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9,208,143 | 2 | 3 | 2. The electronic dictionary device of claim 1 , wherein the first display screen and the second display screen comprise separate display devices. | 2. The electronic dictionary device of claim 1 , wherein the first display screen and the second display screen comprise separate display devices. 3. The electronic dictionary device of claim 2 , further comprising a character input module which inputs a search character; wherein the processor further implements an entry word list display process of creating an entry word list based on the dictionary data when the character input module has input a search character and displaying the entry word list on the second display screen, and wherein the common word list display process displays a list of common words on the first display screen when the entry word list display process displays an entry word list on the second display screen. | 0.5 |
8,271,408 | 12 | 13 | 12. A system for use in an online advertising exchange, comprising one or more server computers coupled to the Internet; and one or more databases coupled to the one or more server computers; wherein the one or more server computers are for: constructing a machine learning-based and pairwise ranking method-based classification model for binary classification of items as positive or negative with regard to a single class based on training using a training set of examples comprising positive examples and unlabelled examples with regard to the class; wherein the model comprises a plurality of features, a single hyperparameter, a single threshold parameter, and a decision function; and wherein the training of the model comprises learning a plurality of weighting parameters, each of the plurality of weighting parameters mapping to a feature of the plurality of features, in such a way that positive examples are to be scored higher, in connection with being positive, than unlabelled examples; and wherein the hyperparameter and the threshold parameter are selected for optimal model performance with regard to, in connection with the single class, constraining positive items to be classified as positive while minimizing a number of unlabelled items to be classified as positive; storing the model, comprising the features, the mapping of the weighting parameters with the features, the weighting parameters, the hyperparameter, the threshold parameter, and the decision function, in at least one of the one or more databases; and using the decision function for classifying items as positive or negative with regard to the class, wherein the deciding is based at least in part on scores and the threshold parameter. | 12. A system for use in an online advertising exchange, comprising one or more server computers coupled to the Internet; and one or more databases coupled to the one or more server computers; wherein the one or more server computers are for: constructing a machine learning-based and pairwise ranking method-based classification model for binary classification of items as positive or negative with regard to a single class based on training using a training set of examples comprising positive examples and unlabelled examples with regard to the class; wherein the model comprises a plurality of features, a single hyperparameter, a single threshold parameter, and a decision function; and wherein the training of the model comprises learning a plurality of weighting parameters, each of the plurality of weighting parameters mapping to a feature of the plurality of features, in such a way that positive examples are to be scored higher, in connection with being positive, than unlabelled examples; and wherein the hyperparameter and the threshold parameter are selected for optimal model performance with regard to, in connection with the single class, constraining positive items to be classified as positive while minimizing a number of unlabelled items to be classified as positive; storing the model, comprising the features, the mapping of the weighting parameters with the features, the weighting parameters, the hyperparameter, the threshold parameter, and the decision function, in at least one of the one or more databases; and using the decision function for classifying items as positive or negative with regard to the class, wherein the deciding is based at least in part on scores and the threshold parameter. 13. The system of claim 12 , wherein classifying an item as positive is based at least in part on a score associated with the item being sufficiently high. | 0.720217 |
9,715,694 | 1 | 5 | 1. A method, comprising: presenting, to a user by at least one server communicatively coupled to a network, a drill-down survey comprising one or more questions wherein each of the questions corresponds to a node in a tree structure, wherein the tree structure comprises parent nodes and child nodes of the parent nodes, and wherein each question corresponding to one of the child nodes is more specific than the question corresponding to each of that child node's parent nodes; parsing, by the at least one server, responses to the questions from the user into a first plurality of keywords associated with at least one of the user, a website of the user, and a business of the user; determining, by the at least one server from one or more of the responses, a third party data source identified by the user, the third party data source being remote from the at least one server and accessible by the at least one server via the network; receiving, by the at least one server from the user, an authorization for the at least one server to access the third party data source using a third party account of the user; obtaining, by the at least one server, additional data about the user from the third party data source, the additional data being obtainable from the third party data source only using the third party account; parsing, by the at least one server, the additional data about the user from the third party data source into a second plurality of keywords; generating, by the at least one server, a keyword basket comprising the first plurality of keywords and the second plurality of keywords; generating, by the at least one server, a candidate domain name relevant to the first plurality of keywords and to the additional data by combining keywords in the keyword basket into a root name of the candidate domain name; and displaying, to the user by the at least one server, a user interface including the candidate domain name, the user interface enabling the user to register the candidate domain name. | 1. A method, comprising: presenting, to a user by at least one server communicatively coupled to a network, a drill-down survey comprising one or more questions wherein each of the questions corresponds to a node in a tree structure, wherein the tree structure comprises parent nodes and child nodes of the parent nodes, and wherein each question corresponding to one of the child nodes is more specific than the question corresponding to each of that child node's parent nodes; parsing, by the at least one server, responses to the questions from the user into a first plurality of keywords associated with at least one of the user, a website of the user, and a business of the user; determining, by the at least one server from one or more of the responses, a third party data source identified by the user, the third party data source being remote from the at least one server and accessible by the at least one server via the network; receiving, by the at least one server from the user, an authorization for the at least one server to access the third party data source using a third party account of the user; obtaining, by the at least one server, additional data about the user from the third party data source, the additional data being obtainable from the third party data source only using the third party account; parsing, by the at least one server, the additional data about the user from the third party data source into a second plurality of keywords; generating, by the at least one server, a keyword basket comprising the first plurality of keywords and the second plurality of keywords; generating, by the at least one server, a candidate domain name relevant to the first plurality of keywords and to the additional data by combining keywords in the keyword basket into a root name of the candidate domain name; and displaying, to the user by the at least one server, a user interface including the candidate domain name, the user interface enabling the user to register the candidate domain name. 5. The method of claim 1 , wherein one or more of the questions is an open-ended question. | 0.733728 |
9,720,948 | 15 | 17 | 15. A computing apparatus, comprising: a processor; and a local storage device configured to maintain a multidimensional index; wherein the processor is configured to provide one alphanumeric key to any record of a plurality of records not including an alphanumeric key and further configured to provide one text description comprising at least one word to any record of the plurality of records not including a text description comprising at least one word; wherein the multidimensional index is determined by the processor and comprises at least one four element index associated with each record, the four element index comprising: a pointer pointing from one alphanumeric key to one associated record; a text description pointer pointing from each text description to the one associated record; a first reverse word index pointer pointing from each word to one alphanumeric key; and a second reverse word index pointer pointing from each word to one text description. | 15. A computing apparatus, comprising: a processor; and a local storage device configured to maintain a multidimensional index; wherein the processor is configured to provide one alphanumeric key to any record of a plurality of records not including an alphanumeric key and further configured to provide one text description comprising at least one word to any record of the plurality of records not including a text description comprising at least one word; wherein the multidimensional index is determined by the processor and comprises at least one four element index associated with each record, the four element index comprising: a pointer pointing from one alphanumeric key to one associated record; a text description pointer pointing from each text description to the one associated record; a first reverse word index pointer pointing from each word to one alphanumeric key; and a second reverse word index pointer pointing from each word to one text description. 17. The computing apparatus of claim 15 , wherein at least one of the pointer, the text description pointer, the first reverse word index pointer, and the second reverse word index pointer comprise an offset to a file containing one associated record. | 0.513566 |
10,135,910 | 6 | 8 | 6. A system comprising: at least one processor; at least one memory device; at least one module stored by the at least one memory device and executable by the at least one processor, wherein the at least one module is configured to perform operations comprising: rendering, by an application executing on a target platform, a document that specifies one or more widgets of each of a first widget type and a second widget type, the rendering including: in response to determining, by the application, that the application includes a first native widget renderer for rendering the one or more widgets of the first widget type, wherein the first native widget renderer is written using an application program interface (API) that is native to the target platform, rendering the one or more widgets of the first widget type by the first native widget renderer for first widget type, and in response to determining, by the application, that the application does not include a second native widget renderer for rendering the one or more widgets of the second widget type, wherein the second native widget renderer is written using the API that is native to the target platform, rendering the one or more widgets of the second widget type by a default widget renderer for the second widget type, wherein the default widget renderer is written using cross-platform code for a plurality of target platforms including the target platform. | 6. A system comprising: at least one processor; at least one memory device; at least one module stored by the at least one memory device and executable by the at least one processor, wherein the at least one module is configured to perform operations comprising: rendering, by an application executing on a target platform, a document that specifies one or more widgets of each of a first widget type and a second widget type, the rendering including: in response to determining, by the application, that the application includes a first native widget renderer for rendering the one or more widgets of the first widget type, wherein the first native widget renderer is written using an application program interface (API) that is native to the target platform, rendering the one or more widgets of the first widget type by the first native widget renderer for first widget type, and in response to determining, by the application, that the application does not include a second native widget renderer for rendering the one or more widgets of the second widget type, wherein the second native widget renderer is written using the API that is native to the target platform, rendering the one or more widgets of the second widget type by a default widget renderer for the second widget type, wherein the default widget renderer is written using cross-platform code for a plurality of target platforms including the target platform. 8. The system of claim 6 , wherein the at least one module is configured to perform operations comprising: downloading, by the application, the default widget renderer for rendering the second widget type from a network location specified by the document. | 0.662698 |
8,719,228 | 1 | 3 | 1. A method for identifying obsolete discussion threads in a forum, comprising: extracting a plurality of keywords from a discussion thread, wherein the discussion thread comprises a plurality of postings posted by a plurality of users; assigning an initial keyword score to each of the plurality of keywords; identifying a change event, wherein the change event is a change affecting a topic of the forum; extracting a keyword from a recorded medium recording the change event, wherein the recorded medium is separate from the forum; comparing the keyword from the recorded medium with the plurality of keywords from the discussion thread to identify a matching keyword in the plurality of keywords; decreasing the initial keyword score of the matching keyword to a decreased score for the matching keyword based on the matching keyword matching the keyword from the recorded medium; aggregating the keyword score assigned to each of the plurality of keywords to obtain a total score for the discussion thread, wherein aggregating comprises using the reduced score for the matching keyword; and displaying a warning on a user interface comprising the discussion thread when the total score is below a first pre-specified threshold. | 1. A method for identifying obsolete discussion threads in a forum, comprising: extracting a plurality of keywords from a discussion thread, wherein the discussion thread comprises a plurality of postings posted by a plurality of users; assigning an initial keyword score to each of the plurality of keywords; identifying a change event, wherein the change event is a change affecting a topic of the forum; extracting a keyword from a recorded medium recording the change event, wherein the recorded medium is separate from the forum; comparing the keyword from the recorded medium with the plurality of keywords from the discussion thread to identify a matching keyword in the plurality of keywords; decreasing the initial keyword score of the matching keyword to a decreased score for the matching keyword based on the matching keyword matching the keyword from the recorded medium; aggregating the keyword score assigned to each of the plurality of keywords to obtain a total score for the discussion thread, wherein aggregating comprises using the reduced score for the matching keyword; and displaying a warning on a user interface comprising the discussion thread when the total score is below a first pre-specified threshold. 3. The method of claim 1 , wherein the initial keyword score of the matching keyword is decreased by subtracting a constant amount. | 0.657068 |
8,081,827 | 4 | 6 | 4. The method defined in claim 1 further wherein extracting one or more features comprises determining a compression type and object location for each of a plurality of objects in the compressed file without decoding any codestream. | 4. The method defined in claim 1 further wherein extracting one or more features comprises determining a compression type and object location for each of a plurality of objects in the compressed file without decoding any codestream. 6. The method defined in claim 4 further comprising weighting bit allocations differently for at least two of the plurality of compression types. | 0.594972 |
8,010,466 | 6 | 7 | 6. The method of claim 5 , further comprising generating a salience score for the plurality of email messages based on a result of the determination of whether the generated hash values and the associated bit mask values match corresponding hash values and the associated bit mask values related to prior email messages of the class. | 6. The method of claim 5 , further comprising generating a salience score for the plurality of email messages based on a result of the determination of whether the generated hash values and the associated bit mask values match corresponding hash values and the associated bit mask values related to prior email messages of the class. 7. The method of claim 6 comprising the further step of taking remedial action when the one of the plurality of email messages is a potentially unwanted email. | 0.5 |
7,855,799 | 4 | 5 | 4. The method of claim 1 , further comprising: receiving an input selecting a specific page comprised in the electronic document, said specific page having the first of the plurality of page sizes; receiving an input requesting to identify an insertion sheet for the specific page; receiving an input identifying a media type to be inserted adjacent to the specific page; storing an association between the specific page and the media type to be inserted adjacent to the specific page. | 4. The method of claim 1 , further comprising: receiving an input selecting a specific page comprised in the electronic document, said specific page having the first of the plurality of page sizes; receiving an input requesting to identify an insertion sheet for the specific page; receiving an input identifying a media type to be inserted adjacent to the specific page; storing an association between the specific page and the media type to be inserted adjacent to the specific page. 5. The method of claim 4 , wherein receiving an input identifying a media type to be inserted adjacent to the specific page further comprises receiving an input identifying to insert a media type before the specific page. | 0.5 |
8,356,030 | 13 | 17 | 13. A system for constructing a domain-specific sentiment classifier for classifying sentiment expressed by documents in a specified domain, comprising: a non-transitory computer readable storage medium storing computer-executable instructions, the computer executable instructions comprising: a scoring module configured to score sentiments expressed by one or more domain-specific documents, the scoring module configured to score by performing steps comprising: determining that one or more of the domain-specific documents include an n-gram, calculating a score for the n-gram included in the one or more domain-specific documents, and calculating a sentiment score for the one or more domain-specific documents based on the score for the n-gram included in the documents; a lexicon module configured to create a domain-specific sentiment lexicon based at least in part on said scoring sentiments expressed by one or more domain-specific documents; a classifier module configured to generate the domain-specific sentiment classifier based on the domain-specific sentiment lexicon; and a storing module configured to store the domain-specific sentiment classifier. | 13. A system for constructing a domain-specific sentiment classifier for classifying sentiment expressed by documents in a specified domain, comprising: a non-transitory computer readable storage medium storing computer-executable instructions, the computer executable instructions comprising: a scoring module configured to score sentiments expressed by one or more domain-specific documents, the scoring module configured to score by performing steps comprising: determining that one or more of the domain-specific documents include an n-gram, calculating a score for the n-gram included in the one or more domain-specific documents, and calculating a sentiment score for the one or more domain-specific documents based on the score for the n-gram included in the documents; a lexicon module configured to create a domain-specific sentiment lexicon based at least in part on said scoring sentiments expressed by one or more domain-specific documents; a classifier module configured to generate the domain-specific sentiment classifier based on the domain-specific sentiment lexicon; and a storing module configured to store the domain-specific sentiment classifier. 17. The system of claim 13 , wherein the classifier module is further configured to: build a model having n-grams of the domain-specific sentiment lexicon as features; and train the model on a training corpus having a set of high-sentiment documents. | 0.725877 |
8,856,111 | 1 | 10 | 1. A method comprising: storing a plurality of entities including a primary entity and a plurality of secondary entities, wherein the entities are text descriptors; storing a plurality of videos; storing a plurality of web pages; matching the primary entity to a primary video subset of the stored videos and a primary web page subset of the stored web pages; determining a first set of co-interaction scores between the primary video subset and a secondary video subset of the stored videos; determining a second set of co-interaction scores between the primary web page subset and a secondary web page subset of the stored web pages; matching the secondary video subset and the secondary web page subset to the secondary entities; determining a relatedness score between the primary entity and each of the secondary entities, the relatedness scores based on the first and second sets of co-interaction scores; and ranking the secondary entities according to their respective relatedness scores. | 1. A method comprising: storing a plurality of entities including a primary entity and a plurality of secondary entities, wherein the entities are text descriptors; storing a plurality of videos; storing a plurality of web pages; matching the primary entity to a primary video subset of the stored videos and a primary web page subset of the stored web pages; determining a first set of co-interaction scores between the primary video subset and a secondary video subset of the stored videos; determining a second set of co-interaction scores between the primary web page subset and a secondary web page subset of the stored web pages; matching the secondary video subset and the secondary web page subset to the secondary entities; determining a relatedness score between the primary entity and each of the secondary entities, the relatedness scores based on the first and second sets of co-interaction scores; and ranking the secondary entities according to their respective relatedness scores. 10. The method of claim 1 wherein determining the relatedness score between the primary entity and a secondary entity comprises aggregating the first and second sets of co-interaction scores. | 0.699686 |
8,001,551 | 1 | 6 | 1. At a Web server, the Web server including a script handler for providing client-side scripts and corresponding appropriately localized resources to a Web browser, a method for utilizing localized resources for client-side scripts, the method comprising: an act of receiving a Web page request from the Web browser, the Web page request indicating a user-interface culture of the Web browser, the user-interface culture including at least a language used by the Web browser; an act of accessing a server-side page that corresponds to the Web page; an act of executing a script manager that is referenced in the server-side page; an act of the script manager accessing a client-side script reference included in the server-side page, the client-side script reference referring to a client-side script that is to be executed at the Web browser, the client-side script including localization calls to external resources; an act of the script manager formulating an adapted client-side script reference to return to the Web browser, the adapted client-side script reference referring to the script handler and including a query portion that identifies at least the referenced client-side script and the user-interface culture of the Web browser; an act of returning the adapted client-side script reference to the Web browser in a Web page responsive to the Web page request; subsequent to returning the adapted client-side script reference to the Web browser, an act of receiving the adapted client-side script reference from the Web browser in response to the Web browser rendering the Web page, reception of the adapted client-side script reference being a request for the referenced client-side script; an act of dispatching the query portion of the adapted client-side script reference to the script handler; an act of the script handler identifying an appropriately localized resource set to use along with the referenced client-side script at the Web server based at least in part on the user-interface culture of the Web browser; an act of the script handler creating a resource set that can be used by the client-side script; and an act of returning the referenced client-side script along with the resource set to the Web browser in a single request such that execution of the client-side script at the Web browser can be localized in accordance with resources contained in the formatted localized resource set. | 1. At a Web server, the Web server including a script handler for providing client-side scripts and corresponding appropriately localized resources to a Web browser, a method for utilizing localized resources for client-side scripts, the method comprising: an act of receiving a Web page request from the Web browser, the Web page request indicating a user-interface culture of the Web browser, the user-interface culture including at least a language used by the Web browser; an act of accessing a server-side page that corresponds to the Web page; an act of executing a script manager that is referenced in the server-side page; an act of the script manager accessing a client-side script reference included in the server-side page, the client-side script reference referring to a client-side script that is to be executed at the Web browser, the client-side script including localization calls to external resources; an act of the script manager formulating an adapted client-side script reference to return to the Web browser, the adapted client-side script reference referring to the script handler and including a query portion that identifies at least the referenced client-side script and the user-interface culture of the Web browser; an act of returning the adapted client-side script reference to the Web browser in a Web page responsive to the Web page request; subsequent to returning the adapted client-side script reference to the Web browser, an act of receiving the adapted client-side script reference from the Web browser in response to the Web browser rendering the Web page, reception of the adapted client-side script reference being a request for the referenced client-side script; an act of dispatching the query portion of the adapted client-side script reference to the script handler; an act of the script handler identifying an appropriately localized resource set to use along with the referenced client-side script at the Web server based at least in part on the user-interface culture of the Web browser; an act of the script handler creating a resource set that can be used by the client-side script; and an act of returning the referenced client-side script along with the resource set to the Web browser in a single request such that execution of the client-side script at the Web browser can be localized in accordance with resources contained in the formatted localized resource set. 6. The method as recited in claim 1 , wherein the script handler identifying an appropriately localized resource set comprises an act of identifying a localized resource set based on a language and a country indicated in the query portion. | 0.934913 |
