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9,489,451 | 10 | 16 | 10. The method of claim 1 further comprises: receiving a composite data definition comprised of two or more data items and at least one dependency between the two or more data items, where each data item has a common meaning for applications that use the data item; assigning a discoverer to each data item associated with the composite data definition, where a discoverer for a given data item is comprised of a group of steps for identifying the given data item in the loosely-structured data; identifying a dependency between the two or more data items associated with the composite data definition; assigning a discoverer to the identified dependency, where a discoverer for a given dependency is comprised of a group of steps for identifying the dependency of data items in the loosely-structured data; iteratively performing the steps of identifying a dependency and assigning a discoverer to the identified dependency for all of the dependencies associated with the composite data definition; receiving input data; and parsing the input data to identify data items by executing discoverers associated with the composite data definition, where the parsing is implemented by computer-executable instructions executed by a computer processor. | 10. The method of claim 1 further comprises: receiving a composite data definition comprised of two or more data items and at least one dependency between the two or more data items, where each data item has a common meaning for applications that use the data item; assigning a discoverer to each data item associated with the composite data definition, where a discoverer for a given data item is comprised of a group of steps for identifying the given data item in the loosely-structured data; identifying a dependency between the two or more data items associated with the composite data definition; assigning a discoverer to the identified dependency, where a discoverer for a given dependency is comprised of a group of steps for identifying the dependency of data items in the loosely-structured data; iteratively performing the steps of identifying a dependency and assigning a discoverer to the identified dependency for all of the dependencies associated with the composite data definition; receiving input data; and parsing the input data to identify data items by executing discoverers associated with the composite data definition, where the parsing is implemented by computer-executable instructions executed by a computer processor. 16. The method of claim 10 further comprises constructing a given validation method which functions to validate a given data item; and associating the given validation method with the discoverer for the given data item, where the given validation method is associated based on an attribute assigned to the given data item. | 0.87738 |
8,508,489 | 18 | 19 | 18. The method of claim 17 wherein said gesture is a stationary pointer contact on said touch surface that exceeds a threshold duration. | 18. The method of claim 17 wherein said gesture is a stationary pointer contact on said touch surface that exceeds a threshold duration. 19. The method of claim 18 wherein said converted handwritten input is displayed on said touch surface at a location generally corresponding to the location of said stationary pointer contact on said touch surface. | 0.930834 |
4,623,985 | 1 | 3 | 1. An electronic translator wherein a first word or words represented in a first language are entered to obtain a second word or words represented in a second language equivalent to the first word or words, comprising: input means for entering the first word or words; first electronic read only memory means for storing a plurality of the first words; second electronic read only memory means for storing a plurality of the second words; access means responsive to said input means for addressing the first memory means for retrieving the input first word or words and for addressing the second memory means for retrieving the second word or words equivalent to the input first word or words; detection means responsive to said access means for detecting that no second word or words in said second memory means corresponds to a particular input first word or words; and holding means responsive to the detection means for holding said particular first word or words without translation or alteration even after addressing said first memory means by said access means. | 1. An electronic translator wherein a first word or words represented in a first language are entered to obtain a second word or words represented in a second language equivalent to the first word or words, comprising: input means for entering the first word or words; first electronic read only memory means for storing a plurality of the first words; second electronic read only memory means for storing a plurality of the second words; access means responsive to said input means for addressing the first memory means for retrieving the input first word or words and for addressing the second memory means for retrieving the second word or words equivalent to the input first word or words; detection means responsive to said access means for detecting that no second word or words in said second memory means corresponds to a particular input first word or words; and holding means responsive to the detection means for holding said particular first word or words without translation or alteration even after addressing said first memory means by said access means. 3. The electronic translator of claim 1, further comprising hold switch means for selectively actuating said holding means. | 0.866594 |
7,565,642 | 8 | 15 | 8. The method of claim 7 in which generating the dependency graph further comprises analyzing the rule set with a business logic generation utility optimized for one of a plurality of target programming languages and generating optimized logic for a selected target programming language. | 8. The method of claim 7 in which generating the dependency graph further comprises analyzing the rule set with a business logic generation utility optimized for one of a plurality of target programming languages and generating optimized logic for a selected target programming language. 15. The method of claim 8 in which the business logic generation utility's generated processing logic comprises a series of calls to a working memory database to retrieve, manipulate and update data. | 0.899291 |
9,495,267 | 10 | 12 | 10. The method of claim 9 , further including: receiving third party annotation information generated by the third party and linking the received third party annotation information with one or more items of the test stimulus information or the test response information; and storing the third party annotation information on storage accessible by the proxy module. | 10. The method of claim 9 , further including: receiving third party annotation information generated by the third party and linking the received third party annotation information with one or more items of the test stimulus information or the test response information; and storing the third party annotation information on storage accessible by the proxy module. 12. The method of claim 10 , further including transmitting the third party annotation information to be displayed to either the tester through the tester interface or the third party through the third party user interface. | 0.915785 |
7,765,157 | 5 | 6 | 5. The method of claim 1 , wherein identifying, in response to the search request and based upon the search text, search results comprises performing a database search of at least one database using the search text to produce the search results. | 5. The method of claim 1 , wherein identifying, in response to the search request and based upon the search text, search results comprises performing a database search of at least one database using the search text to produce the search results. 6. The method of claim 5 , wherein performing the database search of the at least one database using the search text comprises: for each database searched, accessing a database indexing system corresponding to the database using the search text; and producing, based upon the database indexing system access, a database reference as the search results. | 0.759891 |
7,735,621 | 55 | 56 | 55. The Computer readable medium of claim 47 wherein the bill parameter comprises bill orientation. | 55. The Computer readable medium of claim 47 wherein the bill parameter comprises bill orientation. 56. The Computer readable medium of claim 55 where in the bill parameter comprises forward/reverse orientation. | 0.963914 |
8,069,043 | 8 | 9 | 8. The method of claim 7 , further comprising building a higher order tree from the unigram clustering output. | 8. The method of claim 7 , further comprising building a higher order tree from the unigram clustering output. 9. The method of claim 8 , wherein building the higher order tree further comprises: generating history nodes for the higher order tree; and splitting leaves on the higher order tree via domain splits. | 0.887332 |
7,539,982 | 1 | 10 | 1. A method for processing element nodes of an extensible-markup language (XML) script the method comprising: determining that a current element node of the XML script is an argument of an first element node of the XML script, and placing a current stack frame associated with the current element node in a stack above a first stack frame associated with the first element node; determining that the current element node requires evaluation of a new argument of the current element node, the new argument being a new element node of the XML script; inserting a new stack frame associated with the new element node for evaluating the new argument into the stack below the current stack frame associated with the current element node rather than above the current stack frame to simplify relative referencing for evaluation of a subsequent nested argument; evaluating the new argument using the inserted new stack frame; returning a result from evaluation of the new argument to the current element node; and removing the inserted new stack frame from the stack after returning the result from evaluation of the new argument to the current element node and before removing the current stack frame; and repeating the determining, inserting, evaluating returning and removing steps until all the element nodes of the XML script are evaluated. | 1. A method for processing element nodes of an extensible-markup language (XML) script the method comprising: determining that a current element node of the XML script is an argument of an first element node of the XML script, and placing a current stack frame associated with the current element node in a stack above a first stack frame associated with the first element node; determining that the current element node requires evaluation of a new argument of the current element node, the new argument being a new element node of the XML script; inserting a new stack frame associated with the new element node for evaluating the new argument into the stack below the current stack frame associated with the current element node rather than above the current stack frame to simplify relative referencing for evaluation of a subsequent nested argument; evaluating the new argument using the inserted new stack frame; returning a result from evaluation of the new argument to the current element node; and removing the inserted new stack frame from the stack after returning the result from evaluation of the new argument to the current element node and before removing the current stack frame; and repeating the determining, inserting, evaluating returning and removing steps until all the element nodes of the XML script are evaluated. 10. The method of claim 1 wherein the new argument is included in a context of the current stack frame. | 0.924708 |
8,806,455 | 1 | 2 | 1. A computer-implemented method for text processing, comprising: processing at least one body of text comprising semantic elements; recognizing respective syntactic roles of the semantic elements, wherein syntactic roles of the different semantic elements are represented by a given sentence as a hierarchical structure such as a tree, having subordinate and superordinate branches connected at nodes; segmenting the body of text into individual semantic constructs; removing at least one selected semantic element from the semantic constructs, so as to produce respective nuclear semantic constructs; computing respective occurrence frequencies of the nuclear semantic constructs; aggregating similar nuclear constructs, so that frequently occurring nuclear constructs are given high statistical significance; and invoking an action with respect to one or more of the nuclear semantic constructs whose occurrence frequencies meet a predefined condition, wherein removing the at least one selected semantic elements comprises predefining a nuclearization depth, and determining the selected semantic elements to be removed responsively to the predefined nuclearization depth, wherein computing the occurrence frequencies comprises assigning respective weights to occurrences of the nuclear semantic constructs, and computing the occurrence frequencies responsively to the weights. | 1. A computer-implemented method for text processing, comprising: processing at least one body of text comprising semantic elements; recognizing respective syntactic roles of the semantic elements, wherein syntactic roles of the different semantic elements are represented by a given sentence as a hierarchical structure such as a tree, having subordinate and superordinate branches connected at nodes; segmenting the body of text into individual semantic constructs; removing at least one selected semantic element from the semantic constructs, so as to produce respective nuclear semantic constructs; computing respective occurrence frequencies of the nuclear semantic constructs; aggregating similar nuclear constructs, so that frequently occurring nuclear constructs are given high statistical significance; and invoking an action with respect to one or more of the nuclear semantic constructs whose occurrence frequencies meet a predefined condition, wherein removing the at least one selected semantic elements comprises predefining a nuclearization depth, and determining the selected semantic elements to be removed responsively to the predefined nuclearization depth, wherein computing the occurrence frequencies comprises assigning respective weights to occurrences of the nuclear semantic constructs, and computing the occurrence frequencies responsively to the weights. 2. The method according to claim 1 , wherein the body of text comprises transcribed audio of call center sessions. | 0.871622 |
8,326,795 | 1 | 12 | 1. A computer-implemented method comprising: receiving a user input at a computing device, the user input defining behavioral and static aspects of a target process artifact and comprising business process information for use in a specific business process model within an organization, the behavioral aspect comprising inputs for one or more behavioral reasoning processes comprising substitution, auto-completion, and deadlock/liveliness verification; automatically defining a query specification comprising: an axiom component expressing the static aspect using a logical expression, and a process definition component expressing the behavioral aspect using ontologized π-calculus; querying a process artifact library using the query specification, the process artifact library provided as a computer-readable repository that stores one or more of process patterns, models, fragments, and guidelines, the querying comprising: querying the process artifact library relating to the static aspect of the target process artifact to obtain a subset of the process artifact library; after querying, performing π-calculus reasoning, related to the behavioral aspect of the target process, on the subset of the process artifact library; and outputting a candidate process artifact matching the behavioral and static aspects, based on querying the process artifact library. | 1. A computer-implemented method comprising: receiving a user input at a computing device, the user input defining behavioral and static aspects of a target process artifact and comprising business process information for use in a specific business process model within an organization, the behavioral aspect comprising inputs for one or more behavioral reasoning processes comprising substitution, auto-completion, and deadlock/liveliness verification; automatically defining a query specification comprising: an axiom component expressing the static aspect using a logical expression, and a process definition component expressing the behavioral aspect using ontologized π-calculus; querying a process artifact library using the query specification, the process artifact library provided as a computer-readable repository that stores one or more of process patterns, models, fragments, and guidelines, the querying comprising: querying the process artifact library relating to the static aspect of the target process artifact to obtain a subset of the process artifact library; after querying, performing π-calculus reasoning, related to the behavioral aspect of the target process, on the subset of the process artifact library; and outputting a candidate process artifact matching the behavioral and static aspects, based on querying the process artifact library. 12. The method of claim 1 , wherein the query specification further comprises a type indicator indicating whether the candidate process artifact is to be appended to or substituted for an existing process artifact. | 0.832288 |
9,176,642 | 11 | 14 | 11. A computer-implemented method for displaying clusters via a dynamic user interface, comprising: displaying cluster spines, each comprising two or more clusters of documents; providing at least one compass framing at least a portion of one or more of the cluster spines in the display; generating at least one label to identify a concept of one of the framed cluster spines; displaying the label circumferentially around the compass; and changing the concept as the compass moves over others of the cluster spines. | 11. A computer-implemented method for displaying clusters via a dynamic user interface, comprising: displaying cluster spines, each comprising two or more clusters of documents; providing at least one compass framing at least a portion of one or more of the cluster spines in the display; generating at least one label to identify a concept of one of the framed cluster spines; displaying the label circumferentially around the compass; and changing the concept as the compass moves over others of the cluster spines. 14. A method according to claim 11 , further comprising: pinning the labels displayed circumferentially around the compass. | 0.90207 |
8,775,349 | 1 | 34 | 1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions. | 1. A method for producing at least one application description, the method which comprises: reading-in at least one basic document into a computer; analyzing the at least one basic document and thereby constructing a knowledge base with knowledge elements, the knowledge elements thus recognized being at least one data field and/or at least one component, and flagging the knowledge elements at least partly as assumptions; determining at least one conflict-free knowledge partition having a respective set of conflict-free assumptions; producing the at least one application description with a plurality of application blocks from the at least one knowledge partition with the application blocks, and for the purpose of determining the finalized knowledge partitions, generating a graph having nodes and directional and nondirectional edges, wherein the nodes correspond to the assumptions and the directional edges correspond to the prerequisites for the respective assumptions and the nondirectional edges correspond to conflicts between the assumptions. 34. The method according to claim 1 , wherein the basic documents are charts and/or presentation files, and the method comprises producing for each chart a tuple of data fields and a component which encompasses all data fields. | 0.794011 |
8,296,123 | 83 | 84 | 83. The method of claim 78 , further comprising: prior to translating each one of the segments using data from the language model, performing an initial translation of the one segment using data from a different translation resource; and using data from the language model to update the initial translation to produce a final segment translation of the one segment. | 83. The method of claim 78 , further comprising: prior to translating each one of the segments using data from the language model, performing an initial translation of the one segment using data from a different translation resource; and using data from the language model to update the initial translation to produce a final segment translation of the one segment. 84. The method of claim 83 , wherein: the different translation resource is a second language model for the target language that is smaller than the language model. | 0.977063 |
8,515,933 | 16 | 20 | 16. A method for establishing a video database by a host, wherein the host comprises at least a processor, and wherein the processor is configured for: storing a plurality of video bitstreams into a database, wherein the database is stored in a storage device; and establishing meta-data of each of the video bitstreams, wherein each of the meta-data is established by: segmenting the video bitstream according to a scene change point to generate a plurality of shots; indexing the shots by assigning a corresponding index tag to each of the shots according to a content of the shot; and establishing a semantic pattern of each of the shots according to a video feature of the shot, wherein the meta-data at least comprises the index tags and the semantic patterns corresponding to the shots. | 16. A method for establishing a video database by a host, wherein the host comprises at least a processor, and wherein the processor is configured for: storing a plurality of video bitstreams into a database, wherein the database is stored in a storage device; and establishing meta-data of each of the video bitstreams, wherein each of the meta-data is established by: segmenting the video bitstream according to a scene change point to generate a plurality of shots; indexing the shots by assigning a corresponding index tag to each of the shots according to a content of the shot; and establishing a semantic pattern of each of the shots according to a video feature of the shot, wherein the meta-data at least comprises the index tags and the semantic patterns corresponding to the shots. 20. The video database establishing method according to claim 16 , wherein the shots are indexed by assigning the corresponding index tag to each of the shots by adopting a length of the shot. | 0.882064 |
9,646,110 | 7 | 10 | 7. A system of governing information assets managed by an enterprise, the system comprising: a computer processor; and a memory storing an enterprise information asset management application which, when executed on the computer processor, performs an operation comprising: identifying, by an enterprise information asset management application executed on a computing system having at least a processor and a memory, a set of search results responsive to a query requesting a subset of information assets within the enterprise; providing the set of search results; receiving a selection of a first information asset presented in the set of search results; identifying at least a second information asset presented in the set of search results, wherein the first information asset and the second information asset are related to one another by an edge in a semantic graph that represents relationships between the plurality of information assets, wherein the semantic graph associates the plurality of information assets with nodes of the semantic graph, wherein the relationships between nodes in the semantic graph are generated and updated by monitoring user behavior in accessing the plurality of information assets with the set of search results and without requiring user input explicitly specifying to update the relationships, wherein the semantic graph is updated based on a domain ontology; parsing the semantic graph in order to identify at least one information asset selected from: (i) an informal information asset whose relationships satisfy an overuse criterion and (ii) an underused information asset whose relationships satisfy an underuse criterion; and designating the at least one information asset as being overused or underused, whereafter the at least one information asset is formally commissioned or decommissioned. | 7. A system of governing information assets managed by an enterprise, the system comprising: a computer processor; and a memory storing an enterprise information asset management application which, when executed on the computer processor, performs an operation comprising: identifying, by an enterprise information asset management application executed on a computing system having at least a processor and a memory, a set of search results responsive to a query requesting a subset of information assets within the enterprise; providing the set of search results; receiving a selection of a first information asset presented in the set of search results; identifying at least a second information asset presented in the set of search results, wherein the first information asset and the second information asset are related to one another by an edge in a semantic graph that represents relationships between the plurality of information assets, wherein the semantic graph associates the plurality of information assets with nodes of the semantic graph, wherein the relationships between nodes in the semantic graph are generated and updated by monitoring user behavior in accessing the plurality of information assets with the set of search results and without requiring user input explicitly specifying to update the relationships, wherein the semantic graph is updated based on a domain ontology; parsing the semantic graph in order to identify at least one information asset selected from: (i) an informal information asset whose relationships satisfy an overuse criterion and (ii) an underused information asset whose relationships satisfy an underuse criterion; and designating the at least one information asset as being overused or underused, whereafter the at least one information asset is formally commissioned or decommissioned. 10. The system of claim 7 , wherein the operation further comprises: monitoring one of a plurality of users selecting a third information asset presented in the set of search results, and subsequently a fourth information asset presented in the set of search results; and storing an indication of a relationship between the third information asset and the fourth information asset in the semantic graph. | 0.647727 |
9,779,317 | 3 | 4 | 3. The image processing apparatus of claim 2 , wherein the operation interface circuitry further includes a questionnaire result data memory that stores the image information as questionnaire result data, and the second processor is further configured to compile entries for each of the items across pieces of the questionnaire result data. | 3. The image processing apparatus of claim 2 , wherein the operation interface circuitry further includes a questionnaire result data memory that stores the image information as questionnaire result data, and the second processor is further configured to compile entries for each of the items across pieces of the questionnaire result data. 4. The image processing apparatus of claim 3 , wherein the second processor performs control to display a compiled result produced by the second processor. | 0.939595 |
9,203,867 | 4 | 5 | 4. The system of claim 1 , further comprises a privacy editor programmed to provide at least one categorized group of user identity attributes, and to determine a privacy preference for each category. | 4. The system of claim 1 , further comprises a privacy editor programmed to provide at least one categorized group of user identity attributes, and to determine a privacy preference for each category. 5. The system of claim 4 , further comprises: the identity manager is programmed to receive from a service provider environment the security policy having requirements specifying required attributes; and the privacy engine is programmed to identify at least one category referencing the required attributes, and for using the privacy preference of at least one identified category in the evaluation operation. | 0.836661 |
8,375,048 | 34 | 35 | 34. The computer readable storage device of claim 33 , the search results based upon a website associated with at least one of news, local events, sports, an encyclopedia, history, books, movies, or entertainment. | 34. The computer readable storage device of claim 33 , the search results based upon a website associated with at least one of news, local events, sports, an encyclopedia, history, books, movies, or entertainment. 35. The computer readable storage device of claim 34 , the one or more query augmentation terms based at least in part on heuristics. | 0.96665 |
