insertion method, the detecting including transforming the audio signal into a state or domain from which message symbols are extracted. 15. The method of claim 14 wherein the classifying comprises discriminating audio segments based on types, including speech and music. | 0.5 |
7,522,075 | 5 | 6 | 5. The method of claim 1 , wherein: the line feed command characters divide the sequence into portions that are visually displayable when received by a user's device, as two or more lines of equal length. | 5. The method of claim 1 , wherein: the line feed command characters divide the sequence into portions that are visually displayable when received by a user's device, as two or more lines of equal length. 6. The method of claim 5 , wherein: each line initiates and terminates with one or more special marker characters. | 0.5 |
8,725,494 | 1 | 12 | 1. A computer-implemented process, comprising: receiving, in a computer memory: data identifying entities described in a document, wherein the document includes a plurality of tokens appearing in an order in the document, and data defining sentiment values assigned to the tokens in the document; and processing the data in the computer memory with a processor to assign a sentiment value to one of the identified entities in the document, by: applying a filter to a sequence of the sentiment values corresponding to a sequence of the tokens in the order the tokens appear in the document, the filter having a width defined by a number of tokens, the entity having a position in the sequence of tokens, the filter providing a combination of contributions of the sentiment values associated with the tokens surrounding the position of the entity in the document within the width of the filter. | 1. A computer-implemented process, comprising: receiving, in a computer memory: data identifying entities described in a document, wherein the document includes a plurality of tokens appearing in an order in the document, and data defining sentiment values assigned to the tokens in the document; and processing the data in the computer memory with a processor to assign a sentiment value to one of the identified entities in the document, by: applying a filter to a sequence of the sentiment values corresponding to a sequence of the tokens in the order the tokens appear in the document, the filter having a width defined by a number of tokens, the entity having a position in the sequence of tokens, the filter providing a combination of contributions of the sentiment values associated with the tokens surrounding the position of the entity in the document within the width of the filter. 12. The computer-implemented process of claim 1 , further comprising: searching for documents in a repository of documents that contain an entity with an associated sentiment value. | 0.8222 |
9,390,706 | 1 | 3 | 1. A system adapted to assist a user, which comprises: a node comprising a processor and a non-transitory computer readable medium operably couples thereto, the non-transitory computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises: instructions that, when executed, receive a user request; instructions that, when executed, retrieve or determine a personality type of the user from three or more personality types based on one or more user requests; instructions that, when executed, determine a set of outputs, wherein the set of outputs comprises a plurality of different modalities of a device and physical actions to control the device, responsive to the received user request; instructions that, when executed, rank the outputs in the set based on the determined personality type of the user; instructions that, when executed, deliver a ranked output to the user request in a modality of the device, wherein the modality of the device is determined based on the personality type and type of the device configured to deliver the output to the user; and instructions that, when executed, determine a distress level or engagement level of the user, or both, based on the ranked output delivered and the modality of delivery, and weight the ranked output for one or more future interactions with the user based on the determined distress level and/or engagement level. | 1. A system adapted to assist a user, which comprises: a node comprising a processor and a non-transitory computer readable medium operably couples thereto, the non-transitory computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises: instructions that, when executed, receive a user request; instructions that, when executed, retrieve or determine a personality type of the user from three or more personality types based on one or more user requests; instructions that, when executed, determine a set of outputs, wherein the set of outputs comprises a plurality of different modalities of a device and physical actions to control the device, responsive to the received user request; instructions that, when executed, rank the outputs in the set based on the determined personality type of the user; instructions that, when executed, deliver a ranked output to the user request in a modality of the device, wherein the modality of the device is determined based on the personality type and type of the device configured to deliver the output to the user; and instructions that, when executed, determine a distress level or engagement level of the user, or both, based on the ranked output delivered and the modality of delivery, and weight the ranked output for one or more future interactions with the user based on the determined distress level and/or engagement level. 3. The system of claim 1 , further comprising instructions that, when executed, extracts one or more communication attributes from the request. | 0.629534 |
9,378,204 | 1 | 3 | 1. A method, in a data processing system comprising a processor and a memory, for performing context based synonym filtering for natural language processing, the method comprising: parsing, by the data processing system, content into one or more conceptual units, wherein each conceptual unit comprises a portion of text of the content that is associated with a single concept; for each conceptual unit in the one or more conceptual units, identifying, by the data processing system, a term in the conceptual unit that has a synonym to be utilized during natural language processing of the content; determining, by the data processing system, a first measure of relatedness of the term to at least one other term in the conceptual unit; determining, by the data processing system, a second measure of relatedness of the synonym of the term to the at least one other term in the conceptual unit; determining, by the data processing system, whether or not to utilize the synonym when performing natural language processing on the conceptual unit, based on the first measure of relatedness and second measure of relatedness; and performing, by the data processing system, natural language processing on the content based on results of determining whether or not to utilize the synonym, wherein the first measure of relatedness is calculated as the sum, from 1 to N, where N is a number of remaining words in the conceptual unit, of the quantity 1/N*(f(Wn, ORIG)), where f( ) is a semantic distance function, W is the set of remaining words in the conceptual unit, and ORIG is the term, and wherein the second measure of relatedness is calculated as the sum, from 1 to N, of the quantity alpha*1/N*(f(Wn, SYN)), where alpha is a constant, and SYN is the synonym, wherein determining whether or not to utilize the synonym when performing natural language processing on the conceptual unit comprises: comparing the first measure of relatedness to the second measure of relatedness using the following relationship: ∑ n = 1 N 1 N f ( W n , ORIG ) ≤ ∑ n = 1 N α 1 N f ( W n , SYN ) { pass fail } ; and determining to utilize the synonym when performing natural language processing on the conceptual unit in response to the relationship being satisfied. | 1. A method, in a data processing system comprising a processor and a memory, for performing context based synonym filtering for natural language processing, the method comprising: parsing, by the data processing system, content into one or more conceptual units, wherein each conceptual unit comprises a portion of text of the content that is associated with a single concept; for each conceptual unit in the one or more conceptual units, identifying, by the data processing system, a term in the conceptual unit that has a synonym to be utilized during natural language processing of the content; determining, by the data processing system, a first measure of relatedness of the term to at least one other term in the conceptual unit; determining, by the data processing system, a second measure of relatedness of the synonym of the term to the at least one other term in the conceptual unit; determining, by the data processing system, whether or not to utilize the synonym when performing natural language processing on the conceptual unit, based on the first measure of relatedness and second measure of relatedness; and performing, by the data processing system, natural language processing on the content based on results of determining whether or not to utilize the synonym, wherein the first measure of relatedness is calculated as the sum, from 1 to N, where N is a number of remaining words in the conceptual unit, of the quantity 1/N*(f(Wn, ORIG)), where f( ) is a semantic distance function, W is the set of remaining words in the conceptual unit, and ORIG is the term, and wherein the second measure of relatedness is calculated as the sum, from 1 to N, of the quantity alpha*1/N*(f(Wn, SYN)), where alpha is a constant, and SYN is the synonym, wherein determining whether or not to utilize the synonym when performing natural language processing on the conceptual unit comprises: comparing the first measure of relatedness to the second measure of relatedness using the following relationship: ∑ n = 1 N 1 N f ( W n , ORIG ) ≤ ∑ n = 1 N α 1 N f ( W n , SYN ) { pass fail } ; and determining to utilize the synonym when performing natural language processing on the conceptual unit in response to the relationship being satisfied. 3. The method of claim 1 , wherein determining whether or not to utilize the synonym when performing natural language processing on the conceptual unit comprises: comparing the first measure of relatedness to the second measure of relatedness; and determining to utilize the synonym when performing natural language processing on the conceptual unit in response to the first measure having a specified relationship to the second measure. | 0.529095 |