7,509,330 | 1 | 18 | 1. A computer readable storage medium having stored thereon a system for application-layer monitoring of communication between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations, the decoders on the database device being operable to: receive database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for any of the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decode the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database server; and extract query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and a monitoring application residing at an application layer above the decoding layer, the monitoring application residing on the database device at the first network location, the monitoring application being operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders. | 1. A computer readable storage medium having stored thereon a system for application-layer monitoring of communication between one or more database clients and one or more database servers, the system comprising: one or more decoders residing at a decoding layer above a network layer, the decoders residing on a database device at a first network location between one or more database clients residing at one or more second network locations distinct from the first network location and one or more database servers residing at one or more third network locations distinct from both the first network location and the one or more second network locations, the decoders on the database device being operable to: receive database messages communicated over the network from any of the database clients residing at the one or more second network locations and intended for any of the database servers at the one or more third network locations and database messages communicated from the database servers and intended for the database clients; decode the database messages, wherein decoding the database messages comprises decoding a protocol generated as an output of a database connectivity driver in response to an input by a database application residing at an application layer, wherein decoding the database messages comprises decoding database messages of database implementations different from each other and, wherein the database connectivity driver is utilized by the one or more database clients to communicate with the database server; and extract query-language statements from the database messages, wherein the query-language statements are created by the database application at one or more of the database clients and provided as input to the database connectivity driver and the database connectivity driver generate the database message as an output based on the query-language statement; and a monitoring application residing at an application layer above the decoding layer, the monitoring application residing on the database device at the first network location, the monitoring application being operable to receive query-language statements extracted at the decoders and record observations on the database messages based at least in part on the query-language statements extracted at the decoders. 18. The system of claim 1 , further comprising a parser residing at a query-language layer above the decoding layer, the parser being operable to receive query-language statements extracted at the decoders and, before the caching application receives the query-language statements, parse the query-language statements for processing at the caching application. | 0.879357 |
7,778,632 | 1 | 13 | 1. A multi-modal multi-lingual mobile device that facilitates automating an action, comprising: a detection component that employs a plurality of integrated sensors to obtain at least one criterion from an auxiliary act through passive observation, the auxiliary act is a conversation of a user with an entity that is not the mobile device, wherein the at least one criterion is an environmental context that relates to a weather condition, and a schedule manipulation action is performed at least partially in view of at least one of expected travel complications or venue incompatibility with the weather condition; and an analyzer component that evaluates the at least one criterion to infer a user intent and automatically implements the action based at least in part upon operation of a rules-based logic component, wherein the rules based logic component automatically allows execution of the action based at least in part upon satisfaction of a defined rule, and based at least in part upon operation of an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon operation of an artificial intelligence component that comprises a classifier function that maps an input attribute vector x=(x 1 , x 2 , x 3 , x 4 , x n ) to a confidence that input associated with the vector belongs to a class, wherein the x i , are input attributes, wherein the confidence that the input belongs to the class is expressed as f(x)=confidence(class), and wherein the class to which an input belongs infers the action that the user desires to be automatically performed; wherein the auxiliary act is not for an explicit purpose of implementing the action. | 1. A multi-modal multi-lingual mobile device that facilitates automating an action, comprising: a detection component that employs a plurality of integrated sensors to obtain at least one criterion from an auxiliary act through passive observation, the auxiliary act is a conversation of a user with an entity that is not the mobile device, wherein the at least one criterion is an environmental context that relates to a weather condition, and a schedule manipulation action is performed at least partially in view of at least one of expected travel complications or venue incompatibility with the weather condition; and an analyzer component that evaluates the at least one criterion to infer a user intent and automatically implements the action based at least in part upon operation of a rules-based logic component, wherein the rules based logic component automatically allows execution of the action based at least in part upon satisfaction of a defined rule, and based at least in part upon operation of an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon operation of an artificial intelligence component that comprises a classifier function that maps an input attribute vector x=(x 1 , x 2 , x 3 , x 4 , x n ) to a confidence that input associated with the vector belongs to a class, wherein the x i , are input attributes, wherein the confidence that the input belongs to the class is expressed as f(x)=confidence(class), and wherein the class to which an input belongs infers the action that the user desires to be automatically performed; wherein the auxiliary act is not for an explicit purpose of implementing the action. 13. The system of claim 1 , the detection component comprises: an audio recorder component that captures speech of the user interaction with the another user; a speech analysis component that analyzes the captured speech of the user and the another user and determines an identification of the user and the another user, the identification is part of the contextual data; a location detection component that determines a physical location of the user during interaction with the another user, the physical location is part of the contextual data; and a date/time component that determines when the user interacts with the another user, a result of the date/time component determination is part of the contextual data. | 0.5 |
4,674,066 | 8 | 9 | 8. A method for information retrieval for use with a digital data processing apparatus having database storage means for storing signals representative of plural textual expressions and information pertaining thereto, said method comprising the steps of A. accepting an input signal representative of a search linguistic expression in conventional textual reoresentation. B. locating within said database a linguistic exoression matching or similar to said search linguistic expression, said locating step including the steps of converting at least one said database linguistic expression to a linguistically salient word skeleton, and converting said search linguistic expression, or a modified form thereof, to a linguistically salient word skeleton, each said converting step comprising the steps of i. eliminating from the word skeleton produced thereby a selected alpha set, if any, of the expression being converted which lacks isomorphy with a phonetic representation of that selected set, and ii replacing with a different linguistic symbol another selected alpha set, if any, of the expression being converted which lacks isomorphy with a phonetic representation of that other selected set, C. generating for outout a signal indicative of the success of locating at least one database linguistic expression matching or similar to said search linguistic expression and generating for outout signals representative of information pertaining to the matching or similar database linguistic expressions, if any. | 8. A method for information retrieval for use with a digital data processing apparatus having database storage means for storing signals representative of plural textual expressions and information pertaining thereto, said method comprising the steps of A. accepting an input signal representative of a search linguistic expression in conventional textual reoresentation. B. locating within said database a linguistic exoression matching or similar to said search linguistic expression, said locating step including the steps of converting at least one said database linguistic expression to a linguistically salient word skeleton, and converting said search linguistic expression, or a modified form thereof, to a linguistically salient word skeleton, each said converting step comprising the steps of i. eliminating from the word skeleton produced thereby a selected alpha set, if any, of the expression being converted which lacks isomorphy with a phonetic representation of that selected set, and ii replacing with a different linguistic symbol another selected alpha set, if any, of the expression being converted which lacks isomorphy with a phonetic representation of that other selected set, C. generating for outout a signal indicative of the success of locating at least one database linguistic expression matching or similar to said search linguistic expression and generating for outout signals representative of information pertaining to the matching or similar database linguistic expressions, if any. 9. A method according to claim 8 wherein said locating step further comprises the steps of A. selectively modifying said search word skeleton by replacing a set of one or more skeleton symbols with a different set of such symbols, B. comparing said modified search skeleton with a linguistically salient word skeleton of at least one said database linguistic expression, and C. selectively repeating said modifying step and said comparing step. | 0.5 |
8,234,114 | 1 | 5 | 1. A speech interactive system implemented in a computer system having at least a processing device, a storage device, a text input device, a speech input device and an output device, comprising: a target information receiving module implemented by said processing device and including said text input device for receiving target information and setting corresponding target text sentence information; an interactive mode setting and speech processing module implemented by said processing device and including said speech input device for receiving a speech signal, setting an interactive mode, determining target text sentence information for said speech signal, and outputting an assessment for a target text sentence; an interactive information update module implemented by said processing device for updating information in an interactive information recording table stored in said storage device according to said assessment for said target text sentence and a timing count; a decision module implemented by said processing device for deciding an output response for said target text sentence information according to said interactive mode and said information in said interactive information recording table; and an output response module implemented by said processing device and including said output device for outputting response information according to said output response and said information of said interactive information recording table. | 1. A speech interactive system implemented in a computer system having at least a processing device, a storage device, a text input device, a speech input device and an output device, comprising: a target information receiving module implemented by said processing device and including said text input device for receiving target information and setting corresponding target text sentence information; an interactive mode setting and speech processing module implemented by said processing device and including said speech input device for receiving a speech signal, setting an interactive mode, determining target text sentence information for said speech signal, and outputting an assessment for a target text sentence; an interactive information update module implemented by said processing device for updating information in an interactive information recording table stored in said storage device according to said assessment for said target text sentence and a timing count; a decision module implemented by said processing device for deciding an output response for said target text sentence information according to said interactive mode and said information in said interactive information recording table; and an output response module implemented by said processing device and including said output device for outputting response information according to said output response and said information of said interactive information recording table. 5. The system as claimed in claim 1 , wherein when said speech signal is inputted to said interactive mode setting and speech processing module and said target information is provided to said interactive mode setting and speech processing module, said interactive mode is set as a teaching mode. | 0.633995 |
9,866,645 | 50 | 53 | 50. The system of claim 37 , wherein the user device includes an app associated with the third party server. | 50. The system of claim 37 , wherein the user device includes an app associated with the third party server. 53. The system of claim 50 , wherein a user selection of one of the one or more user interface components corresponding to the one or more actionable options causes a corresponding action request to be processed by a second app on the user device. | 0.5 |
8,396,962 | 10 | 15 | 10. A game grammar-based packet capture and analysis method, comprising: capturing packets of game data transmitted and received between a game client and a game server; analyzing the captured packets to generate a game grammar based on analyzed results; and generating packets in compliance with the game grammar to apply the packets to the game server as a load, wherein the generating a game grammar includes: defining packet generation rules by analyzing an entire structure of the packets; grouping a series of packets into a group to define the group as an action of a game; defining protocols of communication between the game client and the server by analyzing the packets; generating the game grammar using the packet generation rules, actions and the protocols. | 10. A game grammar-based packet capture and analysis method, comprising: capturing packets of game data transmitted and received between a game client and a game server; analyzing the captured packets to generate a game grammar based on analyzed results; and generating packets in compliance with the game grammar to apply the packets to the game server as a load, wherein the generating a game grammar includes: defining packet generation rules by analyzing an entire structure of the packets; grouping a series of packets into a group to define the group as an action of a game; defining protocols of communication between the game client and the server by analyzing the packets; generating the game grammar using the packet generation rules, actions and the protocols. 15. The game grammar-based packet capture and analysis method of claim 10 , wherein the generating packets to the game server as a load comprises: generating a plurality of virtual user sessions; generating packets suitable to the game grammar by the virtual user sessions; and transmitting the generated packets to the game server and generating a load on the game server. | 0.53607 |
9,319,556 | 9 | 12 | 9. The computer program product of claim 8 , wherein the process further comprises: (e) obtaining a target grayscale image representing a hardcopy target document, the target grayscale image including one or more halftone text areas and one or more non-halftone text areas, wherein each halftone text area includes a plurality of halftone dots, each halftone dot being formed by a plurality of pixels, each pixel being a smallest unit of the target grayscale image and each pixel having a grayscale pixel value; (f) separating the halftone text areas and the non-halftone text areas of the target grayscale image; (g) separately binarizing the halftone text areas and the non-halftone text areas generated by step (f); (h) down-sampling only the binarized non-halftone text areas generated by step (g) which correspond to the non-halftone text areas of the target grayscale image, without down-sampling the binarized halftone text areas which correspond to the halftone text areas of the same target grayscale image, whereby a binarized target image is generated; and (i) comparing the binarized target image with the binarized original image to determine whether the target document is an authentic copy of the original document. | 9. The computer program product of claim 8 , wherein the process further comprises: (e) obtaining a target grayscale image representing a hardcopy target document, the target grayscale image including one or more halftone text areas and one or more non-halftone text areas, wherein each halftone text area includes a plurality of halftone dots, each halftone dot being formed by a plurality of pixels, each pixel being a smallest unit of the target grayscale image and each pixel having a grayscale pixel value; (f) separating the halftone text areas and the non-halftone text areas of the target grayscale image; (g) separately binarizing the halftone text areas and the non-halftone text areas generated by step (f); (h) down-sampling only the binarized non-halftone text areas generated by step (g) which correspond to the non-halftone text areas of the target grayscale image, without down-sampling the binarized halftone text areas which correspond to the halftone text areas of the same target grayscale image, whereby a binarized target image is generated; and (i) comparing the binarized target image with the binarized original image to determine whether the target document is an authentic copy of the original document. 12. The computer program product of claim 9 , wherein in steps (d) and (h), two or more binarized non-halftone or dark text areas are down-sampled at different down-sampling rates. | 0.923143 |
8,423,353 | 10 | 12 | 10. A computer-implemented dictionary system, comprising: a format component for formatting a dictionary in a universal format consumable by disparate applications; an authoring tool for authoring the formatted dictionary to include at least one of textual data, linguistic data, or dictation data; a dictionary architecture to draw content for the formatted dictionary from other available dictionary sources on networks including: lexicons related to Asian languages, automobiles, printing, financials, construction, abbreviations, Japanese English, translation, old words, sources related to Chinese traditional (CHT) and Chinese simplified (CHS), and compound words, old poems, legal, economy, and medical; a compiler component for compiling the drawn formatted dictionary specific for use in each of the disparate applications in response to a request for the dictionary and conducting checks related to at least one from a set of: geopolitics, accuracy, and performance to ensure the drawn formatted dictionary meets predefined criterion; and a distribution component for synchronizing the compiled formatted dictionary with at least one other compiled formatted dictionary used by at least one application among the disparate applications, wherein the disparate applications comprise speech dictation, spell checking, linguistic analysis, and input method applications and the compiler component compiles the formatted dictionary for use by the linguistic analysis application, the spell checking application, and the speech dictation system. | 10. A computer-implemented dictionary system, comprising: a format component for formatting a dictionary in a universal format consumable by disparate applications; an authoring tool for authoring the formatted dictionary to include at least one of textual data, linguistic data, or dictation data; a dictionary architecture to draw content for the formatted dictionary from other available dictionary sources on networks including: lexicons related to Asian languages, automobiles, printing, financials, construction, abbreviations, Japanese English, translation, old words, sources related to Chinese traditional (CHT) and Chinese simplified (CHS), and compound words, old poems, legal, economy, and medical; a compiler component for compiling the drawn formatted dictionary specific for use in each of the disparate applications in response to a request for the dictionary and conducting checks related to at least one from a set of: geopolitics, accuracy, and performance to ensure the drawn formatted dictionary meets predefined criterion; and a distribution component for synchronizing the compiled formatted dictionary with at least one other compiled formatted dictionary used by at least one application among the disparate applications, wherein the disparate applications comprise speech dictation, spell checking, linguistic analysis, and input method applications and the compiler component compiles the formatted dictionary for use by the linguistic analysis application, the spell checking application, and the speech dictation system. 12. The system of claim 10 , wherein the compiled formatted dictionary is downloaded for use by at least one of the linguistic analysis application, the spell checking application, or the speech dictation system. | 0.5 |
9,696,877 | 1 | 4 | 1. A system comprising: one or more processors; and memory having one or more instructions stored thereon that, responsive to execution by the one or more processors, causes the one or more processors to perform operations comprising: presenting, based on a selected character and in a user interface, multiple character strings representing words or later parts of words or acronyms of which the selected character is a part, at least one of the multiple character strings being a multi-string having two or more character strings of the multiple character strings, the multi-string having or completing a long word and at least one of the two or more character strings having or completing a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at the same time in the user interface; enabling selection, through the user interface and with a gesture, to select the short word or the long word through selection of one or more of the multiple character strings, wherein the selection of the multiple character string for the short word would be selecting a portion of the multiple character string for the long word; receiving selection, through the user interface, of the short word or the long word of the one of the multiple character strings through the gesture; and providing or presenting the selected short word or long word. | 1. A system comprising: one or more processors; and memory having one or more instructions stored thereon that, responsive to execution by the one or more processors, causes the one or more processors to perform operations comprising: presenting, based on a selected character and in a user interface, multiple character strings representing words or later parts of words or acronyms of which the selected character is a part, at least one of the multiple character strings being a multi-string having two or more character strings of the multiple character strings, the multi-string having or completing a long word and at least one of the two or more character strings having or completing a short word, the short word being shorter than the long word and being a constituent part of the long word, the short word and the long word being presented at the same time in the user interface; enabling selection, through the user interface and with a gesture, to select the short word or the long word through selection of one or more of the multiple character strings, wherein the selection of the multiple character string for the short word would be selecting a portion of the multiple character string for the long word; receiving selection, through the user interface, of the short word or the long word of the one of the multiple character strings through the gesture; and providing or presenting the selected short word or long word. 4. The system as recited in claim 1 , wherein enabling selection through the user interface and with the gesture enables selection through a straight line from a starting point at a key of a gesture-sensitive character-entry interface, the starting point at a tap and ending with the straight line. | 0.650235 |
9,521,047 | 11 | 14 | 11. A system comprising: a memory; and a processing device coupled with the memory to: cause display of a user interface having a threshold portion associated with a key performance indicator (KPI), the KPI defined by a search query that derives a value from machine data associated with one or more entities that provide a service, the threshold portion enabling a user to indicate one or more thresholds for the KPI and to indicate a per-entity application of the thresholds, each threshold corresponding to a different one of a plurality of KPI states; receive an indication of the thresholds and of the per-entity application of the thresholds in response to user interaction with the user interface; and store the thresholds in association with a definition of the KPI in accordance with the received indication such that a determining of a KPI state from among a plurality of KPI states is made, for an execution of the search query, on a per-entity basis for at least one of the entities in accordance with the thresholds. | 11. A system comprising: a memory; and a processing device coupled with the memory to: cause display of a user interface having a threshold portion associated with a key performance indicator (KPI), the KPI defined by a search query that derives a value from machine data associated with one or more entities that provide a service, the threshold portion enabling a user to indicate one or more thresholds for the KPI and to indicate a per-entity application of the thresholds, each threshold corresponding to a different one of a plurality of KPI states; receive an indication of the thresholds and of the per-entity application of the thresholds in response to user interaction with the user interface; and store the thresholds in association with a definition of the KPI in accordance with the received indication such that a determining of a KPI state from among a plurality of KPI states is made, for an execution of the search query, on a per-entity basis for at least one of the entities in accordance with the thresholds. 14. The system of claim 11 further comprising to: cause display of a user interface portion showing contributions of one or more of the entities and a visual representation of one or more of the plurality of KPI states, wherein the visual representation is determined at least in part by the thresholds. | 0.744949 |
10,102,196 | 1 | 4 | 1. A method of cutting and pasting text comprising: determining a selected area of text selected by a user; expanding the selected area of text to form an expanded area of text; associating a data label with a portion of the expanded area of text; storing the data label and the associated portion of the expanded area of text; entering input text on an electronic device; detecting a matching data label within the input text, the matching data label matching the data label; displaying the portion of the expanded area of text; receiving an indication that a user wants to replace the matching data label with the portion of the expanded area of text; and replacing the matching data label with the portion of the expanded area of text wherein the step of storing the data label and the associated portion of the expanded area of text comprises storing the data label and the associated portion of the expanded area of text in a clipboard of a computer. | 1. A method of cutting and pasting text comprising: determining a selected area of text selected by a user; expanding the selected area of text to form an expanded area of text; associating a data label with a portion of the expanded area of text; storing the data label and the associated portion of the expanded area of text; entering input text on an electronic device; detecting a matching data label within the input text, the matching data label matching the data label; displaying the portion of the expanded area of text; receiving an indication that a user wants to replace the matching data label with the portion of the expanded area of text; and replacing the matching data label with the portion of the expanded area of text wherein the step of storing the data label and the associated portion of the expanded area of text comprises storing the data label and the associated portion of the expanded area of text in a clipboard of a computer. 4. The method of claim 1 , wherein the step of displaying the portion of the expanded area of text comprises displaying the replacement text in a suggestion window on the electronic device. | 0.566514 |
9,042,191 | 8 | 11 | 8. A computing device comprising: a processor; and a memory macro connected to the processor comprising: a memory array having a plurality of rows, each row of the plurality of rows of the memory array including a plurality of memory words; a plurality of first bits, each first bit of the plurality of first bits associated with a memory word of the plurality of memory words of the each row of the plurality of rows of the memory array, wherein a logic state of the each first bit indicates whether the memory word associated with the each first bit has had a failed bit; a plurality of redundancy rows, each redundancy row of the plurality of redundancy rows including a plurality of redundancy words, each redundancy word of the plurality of redundancy words associated with a corresponding memory word of the plurality of memory words of the each row of the plurality of rows of the memory array; and a corrected data cache having at least one repair word configured to store corrected data and at least one status bit associated with the at least one repair word, the status bit indicating whether the corrected data stored in the repair word is a pending repair, the corrected data cache configured to write the corrected data stored in the repair word to at least one of a counterpart memory word or a counterpart redundancy word. | 8. A computing device comprising: a processor; and a memory macro connected to the processor comprising: a memory array having a plurality of rows, each row of the plurality of rows of the memory array including a plurality of memory words; a plurality of first bits, each first bit of the plurality of first bits associated with a memory word of the plurality of memory words of the each row of the plurality of rows of the memory array, wherein a logic state of the each first bit indicates whether the memory word associated with the each first bit has had a failed bit; a plurality of redundancy rows, each redundancy row of the plurality of redundancy rows including a plurality of redundancy words, each redundancy word of the plurality of redundancy words associated with a corresponding memory word of the plurality of memory words of the each row of the plurality of rows of the memory array; and a corrected data cache having at least one repair word configured to store corrected data and at least one status bit associated with the at least one repair word, the status bit indicating whether the corrected data stored in the repair word is a pending repair, the corrected data cache configured to write the corrected data stored in the repair word to at least one of a counterpart memory word or a counterpart redundancy word. 11. The computing device of claim 8 , wherein the corrected data cache is configured to have a maximum number of pending repairs ranging from 1 to 4 per mega-byte (MB) of memory array. | 0.835125 |