6,029,124 | 1 | 9 | 1. A method of evaluating a speech sample using a computer, the method comprising: receiving training data comprising samples of speech; storing the training data along with identification of speech elements to which portions of the training data are related; receiving a speech sample; performing speech recognition on the speech sample to produce recognition results; and evaluating the recognition results in view of the training data and the identification of the speech elements to which the portions of the training data are related, wherein: performing speech recognition on the speech sample comprises identifying portions of the speech sample to which different speech elements correspond; and evaluating the recognition results comprises comparing a portion of the speech sample identified as corresponding to a particular speech element to one or more portions of the training data identified as corresponding to the particular speech element. | 1. A method of evaluating a speech sample using a computer, the method comprising: receiving training data comprising samples of speech; storing the training data along with identification of speech elements to which portions of the training data are related; receiving a speech sample; performing speech recognition on the speech sample to produce recognition results; and evaluating the recognition results in view of the training data and the identification of the speech elements to which the portions of the training data are related, wherein: performing speech recognition on the speech sample comprises identifying portions of the speech sample to which different speech elements correspond; and evaluating the recognition results comprises comparing a portion of the speech sample identified as corresponding to a particular speech element to one or more portions of the training data identified as corresponding to the particular speech element. 9. The method of claim 1, wherein the training data are associated with different known speakers and evaluating the recognition results comprises determining which of the known speakers is more likely to have produced the speech sample. | 0.781885 |
7,661,124 | 23 | 29 | 23. At a computer system in a Web Services environment, a computer program product for implementing a method of assisting a user in generating a more secure policy document by providing a rule-based tool that automatically selects security conditions for the user's general security criteria such that the user does not have exposure to all security details, the computer program product comprising one or more computer readable storage media having stored thereon computer executable instructions that, when executed by a processor, can cause the messaging system to perform: at a generation phase of the secure policy document: present a set of Web Service security options to a user at a user interface, which abstracts the user from any specific code that will be generated for a secure policy document that satisfies one or more of the set of Web Service security options, the set of Web Service security options including at least an option for communicating using a secure conversation and an option for communicating without using a secure conversation; receive user input selecting a general security criteria from the set of Web Service security options presented, the general security criteria being the option for communicating using a secure conversation; based on the received user input selecting the option for communicating using a secure conversation, access one or more security rules from a repository of extensible security metadata, the one or more security rules corresponding to the general security criteria and relating to client authentication tokens; present a set of Web Service client authentication token options to the user at the user interface, which abstracts the user from any specific code that will be generated for the secure policy document that satisfies one or more of the set of Web Service client authentication tokens to the user at the user interface; receive user input selecting one option from the set of Web Service client authentication token options; based on the received user input select one option from the set of Web Service client authentication token options, accessing one or more security rules from the repository of extensible security metadata, the one or more security rules corresponding to the Web Service client authentication token options and providing more specific rules for implementing the selected option from the set of Web Service client authentication token options; determining whether the secure policy document is a client policy document or a service policy document; and use the one or more security rules corresponding to the general security criteria and to the selected one option to generate the secure policy document in accordance with the general security criteria and the selected one option, wherein generating the secure policy document includes automatically selecting specific security conditions that enforce the general security criteria and selected one option input by the user, and wherein the security conditions that are more specific than the general security criteria and the selected one option input by the user are applied based whether the secure policy document is determined to be a client policy document or a service policy document, such that different one or more security rules are applied in creating the secure policy document when the secure policy document is a client policy document as compared to when the secure policy document is a service policy document. | 23. At a computer system in a Web Services environment, a computer program product for implementing a method of assisting a user in generating a more secure policy document by providing a rule-based tool that automatically selects security conditions for the user's general security criteria such that the user does not have exposure to all security details, the computer program product comprising one or more computer readable storage media having stored thereon computer executable instructions that, when executed by a processor, can cause the messaging system to perform: at a generation phase of the secure policy document: present a set of Web Service security options to a user at a user interface, which abstracts the user from any specific code that will be generated for a secure policy document that satisfies one or more of the set of Web Service security options, the set of Web Service security options including at least an option for communicating using a secure conversation and an option for communicating without using a secure conversation; receive user input selecting a general security criteria from the set of Web Service security options presented, the general security criteria being the option for communicating using a secure conversation; based on the received user input selecting the option for communicating using a secure conversation, access one or more security rules from a repository of extensible security metadata, the one or more security rules corresponding to the general security criteria and relating to client authentication tokens; present a set of Web Service client authentication token options to the user at the user interface, which abstracts the user from any specific code that will be generated for the secure policy document that satisfies one or more of the set of Web Service client authentication tokens to the user at the user interface; receive user input selecting one option from the set of Web Service client authentication token options; based on the received user input select one option from the set of Web Service client authentication token options, accessing one or more security rules from the repository of extensible security metadata, the one or more security rules corresponding to the Web Service client authentication token options and providing more specific rules for implementing the selected option from the set of Web Service client authentication token options; determining whether the secure policy document is a client policy document or a service policy document; and use the one or more security rules corresponding to the general security criteria and to the selected one option to generate the secure policy document in accordance with the general security criteria and the selected one option, wherein generating the secure policy document includes automatically selecting specific security conditions that enforce the general security criteria and selected one option input by the user, and wherein the security conditions that are more specific than the general security criteria and the selected one option input by the user are applied based whether the secure policy document is determined to be a client policy document or a service policy document, such that different one or more security rules are applied in creating the secure policy document when the secure policy document is a client policy document as compared to when the secure policy document is a service policy document. 29. The computer program product of claim 23 , wherein the one or more security rules are abstracted from the user. | 0.900174 |
6,069,622 | 12 | 22 | 12. The method of claim 1, wherein each character has a head portion with at least one facial feature and wherein the interaction event provides an expression indicating a modification of a facial feature of at least one of the characters. | 12. The method of claim 1, wherein each character has a head portion with at least one facial feature and wherein the interaction event provides an expression indicating a modification of a facial feature of at least one of the characters. 22. The method of claim 12, including a prior generated comic panel and wherein determining the placement for each character further comprises determining the placement for each character based upon that character's position in the prior generated comic panel. | 0.953488 |
9,852,363 | 10 | 11 | 10. A system comprising: one or more processors and one or more computer storage media storing instructions that are operable and when executed by the one or more processors, cause the one or more processors to perform operations comprising: obtaining data identifying the particular object category; identifying database images of the objects belonging to the particular object category, comprising: generating a search query derived from a label for the particular object category; selecting a plurality of candidate videos from videos identified in response to submission of the search query; selecting one or more initial frames from each of the candidate videos; detecting one or more initial images of objects belonging to the particular object category in the one or more initial frames; for each initial frame including an initial image of an object belonging to the particular object category, tracking the object through surrounding frames to identify one or more additional images of the object; and selecting one or more images from the one or more initial images and one or more additional images as the database images of objects belonging to the particular object category; and storing the database images as images of objects belong to the particular object category. | 10. A system comprising: one or more processors and one or more computer storage media storing instructions that are operable and when executed by the one or more processors, cause the one or more processors to perform operations comprising: obtaining data identifying the particular object category; identifying database images of the objects belonging to the particular object category, comprising: generating a search query derived from a label for the particular object category; selecting a plurality of candidate videos from videos identified in response to submission of the search query; selecting one or more initial frames from each of the candidate videos; detecting one or more initial images of objects belonging to the particular object category in the one or more initial frames; for each initial frame including an initial image of an object belonging to the particular object category, tracking the object through surrounding frames to identify one or more additional images of the object; and selecting one or more images from the one or more initial images and one or more additional images as the database images of objects belonging to the particular object category; and storing the database images as images of objects belong to the particular object category. 11. The system of claim 10 , wherein storing the database images comprises storing the database images as training data for a machine learning model. | 0.907683 |
7,930,627 | 6 | 7 | 6. An image processing apparatus for matching two documents, which are represented by first document data and second document data, respectively, having at least an overlap area, comprising: a processor coupled to memory; a common layout area finding unit, which extracts first layout blocks from the first document data and second layout blocks from the second document data, and extracts a first layout feature of the first document data based on the first layout blocks and a second layout feature of the second document data based on the second layout blocks, the first layout feature for the first layout block and the second layout feature for the second layout block including items describing a vertical size of the respective first layout block or the second layout block, a horizontal size of the respective first layout block or the second layout block, and a distance from a layout block preceding the first layout block or the second layout block on the two documents to a layout block subsequent to the first layout block or the second layout block on the two documents, wherein each of the first and second layout blocks comprises a block of text and images separated from another block of text and images by a space, and decides common layout areas of the first document data and the second document data based on the first and second layout features, the common layout area having the same layout in the first document data and the second document data, wherein when a predetermined number of first layout features and second layout features match, the first layout block and the second layout block are determined to comprise at least one common layout area, and wherein the predetermined number of the items is less than a total number of items described in the first layout feature and the second layout feature; a common text finding unit which detects text data included in the common layout areas of the first document data and the second document data, and decides common text data in the common layout areas of the first document data and the second document data, the common text data having same text data in the common layout areas of the first document data and the second document data; extracting feature points of the common layout areas of the first document data and the second document data based on the common text data; and a document combining unit which combines the first document data and the second document data according to the feature points. | 6. An image processing apparatus for matching two documents, which are represented by first document data and second document data, respectively, having at least an overlap area, comprising: a processor coupled to memory; a common layout area finding unit, which extracts first layout blocks from the first document data and second layout blocks from the second document data, and extracts a first layout feature of the first document data based on the first layout blocks and a second layout feature of the second document data based on the second layout blocks, the first layout feature for the first layout block and the second layout feature for the second layout block including items describing a vertical size of the respective first layout block or the second layout block, a horizontal size of the respective first layout block or the second layout block, and a distance from a layout block preceding the first layout block or the second layout block on the two documents to a layout block subsequent to the first layout block or the second layout block on the two documents, wherein each of the first and second layout blocks comprises a block of text and images separated from another block of text and images by a space, and decides common layout areas of the first document data and the second document data based on the first and second layout features, the common layout area having the same layout in the first document data and the second document data, wherein when a predetermined number of first layout features and second layout features match, the first layout block and the second layout block are determined to comprise at least one common layout area, and wherein the predetermined number of the items is less than a total number of items described in the first layout feature and the second layout feature; a common text finding unit which detects text data included in the common layout areas of the first document data and the second document data, and decides common text data in the common layout areas of the first document data and the second document data, the common text data having same text data in the common layout areas of the first document data and the second document data; extracting feature points of the common layout areas of the first document data and the second document data based on the common text data; and a document combining unit which combines the first document data and the second document data according to the feature points. 7. The image processing apparatus of the claim 6 , wherein the image processing apparatus further comprises an image reading unit which obtains the first document data and the second document data. | 0.726389 |
8,301,451 | 7 | 11 | 7. A method according to claim 1 , wherein the converting comprises deriving a set of equations expressing static and dynamic constraints and finding a weighted minimum least squares solution, wherein the set of equations is, in matrix notation:
AY pq =X pq , where Y pq comprises a concatenation of the third speech parameter vectors {y i } p . . . q ,
Y pq [y p T . . . x q T ] T , X pq comprises a concatenation of the first speech parameter vectors {x i } p . . . q and the second speech parameter vectors {Δ i } p . . . q ,
Y pq [x p T . . . x q T Δ p T . . . Δ q T ] T , ( ) T represents a transpose operator, M corresponds to a length of a partial time series, M=q−p+1, Y pq has a length in a form of a product Mn 1 , X pq has a length in a form of a product M(n 1 +n 2 ), the matrix A has a size of M(n 1 +n 2 ) by Mn 1 , and the weighted minimum least squares solution is
Y pq =( A T W T WA ) −1 A T W T WX pq , where W is a matrix of weights with a dimension of M(n 1 +n 2 ) by M(n 1 +n 2 ). | 7. A method according to claim 1 , wherein the converting comprises deriving a set of equations expressing static and dynamic constraints and finding a weighted minimum least squares solution, wherein the set of equations is, in matrix notation:
AY pq =X pq , where Y pq comprises a concatenation of the third speech parameter vectors {y i } p . . . q ,
Y pq [y p T . . . x q T ] T , X pq comprises a concatenation of the first speech parameter vectors {x i } p . . . q and the second speech parameter vectors {Δ i } p . . . q ,
Y pq [x p T . . . x q T Δ p T . . . Δ q T ] T , ( ) T represents a transpose operator, M corresponds to a length of a partial time series, M=q−p+1, Y pq has a length in a form of a product Mn 1 , X pq has a length in a form of a product M(n 1 +n 2 ), the matrix A has a size of M(n 1 +n 2 ) by Mn 1 , and the weighted minimum least squares solution is
Y pq =( A T W T WA ) −1 A T W T WX pq , where W is a matrix of weights with a dimension of M(n 1 +n 2 ) by M(n 1 +n 2 ). 11. A method according to claim 7 , wherein: each of the at least one time series of second speech parameters includes n=n 2 =n 1 time derivatives; and AY=X comprises n independent sets of equations A j Y j =X j . | 0.967401 |
9,298,779 | 1 | 10 | 1. A computer-implemented method comprising: receiving a search query; identifying search results responsive to the query including a first search result in a top set of search results wherein the first search result is associated with a first entity; determining the first entity associated with the first search result; identifying a first eligible content item based on the search results for presentation along with the search results, the first eligible content item being associated with a second entity; determining a second entity associated with the first eligible content item; comparing the first and second entities, and when the first and second entities are the same, creating a combined content item, the combined content item being a single display unit including at least a portion of the first search result and at least a portion of content from the first eligible content item wherein the respective portions are less than an entire portion of content and being presented along with other search results responsive to the search query, wherein creating further includes determining content sponsor preferences associated with a content sponsor of the first eligible content item, the content sponsor preferences including one or more specifications for how to combine the first eligible content item with the first search result, and wherein creating further includes generating the combined content item in accordance with the content sponsor preferences; augmenting the combined content item including: identifying one or more entities related to the first entity; identifying one or more content items from an inventory of content items that are associated with the one or more identified related entities; selecting at least one of the identified one or more content items based on a selection criteria; and using content from the selected at least one identified one or more content items to augment the combined content item in accordance with the content sponsor preferences; and providing the augmented content item as a search result for display with the other search results responsive to the search query. | 1. A computer-implemented method comprising: receiving a search query; identifying search results responsive to the query including a first search result in a top set of search results wherein the first search result is associated with a first entity; determining the first entity associated with the first search result; identifying a first eligible content item based on the search results for presentation along with the search results, the first eligible content item being associated with a second entity; determining a second entity associated with the first eligible content item; comparing the first and second entities, and when the first and second entities are the same, creating a combined content item, the combined content item being a single display unit including at least a portion of the first search result and at least a portion of content from the first eligible content item wherein the respective portions are less than an entire portion of content and being presented along with other search results responsive to the search query, wherein creating further includes determining content sponsor preferences associated with a content sponsor of the first eligible content item, the content sponsor preferences including one or more specifications for how to combine the first eligible content item with the first search result, and wherein creating further includes generating the combined content item in accordance with the content sponsor preferences; augmenting the combined content item including: identifying one or more entities related to the first entity; identifying one or more content items from an inventory of content items that are associated with the one or more identified related entities; selecting at least one of the identified one or more content items based on a selection criteria; and using content from the selected at least one identified one or more content items to augment the combined content item in accordance with the content sponsor preferences; and providing the augmented content item as a search result for display with the other search results responsive to the search query. 10. The method of claim 1 wherein augmenting includes adding a text advertisement sponsored by the one or more related entities. | 0.934426 |
8,838,413 | 20 | 23 | 20. A method of analyzing, detecting and recording an occurrence of at least one event during operation of a valve actuator, the method comprising the steps of: receiving a plurality of input signals from a plurality of sensors that monitor operation of the actuator and/or surrounding environment; identifying attributes of the plurality of input signals and classifying the attributes as a potential occurrence of the at least one event; determining at least one relationship between the identified attributes and the at least one event, wherein the at least one relationship includes a time-related succession of intermediate states of operation associated with the valve actuator that are interconnected by transition paths, which are quantified by cause-and-effect relationships and temporal and likelihood factors; and verifying the at least one event is characterized as one of a deviation, malfunction or failure associated with the actuator and/or surrounding environment. | 20. A method of analyzing, detecting and recording an occurrence of at least one event during operation of a valve actuator, the method comprising the steps of: receiving a plurality of input signals from a plurality of sensors that monitor operation of the actuator and/or surrounding environment; identifying attributes of the plurality of input signals and classifying the attributes as a potential occurrence of the at least one event; determining at least one relationship between the identified attributes and the at least one event, wherein the at least one relationship includes a time-related succession of intermediate states of operation associated with the valve actuator that are interconnected by transition paths, which are quantified by cause-and-effect relationships and temporal and likelihood factors; and verifying the at least one event is characterized as one of a deviation, malfunction or failure associated with the actuator and/or surrounding environment. 23. The method of claim 20 , wherein said determining step comprises: characterizing a state of operation associated with an input signal as being degraded; searching a current state of operation database for all other states of operation related to the state of operation associated with the input signal; retrieving past events associated to the related states occurring within a predetermined time to the present time; comparing the state of operation associated with the input signal with operational values associated with the retrieved past events; and determining from historical data of the retrieve past events whether the state of operation associated with the input signal is a deviation, malfunction or failure associated with the actuator. | 0.565318 |
9,501,791 | 13 | 14 | 13. The online marketplace system of claim 11 , wherein the at least one processing device is further caused to: notify the buyer users and the seller users that an agreement has been reached; confirm receipt of first payments from the buyer users according to the payment terms; monitor conformance of the seller users to the seller-financing terms; monitor conformance of the buyer users to the payment terms over the periods of time; and update reputation data within the trust profiles based at least in part on the conformance of the seller users and the buyer users. | 13. The online marketplace system of claim 11 , wherein the at least one processing device is further caused to: notify the buyer users and the seller users that an agreement has been reached; confirm receipt of first payments from the buyer users according to the payment terms; monitor conformance of the seller users to the seller-financing terms; monitor conformance of the buyer users to the payment terms over the periods of time; and update reputation data within the trust profiles based at least in part on the conformance of the seller users and the buyer users. 14. The online marketplace system of claim 13 , wherein the at least one processing device is further caused to: generate reminders of upcoming payments; alert the buyer users when payments are past due; and impose penalties on the buyer users for defaults. | 0.964345 |