10,002,196 | 9 | 14 | 9. A method of searching a collection of electronic documents comprising: replacing a set of synonymous terms within a paragraph with a set of standardized paragraph terms for paragraphs in electronic documents of a collection; associating term weight values with paragraph terms in the sets of standardized paragraph terms, wherein each term weight value is associated with an individual paragraph term; generating a set of search terms in response to receipt of a search query, wherein the search terms are based at least in part on a query string of the search query; replacing the search query with the set of standardized paragraph terms; comparing the set of search terms with the sets of paragraph terms; generating a paragraph score for the paragraphs using the term weight values of the standardized paragraph terms that match one or more of the search terms, wherein each paragraph score is associated with an individual paragraph; generating an overall document score for the electronic documents by combining the paragraph scores of the paragraphs in the electronic documents, wherein each overall document score is associated with an individual electronic document; determining, by a processor, a set of matching documents from the electronic documents associated with the collection based at least in part on the generated overall document scores, wherein the electronic documents within the set of matching documents are sorted by overall document score; and providing the set of matching documents for display. | 9. A method of searching a collection of electronic documents comprising: replacing a set of synonymous terms within a paragraph with a set of standardized paragraph terms for paragraphs in electronic documents of a collection; associating term weight values with paragraph terms in the sets of standardized paragraph terms, wherein each term weight value is associated with an individual paragraph term; generating a set of search terms in response to receipt of a search query, wherein the search terms are based at least in part on a query string of the search query; replacing the search query with the set of standardized paragraph terms; comparing the set of search terms with the sets of paragraph terms; generating a paragraph score for the paragraphs using the term weight values of the standardized paragraph terms that match one or more of the search terms, wherein each paragraph score is associated with an individual paragraph; generating an overall document score for the electronic documents by combining the paragraph scores of the paragraphs in the electronic documents, wherein each overall document score is associated with an individual electronic document; determining, by a processor, a set of matching documents from the electronic documents associated with the collection based at least in part on the generated overall document scores, wherein the electronic documents within the set of matching documents are sorted by overall document score; and providing the set of matching documents for display. 14. The method of claim 9 , wherein the paragraph scores are generated for less than, or equal to, a maximum number of paragraphs. | 0.767857 |
8,271,432 | 1 | 5 | 1. A computerized method for suggesting a product for purchase comprising the steps of: collecting, on a computer, coreference information from a web server serving web pages including a plurality of word groups, each of the word groups comprising a plurality of words, and describing a product in a group of products, the coreference information indicating coreferences in single web sessions of pairs of products in the group of products, the coreference information further indicating a number of a plurality of words across the group of products, a number of occurrences of each word for both coreferenced products of each pair of products, and a number of occurrences of each word for only one coreferenced product of each pair of products; calculating, on a computer, a score for each word of the plurality of words occurring in the plurality of word groups using the coreference information; selecting, on a computer, a subset of the plurality of words based at least in part on the score; performing, on a computer, a dimensionality reduction on the subset; and serving a web page from the web server, the web page including a description of a first product and a recommendation for a second product, the recommendation being based on a result from the performing step. | 1. A computerized method for suggesting a product for purchase comprising the steps of: collecting, on a computer, coreference information from a web server serving web pages including a plurality of word groups, each of the word groups comprising a plurality of words, and describing a product in a group of products, the coreference information indicating coreferences in single web sessions of pairs of products in the group of products, the coreference information further indicating a number of a plurality of words across the group of products, a number of occurrences of each word for both coreferenced products of each pair of products, and a number of occurrences of each word for only one coreferenced product of each pair of products; calculating, on a computer, a score for each word of the plurality of words occurring in the plurality of word groups using the coreference information; selecting, on a computer, a subset of the plurality of words based at least in part on the score; performing, on a computer, a dimensionality reduction on the subset; and serving a web page from the web server, the web page including a description of a first product and a recommendation for a second product, the recommendation being based on a result from the performing step. 5. The method of claim 1 , wherein the coreference record is maintained as an N by N array, where N is a number of products. | 0.92122 |
10,123,725 | 7 | 20 | 7. A method of altering a recipient's ability to hear with a hearing prosthesis implanted in a recipient, comprising: subjecting a recipient who has participated in a plurality of respective temporally spaced aural training tasks to a plurality of respective temporally spaced aural tests, the respective aural tests evoking hearing percepts evoked by the hearing prosthesis; influencing the recipient's commitment to performing subsequent aural training tasks based on first data relating to the aural tests; and at least partially refitting the hearing prosthesis after influencing the recipient's commitment to performing subsequent aural training tasks and after the recipient has engaged in the subsequent aural training tasks. | 7. A method of altering a recipient's ability to hear with a hearing prosthesis implanted in a recipient, comprising: subjecting a recipient who has participated in a plurality of respective temporally spaced aural training tasks to a plurality of respective temporally spaced aural tests, the respective aural tests evoking hearing percepts evoked by the hearing prosthesis; influencing the recipient's commitment to performing subsequent aural training tasks based on first data relating to the aural tests; and at least partially refitting the hearing prosthesis after influencing the recipient's commitment to performing subsequent aural training tasks and after the recipient has engaged in the subsequent aural training tasks. 20. The method of claim 7 , wherein: the action of influencing the recipient's commitment includes presenting second data to the recipient, wherein the second data are data indicating the effects of temporal spacing between respective aural training tasks. | 0.715556 |
8,204,873 | 3 | 13 | 3. A computer implemented method for optimizing a query expression on a database engine of a database server, comprising: sending, by the computer, the query expression to the database engine, wherein the query expression contains a plurality of predicates; initiating, by the computer, query processing of the query expression; incrementing, by the computer, an evaluation counter, wherein the counter increments an evaluation counter value corresponding to a predicate when a predicate evaluation results in a Boolean result; setting, by the computer, a flag within the database engine when the evaluation counter value reaches a threshold value; incrementing, by the computer, a seen counter, wherein the seen counter increments a seen counter value corresponding to each of the plurality of predicates when a predicate is evaluated; assigning, by the computer, a cost value to each predicate of the plurality of predicates determined by a duration of time that a query processor uses to evaluate each predicate; and reordering, by the computer, predicates in the query expression in order of a most efficient predicate with a greatest probability of an early exit of the query expression evaluated first and a least efficient predicate with a lowest probability of an early exit of the query expression evaluated last in the query expression, wherein predicate efficiency is defined as the evaluation counter value divided by a product of the seen counter value and the cost value. | 3. A computer implemented method for optimizing a query expression on a database engine of a database server, comprising: sending, by the computer, the query expression to the database engine, wherein the query expression contains a plurality of predicates; initiating, by the computer, query processing of the query expression; incrementing, by the computer, an evaluation counter, wherein the counter increments an evaluation counter value corresponding to a predicate when a predicate evaluation results in a Boolean result; setting, by the computer, a flag within the database engine when the evaluation counter value reaches a threshold value; incrementing, by the computer, a seen counter, wherein the seen counter increments a seen counter value corresponding to each of the plurality of predicates when a predicate is evaluated; assigning, by the computer, a cost value to each predicate of the plurality of predicates determined by a duration of time that a query processor uses to evaluate each predicate; and reordering, by the computer, predicates in the query expression in order of a most efficient predicate with a greatest probability of an early exit of the query expression evaluated first and a least efficient predicate with a lowest probability of an early exit of the query expression evaluated last in the query expression, wherein predicate efficiency is defined as the evaluation counter value divided by a product of the seen counter value and the cost value. 13. The method of claim 3 , wherein evaluating the efficiency of an ordering of the predicates in the query expression is evaluated during query execution. | 0.761538 |
8,572,013 | 11 | 14 | 11. The system of claim 2 , wherein the data dictionary comprises a plurality of tokens, each of the tokens being associated with a probability for each one of the classifications. | 11. The system of claim 2 , wherein the data dictionary comprises a plurality of tokens, each of the tokens being associated with a probability for each one of the classifications. 14. The system of claim 11 , wherein the item classification application further comprises logic that updates the data dictionary based at least in part on the data associated with the item when the manual confirmation indicates that the identified classification is correct. | 0.762522 |
