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9,679,556 | 23 | 25 | 23. The method of claim 15 , wherein the one or more of an estimated scatter matrix comprises two scatter matrices, one is a between class scatter matrix and the other is a within class scatter matrix. | 23. The method of claim 15 , wherein the one or more of an estimated scatter matrix comprises two scatter matrices, one is a between class scatter matrix and the other is a within class scatter matrix. 25. The method of claim 23 , wherein the error rate for the within class scatter matrix is determined using the mathematical equation: S w = ∑ t = 1 T ( y ( t ) - μ ) ( y ( t ) - μ ) t / T wherein S w represents a within-class scatter matrix, μ represents a global mean vector, (y(t)−μ) represents a vector, (y(t)−μ) t represents a transpose of the vector, and T represents a total number of frames in a training data set. | 0.526432 |
8,180,834 | 18 | 20 | 18. A computer program product comprising a non-transitory computer useable medium including control logic stored therein, the control logic enabling the filtering of messages received by a user, and the control logic, if executed, causing a processor to perform operations comprising: determining, in a message classification module, a score for a received message by analyzing a plurality of portions of a the body of the received message, wherein each portion in the plurality of portions is scored with a portion score; determining a user-defined authoritative status for the received message; determining whether an address associated with a sender of the received message matches an entry on a positive screening list; and assigning a non-spam user-defined authoritative status for the received message if the address associated with the sender matches an entry on the positive screening list; storing the received message in a quarantine folder if the address associated with the sender does not match an entry on the positive screening list; receiving a filtering status indication for the received message; assigning a non-spam user-defined authoritative status for the received message if the filtering status indication indicates user approval of the message; assigning a spam user-defined authoritative status for the received message if the filtering status indication indicates user disapproval of the message; and automatically training the classification module when the score is inconsistent with the user-defined authoritative status. | 18. A computer program product comprising a non-transitory computer useable medium including control logic stored therein, the control logic enabling the filtering of messages received by a user, and the control logic, if executed, causing a processor to perform operations comprising: determining, in a message classification module, a score for a received message by analyzing a plurality of portions of a the body of the received message, wherein each portion in the plurality of portions is scored with a portion score; determining a user-defined authoritative status for the received message; determining whether an address associated with a sender of the received message matches an entry on a positive screening list; and assigning a non-spam user-defined authoritative status for the received message if the address associated with the sender matches an entry on the positive screening list; storing the received message in a quarantine folder if the address associated with the sender does not match an entry on the positive screening list; receiving a filtering status indication for the received message; assigning a non-spam user-defined authoritative status for the received message if the filtering status indication indicates user approval of the message; assigning a spam user-defined authoritative status for the received message if the filtering status indication indicates user disapproval of the message; and automatically training the classification module when the score is inconsistent with the user-defined authoritative status. 20. The computer program product of claim 18 , wherein the operations further comprise: initializing the classification module, wherein initializing the classification module comprises: receiving an indication of a set of existing non-spam messages stored for the user and an indication of a set of existing spam messages stored for the user, determining a ratio of non-spam messages to spam messages, training the classification module using the indicated messages in a ratio representative of the ratio of non-spam to spam messages, and retraining the classification module using the indicated messages in a ratio representative of the ratio of non-spam to spam messages. | 0.5 |
8,024,323 | 1 | 4 | 1. A method in a computing system for defining a group of people, comprising: providing a visual user interface containing a control for receiving a query string; receiving a query string via the control; using an index on a body of documents to identify documents of the body that satisfy the received query string; accessing a record indicating which documents of the body were accessed by each of a population of people during a foregoing time period to identify people among the population that accessed at least a threshold number of the identified documents during the foregoing time period; and displaying within the visual user interface, in conjunction with the control, information characterizing the people identified. | 1. A method in a computing system for defining a group of people, comprising: providing a visual user interface containing a control for receiving a query string; receiving a query string via the control; using an index on a body of documents to identify documents of the body that satisfy the received query string; accessing a record indicating which documents of the body were accessed by each of a population of people during a foregoing time period to identify people among the population that accessed at least a threshold number of the identified documents during the foregoing time period; and displaying within the visual user interface, in conjunction with the control, information characterizing the people identified. 4. The method of claim 1 wherein the body of documents is a set of web pages available at a subject web site. | 0.741706 |
9,600,842 | 29 | 82 | 29. A computer program product embodied on at least one non-transitory computer readable medium and configured to cause at least one hardware processor to operate, the computer program product comprising: code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to identify at least one computer-readable Extensible Markup Language (XML)-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and includes: a plurality of line items with a plurality of data values, and a plurality of computer-readable semantic tags that describe a semantic meaning of the data values, where the at least one computer-readable XML-compliant data document is capable of including multiple hierarchical relationships between two of the plurality of line items; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to parse the at least one computer-readable XML-compliant data document, by: receiving the at least one computer-readable XML-compliant data document, identifying the multiple hierarchical relationships between the two line items, and at least one of the computer-readable semantic tags that describes the semantic meaning of at least one of the data values included in the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to access a plurality of computer-readable rules including: a computer-readable datatype rule for validation of a type of data values, a computer-readable calculation rule for validation of a calculation involving data values, and a computer-readable unit rule for validation of a unit of data values; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to process the at least one computer-readable XML-compliant data document, by: identifying at least a subset of the computer-readable rules including at least one of: the computer-readable datatype rule for validation of the type of data values, the computer-readable calculation rule for validation of the calculation involving data values, or the computer-readable unit rule for validation of the unit of data values; and processing at least a portion of the data values of at least a portion of the plurality of line items of the at least one computer-readable XML-compliant data document, utilizing the at least subset of the computer-readable rules, and at least a portion of the computer-readable semantic tags of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to display a result of a validation of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to develop a report, by: identifying the at least one computer-readable semantic tag that describes the semantic meaning of the at least one data value included in the at least one computer-readable XML-compliant data document, and