10,003,560 | 1 | 3 | 1. A method, comprising: identifying, by a computing device, social signal data based on social signals published using social media accounts, the social signal data including first information that includes a content of the social signals and second information that is different than the first information, wherein the second information includes metadata; identifying, by the computing device, conversations in the social signals using said second information; grouping, by the computing device, the conversations into topic clusters using the first information, wherein said grouping using the first information comprises: forming a first set of topic clusters that corresponds to a first time; and forming one or more second sets of topic clusters that correspond to one or more second different times, respectively; and wherein, responsive to the grouping using the first information, a first one of the conversations is grouped with a second one of the conversations into a same one of the topic clusters of the first set or the one or more second sets, the first one of the conversations based on a root social signal of the social signals that is not explicitly linked, by the second information, with a different root social signal on which the second one of the conversations is based; and linking, by the computing device, the topic clusters together into a plurality of conversation streams, wherein a first conversation stream of the plurality of conversation streams includes a topic cluster of the first set and at least one associated topic cluster of the one or more second sets, and wherein a second conversation stream of the plurality of conversation streams includes a different topic cluster of the first set and at least one associated topic cluster of the one or more second sets; calculating, by the computing device, strengths of the different conversation streams based on a quantity of the social signals contributing to the conversation streams and a quantity and types of followers associated with the conversation streams; and deriving, by the computing device, a score for one of the social media accounts based on the strengths of the conversation streams. | 1. A method, comprising: identifying, by a computing device, social signal data based on social signals published using social media accounts, the social signal data including first information that includes a content of the social signals and second information that is different than the first information, wherein the second information includes metadata; identifying, by the computing device, conversations in the social signals using said second information; grouping, by the computing device, the conversations into topic clusters using the first information, wherein said grouping using the first information comprises: forming a first set of topic clusters that corresponds to a first time; and forming one or more second sets of topic clusters that correspond to one or more second different times, respectively; and wherein, responsive to the grouping using the first information, a first one of the conversations is grouped with a second one of the conversations into a same one of the topic clusters of the first set or the one or more second sets, the first one of the conversations based on a root social signal of the social signals that is not explicitly linked, by the second information, with a different root social signal on which the second one of the conversations is based; and linking, by the computing device, the topic clusters together into a plurality of conversation streams, wherein a first conversation stream of the plurality of conversation streams includes a topic cluster of the first set and at least one associated topic cluster of the one or more second sets, and wherein a second conversation stream of the plurality of conversation streams includes a different topic cluster of the first set and at least one associated topic cluster of the one or more second sets; calculating, by the computing device, strengths of the different conversation streams based on a quantity of the social signals contributing to the conversation streams and a quantity and types of followers associated with the conversation streams; and deriving, by the computing device, a score for one of the social media accounts based on the strengths of the conversation streams. 3. The method of claim 1 , wherein the metadata is included in the social signals. | 0.941092 |
10,157,609 | 9 | 13 | 9. A method for providing speech recognition with local and remote feedback loops, the method comprising: collecting user data including audio and textual data from one or more computing devices associated with a user, wherein the textual data is collected from user generated documents; receiving directed feedback from the user in response to recognized speech, the feedback comprising at least one of textual data or audio; aggregating the collected user data and the directed feedback; filtering the aggregated data at a first level to protect private data; storing the aggregated data filtered at the first level in one or more local models for customizing current language and acoustic models; filtering the aggregated data at a second level for one or more generic language and acoustic models to remove private data; providing the aggregated data filtered at the second level to a system developer to enable the system developer to update the generic language and acoustic models; receiving a speech input; and recognizing, by a speech recognition system, the speech input based at least in part on the updated one or more local models or the updated one or more generic language and acoustic models. | 9. A method for providing speech recognition with local and remote feedback loops, the method comprising: collecting user data including audio and textual data from one or more computing devices associated with a user, wherein the textual data is collected from user generated documents; receiving directed feedback from the user in response to recognized speech, the feedback comprising at least one of textual data or audio; aggregating the collected user data and the directed feedback; filtering the aggregated data at a first level to protect private data; storing the aggregated data filtered at the first level in one or more local models for customizing current language and acoustic models; filtering the aggregated data at a second level for one or more generic language and acoustic models to remove private data; providing the aggregated data filtered at the second level to a system developer to enable the system developer to update the generic language and acoustic models; receiving a speech input; and recognizing, by a speech recognition system, the speech input based at least in part on the updated one or more local models or the updated one or more generic language and acoustic models. 13. The method of claim 9 , wherein the one or more computing devices execute a distributed speech recognition application that capture the user data in a distributed manner. | 0.865325 |
8,812,291 | 20 | 21 | 20. A computer program product, encoded on a computer-readable storage device, operable to cause data processing apparatus to perform operations comprising: receiving an input string having a plurality of tokens, the input string being divided into one or more n-grams, each n-gram having a length k, wherein k is an integer between 1 and a maximum length N, inclusive, the length identifying a number of tokens in each n-gram; and using a language model to identify a probability for a particular n-gram in the input string, the language model including: a collection of n-grams from a corpus, each n-gram having a corresponding relative frequency in the corpus and an order n corresponding to a number of tokens in the n-gram, each n-gram corresponding to a backoff n-gram having an order of n−1, and a collection of backoff factors α k , one backoff factor for each value of k from 2 to N, inclusive, wherein: when the particular n-gram is present in the language model, the probability for the particular n-gram being the relative frequency of the particular n-gram in the language model, and when the particular n-gram is not found in the language model, the probability for the particular n-gram being identified as a backoff score S k for the particular n-gram, wherein the particular n-gram that is not found in the language model has a particular longest backoff n-gram that is present in the language model and that has a particular relative frequency f and a particular length m, and wherein the backoff score S k is a function of the collection of backoff factors, the particular length m and the particular relative frequency of the particular longest backoff n-gram in the language model. | 20. A computer program product, encoded on a computer-readable storage device, operable to cause data processing apparatus to perform operations comprising: receiving an input string having a plurality of tokens, the input string being divided into one or more n-grams, each n-gram having a length k, wherein k is an integer between 1 and a maximum length N, inclusive, the length identifying a number of tokens in each n-gram; and using a language model to identify a probability for a particular n-gram in the input string, the language model including: a collection of n-grams from a corpus, each n-gram having a corresponding relative frequency in the corpus and an order n corresponding to a number of tokens in the n-gram, each n-gram corresponding to a backoff n-gram having an order of n−1, and a collection of backoff factors α k , one backoff factor for each value of k from 2 to N, inclusive, wherein: when the particular n-gram is present in the language model, the probability for the particular n-gram being the relative frequency of the particular n-gram in the language model, and when the particular n-gram is not found in the language model, the probability for the particular n-gram being identified as a backoff score S k for the particular n-gram, wherein the particular n-gram that is not found in the language model has a particular longest backoff n-gram that is present in the language model and that has a particular relative frequency f and a particular length m, and wherein the backoff score S k is a function of the collection of backoff factors, the particular length m and the particular relative frequency of the particular longest backoff n-gram in the language model. 21. The computer program product of claim 20 , where identifying a probability includes looking up a calculated backoff score for the particular n-gram. | 0.795699 |
9,009,149 | 12 | 14 | 12. One or more computing devices associated with a server computing system for determining one or more ranked candidate media in response to media query data generated at a mobile client device corresponding to a query media, the computing devices comprising: one or more processors; and one or more computer-readable non-transitory storage media embodying software that is configured when executed by one or more of the processors to: receive the media query data from the mobile device, the media query data comprising feature data of one or more features of a query media encoded by a similarity preserving hashing function into a plurality of hash bits and coordinate data for each of the one or more features; match the one or more of the features with one or more corresponding features of an media database using the feature data to identify one or more features of the query media within a predetermined hamming distance in a hash table from the one or more corresponding features of the media database to obtain one or more matched features in the media database, the features of the query media and the features of the media database each being assigned to one of a plurality of entries of the one or more hash tables using the plurality of hash bits as table indexes; determine one or more candidate media whose number of matched features exceed a matched feature threshold; generate a geometry similarity score between the query media and each of the one or more candidate media using the feature data and the coordinate data; rank the one or more candidate media based on the numbers of matched features and the geometry similarity score; and send the ranked candidate media to the mobile client device. | 12. One or more computing devices associated with a server computing system for determining one or more ranked candidate media in response to media query data generated at a mobile client device corresponding to a query media, the computing devices comprising: one or more processors; and one or more computer-readable non-transitory storage media embodying software that is configured when executed by one or more of the processors to: receive the media query data from the mobile device, the media query data comprising feature data of one or more features of a query media encoded by a similarity preserving hashing function into a plurality of hash bits and coordinate data for each of the one or more features; match the one or more of the features with one or more corresponding features of an media database using the feature data to identify one or more features of the query media within a predetermined hamming distance in a hash table from the one or more corresponding features of the media database to obtain one or more matched features in the media database, the features of the query media and the features of the media database each being assigned to one of a plurality of entries of the one or more hash tables using the plurality of hash bits as table indexes; determine one or more candidate media whose number of matched features exceed a matched feature threshold; generate a geometry similarity score between the query media and each of the one or more candidate media using the feature data and the coordinate data; rank the one or more candidate media based on the numbers of matched features and the geometry similarity score; and send the ranked candidate media to the mobile client device. 14. The computing devices of claim 12 , wherein the query media comprises a query image. | 0.922942 |
9,753,918 | 1 | 10 | 1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system. | 1. A method comprising: receiving from a user an utterance in a first language including a first term; by a speech translation system, translating the utterance from the first language into a second language; receiving an indication from the user to initiate a user customization process for customizing one or more modules of the speech translation system to the user; and under the user customization process: receiving an indication from the user to add the first term to one or more modules of the speech translation system; in response to the received indication from the user, determining word class information for the first term; adding, by the speech translation system, the first term, the determined word class information, and at least a portion of the translation of the utterance in the second language to a first machine translation module associated with the first language of the speech translation system; and adding the first term and the at least a portion of the translation of the utterance in the second language to a shared database for a community such that the customization performed by the user is available for use by other users of the community in translations by the speech translation system. 10. The method of claim 1 , further comprising: saving the utterance and the translation as sentence pairs upon instruction by the user to save the sentence pairs as a favorite in a speech translation favorites module configured to store a list or hierarchical inventory of such sentence pairs wherein each favorite can be customized and played directly upon user selection in either the first or second language. | 0.659241 |
7,895,068 | 12 | 13 | 12. A method, in a computer system, of establishing a new business relationship between a seeking entity and a sought entity over a network, the method comprising: a) determining, by a first computer, an activity trust level of the new business relationship the seeking entity is seeking to establish with the sought entity; b) determining, by the first computer, a predetermined degree of separation based on the activity trust level; c) sending, by the first computer, an inquiry to determine if an intermediate entity has an existing relationship with the sought entity, the intermediate entity being within the predetermined degree of separation; d) receiving, by the first computer, a response from the intermediate entity; e) determining, by the first computer, that the response indicates an existing relationship between the sought entity and the intermediate entity, a trust level of the sought entity by the intermediate entity, and a corresponding valuation criterion, the trust level being dependent on the corresponding valuation criterion; and f) causing, by the first computer, the new business relationship with the sought entity to be established based on the first computer determining that the response indicates the existing relationship between the sought entity and the intermediate entity. | 12. A method, in a computer system, of establishing a new business relationship between a seeking entity and a sought entity over a network, the method comprising: a) determining, by a first computer, an activity trust level of the new business relationship the seeking entity is seeking to establish with the sought entity; b) determining, by the first computer, a predetermined degree of separation based on the activity trust level; c) sending, by the first computer, an inquiry to determine if an intermediate entity has an existing relationship with the sought entity, the intermediate entity being within the predetermined degree of separation; d) receiving, by the first computer, a response from the intermediate entity; e) determining, by the first computer, that the response indicates an existing relationship between the sought entity and the intermediate entity, a trust level of the sought entity by the intermediate entity, and a corresponding valuation criterion, the trust level being dependent on the corresponding valuation criterion; and f) causing, by the first computer, the new business relationship with the sought entity to be established based on the first computer determining that the response indicates the existing relationship between the sought entity and the intermediate entity. 13. The method of claim 12 , further comprising specifying an acceptable degree of separation and determining whether the existing relationship exists within the specified degree of separation. | 0.898528 |
8,126,742 | 34 | 35 | 34. The system of claim 31 , further comprising: the computer processor further configured to detect, with the processor, a failure to assign the at least one target organizational entity to the at least one portion of the insurance claim; the computer processor further configured to identify, in response to the detected failure to assign the at least one target organizational entity to the insurance claim, with the processor, at least one target exception organizational entity based on the at least some of the insurance claim pattern results stored in the memory and the insurance claim data; the computer processor further configured to determine an assignability of the at least one target exception organizational entity to the at least one portion of the insurance claim; and the computer processor further configured to assign the at least one target exception organizational entity to the at least one portion of the insurance claim based on the determined assignability of the at least one target exception organizational entity. | 34. The system of claim 31 , further comprising: the computer processor further configured to detect, with the processor, a failure to assign the at least one target organizational entity to the at least one portion of the insurance claim; the computer processor further configured to identify, in response to the detected failure to assign the at least one target organizational entity to the insurance claim, with the processor, at least one target exception organizational entity based on the at least some of the insurance claim pattern results stored in the memory and the insurance claim data; the computer processor further configured to determine an assignability of the at least one target exception organizational entity to the at least one portion of the insurance claim; and the computer processor further configured to assign the at least one target exception organizational entity to the at least one portion of the insurance claim based on the determined assignability of the at least one target exception organizational entity. 35. The system of claim 34 , further comprising: the computer processor further configured to detect failure to assign the at least one target exception organizational entity to the at least one portion of the insurance claim; the computer processor further configured to identify, with the processor, a default target organizational entity in response to the detected failure to assign the at least one target exception organizational entity to the at least one portion of the insurance claim; and the computer processor further configured to assign the at least one portion of the insurance claim to the default target organizational entity based on identification of the default target organizational entity. | 0.900698 |
8,560,937 | 1 | 7 | 1. A method for segmenting a document comprising: identifying a rectangular page frame using information from multiple pages of a document; matching the page frame to a page of the document; identifying elements within the matched page frame; for a zone of the document page having a zone width and comprising a set of the elements, the zone comprising at least a portion of the page frame width: a) for a first iteration: segmenting the zone regularly into a number of candidate columns, a width of each of the candidate columns being function of the number of the candidate columns and the zone width; for each of the candidate columns, identifying the elements in the set which are within the candidate column; where the candidate columns meet a threshold for identified elements and a gutter is found which spaces the candidate columns, assigning, to a set of segmented columns, those elements in the set which are within the segmented columns, and identifying remaining elements in the set which are not covered by the segmented columns, the segmented columns corresponding in number to the number of candidate columns and each segmented column being spaced by the computed gutter; b) where there are remaining elements after a), performing at least one of: i) at least one subsequent iteration which includes repeating a), wherein in each subsequent iteration, the set of elements is the remaining elements in the set, and wherein the segmenting of the zone regularly into a number of candidate columns segments the zone into a different number of candidate columns from the first iteration and all other subsequent iterations, and ii) considering the zone as a single segmented column only, identifying the elements in the set which are within the single segmented column; and where there are remaining elements in the set after a) and b), providing for a) and b) to be performed for at least one subsequent zone of the page, wherein for each subsequent zone, the set of elements includes remaining elements not covered by the segmented columns identified for any of the preceding zones. | 1. A method for segmenting a document comprising: identifying a rectangular page frame using information from multiple pages of a document; matching the page frame to a page of the document; identifying elements within the matched page frame; for a zone of the document page having a zone width and comprising a set of the elements, the zone comprising at least a portion of the page frame width: a) for a first iteration: segmenting the zone regularly into a number of candidate columns, a width of each of the candidate columns being function of the number of the candidate columns and the zone width; for each of the candidate columns, identifying the elements in the set which are within the candidate column; where the candidate columns meet a threshold for identified elements and a gutter is found which spaces the candidate columns, assigning, to a set of segmented columns, those elements in the set which are within the segmented columns, and identifying remaining elements in the set which are not covered by the segmented columns, the segmented columns corresponding in number to the number of candidate columns and each segmented column being spaced by the computed gutter; b) where there are remaining elements after a), performing at least one of: i) at least one subsequent iteration which includes repeating a), wherein in each subsequent iteration, the set of elements is the remaining elements in the set, and wherein the segmenting of the zone regularly into a number of candidate columns segments the zone into a different number of candidate columns from the first iteration and all other subsequent iterations, and ii) considering the zone as a single segmented column only, identifying the elements in the set which are within the single segmented column; and where there are remaining elements in the set after a) and b), providing for a) and b) to be performed for at least one subsequent zone of the page, wherein for each subsequent zone, the set of elements includes remaining elements not covered by the segmented columns identified for any of the preceding zones. 7. The method of claim 1 , wherein the set of elements comprises line elements, each line element comprising text. | 0.921596 |
9,081,626 | 13 | 14 | 13. An apparatus, comprising: a memory comprising instructions; and a processor configured to execute the instructions stored on the memory, wherein the processor is further configured, when executing the instructions stored on the memory, to, translate source code written in a first assembly language for implementation by a Programmable Interface Controller (PIC) microcontroller into source code written in an pseudo assembly language; wherein the translating comprises converting a set of sequential instructions of the source code written in the first assembly language to a set of sequential instructions, respectively, written in the pseudo assembly language; convert the source code written in the pseudo assembly language into source code written in a second assembly language for implementation by a non-PIC microcontroller; wherein the converting the source code written in the pseudo assembly language further comprises; identifying a first source code segment written in the pseudo assembly language that includes a conditional statement for checking a status of a bit in a register of the PIC microcontroller; generating a first source code segment written in the second assembly language that implements an interrupt service routine for the non-PIC microcontroller in response to the identifying. | 13. An apparatus, comprising: a memory comprising instructions; and a processor configured to execute the instructions stored on the memory, wherein the processor is further configured, when executing the instructions stored on the memory, to, translate source code written in a first assembly language for implementation by a Programmable Interface Controller (PIC) microcontroller into source code written in an pseudo assembly language; wherein the translating comprises converting a set of sequential instructions of the source code written in the first assembly language to a set of sequential instructions, respectively, written in the pseudo assembly language; convert the source code written in the pseudo assembly language into source code written in a second assembly language for implementation by a non-PIC microcontroller; wherein the converting the source code written in the pseudo assembly language further comprises; identifying a first source code segment written in the pseudo assembly language that includes a conditional statement for checking a status of a bit in a register of the PIC microcontroller; generating a first source code segment written in the second assembly language that implements an interrupt service routine for the non-PIC microcontroller in response to the identifying. 14. The apparatus of claim 13 : wherein the processor is further configured, when executing the instructions stored on the memory, to prompt a user to customize the conversion of the source code written in the pseudo assembly language into the source code written in the second assembly language, and to optimize the source code written in the second assembly language. | 0.715716 |
8,929,519 | 1 | 12 | 1. A computer hardware system configured to analyze speech application performance, comprising: at least one processor, wherein the at least one processor is configured to initiate and/or perform: identifying, from a log of an interactive voice response system including a speech application, a call path for each of a plurality of calls, each call path is defined by an ordered set of dialog nodes of the speech application; counting a number of occurrences of at least one selected type of event for the dialog nodes of the plurality of call paths; and indicating at least one call path from the plurality of call paths according to the number of occurrences of the selected type of event within the at least one indicated call path. | 1. A computer hardware system configured to analyze speech application performance, comprising: at least one processor, wherein the at least one processor is configured to initiate and/or perform: identifying, from a log of an interactive voice response system including a speech application, a call path for each of a plurality of calls, each call path is defined by an ordered set of dialog nodes of the speech application; counting a number of occurrences of at least one selected type of event for the dialog nodes of the plurality of call paths; and indicating at least one call path from the plurality of call paths according to the number of occurrences of the selected type of event within the at least one indicated call path. 12. The system of claim 1 , wherein the event type is selected from the group consisting of: a re-prompt event, a hang-up event, and an agent transfer event. | 0.85779 |