9,665,551 | 1 | 5 | 1. A computer-implemented method for selecting a subset of a set of comments associated with a group of documents, the method comprising: accessing, at memory locations, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and using a computer processor that is coupled to the memory location and programmed to select the subset: selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function. | 1. A computer-implemented method for selecting a subset of a set of comments associated with a group of documents, the method comprising: accessing, at memory locations, the set of comments and a predetermined annotation probability distribution of annotations for another set of comments associated with another group of documents, wherein the annotation probability distribution specifies biases in the annotations for the other set of comments; and using a computer processor that is coupled to the memory location and programmed to select the subset: selecting the subset based on the annotation probability distribution and an objective function from a supervised-learning technique, wherein the objective function is optimized by maximizing an expression comprising the annotation probability distribution and the objective function. 5. The method of claim 1 , wherein: after selecting the subset, the method further comprises obtaining annotations for the subset by: masking a remainder of the set of comments so that only the subset is presented to reviewers; and receiving the annotations for the subset from the reviewers. | 0.5 |
8,832,047 | 11 | 15 | 11. A computer program product, tangibly embodied in a computer-readable storage medium, operable to cause one or more data processing apparatus to perform operations comprising: receiving, by a server from a client, an offline audit log containing information with respect to modifications made to content provided within a first electronic document that is retained locally at the client; making a comparison of data of the first electronic document with data of a second electronic document to determine whether the first electronic document should supersede the second electronic document in a distributed document control system, wherein the determination is based, at least in part, on the information contained within the offline audit log; and based on the determination, storing information in the distributed document control system that links the first electronic document with the second electronic document in a superior-subordinate relationship such that when a request to modify content provided within the second electronic document is received, the distributed document control system provides authorization to modify content provided within the first electronic document. | 11. A computer program product, tangibly embodied in a computer-readable storage medium, operable to cause one or more data processing apparatus to perform operations comprising: receiving, by a server from a client, an offline audit log containing information with respect to modifications made to content provided within a first electronic document that is retained locally at the client; making a comparison of data of the first electronic document with data of a second electronic document to determine whether the first electronic document should supersede the second electronic document in a distributed document control system, wherein the determination is based, at least in part, on the information contained within the offline audit log; and based on the determination, storing information in the distributed document control system that links the first electronic document with the second electronic document in a superior-subordinate relationship such that when a request to modify content provided within the second electronic document is received, the distributed document control system provides authorization to modify content provided within the first electronic document. 15. The computer program product of claim 11 , wherein the first electronic document comprises a document secured previously by a permissions-broker server, and the offline audit log is received at the permissions-broker server. | 0.663717 |
4,508,447 | 8 | 9 | 8. In an automatic document handling method for recirculating a set of documents sheets seriatim in a page order for copying on a copier imaging system for making precollated copy sheet sets, the improvement for higher speed document circulation for copying at a higher copying rate comprising the steps of: automatically, in a first circulation of the set of documents, separating the set of document sheets into two half-sets of alternate page document sheets and sequentially placing said half-sets respectively in two different document trays; automatically, on the second and subsequent copying circulations of the document set, feeding the document sheets alternately from said two document sheet half-sets in said two document trays, combined in page seriatim order, to be copied at said imaging station at said higher copying rate; and wherein during said second and subsequent, but not the last, copying circulations said document sheets are re-separated into said half-sets after they are copied as they are returned to said two document trays. | 8. In an automatic document handling method for recirculating a set of documents sheets seriatim in a page order for copying on a copier imaging system for making precollated copy sheet sets, the improvement for higher speed document circulation for copying at a higher copying rate comprising the steps of: automatically, in a first circulation of the set of documents, separating the set of document sheets into two half-sets of alternate page document sheets and sequentially placing said half-sets respectively in two different document trays; automatically, on the second and subsequent copying circulations of the document set, feeding the document sheets alternately from said two document sheet half-sets in said two document trays, combined in page seriatim order, to be copied at said imaging station at said higher copying rate; and wherein during said second and subsequent, but not the last, copying circulations said document sheets are re-separated into said half-sets after they are copied as they are returned to said two document trays. 9. The automatic document handling method of claim 8 wherein a sheet is automatically acquired and begins feeding from one said tray simultaneously with the feeding of another sheet out of the other said tray to said imaging station. | 0.719277 |
9,202,467 | 3 | 5 | 3. The method of claim 1 , the method further comprising processing the request in at least a portion of a new window capable of presenting the specified web page and associated with a second connection if the first connection identified as being associated with the grammar is not specified in the data structure. | 3. The method of claim 1 , the method further comprising processing the request in at least a portion of a new window capable of presenting the specified web page and associated with a second connection if the first connection identified as being associated with the grammar is not specified in the data structure. 5. The method of claim 3 , the method further comprising associating the new window with a connection if the data structure does not specify any connection associated with the grammar. | 0.594714 |
9,483,738 | 17 | 18 | 17. The non-transitory computer-readable storage medium of claim 16 , further configured for scoring terms for each of the plurality of media programs based on the trained model to rank topics for each media program. | 17. The non-transitory computer-readable storage medium of claim 16 , further configured for scoring terms for each of the plurality of media programs based on the trained model to rank topics for each media program. 18. The non-transitory computer-readable storage medium of claim 17 , wherein scoring comprises: determining a term frequency for terms found in the textual information for each media program; and scoring the topics for each media program based on the probability distribution of terms for the set of topics in the trained model and the corresponding term frequency. | 0.5 |
4,420,817 | 7 | 8 | 7. The device as claimed in claim 4, wherein the inflection control means comprises: means coupled to the second memory means for storing a particular rule pattern developed from the second memory means; fourth memory means for storing information used to change endings of a word for inflection purposes; second addressing means coupled to the storing means and the fourth memory means for selectively addressing the fourth memory in accordance with the particular rule pattern in the storing means so as to select a type of ending from the fourth memory means; and control means coupled to the fourth memory and the first memory means for inflecting one of the entry words from the first memory means using the ending selected from the fourth memory means. | 7. The device as claimed in claim 4, wherein the inflection control means comprises: means coupled to the second memory means for storing a particular rule pattern developed from the second memory means; fourth memory means for storing information used to change endings of a word for inflection purposes; second addressing means coupled to the storing means and the fourth memory means for selectively addressing the fourth memory in accordance with the particular rule pattern in the storing means so as to select a type of ending from the fourth memory means; and control means coupled to the fourth memory and the first memory means for inflecting one of the entry words from the first memory means using the ending selected from the fourth memory means. 8. The device as claimed in claim 7, further comprising counting means connected to the second detection means for counting the number of output signals developed from the second detection means, the output signals representing the occurrence of inconsistency of the letters between one of the inflected forms and the first word, said counting means continually actuating said second addressing means until no output signals are produced by said second detection means. | 0.5 |
9,734,261 | 6 | 7 | 6. The method of claim 1 further comprising: storing the received client query in a query database; receiving a second client query entered from the client-retrieved instance of the web page; and storing the second client query in the query database and associating the second client query with the client query. | 6. The method of claim 1 further comprising: storing the received client query in a query database; receiving a second client query entered from the client-retrieved instance of the web page; and storing the second client query in the query database and associating the second client query with the client query. 7. The method of claim 6 wherein said retrieving from the database the plurality of queries comprises: determining a query identifier associated with the client query that distinguishes the client query from other client queries; and retrieving from the query database a plurality of queries associated with the query identifier. | 0.5 |