retrieving data from one or more sources to represent the at least one data value in the report. | 29. A computer program product embodied on at least one non-transitory computer readable medium and configured to cause at least one hardware processor to operate, the computer program product comprising: code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to identify at least one computer-readable Extensible Markup Language (XML)-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and includes: a plurality of line items with a plurality of data values, and a plurality of computer-readable semantic tags that describe a semantic meaning of the data values, where the at least one computer-readable XML-compliant data document is capable of including multiple hierarchical relationships between two of the plurality of line items; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to parse the at least one computer-readable XML-compliant data document, by: receiving the at least one computer-readable XML-compliant data document, identifying the multiple hierarchical relationships between the two line items, and at least one of the computer-readable semantic tags that describes the semantic meaning of at least one of the data values included in the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to access a plurality of computer-readable rules including: a computer-readable datatype rule for validation of a type of data values, a computer-readable calculation rule for validation of a calculation involving data values, and a computer-readable unit rule for validation of a unit of data values; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to process the at least one computer-readable XML-compliant data document, by: identifying at least a subset of the computer-readable rules including at least one of: the computer-readable datatype rule for validation of the type of data values, the computer-readable calculation rule for validation of the calculation involving data values, or the computer-readable unit rule for validation of the unit of data values; and processing at least a portion of the data values of at least a portion of the plurality of line items of the at least one computer-readable XML-compliant data document, utilizing the at least subset of the computer-readable rules, and at least a portion of the computer-readable semantic tags of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to display a result of a validation of the at least one computer-readable XML-compliant data document; code stored on the at least one non-transitory computer readable medium and configured to cause the at least one hardware processor to develop a report, by: identifying the at least one computer-readable semantic tag that describes the semantic meaning of the at least one data value included in the at least one computer-readable XML-compliant data document, and retrieving data from one or more sources to represent the at least one data value in the report. 82. The computer program product of claim 29 , wherein the computer program product is configured for identifying taxonomy software elements in connection with at least one source data document. | 0.94498 |
8,789,011 | 8 | 11 | 8. A method of modeling an arbitrarily complex environment, comprising: at a computer communicatively connected to networked devices, defining a data model having a set of data structures, the set of data structures comprising: a components data structure, a relationships data structure, and a blueprints data structure, wherein a component in the components data structure represents a logical or physical entity in the arbitrarily complex environment, wherein a relationship in the relationships data structure represents an association or dependency between two or more components in the arbitrarily complex environment, wherein a blueprint in the blueprints data structure represents a container for the two or more components and the association or dependency between the two or more components, wherein the data model comprises a set of blueprints for modeling the arbitrarily complex environment or a subset thereof; storing the components data structure, the relationships data structure, and the blueprints data structure corresponding to the data model in a table schema that includes a plurality of linked tables; and making a change to the components data structure, the relationships data structure, or the blueprints data structure, wherein the table schema is not altered by the change. | 8. A method of modeling an arbitrarily complex environment, comprising: at a computer communicatively connected to networked devices, defining a data model having a set of data structures, the set of data structures comprising: a components data structure, a relationships data structure, and a blueprints data structure, wherein a component in the components data structure represents a logical or physical entity in the arbitrarily complex environment, wherein a relationship in the relationships data structure represents an association or dependency between two or more components in the arbitrarily complex environment, wherein a blueprint in the blueprints data structure represents a container for the two or more components and the association or dependency between the two or more components, wherein the data model comprises a set of blueprints for modeling the arbitrarily complex environment or a subset thereof; storing the components data structure, the relationships data structure, and the blueprints data structure corresponding to the data model in a table schema that includes a plurality of linked tables; and making a change to the components data structure, the relationships data structure, or the blueprints data structure, wherein the table schema is not altered by the change. 11. The method of claim 8 , further comprising defining a hierarchy of component and relationship types. | 0.793651 |
8,700,627 | 1 | 9 | 1. A method for displaying relationships between concepts to provide classification suggestions via inclusion, comprising the steps of: designating reference concepts each associated with a classification code and a visual representation of that classification code comprising at least one of a shape, a color, and a symbol, wherein each concept comprises nouns and noun phrases with common semantic meaning that are extracted from a set of documents; extracting uncoded concepts from unclassified documents and associating each of the uncoded concepts with a visual representation different from the representations of the classification codes; forming a grouped concept set by grouping a subset of the classified reference concepts with a set of uncoded concepts; generating clusters, each comprising a portion of the uncoded concepts and the classified reference concepts of the grouped concept set, comprising: determining a similarity between the concepts in the grouped concept set; and putting the concepts whose similarity exceeds a threshold into one of the clusters: visually depicting relationships between the uncoded concepts and one or more classified reference concepts in at least one of the clusters as suggestions for classifying the uncoded concepts in that cluster, comprising displaying the visual representation associated with each of the classified reference concepts in that cluster and the visual representation of each of the uncoded concepts in that cluster, wherein the steps are performed by a suitably programmed computer. | 1. A method for displaying relationships between concepts to provide classification suggestions via inclusion, comprising the steps of: designating reference concepts each associated with a classification code and a visual representation of that classification code comprising at least one of a shape, a color, and a symbol, wherein each concept comprises nouns and noun phrases with common semantic meaning that are extracted from a set of documents; extracting uncoded concepts from unclassified documents and associating each of the uncoded concepts with a visual representation different from the representations of the classification codes; forming a grouped concept set by grouping a subset of the classified reference concepts with a set of uncoded concepts; generating clusters, each comprising a portion of the uncoded concepts and the classified reference concepts of the grouped concept set, comprising: determining a similarity between the concepts in the grouped concept set; and putting the concepts whose similarity exceeds a threshold into one of the clusters: visually depicting relationships between the uncoded concepts and one or more classified reference concepts in at least one of the clusters as suggestions for classifying the uncoded concepts in that cluster, comprising displaying the visual representation associated with each of the classified reference concepts in that cluster and the visual representation of each of the uncoded concepts in that cluster, wherein the steps are performed by a suitably programmed computer. 9. A method according to claim 1 , further comprising: generating the set of classified reference concepts, comprising at least one of: identifying dissimilar uncoded concepts for a document review project and assigning a classification code to each of the dissimilar uncoded concepts for inclusion in the reference concepts set; and clustering uncoded concepts for a document review project, selecting one or more of the uncoded concepts in one or more of the clusters, and assigning a classification code to each of the selected uncoded concepts for inclusion in the reference concepts set. | 0.5 |