9,280,766 | 1 | 2 | 1. A system for determining EDI rules to enforce, comprising: a computer system having a processor, a memory, a storage device, a network interface, and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: determine entity-specific rules from corresponding companion guides for each of a plurality of entities; express each entity-specific rule in a neutral and machine readable format; classify each of the entity-specific rules by determining for each entity-specific rule: whether the entity-specific rule is common with at least one other entity-specific rule, or whether the entity-specific rule is similar to at least one other entity-specific rule, or whether the entity-specific rule is unique; convey results of classifying the entity-specific rules by: creating an inventory of rules, the inventory including a common set of rules for the plurality of entities; dynamically adjusting said inventory of the rules based upon the entity-specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; storing the inventory of rules in a storage according to the classification of each rule as common, similar, or unique; creating a respective, corresponding pointer to the entity-specific rules in the inventory of rules associated with at least one of the plurality of entities; and storing the corresponding pointer in a storage for use in retrieving an appropriate current rule set when validating an EDI document for the at least one of the plurality of entities. | 1. A system for determining EDI rules to enforce, comprising: a computer system having a processor, a memory, a storage device, a network interface, and a bus for exchanging information therebetween, the memory storing computer usable program code executed by the processor to: determine entity-specific rules from corresponding companion guides for each of a plurality of entities; express each entity-specific rule in a neutral and machine readable format; classify each of the entity-specific rules by determining for each entity-specific rule: whether the entity-specific rule is common with at least one other entity-specific rule, or whether the entity-specific rule is similar to at least one other entity-specific rule, or whether the entity-specific rule is unique; convey results of classifying the entity-specific rules by: creating an inventory of rules, the inventory including a common set of rules for the plurality of entities; dynamically adjusting said inventory of the rules based upon the entity-specific rules where the entity specific rules are derived from a plurality of companion guides, each companion guide associated with one of the plurality of entities; storing the inventory of rules in a storage according to the classification of each rule as common, similar, or unique; creating a respective, corresponding pointer to the entity-specific rules in the inventory of rules associated with at least one of the plurality of entities; and storing the corresponding pointer in a storage for use in retrieving an appropriate current rule set when validating an EDI document for the at least one of the plurality of entities. 2. The system of claim 1 , wherein the memory further stores computer usable program code executed by the processor to: determine a first current rule set for a first one of the plurality of entities comprising at least one of the entity-specific rules; and validate a first EDI document associated with the first one of the plurality of entities by: comparing the first EDI document to the first current rule set; forwarding the first EDI document to the first one of the plurality of entities if the EDI document matches the first current rule set, wherein the EDI document is validated; and returning the first EDI document to a sender if the first EDI document does not match the first current rule set, wherein the first EDI document is invalidated. | 0.621866 |
9,477,991 | 57 | 58 | 57. The method of claim 53 , wherein the at least the second query includes at least one of a word, a plurality of words, a phrase, a user profile, a portion of a user profile, a regular expression, a natural language filter, a grammar, a social group, an organization, and a user identification; wherein at least a portion of the user-provided data from the plurality of users corresponds to the at least one result and at least one of the word, the plurality of words, the phrase, the user profile, the portion of the user profile, the regular expression, the natural language filter, the grammar, the social group, the organization, and the user identification; and wherein the at least one result is based on the at least the portion of the user-provided data from the plurality of users that corresponds to the at least one result and the at least one of the word, the plurality of words, the phrase, the user profile, the portion of the user profile, the regular expression, the natural language filter, the grammar, the social group, the organization, and the user identification. | 57. The method of claim 53 , wherein the at least the second query includes at least one of a word, a plurality of words, a phrase, a user profile, a portion of a user profile, a regular expression, a natural language filter, a grammar, a social group, an organization, and a user identification; wherein at least a portion of the user-provided data from the plurality of users corresponds to the at least one result and at least one of the word, the plurality of words, the phrase, the user profile, the portion of the user profile, the regular expression, the natural language filter, the grammar, the social group, the organization, and the user identification; and wherein the at least one result is based on the at least the portion of the user-provided data from the plurality of users that corresponds to the at least one result and the at least one of the word, the plurality of words, the phrase, the user profile, the portion of the user profile, the regular expression, the natural language filter, the grammar, the social group, the organization, and the user identification. 58. The method of claim 57 , wherein the user-provided data includes at least one post to at least one social network service. | 0.97719 |
8,447,736 | 1 | 7 | 1. A method for compressing a grammar, the method comprising: receiving a grammar to be compressed by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; eliminating, from the grammar, all but one of any duplicate rules identified from parsing the grammar, wherein duplicate rules include rules having the same token classes in the same order; identifying, from the set of token classes within each remaining rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify two or more token classes within the set of unimportant token classes that are similar; merging the two or more token classes within the set of unimportant token classes identified from the currently received grammar to generate a merged token class by removing duplicate tokens and combining remaining tokens from the two or more token classes; and substituting the merged token class in the grammar for the two or more token classes that were merged to generate the merged token class to generate a compressed grammar. | 1. A method for compressing a grammar, the method comprising: receiving a grammar to be compressed by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; eliminating, from the grammar, all but one of any duplicate rules identified from parsing the grammar, wherein duplicate rules include rules having the same token classes in the same order; identifying, from the set of token classes within each remaining rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify two or more token classes within the set of unimportant token classes that are similar; merging the two or more token classes within the set of unimportant token classes identified from the currently received grammar to generate a merged token class by removing duplicate tokens and combining remaining tokens from the two or more token classes; and substituting the merged token class in the grammar for the two or more token classes that were merged to generate the merged token class to generate a compressed grammar. 7. The method of claim 1 , wherein analyzing the set of unimportant classes comprises employing a similarity function to identify similar unimportant token classes. | 0.954721 |
8,781,835 | 8 | 10 | 8. An apparatus comprising at least one processor and at least one memory storing computer program code for one or more programs, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to cause the apparatus to at least: generate a plurality of input models representing an input by using a statistical model synthesizer to statistically model the input; determine a speech unit sequence representing at least a portion of the input by using the input models to influence selection of one or more pre-recorded speech units having parameter representations identify one or more bad units in the speech unit sequence, wherein determining the speech unit sequence and identifying one or more bad units in the speech unit sequence are performed substantially simultaneously; and replace the identified one or more bad units with one or more parameters generated using the statistical model synthesizer. | 8. An apparatus comprising at least one processor and at least one memory storing computer program code for one or more programs, wherein the at least one memory and stored computer program code are configured, with the at least one processor, to cause the apparatus to at least: generate a plurality of input models representing an input by using a statistical model synthesizer to statistically model the input; determine a speech unit sequence representing at least a portion of the input by using the input models to influence selection of one or more pre-recorded speech units having parameter representations identify one or more bad units in the speech unit sequence, wherein determining the speech unit sequence and identifying one or more bad units in the speech unit sequence are performed substantially simultaneously; and replace the identified one or more bad units with one or more parameters generated using the statistical model synthesizer. 10. The apparatus of claim 8 , wherein the at least one memory and stored computer program code are configured, with the at least one processor, to further cause the apparatus to identify one or more bad units at least in part by identifying one or more units having costs exceeding one or more of a threshold target cost or a threshold concatenation cost. | 0.699831 |
10,049,362 | 1 | 7 | 1. A method of authenticating data, comprising: training a voice biometric system to identify a user from a message spoken by the user; requesting, by the voice biometric system, a spoken message comprising a financial transaction detail from the user, the financial transaction detail related to a financial transaction between the user and a merchant; receiving, by the voice biometric system, the spoken message from the user, the spoken message comprising word content, the word content comprising the financial transaction detail related to the financial transaction between the user and the merchant; authenticating, by the voice biometric system, the word content included in the spoken message as word content spoken by the user; and providing a result of the authentication including the authenticated word content, thereby permitting a comparison of the authenticated word content to information related to the financial transaction between the user and the merchant to provide a degree of confidence that the financial transaction is not fraudulent. | 1. A method of authenticating data, comprising: training a voice biometric system to identify a user from a message spoken by the user; requesting, by the voice biometric system, a spoken message comprising a financial transaction detail from the user, the financial transaction detail related to a financial transaction between the user and a merchant; receiving, by the voice biometric system, the spoken message from the user, the spoken message comprising word content, the word content comprising the financial transaction detail related to the financial transaction between the user and the merchant; authenticating, by the voice biometric system, the word content included in the spoken message as word content spoken by the user; and providing a result of the authentication including the authenticated word content, thereby permitting a comparison of the authenticated word content to information related to the financial transaction between the user and the merchant to provide a degree of confidence that the financial transaction is not fraudulent. 7. The method as claimed in claim 1 , further comprising comparing the financial transaction detail included in the authenticated word content to the information related to the financial transaction between the user and the merchant to provide the degree of confidence that the financial transaction is not fraudulent. | 0.75425 |
10,057,199 | 7 | 13 | 7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment. | 7. The method of claim 1 , wherein the qualitative analysis comprises a collective qualitative analysis of a subset of the impressions related to the comment. 13. The method of claim 7 , wherein the subset comprises one or more of the impressions having a timestamp within a threshold recent period of time. | 0.955979 |
9,985,978 | 15 | 19 | 15. An apparatus for determining whether email content is potentially malicious, contains potentially malicious content, has originated from a potentially malicious entity, or contains links or other references to potentially malicious web content, comprising: a first module determining if the email content contains predetermined suspected malicious phrases, the first module including a scoring engine, a security device, at least one mail server and an intelligent database; a second module determining if at least one link in the email content references potentially malicious web content using at least one of an IP address, URL, and a domain name, the second module including a search engine, the security device, the email crawler, a web crawler, and the exclusion processor, the determining being a two step process of performing an initial analysis based on existing identification information about said at least one link, which includes IP address, URL, and the domain name, before accepting a remaining portion of the email content, which includes message body data; and a third module evaluating metadata in the email content to determine if the email content is potentially malicious, the third module includes a scoring engine, the security device, and the email crawler, the scoring engine performing a scoring process and providing a page score for a digital document to represent a likelihood that the digital document includes potentially malicious content, the scoring engine using a Word Expression equation, which includes at least one variable to represent a number of occurrences of at least specific keywords, and patterning in the potentially malicious content in the digital document, the scoring engine comparing information extracted from the digital document and forwards the digital document for review and analysis, and the scoring engine providing at least one of real-time and post-production evaluation of the digital document and provides an output value, including the page score. | 15. An apparatus for determining whether email content is potentially malicious, contains potentially malicious content, has originated from a potentially malicious entity, or contains links or other references to potentially malicious web content, comprising: a first module determining if the email content contains predetermined suspected malicious phrases, the first module including a scoring engine, a security device, at least one mail server and an intelligent database; a second module determining if at least one link in the email content references potentially malicious web content using at least one of an IP address, URL, and a domain name, the second module including a search engine, the security device, the email crawler, a web crawler, and the exclusion processor, the determining being a two step process of performing an initial analysis based on existing identification information about said at least one link, which includes IP address, URL, and the domain name, before accepting a remaining portion of the email content, which includes message body data; and a third module evaluating metadata in the email content to determine if the email content is potentially malicious, the third module includes a scoring engine, the security device, and the email crawler, the scoring engine performing a scoring process and providing a page score for a digital document to represent a likelihood that the digital document includes potentially malicious content, the scoring engine using a Word Expression equation, which includes at least one variable to represent a number of occurrences of at least specific keywords, and patterning in the potentially malicious content in the digital document, the scoring engine comparing information extracted from the digital document and forwards the digital document for review and analysis, and the scoring engine providing at least one of real-time and post-production evaluation of the digital document and provides an output value, including the page score. 19. The apparatus of claim 15 , wherein the email content is evaluated remotely by a third party entity. | 0.80303 |
7,599,580 | 1 | 32 | 1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user. | 1. A method in a computing system for processing a distinguished text capture operation, comprising: receiving human-readable text captured by a user via a portable capture device from a distinguished rendered document in the distinguished text capture operation; receiving supplemental information distinct from the captured text, said supplemental information comprising an identity associated with said user; and automatically determining, by the computing system in response to the distinguished text capture operation and based upon both the captured text and the supplemental information, which one of a predetermined plurality of actions is likely optimal for said user. 32. The method of claim 1 wherein the received supplemental information includes information about previous text capture operations performed by users other than said user and about the conditions under which the previous text capture operation was performed, and wherein the determined action is identifying a single electronic document as corresponding to the distinguished rendered document. | 0.733424 |
9,326,116 | 17 | 26 | 17. An electronic book reading device comprising: a pause position manager configured to: receive identification of a current user reading position within an electronic text of an electronic book for a current reading session; and determine candidate pause positions within the electronic text of the electronic book based on the current user reading position and from among a portion of the electronic text extending from the current user reading position and another reading position following the current user reading position; select a suggested pause position from the determined candidate pause positions based on an available reading time and reading speed associated with a user profile of the current user for the current reading session; and a user interface configured to present the suggested pause position to indicate where to pause in reading the electronic text of the electronic book for the current reading session. | 17. An electronic book reading device comprising: a pause position manager configured to: receive identification of a current user reading position within an electronic text of an electronic book for a current reading session; and determine candidate pause positions within the electronic text of the electronic book based on the current user reading position and from among a portion of the electronic text extending from the current user reading position and another reading position following the current user reading position; select a suggested pause position from the determined candidate pause positions based on an available reading time and reading speed associated with a user profile of the current user for the current reading session; and a user interface configured to present the suggested pause position to indicate where to pause in reading the electronic text of the electronic book for the current reading session. 26. The electronic device of claim 17 , wherein the pause position manager is configured to determine the candidate pause positions based on a content of the electronic text of the electronic book. | 0.762077 |
8,548,844 | 1 | 11 | 1. A computer-implemented data mining system for use in rating endorsers, comprising: a server computer having a tangible computing processor, the processor in data communication with a non-transitory computer memory that stores instructions which, when executed on the processor, cause the computer to implement: a search engine that searches a plurality of RSS feeds for mentions of an identified endorser in conjunction with keywords; a ratings engine that rates the mentions in at least a portion of the RSS feeds based on an identified subset of a categorical hierarchy of the keywords and a number of words in the RSS feeds between the endorser and the corresponding keywords, wherein positive mentions and negative mentions are separately tracked and combined into an overall rating; an information engine that obtains information regarding a number of viewings of the rated mentions in the RSS feeds; a repository that stores each of the plurality of RSS feeds; and a data miner communicatively connected to the search engine, the ratings engine, and the repository, the data miner operative to generate a consumer opinion index of the endorser based on a correlation of the rating of the mentions and the number of viewings, wherein the RSS feeds stored in the repository, the mentions of the subject in conjunction with the keywords, and the consumer opinion index are searchable, wherein the mentions are permanently available from the repository; and wherein the endorser is one of an affinity brand, a marketing partner, and a sponsor. | 1. A computer-implemented data mining system for use in rating endorsers, comprising: a server computer having a tangible computing processor, the processor in data communication with a non-transitory computer memory that stores instructions which, when executed on the processor, cause the computer to implement: a search engine that searches a plurality of RSS feeds for mentions of an identified endorser in conjunction with keywords; a ratings engine that rates the mentions in at least a portion of the RSS feeds based on an identified subset of a categorical hierarchy of the keywords and a number of words in the RSS feeds between the endorser and the corresponding keywords, wherein positive mentions and negative mentions are separately tracked and combined into an overall rating; an information engine that obtains information regarding a number of viewings of the rated mentions in the RSS feeds; a repository that stores each of the plurality of RSS feeds; and a data miner communicatively connected to the search engine, the ratings engine, and the repository, the data miner operative to generate a consumer opinion index of the endorser based on a correlation of the rating of the mentions and the number of viewings, wherein the RSS feeds stored in the repository, the mentions of the subject in conjunction with the keywords, and the consumer opinion index are searchable, wherein the mentions are permanently available from the repository; and wherein the endorser is one of an affinity brand, a marketing partner, and a sponsor. 11. The system of claim 1 , wherein the RRS feeds are limited to a predefined geographic scope. | 0.676871 |
10,095,683 | 1 | 2 | 1. A method comprising, by one or more computing devices: receiving, from a client system of a first user of an online social network, a search query comprising one or more n-grams; determining, based on a contextual speller model, that at least one n-gram of the one or more n-grams is misspelled, wherein the contextual speller model is based at least on a standard language model and a personal language model customized for the first user based on social-networking data associated with the first user; identifying, for each misspelled n-gram, one or more variant-tokens based at least on the search query and the contextual speller model; generating one or more unique combinations of the n-grams and variant-tokens, wherein each unique combination comprises a variant-token corresponding to each misspelled n-gram; calculating a relevance-score for each unique combination based at least in part on the search query and the contextual speller model, wherein the relevance-score for a unique combination is based on a comparison of a probability associated with the n-grams or variant tokens of the unique combination in the standard language model of the contextual speller model to a probability associated with the n-grams or variant tokens of the unique combination in the personal language model of the contextual speller model; generating one or more corrected queries, each corrected query comprising a unique combination having a relevance-score greater than a threshold relevance-score; and sending, to the client system of the first user for display in response to receiving the search query, one or more of the corrected queries. | 1. A method comprising, by one or more computing devices: receiving, from a client system of a first user of an online social network, a search query comprising one or more n-grams; determining, based on a contextual speller model, that at least one n-gram of the one or more n-grams is misspelled, wherein the contextual speller model is based at least on a standard language model and a personal language model customized for the first user based on social-networking data associated with the first user; identifying, for each misspelled n-gram, one or more variant-tokens based at least on the search query and the contextual speller model; generating one or more unique combinations of the n-grams and variant-tokens, wherein each unique combination comprises a variant-token corresponding to each misspelled n-gram; calculating a relevance-score for each unique combination based at least in part on the search query and the contextual speller model, wherein the relevance-score for a unique combination is based on a comparison of a probability associated with the n-grams or variant tokens of the unique combination in the standard language model of the contextual speller model to a probability associated with the n-grams or variant tokens of the unique combination in the personal language model of the contextual speller model; generating one or more corrected queries, each corrected query comprising a unique combination having a relevance-score greater than a threshold relevance-score; and sending, to the client system of the first user for display in response to receiving the search query, one or more of the corrected queries. 2. The method of claim 1 , further comprising: receiving from the first user a selection of one of the corrected queries; identifying one or more objects matching the selected query; and sending, to the client system of the first user, a search-result page responsive to the selected query, the search-results page comprising one or more references to one or more of the identified objects, respectively. | 0.754854 |
8,396,710 | 21 | 25 | 21. A system comprising: a speech recognition module configured to detect a keyword in a speech input; one or more memory devices configured to store a portion of the speech input; a transceiver configured to initiate a connection with a remote system upon detection, by the speech recognition module, of the keyword and to transmit the stored portion of the speech input to the remote system; and an updating module configured to update or modify a set of recognizable keywords stored by the one or more memory devices based on updates or modifications received from the remote system responsive to analysis of the stored portion of the speech input performed by a speech recognition operation of the remote system. | 21. A system comprising: a speech recognition module configured to detect a keyword in a speech input; one or more memory devices configured to store a portion of the speech input; a transceiver configured to initiate a connection with a remote system upon detection, by the speech recognition module, of the keyword and to transmit the stored portion of the speech input to the remote system; and an updating module configured to update or modify a set of recognizable keywords stored by the one or more memory devices based on updates or modifications received from the remote system responsive to analysis of the stored portion of the speech input performed by a speech recognition operation of the remote system. 25. The system of claim 21 , wherein detecting the keyword in the speech input comprises scanning speech input issued by a user at a local device. | 0.78012 |
8,977,255 | 19 | 30 | 19. A method for operating an electronic device supporting or coupling to a plurality of functions, one of the functions being wireless voice communications and another of the functions being media playback, said method comprising: determining whether a voice call is incoming; receiving a first voice command; determining whether the first voice command corresponds to a request for caller information; and in response to a determination that the first voice command corresponds to a request for caller information, presenting caller information to the user via an audio output. | 19. A method for operating an electronic device supporting or coupling to a plurality of functions, one of the functions being wireless voice communications and another of the functions being media playback, said method comprising: determining whether a voice call is incoming; receiving a first voice command; determining whether the first voice command corresponds to a request for caller information; and in response to a determination that the first voice command corresponds to a request for caller information, presenting caller information to the user via an audio output. 30. A method as recited in claim 19 , wherein the electronic device is a portable multi-function device that supports both wireless voice communications and media playback. | 0.919701 |