9,135,396 | 31 | 39 | 31. A computer-readable non-transitory storage medium storing program instructions computer-executable to: for each particular item of a plurality of items: determine one or more other items of the plurality of items that are each distinct from but similar to the particular item, wherein said determining is based on accessing data that includes, for each item of the plurality of items, a textual description of the item that describes the item but is not itself an item in the plurality of items; for each given item of the determined one or more other items, identify an item data pair with one member comprising a sequence of text strings from the textual description of the particular item, and the other member comprising another sequence of text strings from the textual description of the given item; subsequent to said identifying, align each identified item data pair, wherein to align the identified item data pair the program instructions are configured to align text in the sequence of text strings from the textual description of the particular item with text in the other sequence of text strings from the textual description of the given item; and for each aligned item data pair, determine one or more misalignments of the aligned item data pair, and assign a similarity score to the aligned item data pair dependent on the one or more misalignments, wherein the similarity score indicates a degree of confidence that the given item and the particular item are distinct variants of each other; and based on a plurality of the aligned item data pairs and similarity scores assigned to each of those aligned item data pairs, determine a variant set comprising multiple ones of the plurality of items, wherein each item of the variant set is determined to be a variant of each other item of the variant set; wherein at least one of the aligned item data pairs comprises multiple misalignments; for each misalignment of the multiple misalignments, determine a respective subscore based on that misalignment; wherein to assign the similarity score to said at least one aligned item data pair, the program instructions are configured to assign a result of a combination of each of said subscores to said at least one aligned item data pair. | 31. A computer-readable non-transitory storage medium storing program instructions computer-executable to: for each particular item of a plurality of items: determine one or more other items of the plurality of items that are each distinct from but similar to the particular item, wherein said determining is based on accessing data that includes, for each item of the plurality of items, a textual description of the item that describes the item but is not itself an item in the plurality of items; for each given item of the determined one or more other items, identify an item data pair with one member comprising a sequence of text strings from the textual description of the particular item, and the other member comprising another sequence of text strings from the textual description of the given item; subsequent to said identifying, align each identified item data pair, wherein to align the identified item data pair the program instructions are configured to align text in the sequence of text strings from the textual description of the particular item with text in the other sequence of text strings from the textual description of the given item; and for each aligned item data pair, determine one or more misalignments of the aligned item data pair, and assign a similarity score to the aligned item data pair dependent on the one or more misalignments, wherein the similarity score indicates a degree of confidence that the given item and the particular item are distinct variants of each other; and based on a plurality of the aligned item data pairs and similarity scores assigned to each of those aligned item data pairs, determine a variant set comprising multiple ones of the plurality of items, wherein each item of the variant set is determined to be a variant of each other item of the variant set; wherein at least one of the aligned item data pairs comprises multiple misalignments; for each misalignment of the multiple misalignments, determine a respective subscore based on that misalignment; wherein to assign the similarity score to said at least one aligned item data pair, the program instructions are configured to assign a result of a combination of each of said subscores to said at least one aligned item data pair. 39. The computer-readable non-transitory storage medium of claim 31 , wherein each of said subscores is configured to be weighted according to a respective configurable weight. | 0.929147 |
9,361,400 | 7 | 11 | 7. A method of initializing an extensible markup language (XML) database, the method comprising: dynamically generating an empty structure for the XML database and code to access and handle objects in the XML database, the dynamically generated XML database structure and code corresponding to an XML file, the dynamically generating comprising: parsing the XML file to extract a plurality of records therefrom, the records arranged in a hierarchical form; creating, for each record extracted from the XML file, a plurality of class objects defining part of the structure for the XML database, each class having associated therewith one or more attributes of the each record; and creating a plurality of handling methods for each of one or more attributes associated with each object within a class, the handling methods defining how data associated with the attributes can be accessed in the database. | 7. A method of initializing an extensible markup language (XML) database, the method comprising: dynamically generating an empty structure for the XML database and code to access and handle objects in the XML database, the dynamically generated XML database structure and code corresponding to an XML file, the dynamically generating comprising: parsing the XML file to extract a plurality of records therefrom, the records arranged in a hierarchical form; creating, for each record extracted from the XML file, a plurality of class objects defining part of the structure for the XML database, each class having associated therewith one or more attributes of the each record; and creating a plurality of handling methods for each of one or more attributes associated with each object within a class, the handling methods defining how data associated with the attributes can be accessed in the database. 11. The method of claim 7 , further comprising: determining whether a class object is a parent class, and for each parent class, creating a vector container in the class object to store the associated child objects. | 0.5 |
8,150,679 | 1 | 9 | 1. An apparatus for facilitating detection that a received text message forms a fraudulent message, said apparatus comprising: a text analyzer configured to analyze a textual portion of the received text message to detect non-native language content; and a detector configured to detect, based upon analysis made by said text analyzer, at least an indicia indicative of whether the received message forms a fraudulent message; in which the detector calculates a likelihood value indicative of a likelihood that the received text message forms a fraudulent message via a weighted function of the textual portion of the text message, non-native grammatical errors therein, non-native usage errors therein, and general errors therein; wherein the detector further calculates weighting factors associated with a number of variables within the weighting function. | 1. An apparatus for facilitating detection that a received text message forms a fraudulent message, said apparatus comprising: a text analyzer configured to analyze a textual portion of the received text message to detect non-native language content; and a detector configured to detect, based upon analysis made by said text analyzer, at least an indicia indicative of whether the received message forms a fraudulent message; in which the detector calculates a likelihood value indicative of a likelihood that the received text message forms a fraudulent message via a weighted function of the textual portion of the text message, non-native grammatical errors therein, non-native usage errors therein, and general errors therein; wherein the detector further calculates weighting factors associated with a number of variables within the weighting function. 9. The apparatus of claim 1 further comprising an alerter configured to generate an alert to alert detection by said detector of indicia indicative that the received message forms a fraudulent message. | 0.712857 |
8,688,456 | 17 | 18 | 17. The computer-readable storage device of claim 16 , the computer-readable storage device having further instructions stored which result in the operations further comprising: generating a website specific language model using the linguistic item and the weighted anchor text. | 17. The computer-readable storage device of claim 16 , the computer-readable storage device having further instructions stored which result in the operations further comprising: generating a website specific language model using the linguistic item and the weighted anchor text. 18. The computer-readable storage device of claim 17 , the computer-readable storage device having yet additional instructions stored which result in the operations further comprising: integrating the website specific language model into the live spoken dialog. | 0.5 |
9,436,755 | 11 | 12 | 11. The method of claim 1 , further comprising: determining a subset of the task indications with corresponding said task association scores that satisfy a threshold task association score indicative of a likely task request; and storing the subset of the task indications as likely task indications. | 11. The method of claim 1 , further comprising: determining a subset of the task indications with corresponding said task association scores that satisfy a threshold task association score indicative of a likely task request; and storing the subset of the task indications as likely task indications. 12. The method of claim 11 , wherein storing the subset of the task indications as likely task indications includes storing, in a database, each of the task indications of the subset and associated said task association scores. | 0.5 |
8,886,624 | 1 | 4 | 1. A search system using an extended keyword pool, the system comprising: a processor including a purchased keyword module configured to generate a purchased keyword set by searching for a keyword having a purchase history through a search advertisement; the processor including an additional keyword module configured to generate an additional keyword set by extracting a keyword from at least one source; the processor including a unified search keyword module configured to generate a unified search keyword set by searching for a keyword having a number of hits greater than a determined number of hits during a determined period; and the processor including a search module configured to, provide an associated keyword or an extended keyword with respect to a search word, using an extended keyword pool, the extended keyword pool being generated such that the purchased keyword set, the additional keyword set, and the unified search keyword set are connected to one another, provide the associated keyword or the extended keyword with respect to the search word based on new keyword scores or associated scores of keywords included in the extended keyword pool, increase the new keyword scores of the keywords included in the unified search keyword set, excluding the keywords included in the purchased keyword set and the additional keyword set, and increase the associated scores of intersection keywords commonly included in the purchased keyword set and the additional keyword set. | 1. A search system using an extended keyword pool, the system comprising: a processor including a purchased keyword module configured to generate a purchased keyword set by searching for a keyword having a purchase history through a search advertisement; the processor including an additional keyword module configured to generate an additional keyword set by extracting a keyword from at least one source; the processor including a unified search keyword module configured to generate a unified search keyword set by searching for a keyword having a number of hits greater than a determined number of hits during a determined period; and the processor including a search module configured to, provide an associated keyword or an extended keyword with respect to a search word, using an extended keyword pool, the extended keyword pool being generated such that the purchased keyword set, the additional keyword set, and the unified search keyword set are connected to one another, provide the associated keyword or the extended keyword with respect to the search word based on new keyword scores or associated scores of keywords included in the extended keyword pool, increase the new keyword scores of the keywords included in the unified search keyword set, excluding the keywords included in the purchased keyword set and the additional keyword set, and increase the associated scores of intersection keywords commonly included in the purchased keyword set and the additional keyword set. 4. The system of claim 1 , wherein the at least one source comprises at least one of news, blogs, Knowledge pages, shopping, site crawling, shopping mall query information, and issue keywords. | 0.883354 |