8,057,515 | 16 | 19 | 16. A spine stabilization device comprising: a bone screw having a distal end adapted to engage a bone; a housing at a proximal end of said bone anchor; a longitudinal bore in said housing; said bore being aligned with the bone screw and having an open end and a closed end; a hemispherical pocket at the closed end of said bore; a deflectable post having a proximal end, an elongated body and a distal end; the proximal end of said deflectable post extending from the open end of said longitudinal bore; a spherical retainer at the distal end of the deflectable post; the spherical retainer being received in the hemispherical pocket of the bore; a fastener which secures the spherical retainer in the hemispherical pocket and allows the deflectable post to pivot and rotate relative to the bone anchor; and a spring positioned within the bore between the deflectable post and the housing such that the spring flexibly resists pivoting of the deflectable post towards the housing. | 16. A spine stabilization device comprising: a bone screw having a distal end adapted to engage a bone; a housing at a proximal end of said bone anchor; a longitudinal bore in said housing; said bore being aligned with the bone screw and having an open end and a closed end; a hemispherical pocket at the closed end of said bore; a deflectable post having a proximal end, an elongated body and a distal end; the proximal end of said deflectable post extending from the open end of said longitudinal bore; a spherical retainer at the distal end of the deflectable post; the spherical retainer being received in the hemispherical pocket of the bore; a fastener which secures the spherical retainer in the hemispherical pocket and allows the deflectable post to pivot and rotate relative to the bone anchor; and a spring positioned within the bore between the deflectable post and the housing such that the spring flexibly resists pivoting of the deflectable post towards the housing. 19. The spine stabilization device of claim 16 , wherein said spring is made of PEEK. | 0.921731 |
8,935,265 | 1 | 3 | 1. A method in a computer system for finding and presenting information, the method comprising: acquiring an image of a first copy of a document having original information and one or more first annotations; isolating the one or more first annotations of the document; performing a semantic evaluation of the one or more isolated first annotations; performing a semantic evaluation of the original information; creating an association between a portion of the isolated first annotations and one or more portions of the original information; performing a semantic search for related information from a corpus of documents using at least one of a portion of the isolated first annotations and a portion of the original information, the corpus of documents including a plurality of historical documents including one or more prior annotations previously made thereto, wherein the semantic search includes comparing a grammatical relationship in the portion of the isolated first annotations or the portion of the original information to the one or more prior annotations included in the plurality of historical documents and to data in the plurality of historical documents; identifying related information based at least in part upon the semantic search for related information from the corpus of documents, wherein the related information comprises one or more of the one or more prior annotations previously made to the historical documents and data in one of the historical documents of the plurality of historical documents; storing the related information, at least a portion of the created association, at least a portion of the isolated first annotations or at least a portion of the one or more portions of the original information; acquiring an image of a second copy of the document having original information and one or more second annotations; isolating the one or more second annotations in the second copy of the document; performing a semantic evaluation of the isolated second annotations; creating an association between a portion of the isolated second annotations and the one or more portions of the original information; storing at least a portion of the created association between the portion of the isolated second annotations and one or more portions of the original information; retrieving from the document a geolocation identifier for the document, the geolocation identifier indicating a location of the document at the time the document was previously annotated or marked up; and retrieving a geolocation identifier associated with the isolated first annotations and the isolated second annotations. | 1. A method in a computer system for finding and presenting information, the method comprising: acquiring an image of a first copy of a document having original information and one or more first annotations; isolating the one or more first annotations of the document; performing a semantic evaluation of the one or more isolated first annotations; performing a semantic evaluation of the original information; creating an association between a portion of the isolated first annotations and one or more portions of the original information; performing a semantic search for related information from a corpus of documents using at least one of a portion of the isolated first annotations and a portion of the original information, the corpus of documents including a plurality of historical documents including one or more prior annotations previously made thereto, wherein the semantic search includes comparing a grammatical relationship in the portion of the isolated first annotations or the portion of the original information to the one or more prior annotations included in the plurality of historical documents and to data in the plurality of historical documents; identifying related information based at least in part upon the semantic search for related information from the corpus of documents, wherein the related information comprises one or more of the one or more prior annotations previously made to the historical documents and data in one of the historical documents of the plurality of historical documents; storing the related information, at least a portion of the created association, at least a portion of the isolated first annotations or at least a portion of the one or more portions of the original information; acquiring an image of a second copy of the document having original information and one or more second annotations; isolating the one or more second annotations in the second copy of the document; performing a semantic evaluation of the isolated second annotations; creating an association between a portion of the isolated second annotations and the one or more portions of the original information; storing at least a portion of the created association between the portion of the isolated second annotations and one or more portions of the original information; retrieving from the document a geolocation identifier for the document, the geolocation identifier indicating a location of the document at the time the document was previously annotated or marked up; and retrieving a geolocation identifier associated with the isolated first annotations and the isolated second annotations. 3. The method of claim 1 , wherein the method further comprises: encrypting the isolated first annotations; and storing original information, the encrypted isolated first annotations, and the created association in a new document. | 0.813312 |
9,171,265 | 1 | 3 | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors to perform acts comprising: programming a computer-implemented classifier with multiple qualifications associated with a job description; receiving a first set of training resumes that specify the multiple qualifications; receiving a second set of training resumes that do not specify at least one of the multiple qualifications; training the computer-implemented classifier to categorize resumes as meeting the multiple qualifications or not meeting the multiple qualifications based at least in part on the first set of training resumes and the second set of training resumes, wherein the training the computer-implemented classifier produces a trained computer-implemented classifier; publishing a request to a pool of human workers via a crowdsourcing electronic marketplace to request the human workers to locate resumes that meet the multiple qualifications and to request contact information of candidates associated with the resumes, wherein the candidates are not included in the pool of human workers; receiving, based at least in part on the request, a resume of a candidate from a human worker included in the pool of human workers; and categorizing, using the trained computer-implemented classifier, the resume as either meeting the multiple qualifications or not meeting the multiple qualifications based at least in part on the contact information of the candidate being received from the human worker, and wherein the trained computer-implemented classifier applies predetermined criteria to classify the resume. | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors to perform acts comprising: programming a computer-implemented classifier with multiple qualifications associated with a job description; receiving a first set of training resumes that specify the multiple qualifications; receiving a second set of training resumes that do not specify at least one of the multiple qualifications; training the computer-implemented classifier to categorize resumes as meeting the multiple qualifications or not meeting the multiple qualifications based at least in part on the first set of training resumes and the second set of training resumes, wherein the training the computer-implemented classifier produces a trained computer-implemented classifier; publishing a request to a pool of human workers via a crowdsourcing electronic marketplace to request the human workers to locate resumes that meet the multiple qualifications and to request contact information of candidates associated with the resumes, wherein the candidates are not included in the pool of human workers; receiving, based at least in part on the request, a resume of a candidate from a human worker included in the pool of human workers; and categorizing, using the trained computer-implemented classifier, the resume as either meeting the multiple qualifications or not meeting the multiple qualifications based at least in part on the contact information of the candidate being received from the human worker, and wherein the trained computer-implemented classifier applies predetermined criteria to classify the resume. 3. One or more non-transitory computer-readable media as recited in claim 1 , the acts further comprising causing compensation to be provided to the human worker at least partly in response to categorizing the resume as meeting the multiple qualifications. | 0.591054 |
8,874,589 | 10 | 17 | 10. A system for setting a threshold similarity score value for a first plurality of network device identifiers, comprising: a hardware processing circuit operable to: receive the first plurality of network device identifiers and characteristic data associated with network activity of each of the first plurality of network device identifiers; receive a second plurality of network device identifiers that do not appear in the first plurality of network device identifiers and characteristic data associated with network activity of each of the second plurality of network device identifiers; calculate, for each network device of the second plurality of network device identifiers, a similarity score that represents a degree of similarity between the characteristic data for the network device identifier of the second plurality and the characteristic data for the network device identifiers of the first plurality; designate a performance target relating to a factor indicative of an interest in or usefulness of content placed on a webpage, the performance target used to identify a smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; designate a threshold similarity score value selected as a starting value for determining a lowest similarity score value that is used to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; identify a first number of network device identifiers from the second plurality that have similarity scores above the threshold similarity score value; receive, for each of the identified network device identifiers of the second plurality that have a similarity score above the threshold similarity score value, performance statistics data corresponding to the factor related to the designated performance target; aggregate the performance statistics data of each of the identified network device identifiers to determine an aggregate performance statistics data; determine, from the aggregate performance statistics data, that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; iteratively adjust, responsive to determining that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target, the threshold similarity score value to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; and set the adjusted threshold similarity score value to an experimental threshold similarity score value that represents the lowest similarity score value that identifies the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target. | 10. A system for setting a threshold similarity score value for a first plurality of network device identifiers, comprising: a hardware processing circuit operable to: receive the first plurality of network device identifiers and characteristic data associated with network activity of each of the first plurality of network device identifiers; receive a second plurality of network device identifiers that do not appear in the first plurality of network device identifiers and characteristic data associated with network activity of each of the second plurality of network device identifiers; calculate, for each network device of the second plurality of network device identifiers, a similarity score that represents a degree of similarity between the characteristic data for the network device identifier of the second plurality and the characteristic data for the network device identifiers of the first plurality; designate a performance target relating to a factor indicative of an interest in or usefulness of content placed on a webpage, the performance target used to identify a smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; designate a threshold similarity score value selected as a starting value for determining a lowest similarity score value that is used to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; identify a first number of network device identifiers from the second plurality that have similarity scores above the threshold similarity score value; receive, for each of the identified network device identifiers of the second plurality that have a similarity score above the threshold similarity score value, performance statistics data corresponding to the factor related to the designated performance target; aggregate the performance statistics data of each of the identified network device identifiers to determine an aggregate performance statistics data; determine, from the aggregate performance statistics data, that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; iteratively adjust, responsive to determining that the first number of network device identifiers is not the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target, the threshold similarity score value to identify the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target; and set the adjusted threshold similarity score value to an experimental threshold similarity score value that represents the lowest similarity score value that identifies the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the designated performance target. 17. The system of claim 10 , wherein in the adjusting, the processing circuit is further operable to select a lowest similarity score that identifies the smallest number of network device identifiers of the second plurality of network device users that have performance statistics data relating to the factor, which when aggregated, achieves the performance target with a predetermined level of confidence as the experimental threshold similarity score value. | 0.5 |
9,798,391 | 22 | 26 | 22. A method of operating a device, the method comprising: displaying, by a display device supported by a housing, a play of a game; detecting, by an accelerometer, motion of the housing during the play of the game; analyzing, by a controller, the detected motion of the housing and determining, by the controller, whether the detected motion of the housing corresponds to a designated gesture; and responsive to determining that the detected motion of the housing corresponds to the designated gesture: determining, by the controller, a game input associated with the designated gesture, the determined game input being one of a plurality of different game inputs; determining, by the controller, an aspect of the play of the game to modify based on the determined game input; and causing, by the controller, a modification of the determined aspect of the play of the game. | 22. A method of operating a device, the method comprising: displaying, by a display device supported by a housing, a play of a game; detecting, by an accelerometer, motion of the housing during the play of the game; analyzing, by a controller, the detected motion of the housing and determining, by the controller, whether the detected motion of the housing corresponds to a designated gesture; and responsive to determining that the detected motion of the housing corresponds to the designated gesture: determining, by the controller, a game input associated with the designated gesture, the determined game input being one of a plurality of different game inputs; determining, by the controller, an aspect of the play of the game to modify based on the determined game input; and causing, by the controller, a modification of the determined aspect of the play of the game. 26. The method of claim 22 , wherein the game is a wagering game. | 0.5 |
9,659,069 | 1 | 10 | 1. A method for highlighting items corresponding to search results, comprising: displaying a plurality of items in a user interface display; while maintaining display of the plurality of items: receiving a first user input representing at least a portion of a search term; in response to receiving the first user input, highlighting at least a subset of the plurality of items, the subset of the plurality of items including: a first item that represents at least a one item having metadata that at least partially matches the first user input; a second item that represents at least one item having metadata that at least partially matches the first user input; and a third item that represents at least one item having metadata that represents at least one item having metadata that at least partially matches the first user input; while the first item, the second item and the third item are highlighted, receiving a second user input representing an additional portion of the search term; and in response to receiving the second user input, incrementally changing the displaying and highlighting of the plurality of items in response to the second user input, including: maintaining the highlighting of the first item, wherein the first item represents at least one item having metadata that at least partially matches the first user input and the second user input representing the additional portion of the search term; maintaining the highlighting of the second item, wherein the second item represents at least one item having metadata that at least partially matches the first user input and the second user input representing the additional portion of the search term; and ceasing to highlight the third item, wherein the third item does not represent any items having metadata that at least partially matches the first user input and the second input representing the additional portion of the search term. | 1. A method for highlighting items corresponding to search results, comprising: displaying a plurality of items in a user interface display; while maintaining display of the plurality of items: receiving a first user input representing at least a portion of a search term; in response to receiving the first user input, highlighting at least a subset of the plurality of items, the subset of the plurality of items including: a first item that represents at least a one item having metadata that at least partially matches the first user input; a second item that represents at least one item having metadata that at least partially matches the first user input; and a third item that represents at least one item having metadata that represents at least one item having metadata that at least partially matches the first user input; while the first item, the second item and the third item are highlighted, receiving a second user input representing an additional portion of the search term; and in response to receiving the second user input, incrementally changing the displaying and highlighting of the plurality of items in response to the second user input, including: maintaining the highlighting of the first item, wherein the first item represents at least one item having metadata that at least partially matches the first user input and the second user input representing the additional portion of the search term; maintaining the highlighting of the second item, wherein the second item represents at least one item having metadata that at least partially matches the first user input and the second user input representing the additional portion of the search term; and ceasing to highlight the third item, wherein the third item does not represent any items having metadata that at least partially matches the first user input and the second input representing the additional portion of the search term. 10. The method of claim 1 , wherein highlighting at least the subset of the plurality of items comprises: determining that at least one of the plurality of items matches the first user input and highlighting items representing the matching items using a first type of highlight; and determining that at least one of the plurality of items at least partially matches the first user input and highlighting items representing the partially matching items using a second type of highlight. | 0.5 |
9,430,577 | 11 | 19 | 11. A method comprising: determining at least one spammer targeted keyword relating to a common keyword used in commerce search queries, the determining being based in part on a popularity of the at least one spammer targeted keyword amongst advertisers, wherein the popularity of the at least one spammer targeted keyword amongst the advertisers is based in part on a number of bids provided by the advertisers, and wherein the at least one spammer targeted keyword is associated with a syndication business, the syndication business including at least a publisher, an advertiser, and a syndicator; inputting the at least one spammer targeted keyword to a search engine to generate search results including a plurality of uniform resource locators (URLs); accessing, by one or more processors, one or more URLs of the plurality of URLs; recording the one or more URLs, wherein the recording comprises redirection tracking that intercepts redirection traffic; grouping the one or more recorded URLs using similarity-based grouping; verifying that at least one of the one or more URLs comprises a spam URL; and determining that the spam URL is associated with a spam syndication program, the spam syndication program including at least a spam publisher associated with a doorway page for redirecting a browser to a redirection domain associated with the spam publisher. | 11. A method comprising: determining at least one spammer targeted keyword relating to a common keyword used in commerce search queries, the determining being based in part on a popularity of the at least one spammer targeted keyword amongst advertisers, wherein the popularity of the at least one spammer targeted keyword amongst the advertisers is based in part on a number of bids provided by the advertisers, and wherein the at least one spammer targeted keyword is associated with a syndication business, the syndication business including at least a publisher, an advertiser, and a syndicator; inputting the at least one spammer targeted keyword to a search engine to generate search results including a plurality of uniform resource locators (URLs); accessing, by one or more processors, one or more URLs of the plurality of URLs; recording the one or more URLs, wherein the recording comprises redirection tracking that intercepts redirection traffic; grouping the one or more recorded URLs using similarity-based grouping; verifying that at least one of the one or more URLs comprises a spam URL; and determining that the spam URL is associated with a spam syndication program, the spam syndication program including at least a spam publisher associated with a doorway page for redirecting a browser to a redirection domain associated with the spam publisher. 19. The method of claim 11 , further comprising removing the spam URL from a search result. | 0.941138 |
8,380,512 | 1 | 3 | 1. A computer-implemented method comprising the steps of: receiving, at a search engine, a phonetically-spelled string; wherein the phonetically-spelled string is the result of transforming an audio input into the phonetically-spelled string that has not been converted into any predetermined set of correctly-spelled words; identifying one or more previously-submitted phonetically-spelled query strings from a plurality of other users based on the phonetically-spelled string; and generating a set of query results based, at least in part, on the phonetically-spelled string and on the one or more previously-submitted phonetically-spelled query strings; wherein the steps of the method are performed by one or more computing devices. | 1. A computer-implemented method comprising the steps of: receiving, at a search engine, a phonetically-spelled string; wherein the phonetically-spelled string is the result of transforming an audio input into the phonetically-spelled string that has not been converted into any predetermined set of correctly-spelled words; identifying one or more previously-submitted phonetically-spelled query strings from a plurality of other users based on the phonetically-spelled string; and generating a set of query results based, at least in part, on the phonetically-spelled string and on the one or more previously-submitted phonetically-spelled query strings; wherein the steps of the method are performed by one or more computing devices. 3. The method of claim 1 wherein transforming the audio input into the phonetically-spelled string includes disambiguating the phonetically-spelled string. | 0.602564 |
8,725,563 | 1 | 11 | 1. A computer-implemented search system for locating and rating a plurality of electronic mentions of respective ones of a plurality of endorsers, comprising: a server computer having a tangible computer 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 web crawl engine that finds mentions of ones of the plurality of endorsers in proximity to respective ones of a plurality of keywords; a content reviewer that electronically presents to live reviewer the found mentions, wherein the live reviewer assigns a respective rating to respective ones of the found mentions; a scoring input for receiving a first rating of a particular one of the found mentions from the live reviewer; at least one electronic rating input for receiving second ratings of the same particular one of the found mentions; a correlator that normalizes the ratings of the particular one of the found mentions at least in part by comparing the first rating to the second ratings, and that correlates ones of the plurality of endorsers to a desired purchaser profile based at least in part on the normalized rating; and a management engine that manages the first and second ones of the ratings; wherein said management engine grants privileges to live reviewer. | 1. A computer-implemented search system for locating and rating a plurality of electronic mentions of respective ones of a plurality of endorsers, comprising: a server computer having a tangible computer 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 web crawl engine that finds mentions of ones of the plurality of endorsers in proximity to respective ones of a plurality of keywords; a content reviewer that electronically presents to live reviewer the found mentions, wherein the live reviewer assigns a respective rating to respective ones of the found mentions; a scoring input for receiving a first rating of a particular one of the found mentions from the live reviewer; at least one electronic rating input for receiving second ratings of the same particular one of the found mentions; a correlator that normalizes the ratings of the particular one of the found mentions at least in part by comparing the first rating to the second ratings, and that correlates ones of the plurality of endorsers to a desired purchaser profile based at least in part on the normalized rating; and a management engine that manages the first and second ones of the ratings; wherein said management engine grants privileges to live reviewer. 11. The search system of claim 1 , wherein the normalization comprises a prioritization of the keywords. | 0.724868 |
7,490,092 | 25 | 99 | 25. A method of indexing and searching timed media files, as recited in claim 1 , wherein said calculation includes the processing of language contained within the timed media file. | 25. A method of indexing and searching timed media files, as recited in claim 1 , wherein said calculation includes the processing of language contained within the timed media file. 99. A method of indexing and searching timed media files, as recited in claim 25 , wherein said processing of languages includes the identification of anaphora within the language. | 0.647059 |