8,365,071 | 15 | 18 | 15. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory having a plurality of objects stored therein; an input apparatus comprising a plurality of input keys and being structured to provide input to the processor apparatus; an output apparatus structured to receive output signals from the processor apparatus; at least some of the input keys each having a number of linguistic elements assigned thereto; the plurality of objects comprising a plurality of language objects, a plurality of characters, and a plurality of words, at least some of the language objects each being associated with a plurality of the characters, each word comprising a number of the characters, each language object comprising a number of the linguistic elements; the memory further having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting an ambiguous text input comprising a number of selections of a number of input keys, at least some of the number of input keys each having as the number of linguistic elements assigned thereto a plurality of linguistic elements assigned thereto; generating a string of language objects that corresponds with at least an initial portion of the ambiguous input; outputting one of the language objects of the string of language objects and at least one variant language object as an alternative to the one of the language objects of the string of language objects in a first region of the output apparatus, the one of the language objects of the string of language objects and the at least one variant language object being selectable; outputting a character interpretation that comprises a number of words comprising characters that correspond with at least a portion of the string of language objects in a second region of the output apparatus, the character interpretation being selectable; applying a selection focus to the one of the language objects of the string of language objects, the at least one variant language object, or the character interpretation; and in response to detecting a selection of the one of the language objects of the string of language objects or the at least one variant language object, outputting a second one of the language objects of the string of language objects and at least one second variant language object in the first region, wherein the second one of the language objects of the string of language objects comprises a different portion of the string of language objects than the one of the language objects of the string of language objects. | 15. A handheld electronic device comprising: a processor apparatus comprising a processor and a memory having a plurality of objects stored therein; an input apparatus comprising a plurality of input keys and being structured to provide input to the processor apparatus; an output apparatus structured to receive output signals from the processor apparatus; at least some of the input keys each having a number of linguistic elements assigned thereto; the plurality of objects comprising a plurality of language objects, a plurality of characters, and a plurality of words, at least some of the language objects each being associated with a plurality of the characters, each word comprising a number of the characters, each language object comprising a number of the linguistic elements; the memory further having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: detecting an ambiguous text input comprising a number of selections of a number of input keys, at least some of the number of input keys each having as the number of linguistic elements assigned thereto a plurality of linguistic elements assigned thereto; generating a string of language objects that corresponds with at least an initial portion of the ambiguous input; outputting one of the language objects of the string of language objects and at least one variant language object as an alternative to the one of the language objects of the string of language objects in a first region of the output apparatus, the one of the language objects of the string of language objects and the at least one variant language object being selectable; outputting a character interpretation that comprises a number of words comprising characters that correspond with at least a portion of the string of language objects in a second region of the output apparatus, the character interpretation being selectable; applying a selection focus to the one of the language objects of the string of language objects, the at least one variant language object, or the character interpretation; and in response to detecting a selection of the one of the language objects of the string of language objects or the at least one variant language object, outputting a second one of the language objects of the string of language objects and at least one second variant language object in the first region, wherein the second one of the language objects of the string of language objects comprises a different portion of the string of language objects than the one of the language objects of the string of language objects. 18. The handheld electronic device of claim 15 wherein the operations further comprise outputting the one of the language objects of the string of language objects, the at least one variant language object, and the character interpretation as objects that are selectable by one or more predetermined inputs. | 0.676842 |
6,122,361 | 10 | 11 | 10. An automated directory assistance system as defined in claim 8, comprising: a) an input for receiving data indicative of at least a portion of a telephone number of a terminal at which the user is inputting the spoken utterance, b) an identification unit for identifying a data structure associated with the data indicative of at least a portion of a telephone number of a terminal at which the user is inputting the spoken utterance, c) a search unit for searching the data structure identified at paragraph b to extract therefrom probability data corresponding to at least one candidate. | 10. An automated directory assistance system as defined in claim 8, comprising: a) an input for receiving data indicative of at least a portion of a telephone number of a terminal at which the user is inputting the spoken utterance, b) an identification unit for identifying a data structure associated with the data indicative of at least a portion of a telephone number of a terminal at which the user is inputting the spoken utterance, c) a search unit for searching the data structure identified at paragraph b to extract therefrom probability data corresponding to at least one candidate. 11. An automated directory assistance system as defined in claim 10, wherein said search unit for searching the data structure has the ability to search the data structure for each of said plurality of vocabulary items and output probability data associated with each candidate. | 0.889945 |
9,213,685 | 4 | 5 | 4. The method of claim 3 , wherein the translation of the message in the first language includes the translation of at least a portion of the message in the first language into the second language. | 4. The method of claim 3 , wherein the translation of the message in the first language includes the translation of at least a portion of the message in the first language into the second language. 5. The method of claim 4 , wherein the step of generating the translated message in the second language comprises replacing the at least a portion of the message in the first language with the translation of the at least a portion of the message in the first language. | 0.897944 |
8,869,299 | 12 | 21 | 12. A system method for classifying and redacting a document having a security label, for distributing to multiple recipients having different security levels, the method comprising: a processor, and a non-transitory computer readable storage medium having computer readable instructions stored thereon for execution by the processor, the processor being configured to: select a segment of the document; automatically analyze contents of the selected segment in real time by using an artificial intelligence (Al) system; automatically classify the segment based on results of the analysis performed by the Al system, and further generate a security label associated with the segment of the document, comprising providing a first reference to a security classification level of the segment of the document, wherein the first reference is stored internal to the document, and the security classification level is stored external to the document; automatically mark the segment in accordance with a respective classification option, producing a marked segment; automatically classify the document based on classifications of segments of the document; automatically redact the document in real time in accordance with a respective clearance level of a recipient of the document, producing a redacted document, comprising arranging recipients of the document in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and automatically distribute the redacted document to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy. | 12. A system method for classifying and redacting a document having a security label, for distributing to multiple recipients having different security levels, the method comprising: a processor, and a non-transitory computer readable storage medium having computer readable instructions stored thereon for execution by the processor, the processor being configured to: select a segment of the document; automatically analyze contents of the selected segment in real time by using an artificial intelligence (Al) system; automatically classify the segment based on results of the analysis performed by the Al system, and further generate a security label associated with the segment of the document, comprising providing a first reference to a security classification level of the segment of the document, wherein the first reference is stored internal to the document, and the security classification level is stored external to the document; automatically mark the segment in accordance with a respective classification option, producing a marked segment; automatically classify the document based on classifications of segments of the document; automatically redact the document in real time in accordance with a respective clearance level of a recipient of the document, producing a redacted document, comprising arranging recipients of the document in a hierarchy in accordance with respective clearance levels such that a recipient with a higher clearance level occupies a higher level in the hierarchy in comparison to a recipient with a lower clearance level; and automatically distribute the redacted document to the recipients of a particular level in the hierarchy concurrently with the redacting marked segments for the recipients at the immediate lower level in the hierarchy. 21. The system of claim 12 , wherein the Al is a decision tree Al system, comprising decision nodes and conclusion nodes, each decision node having outcomes connecting the decision node to another decision node or to the conclusion node. | 0.526 |
9,697,108 | 1 | 3 | 1. A method, comprising: recording an interaction between a test device operating system and an application, the recording of the interaction being by an initiating of the recording of a template to capture a first screenshot of the test device, the interaction being based on a user input from a user; wherein the recording of the interaction comprises intercepting at least one method invocation based on the user input, processing the method invocation using wrappered instantiated objects from a call stack, overriding at least one instantiated object with a category implementation, calling the category implementation, logging data using the called category implementation, the logged data pertaining to the interaction of the user with the test device operating system in an application recording phase, testing each of the at least one method invocations in a series of method invocations from the called category implementation, capturing a second screenshot of a result of the testing, visually comparing the first screenshot with the second screenshot, constructing verification points, aggregating the tested method invocations, and returning the data to the test device operating system to preserve the call stack; wherein the instantiated objects are class implementations wrappered in the category implementations; sending the recorded interaction between the test device operating system and the application to a server; and testing an initiation of the application recording phase using a visible overlaid control set; compiling data pertaining to the recorded interaction in a script compiler of the server, the data comprising human-readable action-description language; sending the compiled data comprising human-readable action-description language from the script compiler of the server to a developer device; returning modified data from the developer device to the server; wherein data pertaining to the recorded interaction is compressed as a text-based standard that outlines captured events as objects, wherein the compressed data is formatted to obfuscate the recorded interaction. | 1. A method, comprising: recording an interaction between a test device operating system and an application, the recording of the interaction being by an initiating of the recording of a template to capture a first screenshot of the test device, the interaction being based on a user input from a user; wherein the recording of the interaction comprises intercepting at least one method invocation based on the user input, processing the method invocation using wrappered instantiated objects from a call stack, overriding at least one instantiated object with a category implementation, calling the category implementation, logging data using the called category implementation, the logged data pertaining to the interaction of the user with the test device operating system in an application recording phase, testing each of the at least one method invocations in a series of method invocations from the called category implementation, capturing a second screenshot of a result of the testing, visually comparing the first screenshot with the second screenshot, constructing verification points, aggregating the tested method invocations, and returning the data to the test device operating system to preserve the call stack; wherein the instantiated objects are class implementations wrappered in the category implementations; sending the recorded interaction between the test device operating system and the application to a server; and testing an initiation of the application recording phase using a visible overlaid control set; compiling data pertaining to the recorded interaction in a script compiler of the server, the data comprising human-readable action-description language; sending the compiled data comprising human-readable action-description language from the script compiler of the server to a developer device; returning modified data from the developer device to the server; wherein data pertaining to the recorded interaction is compressed as a text-based standard that outlines captured events as objects, wherein the compressed data is formatted to obfuscate the recorded interaction. 3. The method of claim 1 , further comprising compiling a script from compiler templates based on encoded data pertaining to the recorded interaction. | 0.660633 |
7,526,073 | 1 | 10 | 1. A computer-readable medium having instructions stored thereon that, when executed by a computer, cause the computer to: open a short message service (SMS) menu selected by a user of a first telecommunications terminal; activate an interactive voice response (IVR) option selected from the SMS menu, wherein an IVR system prompts the user to supply spoken input, the spoken input comprising a spoken message; translate the spoken message to a text message; and transmit the text message to a second telecommunications terminal over a telecommunications network. | 1. A computer-readable medium having instructions stored thereon that, when executed by a computer, cause the computer to: open a short message service (SMS) menu selected by a user of a first telecommunications terminal; activate an interactive voice response (IVR) option selected from the SMS menu, wherein an IVR system prompts the user to supply spoken input, the spoken input comprising a spoken message; translate the spoken message to a text message; and transmit the text message to a second telecommunications terminal over a telecommunications network. 10. The computer-readable medium of claim 1 , wherein the first telecommunications terminal is a wireline telephone and the second telecommunications terminal is a wireless terminal. | 0.740741 |
10,146,672 | 12 | 15 | 12. One or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors causes: selecting the (UI) model using a selection module ( 210 ); creating a test case model for the selected UI model and populating the created test case model into a test case editor ( 222 ) using a test case model creation module ( 212 ), wherein the test case model is created as a sequence of UI Actions based on a structure pattern of the selected UI model; validating the test case model for the selected UI model using a validation module ( 214 ); generating a test case script from the test case model for the selected UI model using a script generation module ( 216 ). | 12. One or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors causes: selecting the (UI) model using a selection module ( 210 ); creating a test case model for the selected UI model and populating the created test case model into a test case editor ( 222 ) using a test case model creation module ( 212 ), wherein the test case model is created as a sequence of UI Actions based on a structure pattern of the selected UI model; validating the test case model for the selected UI model using a validation module ( 214 ); generating a test case script from the test case model for the selected UI model using a script generation module ( 216 ). 15. The one or more non-transitory machine readable information storage mediums of claim 12 , further comprising a synchronizing module ( 218 ) configured to synchronize the test case model for the selected UI model with the selected UI model as the sequence of UI Actions based on the structure pattern of the selected UI model. | 0.602657 |
5,446,883 | 1 | 6 | 1. A method for retrieving a solution document in response to an inquiry from among a system of distributed data bases, the system having at least a first and a second computer, each computer having a data base of solution documents, the method comprising the steps of: receiving at least one inquiry into the first computer, the inquiry having a subject; searching the data base of the first computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the first computer related to the subject of the inquiry, retrieving the solution document from the first computer; responsive to finding no solution document in the data base of the first computer related to the subject of the inquiry, performing the steps of: generating in the first computer, a document from at least one inquiry in the first computer for which no solution document was found, the document containing for each such inquiry the subject of the inquiry, and an identity of the computer in which the inquiry originated; transmitting the document to the second computer; extracting in the second computer any inquiries from the document; for each extracted inquiry, searching the data base of the second computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the second computer, retrieving the solution document from the second computer and exporting the solution document to the computer in which the inquiry originated; and, responsive to finding no solution document in the data base of the second computer, notifying the computer in which the inquiry originated that no solution document has been found. | 1. A method for retrieving a solution document in response to an inquiry from among a system of distributed data bases, the system having at least a first and a second computer, each computer having a data base of solution documents, the method comprising the steps of: receiving at least one inquiry into the first computer, the inquiry having a subject; searching the data base of the first computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the first computer related to the subject of the inquiry, retrieving the solution document from the first computer; responsive to finding no solution document in the data base of the first computer related to the subject of the inquiry, performing the steps of: generating in the first computer, a document from at least one inquiry in the first computer for which no solution document was found, the document containing for each such inquiry the subject of the inquiry, and an identity of the computer in which the inquiry originated; transmitting the document to the second computer; extracting in the second computer any inquiries from the document; for each extracted inquiry, searching the data base of the second computer for a solution document related to the subject of the inquiry; responsive to finding at least one solution document in the data base of the second computer, retrieving the solution document from the second computer and exporting the solution document to the computer in which the inquiry originated; and, responsive to finding no solution document in the data base of the second computer, notifying the computer in which the inquiry originated that no solution document has been found. 6. The method of claim 1, wherein in each computer the data base of solution documents is organized in an acyclic graph. | 0.951338 |
9,703,875 | 10 | 12 | 10. A method comprising: receiving a query, over a network, from a client machine, the query including at least one keyword; identifying a filter context based on the query, the filter context including a first plurality of filters, the first plurality of filters including a plurality of attribute-value pairs, the plurality of attribute-value pairs including a first attribute-value pair including a first filter and a second attribute-value pair including a second filter, the identifying the filter context being performed by one or more processors; identifying a second plurality of filters responsive to the receiving of the query, the identifying the second plurality of filters is based on the filter context and probabilities describing occurrences of attribute-value pairs in a first plurality of listings that respectively describe items that were previously transacted on a network-based marketplace; generating a user interface including search results that are identified based on the filter context; and communicating the user interface, over the network, to the client machine. | 10. A method comprising: receiving a query, over a network, from a client machine, the query including at least one keyword; identifying a filter context based on the query, the filter context including a first plurality of filters, the first plurality of filters including a plurality of attribute-value pairs, the plurality of attribute-value pairs including a first attribute-value pair including a first filter and a second attribute-value pair including a second filter, the identifying the filter context being performed by one or more processors; identifying a second plurality of filters responsive to the receiving of the query, the identifying the second plurality of filters is based on the filter context and probabilities describing occurrences of attribute-value pairs in a first plurality of listings that respectively describe items that were previously transacted on a network-based marketplace; generating a user interface including search results that are identified based on the filter context; and communicating the user interface, over the network, to the client machine. 12. The method of claim 10 , wherein the first plurality of listings includes a listing that includes a title, wherein the identifying the second plurality of filters includes sorting the second plurality of filters based on a probability of the first attribute-value pair randomly occurring in the title. | 0.604922 |
9,378,293 | 1 | 4 | 1. A method for authoring an output page, the method comprising: reading page markup language data; validating the page markup language data according to a schema for the page markup language; presenting one or more available components defined using component markup language, the available components including pre-defined layouts of an output page; reading component markup language data, the component markup language data including at least one component reference from the one or more available components; validating the component reference in the page markup language data; translating the page markup language data and the component markup language data to intermediate output page markup language data; translating the intermediate output page markup language data to first output page markup language data; editing at least one component of the one or more available components, the at least one component referenced by the first output page markup language data; and updating the first output page markup language data based on the editing of the at least one component. | 1. A method for authoring an output page, the method comprising: reading page markup language data; validating the page markup language data according to a schema for the page markup language; presenting one or more available components defined using component markup language, the available components including pre-defined layouts of an output page; reading component markup language data, the component markup language data including at least one component reference from the one or more available components; validating the component reference in the page markup language data; translating the page markup language data and the component markup language data to intermediate output page markup language data; translating the intermediate output page markup language data to first output page markup language data; editing at least one component of the one or more available components, the at least one component referenced by the first output page markup language data; and updating the first output page markup language data based on the editing of the at least one component. 4. The method of claim 1 , further comprising: reading a library of page markup language templates; and translating the first output page markup language data to second output page markup language data using the library of page markup language templates. | 0.673522 |
9,298,869 | 12 | 13 | 12. The method of claim 3 , wherein the data structure of the power domain hierarchy comprises a plurality of design instances; and the step of analyzing the power intent description contents to determine the one or more power domain relationships between the plurality of power domains in the data structure of the power domain hierarchy further comprises: based on the power intent description contents retrieved from the power intent description file, determining a mapping relationship between a scope of a specific design instance of the plurality of design instances and a base domain of the specific design instance, and selectively updating the mapping relationship when needed; and determining the one or more power domain relationships between the plurality of power domains in the data structure of the power domain hierarchy with aid of the mapping relationship. | 12. The method of claim 3 , wherein the data structure of the power domain hierarchy comprises a plurality of design instances; and the step of analyzing the power intent description contents to determine the one or more power domain relationships between the plurality of power domains in the data structure of the power domain hierarchy further comprises: based on the power intent description contents retrieved from the power intent description file, determining a mapping relationship between a scope of a specific design instance of the plurality of design instances and a base domain of the specific design instance, and selectively updating the mapping relationship when needed; and determining the one or more power domain relationships between the plurality of power domains in the data structure of the power domain hierarchy with aid of the mapping relationship. 13. The method of claim 12 , wherein any design instance of the plurality of design instances falls within a power domain of the plurality of power domains in the data structure of the power domain hierarchy. | 0.906643 |