10,134,397 | 7 | 9 | 7. An electronic device comprising: a sensor; a microphone; memory storing instructions; one or more processors configured to execute the instructions to: determine, based on one or more signals from the sensor and when a multimodal interface of an electronic device is at a text modality, that a context satisfies a criterion; and responsive to determining that the context satisfies the criterion: preemptively establish a voice-to-text conversion session between the electronic device and a voice-to-text conversion processor, the voice-to-text conversion session used to process voice input received via the microphone at a voice modality of the multimodal interface; provide output to indicate that the voice-to-text conversion session is available; receive a voice input; initiate processing of at least a portion of the voice input at the voice-to-text conversion processor within the session; and build a complete query based on output from the voice-to-text conversion processor. | 7. An electronic device comprising: a sensor; a microphone; memory storing instructions; one or more processors configured to execute the instructions to: determine, based on one or more signals from the sensor and when a multimodal interface of an electronic device is at a text modality, that a context satisfies a criterion; and responsive to determining that the context satisfies the criterion: preemptively establish a voice-to-text conversion session between the electronic device and a voice-to-text conversion processor, the voice-to-text conversion session used to process voice input received via the microphone at a voice modality of the multimodal interface; provide output to indicate that the voice-to-text conversion session is available; receive a voice input; initiate processing of at least a portion of the voice input at the voice-to-text conversion processor within the session; and build a complete query based on output from the voice-to-text conversion processor. 9. The device of claim 7 , wherein the sensor is an accelerometer. | 0.856522 |
10,133,781 | 10 | 13 | 10. A method of generating a query in a user interface, the method comprising: displaying, in a visio-spatial user interface generated by a processor based device, a user interface (UI) element representation of a first query item, the first query item being a data structure belonging to a data set and having at least one attribute; displaying, in the visio-spatial user interface, a UI element representation of a second query item, the second query item being an anchor query item type of data structure defined as relating to at least one particular attribute of another query item; receiving an indication of a user selectively positioning one of the UI element representation of one of the first query item and the UI element representation of the second query item in proximate location to the UI element representation of the other of the first query item and the second query item in the visio-spatial user interface, the visio-spatial user interface including a display of both the UI element representation of the first query item and the UI element representation of the second query item; associating, by a processor, the second query item with the first query item in response to the user selectively manipulating at least one of the UI element representation of the first query item and the UI element representation of the second query item within the visio-spatial user interface to indicate a relationship between the first query item and the second query item; automatically retrieving, in response to the second query item being associated with the first query item, a value for the at least one particular attribute of the second query item defined as relating to another query item from the first query item; generating, by the processor, query search terms including a combination of the retrieved value and the second query item; and saving a record of the query search terms. | 10. A method of generating a query in a user interface, the method comprising: displaying, in a visio-spatial user interface generated by a processor based device, a user interface (UI) element representation of a first query item, the first query item being a data structure belonging to a data set and having at least one attribute; displaying, in the visio-spatial user interface, a UI element representation of a second query item, the second query item being an anchor query item type of data structure defined as relating to at least one particular attribute of another query item; receiving an indication of a user selectively positioning one of the UI element representation of one of the first query item and the UI element representation of the second query item in proximate location to the UI element representation of the other of the first query item and the second query item in the visio-spatial user interface, the visio-spatial user interface including a display of both the UI element representation of the first query item and the UI element representation of the second query item; associating, by a processor, the second query item with the first query item in response to the user selectively manipulating at least one of the UI element representation of the first query item and the UI element representation of the second query item within the visio-spatial user interface to indicate a relationship between the first query item and the second query item; automatically retrieving, in response to the second query item being associated with the first query item, a value for the at least one particular attribute of the second query item defined as relating to another query item from the first query item; generating, by the processor, query search terms including a combination of the retrieved value and the second query item; and saving a record of the query search terms. 13. The method of claim 10 , wherein the at least one particular attribute is an attribute type. | 0.905882 |
6,061,654 | 16 | 17 | 16. The method according to claim 1, further comprising the steps of: i) prompting the user to indicate whether the selected reference identifier matches the entered identifier; j) if the user indicates that the selected reference identifier matches the entered identifier, acknowledging the user as having entered a valid identifier; k) if the user indicates that the selected reference identifier does not match the entered identifier: l) providing a second plurality of reference identifiers, the second plurality of reference identifiers including every reference identifier except the selected reference identifier; m) repeating steps e) and f) for every reference identifier included in the second plurality of reference identifiers, each one of the reference identifiers of the second plurality of reference identifiers being associated with a second corresponding identifier recognition probability; and n) selecting from the second plurality of reference identifiers the reference identifier most likely matching the entered identifier based on the second corresponding identifier recognition probabilities. | 16. The method according to claim 1, further comprising the steps of: i) prompting the user to indicate whether the selected reference identifier matches the entered identifier; j) if the user indicates that the selected reference identifier matches the entered identifier, acknowledging the user as having entered a valid identifier; k) if the user indicates that the selected reference identifier does not match the entered identifier: l) providing a second plurality of reference identifiers, the second plurality of reference identifiers including every reference identifier except the selected reference identifier; m) repeating steps e) and f) for every reference identifier included in the second plurality of reference identifiers, each one of the reference identifiers of the second plurality of reference identifiers being associated with a second corresponding identifier recognition probability; and n) selecting from the second plurality of reference identifiers the reference identifier most likely matching the entered identifier based on the second corresponding identifier recognition probabilities. 17. The method according to claim 16, wherein the reference identifier selected in step n) corresponds to the highest identifier recognition probability of the second corresponding identifier recognition probabilities. | 0.911454 |