10,114,817 | 9 | 10 | 9. A method comprising: receiving, from a computing device of a particular user, data about the particular user; storing the data as one or more profile data items in a user profile of the particular user; identifying the one or more profile data items of the particular user, wherein the one or more profile data items are in a first language; translating (a) the one or more profile data items to produce one or more translated profile data items that are in a second language that is different than the first language or (b) a content item that is in the second language to produce a translated content item that is in the first language; performing a comparison between (c) the one or more translated profile data items and the content item that is in the second language or (d) the one or more profile data items and the translated content item; based on the comparison, determining whether to present at least a portion of the content item or a translated version of the portion of the content item to the particular user; causing the portion of the content item or the translated version of the portion of the content item to be presented to the particular user; wherein the method is performed by one or more computing devices. | 9. A method comprising: receiving, from a computing device of a particular user, data about the particular user; storing the data as one or more profile data items in a user profile of the particular user; identifying the one or more profile data items of the particular user, wherein the one or more profile data items are in a first language; translating (a) the one or more profile data items to produce one or more translated profile data items that are in a second language that is different than the first language or (b) a content item that is in the second language to produce a translated content item that is in the first language; performing a comparison between (c) the one or more translated profile data items and the content item that is in the second language or (d) the one or more profile data items and the translated content item; based on the comparison, determining whether to present at least a portion of the content item or a translated version of the portion of the content item to the particular user; causing the portion of the content item or the translated version of the portion of the content item to be presented to the particular user; wherein the method is performed by one or more computing devices. 10. The method of claim 9 , wherein determining whether to present comprises determining whether to present the translated version of the portion of the content item to the particular user. | 0.856601 |
10,002,191 | 2 | 3 | 2. The method of claim 1 , further comprising: receiving audio data; causing a first audio fingerprint of the received audio data to be compared to audio fingerprints corresponding to a plurality of programs; and receiving an identity of a first program of the plurality of programs to which the first audio fingerprint corresponds based on the comparison; wherein the program that is currently being presented is identified based on the received identity of the first program. | 2. The method of claim 1 , further comprising: receiving audio data; causing a first audio fingerprint of the received audio data to be compared to audio fingerprints corresponding to a plurality of programs; and receiving an identity of a first program of the plurality of programs to which the first audio fingerprint corresponds based on the comparison; wherein the program that is currently being presented is identified based on the received identity of the first program. 3. The method of claim 2 , further comprising receiving a portion of the first program that is currently being presented based on a comparison of the first audio fingerprint to a plurality of audio fingerprints associated with the first program, wherein each of the plurality of audio fingerprints associated with the first program correspond to a particular portion of the first program. | 0.5 |
7,711,573 | 466 | 476 | 466. A system for using a computer to improve a precision ratio when searching a resume database, comprising: means for receiving a resume; means for parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; means for storing the resume in the resume database; means for associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; means for creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; means for storing the parsed resume in the resume database; means for sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and means for receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. | 466. A system for using a computer to improve a precision ratio when searching a resume database, comprising: means for receiving a resume; means for parsing the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; means for storing the resume in the resume database; means for associating at least one of said at least one skill or experience-related phrase located in the resume with at least one implied skill or experience-related phrase, wherein a term of experience for each said at least one implied skill or experience-related phrase is the term of experience computed for said at least one of said at least one skill or experience-related phrase, and wherein said at least one skill or experience-related phrase and said at least one implied skill or experience-related phrase are searchable phrases in the resume; means for creating a parsed resume based on the resume, the parsed resume including each searchable phrase in the resume, the term of experience for each searchable phrase, and a relationship between the term of experience and each searchable phrase; means for storing the parsed resume in the resume database; means for sending a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and means for receiving a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 476. The system of claim 466 , wherein said at least one skill or experience-related phrase includes at least one attribute for a candidate. | 0.861933 |
7,865,465 | 1 | 4 | 1. A model edit control system for controlling editing of a data model, the model edit control system comprising: a computer; and a computer readable medium storing instructions, wherein the instructions, when executed by the computer, cause the computer to implement; a model repository manager, wherein the model repository manager is configured to copy a stored model stored in a repository to multiple users for executing actions on multiple model copies in parallel; an action log manager, wherein the action log manager is configured to create a model action log for tracking actions executed on the stored model and to create a current action log for each model copy to record actions executed on the model copy; and a model merger manager, wherein the model merger manager is configured to merge the model copies into the stored model in the repository by playing actions in the current action log against the stored model, wherein the model merger manager comprises: an action player, wherein the action player is configured to play the executed actions in the model copies against the stored model in the repository based on the current action log of each model copy; and a conflict handler, wherein the conflict handler is configured to handle conflict between the stored model in the repository and the model copies based on the action log of each model copy, wherein the conflict handler comprises: a conflict information handler, wherein the conflict information handler is configured to provide information of at least one conflict identified responsive to playing the executed actions to the user of the model copy; and an option handler, wherein the option handler is configured to present options of resolving the at least one conflict and receiving a selected option. | 1. A model edit control system for controlling editing of a data model, the model edit control system comprising: a computer; and a computer readable medium storing instructions, wherein the instructions, when executed by the computer, cause the computer to implement; a model repository manager, wherein the model repository manager is configured to copy a stored model stored in a repository to multiple users for executing actions on multiple model copies in parallel; an action log manager, wherein the action log manager is configured to create a model action log for tracking actions executed on the stored model and to create a current action log for each model copy to record actions executed on the model copy; and a model merger manager, wherein the model merger manager is configured to merge the model copies into the stored model in the repository by playing actions in the current action log against the stored model, wherein the model merger manager comprises: an action player, wherein the action player is configured to play the executed actions in the model copies against the stored model in the repository based on the current action log of each model copy; and a conflict handler, wherein the conflict handler is configured to handle conflict between the stored model in the repository and the model copies based on the action log of each model copy, wherein the conflict handler comprises: a conflict information handler, wherein the conflict information handler is configured to provide information of at least one conflict identified responsive to playing the executed actions to the user of the model copy; and an option handler, wherein the option handler is configured to present options of resolving the at least one conflict and receiving a selected option. 4. The model edit control system as claimed in claim 1 , wherein the action player comprises: an object handler, wherein the object handler is configured to compare each object to be merged in the model copy with objects in the stored model and identify any object to be merged and missing from the stored model. | 0.744681 |