9,967,101 | 9 | 11 | 9. A non-transitory computer-readable medium having computer instructions stored thereon that are executable by a processing device to perform or control performance of operations comprising: determining a random enrollment polynomial; extracting a set of enrollment feature points from an enrollment biometric measurement; randomly selecting one or more enrollment code words from a linear error correction code; determining obfuscated enrollment feature point data describing an obfuscated version of the set of enrollment feature points that is obfuscated using the one or more enrollment code words so that the set of enrollment feature points cannot be determined from the obfuscated enrollment feature point data without the one or more enrollment code words; determining obfuscated enrollment code word data describing an obfuscated version of the one or more enrollment code words that is obfuscated using the random enrollment polynomial so that the one or more code words cannot be determined from the obfuscated enrollment code word data without the random enrollment polynomial; determining an enrollment biometric template including the obfuscated enrollment feature point data and the obfuscated enrollment code word data; generating a public key based on the random enrollment polynomial, wherein the public key obfuscates the random enrollment polynomial; determining enrollment data that keeps the one or more enrollment code words and the random enrollment polynomial secret, the enrollment data including the enrollment biometric template and the public key; extracting a set of verification feature points from a verification biometric measurement responsive to receiving a verification challenge including the enrollment data and a random number value, wherein the enrollment data is associated with an enrollment user and the verification biometric measurement is associated with a verification user attempting to authenticate as the enrollment user; analyzing the enrollment data to determine the obfuscated enrollment feature point data included in the enrollment biometric template of the enrollment data; determining one or more verification code words based on the set of verification feature points and the obfuscated enrollment feature point data; analyzing the enrollment data to determine the public key included in the enrollment data; and determining a verification polynomial based on the one or more verification code words. | 9. A non-transitory computer-readable medium having computer instructions stored thereon that are executable by a processing device to perform or control performance of operations comprising: determining a random enrollment polynomial; extracting a set of enrollment feature points from an enrollment biometric measurement; randomly selecting one or more enrollment code words from a linear error correction code; determining obfuscated enrollment feature point data describing an obfuscated version of the set of enrollment feature points that is obfuscated using the one or more enrollment code words so that the set of enrollment feature points cannot be determined from the obfuscated enrollment feature point data without the one or more enrollment code words; determining obfuscated enrollment code word data describing an obfuscated version of the one or more enrollment code words that is obfuscated using the random enrollment polynomial so that the one or more code words cannot be determined from the obfuscated enrollment code word data without the random enrollment polynomial; determining an enrollment biometric template including the obfuscated enrollment feature point data and the obfuscated enrollment code word data; generating a public key based on the random enrollment polynomial, wherein the public key obfuscates the random enrollment polynomial; determining enrollment data that keeps the one or more enrollment code words and the random enrollment polynomial secret, the enrollment data including the enrollment biometric template and the public key; extracting a set of verification feature points from a verification biometric measurement responsive to receiving a verification challenge including the enrollment data and a random number value, wherein the enrollment data is associated with an enrollment user and the verification biometric measurement is associated with a verification user attempting to authenticate as the enrollment user; analyzing the enrollment data to determine the obfuscated enrollment feature point data included in the enrollment biometric template of the enrollment data; determining one or more verification code words based on the set of verification feature points and the obfuscated enrollment feature point data; analyzing the enrollment data to determine the public key included in the enrollment data; and determining a verification polynomial based on the one or more verification code words. 11. The non-transitory computer-readable medium of claim 9 , wherein the enrollment data is transmitted via an unencrypted communication. | 0.833333 |
7,801,354 | 3 | 5 | 3. The learning device according to claim 2 , wherein the model feature points and the learning feature points are selected in accordance with types of feature quantities at the corresponding feature points. | 3. The learning device according to claim 2 , wherein the model feature points and the learning feature points are selected in accordance with types of feature quantities at the corresponding feature points. 5. The learning device according to claim 3 , wherein the model feature points and the learning feature points exist within a region in the recognition target. | 0.938752 |
4,744,050 | 1 | 9 | 1. In a text processor comprising input means for inputting a character string comprised of characters of a first type, macro table containing therein as pairs a phrases comprised of characters of a second type and macro codes corresponding to each phrase and comprised of character strings of characters of the first type, and conversion means for effecting a first conversion by searching said macro table based upon the input character string and selecting a phrase from among the phrases contained in the macro table corresponding to the character string inputted by said input means when the input character string is equal to one of the macro codes already contained in said macro table, and for effecting a second conversion by generating a single-character of the second type or a phrase comprised of characters of the second type, both having the same reading as that represented by the input character string when the input character string is not equal to any of the macro codes contained in the macro table; a method for automatically registering frequently used phrases and macro codes therefor into said macro table, comprising steps of: (a) repeatedly storing into a phrase table, phrases each generated by said second conversion for the input character string at least when a generated phrase is different from any of the phrases already stored in said phrase table; (b) incrementing frequency-of-occurrence-data signals of each of the phrases already stored in the phrase table each time a phrase, the same as a phrase already stored in the phrase table, is generated by said second conversion; (c) selecting, at predetermined timings, at least one phrase of the phrases already stored in the phrase table which satisfies a predetermined condition as to frequency of occurrence in order for the phrase to be registered in the macro table, in accordance with the frequency-of-occurrence-data signal of the phrases already stored in the phrase table; (d) determining a macro code for the selected phrase so that the determined macro code differs from any of macro codes already registered in said macro table; (e) registering as a pair the selected phrase and the determined macro code in the macro table; and (f) indicating the selected phrase and the determined macro code to an operator of the text processor. | 1. In a text processor comprising input means for inputting a character string comprised of characters of a first type, macro table containing therein as pairs a phrases comprised of characters of a second type and macro codes corresponding to each phrase and comprised of character strings of characters of the first type, and conversion means for effecting a first conversion by searching said macro table based upon the input character string and selecting a phrase from among the phrases contained in the macro table corresponding to the character string inputted by said input means when the input character string is equal to one of the macro codes already contained in said macro table, and for effecting a second conversion by generating a single-character of the second type or a phrase comprised of characters of the second type, both having the same reading as that represented by the input character string when the input character string is not equal to any of the macro codes contained in the macro table; a method for automatically registering frequently used phrases and macro codes therefor into said macro table, comprising steps of: (a) repeatedly storing into a phrase table, phrases each generated by said second conversion for the input character string at least when a generated phrase is different from any of the phrases already stored in said phrase table; (b) incrementing frequency-of-occurrence-data signals of each of the phrases already stored in the phrase table each time a phrase, the same as a phrase already stored in the phrase table, is generated by said second conversion; (c) selecting, at predetermined timings, at least one phrase of the phrases already stored in the phrase table which satisfies a predetermined condition as to frequency of occurrence in order for the phrase to be registered in the macro table, in accordance with the frequency-of-occurrence-data signal of the phrases already stored in the phrase table; (d) determining a macro code for the selected phrase so that the determined macro code differs from any of macro codes already registered in said macro table; (e) registering as a pair the selected phrase and the determined macro code in the macro table; and (f) indicating the selected phrase and the determined macro code to an operator of the text processor. 9. A method for automatically registering frequently used phrases according to claim 1, wherein said phrase selecting step is carried out each time the second conversion is effected. | 0.913989 |
7,730,005 | 10 | 13 | 10. The computer program product of claim 9 , further comprising: computer usable program code for creating an action item associated with the lesson learned, wherein the action item comprises at least a target date for completion, an owner assignment, and a manager of the owner assignment, and wherein the target date for completion, the owner assignment, and the manager of the owner assignment is received from a submitter; computer usable program code for sending the action item to an owner; computer usable program code for receiving an action resolution from the owner in response to sending the action item; computer usable program code for forwarding the action resolution to the submitter; computer usable program code for receiving the submitter response to the action resolution; and computer usable program code for changing the status of the action item accordingly. | 10. The computer program product of claim 9 , further comprising: computer usable program code for creating an action item associated with the lesson learned, wherein the action item comprises at least a target date for completion, an owner assignment, and a manager of the owner assignment, and wherein the target date for completion, the owner assignment, and the manager of the owner assignment is received from a submitter; computer usable program code for sending the action item to an owner; computer usable program code for receiving an action resolution from the owner in response to sending the action item; computer usable program code for forwarding the action resolution to the submitter; computer usable program code for receiving the submitter response to the action resolution; and computer usable program code for changing the status of the action item accordingly. 13. The computer program product of claim 10 , further comprising: computer usable program code for, responsive to a submission of the action resolution by the owner, changing the status of the action item to a pending submitter sign-off status; and computer usable program code for, responsive to a response of the submitter to the action resolution indicating acceptance, changing the status of the action item to a closed status. | 0.832947 |
8,595,220 | 11 | 17 | 11. A system for sharing summaries indicative of a document, comprising: one or more processing units; and memory comprising instructions that when executed by at least some of the one or more processing units, perform a method comprising: providing, for presentation to a first distinctly identifiable entity, a first summary of the document, the first summary authored by a second distinctly identifiable entity; receiving feedback from the first distinctly identifiable entity resulting in a modification to the first summary to generate a first modified summary; providing, for presentation to a third distinctly identifiable entity, the first modified summary of the document and a second summary of the document in a first ranked order; receiving feedback from the third distinctly identifiable entity related to at least one of the first modified summary or the second summary; and providing the first modified summary and the second summary in a second ranked order, the second ranked order different than the first ranked order, the second ranked order a function of the feedback received from the third distinctly identifiable entity. | 11. A system for sharing summaries indicative of a document, comprising: one or more processing units; and memory comprising instructions that when executed by at least some of the one or more processing units, perform a method comprising: providing, for presentation to a first distinctly identifiable entity, a first summary of the document, the first summary authored by a second distinctly identifiable entity; receiving feedback from the first distinctly identifiable entity resulting in a modification to the first summary to generate a first modified summary; providing, for presentation to a third distinctly identifiable entity, the first modified summary of the document and a second summary of the document in a first ranked order; receiving feedback from the third distinctly identifiable entity related to at least one of the first modified summary or the second summary; and providing the first modified summary and the second summary in a second ranked order, the second ranked order different than the first ranked order, the second ranked order a function of the feedback received from the third distinctly identifiable entity. 17. The system of claim 11 , the method comprising: receiving user input from the third distinctly identifiable entity indicative of a desire to retrieve summaries pertaining to a subject, the providing for presentation to a third distinctly identifiable entity comprising: providing the first modified summary and the second summary based upon the user input. | 0.501385 |
7,792,830 | 5 | 6 | 5. A method as claimed in claim 1 , wherein analyzing the average precision against the number of terms includes clustering results of the queries into categories of behaviour. | 5. A method as claimed in claim 1 , wherein analyzing the average precision against the number of terms includes clustering results of the queries into categories of behaviour. 6. A method as claimed in claim 5 , wherein the categories of behaviour include: easily findable document sets, document sets requiring long queries to be located, and document sets which are not findable. | 0.94789 |
8,996,687 | 27 | 30 | 27. The apparatus of claim 24 , wherein the query is to include device descriptive information, application descriptive information and identity information. | 27. The apparatus of claim 24 , wherein the query is to include device descriptive information, application descriptive information and identity information. 30. The apparatus of claim 27 , wherein the operations further comprise receiving a context grant message including the context information when authorization based on at least the application descriptive information is successful. | 0.901366 |
7,777,729 | 1 | 2 | 1. A method for editing handwritten data using a pen enabled computing device having a writing surface and a writing stylus selectively communicable with the writing surface, said method comprising: detecting a position and a movement of the writing stylus with respect to the writing surface to form a handwritten input; automatically defining a bounding box encompassing at least a portion of each stroke of the handwritten input, wherein a size of the bounding box is based on the position and the movement of the writing stylus; storing the handwritten input and the bounding box; and editing the handwritten input to at least one of add textual data to the handwritten input, insert textual data between strokes encompassed by adjacent bounding boxes, delete at least one stroke encompassed by a bounding box, and replace at least one stroke encompassed by a bounding box with alternate textual data. | 1. A method for editing handwritten data using a pen enabled computing device having a writing surface and a writing stylus selectively communicable with the writing surface, said method comprising: detecting a position and a movement of the writing stylus with respect to the writing surface to form a handwritten input; automatically defining a bounding box encompassing at least a portion of each stroke of the handwritten input, wherein a size of the bounding box is based on the position and the movement of the writing stylus; storing the handwritten input and the bounding box; and editing the handwritten input to at least one of add textual data to the handwritten input, insert textual data between strokes encompassed by adjacent bounding boxes, delete at least one stroke encompassed by a bounding box, and replace at least one stroke encompassed by a bounding box with alternate textual data. 2. A method according to claim 1 wherein detecting the position and movement of the writing stylus comprises sampling the motion of the writing stylus with respect to the writing surface so as to form a coordinate representation of each stroke of the handwritten input. | 0.656888 |
8,024,321 | 6 | 8 | 6. An apparatus, comprising: at least one processor; a memory; and program code resident in the memory and configured to be executed by the at least one processor to process a database query by retrieving a cached access plan for the database query, the access plan including look ahead predicate generation information; and determining whether to perform look ahead predicate generation for the database query based upon the look ahead predicate generation information in the access plan. | 6. An apparatus, comprising: at least one processor; a memory; and program code resident in the memory and configured to be executed by the at least one processor to process a database query by retrieving a cached access plan for the database query, the access plan including look ahead predicate generation information; and determining whether to perform look ahead predicate generation for the database query based upon the look ahead predicate generation information in the access plan. 8. The apparatus of claim 6 , wherein the program code is configured to update the look ahead predicate generation information in the cached access plan based upon at least one change in the way look ahead predicate generation is used to process the database query. | 0.729039 |
9,052,812 | 1 | 10 | 1. A system comprising: a first workstation that instantiates a graphical design environment that provides a drag and drop interface to a first user, wherein the drag and drop interface allows a first user to add a widget to a design; a note interface in the graphical design environment that displays a note field for accepting a text string from the first user; an intermittent coded representation of the design that: (i) is exported from the design environment; and (ii) includes a set of at least two widgets that includes the widget; a second workstation that instantiates a first design player that renders the design using the intermittent coded representation for a second user after the design has been exported from the graphical design environment; a first discussion interface that: (i) is displayed in the first design player consistently with the design; (ii) displays the text string from the first user as a note; and (iii) accepts a first comment from the second user regarding the note; an interface element that: (i) is in the first discussion interface with the note; and (ii) when selected, places the first design player into a state wherein a selection of the widget by the second user links the note with the widget, wherein the state exposes each widget in the set of at least two widgets for selection by the second user; a third workstation that instantiates a second design player that renders the design using a copy of the intermittent coded representation for a third user after the design has been exported from the graphical design environment; a second discussion interface that: (i) is displayed in the second design player consistently with the design; and (ii) accepts a second comment from the third user; and a data store that is accessible to the graphical design environment and the first design player, and that is not accessible to the second design player; wherein the first comment is displayed in real time in the graphical design environment after being accepted in the first discussion interface; wherein the second comment is displayed in the graphical design environment after being accepted in the second discussion interface, saved to disk, and imported into the data store; and wherein the text string and comment are stored in the data store along with an indication of the widget selected by the second user. | 1. A system comprising: a first workstation that instantiates a graphical design environment that provides a drag and drop interface to a first user, wherein the drag and drop interface allows a first user to add a widget to a design; a note interface in the graphical design environment that displays a note field for accepting a text string from the first user; an intermittent coded representation of the design that: (i) is exported from the design environment; and (ii) includes a set of at least two widgets that includes the widget; a second workstation that instantiates a first design player that renders the design using the intermittent coded representation for a second user after the design has been exported from the graphical design environment; a first discussion interface that: (i) is displayed in the first design player consistently with the design; (ii) displays the text string from the first user as a note; and (iii) accepts a first comment from the second user regarding the note; an interface element that: (i) is in the first discussion interface with the note; and (ii) when selected, places the first design player into a state wherein a selection of the widget by the second user links the note with the widget, wherein the state exposes each widget in the set of at least two widgets for selection by the second user; a third workstation that instantiates a second design player that renders the design using a copy of the intermittent coded representation for a third user after the design has been exported from the graphical design environment; a second discussion interface that: (i) is displayed in the second design player consistently with the design; and (ii) accepts a second comment from the third user; and a data store that is accessible to the graphical design environment and the first design player, and that is not accessible to the second design player; wherein the first comment is displayed in real time in the graphical design environment after being accepted in the first discussion interface; wherein the second comment is displayed in the graphical design environment after being accepted in the second discussion interface, saved to disk, and imported into the data store; and wherein the text string and comment are stored in the data store along with an indication of the widget selected by the second user. 10. The system of claim 1 , wherein: the first discussion interface displays an identifier for the first user with the note. | 0.846154 |
8,224,845 | 12 | 14 | 12. A computer program product for generating a transactions prediction model for optimizing a plurality of transactions associated with a database system, the computer program product comprising: a non-transitory computer readable medium; first program instructions for capturing a database workload, wherein the database workload includes a plurality of statements corresponding with the transactions over a specified period of time, wherein each of the plurality of statements includes at least one variable parameter, and wherein each of the plurality of statements includes a database command; second program instructions for generating a plurality of first generalized statements from the plurality of statements by replacing the at least one variable parameter with a constant value; third program instructions for generating a plurality of second generalized statements, wherein two or more of the plurality of first generalized statements are the same grouping the two or more of the plurality of first generalized statements to correspond with the plurality of second generalized statements; fourth program instructions for creating a plurality of transactions classes, wherein each of the plurality of transaction classes includes at least one of the plurality of first generalized statements, and wherein each of the plurality of transaction classes represents a common sequence of transactions; fifth program instructions for identifying a plurality of possible sequences between the plurality of transaction classes, wherein the plurality of transaction classes correspond with the database workload; sixth program instructions for calculating a probability of the possible sequences between the plurality of transaction classes to generate the transactions prediction model; seventh program instructions for receiving a current transaction; eighth program instructions for identifying one of the plurality of transaction classes corresponding with the current transaction from the transactions prediction model; ninth program instructions for predicting a next transaction class based on a highest probability of the transactions prediction model; and tenth program instructions for pre-fetching data associated with the next transaction class. | 12. A computer program product for generating a transactions prediction model for optimizing a plurality of transactions associated with a database system, the computer program product comprising: a non-transitory computer readable medium; first program instructions for capturing a database workload, wherein the database workload includes a plurality of statements corresponding with the transactions over a specified period of time, wherein each of the plurality of statements includes at least one variable parameter, and wherein each of the plurality of statements includes a database command; second program instructions for generating a plurality of first generalized statements from the plurality of statements by replacing the at least one variable parameter with a constant value; third program instructions for generating a plurality of second generalized statements, wherein two or more of the plurality of first generalized statements are the same grouping the two or more of the plurality of first generalized statements to correspond with the plurality of second generalized statements; fourth program instructions for creating a plurality of transactions classes, wherein each of the plurality of transaction classes includes at least one of the plurality of first generalized statements, and wherein each of the plurality of transaction classes represents a common sequence of transactions; fifth program instructions for identifying a plurality of possible sequences between the plurality of transaction classes, wherein the plurality of transaction classes correspond with the database workload; sixth program instructions for calculating a probability of the possible sequences between the plurality of transaction classes to generate the transactions prediction model; seventh program instructions for receiving a current transaction; eighth program instructions for identifying one of the plurality of transaction classes corresponding with the current transaction from the transactions prediction model; ninth program instructions for predicting a next transaction class based on a highest probability of the transactions prediction model; and tenth program instructions for pre-fetching data associated with the next transaction class. 14. The computer program product of claim 12 , further comprising: twelfth program instructions for determining a think time between the possible sequences, the think time configured to at least predict when to start the next transaction class. | 0.502041 |
9,576,048 | 10 | 13 | 10. An apparatus comprising: a memory; and at least one processor, coupled to said memory, and operative to: carry out offline functionality-based co-ranking and clustering on a knowledge base, said knowledge base characterizing a heterogeneous information technology services network comprising a plurality of services, a plurality of providers, and a plurality of attributes; store results of said functionality-based co-ranking and clustering as annotations of said services and said providers in said knowledge base, to obtain an annotated knowledge base; obtain a service requirement from a customer requiring information technology services; query said annotated knowledge base, based on said service requirement; and return to said customer an ordered list of at least given ones of said services, based on said querying, wherein said at least one processor is operative to carry out said offline functionality-based co-ranking and clustering on said knowledge base by: calculating an initial service clustering for said heterogeneous information technology services network; classifying said providers into a plurality of service clusters; within each of said service clusters, ranking each of said providers; integrating ranking and clustering distances between said providers into a uniform provider distance to obtain updated provider similarity; classifying said services into a plurality of provider clusters; within each of said provider clusters, ranking each of said services; and integrating ranking and clustering distances between said services into a uniform service distance to obtain updated service similarity. | 10. An apparatus comprising: a memory; and at least one processor, coupled to said memory, and operative to: carry out offline functionality-based co-ranking and clustering on a knowledge base, said knowledge base characterizing a heterogeneous information technology services network comprising a plurality of services, a plurality of providers, and a plurality of attributes; store results of said functionality-based co-ranking and clustering as annotations of said services and said providers in said knowledge base, to obtain an annotated knowledge base; obtain a service requirement from a customer requiring information technology services; query said annotated knowledge base, based on said service requirement; and return to said customer an ordered list of at least given ones of said services, based on said querying, wherein said at least one processor is operative to carry out said offline functionality-based co-ranking and clustering on said knowledge base by: calculating an initial service clustering for said heterogeneous information technology services network; classifying said providers into a plurality of service clusters; within each of said service clusters, ranking each of said providers; integrating ranking and clustering distances between said providers into a uniform provider distance to obtain updated provider similarity; classifying said services into a plurality of provider clusters; within each of said provider clusters, ranking each of said services; and integrating ranking and clustering distances between said services into a uniform service distance to obtain updated service similarity. 13. The apparatus of claim 10 , wherein said at least one processor is further operative to: repeat said steps of classifying said providers, ranking each of said providers; integrating said ranking and clustering distances between said providers, classifying said services, ranking each of said services, and integrating ranking and clustering distances between said services, until convergence is achieved; wherein, in said storing of said results of said functionality-based co-ranking and clustering as annotations of said services and said providers in said knowledge base, to obtain said annotated knowledge base, said results comprise results of said convergence. | 0.720833 |