9,043,331 | 30 | 31 | 30. A system comprising: at least one processor; and a non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the at least one processor to: maintain, on a non-transitory computer readable medium, a URL database comprising one or more URLs; query, without user intervention, a first third-party database for information associated with the one or more URLs; query, without user intervention, a second third-party database for information associated with the one or more URLs; merge the information associated with the one or more URLs from the first third-party database and the information associated with the one or more URLs from the second third-party database; determining if the one or more URLs are root URLs based on a set of predefined rules; if it is determined that the one or more URLs are root URLs, classifying the one or more URLs as root URLs in the URL database and updating the URL database to add the classification that the one or more URLs are root URLs; and updating the URL database to include the merged information from the first third-party database and the second third-party database. | 30. A system comprising: at least one processor; and a non-transitory computer-readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the at least one processor to: maintain, on a non-transitory computer readable medium, a URL database comprising one or more URLs; query, without user intervention, a first third-party database for information associated with the one or more URLs; query, without user intervention, a second third-party database for information associated with the one or more URLs; merge the information associated with the one or more URLs from the first third-party database and the information associated with the one or more URLs from the second third-party database; determining if the one or more URLs are root URLs based on a set of predefined rules; if it is determined that the one or more URLs are root URLs, classifying the one or more URLs as root URLs in the URL database and updating the URL database to add the classification that the one or more URLs are root URLs; and updating the URL database to include the merged information from the first third-party database and the second third-party database. 31. The system of claim 30 , wherein the additional information associated with the one or more URLs comprises geographical information. | 0.5 |
9,071,649 | 1 | 2 | 1. A method comprising: receiving real time live data that includes one or more contexts from multiple data systems on the Internet (cloud) configured to deliver the data to a mobile device; correlating the data based on the one or more contexts of the data; determining a subset of the data based on a context of the mobile device after correlating the data from the multiple data systems based on the one or more contexts of the data, the context of the mobile device based on a calendar entry of a user of the mobile device and a location of the mobile device; delivering in real time, by a push engine, the subset of the data to the mobile device based on a push mechanism. | 1. A method comprising: receiving real time live data that includes one or more contexts from multiple data systems on the Internet (cloud) configured to deliver the data to a mobile device; correlating the data based on the one or more contexts of the data; determining a subset of the data based on a context of the mobile device after correlating the data from the multiple data systems based on the one or more contexts of the data, the context of the mobile device based on a calendar entry of a user of the mobile device and a location of the mobile device; delivering in real time, by a push engine, the subset of the data to the mobile device based on a push mechanism. 2. The method of claim 1 , wherein the subset of the data includes service lead data. | 0.855932 |
7,559,022 | 13 | 14 | 13. The method according to claim 1 , wherein one or more rules for distribution of the file are specified by an author of the authored work and included in the file. | 13. The method according to claim 1 , wherein one or more rules for distribution of the file are specified by an author of the authored work and included in the file. 14. The method according to claim 13 , wherein the rules include at least one of: a number of times the file is accessed, the amount of time file may be accessed, a number of email addresses which may access the file, and specific email addresses which may or may not access the file. | 0.5 |
7,926,112 | 11 | 19 | 11. A system, comprising: a computer readable storage medium storing program instructions for protecting a computing device from potentially harmful code in a document; a processor in communication with the computer readable storage medium to acquire and execute the program instructions, wherein the processor executes the program instructions to: receive a data structure representation of the document; add dynamically one or more definitions of potentially harmful active content to an editable configuration file, each definition identifying potentially harmful active content and specifying an action to be performed on that potentially harmful active content if that potentially harmful active content is found in the document; parse the editable configuration file to generate a data structure representation of the one or more definitions in the editable configuration file; compare the data structure representation of the document with the data structure representation of the one or more definitions of potentially harmful active content to identify potentially harmful active content within the document; and modify the document to render harmless any identified potentially harmful active content before presenting the document to the computing device. | 11. A system, comprising: a computer readable storage medium storing program instructions for protecting a computing device from potentially harmful code in a document; a processor in communication with the computer readable storage medium to acquire and execute the program instructions, wherein the processor executes the program instructions to: receive a data structure representation of the document; add dynamically one or more definitions of potentially harmful active content to an editable configuration file, each definition identifying potentially harmful active content and specifying an action to be performed on that potentially harmful active content if that potentially harmful active content is found in the document; parse the editable configuration file to generate a data structure representation of the one or more definitions in the editable configuration file; compare the data structure representation of the document with the data structure representation of the one or more definitions of potentially harmful active content to identify potentially harmful active content within the document; and modify the document to render harmless any identified potentially harmful active content before presenting the document to the computing device. 19. The system of claim 11 , wherein the action specified by a given definition is to replace the identified potentially harmful active content in the document with active content known to be harmless. | 0.66388 |
9,342,583 | 14 | 15 | 14. A non-transitory computer-readable medium encoded with a computer program comprising instructions that when executed operate to cause a computer to perform operations comprising: identifying image features in images from a plurality of distinct content items; determining that, for a subset of the distinct content items, the content items in the subset each have respective images that have at least a minimum number of the identified image features in common; generating implicit links between the content items in the identified subset based on determining that the content items in the subset have at least the minimum number of the identified image features in common; assigning weightings to the implicit links between the subset of the content items; and determining a rank score for at least one of the content items in the subset based at least in part on the weightings of the implicit links, the rank score being a value indicative of the importance of the content item relative to others of the distinct content items. | 14. A non-transitory computer-readable medium encoded with a computer program comprising instructions that when executed operate to cause a computer to perform operations comprising: identifying image features in images from a plurality of distinct content items; determining that, for a subset of the distinct content items, the content items in the subset each have respective images that have at least a minimum number of the identified image features in common; generating implicit links between the content items in the identified subset based on determining that the content items in the subset have at least the minimum number of the identified image features in common; assigning weightings to the implicit links between the subset of the content items; and determining a rank score for at least one of the content items in the subset based at least in part on the weightings of the implicit links, the rank score being a value indicative of the importance of the content item relative to others of the distinct content items. 15. The non-transitory computer-readable medium of claim 14 , wherein assigning the weightings to the implicit links comprises assigning, to a particular implicit link between a first content item of the distinct content items and a second content item of the distinct content items, a weighting determined based at least in part on a number of identified image features in common between an image of the first content item and an image of the second content item. | 0.5 |