10,032,134 | 2 | 3 | 2. The method of claim 1 further comprising: sending approval requests to the remaining updated set of approvers; receiving responses from the updated set of approvers; and storing the received responses as prior approvals associated with the unique identifier associated with the received request to be applied to future requests associated with the unique identifier. | 2. The method of claim 1 further comprising: sending approval requests to the remaining updated set of approvers; receiving responses from the updated set of approvers; and storing the received responses as prior approvals associated with the unique identifier associated with the received request to be applied to future requests associated with the unique identifier. 3. The method of claim 2 wherein after responses from each of the set of approvers are received, an outcome of the requested decision is received. | 0.5 |
9,710,825 | 19 | 23 | 19. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query having a plurality of query terms; obtaining a plurality of meanings associated with each of the plurality of query terms, including a first plurality of meanings associated with a first query term and a second plurality of meanings associated with a different second query term, wherein each meaning of the plurality of meanings is a sequence of one or more terms having a respective score corresponding to a likelihood of a query term having the meaning; obtaining data representing a semantic space having a plurality of elements, each element being associated with a different respective meaning, and wherein each of the plurality of elements has a connection with at least one other element in the semantic space, wherein the connection between two elements indicates that the two elements have a similar meaning; determining that a first meaning of the first plurality of meanings for the first query term has a connection in the semantic space with a second meaning of the second plurality of meanings for the second query term; in response to determining that the first meaning has a connection in the semantic space with the second meaning, increasing respective scores associated with the first meaning, the second meaning, or both, an increase indicating a higher probability that a respective meaning relates to the query; ranking the plurality of meanings according to the respective scores associated with the plurality of meanings; selecting a highest-ranked meaning of the plurality of meanings; identifying a first element in the semantic space having the highest-ranked meaning; determining a plurality of additional elements in the semantic space that are each located within a threshold semantic distance of the first element; identifying one or more advertisements associated, in the semantic space, with one or more of the additional elements that are located within the threshold semantic distance of the first element, wherein the one or more of the additional elements differ from the plurality of query terms; and providing the identified one or more advertisements in response to receiving the query. | 19. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a query having a plurality of query terms; obtaining a plurality of meanings associated with each of the plurality of query terms, including a first plurality of meanings associated with a first query term and a second plurality of meanings associated with a different second query term, wherein each meaning of the plurality of meanings is a sequence of one or more terms having a respective score corresponding to a likelihood of a query term having the meaning; obtaining data representing a semantic space having a plurality of elements, each element being associated with a different respective meaning, and wherein each of the plurality of elements has a connection with at least one other element in the semantic space, wherein the connection between two elements indicates that the two elements have a similar meaning; determining that a first meaning of the first plurality of meanings for the first query term has a connection in the semantic space with a second meaning of the second plurality of meanings for the second query term; in response to determining that the first meaning has a connection in the semantic space with the second meaning, increasing respective scores associated with the first meaning, the second meaning, or both, an increase indicating a higher probability that a respective meaning relates to the query; ranking the plurality of meanings according to the respective scores associated with the plurality of meanings; selecting a highest-ranked meaning of the plurality of meanings; identifying a first element in the semantic space having the highest-ranked meaning; determining a plurality of additional elements in the semantic space that are each located within a threshold semantic distance of the first element; identifying one or more advertisements associated, in the semantic space, with one or more of the additional elements that are located within the threshold semantic distance of the first element, wherein the one or more of the additional elements differ from the plurality of query terms; and providing the identified one or more advertisements in response to receiving the query. 23. The computer program product of claim 19 , wherein the operations further comprise comparing all of the first plurality of meanings to all of the second plurality of meanings to determine if any pair of meanings has a connection in the semantic space. | 0.697867 |
7,707,553 | 5 | 6 | 5. The method of claim 4 wherein the step of filling the variable fields includes using the template fixed portions of source code which implements a scenario for checking creation of the selected object. | 5. The method of claim 4 wherein the step of filling the variable fields includes using the template fixed portions of source code which implements a scenario for checking creation of the selected object. 6. The method of claim 5 further comprising the computer implemented steps of: creating a deployable object representing the selected object; finding an object with a same key as the created deployable object; checking that the found object is the same as the created deployable object by checking that both objects have the same persisted fields; trying to create another object with the same key; checking that an error or an exception is raised in response to trying to create said another object; and removing the created deployable object. | 0.5 |
8,793,133 | 1 | 2 | 1. A computer implemented method, comprising: displaying by a computing device on a user interface an electronic representation of a document stored by the computing device where a first portion of the document is pre-associated with a first voice model and a remaining portion of the document is not pre-associated with a voice model, with pre-associated and non-pre-associated text being displayed with different indicia to indicate the portions that pre-associated and non-pre-associated text; receiving by the computing device a user-based selection of text corresponding to at least part of the first portion of the document displayed on the user interface; applying, by the computing device, in response to the user-based selection of the at least part of the first portion a first set of indicia to the user-selected first portion of the document; and overwriting the at least part of the pre-association of the first voice model, by the computing device, with a second, different voice model for the user based selection of at the least part of the first portion. | 1. A computer implemented method, comprising: displaying by a computing device on a user interface an electronic representation of a document stored by the computing device where a first portion of the document is pre-associated with a first voice model and a remaining portion of the document is not pre-associated with a voice model, with pre-associated and non-pre-associated text being displayed with different indicia to indicate the portions that pre-associated and non-pre-associated text; receiving by the computing device a user-based selection of text corresponding to at least part of the first portion of the document displayed on the user interface; applying, by the computing device, in response to the user-based selection of the at least part of the first portion a first set of indicia to the user-selected first portion of the document; and overwriting the at least part of the pre-association of the first voice model, by the computing device, with a second, different voice model for the user based selection of at the least part of the first portion. 2. The method of claim 1 wherein words in the first portion are narrated using the second voice model and at least some of the other words in the first portion of the document are narrated using the first voice model. | 0.719638 |
8,914,769 | 9 | 13 | 9. A method for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the method comprising: identifying a server data structure defined according to the first programming language; determining types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client; generating a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; and generating source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. | 9. A method for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the method comprising: identifying a server data structure defined according to the first programming language; determining types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client; generating a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; and generating source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. 13. The method of claim 9 further comprising: compiling the source code to create the client for the server. | 0.861893 |
10,042,934 | 5 | 12 | 5. A system comprising: a first computing system in communication with a second computing system comprising a user interface, the first computing system comprising one or more memory devices and one or more processors, the first computing system configured to: receive, over one or more computer networks from the second computing system, a plurality of elements from the user interface; receive filter criteria over the one or more computer networks from the second computing system, the filter criteria generated by a user manipulating one or more visual characteristics of one or more of the plurality of elements and one or more inferred terms displayed in the user interface, wherein the one or more inferred terms are derived from the plurality of elements using a vectoral analysis algorithm; generate a query in accordance with one or more of the plurality of elements, the one or inferred terms, and the filter criteria; and transmit, over the one or more computer networks, the generated query to a third computing system of a search engine. | 5. A system comprising: a first computing system in communication with a second computing system comprising a user interface, the first computing system comprising one or more memory devices and one or more processors, the first computing system configured to: receive, over one or more computer networks from the second computing system, a plurality of elements from the user interface; receive filter criteria over the one or more computer networks from the second computing system, the filter criteria generated by a user manipulating one or more visual characteristics of one or more of the plurality of elements and one or more inferred terms displayed in the user interface, wherein the one or more inferred terms are derived from the plurality of elements using a vectoral analysis algorithm; generate a query in accordance with one or more of the plurality of elements, the one or inferred terms, and the filter criteria; and transmit, over the one or more computer networks, the generated query to a third computing system of a search engine. 12. The system of claim 5 , wherein the plurality of elements comprise one or more of: keywords; sentences; phrases; paragraphs; documents; photographs; and icons. | 0.710993 |