8,005,665 | 28 | 32 | 28. A processing system configured to create an abstract for a document, the processing system comprising: a memory device configured to store the document and a threshold score; a processing device; a bus operably coupling the processing device to the memory; the processing device configured to: access the memory to retrieve the document and the threshold score; read a sequence of words in the document; determine a score for respective words in the sequence of words based on at least a length of the respective words; compare the score to the threshold score; and terminate the reading of the sequence of words in response to determining that a phrase delimiter has been reached, wherein the phrase delimiter includes at least one of a word longer than a predetermined length or a sequence of a first predetermined number of words having a score less than the threshold score. | 28. A processing system configured to create an abstract for a document, the processing system comprising: a memory device configured to store the document and a threshold score; a processing device; a bus operably coupling the processing device to the memory; the processing device configured to: access the memory to retrieve the document and the threshold score; read a sequence of words in the document; determine a score for respective words in the sequence of words based on at least a length of the respective words; compare the score to the threshold score; and terminate the reading of the sequence of words in response to determining that a phrase delimiter has been reached, wherein the phrase delimiter includes at least one of a word longer than a predetermined length or a sequence of a first predetermined number of words having a score less than the threshold score. 32. The processing system of claim 28 wherein the processing device is further configured to add the sequence of words as a significant phrase to a significant phrase data structure in response to determining that the number of words in the sequence that have the score greater than the threshold score equals or exceeds a predetermined number. | 0.5 |
8,849,812 | 1 | 18 | 1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein the determining of the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme based on a clustering technique, the clustering technique being a min hash clustering or a n-squared clustering based on bi-grams; and determine the topic based on the clustered at least one theme; automatically generate content for the topic; and select the content that is contextually relevant for display within a corpus of content, wherein the content is optimized for the topic; wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and wherein: in the event that the corpus of content includes the web site, content of the web site is different from other web pages of the website; in the event that the corpus of content includes a user's social networking web page, content of the user's social networking web page is different from another user's social networking web page; in the event that the corpus of content includes content customized for mobile devices, content of a mobile device is different from another mobile device; in the event that the corpus of content includes content customized based on location awareness, content of a location is different from another location; and in the event that the corpus of content includes the electronic mail message, the electronic mail message is different from another electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein the determining of the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme based on a clustering technique, the clustering technique being a min hash clustering or a n-squared clustering based on bi-grams; and determine the topic based on the clustered at least one theme; automatically generate content for the topic; and select the content that is contextually relevant for display within a corpus of content, wherein the content is optimized for the topic; wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and wherein: in the event that the corpus of content includes the web site, content of the web site is different from other web pages of the website; in the event that the corpus of content includes a user's social networking web page, content of the user's social networking web page is different from another user's social networking web page; in the event that the corpus of content includes content customized for mobile devices, content of a mobile device is different from another mobile device; in the event that the corpus of content includes content customized based on location awareness, content of a location is different from another location; and in the event that the corpus of content includes the electronic mail message, the electronic mail message is different from another electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions. 18. The system recited in claim 1 , wherein the processor is further configured to: analyze user behavior to determine topics based on user demand, wherein the analyzed user behavior includes user search history, user purchase history, user device preference, user presentation preferences, content generated using pixel log related data, user reviews, social networking related data, visited information, or any combination thereof. | 0.5 |
9,148,396 | 1 | 2 | 1. A method comprising: determining, by a mobile device while generating a message, that the message is a partial message; determining at least one type of an exceptional condition from a plurality of types of exceptional conditions, the plurality of types of exceptional conditions consisting of: generation of the message ended prematurely; a time out condition occurred on the mobile device; a response from the mobile device to a prompt was not received; inactivity on the mobile device for a predetermined amount of time; and sequentially repeated characters entered on the mobile device; generating, by the mobile device, a tag indicative of the at least one type of the exceptional condition; combining the tag with the current contents of the message; and sending the combined tag and current contents of the message. | 1. A method comprising: determining, by a mobile device while generating a message, that the message is a partial message; determining at least one type of an exceptional condition from a plurality of types of exceptional conditions, the plurality of types of exceptional conditions consisting of: generation of the message ended prematurely; a time out condition occurred on the mobile device; a response from the mobile device to a prompt was not received; inactivity on the mobile device for a predetermined amount of time; and sequentially repeated characters entered on the mobile device; generating, by the mobile device, a tag indicative of the at least one type of the exceptional condition; combining the tag with the current contents of the message; and sending the combined tag and current contents of the message. 2. The method of claim 1 , wherein the exceptional condition comprises inactivity for the predetermined amount of time. | 0.729545 |
8,874,434 | 3 | 4 | 3. The method of claim 2 , wherein the GTN includes a deep convolutional neural network (CNN). | 3. The method of claim 2 , wherein the GTN includes a deep convolutional neural network (CNN). 4. The method of claim 3 , wherein the CNN generates scores for potential chunk tags for words of the sentence. | 0.5 |
8,762,962 | 1 | 6 | 1. A method, executed by electronic computer hardware in combination with software, for automatic translation of a computer program language code, comprising: tokenizing one or more characters of a source programming language code to generate a list of tokens; parsing the list of tokens to generate a grammatical data structure, wherein the grammatical data structure comprises one or more data nodes; processing the one or more data nodes of the grammatical data, structure to generate a document object model, wherein the document object model comprises one or more portable data nodes; and analyzing the one or more portable data nodes in the document object model to generate one or more characters of a target programming language code; normalizing the source programming language, wherein one or more features of the source programming language are managed based on one or more features of the target programming language, comprising: identifying one or more non-equivalent and one or more equivalent features from the one or more features in the source programming language, wherein the one or more non-equivalent features and the one or more equivalent features are identified based on the one or more features of the target programming language; and removing the one or more non-equivalent features of the source programming language; wherein equivalent features are features that are configured to be mapped the source programming language and the target programming language. | 1. A method, executed by electronic computer hardware in combination with software, for automatic translation of a computer program language code, comprising: tokenizing one or more characters of a source programming language code to generate a list of tokens; parsing the list of tokens to generate a grammatical data structure, wherein the grammatical data structure comprises one or more data nodes; processing the one or more data nodes of the grammatical data, structure to generate a document object model, wherein the document object model comprises one or more portable data nodes; and analyzing the one or more portable data nodes in the document object model to generate one or more characters of a target programming language code; normalizing the source programming language, wherein one or more features of the source programming language are managed based on one or more features of the target programming language, comprising: identifying one or more non-equivalent and one or more equivalent features from the one or more features in the source programming language, wherein the one or more non-equivalent features and the one or more equivalent features are identified based on the one or more features of the target programming language; and removing the one or more non-equivalent features of the source programming language; wherein equivalent features are features that are configured to be mapped the source programming language and the target programming language. 6. The method of claim 1 wherein normalizing the source programming language comprises: identifying one or more non-equivalent features from the one or more features in the source programming language, wherein the one or more non-equivalent features are identified based on the one or more features of the target programming language; and replacing the one or more non-equivalent features with the one or more equivalent features of the source programming language. | 0.5 |
9,195,789 | 13 | 18 | 13. The computer readable storage medium of claim 12 , wherein instructions to perform the simulation comprise instructions to: enable the called HDL module; pipeline input arguments from the an interpretive computer programming language module into the called HDL module; receive pipelined output data from the called HDL module; format the receiving pipelined output data; and return the formatted data to the interpretive computer programming language module. | 13. The computer readable storage medium of claim 12 , wherein instructions to perform the simulation comprise instructions to: enable the called HDL module; pipeline input arguments from the an interpretive computer programming language module into the called HDL module; receive pipelined output data from the called HDL module; format the receiving pipelined output data; and return the formatted data to the interpretive computer programming language module. 18. The computer readable medium of claim 13 , wherein instructions to perform the simulation further comprises instructions that cause the processor to disable the called HDL module. | 0.719325 |
7,769,741 | 1 | 5 | 1. An information retrieval system, comprising: a plurality of files stored in memory, each defining a different hierarchical relationships of terms describing an organizational framework for information; a user interface which permits a user to select a level within each of at least two of the different hierarchical relationships; a search query generator responsive to the selection of the level within each of the at least two different hierarchical relationships to construct individual search queries of terms that are based upon the selected levels, and combine the individual search queries of terms to form a search query that is provided to a search engine, wherein the search engine searches a source of information to locate documents which correspond to the search query; and a display which displays information about the located documents to the user. | 1. An information retrieval system, comprising: a plurality of files stored in memory, each defining a different hierarchical relationships of terms describing an organizational framework for information; a user interface which permits a user to select a level within each of at least two of the different hierarchical relationships; a search query generator responsive to the selection of the level within each of the at least two different hierarchical relationships to construct individual search queries of terms that are based upon the selected levels, and combine the individual search queries of terms to form a search query that is provided to a search engine, wherein the search engine searches a source of information to locate documents which correspond to the search query; and a display which displays information about the located documents to the user. 5. The information retrieval system of claim 1 , wherein the individual search queries are combined by boolean “AND” operators to form the search query. | 0.802597 |
8,112,402 | 1 | 14 | 1. A computer implemented method, performed by a computer having a processor, of disambiguating references to named entities, comprising: identifying a surface form of a named entity in a text, the surface form being an ambiguous orthographic representation of a common name for the named entity, the surface form having a corresponding surface form reference in a surface form reference database; enumerating, from the surface form reference, a plurality of different reference named entities based on the identified surface form of the named entity, wherein the surface form is associated in the surface form reference with the plurality of different reference named entities each being formed of a different set of words, and each of the different reference named entities is associated with a named entity reference, the named entity references being stored in a named entity reference database that is separate from the surface form reference database, each of the named entity references associating one of the different reference named entities to multiple entity indicators, the entity indicators including both labels applied to a respective named entity in an information resource, and context indicators applied to the respective named entity in the information resource, in which the labels comprise classifying identifiers applied to the respective named entities in the information resource; evaluating, with the processor, one or more measures of correlation between one or more of the entity indicators in the information resource for each of the identified reference named entities, and the text, the evaluation including comparisons of the text to both the labels and the context indicators; identifying, with the processor, one of the reference named entities for which the associated entity indicators have a relatively high correlation to the text; and providing a disambiguation output that indicates the identified reference named entity to be associated with the surface form of the named entity in the text. | 1. A computer implemented method, performed by a computer having a processor, of disambiguating references to named entities, comprising: identifying a surface form of a named entity in a text, the surface form being an ambiguous orthographic representation of a common name for the named entity, the surface form having a corresponding surface form reference in a surface form reference database; enumerating, from the surface form reference, a plurality of different reference named entities based on the identified surface form of the named entity, wherein the surface form is associated in the surface form reference with the plurality of different reference named entities each being formed of a different set of words, and each of the different reference named entities is associated with a named entity reference, the named entity references being stored in a named entity reference database that is separate from the surface form reference database, each of the named entity references associating one of the different reference named entities to multiple entity indicators, the entity indicators including both labels applied to a respective named entity in an information resource, and context indicators applied to the respective named entity in the information resource, in which the labels comprise classifying identifiers applied to the respective named entities in the information resource; evaluating, with the processor, one or more measures of correlation between one or more of the entity indicators in the information resource for each of the identified reference named entities, and the text, the evaluation including comparisons of the text to both the labels and the context indicators; identifying, with the processor, one of the reference named entities for which the associated entity indicators have a relatively high correlation to the text; and providing a disambiguation output that indicates the identified reference named entity to be associated with the surface form of the named entity in the text. 14. The method of claim 1 , wherein evaluating the one or more measures of similarity comprises using at least one element from a group consisting of: a vector space model; Jensen-Shannon divergence; Kullback-Liebler divergence; and mutual information. | 0.873494 |
8,364,416 | 20 | 24 | 20. An apparatus for processing information on nucleotide sequence, comprising: a transmitter/receiver for receiving positional information representing a position in a nucleotide sequence in accordance with a request for an object and/or service; and a CPU that: obtains from a memory device, from among a plurality of pieces of polymorphism pattern, a polymorphism pattern associated with the positional information received by the transmitter/receiver, wherein the obtained polymorphism pattern is information on nucleotide sequence which differs among individual organisms and shows a pattern of nucleotide or nucleotide sequence in a polymorphism; causes the transmitter/receiver to transmit the obtained polymorphism pattern; causes the transmitter/receiver to receive semantic information corresponding to the transmitted polymorphism pattern and/or information associated with the semantic information in association with positional information, wherein the semantic information refers to information on phenotypes caused by one or more differences in polymorphism patterns; makes a determination as to whether the received positional information matches positional information related to the transmitted polymorphism pattern; and causes the apparatus to disclose information concerning a party that received the transmitted polymorphism pattern, and wherein the third party is an organization for ensuring compliance with rules concerning transmission/reception of positional information or polymorphism pattern through a communication network, and wherein the causing of the apparatus to disclose is performed in response to the determination as to whether the received positional information matches positional information related to the transmitted polymorphism pattern. | 20. An apparatus for processing information on nucleotide sequence, comprising: a transmitter/receiver for receiving positional information representing a position in a nucleotide sequence in accordance with a request for an object and/or service; and a CPU that: obtains from a memory device, from among a plurality of pieces of polymorphism pattern, a polymorphism pattern associated with the positional information received by the transmitter/receiver, wherein the obtained polymorphism pattern is information on nucleotide sequence which differs among individual organisms and shows a pattern of nucleotide or nucleotide sequence in a polymorphism; causes the transmitter/receiver to transmit the obtained polymorphism pattern; causes the transmitter/receiver to receive semantic information corresponding to the transmitted polymorphism pattern and/or information associated with the semantic information in association with positional information, wherein the semantic information refers to information on phenotypes caused by one or more differences in polymorphism patterns; makes a determination as to whether the received positional information matches positional information related to the transmitted polymorphism pattern; and causes the apparatus to disclose information concerning a party that received the transmitted polymorphism pattern, and wherein the third party is an organization for ensuring compliance with rules concerning transmission/reception of positional information or polymorphism pattern through a communication network, and wherein the causing of the apparatus to disclose is performed in response to the determination as to whether the received positional information matches positional information related to the transmitted polymorphism pattern. 24. The apparatus of claim 20 , wherein the information on phenotypes caused by one or more differences in polymorphism patterns includes information on diatheses and properties. | 0.770026 |
5,412,714 | 17 | 24 | 17. A method of call-processing in a telecommunications system having a plurality of endpoints and having a network numbering plan for addressing the endpoints, wherein callers supply sequences of symbols to specify treatment that is to be given to calls, each sequence comprising at least one symbol string that is defined for the network numbering plan, comprising the steps of: defining for the system a network numbering plan comprising a plurality of types of symbol strings, and addresses of at least some of the endpoints of the system within the network numbering plan each comprising a plurality of symbol strings of a plurality of the types; in response to receipt of a symbol sequence including a plurality of symbol strings of a plurality of the types, the included symbol swings appearing in the symbol sequence in any order, using the definition of the network numbering plan to identify the included strings irrespective of their order in the received/symbol sequence; and in response to the identification, effecting establishment of a connection to an endpoint of the system having an address within the network numbering plan formed by the identified included symbol strings, irrespective of the order of the identified included symbol strings in the received symbol sequence. | 17. A method of call-processing in a telecommunications system having a plurality of endpoints and having a network numbering plan for addressing the endpoints, wherein callers supply sequences of symbols to specify treatment that is to be given to calls, each sequence comprising at least one symbol string that is defined for the network numbering plan, comprising the steps of: defining for the system a network numbering plan comprising a plurality of types of symbol strings, and addresses of at least some of the endpoints of the system within the network numbering plan each comprising a plurality of symbol strings of a plurality of the types; in response to receipt of a symbol sequence including a plurality of symbol strings of a plurality of the types, the included symbol swings appearing in the symbol sequence in any order, using the definition of the network numbering plan to identify the included strings irrespective of their order in the received/symbol sequence; and in response to the identification, effecting establishment of a connection to an endpoint of the system having an address within the network numbering plan formed by the identified included symbol strings, irrespective of the order of the identified included symbol strings in the received symbol sequence. 24. The method of claim 17 in a telecommunications system further having a plurality of feature modules and having the network numbering plan further for accessing the feature modules, wherein: the step of defining comprises the step of defining the network numbering plan to include feature access codes of the feature modules of the system, the feature access codes each comprising a plurality of symbol strings of a plurality of the types; and the step of effecting establishment of a connection includes the step of invoking execution of a feature module of the system having a feature access code within the network numbering plan formed by the identified included symbol strings, irrespective of the order of the identified included symbol strings in the received symbol sequence. | 0.5 |
8,762,837 | 7 | 10 | 7. A method for the efficient transmission of a plurality of images within a document, said method comprising: selecting, by a user of a display device, said document stored within a central database; and transmitting at said user's request, by said central database to said display device, said plurality of images corresponding to said document, a first of said images being a full image of the first page of said document, in a first file, and the remainder of said plurality of images being pages of said document subsequent said first page, in a second single file of thumbnail images, whereby when said user of said display device selects a given thumbnail image from said second single file of thumbnail images, the central database forwards the full image corresponding to said given thumbnail image. | 7. A method for the efficient transmission of a plurality of images within a document, said method comprising: selecting, by a user of a display device, said document stored within a central database; and transmitting at said user's request, by said central database to said display device, said plurality of images corresponding to said document, a first of said images being a full image of the first page of said document, in a first file, and the remainder of said plurality of images being pages of said document subsequent said first page, in a second single file of thumbnail images, whereby when said user of said display device selects a given thumbnail image from said second single file of thumbnail images, the central database forwards the full image corresponding to said given thumbnail image. 10. The method according to claim 7 , wherein the document comprises image identification numbers for indexing each of said plurality of images in said document. | 0.503086 |
9,330,411 | 10 | 17 | 10. A tangible computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for generating a product recommendation, the method comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation. | 10. A tangible computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for generating a product recommendation, the method comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation. 17. The computer-readable storage medium of claim 10 , wherein the computer-readable storage medium stores additional instructions that, when executed, cause the computer to perform additional steps comprising: receiving data indicating a new primitive and input/output arguments of the new primitive; and adding the new primitive to a set of primitives. | 0.840684 |
7,672,935 | 13 | 17 | 13. An article of manufacture, comprising a machine-accessible storage medium including data that, when accessed by a machine, cause the machine to perform a method comprising: receiving a request, at a lightweight directory access protocol (LDAP) directory server, to retrieve data from a LDAP repository communicably coupled to the LDAP server, wherein the request is in the form of a filter that is a logical expression including search terms related to the data; evaluating, by the LDAP server, the filter in terms of statistical data being tracked by the LDAP server; adding, by the LDAP server, statistical data related to the filter to a set of filter tracking data maintained by the LDAP server for one or more filters, wherein the filter tracking data includes at least one of an access frequency of each filter, an evaluation time of each filter, a time that a request for each filter is received, system load when the request for each filter is received, and a number of entries processed for each filter; generating, by the LDAP server, one or more LDAP indices for each of the one or more filters; selecting, by the LDAP server, a defined number of the one or more LDAP indices with a highest dynamic ranking to maintain in the LDAP repository, wherein the dynamic ranking is determined from the statistical data determined for the filter associated with each potential LDAP index; and deleting, by the LDAP server, one or more remaining LDAP indices that are not selected for maintenance; wherein the filter tracking data is updated each time the LDAP server receives another request, and the selecting and deleting the one or more remaining LDAP indices is repeated using updated dynamic rankings based on the updated filter tracking data on an on-going basis. | 13. An article of manufacture, comprising a machine-accessible storage medium including data that, when accessed by a machine, cause the machine to perform a method comprising: receiving a request, at a lightweight directory access protocol (LDAP) directory server, to retrieve data from a LDAP repository communicably coupled to the LDAP server, wherein the request is in the form of a filter that is a logical expression including search terms related to the data; evaluating, by the LDAP server, the filter in terms of statistical data being tracked by the LDAP server; adding, by the LDAP server, statistical data related to the filter to a set of filter tracking data maintained by the LDAP server for one or more filters, wherein the filter tracking data includes at least one of an access frequency of each filter, an evaluation time of each filter, a time that a request for each filter is received, system load when the request for each filter is received, and a number of entries processed for each filter; generating, by the LDAP server, one or more LDAP indices for each of the one or more filters; selecting, by the LDAP server, a defined number of the one or more LDAP indices with a highest dynamic ranking to maintain in the LDAP repository, wherein the dynamic ranking is determined from the statistical data determined for the filter associated with each potential LDAP index; and deleting, by the LDAP server, one or more remaining LDAP indices that are not selected for maintenance; wherein the filter tracking data is updated each time the LDAP server receives another request, and the selecting and deleting the one or more remaining LDAP indices is repeated using updated dynamic rankings based on the updated filter tracking data on an on-going basis. 17. The article of manufacture of claim 13 , wherein deleting the potential LDAP indices further includes deleting one of the one or more remaining LDAP indices from the LDAP repository if its dynamic ranking falls below a threshold level. | 0.677898 |