7,577,651 | 66 | 67 | 66. The system of claim 62 wherein determining comprises predicting an average precision of the search query using a combination of the features of the temporal profile. | 66. The system of claim 62 wherein determining comprises predicting an average precision of the search query using a combination of the features of the temporal profile. 67. The system of claim 66 wherein determining comprises predicting an average precision of the search query using a combination of the features of the temporal profile and a content feature. | 0.9389 |
7,475,000 | 1 | 4 | 1. A computerized system for generating user-configured designs of integrated circuits, comprising: a user interface adapted to provide and receive information to and from a user, respectively; and an object-oriented design environment operatively coupled to said user interface and having a plurality of associated design tools, wherein a plurality of components associated with said designs of integrated circuits are represented as objects, at least a portion of said objects being encapsulated and containing information relating to both the interface and build hierarchy associated with its respective design component, said design tools using said information within said objects to build said design, said objects being user-configurable and selectable within said environment via said user interface; wherein said objects being user configurable comprises adding an extension instruction to said designs of integrated circuits, said extension instruction comprising a mixed length instruction set architecture that utilizes instructions of at least two lengths without a mode switch. | 1. A computerized system for generating user-configured designs of integrated circuits, comprising: a user interface adapted to provide and receive information to and from a user, respectively; and an object-oriented design environment operatively coupled to said user interface and having a plurality of associated design tools, wherein a plurality of components associated with said designs of integrated circuits are represented as objects, at least a portion of said objects being encapsulated and containing information relating to both the interface and build hierarchy associated with its respective design component, said design tools using said information within said objects to build said design, said objects being user-configurable and selectable within said environment via said user interface; wherein said objects being user configurable comprises adding an extension instruction to said designs of integrated circuits, said extension instruction comprising a mixed length instruction set architecture that utilizes instructions of at least two lengths without a mode switch. 4. The system of claim 1 , wherein said plurality of components comprise a processor core and an extension instruction, said information comprising HDL that must be added to HDL associated with said core for said extension. | 0.502232 |
8,271,286 | 1 | 12 | 1. A non-transitory computer readable storage media storing thereon computer readable instructions that, when executed by a computing device, cause the computing device to: receive a voice input signal; convert the voice input signal into a text representation of the voice input signal; determine if the voice input signal is to be employed for use as at least one of: a domain name and a messaging address; in response to determining the voice input signal is to be employed for use in a domain name: generate a uniform resource identifier (URI) by appending to the text representation of the voice input signal at least a top level domain identifier; and determine a registration status of the URI, the registration status comprising one of: registered and unregistered. | 1. A non-transitory computer readable storage media storing thereon computer readable instructions that, when executed by a computing device, cause the computing device to: receive a voice input signal; convert the voice input signal into a text representation of the voice input signal; determine if the voice input signal is to be employed for use as at least one of: a domain name and a messaging address; in response to determining the voice input signal is to be employed for use in a domain name: generate a uniform resource identifier (URI) by appending to the text representation of the voice input signal at least a top level domain identifier; and determine a registration status of the URI, the registration status comprising one of: registered and unregistered. 12. The non-transitory computer readable storage media of claim 1 , wherein the generating the URI further comprises appending to the text representation of the voice input signal at least a second level domain identifier. | 0.786948 |
9,026,535 | 17 | 19 | 17. A non-transitory computer-readable medium comprising software, the software when executed by one or more processing units operable to perform operations comprising: accessing text; identifying a plurality of terms from the text; determining a plurality of term vectors associated with the identified plurality of terms; calculating a weight of each of the determined plurality of term vectors; clustering the determined plurality of term vectors into a plurality of clusters, the plurality of clusters comprising a first cluster related to a first concept of the text and a second cluster related to a second concept of the text, the first concept being distinct from the second concept, the first and second clusters each comprising two or more of the determined term vectors, the clustering comprising grouping two or more of the determined term vectors together based on the determined weights of the two or more term vectors and a distance between the two or more term vectors; identifying, using latent semantic analysis (LSA), a first set of terms associated with the first cluster; identifying, using LSA, a second set of terms associated with the second cluster; determining a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the weights of the term vectors of the first cluster, and wherein the second weight is based at least on the weights of the term vectors of the second cluster; determining a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; selecting one or more terms from the first set of terms according to the determined first percentage; selecting one or more terms from the second set of terms according to the determined second percentage; combining the selected terms from the first and second sets of terms into the list of output terms, the list of output terms having the first and second concepts of the text; and storing the list of output terms in one or more memory units. | 17. A non-transitory computer-readable medium comprising software, the software when executed by one or more processing units operable to perform operations comprising: accessing text; identifying a plurality of terms from the text; determining a plurality of term vectors associated with the identified plurality of terms; calculating a weight of each of the determined plurality of term vectors; clustering the determined plurality of term vectors into a plurality of clusters, the plurality of clusters comprising a first cluster related to a first concept of the text and a second cluster related to a second concept of the text, the first concept being distinct from the second concept, the first and second clusters each comprising two or more of the determined term vectors, the clustering comprising grouping two or more of the determined term vectors together based on the determined weights of the two or more term vectors and a distance between the two or more term vectors; identifying, using latent semantic analysis (LSA), a first set of terms associated with the first cluster; identifying, using LSA, a second set of terms associated with the second cluster; determining a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the weights of the term vectors of the first cluster, and wherein the second weight is based at least on the weights of the term vectors of the second cluster; determining a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; selecting one or more terms from the first set of terms according to the determined first percentage; selecting one or more terms from the second set of terms according to the determined second percentage; combining the selected terms from the first and second sets of terms into the list of output terms, the list of output terms having the first and second concepts of the text; and storing the list of output terms in one or more memory units. 19. The non-transitory computer-readable medium of claim 17 , the one or more processing units further operable to perform operations comprising: creating a query pseudo-document from the determined plurality of term vectors; creating a first leaned pseudo-document using the query pseudo-document; and creating a second leaned pseudo-document using and the query pseudo-document; and wherein: identifying the first set of terms associated with the first cluster comprises using LSA of the first leaned pseudo-document; and identifying the second set of terms associated with the second cluster comprises using LSA of the second leaned pseudo-document. | 0.500766 |
8,320,531 | 10 | 12 | 10. A method in accordance with claim 2 , further comprising establishing the telephone connection. | 10. A method in accordance with claim 2 , further comprising establishing the telephone connection. 12. A method in accordance with claim 10 , wherein the step of establishing the telephone connection comprises: receiving from the user a designated telephone number; and calling the user at the designated telephone number. | 0.931763 |
5,384,703 | 1 | 21 | 1. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing text represented by characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of expressions in the document not contained in a stop list and having at least a first predetermined level of complexity, said stop list stored in the memory of said computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring expressions determined in step (a), said seed list stored in said memory of said computer; c) using said computer, automatically forming a summary of the document comprised of regions in the document containing at least two members of said seed list, said summary stored in said memory of said computer; and d) using said computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the members of said seed list to said stop list and reducing said first predetermined level of complexity. | 1. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing text represented by characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of expressions in the document not contained in a stop list and having at least a first predetermined level of complexity, said stop list stored in the memory of said computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring expressions determined in step (a), said seed list stored in said memory of said computer; c) using said computer, automatically forming a summary of the document comprised of regions in the document containing at least two members of said seed list, said summary stored in said memory of said computer; and d) using said computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the members of said seed list to said stop list and reducing said first predetermined level of complexity. 21. The method of claim 1, wherein said second predetermined number is at least six. | 0.95736 |
8,244,529 | 13 | 14 | 13. The method for multi-pass echo residue detection of claim 12 , further comprising: determining that the user speech input has an unacceptable level of echo residue when the amplitude of the maximum correlation result is greater than the predetermined maximum correlation threshold. | 13. The method for multi-pass echo residue detection of claim 12 , further comprising: determining that the user speech input has an unacceptable level of echo residue when the amplitude of the maximum correlation result is greater than the predetermined maximum correlation threshold. 14. The method for multi-pass echo residue detection of claim 13 , further comprising: storing the user speech input determined as having an acceptable level of echo residue and the user speech input determined as having an unacceptable level of echo residue in a data warehouse. | 0.795154 |
8,438,573 | 7 | 9 | 7. A non-transitory computer-readable storage medium storing instructions which, when executed, cause one or more processors to perform the steps of: interpreting a resource profile of a first resource in a plurality of resources, wherein each resource in the plurality of resources is a logical or physical entity that enables an application to provide services, and the resource profile includes one or more attributes of the first resource, wherein at least one attribute defines a dependency between the first resource and a resource type and not any particular resource of that resource type, and wherein at least one attribute is inherited by the resource profile from a type profile that includes default attributes that augment the resource profile by supplying a value for at least one attribute that is not defined in the resource profile; determining, based on the resource profile of the first resource that the first resource is of a first resource type and has a dependency on a second resource type; and managing the plurality of resources by at least: determining that a second resource is an instance of the second resource type; provisioning the second resource to satisfy the dependency; and provisioning the first resource. | 7. A non-transitory computer-readable storage medium storing instructions which, when executed, cause one or more processors to perform the steps of: interpreting a resource profile of a first resource in a plurality of resources, wherein each resource in the plurality of resources is a logical or physical entity that enables an application to provide services, and the resource profile includes one or more attributes of the first resource, wherein at least one attribute defines a dependency between the first resource and a resource type and not any particular resource of that resource type, and wherein at least one attribute is inherited by the resource profile from a type profile that includes default attributes that augment the resource profile by supplying a value for at least one attribute that is not defined in the resource profile; determining, based on the resource profile of the first resource that the first resource is of a first resource type and has a dependency on a second resource type; and managing the plurality of resources by at least: determining that a second resource is an instance of the second resource type; provisioning the second resource to satisfy the dependency; and provisioning the first resource. 9. The non-transitory computer-readable storage medium of claim 7 , wherein the resource types are part of a resource type hierarchy; and wherein the step of managing the dependencies further includes determining, based at least in part on the resource type hierarchy, that a third type satisfies a dependency specifying the second type. | 0.501479 |
9,444,773 | 16 | 22 | 16. A system comprising: a data repository that stores language capabilities of users within a pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and an analysis engine comprising a processor, the analysis engine configured to: receive data entered at a user interface of a user device by a first user associated with the pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested, determine, using data from the data repository, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, and cause an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to be transmitted to the user device for display on the user interface; wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group. | 16. A system comprising: a data repository that stores language capabilities of users within a pre-determined user group, the language capabilities of the users within the pre-determined user group being determined automatically based on mining a corpus of electronic documents associated with the pre-determined user group; and an analysis engine comprising a processor, the analysis engine configured to: receive data entered at a user interface of a user device by a first user associated with the pre-determined user group, the data comprising an identification of a) a source language and b) a target language to which translation from the source language is requested, determine, using data from the data repository, that one or more second users of the pre-determined user group is associated with the source language and associated with the target language, each of the second users being a candidate to perform a translation from the source language to the target language, and cause an identification of the one or more second users, each of whom is a candidate to perform a translation from the source language to the target language, to be transmitted to the user device for display on the user interface; wherein the display of the identification of the one or more second users is based on a permission that allows a corresponding second user to be identified to one or more other users in the pre-determined user group. 22. The system of claim 16 , wherein the permission is provided by the corresponding second user. | 0.917797 |
9,122,318 | 17 | 20 | 17. A method of reducing data entry errors in a system having an input component, a display component and a processor operatively coupled to the input and display components, the method comprising: displaying, by the input component, a plurality of keys selectable by a user in accordance with a controllable viewing mode, receiving, by the input component, input by the user; displaying, by the display component, one or more key images based on the input by the user; ascertaining, by the processor, a subset of the keys selectable by the user based upon respective likelihoods that each of the keys follows a previously selected key or keys within a predetermined language or subset thereof; defining the controllable viewing mode so that the input component displays each of the keys within the ascertained subset of keys in a manner visually distinguishable by the user from each of the keys not within the ascertained subset of keys; defining the controllable viewing mode so that the input component is controlled to display each of the keys within the ascertained subset of keys in a three-dimensional format that includes a top surface and side surfaces, and to display each of the keys not within the ascertained subset of keys in a three-dimensional format that includes a bottom surface and side surfaces. | 17. A method of reducing data entry errors in a system having an input component, a display component and a processor operatively coupled to the input and display components, the method comprising: displaying, by the input component, a plurality of keys selectable by a user in accordance with a controllable viewing mode, receiving, by the input component, input by the user; displaying, by the display component, one or more key images based on the input by the user; ascertaining, by the processor, a subset of the keys selectable by the user based upon respective likelihoods that each of the keys follows a previously selected key or keys within a predetermined language or subset thereof; defining the controllable viewing mode so that the input component displays each of the keys within the ascertained subset of keys in a manner visually distinguishable by the user from each of the keys not within the ascertained subset of keys; defining the controllable viewing mode so that the input component is controlled to display each of the keys within the ascertained subset of keys in a three-dimensional format that includes a top surface and side surfaces, and to display each of the keys not within the ascertained subset of keys in a three-dimensional format that includes a bottom surface and side surfaces. 20. The method of claim 17 , wherein the input component and the display component collectively are a touch sensitive display. | 0.903226 |
8,706,713 | 14 | 22 | 14. A method of searching for desired information, the method comprising: receiving, from a user device having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user device as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user device, and non-selection of the first advertisement at the user device; receiving refinement information comprising a refined search argument from the user device; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user device. | 14. A method of searching for desired information, the method comprising: receiving, from a user device having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user device as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user device, and non-selection of the first advertisement at the user device; receiving refinement information comprising a refined search argument from the user device; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user device. 22. The method of claim 14 , further comprising maintaining a user profile associated with the user device. | 0.742788 |
7,626,111 | 3 | 4 | 3. The method of claim 1 , wherein the classifying a mood and a genre of the music file using the generated music content summary includes: extracting a modified discrete cosine transformation (MDCT)-based timbre feature from the music content summary; extracting an MDCT-based tempo feature from the music content summary; and classifying the mood and the genre of the music file based on the extracted timbre feature tempo feature. | 3. The method of claim 1 , wherein the classifying a mood and a genre of the music file using the generated music content summary includes: extracting a modified discrete cosine transformation (MDCT)-based timbre feature from the music content summary; extracting an MDCT-based tempo feature from the music content summary; and classifying the mood and the genre of the music file based on the extracted timbre feature tempo feature. 4. The method of claim 3 , wherein the extracting an MDCT-based timbre feature from the music content summary includes: extracting MDCT coefficients by decoding a part of the music content summary; selecting a predetermined number of MDCT coefficients of a sub-band from the extracted MDCT coefficients; and extracting a spectral centroid, a bandwidth, a rolloff, a flux, and a flatness from the selected MDCT coefficients. | 0.835409 |
8,886,624 | 25 | 27 | 25. A search method using an extended keyword pool, the method comprising: generating a purchased keyword set by searching for a keyword having a purchase history through a search advertisement; generating an additional keyword set by extracting a keyword from at least one source; generating 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; providing an associated keyword or an extended keyword with respect to a search word, using the keywords included in the purchased keyword set, the additional keyword set, and the unified search keyword set, as a keyword pool; providing 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; increasing 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 increasing the associated scores of intersection keywords commonly included in the purchased keyword set and the additional keyword set. | 25. A search method using an extended keyword pool, the method comprising: generating a purchased keyword set by searching for a keyword having a purchase history through a search advertisement; generating an additional keyword set by extracting a keyword from at least one source; generating 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; providing an associated keyword or an extended keyword with respect to a search word, using the keywords included in the purchased keyword set, the additional keyword set, and the unified search keyword set, as a keyword pool; providing 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; increasing 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 increasing the associated scores of intersection keywords commonly included in the purchased keyword set and the additional keyword set. 27. The method of claim 25 , wherein generating the additional keyword set comprises updating the additional keyword set by extracting a keyword from the at least one source at every desired period. | 0.912467 |
8,213,719 | 13 | 17 | 13. A computer-readable storage device comprising instructions for controlling a computer system to edit 2D structures using a natural input method, wherein the instructions, upon execution, cause a processor to perform actions comprising: receiving from a typeset application a typeset format representation of a 2D object; converting the 2D object from the typeset format representation to a digital ink representation of the 2D object; providing the converted digital ink representation of the 2D object to a natural input application, wherein the natural input application includes at least one recognizer for a specific 2D domain; receiving modified typeset format representation of the 2D object from the recognizer of the natural input application; and providing the modified typeset format representation of the 2D object to the typeset application. | 13. A computer-readable storage device comprising instructions for controlling a computer system to edit 2D structures using a natural input method, wherein the instructions, upon execution, cause a processor to perform actions comprising: receiving from a typeset application a typeset format representation of a 2D object; converting the 2D object from the typeset format representation to a digital ink representation of the 2D object; providing the converted digital ink representation of the 2D object to a natural input application, wherein the natural input application includes at least one recognizer for a specific 2D domain; receiving modified typeset format representation of the 2D object from the recognizer of the natural input application; and providing the modified typeset format representation of the 2D object to the typeset application. 17. The device of claim 13 wherein providing the modified typeset format representation comprises invoking an API of the typeset application for inserting typeset objects into the typeset application. | 0.678457 |
6,088,698 | 17 | 19 | 17. A method of selectively delivering regions of a virtual world to a display client, wherein the virtual world is defined in a plurality of nodes each stored in and described by a table of a relational database management system, the method comprising the steps of: defining a field of view of the display client; storing information in the table that associates each of the nodes with one of the regions of the virtual world; defining a sensor in one of the regions of the virtual world that is adjacent to another of the regions; sensing when the field of view encounters the sensor; and delivering to the display client the nodes that are associated with another of the regions. | 17. A method of selectively delivering regions of a virtual world to a display client, wherein the virtual world is defined in a plurality of nodes each stored in and described by a table of a relational database management system, the method comprising the steps of: defining a field of view of the display client; storing information in the table that associates each of the nodes with one of the regions of the virtual world; defining a sensor in one of the regions of the virtual world that is adjacent to another of the regions; sensing when the field of view encounters the sensor; and delivering to the display client the nodes that are associated with another of the regions. 19. The method recited in claim 17, further comprising the steps of: receiving a source definition of the image; parsing the source definition into a plurality of nodes that define elements of the image; and storing each of the nodes in the description in the table. | 0.829923 |