7,599,916 | 15 | 18 | 15. A computer system for performing context based document searches comprising: a processing unit coupled to a computer storage medium, the computer storage medium having stored thereon a plurality of computer software components executable by the processing unit, the computer software components comprising a grid builder, a content tag assignment mechanism, a feature association mechanism, a user event tracker, and a keyword matching mechanism: the grid builder constructs a content space grid comprising content tiles, each of the content tiles is associated with feature vectors and is arranged according to subject matter of words or word phrases represented by the feature vectors, wherein the feature vectors of each of the content tiles are related to a position of the content tiles on the content space grid, and wherein the position ensures that the content tiles shared a common boundary in the content space grid have related words or word phrases associated therewith; the content tag assignment mechanism assigns a content tag to each of the content tiles according to the feature vectors, wherein the content tag is assigned to each of the content tiles, respectively, and identifies locations of the content tiles within the content space grid; the feature association mechanism assigns a series of feature values for a document according to a content therein, associating the document with one or more content tiles by comparing the series of feature values for the document against the feature vectors of the content tiles, and assigning the content tag to the document based on the content tiles associated therewith based on the comparison; the user event tracker maintains a history of user events that indicates documents by updating content tags corresponding to each content tile and selecting the content tags corresponding to user preferences; and the keyword matching mechanism matches a content tag appended to a search query with a document, wherein matching comprises comparing the content tag appended to the search query against the content tag assigned to each of the one or more content tiles to find at least one corresponding content tile and to identify the document associated therewith. | 15. A computer system for performing context based document searches comprising: a processing unit coupled to a computer storage medium, the computer storage medium having stored thereon a plurality of computer software components executable by the processing unit, the computer software components comprising a grid builder, a content tag assignment mechanism, a feature association mechanism, a user event tracker, and a keyword matching mechanism: the grid builder constructs a content space grid comprising content tiles, each of the content tiles is associated with feature vectors and is arranged according to subject matter of words or word phrases represented by the feature vectors, wherein the feature vectors of each of the content tiles are related to a position of the content tiles on the content space grid, and wherein the position ensures that the content tiles shared a common boundary in the content space grid have related words or word phrases associated therewith; the content tag assignment mechanism assigns a content tag to each of the content tiles according to the feature vectors, wherein the content tag is assigned to each of the content tiles, respectively, and identifies locations of the content tiles within the content space grid; the feature association mechanism assigns a series of feature values for a document according to a content therein, associating the document with one or more content tiles by comparing the series of feature values for the document against the feature vectors of the content tiles, and assigning the content tag to the document based on the content tiles associated therewith based on the comparison; the user event tracker maintains a history of user events that indicates documents by updating content tags corresponding to each content tile and selecting the content tags corresponding to user preferences; and the keyword matching mechanism matches a content tag appended to a search query with a document, wherein matching comprises comparing the content tag appended to the search query against the content tag assigned to each of the one or more content tiles to find at least one corresponding content tile and to identify the document associated therewith. 18. The computer system of claim 15 , further comprising a document indexing mechanism to store associations between content tags and documents that are assigned according to a pre-search process. | 0.606426 |
9,177,013 | 1 | 9 | 1. A computer based method for identifying, processing, and managing a set of citations in an electronic document, the method comprising: a. identifying, using an identifying module to process the electronic document, a first citation; b. determining, using a reference management module, the first citation is an unformatted citation; c. querying, using a query module, a first citation library stored in a first location, the first citation library comprising a first set of citation data; d. comparing, using a comparing module, the first citation to the first set of citation data; e. determining, using a citation matching module, a first set of possible matching citations from the first set of citation data; f. based on detecting a predetermined event, querying, using the query module, a second citation library stored in a second location, the second citation library comprising a second set of citation data, wherein the first and second sets of citation data respectively comprise overlapping citation data and citation format data; g. comparing, using the comparing module, the first citation to the second set of citation data; h. determining, using the citation matching module, a second set of possible matching citations from the second set of citation data; and i. formatting, using the reference management module, the first citation based on a selected citation from either the first or second set of possible matching citations. | 1. A computer based method for identifying, processing, and managing a set of citations in an electronic document, the method comprising: a. identifying, using an identifying module to process the electronic document, a first citation; b. determining, using a reference management module, the first citation is an unformatted citation; c. querying, using a query module, a first citation library stored in a first location, the first citation library comprising a first set of citation data; d. comparing, using a comparing module, the first citation to the first set of citation data; e. determining, using a citation matching module, a first set of possible matching citations from the first set of citation data; f. based on detecting a predetermined event, querying, using the query module, a second citation library stored in a second location, the second citation library comprising a second set of citation data, wherein the first and second sets of citation data respectively comprise overlapping citation data and citation format data; g. comparing, using the comparing module, the first citation to the second set of citation data; h. determining, using the citation matching module, a second set of possible matching citations from the second set of citation data; and i. formatting, using the reference management module, the first citation based on a selected citation from either the first or second set of possible matching citations. 9. The method of claim 1 further comprising presenting for selecting a citation from one or both of the first and second possible matching citations. | 0.823877 |