8,818,931 | 12 | 13 | 12. The system of claim 8 comprising the one or more processor-based devices configured to execute: the expertise access function that accesses the plurality of expertise levels that are associated with each of the plurality of computer-implemented objects, wherein the plurality of expertise levels are associated with a plurality of users of the computer-implemented system who are each represented by one of the plurality of the computer-implemented objects. | 12. The system of claim 8 comprising the one or more processor-based devices configured to execute: the expertise access function that accesses the plurality of expertise levels that are associated with each of the plurality of computer-implemented objects, wherein the plurality of expertise levels are associated with a plurality of users of the computer-implemented system who are each represented by one of the plurality of the computer-implemented objects. 13. The system of claim 12 comprising the one or more processor-based devices configured to execute: the expertise access function that accesses the plurality of expertise levels that are associated with each of the plurality of computer-implemented objects, wherein the plurality of expertise levels are associated with the plurality of users of the computer-implemented system who are each represented by one of the plurality of the computer-implemented objects, wherein the plurality of expertise values are inferred from usage behaviors. | 0.5 |
8,732,479 | 19 | 21 | 19. An apparatus for performing a method for backing up a user file, the apparatus comprising a client system comprising: at least one communications interface; at least one memory to store processor-executable instructions; and at least one processor communicatively coupled to the at least one communications interface and the at least one memory, wherein upon execution of the processor-executable instructions, the at least one processor: A) generates a plurality of file segments each corresponding to a portion of the user file; B) encrypts each of the plurality of file segments; C) determines destination mapping information for each of the plurality of encrypted file segments, the destination mapping information comprising a location address in storage of a second system, different from the client system, where the corresponding encrypted file segment will be stored; D) updates a backup status file associated with the user file with the plurality of destination mapping information for each of the corresponding plurality of encrypted file segments; E) transmits the plurality of encrypted file segments to the second system for backup, while keeping metadata of the user file at the client device in the backup status file; and F) subsequently retrieving the plurality of encrypted file segments from the second system for restoration, the encrypted file segments requested via the mapping information and storage identifying information in the backup status file, the metadata used to structurally reconstruct the client file system. | 19. An apparatus for performing a method for backing up a user file, the apparatus comprising a client system comprising: at least one communications interface; at least one memory to store processor-executable instructions; and at least one processor communicatively coupled to the at least one communications interface and the at least one memory, wherein upon execution of the processor-executable instructions, the at least one processor: A) generates a plurality of file segments each corresponding to a portion of the user file; B) encrypts each of the plurality of file segments; C) determines destination mapping information for each of the plurality of encrypted file segments, the destination mapping information comprising a location address in storage of a second system, different from the client system, where the corresponding encrypted file segment will be stored; D) updates a backup status file associated with the user file with the plurality of destination mapping information for each of the corresponding plurality of encrypted file segments; E) transmits the plurality of encrypted file segments to the second system for backup, while keeping metadata of the user file at the client device in the backup status file; and F) subsequently retrieving the plurality of encrypted file segments from the second system for restoration, the encrypted file segments requested via the mapping information and storage identifying information in the backup status file, the metadata used to structurally reconstruct the client file system. 21. The apparatus of claim 19 , wherein the at least one processor determines storage identifying information for each file segment, the storage identifying information including computer information, session information, file information, and file version information. | 0.631507 |
9,262,506 | 12 | 13 | 12. The system of claim 11 , wherein the processor is further configured with logic to: create at least one new category in the master taxonomy for the outlier documents in response to a sufficient quantity of outlier documents having insufficient classification score values. | 12. The system of claim 11 , wherein the processor is further configured with logic to: create at least one new category in the master taxonomy for the outlier documents in response to a sufficient quantity of outlier documents having insufficient classification score values. 13. The system of claim 12 , wherein the processor is further configured with logic to: re-classify documents of the master taxonomy within the at least one new category. | 0.627193 |
8,572,218 | 1 | 11 | 1. A computer-implemented method for transport data compression between a server and a client, comprising the steps of: generating, by the server, a first compression dictionary for compressing a first chunk of data; compressing, by the server, the first chunk of data using the first compression dictionary to form a first compressed chunk of data; transmitting the first compressed chunk of data and the first compression dictionary from the server to the client, wherein the client decompresses the first compressed chunk of data using the first dictionary; generating, by the server, a second compression dictionary for compressing a second chunk of data; compressing, by the server, the second chunk of data using the second compression dictionary to form a second compressed chunk of data; generating, by the server, a dictionary patch based on the first compression dictionary and the second compression dictionary; and transmitting the second compressed chunk of data and the dictionary patch to the client, wherein the client updates the first compression dictionary using the dictionary patch to form the second compression dictionary and decompresses the second compressed chunk of data using the second compression dictionary. | 1. A computer-implemented method for transport data compression between a server and a client, comprising the steps of: generating, by the server, a first compression dictionary for compressing a first chunk of data; compressing, by the server, the first chunk of data using the first compression dictionary to form a first compressed chunk of data; transmitting the first compressed chunk of data and the first compression dictionary from the server to the client, wherein the client decompresses the first compressed chunk of data using the first dictionary; generating, by the server, a second compression dictionary for compressing a second chunk of data; compressing, by the server, the second chunk of data using the second compression dictionary to form a second compressed chunk of data; generating, by the server, a dictionary patch based on the first compression dictionary and the second compression dictionary; and transmitting the second compressed chunk of data and the dictionary patch to the client, wherein the client updates the first compression dictionary using the dictionary patch to form the second compression dictionary and decompresses the second compressed chunk of data using the second compression dictionary. 11. The method of claim 1 , wherein the server returns a new compression dictionary with a subsequent compressed chunk of data if the new compression dictionary is significantly different from a previously used compression dictionary. | 0.746204 |
9,557,909 | 1 | 11 | 1. A method implemented by a computing device, the method comprising: abstracting, by an operating system of the computing device, a plurality of items to be displayed as specified by an application through an application programming interface (API) made available to the application by the operating system, the abstraction not integrated within the application, the abstracting comprising: receiving the plurality of items to be displayed from the application through the API; creating, by the operating system without further input from the application, groups to be used to represent content in a zoomed view of a semantic swap; determining a first letter of each of the items to be represented in the zoomed view; organizing each of the items into the created groups based on the determined first letter of each of the items; sending, by the operating system through the API, a view of the items to be displayed within an interface corresponding to the application; and responsive to receipt of an input to initiate a semantic swap, sending, by the operating system and through the API, a view of the created groups to the application to replace the view of the items. | 1. A method implemented by a computing device, the method comprising: abstracting, by an operating system of the computing device, a plurality of items to be displayed as specified by an application through an application programming interface (API) made available to the application by the operating system, the abstraction not integrated within the application, the abstracting comprising: receiving the plurality of items to be displayed from the application through the API; creating, by the operating system without further input from the application, groups to be used to represent content in a zoomed view of a semantic swap; determining a first letter of each of the items to be represented in the zoomed view; organizing each of the items into the created groups based on the determined first letter of each of the items; sending, by the operating system through the API, a view of the items to be displayed within an interface corresponding to the application; and responsive to receipt of an input to initiate a semantic swap, sending, by the operating system and through the API, a view of the created groups to the application to replace the view of the items. 11. A method as described in claim 1 , wherein the input to initiate the semantic swap is a zoom operation. | 0.812937 |
8,935,323 | 2 | 3 | 2. The method of claim 1 , further comprising the step of importing at least one blog feed reader into said blogging application. | 2. The method of claim 1 , further comprising the step of importing at least one blog feed reader into said blogging application. 3. The method of claim 2 , wherein said importing step comprises the steps of importing content both from a feed which is internal to the collaborative environment, and also from a feed which is external to the collaborative environment. | 0.5 |
8,065,286 | 1 | 16 | 1. A method of performing a search, comprising: receiving a query from a query source; selectively including a keyword among a plurality of keywords based on a predetermined frequency of the keyword in a corpus; registering, by a searcher, for the keyword; selecting the searcher based on a ranking of the searcher among searchers registered for the keyword when determining that the keyword is a highest ranking keyword of the query; selecting the searcher based on a generalist ranking of the searcher when determining that the query does not indicate a keyword registered by at least one searcher; conducting the search by the searcher using a resource ranked highest by the searcher for conducting searches; presenting search results to the searcher from a plurality of resources selected based on the searcher, the searcher reviewing the search results from the resource ranked highest and the plurality of resources and selecting a result considered optimal for the query; and supplying the result to the query source subsequent to said reviewing by the searcher. | 1. A method of performing a search, comprising: receiving a query from a query source; selectively including a keyword among a plurality of keywords based on a predetermined frequency of the keyword in a corpus; registering, by a searcher, for the keyword; selecting the searcher based on a ranking of the searcher among searchers registered for the keyword when determining that the keyword is a highest ranking keyword of the query; selecting the searcher based on a generalist ranking of the searcher when determining that the query does not indicate a keyword registered by at least one searcher; conducting the search by the searcher using a resource ranked highest by the searcher for conducting searches; presenting search results to the searcher from a plurality of resources selected based on the searcher, the searcher reviewing the search results from the resource ranked highest and the plurality of resources and selecting a result considered optimal for the query; and supplying the result to the query source subsequent to said reviewing by the searcher. 16. The method as recited in claim 1 , wherein the query source comprises one of a user computer system, a digital query source, a user application, a telephone, an automated query source, a translation system and a speech query source. | 0.506276 |
9,524,319 | 16 | 18 | 16. An apparatus comprising: a memory device; and one or more processors operably coupled to the memory device, the one or more processors configured to: receive a product query from a customer; identify a first group of mappings generated for dominant product queries from a query log containing product queries made by previous customers; identify a second group of mappings from the query log that includes mappings between a first set of product queries from the query log and categories shown in the query log for the first set of product queries, and mappings between a second set of product queries from the query log and clicked products from the query log for the second set of product queries; apply the second group of mappings for the product query from the customer when category mappings for the product query from the customer are in the second group of mappings; and apply the first group of mappings for the product query from the customer when the category mappings for the product query from the customer are in the first group of mappings but not in the second group of mappings. | 16. An apparatus comprising: a memory device; and one or more processors operably coupled to the memory device, the one or more processors configured to: receive a product query from a customer; identify a first group of mappings generated for dominant product queries from a query log containing product queries made by previous customers; identify a second group of mappings from the query log that includes mappings between a first set of product queries from the query log and categories shown in the query log for the first set of product queries, and mappings between a second set of product queries from the query log and clicked products from the query log for the second set of product queries; apply the second group of mappings for the product query from the customer when category mappings for the product query from the customer are in the second group of mappings; and apply the first group of mappings for the product query from the customer when the category mappings for the product query from the customer are in the first group of mappings but not in the second group of mappings. 18. The apparatus of claim 16 wherein the one or more processors are further configured to present search results for the product query from the customer based on: the first group of mappings when the category mappings for the product query from the customer are in the first group of mappings but not in the second group of mappings; and the second group of mappings when the category mappings for the product query from the customer are in the second group of mappings. | 0.5 |
8,417,522 | 1 | 9 | 1. A speech recognition method, comprising: receiving a speech input signal in a first noise environment which comprises a sequence of observations; determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, comprising, providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognise speech in a second noise environment, said model having a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation, and adapting the model trained in the second environment to that of the first environment; the speech recognition method further comprising, determining the likelihood of a sequence of observations occurring in a given language using a language model; and combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein adapting the model trained in the second environment to that of the first environment comprises using second order or higher order Taylor expansion coefficients derived for a group of probability distributions and wherein the same expansion coefficient is used for the whole group; the speech recognition method further comprising estimating noise parameters used to determine the Taylor expansion coefficients, wherein the noise parameters comprise a component for additive noise and a component for convolutional noise, and an observation in the first noise environment is related to an observation in the second noise environment by:
y=x+h+g ( x, n, h )= x+h+C ln(1+ e C −1 (n−x−h) ) (1) where y is the observation in the first noise environment, x is the observation in the second noise environment, n is the additive noise, h is the convolutional noise in the first environment with respect to the second environment and C is the discrete cosine transformation matrix. | 1. A speech recognition method, comprising: receiving a speech input signal in a first noise environment which comprises a sequence of observations; determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model, comprising, providing an acoustic model for performing speech recognition on a input signal which comprises a sequence of observations, wherein said model has been trained to recognise speech in a second noise environment, said model having a plurality of model parameters relating to the probability distribution of a word or part thereof being related to an observation, and adapting the model trained in the second environment to that of the first environment; the speech recognition method further comprising, determining the likelihood of a sequence of observations occurring in a given language using a language model; and combining the likelihoods determined by the acoustic model and the language model and outputting a sequence of words identified from said speech input signal, wherein adapting the model trained in the second environment to that of the first environment comprises using second order or higher order Taylor expansion coefficients derived for a group of probability distributions and wherein the same expansion coefficient is used for the whole group; the speech recognition method further comprising estimating noise parameters used to determine the Taylor expansion coefficients, wherein the noise parameters comprise a component for additive noise and a component for convolutional noise, and an observation in the first noise environment is related to an observation in the second noise environment by:
y=x+h+g ( x, n, h )= x+h+C ln(1+ e C −1 (n−x−h) ) (1) where y is the observation in the first noise environment, x is the observation in the second noise environment, n is the additive noise, h is the convolutional noise in the first environment with respect to the second environment and C is the discrete cosine transformation matrix. 9. A speech recognition method according to claim 1 , wherein the first environment is a noisy environment and the second environment is a noise free environment. | 0.706522 |
9,355,091 | 10 | 11 | 10. A method for classifying text according to language using one or more computer processors, comprising: i) accessing, by a training module, a training data set from a training data set database having a plurality of text strings, each text string being associated with a tag that indicates a language in which the text string is written, the training module comprising a training computer processor coupled to a memory having instructions that cause the training computer processor to access the training data; ii) statistically associating, using the training module, one or more permutations of consecutive characters extracted from each of the text strings of the training data set with corresponding tagged language and storing statistical association data, associating the permutations with their corresponding language, in a statistical association database; iii) receiving an input data set having one or more input text strings by a classification module that comprises a classifying computer processor coupled to a memory including instructions that cause the classifying computer processor to extract one or more permutations of consecutive characters from each of the input text strings and classify each input text string according to a language in which the input text string is written by comparing the consecutive character permutations extracted from the input text string with the statistical association data, tag each classified input text string with a tag that indicates its language, and output the tagged input text string; and iv) receiving, by the training module the tagged input text strings, statistically associating the tagged input text strings with the tagged language, and updating the statistical association data in the statistical association database. | 10. A method for classifying text according to language using one or more computer processors, comprising: i) accessing, by a training module, a training data set from a training data set database having a plurality of text strings, each text string being associated with a tag that indicates a language in which the text string is written, the training module comprising a training computer processor coupled to a memory having instructions that cause the training computer processor to access the training data; ii) statistically associating, using the training module, one or more permutations of consecutive characters extracted from each of the text strings of the training data set with corresponding tagged language and storing statistical association data, associating the permutations with their corresponding language, in a statistical association database; iii) receiving an input data set having one or more input text strings by a classification module that comprises a classifying computer processor coupled to a memory including instructions that cause the classifying computer processor to extract one or more permutations of consecutive characters from each of the input text strings and classify each input text string according to a language in which the input text string is written by comparing the consecutive character permutations extracted from the input text string with the statistical association data, tag each classified input text string with a tag that indicates its language, and output the tagged input text string; and iv) receiving, by the training module the tagged input text strings, statistically associating the tagged input text strings with the tagged language, and updating the statistical association data in the statistical association database. 11. The method of claim 10 , wherein steps (iii) and (iv) are repeated one or more times. | 0.536458 |
8,707,199 | 2 | 3 | 2. The method of claim 1 wherein the storing comprises: generating a data object of a particular type in accordance with an associated application; populating the data object in accordance with the text in text entry field; storing the data object in the memory. | 2. The method of claim 1 wherein the storing comprises: generating a data object of a particular type in accordance with an associated application; populating the data object in accordance with the text in text entry field; storing the data object in the memory. 3. The method of claim 2 comprising selecting the associated application in accordance with received selection input selecting the associated application from a number of applications. | 0.5 |
8,599,836 | 20 | 24 | 20. A method of creating and launching on demand a pre-recorded voice interaction with a contact utilizing an outbound web-based contact center comprising a speech application having interactive voice response comprising the following, steps: a. Accessing a website comprising a URL address of a service provider of the contact center accessible by a user via a user computer equipped with a web browser, b. Creating a user account by providing user information comprising a user password, c. Creating a script comprising one or more events from the group comprising message events and questions events, d. Providing contact information, the contact information comprising a contact's direct phone number, e. Optionally inputting custom answers per a call script where the call script comprises at least one question anticipating a custom answer from a contact, the custom answers to be recognized by a speech application of a hosted contact center, f. Producing voice recordings of each event of the call script; g. Creating a call sequence based on the call script, the call sequence comprising a prompt for each event of the call script, the prompts from the group comprising voice recordings and text-to-speech prompts, the call sequence created via an event adding wizard and logic adding wizard, the user pointing and clicking to successively add a prompt for each event and a logic for controlling the sequencing of the prompts dependent upon the contact's response to a question event when the script comprises a question event, the call sequence optionally comprising a Transfer to Live Attendant Event whereby the call is automatically transferred to a user-specified phone number when the contact elicits a specified response to a question event in the call sequence, h. Generating a broadcast, the broadcast comprising a saved call sequence and contacts or contact groups, i. Launching the broadcast, j. Reviewing one or more reports comprising, information from contact responses to question events in the call sequence of the broadcast. | 20. A method of creating and launching on demand a pre-recorded voice interaction with a contact utilizing an outbound web-based contact center comprising a speech application having interactive voice response comprising the following, steps: a. Accessing a website comprising a URL address of a service provider of the contact center accessible by a user via a user computer equipped with a web browser, b. Creating a user account by providing user information comprising a user password, c. Creating a script comprising one or more events from the group comprising message events and questions events, d. Providing contact information, the contact information comprising a contact's direct phone number, e. Optionally inputting custom answers per a call script where the call script comprises at least one question anticipating a custom answer from a contact, the custom answers to be recognized by a speech application of a hosted contact center, f. Producing voice recordings of each event of the call script; g. Creating a call sequence based on the call script, the call sequence comprising a prompt for each event of the call script, the prompts from the group comprising voice recordings and text-to-speech prompts, the call sequence created via an event adding wizard and logic adding wizard, the user pointing and clicking to successively add a prompt for each event and a logic for controlling the sequencing of the prompts dependent upon the contact's response to a question event when the script comprises a question event, the call sequence optionally comprising a Transfer to Live Attendant Event whereby the call is automatically transferred to a user-specified phone number when the contact elicits a specified response to a question event in the call sequence, h. Generating a broadcast, the broadcast comprising a saved call sequence and contacts or contact groups, i. Launching the broadcast, j. Reviewing one or more reports comprising, information from contact responses to question events in the call sequence of the broadcast. 24. The method per claim 20 wherein the script comprises a questionnaire for a clinical research trial. | 0.869289 |