9,858,348 | 6 | 8 | 6. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for generating a database that stores associations between each of a plurality of media objects and temporal, spatial, social network or topical data, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data or interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media; logic executed by the processor for parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for determining, when the request includes social criteria, media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying, when the request includes topical criteria, topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying, when the request includes temporal criteria, a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. | 6. A system comprising: a processor; a storage medium for tangibly storing thereon program logic for execution by the processor, the program logic comprising: logic executed by the processor for generating a database that stores associations between each of a plurality of media objects and temporal, spatial, social network or topical data, wherein the database includes relationships between specific media objects and metadata sources associated with a specific media object, user profile data, social network data or interaction data; logic executed by the processor for receiving a request from a requesting device associated with a user for media; logic executed by the processor for parsing the request to identify at least two of social criteria, topical criteria, or temporal criteria included in the request, the social criteria describing one or more people or types of people associated with the requested media, the topical criteria describing one or more topics associated with the requested media, and the temporal criteria describing a past time period associated with the requested media; logic executed by the processor for determining, when the request includes social criteria, media associated with the one or more people or types of people defined by the social criteria based on the association; logic executed by the processor for identifying, when the request includes topical criteria, topics associated with the request and determining media associated with the identified topics based on the association; logic executed by the processor for identifying, when the request includes temporal criteria, a time associated with the request and determining media associated with the identified time based on the association; logic executed by the processor for locating a plurality of media files that each match the at least two of social criteria, topical criteria, or temporal criteria included in the request based on the determined media associated with the one or more people or types of people, media associated with the identified topics, or media associated with the identified time; and logic executed by the processor for transmitting the plurality of media files on the playlist over the network to the requesting device. 8. The system of claim 6 wherein the request for media related to a context has a trigger condition and the request is not processed until the trigger condition occurs, wherein the trigger condition is selected from the list: a time, a date, a calendar event, the presence of the requesting device in a physical location, display of an advertisement on the requesting device, selection of an advertisement on the requesting device. | 0.5 |
4,817,156 | 20 | 21 | 20. The method of claim 19, wherein the step of producing smoothed probabilities includes the steps of: (r) dividing the short string of labels into two portions; (s) applying a forward-backward algorithm, which is based on the updated probabilities, to the first portion of labels to generate counts C.sub.1 (F.sub.2 (l), A.sub.ij) and C.sub.1 (A.sub.ij) and a probability P.sub.1 (F.sub.2 (l).vertline.A.sub.ij) for each label output; (t) applying a forward-backward algorithm, which is based on the last update probabilities, to the second portion to generate counts C.sub.2 (F.sub.2 (l), A.sub.ij) and C.sub.2 (A.sub.ij) and a probability P.sub.2 (Fhd 2(l).vertline., A.sub.ij) for each label output, and (u) evaluating a factor .lambda..sub.m to maximize the likelihood the expression: ##EQU29## where P.sub.o represents an initial probability and wherein S.sub.m represents an mth class of M transitions where transitions are classified based on transition count value. | 20. The method of claim 19, wherein the step of producing smoothed probabilities includes the steps of: (r) dividing the short string of labels into two portions; (s) applying a forward-backward algorithm, which is based on the updated probabilities, to the first portion of labels to generate counts C.sub.1 (F.sub.2 (l), A.sub.ij) and C.sub.1 (A.sub.ij) and a probability P.sub.1 (F.sub.2 (l).vertline.A.sub.ij) for each label output; (t) applying a forward-backward algorithm, which is based on the last update probabilities, to the second portion to generate counts C.sub.2 (F.sub.2 (l), A.sub.ij) and C.sub.2 (A.sub.ij) and a probability P.sub.2 (Fhd 2(l).vertline., A.sub.ij) for each label output, and (u) evaluating a factor .lambda..sub.m to maximize the likelihood the expression: ##EQU29## where P.sub.o represents an initial probability and wherein S.sub.m represents an mth class of M transitions where transitions are classified based on transition count value. 21. The method of claim 20, wherein the step of producing the smoothed probabilities further comprises the step of: (v) computing: ##EQU30## wherein .lambda..sub.m is a selectable weighting factor and wherein A.sub.ij represents a transition from a state i to a state j in a phone machine. | 0.5 |
10,108,602 | 18 | 20 | 18. The computer program product of claim 17 wherein the actions further comprise: from the plurality of morphemes, selecting a leading morpheme that corresponds to a first portion of the identified portmanteau and a trailing morpheme that corresponds to a second portion of the identified portmanteau; and analyzing a combined usage of the leading and trailing morphemes, wherein the derived portmanteau definition is based on the combined usage. | 18. The computer program product of claim 17 wherein the actions further comprise: from the plurality of morphemes, selecting a leading morpheme that corresponds to a first portion of the identified portmanteau and a trailing morpheme that corresponds to a second portion of the identified portmanteau; and analyzing a combined usage of the leading and trailing morphemes, wherein the derived portmanteau definition is based on the combined usage. 20. The computer program product of claim 18 wherein the actions further comprise: selecting a leading candidate word from the plurality of candidate words, wherein the leading candidate word corresponds to the leading morpheme; selecting a trailing candidate word from the plurality of candidate words, wherein the trailing candidate word corresponds to the trailing morpheme; and generating a possible definition of the identified portmanteau by combining a first definition that corresponds to the leading candidate word with a second definition that corresponds to the trailing candidate word, wherein the combined usage is based on the generated possible definition. | 0.5 |
7,529,352 | 1 | 2 | 1. A method for routing a call from a caller to an emergency services operator comprising: receiving a plurality of dialed digits, said plurality comprising fewer than seven; determining whether said plurality of dialed digits matches an emergency services number used anywhere in the world; determining a plurality of languages associated with a jurisdiction associated with said emergency number; determining a preferred language of said call from said plurality of languages; routing said call to an emergency services operator position capable of communicating in said preferred language. | 1. A method for routing a call from a caller to an emergency services operator comprising: receiving a plurality of dialed digits, said plurality comprising fewer than seven; determining whether said plurality of dialed digits matches an emergency services number used anywhere in the world; determining a plurality of languages associated with a jurisdiction associated with said emergency number; determining a preferred language of said call from said plurality of languages; routing said call to an emergency services operator position capable of communicating in said preferred language. 2. A method in accordance with claim 1 further comprising: determining a language associated with a jurisdiction wherein the plurality of dialed digits comprises an emergency services number, and wherein said step of routing said call comprises routing said call to an emergency services operator position wherein the determined language is understood. | 0.5 |
9,069,853 | 13 | 15 | 13. A computing system comprising: a network interface configured to couple to a network; a processor coupled to the network interface; and a memory accessible to the processor and storing instructions that, when executed, cause the processor to: receive a user input including a text input and a selection indicating a selected one of a plurality of goal oriented searches from a user device via the network interface, the plurality of goal oriented searches including a patent invalidity search; retrieve a first document based on the text input, the text input including a patent number; extract data from the first document, the extracted data including at least one of a list of citations and a priority date; search one or more data sources using the data from the first document based on the selected one of the plurality of goal oriented searches to produce a set of documents that satisfy multiple criteria defined by the selected one; apply a rule derived from explicit user interactions and implicit user interactions to produce a matrix including highest probability keywords identified from the search results; identify a plurality of search results using a greedy algorithm; retrieve ancillary information from a secondary search of at least one other data source using a query that is related to data from the plurality of search results, the ancillary information including associative data that is not included within the search results; correlate the search results with the ancillary information to identify associations between search results to produce augmented search results; refine the rule based on the data; and filter the set of documents based on the extracted data to produce search results. | 13. A computing system comprising: a network interface configured to couple to a network; a processor coupled to the network interface; and a memory accessible to the processor and storing instructions that, when executed, cause the processor to: receive a user input including a text input and a selection indicating a selected one of a plurality of goal oriented searches from a user device via the network interface, the plurality of goal oriented searches including a patent invalidity search; retrieve a first document based on the text input, the text input including a patent number; extract data from the first document, the extracted data including at least one of a list of citations and a priority date; search one or more data sources using the data from the first document based on the selected one of the plurality of goal oriented searches to produce a set of documents that satisfy multiple criteria defined by the selected one; apply a rule derived from explicit user interactions and implicit user interactions to produce a matrix including highest probability keywords identified from the search results; identify a plurality of search results using a greedy algorithm; retrieve ancillary information from a secondary search of at least one other data source using a query that is related to data from the plurality of search results, the ancillary information including associative data that is not included within the search results; correlate the search results with the ancillary information to identify associations between search results to produce augmented search results; refine the rule based on the data; and filter the set of documents based on the extracted data to produce search results. 