7,973,793 | 4 | 7 | 4. The scenario generating apparatus according to claim 1 , further comprising: an editing resource generator that generates editing resource information from the acquired external information, wherein the scenario editor edits the scenario generated by the scenario generator using at least one of the acquired external information and the editing resource information generated by the editing resource generator. | 4. The scenario generating apparatus according to claim 1 , further comprising: an editing resource generator that generates editing resource information from the acquired external information, wherein the scenario editor edits the scenario generated by the scenario generator using at least one of the acquired external information and the editing resource information generated by the editing resource generator. 7. The scenario generating apparatus according to claim 4 , further comprising: an editing resource generating knowledge storage that stores editing resource generating knowledge, comprising a combination of a type of the editing resource information, the external information to be used to generate the editing resource information and a generating rule for generating the editing resource information using the external information, wherein the editing resource generator generates editing resource information requested from the scenario editor with reference to the editing resource generating knowledge stored in the editing resource generating knowledge storage, and outputs the editing resource information to the scenario editor. | 0.647031 |
8,949,125 | 11 | 13 | 11. The method of claim 10 , wherein selecting one of the user spoken utterances comprises: generating the speech model for each received user spoken utterance of the plurality of user spoken utterances; and measuring a distance value between each of the generated speech models and every other generated speech model; wherein selecting one of the plurality of user spoken utterances is based on the measured distance values between the speech model for the selected user spoken utterance and every other generated speech model. | 11. The method of claim 10 , wherein selecting one of the user spoken utterances comprises: generating the speech model for each received user spoken utterance of the plurality of user spoken utterances; and measuring a distance value between each of the generated speech models and every other generated speech model; wherein selecting one of the plurality of user spoken utterances is based on the measured distance values between the speech model for the selected user spoken utterance and every other generated speech model. 13. The method of claim 11 , wherein the distance value is a minimum edit distance. | 0.538889 |
7,840,488 | 7 | 10 | 7. The method of claim 5 , wherein the prioritizing step further comprises: employing the usage cost in combination with a preference for the enforcement of the condition. | 7. The method of claim 5 , wherein the prioritizing step further comprises: employing the usage cost in combination with a preference for the enforcement of the condition. 10. The method of claim 7 , wherein the usage cost and the preference are initially set to default values. | 0.783673 |
9,002,887 | 21 | 23 | 21. A non-transitory computer-readable medium storing instructions for controlling a computing device to generate advertisement sets based on analysis of external referrals to a web site, the instructions when executed by a processing device causing the processing device to: collect information from an external source that is external to the computing device and that refers visitors of the referring source to the website, the information corresponding to referrals by the external source to visit the website, each referral comprising referral information corresponding to a request for additional content that is sent responsive to user interaction with content of the external source and that resulted in the visit to the website; for each referral, identify a referral type based at least in part upon a unique combination of a landing page type of the referral and one or more elements selected from a referring source identifier and a product identifier, the landing page type identifying a type of landing page that is displayed in response to user interaction with the referral; collect financial information relating to each visit referred by the external source; aggregate referral information for each referral type, the aggregated referral information including financial information for the referrals; and for at least one referral type, generate, based at least in part upon the aggregated referral information, an advertisement set for the referral type that includes a link corresponding to the landing page type of the referral type when the financial information for the referral type satisfies an advertisement criterion, the advertisement set having an associated link including a query string corresponding to the referral type; and submit the generated advertisement set for placement. | 21. A non-transitory computer-readable medium storing instructions for controlling a computing device to generate advertisement sets based on analysis of external referrals to a web site, the instructions when executed by a processing device causing the processing device to: collect information from an external source that is external to the computing device and that refers visitors of the referring source to the website, the information corresponding to referrals by the external source to visit the website, each referral comprising referral information corresponding to a request for additional content that is sent responsive to user interaction with content of the external source and that resulted in the visit to the website; for each referral, identify a referral type based at least in part upon a unique combination of a landing page type of the referral and one or more elements selected from a referring source identifier and a product identifier, the landing page type identifying a type of landing page that is displayed in response to user interaction with the referral; collect financial information relating to each visit referred by the external source; aggregate referral information for each referral type, the aggregated referral information including financial information for the referrals; and for at least one referral type, generate, based at least in part upon the aggregated referral information, an advertisement set for the referral type that includes a link corresponding to the landing page type of the referral type when the financial information for the referral type satisfies an advertisement criterion, the advertisement set having an associated link including a query string corresponding to the referral type; and submit the generated advertisement set for placement. 23. The non-transitory computer-readable medium of claim 21 wherein the advertisement criterion is based on an aggregated revenue threshold. | 0.583333 |
9,449,044 | 10 | 19 | 10. One or more non-transitory computer-readable storage media storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a command, the command comprising: a first name, a second name, and a dot operator, the dot operator being between the first name and the second name; detect a possible mistake in the second name; access a set of known identifiers, the set of known identifiers including expected identifiers; calculate a first numerical score for the known identifiers using a keyboard penalty matrix and based on the possible mistake detected in the second name and the known identifiers; calculate a second numerical score using frequencies of occurrence of the known identifiers and the calculated first numerical score; and select one or more expected identifiers for the second name, the selecting being based on the first numerical score and the second numerical score. | 10. One or more non-transitory computer-readable storage media storing instructions, the instructions comprising: one or more instructions that, when executed by one or more processors, cause the one or more processors to: receive a command, the command comprising: a first name, a second name, and a dot operator, the dot operator being between the first name and the second name; detect a possible mistake in the second name; access a set of known identifiers, the set of known identifiers including expected identifiers; calculate a first numerical score for the known identifiers using a keyboard penalty matrix and based on the possible mistake detected in the second name and the known identifiers; calculate a second numerical score using frequencies of occurrence of the known identifiers and the calculated first numerical score; and select one or more expected identifiers for the second name, the selecting being based on the first numerical score and the second numerical score. 19. The one or more computer-readable storage media of claim 10 , where the second name is located to the right of the first name on a command line or in a software code listing and the second name is within scope of the first name. | 0.5 |