7,536,287 | 9 | 10 | 9. A computer-implemented method for simulating a scenario involving at least one participant, the computer-implemented method comprising: assigning a role to the participant; activating, using the computer, a first event upon the first event accumulating a quantity of points over a first threshold; allowing triggering, using the computer, upon activation of the first event, of effect logic representing a causal relationship between the first event and a second event; providing, using the computer, by the effect logic, at least one point to the second event upon the effect logic being triggered; activating, using the computer, the second event upon the second event accumulating a quantity of points over a third threshold; activating, using the computer, decision logic upon the second event being activated; presenting, using the computer, upon decision logic being triggered, a decision comprising a plurality of choices to the role; and selecting, by the participant, from the plurality of choices. | 9. A computer-implemented method for simulating a scenario involving at least one participant, the computer-implemented method comprising: assigning a role to the participant; activating, using the computer, a first event upon the first event accumulating a quantity of points over a first threshold; allowing triggering, using the computer, upon activation of the first event, of effect logic representing a causal relationship between the first event and a second event; providing, using the computer, by the effect logic, at least one point to the second event upon the effect logic being triggered; activating, using the computer, the second event upon the second event accumulating a quantity of points over a third threshold; activating, using the computer, decision logic upon the second event being activated; presenting, using the computer, upon decision logic being triggered, a decision comprising a plurality of choices to the role; and selecting, by the participant, from the plurality of choices. 10. The method of claim 9 further comprising presenting a message to the role upon the second event being activated. | 0.854271 |
9,245,254 | 1 | 32 | 1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information. | 1. A method for ability enhancement, the method comprising: by a computer system, receiving data representing speech signals from a voice conference amongst multiple speakers, wherein the multiple speakers are remotely located from one another, wherein each of the multiple speakers uses a separate conferencing device to participate in the voice conference; determining speaker-related information associated with the multiple speakers, based on the data representing speech signals from the voice conference; recording conference history information based on the speaker-related information, by recording indications of topics discussed during the voice conference by: performing speech recognition to convert the data representing speech signals into text; analyzing the text to identify frequently used terms or phrases; and determining the topics discussed during the voice conference based on the frequently used terms or phrases; audibly notifying a user to view the conference history information on a display device, wherein the user is notified in a manner that is not audible to at least some of the multiple speakers; and presenting, on the display device, at least some of the conference history information to the user; translating an utterance of one of the multiple speakers in a first language into a message in a second language, based on the speaker-related information, wherein the speaker related information is determined by automatically determining the second and the first language comprising steps of: concurrently or simultaneously applying multiple speech recognizers and using GPS information indicating the speakers' locations; and recording the message in the second language as part of the conference history information. 32. The method of claim 1 , further comprising: performing the receiving data representing speech signals from a voice conference amongst multiple speakers, the determining speaker-related information associated with the multiple speakers, the recording conference history information based on the speaker-related information, and/or the presenting at least some of the conference history information on a mobile device that is operated by the user. | 0.658815 |
8,001,066 | 8 | 10 | 8. A multimedia recognition system comprising: a plurality of indexers configured to: receive multimedia data, the multimedia data including at least two of audio data, video data, and text data, and analyze the multimedia data based on training data to generate a plurality of documents; and a memory system configured to: store the documents from the indexers, obtain new documents, the new documents including one or more of correction and/or enhancement of the documents, annotation of the documents with bookmarks, highlights, and notes, attachment of rich documents and insertion of rich documents, store the new documents, and provide the new documents to one or more of the indexers for retraining based on the new documents. | 8. A multimedia recognition system comprising: a plurality of indexers configured to: receive multimedia data, the multimedia data including at least two of audio data, video data, and text data, and analyze the multimedia data based on training data to generate a plurality of documents; and a memory system configured to: store the documents from the indexers, obtain new documents, the new documents including one or more of correction and/or enhancement of the documents, annotation of the documents with bookmarks, highlights, and notes, attachment of rich documents and insertion of rich documents, store the new documents, and provide the new documents to one or more of the indexers for retraining based on the new documents. 10. The system of claim 8 wherein when obtaining the new documents, the memory system is configured to: employ an agent to actively seek out and retrieve new documents. | 0.799043 |
9,607,612 | 1 | 3 | 1. A computing device for speech recognition, the computing device comprising: a processor; an audio sensor; an audio input module to: capture audio input using the audio sensor; and distort, by the processor, a waveform of the audio input to produce a plurality of distorted audio variations, wherein to distort the waveform comprises to adjust a temporal duration of the waveform; and a speech recognition module to: perform speech recognition on the audio input and each of the distorted audio variations to produce a plurality of speech recognition results; and select, by the processor, a result from the speech recognition results based on contextual information. | 1. A computing device for speech recognition, the computing device comprising: a processor; an audio sensor; an audio input module to: capture audio input using the audio sensor; and distort, by the processor, a waveform of the audio input to produce a plurality of distorted audio variations, wherein to distort the waveform comprises to adjust a temporal duration of the waveform; and a speech recognition module to: perform speech recognition on the audio input and each of the distorted audio variations to produce a plurality of speech recognition results; and select, by the processor, a result from the speech recognition results based on contextual information. 3. The computing device of claim 1 , wherein to adjust the temporal duration of the waveform comprises to insert a pause at a phonetic split point of the audio input identified by performing speech recognition on the audio input. | 0.747797 |
9,390,707 | 15 | 17 | 15. The computer program product of claim 13 , the computer readable storage medium further comprising instructions to assign a greater weight to at least one word exceeding a predefined number of characters as compared to at least one other word below the predetermined number of characters. | 15. The computer program product of claim 13 , the computer readable storage medium further comprising instructions to assign a greater weight to at least one word exceeding a predefined number of characters as compared to at least one other word below the predetermined number of characters. 17. The computer program product of claim 15 , the computer readable storage medium further comprising instructions to assign a confidence level to each axiom of the set of axioms. | 0.5 |
7,503,075 | 1 | 5 | 1. A method of accessing data stored in one or more database servers to control access to documents requested by a user, comprising; receiving, at a server, a request from the user for access to one or more documents; retrieving from the one or more database servers, in a single operation, an access level associated with each of the one or more documents; identifying one or more predefined access levels granted to the user; generating a list of the one or more documents and the respective associated access level information; filtering the list to eliminate one or more of the requested documents having access levels not available to the user; generating one or more database server queries based on the filtered list of requested documents; retrieving document data associated with each respective document based on the filtered list of requested documents from the one or more database servers, wherein the document data is organized in a document tree list architecture; and reporting the retrieved document data to the user. | 1. A method of accessing data stored in one or more database servers to control access to documents requested by a user, comprising; receiving, at a server, a request from the user for access to one or more documents; retrieving from the one or more database servers, in a single operation, an access level associated with each of the one or more documents; identifying one or more predefined access levels granted to the user; generating a list of the one or more documents and the respective associated access level information; filtering the list to eliminate one or more of the requested documents having access levels not available to the user; generating one or more database server queries based on the filtered list of requested documents; retrieving document data associated with each respective document based on the filtered list of requested documents from the one or more database servers, wherein the document data is organized in a document tree list architecture; and reporting the retrieved document data to the user. 5. A method according to claim 1 , wherein the document data is accessed in the document tree list architecture by referring to one or more nodes connected to a node containing the desired document data. | 0.624074 |
7,920,132 | 1 | 8 | 1. A text entry system comprising: a user input device comprising a virtual keyboard including an auto-correcting region comprising a plurality of the characters of a character set, where the characters occupy different character locations with different known coordinates in the auto-correcting region, wherein an interaction location associated with a user interaction is determined when a user interacts with the user input device within the auto-correcting region, the interaction location including coordinates of a contact point on the auto-correcting region, and the determined interaction location is added to a current input sequence of interaction locations; a machine readable vocabulary containing a plurality of objects, wherein one or more of the objects comprise a string of one or a plurality of characters forming all or part of a word or phrase; an output device having an output text region and an object choice list region; and a processor coupled to the user input device, the vocabulary, and the output device, said processor programmed to perform operations comprising: responsive to each new user interaction, conducting object-level analysis of various candidate objects from the vocabulary, comprising operations of: associating each user interaction with a different character of the given object, and scoring the given object according to factors including distances from the interaction locations in the current input sequence and the known coordinates of the associated characters of the given object; additionally responsive to each new user interaction, causing the object choice list region to display multiple objects according to scores produced by the object-level analysis; operating the output text region to display text entered by the user and to serve as a buffer for text input and editing; responsive to the user selecting one of the objects displayed in the object choice list, entering the selected object in the output text region. | 1. A text entry system comprising: a user input device comprising a virtual keyboard including an auto-correcting region comprising a plurality of the characters of a character set, where the characters occupy different character locations with different known coordinates in the auto-correcting region, wherein an interaction location associated with a user interaction is determined when a user interacts with the user input device within the auto-correcting region, the interaction location including coordinates of a contact point on the auto-correcting region, and the determined interaction location is added to a current input sequence of interaction locations; a machine readable vocabulary containing a plurality of objects, wherein one or more of the objects comprise a string of one or a plurality of characters forming all or part of a word or phrase; an output device having an output text region and an object choice list region; and a processor coupled to the user input device, the vocabulary, and the output device, said processor programmed to perform operations comprising: responsive to each new user interaction, conducting object-level analysis of various candidate objects from the vocabulary, comprising operations of: associating each user interaction with a different character of the given object, and scoring the given object according to factors including distances from the interaction locations in the current input sequence and the known coordinates of the associated characters of the given object; additionally responsive to each new user interaction, causing the object choice list region to display multiple objects according to scores produced by the object-level analysis; operating the output text region to display text entered by the user and to serve as a buffer for text input and editing; responsive to the user selecting one of the objects displayed in the object choice list, entering the selected object in the output text region. 8. The system of claim 1 , wherein the auto-correcting keyboard region comprises one or a plurality of known locations associated with one or a plurality of punctuation characters and/or diacritic marks, and wherein the vocabulary comprises one or a plurality of objects which include one or a plurality of the punctuation characters and/or diacritic marks associated with locations in said region. | 0.766979 |
8,570,376 | 1 | 2 | 1. A method for storing selected video segments for a person or a plurality of persons that visited an area covered by a plurality of means for capturing images using at least a computer that executes computer vision algorithms on a plurality of video streams, comprising the following steps of: a) finding information for the trip of the person or the plurality of persons based on track sequences calculated from tracking the person or the plurality of persons in video streams, b) determining a first set of video segments that contain the trip information of the person or the plurality of persons and a second set of video segments that do not contain the trip information of the person or the plurality of persons in each of the video streams, c) removing the second set of video segments from each of the video streams, d) selecting video segments from the first set of video segments based on predefined selection criteria, applying multi-layered spatiotemporal constraints to select the video segments, for the statistical behavior analysis e) applying domain-specific sampling criteria to the selection of video segments, and f) compacting each of the video streams using the first set of video segments, after removing the second set of video segments from each of the video streams, and whereby the application of the multi-layered spatiotemporal constraints further reduces the size of the selected video segments. | 1. A method for storing selected video segments for a person or a plurality of persons that visited an area covered by a plurality of means for capturing images using at least a computer that executes computer vision algorithms on a plurality of video streams, comprising the following steps of: a) finding information for the trip of the person or the plurality of persons based on track sequences calculated from tracking the person or the plurality of persons in video streams, b) determining a first set of video segments that contain the trip information of the person or the plurality of persons and a second set of video segments that do not contain the trip information of the person or the plurality of persons in each of the video streams, c) removing the second set of video segments from each of the video streams, d) selecting video segments from the first set of video segments based on predefined selection criteria, applying multi-layered spatiotemporal constraints to select the video segments, for the statistical behavior analysis e) applying domain-specific sampling criteria to the selection of video segments, and f) compacting each of the video streams using the first set of video segments, after removing the second set of video segments from each of the video streams, and whereby the application of the multi-layered spatiotemporal constraints further reduces the size of the selected video segments. 2. The method according to claim 1 , wherein the method further comprises a step of selecting video segments from the compact video streams based on selection criteria, further reducing the size of video data. | 0.772826 |
8,046,297 | 1 | 10 | 1. A computer comprising: one or more central processing units, one or more memories and one or more network interfaces to one or more networks, the computer further comprising a program code which, when executed on said one or more central processing units, is configured to perform a search and a business transaction based on user input, a user interface comprising at least one display being configured to display in conjunction with execution of the program code, an input environment configured for user inputting of search criteria, said input environment being configured for user inputting of an order, said search criteria defining a search for at least one desired entity; the program code establishing a search engine configured for performing a search on at least two different web-based data sources to generate a search result; the search engine being configured to search based on the user input of a configuration comprising a combination of at least two different entities, a first entity and a second entity being includable in the at least two different entities that the search engine is configured to search, the search engine establishing a search for the configuration, wherein the different entities are purchasable from different web-based data sources, said search engine being configured for performing a search for said configuration on at least two different web-based data sources for said combination of entities, said search engine presenting at least one found configuration of the different entities by means of said user interface, said search engine being configured to provide at least one order input defining a configuration determined on the basis of said at least one found configuration presented by means of said user interface, said search engine being configured to take mutual dependencies between said entities into consideration. | 1. A computer comprising: one or more central processing units, one or more memories and one or more network interfaces to one or more networks, the computer further comprising a program code which, when executed on said one or more central processing units, is configured to perform a search and a business transaction based on user input, a user interface comprising at least one display being configured to display in conjunction with execution of the program code, an input environment configured for user inputting of search criteria, said input environment being configured for user inputting of an order, said search criteria defining a search for at least one desired entity; the program code establishing a search engine configured for performing a search on at least two different web-based data sources to generate a search result; the search engine being configured to search based on the user input of a configuration comprising a combination of at least two different entities, a first entity and a second entity being includable in the at least two different entities that the search engine is configured to search, the search engine establishing a search for the configuration, wherein the different entities are purchasable from different web-based data sources, said search engine being configured for performing a search for said configuration on at least two different web-based data sources for said combination of entities, said search engine presenting at least one found configuration of the different entities by means of said user interface, said search engine being configured to provide at least one order input defining a configuration determined on the basis of said at least one found configuration presented by means of said user interface, said search engine being configured to take mutual dependencies between said entities into consideration. 10. The computer according to claim 1 , wherein said configuration comprising a combination of at least two different entities is a desired configuration comprising a combination of at least two different entities. | 0.655949 |
8,086,028 | 1 | 6 | 1. A method of generating a set of tuple-term pairs from a corpus of text, comprising: compiling via a processor concordance lines associated with terms in the corpus; identifying a set of verb-argument tuples and associated terms from the concordance lines; selecting from the set each verb-argument tuple and associated term having a computed numerical quantification of strength of association greater than a threshold, wherein the selected verb-argument tuples and associated terms represent most likely actions associated with the terms; and storing in a database each tuple-term pair in the set of tuple-term pairs that matches a verb in a sentence input to a text-to-scene conversion system that constructs an arbitrary three-dimensional scene from input text without using previously stored images. | 1. A method of generating a set of tuple-term pairs from a corpus of text, comprising: compiling via a processor concordance lines associated with terms in the corpus; identifying a set of verb-argument tuples and associated terms from the concordance lines; selecting from the set each verb-argument tuple and associated term having a computed numerical quantification of strength of association greater than a threshold, wherein the selected verb-argument tuples and associated terms represent most likely actions associated with the terms; and storing in a database each tuple-term pair in the set of tuple-term pairs that matches a verb in a sentence input to a text-to-scene conversion system that constructs an arbitrary three-dimensional scene from input text without using previously stored images. 6. The method of claim 1 , further comprising deleting duplicate concordance lines. | 0.940714 |
9,582,540 | 8 | 13 | 8. A computer program product for executing a database query, comprising a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor, causes the processor to: generate one or more predicates based on implicit filtering present within the database query, wherein each of the one or more predicates specifies a condition with respect to a respective predicate value; select an access path for the database query based on the one or more predicates and integrating the one or more predicates within the selected access plan; execute a set number of operations of the database query in accordance with the selected access plan; repeatedly update the respective predicate value of at least one predicate of the one or more predicates based on data accessed, wherein the updating increases filtering of data, and execute the database query until the filtering of the data cannot be improved by an updated predicate value. | 8. A computer program product for executing a database query, comprising a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor, causes the processor to: generate one or more predicates based on implicit filtering present within the database query, wherein each of the one or more predicates specifies a condition with respect to a respective predicate value; select an access path for the database query based on the one or more predicates and integrating the one or more predicates within the selected access plan; execute a set number of operations of the database query in accordance with the selected access plan; repeatedly update the respective predicate value of at least one predicate of the one or more predicates based on data accessed, wherein the updating increases filtering of data, and execute the database query until the filtering of the data cannot be improved by an updated predicate value. 13. The computer program product of claim 8 , wherein the computer readable code is configured to cause the processor to select the access path based upon a cost function that determines an optimal time during query execution to apply the generated one or more predicates. | 0.5 |
8,463,782 | 13 | 17 | 13. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: traversing a corpus of documents to identify a plurality of lists within the documents, wherein each list comprises structured data delimited from other data in a document, and wherein each list specifies an enumeration of elements; selecting a pair of terms based on determining that both terms of the pair are contained in a first quantity of lists that are included in the documents in the corpus, wherein the first quantity is more than a first predetermined quantity, and wherein each list in the first quantity of lists includes more than a second predetermined quantity of terms; determining a first value that represents a quantity of documents in the corpus that include a list that contains both terms of the pair; determining a second value that represents a quantity of the documents in the set corpus that include a list that contains at least one of the terms of the pair; when both terms of the pair are contained in the first quantity of lists that are included in the documents in the corpus, determining a correlation value from the first value and the second value; determining that the correlation value satisfies a threshold; and designating the pair of terms as potentially non-synonymous terms by adding the pair of terms to a blacklist, based on determining that the correlation value satisfies the threshold, wherein the blacklist is accessed for synonym determination. | 13. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: traversing a corpus of documents to identify a plurality of lists within the documents, wherein each list comprises structured data delimited from other data in a document, and wherein each list specifies an enumeration of elements; selecting a pair of terms based on determining that both terms of the pair are contained in a first quantity of lists that are included in the documents in the corpus, wherein the first quantity is more than a first predetermined quantity, and wherein each list in the first quantity of lists includes more than a second predetermined quantity of terms; determining a first value that represents a quantity of documents in the corpus that include a list that contains both terms of the pair; determining a second value that represents a quantity of the documents in the set corpus that include a list that contains at least one of the terms of the pair; when both terms of the pair are contained in the first quantity of lists that are included in the documents in the corpus, determining a correlation value from the first value and the second value; determining that the correlation value satisfies a threshold; and designating the pair of terms as potentially non-synonymous terms by adding the pair of terms to a blacklist, based on determining that the correlation value satisfies the threshold, wherein the blacklist is accessed for synonym determination. 17. The system of claim 13 , wherein: one or more lists in the plurality of lists comprise a HyperText Markup Language (HTML) ordered list, an HTML unordered list, or an HTML definition list. | 0.818441 |
4,156,107 | 13 | 16 | 13. A circuit for rendering an intelligible electrical speech signal unintelligible but recognizable as representing speech, characterized by means for distorting the speech signal in a first prescribed manner to produce a first distorted signal, means for distorting the first distorted signal in a second prescribed manner to produce a second distorted signal, and means for distorting the second distorted signal in a third prescribed manner, wherein said three distorting means make up the group consisting of means for sampling an analog signal at a prescribed rate to produce individual samples of the analog signal each having a prescribed duration and having a duty cycle of substantially less than 100%, means for rectifying a second analog signal, and means for attenuating individual audio frequency components of a third analog signal by prescribed amounts according to the frequency of the components. | 13. A circuit for rendering an intelligible electrical speech signal unintelligible but recognizable as representing speech, characterized by means for distorting the speech signal in a first prescribed manner to produce a first distorted signal, means for distorting the first distorted signal in a second prescribed manner to produce a second distorted signal, and means for distorting the second distorted signal in a third prescribed manner, wherein said three distorting means make up the group consisting of means for sampling an analog signal at a prescribed rate to produce individual samples of the analog signal each having a prescribed duration and having a duty cycle of substantially less than 100%, means for rectifying a second analog signal, and means for attenuating individual audio frequency components of a third analog signal by prescribed amounts according to the frequency of the components. 16. The invention of claim 13 wherein the rectifying means is characterized by a fullwave rectifier. | 0.83165 |
8,024,370 | 13 | 14 | 13. The computer system of claim 9 , wherein each attribute file of the plurality of attribute files complies with a naming convention. | 13. The computer system of claim 9 , wherein each attribute file of the plurality of attribute files complies with a naming convention. 14. The computer system of claim 13 , wherein the software instructions further cause the processor to: hide a specific cell in the pseudo-world when a name of an attribute file corresponding to the specific cell is changed, wherein the name of the attribute file corresponding to the specific cell is changed to not comply with the naming convention. | 0.5 |