15. The system of claim 13 , wherein the memory further comprises instructions executable by the processor to send data related to the selected one of the plurality of goal oriented searches to one or more data sources and to generate a visualization of search results from the selected one of the plurality of goal oriented searches. | 0.5 |
7,596,544 | 11 | 12 | 11. The method of claim 10 wherein said set-expression cardinality estimate is provided by said number of said set-union cardinality estimate multiplied by said second number of first-level hash buckets and divided by said first number of hash buckets. | 11. The method of claim 10 wherein said set-expression cardinality estimate is provided by said number of said set-union cardinality estimate multiplied by said second number of first-level hash buckets and divided by said first number of hash buckets. 12. The method of claim 11 wherein said set-expression witness elements are selected from said first-level hash-buckets having an index higher than the log of said set-union cardinality estimate; and wherein said corresponding pair of first-level hash-buckets are singleton-union and singleton set-expression hash-buckets. | 0.5 |
9,997,157 | 9 | 13 | 9. One or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the computing system to personalize a language model for a particular target user, the computer-executable instructions causing the computing system to: identify a first set of data from usage history associated with the target user, the first set of data comprising at least one entity or user action; analyzing the usage history information for statistical data; map the first set of data to a personalized knowledge source for the target user, wherein the mapping comprises assigning probabilities to entities and relationships in the personalized knowledge source based on the statistical data, thereby providing a probabilistic personalized knowledge source; determine a set of users similar to the target user; map a second set of data to the personalized knowledge source for the target user, the second set of data comprising at least one entity or user action corresponding to the set of users similar to the target user, thereby creating an extended personalized knowledge source, the extended personalized knowledge source comprising a second entity and a triple indicating a relationship between the at least one entity or user action and the second entity, the mapping comprising at least one of incrementing a count of the one or more of the entity or calculating a weight of the one or more of the entity; and utilize the extended personalized knowledge source to build a personal language model for the target user for speech recognition. | 9. One or more computer storage media having computer-executable instructions embodied thereon that, when executed by a computing system having a processor and memory, cause the computing system to personalize a language model for a particular target user, the computer-executable instructions causing the computing system to: identify a first set of data from usage history associated with the target user, the first set of data comprising at least one entity or user action; analyzing the usage history information for statistical data; map the first set of data to a personalized knowledge source for the target user, wherein the mapping comprises assigning probabilities to entities and relationships in the personalized knowledge source based on the statistical data, thereby providing a probabilistic personalized knowledge source; determine a set of users similar to the target user; map a second set of data to the personalized knowledge source for the target user, the second set of data comprising at least one entity or user action corresponding to the set of users similar to the target user, thereby creating an extended personalized knowledge source, the extended personalized knowledge source comprising a second entity and a triple indicating a relationship between the at least one entity or user action and the second entity, the mapping comprising at least one of incrementing a count of the one or more of the entity or calculating a weight of the one or more of the entity; and utilize the extended personalized knowledge source to build a personal language model for the target user for speech recognition. 13. The one or more computer storage media of claim 9 , wherein the set of users share similar interests or intents with the target user. | 0.807584 |
8,266,153 | 8 | 9 | 8. A computer processing system for generating an object relevance display, the system comprising: a computer, including a non-transitory computer readable storage memory and an object ordering processor, wherein the object ordering processor, in response to receiving an object relevance display request comprising a set of objects to display, retrieves a set of stored relevance values associated with the set of objects and sorts the set of objects according to their associated relevance values, wherein a relevance value is calculated based on the number of references to an object wherein calculating each relevance value comprises associating a weight factor with each of a set of metadata sources, calculating a weighted number of references for each of the set of metadata sources by multiplying the number of references determined from a metadata source by the weight factor associated with the metadata source, and calculating the relevance value based on a weighted number of references to the object determined from the set of metadata sources; and a display generator that generates the object relevance display in response to receiving the sorted set of objects, the object relevance display comprising a set of icons representing the sorted set of objects and their associated relevance values. | 8. A computer processing system for generating an object relevance display, the system comprising: a computer, including a non-transitory computer readable storage memory and an object ordering processor, wherein the object ordering processor, in response to receiving an object relevance display request comprising a set of objects to display, retrieves a set of stored relevance values associated with the set of objects and sorts the set of objects according to their associated relevance values, wherein a relevance value is calculated based on the number of references to an object wherein calculating each relevance value comprises associating a weight factor with each of a set of metadata sources, calculating a weighted number of references for each of the set of metadata sources by multiplying the number of references determined from a metadata source by the weight factor associated with the metadata source, and calculating the relevance value based on a weighted number of references to the object determined from the set of metadata sources; and a display generator that generates the object relevance display in response to receiving the sorted set of objects, the object relevance display comprising a set of icons representing the sorted set of objects and their associated relevance values. 9. The computer processing system of claim 8 wherein the object relevance display request further comprises a set of filtering parameters, and the object ordering processor selects a subset of the objects to display based on the set of filtering parameters. | 0.571667 |
10,140,333 | 1 | 12 | 1. A method for performing queries on a search engine, based on input from a user, the method comprising: retrieving database entries from one or more relational databases; flattening the one or more relational databases with a plurality of the database entries; indexing the plurality of flattened database entries to form a full-text search engine index; prompting the user to enter an input; continuously monitoring the user input; each time an input is entered by the user, processing the user input by: computing a set of non-null partial queries in response to the input entered by the user, the non-null partial queries each being both valid on the one or more relational databases and having matching, instantiated records on the one or more relational databases thereby always resulting in non-null responses; associating a structured item to each non-null partial query; allowing the user to select one of the structured items; if the user selects one of the structured items, replacing the user input by the nonnull partial query associated to the selected structured item; when the user validates the input, executing the input as a query; and providing documents to the user corresponding to the executed query. | 1. A method for performing queries on a search engine, based on input from a user, the method comprising: retrieving database entries from one or more relational databases; flattening the one or more relational databases with a plurality of the database entries; indexing the plurality of flattened database entries to form a full-text search engine index; prompting the user to enter an input; continuously monitoring the user input; each time an input is entered by the user, processing the user input by: computing a set of non-null partial queries in response to the input entered by the user, the non-null partial queries each being both valid on the one or more relational databases and having matching, instantiated records on the one or more relational databases thereby always resulting in non-null responses; associating a structured item to each non-null partial query; allowing the user to select one of the structured items; if the user selects one of the structured items, replacing the user input by the nonnull partial query associated to the selected structured item; when the user validates the input, executing the input as a query; and providing documents to the user corresponding to the executed query. 12. The method according to claim 1 , wherein each structured item is presented with highlighting corresponding to the user input. | 0.822404 |
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