7,761,448 | 1 | 7 | 1. A system for ranking search results, comprising a search engine on a computing device, the search engine configured to execute computer-executable instructions, which when executed by the computing system cause the computing system to perform a method comprising: discovering a plurality of documents on a network; recording document and link information for each of the plurality of documents on the network; generating a representation of the network from the document and link information, wherein the representation of the network includes a plurality of nodes, each document being represented by one of the plurality of nodes; receiving manually input click distances designating a subset of the plurality of nodes as highest authority nodes, the subset of the plurality of nodes including at least a first highest authority node and a second highest authority node, wherein the manually input click distances indicate a relative importance of each highest authority node with respect to other highest authority nodes; initializing click distances for a second subset of the plurality of nodes to a maximum value, the second subset of the plurality of nodes not including highest authority nodes and comprising at least a first non-highest authority node and a second non-highest authority node; computing click distances for the first and second non-highest authority nodes by: determining a first click distance for the first non-highest authority node, the first click distance being a first number of branches traversed on a first shortest path between the first non-highest authority node and the first highest authority node; determining a second click distance for the first non-highest authority node, the second click distance being a second number of branches traversed on a second shortest path between the first non-highest authority node and the second highest authority node; determining a third click distance for the second non-highest authority node, the third click distance being a third number of branches traversed on a third shortest path between the second non-highest authority node and the first highest authority node; and determining a fourth click distance for the second non-highest authority node, the fourth click distance being a fourth number of branches traversed on a fourth shortest path between the second non-highest authority node and the second highest authority node; storing the first, second, third, and fourth click distances in memory, such that the first and second click distances are associated with a first document, and the third and fourth click distances are associated with a second document; calculating search rank results using at least one of the first, second, third, and fourth click distances associated with each of the first and second documents as a query-independent relevance measure in ranking the plurality of documents; and storing search rank results in memory, wherein the search rank results comprise a list of documents arranged in a descending order of relevance. | 1. A system for ranking search results, comprising a search engine on a computing device, the search engine configured to execute computer-executable instructions, which when executed by the computing system cause the computing system to perform a method comprising: discovering a plurality of documents on a network; recording document and link information for each of the plurality of documents on the network; generating a representation of the network from the document and link information, wherein the representation of the network includes a plurality of nodes, each document being represented by one of the plurality of nodes; receiving manually input click distances designating a subset of the plurality of nodes as highest authority nodes, the subset of the plurality of nodes including at least a first highest authority node and a second highest authority node, wherein the manually input click distances indicate a relative importance of each highest authority node with respect to other highest authority nodes; initializing click distances for a second subset of the plurality of nodes to a maximum value, the second subset of the plurality of nodes not including highest authority nodes and comprising at least a first non-highest authority node and a second non-highest authority node; computing click distances for the first and second non-highest authority nodes by: determining a first click distance for the first non-highest authority node, the first click distance being a first number of branches traversed on a first shortest path between the first non-highest authority node and the first highest authority node; determining a second click distance for the first non-highest authority node, the second click distance being a second number of branches traversed on a second shortest path between the first non-highest authority node and the second highest authority node; determining a third click distance for the second non-highest authority node, the third click distance being a third number of branches traversed on a third shortest path between the second non-highest authority node and the first highest authority node; and determining a fourth click distance for the second non-highest authority node, the fourth click distance being a fourth number of branches traversed on a fourth shortest path between the second non-highest authority node and the second highest authority node; storing the first, second, third, and fourth click distances in memory, such that the first and second click distances are associated with a first document, and the third and fourth click distances are associated with a second document; calculating search rank results using at least one of the first, second, third, and fourth click distances associated with each of the first and second documents as a query-independent relevance measure in ranking the plurality of documents; and storing search rank results in memory, wherein the search rank results comprise a list of documents arranged in a descending order of relevance. 7. The system of claim 1 wherein calculating the search rank results further comprises ranking the first and second documents according to a scoring function (score) that is determined according to at least: the at least one of the click distances associated with each of the first and second documents (CD), a weight of a query-independent component (W cd ), a weight of the click distance (b cd ), a weight of a URL depth (b ud ), the URL depth (UD) and a click distance saturation constant (K cd ). | 0.657319 |
8,561,161 | 7 | 9 | 7. An apparatus for authenticating a user within a data processing system to enable the user to access a controlled resource, the apparatus comprising: a processor; a computer memory holding computer program instructions which when executed by the processor perform a method comprising: generating an authentication assertion for the user at a first trust proxy within a first domain; at a system in a second domain, receiving a request from a client to access a controlled resource within the second domain; sending the authentication assertion from the first domain to a second trust proxy in the second domain by the second trust proxy pulling the authentication assertion from the first trust proxy after receipt at the system in the second domain of the request for the controlled resource; validating the authentication assertion at the second trust proxy in the second domain; upon validating the authentication assertion, building a session for the user so that the user appears to the system in the second domain as an authenticated user; and providing access to the controlled resource using the session. | 7. An apparatus for authenticating a user within a data processing system to enable the user to access a controlled resource, the apparatus comprising: a processor; a computer memory holding computer program instructions which when executed by the processor perform a method comprising: generating an authentication assertion for the user at a first trust proxy within a first domain; at a system in a second domain, receiving a request from a client to access a controlled resource within the second domain; sending the authentication assertion from the first domain to a second trust proxy in the second domain by the second trust proxy pulling the authentication assertion from the first trust proxy after receipt at the system in the second domain of the request for the controlled resource; validating the authentication assertion at the second trust proxy in the second domain; upon validating the authentication assertion, building a session for the user so that the user appears to the system in the second domain as an authenticated user; and providing access to the controlled resource using the session. 9. The apparatus of claim 7 wherein the method further comprises: establishing a trust relationship between the first trust proxy and the second trust proxy. | 0.71558 |