9,477,929 | 1 | 7 | 1. A computer method, comprising carrying out operations on a computer, the operations comprising: maintaining machine readable embodiments on a medium of a bipartite graph and a tripartite graph, the tripartite graph comprising a first plurality of nodes corresponding to labeled and unlabeled examples from source and target domains; a second plurality of nodes corresponding to features; and a first plurality of edges connecting the nodes corresponding to the features to the nodes corresponding to the examples according to whether the features appear in the examples or not; the bipartite graph comprising the first plurality of nodes corresponding to the examples; and a second plurality of edges connecting the examples, the edges being associated with indications that indicate whether connected examples are in a same domain or not; deriving labels for at least one target domain based on the tripartite and bipartite graphs; and presenting an embodiment of the labels as a result, wherein said deriving comprises: formulating an objective function based on said bipartite and tripartite graphs, said objective function encompassing smoothness and consistency constraints and providing label information in the target domain at least responsive to label information in the source domain; applying the objective function to the all examples, whether labeled or unlabeled, and all features in order to obtain at least one result relative to the unlabeled examples; minimizing the objective function to yield a label function; and providing output labels responsive to the label function. | 1. A computer method, comprising carrying out operations on a computer, the operations comprising: maintaining machine readable embodiments on a medium of a bipartite graph and a tripartite graph, the tripartite graph comprising a first plurality of nodes corresponding to labeled and unlabeled examples from source and target domains; a second plurality of nodes corresponding to features; and a first plurality of edges connecting the nodes corresponding to the features to the nodes corresponding to the examples according to whether the features appear in the examples or not; the bipartite graph comprising the first plurality of nodes corresponding to the examples; and a second plurality of edges connecting the examples, the edges being associated with indications that indicate whether connected examples are in a same domain or not; deriving labels for at least one target domain based on the tripartite and bipartite graphs; and presenting an embodiment of the labels as a result, wherein said deriving comprises: formulating an objective function based on said bipartite and tripartite graphs, said objective function encompassing smoothness and consistency constraints and providing label information in the target domain at least responsive to label information in the source domain; applying the objective function to the all examples, whether labeled or unlabeled, and all features in order to obtain at least one result relative to the unlabeled examples; minimizing the objective function to yield a label function; and providing output labels responsive to the label function. 7. The method of claim 1 , wherein the examples are machine readable embodiments of documents; and the features are machine embodiments of words within the documents. | 0.877219 |
7,755,646 | 14 | 16 | 14. An image management system comprising: processing circuitry configured to access image data of a plurality of images, said processing circuitry being configured to generate graphical representations of objects contained in the plurality of images based upon centroids of the objects, to determine the centroids and the sizes of the graphical representations, to determine morphologies of the graphical representations, and to assign human readable lexical representations of the locations of the centroids, the sizes, the colors and the morphologies of the graphical representations; and storage circuitry configured to store the plurality of images and to store the plurality of human readable lexical representations of the plurality of images. | 14. An image management system comprising: processing circuitry configured to access image data of a plurality of images, said processing circuitry being configured to generate graphical representations of objects contained in the plurality of images based upon centroids of the objects, to determine the centroids and the sizes of the graphical representations, to determine morphologies of the graphical representations, and to assign human readable lexical representations of the locations of the centroids, the sizes, the colors and the morphologies of the graphical representations; and storage circuitry configured to store the plurality of images and to store the plurality of human readable lexical representations of the plurality of images. 16. The image management system according to claim 14 , wherein the processing circuitry is further configured to chart the locations of the centroids on a morpho-lexical histogram, to divide the morpho-lexical histogram into a plurality of virtual regions, and to assign human readable representations of the morphologies of the graphical representations based upon the relationships between the virtual regions and the graphical representations contained within the virtual regions. | 0.5 |
9,286,351 | 1 | 2 | 1. A computer-implemented method utilizing at least one computer system for determining a potential point of novelty of a patent, the method comprising: electronically retrieving at least one independent claim of the patent as issued; electronically retrieving at least one independent claim of the corresponding patent application as published; automatically comparing the at least one issued claim to the at least one published claim to identify at least one unique keyword present in the at least one issued claim but not present in the at least one published claim; cross-referencing the at least one unique keyword to a passage in the specification of the issued patent; flagging the at least one unique keyword to a user; identifying at least one prior art document and at least one other prior art document; calculating an overlap score for the at least one prior art document based on at least one occurrence of the at least one unique keyword in the at least one prior art document; calculating an overlap score for at least one other prior art document based on at least one occurrence of the at least one unique keyword in the at least one other prior art document; calculating a ranking for the at least one prior art document by comparing the overlap score of the at least one prior art document to the overlap score of at least one other prior art document; displaying, in a user interface, a graphical representation of the overlap score of the at least one prior art document and a graphical representation of the overlap score of the at least one other prior art document based on the ranking; identifying a priority date of the at least one prior art document and a priority date of the at least one other prior art document; identifying an owner of the at least one prior art document and an owner of the at least one other prior art document; and displaying on a time line, in the user interface, the owner and the priority date of the at least one prior art document and the owner and the priority date of the at least one other prior art document. | 1. A computer-implemented method utilizing at least one computer system for determining a potential point of novelty of a patent, the method comprising: electronically retrieving at least one independent claim of the patent as issued; electronically retrieving at least one independent claim of the corresponding patent application as published; automatically comparing the at least one issued claim to the at least one published claim to identify at least one unique keyword present in the at least one issued claim but not present in the at least one published claim; cross-referencing the at least one unique keyword to a passage in the specification of the issued patent; flagging the at least one unique keyword to a user; identifying at least one prior art document and at least one other prior art document; calculating an overlap score for the at least one prior art document based on at least one occurrence of the at least one unique keyword in the at least one prior art document; calculating an overlap score for at least one other prior art document based on at least one occurrence of the at least one unique keyword in the at least one other prior art document; calculating a ranking for the at least one prior art document by comparing the overlap score of the at least one prior art document to the overlap score of at least one other prior art document; displaying, in a user interface, a graphical representation of the overlap score of the at least one prior art document and a graphical representation of the overlap score of the at least one other prior art document based on the ranking; identifying a priority date of the at least one prior art document and a priority date of the at least one other prior art document; identifying an owner of the at least one prior art document and an owner of the at least one other prior art document; and displaying on a time line, in the user interface, the owner and the priority date of the at least one prior art document and the owner and the priority date of the at least one other prior art document. 2. The method of claim 1 , further comprising identifying at least one common keyword present in both of the at least one published and issued claims; and calculating the overlap score for the at least one prior art document based on at least one occurrence of the at least one common keyword in the at least one prior art document. | 0.5 |
7,870,124 | 13 | 14 | 13. A machine-readable storage medium storing instructions which, when executed by one or more processors, causes: receiving a first query that conforms to a first XML query language; determining that an operator included in the first query requires one or more node references, to one or more nodes, as operands of the operator instead of a value of any of the one or more nodes; wherein the operator included in the first query is one of a node comparison operator or an operator that requires context node traversal; and in response to determining that the operator included in the first query requires one or more node references as operands of the operator, generating, based on the first query, a second query (a) that conforms to a second XML query language that is different than the first XML query language and (b) that includes a particular operator not included in the first query; wherein execution of the particular operator included in the second query causes a reference, to a node in an XML document, to be returned instead of a value of the node. | 13. A machine-readable storage medium storing instructions which, when executed by one or more processors, causes: receiving a first query that conforms to a first XML query language; determining that an operator included in the first query requires one or more node references, to one or more nodes, as operands of the operator instead of a value of any of the one or more nodes; wherein the operator included in the first query is one of a node comparison operator or an operator that requires context node traversal; and in response to determining that the operator included in the first query requires one or more node references as operands of the operator, generating, based on the first query, a second query (a) that conforms to a second XML query language that is different than the first XML query language and (b) that includes a particular operator not included in the first query; wherein execution of the particular operator included in the second query causes a reference, to a node in an XML document, to be returned instead of a value of the node. 14. The machine-readable storage medium of claim 13 , wherein the first XML query language is an XQuery query language. | 0.88469 |
8,869,048 | 8 | 9 | 8. The system of claim 6 , said user interface container defining a property sheet user interface. | 8. The system of claim 6 , said user interface container defining a property sheet user interface. 9. The system of claim 8 , said property sheet user interface comprising tabs associated with each of said plurality of user interface sections. | 0.5 |
8,838,564 | 8 | 11 | 8. A method implemented on a computing machine, comprising: receiving a plurality of candidate pieces of content; receiving a plurality of aggregated user activity streams, each aggregated user activity stream containing a record of at least one social activity performed by a user on a web page; extracting a plurality of topics from the plurality of aggregated user activity streams; calculating a velocity of each extracted topic based on a difference between a metric of the topic over a first period of time and a metric of the topic over a second period of time, wherein the second period of time came before the first period of time; calculating a trending score for each of the plurality of candidate pieces of content based on a measure of the velocities of one or more extracted topics contained in the candidate piece of content; ranking the plurality of candidate pieces of content based on the trending score; and publishing one or more of the plurality of candidate pieces of content based on the ranking. | 8. A method implemented on a computing machine, comprising: receiving a plurality of candidate pieces of content; receiving a plurality of aggregated user activity streams, each aggregated user activity stream containing a record of at least one social activity performed by a user on a web page; extracting a plurality of topics from the plurality of aggregated user activity streams; calculating a velocity of each extracted topic based on a difference between a metric of the topic over a first period of time and a metric of the topic over a second period of time, wherein the second period of time came before the first period of time; calculating a trending score for each of the plurality of candidate pieces of content based on a measure of the velocities of one or more extracted topics contained in the candidate piece of content; ranking the plurality of candidate pieces of content based on the trending score; and publishing one or more of the plurality of candidate pieces of content based on the ranking. 11. The method of claim 8 , wherein the velocity of each topic is calculated based on an average of historical metrics taken over a plurality of related periods of time including particular hours of the day over one or more days, particular days of the week over one or more weeks, particular weeks of the year over one or more years, particular months of the year over one or more years, particular seasons of the year over one or more years, or particular holidays over one or more years. | 0.5 |
8,924,374 | 32 | 33 | 32. The computer readable storage medium of claim 31 , wherein the instructions for generating the customized data model further include instructions for inserting metadata into the data model that separates the plain-text document into multiple candidate chunks. | 32. The computer readable storage medium of claim 31 , wherein the instructions for generating the customized data model further include instructions for inserting metadata into the data model that separates the plain-text document into multiple candidate chunks. 33. The computer readable storage medium of claim 32 , wherein the metadata in the data model is one or more XML tags and the text following at least one of the XML tags is identified as a candidate chunk. | 0.5 |
9,911,052 | 17 | 22 | 17. A system for providing handwriting recognition for a superimposed stroke input to a computing device, the computing device comprising a processor and at least one computer readable program for recognizing the input under control of the processor, said at least one program configured to: create, with a segmentation expert, a segmentation graph based on a plurality of input strokes, at least two of the strokes being at least partially superimposed on one another, wherein the segmentation graph consists of nodes and paths corresponding to character hypotheses formed by segmenting the input strokes to take into account the at least partially superimposed strokes; assign, with a recognition expert, a recognition score to each node of the segmentation graph based on language recognition information; generate, with a language expert, linguistic meaning of the input strokes by optimizing the recognition scores of the node paths of the segmentation graph based on a language model; and provide an output based on the collaborative analysis of the segmentation graph, the recognition score, and the language model by the segmentation, recognition and language experts. | 17. A system for providing handwriting recognition for a superimposed stroke input to a computing device, the computing device comprising a processor and at least one computer readable program for recognizing the input under control of the processor, said at least one program configured to: create, with a segmentation expert, a segmentation graph based on a plurality of input strokes, at least two of the strokes being at least partially superimposed on one another, wherein the segmentation graph consists of nodes and paths corresponding to character hypotheses formed by segmenting the input strokes to take into account the at least partially superimposed strokes; assign, with a recognition expert, a recognition score to each node of the segmentation graph based on language recognition information; generate, with a language expert, linguistic meaning of the input strokes by optimizing the recognition scores of the node paths of the segmentation graph based on a language model; and provide an output based on the collaborative analysis of the segmentation graph, the recognition score, and the language model by the segmentation, recognition and language experts. 22. A system according to claim 17 , wherein the language model includes linguistic information specific to one or more languages. | 0.640884 |
8,947,745 | 12 | 17 | 12. An imaging scanner comprising: an image capturing component configured to sequentially capturing two or more images of a single document; and a processor configured to: identify a first location in a first captured image where information to be decoded is located, analyze each character in the first location, and produce a first string including both a corresponding character and a first confidence value for each character in the first location; determine that a first measurement of the confidence values in the first string is beyond a range associated with a first confidence threshold; identify a second location in a second captured image where information to be decoded is located, analyze each character in the second location, produce a second string including both a corresponding character and a second confidence value for each character in the second location; compare the first confidence value for each character in an identified location in the first string with the second confidence value for the character in the same identified location in the second string; select a character from one of the first string or the second string with a higher confidence value; and produce and output a combined string including the selected characters. | 12. An imaging scanner comprising: an image capturing component configured to sequentially capturing two or more images of a single document; and a processor configured to: identify a first location in a first captured image where information to be decoded is located, analyze each character in the first location, and produce a first string including both a corresponding character and a first confidence value for each character in the first location; determine that a first measurement of the confidence values in the first string is beyond a range associated with a first confidence threshold; identify a second location in a second captured image where information to be decoded is located, analyze each character in the second location, produce a second string including both a corresponding character and a second confidence value for each character in the second location; compare the first confidence value for each character in an identified location in the first string with the second confidence value for the character in the same identified location in the second string; select a character from one of the first string or the second string with a higher confidence value; and produce and output a combined string including the selected characters. 17. The imaging scanner of claim 12 , wherein the processor is configured to determine that the second measurement of the confidence values in the first string is within the range associated with the second confidence threshold and end a decoding process. | 0.862311 |
7,778,632 | 1 | 6 | 1. A multi-modal multi-lingual mobile device that facilitates automating an action, comprising: a detection component that employs a plurality of integrated sensors to obtain at least one criterion from an auxiliary act through passive observation, the auxiliary act is a conversation of a user with an entity that is not the mobile device, wherein the at least one criterion is an environmental context that relates to a weather condition, and a schedule manipulation action is performed at least partially in view of at least one of expected travel complications or venue incompatibility with the weather condition; and an analyzer component that evaluates the at least one criterion to infer a user intent and automatically implements the action based at least in part upon operation of a rules-based logic component, wherein the rules based logic component automatically allows execution of the action based at least in part upon satisfaction of a defined rule, and based at least in part upon operation of an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon operation of an artificial intelligence component that comprises a classifier function that maps an input attribute vector x=(x 1 , x 2 , x 3 , x 4 , x n ) to a confidence that input associated with the vector belongs to a class, wherein the x i , are input attributes, wherein the confidence that the input belongs to the class is expressed as f(x)=confidence(class), and wherein the class to which an input belongs infers the action that the user desires to be automatically performed; wherein the auxiliary act is not for an explicit purpose of implementing the action. | 1. A multi-modal multi-lingual mobile device that facilitates automating an action, comprising: a detection component that employs a plurality of integrated sensors to obtain at least one criterion from an auxiliary act through passive observation, the auxiliary act is a conversation of a user with an entity that is not the mobile device, wherein the at least one criterion is an environmental context that relates to a weather condition, and a schedule manipulation action is performed at least partially in view of at least one of expected travel complications or venue incompatibility with the weather condition; and an analyzer component that evaluates the at least one criterion to infer a user intent and automatically implements the action based at least in part upon operation of a rules-based logic component, wherein the rules based logic component automatically allows execution of the action based at least in part upon satisfaction of a defined rule, and based at least in part upon operation of an implementation component configured to identify an individual, the implementation component using an algorithm together with a desired degree of certainty, and based at least in part upon operation of an artificial intelligence component that comprises a classifier function that maps an input attribute vector x=(x 1 , x 2 , x 3 , x 4 , x n ) to a confidence that input associated with the vector belongs to a class, wherein the x i , are input attributes, wherein the confidence that the input belongs to the class is expressed as f(x)=confidence(class), and wherein the class to which an input belongs infers the action that the user desires to be automatically performed; wherein the auxiliary act is not for an explicit purpose of implementing the action. 6. The multi-modal multi-lingual mobile device of claim 1 , the detection component comprises at least one of an input component, an inquiry component and a sensor component. | 0.878661 |
8,185,830 | 32 | 33 | 32. The article of claim 27 , wherein the user group configuration settings specify an authentication method to authenticate the users in the user group. | 32. The article of claim 27 , wherein the user group configuration settings specify an authentication method to authenticate the users in the user group. 33. The article of claim 32 , wherein sending the user group container document over a public network to each of a plurality of client devices comprises authenticating users of the client devices according to the authentication method. | 0.5 |
9,829,984 | 86 | 89 | 86. The computer-readable storage medium of claim 85 , further comprising computer program instructions for: tracking the motion of the object across a subset of the plurality of video frames; obtaining estimated motion parameters of the object based on the tracking; refining the estimated motion parameters of the object; and recognizing the visual gesture based at least in part on the detected motion of the object. | 86. The computer-readable storage medium of claim 85 , further comprising computer program instructions for: tracking the motion of the object across a subset of the plurality of video frames; obtaining estimated motion parameters of the object based on the tracking; refining the estimated motion parameters of the object; and recognizing the visual gesture based at least in part on the detected motion of the object. 89. The computer-readable storage medium of claim 86 , wherein the computer program instructions for tracking the motion of the object comprise computer program instructions for: obtaining the motion vectors of the object, a motion vector of the object indicating a position of the object in the video frame relative to its corresponding position in a previous or reference video frame of the video. | 0.560573 |
8,078,645 | 16 | 17 | 16. A tangible non-transitory machine-readable medium having information stored thereon, wherein the information, when read by a machine, causes the machine to perform the following: traversing through a data stream containing a plurality of name-value pairs organized in a multi-level nested data structure; and for each name-value pair encountered in the multi-level nested data structure, if the name-value pair is located at two levels outside an innermost level, then constructing a new table as a current table corresponding to the name-value pair, if the name-value pair is located at one level outside the innermost level, then constructing a new row within the current table as a current row corresponding to the name-value pair, and if the name-value pair is located at the innermost level, then adding the name-value pair to the current row of the current table as a field. | 16. A tangible non-transitory machine-readable medium having information stored thereon, wherein the information, when read by a machine, causes the machine to perform the following: traversing through a data stream containing a plurality of name-value pairs organized in a multi-level nested data structure; and for each name-value pair encountered in the multi-level nested data structure, if the name-value pair is located at two levels outside an innermost level, then constructing a new table as a current table corresponding to the name-value pair, if the name-value pair is located at one level outside the innermost level, then constructing a new row within the current table as a current row corresponding to the name-value pair, and if the name-value pair is located at the innermost level, then adding the name-value pair to the current row of the current table as a field. 17. The medium of claim 16 , wherein the data stream is represented using a predefined syntax, and traversing through the data stream does not rely on a schema of the predefined syntax. | 0.727139 |
7,716,199 | 27 | 30 | 27. A system comprising: one or more computers; a computer-readable medium coupled to the one or more computers having commands stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each context file contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. | 27. A system comprising: one or more computers; a computer-readable medium coupled to the one or more computers having commands stored thereon which, when executed by the one or more computers, causes the one or more computers to perform operations comprising: receiving multiple context files from one or more third-party content providers, wherein each context file contains one or more commands for controlling an operation of the search engine in processing a search query input and in presenting search results, each context file is one of a plurality of predefined context files; receiving in a search engine the search query input, the search query input received from an interface provided by one of the third party content providers; aggregating the commands in the multiple context files into a set of aggregated commands; using the aggregated commands to control an organization and a presentation of the search results resulting from the processing of the search query input, including: processing the search query input using the aggregated commands to produce a context processed search query; generating context processed search results responsive to the context processed search query; and providing the context processed search results in accordance with the aggregated commands. 30. The system of claim 27 , further comprising: selecting a specific context file specific to the search query input; and selecting a global context file associated with all search engine query inputs. | 0.717087 |