7,957,954 | 9 | 14 | 9. A data processing system comprising a processor and a computer readable memory unit coupled to the processor, said memory unit containing program code configured to be executed by the processor to implement a method for providing national language support for an application, said method comprising: generating a multi-language property file by processing each individual property file of a plurality of individual property files, wherein each individual property file comprises a file name comprising a label appended to a class and further comprises file content comprising a key value and a translated text pertaining to the label, wherein the key value is a member of the class, wherein said processing each individual property file comprises generating a translation and recording the generated translation in the multi-language property file, wherein the generated translation comprises the translated text and a key comprising the label appended to the key value, wherein the label is null, consists of a language identifier, or consists of the language identifier and a locale identifier, and wherein the translated text of each said translation is formatted in a character set that is displayable in a natural font of a language represented by the translated text; ascertaining, from an operating system of the data processing system, a language identifier and a locale identifier, wherein execution of a language independent application is configured to be performed in a locale identified by the ascertained locale identifier and to display text in accordance with a first key value and in a language identified by the ascertained language identifier; executing the application in the locale identified by the ascertained locale identifier; during said executing the application, selecting from the multi-language property file a translation whose label comprises a key value that matches the first key value and whose label further comprises the ascertained language identifier and the ascertained locale identifier of the executing application or whose label comprises the ascertained language identifier but not the ascertained locale identifier of the executing application or whose label is null; during said executing the application, displaying the translated text of the selected translation in the language identified by the ascertained language identifier. | 9. A data processing system comprising a processor and a computer readable memory unit coupled to the processor, said memory unit containing program code configured to be executed by the processor to implement a method for providing national language support for an application, said method comprising: generating a multi-language property file by processing each individual property file of a plurality of individual property files, wherein each individual property file comprises a file name comprising a label appended to a class and further comprises file content comprising a key value and a translated text pertaining to the label, wherein the key value is a member of the class, wherein said processing each individual property file comprises generating a translation and recording the generated translation in the multi-language property file, wherein the generated translation comprises the translated text and a key comprising the label appended to the key value, wherein the label is null, consists of a language identifier, or consists of the language identifier and a locale identifier, and wherein the translated text of each said translation is formatted in a character set that is displayable in a natural font of a language represented by the translated text; ascertaining, from an operating system of the data processing system, a language identifier and a locale identifier, wherein execution of a language independent application is configured to be performed in a locale identified by the ascertained locale identifier and to display text in accordance with a first key value and in a language identified by the ascertained language identifier; executing the application in the locale identified by the ascertained locale identifier; during said executing the application, selecting from the multi-language property file a translation whose label comprises a key value that matches the first key value and whose label further comprises the ascertained language identifier and the ascertained locale identifier of the executing application or whose label comprises the ascertained language identifier but not the ascertained locale identifier of the executing application or whose label is null; during said executing the application, displaying the translated text of the selected translation in the language identified by the ascertained language identifier. 14. The data processing system of claim 9 , wherein the method determines that no translation in the multi-language property file includes a label that comprises the ascertained language identifier or the ascertained locale, and wherein the label of the selected translation is null. | 0.680587 |
9,514,216 | 16 | 18 | 16. An article comprising: a non-transitory computer readable medium having computer implementable instructions stored thereon to be implemented by one or more processing units in a computing device to transform the computing device into a special purpose device to: access a plurality of segmented portions of at least one of a plurality of web pages to be displayable by one or more digital signals of one or more files stored in a memory, wherein a particular web page of the plurality of web pages is to comprise at least two of the plurality of segmented portions; use one or more machine learned models to: identify one or more feature properties of the plurality of segmented portions within the one or more files, or otherwise to be inferable from the one or more files, classify the at least two of the plurality of segmented portions as at least one of a plurality of segment types to be based, at least in part, on the one or more identified feature properties, the one or more feature properties to be identified are to comprise at least language feature properties of language model of content to be displayed in one or more of the at least two of the plurality of segmented portions, and determine content quality scores for at least two of the plurality of segmented portions of at least the particular web page; and establish one or more digital signals to represent an index within a memory to be coupled to the one or more processing units, the index to be established for the plurality of segmented portions and to be based, at least in part, on the segment type, the index to indicate the content quality scores. | 16. An article comprising: a non-transitory computer readable medium having computer implementable instructions stored thereon to be implemented by one or more processing units in a computing device to transform the computing device into a special purpose device to: access a plurality of segmented portions of at least one of a plurality of web pages to be displayable by one or more digital signals of one or more files stored in a memory, wherein a particular web page of the plurality of web pages is to comprise at least two of the plurality of segmented portions; use one or more machine learned models to: identify one or more feature properties of the plurality of segmented portions within the one or more files, or otherwise to be inferable from the one or more files, classify the at least two of the plurality of segmented portions as at least one of a plurality of segment types to be based, at least in part, on the one or more identified feature properties, the one or more feature properties to be identified are to comprise at least language feature properties of language model of content to be displayed in one or more of the at least two of the plurality of segmented portions, and determine content quality scores for at least two of the plurality of segmented portions of at least the particular web page; and establish one or more digital signals to represent an index within a memory to be coupled to the one or more processing units, the index to be established for the plurality of segmented portions and to be based, at least in part, on the segment type, the index to indicate the content quality scores. 18. The article as recited in claim 16 , wherein the computer implementable instructions to be implemented by the one or more processing units in the computing device are to operatively transform the computing device into the special purpose device to combine the at least two of the plurality of segmented portions into a single segmented portion to be based, at least in part, on at least one feature for the two or more of the plurality of segmented portions. | 0.628617 |
8,832,525 | 11 | 12 | 11. A memory controller, comprising: a memory access circuit for reading a first code word and a second code word from one or more memory devices, wherein the first code word and the second code word respectively comprises a plurality of coded bits; and a low density parity check (LDPC) decoding circuit for decoding the first code word according to the hard information of the coded bits of the first code word; wherein when the LDPC decoding circuit does not decode the first code word successfully according to the hard information of the coded bits of the first code word, the LDPC decoding circuit configures the memory access circuit to read the soft information of the coded bits of the first code word and the soft information of the coded bits of the second code word, and decodes the first code word and the second code word according to the soft information of the coded bits of the first code word and the soft information of the coded bits of the second code word. | 11. A memory controller, comprising: a memory access circuit for reading a first code word and a second code word from one or more memory devices, wherein the first code word and the second code word respectively comprises a plurality of coded bits; and a low density parity check (LDPC) decoding circuit for decoding the first code word according to the hard information of the coded bits of the first code word; wherein when the LDPC decoding circuit does not decode the first code word successfully according to the hard information of the coded bits of the first code word, the LDPC decoding circuit configures the memory access circuit to read the soft information of the coded bits of the first code word and the soft information of the coded bits of the second code word, and decodes the first code word and the second code word according to the soft information of the coded bits of the first code word and the soft information of the coded bits of the second code word. 12. The memory controller of claim 11 , wherein the LDPC decoding circuit generate a plurality of check node messages and a plurality of variable node messages according to the hard information of the first code word to determine whether the LDPC decoding circuit decodes the first code word successfully. | 0.786713 |
9,223,773 | 1 | 7 | 1. A computer system for generating custom template-based documents, the computer system comprising: a template storage device; and one or more hardware processors programmed, via executable code instructions, to implement: a template generator configured to: access a placeholder template comprising one or more placeholders indicating locations for insertion of executable instructions; receive executable instructions to be included in the placeholder template; and store, in the template storage device, a template including one or more sets of the received executable instructions inserted into corresponding placeholders of the placeholder template; a user interface unit configured to: generate one or more user interfaces configured to display one or more selectable graphics each corresponding to one or more respective data objects; and receive, via the one or more user interfaces, selection of one or more data objects to include in a custom document based at least in part on a selection of the one or more selectable graphics by a user, at least one of the selected one or more data objects comprising a person data object; a template selection unit configured to receive a selection of the template; and a template processor configured to: parse the one or more sets of executable instructions included in the template; execute each of the one or more sets of executable instructions, wherein at least one set of first executable instructions includes instructions to access properties of the selected data objects stored in one or more data sources, and wherein at least one of the accessed properties is associated with the person data object, and wherein at least one set of second executable instructions is configured to determine an additional data object and at least one property associated with the additional data object based on at least one property of the selected one or more data objects; generate an output for each of the one or more sets of executable instructions; and generate the custom document by replacing the one or more sets of executable instructions in the template with the output generated by execution of corresponding sets of executable instructions, at least some of the output including properties of the selected one or more data objects, the at least one property associated with the person data object, and the at least one property associated with the additional data object. | 1. A computer system for generating custom template-based documents, the computer system comprising: a template storage device; and one or more hardware processors programmed, via executable code instructions, to implement: a template generator configured to: access a placeholder template comprising one or more placeholders indicating locations for insertion of executable instructions; receive executable instructions to be included in the placeholder template; and store, in the template storage device, a template including one or more sets of the received executable instructions inserted into corresponding placeholders of the placeholder template; a user interface unit configured to: generate one or more user interfaces configured to display one or more selectable graphics each corresponding to one or more respective data objects; and receive, via the one or more user interfaces, selection of one or more data objects to include in a custom document based at least in part on a selection of the one or more selectable graphics by a user, at least one of the selected one or more data objects comprising a person data object; a template selection unit configured to receive a selection of the template; and a template processor configured to: parse the one or more sets of executable instructions included in the template; execute each of the one or more sets of executable instructions, wherein at least one set of first executable instructions includes instructions to access properties of the selected data objects stored in one or more data sources, and wherein at least one of the accessed properties is associated with the person data object, and wherein at least one set of second executable instructions is configured to determine an additional data object and at least one property associated with the additional data object based on at least one property of the selected one or more data objects; generate an output for each of the one or more sets of executable instructions; and generate the custom document by replacing the one or more sets of executable instructions in the template with the output generated by execution of corresponding sets of executable instructions, at least some of the output including properties of the selected one or more data objects, the at least one property associated with the person data object, and the at least one property associated with the additional data object. 7. The system of claim 1 , wherein the template processor comprises: a code interface configured to parse code in multiple programming languages. | 0.866728 |
8,688,451 | 1 | 7 | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user via a microphone associated with an automatic speech recognition system; (b) processing the input speech using a first grammar to obtain parameter values of a first N-best list of vocabulary using at least one processor associated with the automatic speech recognition system; (c) comparing at least one parameter value of a top result of the first N-best list to at least one predetermined threshold value; and (d) subsequently processing the input speech using a second grammar to obtain parameter values of a second N-best list of vocabulary, if the compared at least one parameter value is below the at least one predetermined threshold value; (e) determining the input speech to be in-vocabulary, if any of the results of the first N-best list is also present within the second N-best list, but out-of vocabulary if any of the results of the first N-best list is not within the second N-best list; and (f) providing audible feedback to the user if the input speech is determined to be out-of-vocabulary. | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user via a microphone associated with an automatic speech recognition system; (b) processing the input speech using a first grammar to obtain parameter values of a first N-best list of vocabulary using at least one processor associated with the automatic speech recognition system; (c) comparing at least one parameter value of a top result of the first N-best list to at least one predetermined threshold value; and (d) subsequently processing the input speech using a second grammar to obtain parameter values of a second N-best list of vocabulary, if the compared at least one parameter value is below the at least one predetermined threshold value; (e) determining the input speech to be in-vocabulary, if any of the results of the first N-best list is also present within the second N-best list, but out-of vocabulary if any of the results of the first N-best list is not within the second N-best list; and (f) providing audible feedback to the user if the input speech is determined to be out-of-vocabulary. 7. The method of claim 1 , further comprising the step of creating the second grammar by generating a limited set of vocabulary that includes in-vocabulary within the first grammar. | 0.608225 |
10,127,282 | 1 | 5 | 1. A method for operating a computing device, the method comprising: determining a bit vector for a Bloom filter by (i) determining a set of ternary content addressable memory (TCAM) words to store in a TCAM array, and (ii) performing one or more hash function operations on each of the set of TCAM words; partitioning the TCAM array into a first portion to store the bit vector and a second portion to store the set of TCAM words; storing (i) the bit vector in the first portion of the TCAM array, and (ii) the set of TCAM words in the second portion of the TCAM array; and performing a search of the TCAM array using a search word by (i) performing the one or more hash function operations on the search word to generate a hashed search word, and (iii) determining whether bits at specified positions of the hashed search word match bits at corresponding positions of the bit vector stored in the first portion of the TCAM array before searching the second portion of the TCAM array with the search word. | 1. A method for operating a computing device, the method comprising: determining a bit vector for a Bloom filter by (i) determining a set of ternary content addressable memory (TCAM) words to store in a TCAM array, and (ii) performing one or more hash function operations on each of the set of TCAM words; partitioning the TCAM array into a first portion to store the bit vector and a second portion to store the set of TCAM words; storing (i) the bit vector in the first portion of the TCAM array, and (ii) the set of TCAM words in the second portion of the TCAM array; and performing a search of the TCAM array using a search word by (i) performing the one or more hash function operations on the search word to generate a hashed search word, and (iii) determining whether bits at specified positions of the hashed search word match bits at corresponding positions of the bit vector stored in the first portion of the TCAM array before searching the second portion of the TCAM array with the search word. 5. The method of claim 1 , wherein partitioning the TCAM array includes (i) determining a number of bits of the bit vector for the Bloom filter, (ii) determining that the number of bits of the bit vector for the Bloom filter is equal to or less than a number of bits in a TCAM word in the TCAM array, and (iii) determining that the first portion of the TCAM array is a size of one TCAM word and the second portion of the TCAM array is a remainder of the TCAM array. | 0.786501 |
9,015,099 | 10 | 19 | 10. A method for providing an automated suggestion in response to a current situation pertaining to a location, position, or movement of a person in relation to a physical environment, the method comprising, with a mobile electronic device: by one or more sensors coupled to the mobile electronic device, receiving one or more real-time inputs indicative of an implicit cue regarding a user-specific physical activity in relation to a surrounding physical environment; by an automated inference engine coupled to the mobile electronic device, accessing the real-time inputs and one more items of previously stored information; by the automated inference engine, based on a combination of the one or more real-time inputs and the stored user-specific information, generating a plurality of user-specific contexts, each user-specific context corresponding to a different inferred purpose for the user-specific physical activity; by the automated inference engine, algorithmically selecting a user-specific context of the plurality of different user-specific contexts; generating an automated response based on the selected user-specific context; and by a processor of the mobile electronic device, executing the automated response. | 10. A method for providing an automated suggestion in response to a current situation pertaining to a location, position, or movement of a person in relation to a physical environment, the method comprising, with a mobile electronic device: by one or more sensors coupled to the mobile electronic device, receiving one or more real-time inputs indicative of an implicit cue regarding a user-specific physical activity in relation to a surrounding physical environment; by an automated inference engine coupled to the mobile electronic device, accessing the real-time inputs and one more items of previously stored information; by the automated inference engine, based on a combination of the one or more real-time inputs and the stored user-specific information, generating a plurality of user-specific contexts, each user-specific context corresponding to a different inferred purpose for the user-specific physical activity; by the automated inference engine, algorithmically selecting a user-specific context of the plurality of different user-specific contexts; generating an automated response based on the selected user-specific context; and by a processor of the mobile electronic device, executing the automated response. 19. A computing device comprising at least one processor and computer circuitry coupled to the at least one processor, wherein the computer circuitry is arranged to cause the at least one processor to perform the method of claim 10 . | 0.721292 |
10,102,202 | 1 | 5 | 1. A conversion management (CM) computing device including a processor in communication with a memory, said processor configured to: receive, from a developer computing device, an application identifier associated with a computer application and a plurality of input text strings from the computer application; convert the plurality of input text strings into a plurality of input text tokens; store a setup profile including the application identifier and the plurality of input text tokens; receive a locale request, from a user computing device, including the application identifier and a locale identifier, the locale identifier identifying a language of use for the computer application; identify a matching entry included within a localization table for each of the plurality of input text tokens, wherein each matching entry includes a stored text token matching the respective input text token, a stored locale identifier matching the locale identifer, and an associated translated text string; generate a configuration file including the application identifier, the matched locale identifier, and the associated translated text strings for each of the plurality of input text tokens; and transmit the configuration file to the user computing device. | 1. A conversion management (CM) computing device including a processor in communication with a memory, said processor configured to: receive, from a developer computing device, an application identifier associated with a computer application and a plurality of input text strings from the computer application; convert the plurality of input text strings into a plurality of input text tokens; store a setup profile including the application identifier and the plurality of input text tokens; receive a locale request, from a user computing device, including the application identifier and a locale identifier, the locale identifier identifying a language of use for the computer application; identify a matching entry included within a localization table for each of the plurality of input text tokens, wherein each matching entry includes a stored text token matching the respective input text token, a stored locale identifier matching the locale identifer, and an associated translated text string; generate a configuration file including the application identifier, the matched locale identifier, and the associated translated text strings for each of the plurality of input text tokens; and transmit the configuration file to the user computing device. 5. The CM computing device of claim 1 said processor further configured to transmit the configuration file to the developer computing device for storage within the developer computing device, wherein the configuration file is accessible by the user computing device when the computer application is configured on the user computing device. | 0.69678 |
4,675,840 | 2 | 3 | 2. A computer system as set forth in claim 1 wherein said first and second data conveyance means include: means for sequentially addressing memory locations in said speech memory; means for setting said addressing means to the initial address of said speech memory; and means for incrementing said addressing means to address sequential locations of said speech memory. | 2. A computer system as set forth in claim 1 wherein said first and second data conveyance means include: means for sequentially addressing memory locations in said speech memory; means for setting said addressing means to the initial address of said speech memory; and means for incrementing said addressing means to address sequential locations of said speech memory. 3. A computer system a set forth in claim 2 wherein said speech memory comprises: dynamic random access memory; and means for periodically refreshing said dynamic memory. | 0.937911 |
9,602,965 | 8 | 10 | 8. The method of claim 1 , further comprising accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, wherein the first user corresponds to a first node in the social graph and the plurality of candidate place-entities corresponds to a plurality of second nodes in the social graph, respectively. | 8. The method of claim 1 , further comprising accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, wherein the first user corresponds to a first node in the social graph and the plurality of candidate place-entities corresponds to a plurality of second nodes in the social graph, respectively. 10. The method of claim 8 , wherein the confidence score is further based on social-graph information associated with a second user of the online social network, the second user being within a threshold degree of separation from the first user. | 0.900651 |
8,386,889 | 1 | 7 | 1. A control module comprising: an encoder module configured to (i) receive data, and (ii) based on the data, generate a first code word for a plurality of drives; a detector module configured to, in response to detecting an error in a first drive of the plurality of drives subsequent to generation of the first code word, initiate replacement of the first drive with a second drive, wherein the encoder module is configured to generate a second code word for the second drive; a mapping module configured to (i) map physical locations of the data in the plurality of drives to logical locations of the first code word, (ii) assign a predetermined value to one of the logical locations corresponding to the first drive to identify an unused one of the logical locations, and (iii) assign the unused one of the logical locations to the second drive based on the predetermined value; and a difference module configured to generate a third code word based on each of the first code word and the second code word, wherein the encoder module is configured to generate an updated code word for the plurality of drives based on the first code word and the third code word. | 1. A control module comprising: an encoder module configured to (i) receive data, and (ii) based on the data, generate a first code word for a plurality of drives; a detector module configured to, in response to detecting an error in a first drive of the plurality of drives subsequent to generation of the first code word, initiate replacement of the first drive with a second drive, wherein the encoder module is configured to generate a second code word for the second drive; a mapping module configured to (i) map physical locations of the data in the plurality of drives to logical locations of the first code word, (ii) assign a predetermined value to one of the logical locations corresponding to the first drive to identify an unused one of the logical locations, and (iii) assign the unused one of the logical locations to the second drive based on the predetermined value; and a difference module configured to generate a third code word based on each of the first code word and the second code word, wherein the encoder module is configured to generate an updated code word for the plurality of drives based on the first code word and the third code word. 7. The control module of claim 1 , wherein: the encoder module is configured to generate the first code word for a plurality of drives based on a cyclic code generator polynomial; and the cyclic code generator polynomial is a Reed-Solomon code generator polynomial. | 0.625706 |
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