8,108,216 | 23 | 24 | 23. The computer readable storage medium according to claim 17 , wherein the third segment sequence is obtained by adding a next segment located at a position next to a portion of the first segment sequence which corresponds to the second segment sequence to the second segment sequence. | 23. The computer readable storage medium according to claim 17 , wherein the third segment sequence is obtained by adding a next segment located at a position next to a portion of the first segment sequence which corresponds to the second segment sequence to the second segment sequence. 24. The computer readable storage medium according to claim 23 , wherein the third speech unit string is generated by adding a speech unit corresponding to the next segment to the second speech unit string. | 0.5 |
8,730,955 | 1 | 2 | 1. An apparatus, comprising: a capture system configured to couple to a router, which interacts with a plurality of clients in a network environment, wherein the capture system includes a packet capture module for receiving packets associated with traffic flows involving the clients and stores the packets in a receiver packet memory in the capture system; a network interface module; and an application, wherein the packet capture module operates between the network interface module and the application, and wherein the network interface module and the packet capture module operate on a kernel portion of the capture system that is separate from an application portion of the capture system; wherein: the packet capture module further includes a control memory accessible by the network interface module and by the application; the control memory comprising a head pointer updated by the network interface module, and a tail pointer updated by the application; the head pointer and the tail pointer identify the packets in the receiver packet memory which are unprocessed by the application. | 1. An apparatus, comprising: a capture system configured to couple to a router, which interacts with a plurality of clients in a network environment, wherein the capture system includes a packet capture module for receiving packets associated with traffic flows involving the clients and stores the packets in a receiver packet memory in the capture system; a network interface module; and an application, wherein the packet capture module operates between the network interface module and the application, and wherein the network interface module and the packet capture module operate on a kernel portion of the capture system that is separate from an application portion of the capture system; wherein: the packet capture module further includes a control memory accessible by the network interface module and by the application; the control memory comprising a head pointer updated by the network interface module, and a tail pointer updated by the application; the head pointer and the tail pointer identify the packets in the receiver packet memory which are unprocessed by the application. 2. The apparatus of claim 1 , wherein at least some of the packets received from the network interface module are read into the packet capture module by a network interface driver that is configured to interact with both the network interface module and the kernel portion of the capture system, and wherein the capture system only uses one kernel copy of a received packet before it is provided to the application on the application portion of the capture system. | 0.5 |
9,418,374 | 7 | 9 | 7. A method, comprising: identifying a key phrase that appears in digital content; generating a score for the key phrase based at least in part on social media popularity of the key phrase and frequency of the key phrase on a peer group of digital pages associated with a target digital page of the digital content, the peer group of digital pages of a plurality of network accessible sites; identifying said peer group of digital pages, at least in part, by identifying at least one of an outbound link from or an inbound link to the target digital page; determining, based at least in part on the score, whether to use the key phrase to select contextually relevant content to associate with the digital content; and responsive to determining to use the key phrase to select contextually relevant content to associate with the digital document, storing an indication of the determination in a memory device. | 7. A method, comprising: identifying a key phrase that appears in digital content; generating a score for the key phrase based at least in part on social media popularity of the key phrase and frequency of the key phrase on a peer group of digital pages associated with a target digital page of the digital content, the peer group of digital pages of a plurality of network accessible sites; identifying said peer group of digital pages, at least in part, by identifying at least one of an outbound link from or an inbound link to the target digital page; determining, based at least in part on the score, whether to use the key phrase to select contextually relevant content to associate with the digital content; and responsive to determining to use the key phrase to select contextually relevant content to associate with the digital document, storing an indication of the determination in a memory device. 9. The method of claim 7 , further comprising generating the score based at least in part on a rate of change in a popularity level of the key phrase. | 0.825175 |
10,147,414 | 1 | 15 | 1. A machine, comprising: a processor; and a memory connected to the processor, the memory storing instructions executed by the processor to: supply a name page in response to a request from an administrator machine under the control of an organizer; receive name page updates from the administrator machine, wherein the name page updates include a list of names of participants for an event specified by the organizer and to which the participants are to be invited and associated network contact information for the participants; identify one or more of the participants included in the list of names of participants included in the name page for whom audio name information exists within memory; identify one or more of the participants included in the list of names of participants included in the name page for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory, wherein the textual name information and the network contact information for the one or more participants is provided by only the organizer and only for the event specified by the organizer and without receiving input from the one or more participants; form a link to the name page, the link including a token that uniquely identifies one of the participants identified in the list of names of participants included in the name page for whom audio name information does not exist within the memory and that uniquely identifies the name page; transmit, using the network contact information for the one of the participants in the name page, the link to the name page to a client machine associated with the one of the participants uniquely identified by the token to allow the one of the participants to provide audio name information for storage in the memory, the audio name information including a prompt for a first name and a prompt for a last name of the one of the participants; provide, in a graphical user interface associated with the name page, statistics representative of a total number of participants included in the list of names of participants for the event specified by the organizer, a number of the one or more identified participants included in the name page for whom audio name information exists within memory, a number of the one or more identified participants included in the name page for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory; and a number of participants included in the list of names of participants for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory who have received a link to the name page transmitted by the processor; receive audio name information from the client machine associated with the one of the participants uniquely identified by the token; identify, based on the token, that the received audio name information from the client machine associated with the one of the participants uniquely identified by the token is received using the same network contact information for the one of the participants to which the link to the name page is transmitted; associate the received audio name information received from the client machine with the one of the participants in the name page uniquely identified by the token; store the received audio name information from the one of the participants uniquely identified by the token in the memory for access via the name page uniquely identified by the token; and update the statistics provided within the graphical user interface associated with the name page to reflect an adjusted number of the one or more identified participants included in the name page for whom audio name information exists within memory and an adjusted number of the one or more identified participants included in the name page for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory. | 1. A machine, comprising: a processor; and a memory connected to the processor, the memory storing instructions executed by the processor to: supply a name page in response to a request from an administrator machine under the control of an organizer; receive name page updates from the administrator machine, wherein the name page updates include a list of names of participants for an event specified by the organizer and to which the participants are to be invited and associated network contact information for the participants; identify one or more of the participants included in the list of names of participants included in the name page for whom audio name information exists within memory; identify one or more of the participants included in the list of names of participants included in the name page for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory, wherein the textual name information and the network contact information for the one or more participants is provided by only the organizer and only for the event specified by the organizer and without receiving input from the one or more participants; form a link to the name page, the link including a token that uniquely identifies one of the participants identified in the list of names of participants included in the name page for whom audio name information does not exist within the memory and that uniquely identifies the name page; transmit, using the network contact information for the one of the participants in the name page, the link to the name page to a client machine associated with the one of the participants uniquely identified by the token to allow the one of the participants to provide audio name information for storage in the memory, the audio name information including a prompt for a first name and a prompt for a last name of the one of the participants; provide, in a graphical user interface associated with the name page, statistics representative of a total number of participants included in the list of names of participants for the event specified by the organizer, a number of the one or more identified participants included in the name page for whom audio name information exists within memory, a number of the one or more identified participants included in the name page for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory; and a number of participants included in the list of names of participants for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory who have received a link to the name page transmitted by the processor; receive audio name information from the client machine associated with the one of the participants uniquely identified by the token; identify, based on the token, that the received audio name information from the client machine associated with the one of the participants uniquely identified by the token is received using the same network contact information for the one of the participants to which the link to the name page is transmitted; associate the received audio name information received from the client machine with the one of the participants in the name page uniquely identified by the token; store the received audio name information from the one of the participants uniquely identified by the token in the memory for access via the name page uniquely identified by the token; and update the statistics provided within the graphical user interface associated with the name page to reflect an adjusted number of the one or more identified participants included in the name page for whom audio name information exists within memory and an adjusted number of the one or more identified participants included in the name page for whom only textual name information and network contact information exists in the memory and for whom audio name information does not exist within the memory. 15. The machine of claim 1 wherein the memory stores instructions executed by the processor to: enable a search by a client machine of names associated with the name page to selectively form a name match; and supply to the client machine audio name information in response to the name match. | 0.5 |
9,940,352 | 10 | 14 | 10. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform operations comprising: accessing a communication between a first user and a second user; identifying at least one entity within the communication; predicting at least one contextually relevant action associated with the at least one entity, wherein predicting the at least one contextually relevant action comprises: identifying at least one relevant action associated with the identified entity; accessing a database of historical trends and activities of actions taken with respect to the identified entity; identifying amplifying words within the communication; computing a correlation between the identified relevant action, the historical trends and activities, and identified amplifying words; and determining an hierarchy of contextually relevant actions as a function of the computed correlation; selecting at least one contextually relevant action from the hierarchy of contextually relevant actions; and delivering the selected contextually relevant action to at least the second user. | 10. A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to perform operations comprising: accessing a communication between a first user and a second user; identifying at least one entity within the communication; predicting at least one contextually relevant action associated with the at least one entity, wherein predicting the at least one contextually relevant action comprises: identifying at least one relevant action associated with the identified entity; accessing a database of historical trends and activities of actions taken with respect to the identified entity; identifying amplifying words within the communication; computing a correlation between the identified relevant action, the historical trends and activities, and identified amplifying words; and determining an hierarchy of contextually relevant actions as a function of the computed correlation; selecting at least one contextually relevant action from the hierarchy of contextually relevant actions; and delivering the selected contextually relevant action to at least the second user. 14. The computer readable medium of claim 10 , wherein the operations to access a communication between a first user and second user comprise accessing an audio communication. | 0.767905 |
8,903,759 | 21 | 25 | 21. A method in a computing system for providing a choice of actions for selection by a user, comprising: receiving captured text, the captured text being a text transcription of an image of a human-perceptible textual portion of a printed document captured by a handheld information capture device; identifying an electronic counterpart to the printed document from the captured text, wherein the printed document has one or more context points, each of the context points is a visible feature of the printed document, each of the context points is associated in the electronic counterpart with an action, and each of the context points has a location within the printed document; determining a location within the printed document from which the captured text was captured; determining distances between the location within the printed document of the captured text and the locations of one or more context points within the printed document; identifying markup data that maps regions of the printed document to regions of the electronic counterpart to the printed document, wherein the markup data comprises at least one of actions or rules for determining actions; determining a plurality of actions to be performed, based at least in part on the determined distances, and based at least in part on markup data associated with the received text; and providing a menu of choices to the user that includes at least a portion of the determined plurality of actions. | 21. A method in a computing system for providing a choice of actions for selection by a user, comprising: receiving captured text, the captured text being a text transcription of an image of a human-perceptible textual portion of a printed document captured by a handheld information capture device; identifying an electronic counterpart to the printed document from the captured text, wherein the printed document has one or more context points, each of the context points is a visible feature of the printed document, each of the context points is associated in the electronic counterpart with an action, and each of the context points has a location within the printed document; determining a location within the printed document from which the captured text was captured; determining distances between the location within the printed document of the captured text and the locations of one or more context points within the printed document; identifying markup data that maps regions of the printed document to regions of the electronic counterpart to the printed document, wherein the markup data comprises at least one of actions or rules for determining actions; determining a plurality of actions to be performed, based at least in part on the determined distances, and based at least in part on markup data associated with the received text; and providing a menu of choices to the user that includes at least a portion of the determined plurality of actions. 25. The method of claim 21 , wherein the plurality of action include scrolling to the captured text in the electronic counterpart. | 0.703196 |
8,266,312 | 4 | 5 | 4. The method according to claim 3 , further comprising, if an element of said XML-type document is one of a command and an item: appending an opening XML-type fragment representing the element to said buffer; and reserving space in said buffer for a corresponding closing XML-type fragment. | 4. The method according to claim 3 , further comprising, if an element of said XML-type document is one of a command and an item: appending an opening XML-type fragment representing the element to said buffer; and reserving space in said buffer for a corresponding closing XML-type fragment. 5. The method according to claim 4 , further comprising, (a) if appending said XML-type fragment to said buffer results in a size limit violation: removing said opening XML-type fragment from said buffer; and notifying a user that the element has not been encoded; (b) if appending said XML-type fragment results in the contents of said buffer being ‘valid’: flushing said buffer to said transport layer; and notifying a user that the element was encoded; (c) if appending said XML-type fragment results in the contents of said buffer being ‘invalid’: not flushing said buffer; and notifying a user that the element has not been encoded. | 0.5 |
7,499,910 | 13 | 14 | 13. The computer-readable program code embedded in the memory of claim 1 , wherein the set of rules, when implemented, checks for permissible roll-ups of aggregates. | 13. The computer-readable program code embedded in the memory of claim 1 , wherein the set of rules, when implemented, checks for permissible roll-ups of aggregates. 14. The computer-readable program code embedded in the memory of claim 13 , wherein the permissible aggregate roll-ups are determined by evaluating restrictions included in the new query against restrictions included in the cached query. | 0.5 |
9,223,537 | 40 | 43 | 40. A method comprising: under control of one or more computing devices configured to implement a virtual assistant, parsing user input with a natural language processing system that employs a language model, the user input comprising at least one of gesture input, audio input, keypad input, or touch input; representing the user input in a conversation user interface; determining, with the natural language processing system, a response to the user input; representing the response to the user input in the conversation user interface; enabling a user to interact with the conversation user interface to ascertain how the response was determined and to modify assumptions used to determine the response, wherein modification of one or more assumptions results in a modified response, and wherein individual assumptions comprise at least one of a value obtained via the conversation user interface, a value that is external to the conversation user interface, or a value that is obtained from a previous conversation between the user and the virtual assistant; and representing the modified response in the conversation user interface. | 40. A method comprising: under control of one or more computing devices configured to implement a virtual assistant, parsing user input with a natural language processing system that employs a language model, the user input comprising at least one of gesture input, audio input, keypad input, or touch input; representing the user input in a conversation user interface; determining, with the natural language processing system, a response to the user input; representing the response to the user input in the conversation user interface; enabling a user to interact with the conversation user interface to ascertain how the response was determined and to modify assumptions used to determine the response, wherein modification of one or more assumptions results in a modified response, and wherein individual assumptions comprise at least one of a value obtained via the conversation user interface, a value that is external to the conversation user interface, or a value that is obtained from a previous conversation between the user and the virtual assistant; and representing the modified response in the conversation user interface. 43. A method of claim 40 , further comprising learning characteristics of the user and choosing the assumptions used to determine the response from the characteristics. | 0.623318 |
9,400,987 | 1 | 10 | 1. A method comprising the steps: receiving, at a computing device over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating, via at least one processor of the computing device, a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying, via at least one processor of the computing device, at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting, via at least one processor of the computing device, one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, at the computing device over the network by the computing device, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating, via at least one processor of the computing device, a dynamic webpage having content relating to the user context query. | 1. A method comprising the steps: receiving, at a computing device over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating, via at least one processor of the computing device, a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying, via at least one processor of the computing device, at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting, via at least one processor of the computing device, one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, at the computing device over the network by the computing device, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating, via at least one processor of the computing device, a dynamic webpage having content relating to the user context query. 10. The method of claim 1 wherein the user interface is the display of the inserted at least one data object. | 0.878889 |
8,577,912 | 15 | 16 | 15. The system of claim 14 , further comprising: a data store configured to maintain an index that associates the one or more codes with one or more document locations corresponding to the plurality of documents. | 15. The system of claim 14 , further comprising: a data store configured to maintain an index that associates the one or more codes with one or more document locations corresponding to the plurality of documents. 16. The system of claim 15 , wherein the request to access the first document includes a selection of a link to a linking service that maintains the index. | 0.5 |
7,882,149 | 1 | 11 | 1. A method for determining whether a document is acceptable or rejected for use by an apparatus, said apparatus comprising a parser for parsing said document, wherein the document is stored on a computer-readable storage medium and includes plural elements and attributes arranged according to a schema of elements and attributes, said method comprising the steps of: using a computer to determine a version of the document; compiling a metaschema based on the parser and the determined version of the document, said metaschema providing a set of rules for a valid change of the schema, each of the set of rules comprising a value and an expression of at least one of an element and an attribute of the schema; using a computer to execute steps of: (a) determining a similarity score for said document by comparing at least one of the elements and the attributes of said document to the value and the expression of at least one of an element and an attribute of the schema in the metaschema; and (b) mapping the document to the schema to produce a list of data values for information requested from the compiled metaschema; and using a computer to use the similarity score to accept or reject further use of the document, wherein the list of data values is used to extract information from the mapped document if the document is accepted for further use. | 1. A method for determining whether a document is acceptable or rejected for use by an apparatus, said apparatus comprising a parser for parsing said document, wherein the document is stored on a computer-readable storage medium and includes plural elements and attributes arranged according to a schema of elements and attributes, said method comprising the steps of: using a computer to determine a version of the document; compiling a metaschema based on the parser and the determined version of the document, said metaschema providing a set of rules for a valid change of the schema, each of the set of rules comprising a value and an expression of at least one of an element and an attribute of the schema; using a computer to execute steps of: (a) determining a similarity score for said document by comparing at least one of the elements and the attributes of said document to the value and the expression of at least one of an element and an attribute of the schema in the metaschema; and (b) mapping the document to the schema to produce a list of data values for information requested from the compiled metaschema; and using a computer to use the similarity score to accept or reject further use of the document, wherein the list of data values is used to extract information from the mapped document if the document is accepted for further use. 11. A method according to claim 1 , comprising the further step of: using a computer to constrain evolution of a schema associated with the document. | 0.708984 |
7,860,316 | 16 | 17 | 16. A method of automatically creating an index in an image forming apparatus, the method comprising: scanning a document with a scan apparatus; separating the scanned document with a text/image separation apparatus into a text area and an image area and separating texts in the text area into symbols based on pixel data of the separated text area by comparing at least one pixel of the pixel data in the separated text area with a plurality of neighboring pixels to determine and separate individual symbols of the text area; extracting one or more properties of the separated symbols and comparing the extracted symbol properties with one or more index thresholds to determine whether the text including the symbols is an index object with an index determination apparatus, where the index thresholds are set as an average value of preset symbol properties calculated based on variation of the preset symbol properties; and creating an index page with an index page creation apparatus including the text determined as the index object and information about a page including the text that corresponds to the index object, wherein the symbols are determined as index-object symbols, the index-object symbols are grouped, and the texts including the groups of the index-object symbols are determined as objects in the index, when the extracted symbol properties are greater than the index thresholds. | 16. A method of automatically creating an index in an image forming apparatus, the method comprising: scanning a document with a scan apparatus; separating the scanned document with a text/image separation apparatus into a text area and an image area and separating texts in the text area into symbols based on pixel data of the separated text area by comparing at least one pixel of the pixel data in the separated text area with a plurality of neighboring pixels to determine and separate individual symbols of the text area; extracting one or more properties of the separated symbols and comparing the extracted symbol properties with one or more index thresholds to determine whether the text including the symbols is an index object with an index determination apparatus, where the index thresholds are set as an average value of preset symbol properties calculated based on variation of the preset symbol properties; and creating an index page with an index page creation apparatus including the text determined as the index object and information about a page including the text that corresponds to the index object, wherein the symbols are determined as index-object symbols, the index-object symbols are grouped, and the texts including the groups of the index-object symbols are determined as objects in the index, when the extracted symbol properties are greater than the index thresholds. 17. The method of claim 16 , wherein the extracted symbol properties comprise one or more of a symbol width, a symbol height, and a stroke width. | 0.735401 |
Subsets and Splits