8,930,359 | 11 | 12 | 11. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining, in response to a search one or more search indexes based on a query, a ranked set of search results that includes both (i) one or more particular web search results and (ii) one or more particular custom content search results, wherein the one or more particular web search results identify respective web resources that are indexed in the one or more search indices, and wherein the one or more particular custom content search results identify respective custom content resources in a collection of resources that are exposed to a search engine by an owner of the custom content resources and that are indexed in the one or more search indexes; identifying a presentation setting for presenting combined search results that include one or more web search results and one or more custom content search results, the presentation setting specifying how to visually distinguish the one or more web search results from the one or more custom content search results on a search results page, wherein the presentation setting is specified by the owner of the that exposed to the search engine the collection of resources that includes the one or more custom content resources that are identified by the one or more particular custom content search results; generating, based on the presentation setting for presenting combined search results that include one or more web search results and one or more custom content search results, a search results page that includes a subset of the ranked set of search results, the subset including one or more of the particular web search results and one or more of the particular custom content search results, including visually distinguishing the one or more web search results from the one or more custom content search results on the search results page according to the presentation setting; and providing the search results page for output in response to the query. | 11. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining, in response to a search one or more search indexes based on a query, a ranked set of search results that includes both (i) one or more particular web search results and (ii) one or more particular custom content search results, wherein the one or more particular web search results identify respective web resources that are indexed in the one or more search indices, and wherein the one or more particular custom content search results identify respective custom content resources in a collection of resources that are exposed to a search engine by an owner of the custom content resources and that are indexed in the one or more search indexes; identifying a presentation setting for presenting combined search results that include one or more web search results and one or more custom content search results, the presentation setting specifying how to visually distinguish the one or more web search results from the one or more custom content search results on a search results page, wherein the presentation setting is specified by the owner of the that exposed to the search engine the collection of resources that includes the one or more custom content resources that are identified by the one or more particular custom content search results; generating, based on the presentation setting for presenting combined search results that include one or more web search results and one or more custom content search results, a search results page that includes a subset of the ranked set of search results, the subset including one or more of the particular web search results and one or more of the particular custom content search results, including visually distinguishing the one or more web search results from the one or more custom content search results on the search results page according to the presentation setting; and providing the search results page for output in response to the query. 12. The computer program product of claim 11 , wherein the presentation setting specifies a visual format for presenting the one or more custom content search results on the search results page. | 0.84891 |
9,307,031 | 12 | 13 | 12. The method of claim 8 , wherein the extension header includes customized information that is passed in by the HTML5 application. | 12. The method of claim 8 , wherein the extension header includes customized information that is passed in by the HTML5 application. 13. The method of claim 12 , wherein the customized information is passed to the extension header as a last parameter of a method in said HTML5 application. | 0.5 |
9,575,994 | 1 | 8 | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. | 1. A method for data retrieval of a final result list, the method comprising: generating a semantic annotation database that maps text from a report that describe at least one image to at least one unique resource identifier (URI) that identifies structures illustrated in the at least one image by, analyzing the at least one image to detect structures, mapping the detected structures to a first URI of the at least one URI associated with similar structures stored in a knowledge database, storing the detected structures and the first URI as a first semantic annotation in the semantic annotation database, analyzing the report to identify a content of a text passage, mapping the identified content of the text passage to a second URI of the at least one URI to generate a mapped text passage, and storing a begin and an end of the mapped text passage and the second URI as a second semantic annotation in the semantic annotation database such that the first semantic annotation and the second semantic annotation are stored together in the semantic annotation database, generating an image feature database that stores features contained in the at least one image by, detecting a region of interest (ROI) in the at least one image that includes the detected structures, analyzing the ROI to compute at least one low-level feature therein, the at least one low-level feature being one of a gradient and histogram features of the ROI, and storing the at least one level feature with a reference to the at least one image and an index for fast retrieval in the image feature database; and searching for a resulting set of images by comparing both features of a reference image received by a user with at least one feature in the image feature database and textual search terms input by the user and the semantic annotation database by, receiving an input query describing a search to be executed, the input query containing both the reference image and the textual search terms input by the user, forming a first query based on the textual search terms contained in the input query and on additional anatomic information provided by the knowledge database, the additional anatomic information being an expanded list of synonyms associated with the textual search terms, generating a first result list providing search results of the first query based on the first semantic annotation and the second semantic annotation of the semantic annotation database, forming a second query based on the reference image contained in the input query and on at least one computed feature based on the input query, generating a second result list providing search results of the second query based on the at least one low-level feature in the image feature database, and aggregating the first result list and the second result list to form a final result list that provides reference to at least one of the at least one image and an image region of the at least one of the at least one image. 8. The method of claim 1 , wherein the storing of the identified text passage includes a storage of a reference information to the report that is stored in a report database. | 0.865741 |
8,131,540 | 1 | 9 | 1. A method in a computer system for performing a relationship search of a corpus of documents, each document having at least one sentence, comprising: receiving a relationship search query that designates a desired grammatical relationship between a first entity and at least one of a second entity or an action; transforming the search query into a Boolean expression; under control of the computer system, automatically determining a set of data objects that match the Boolean expression using a keyword-style search of a data structure that indexes terms of the documents in a memory of the computer system by including, for at least some of a plurality of terms, grammatical relationship information that specifies that the corresponding term is a subject, object, or modifier of another term, and including for at least one of the plurality of terms having the included grammatical relationship information, semantic information that specifies an entity type that identifies the term as a type of person, location, or thing; when the received relationship search query designates a desired grammatical relationship between the first entity and any action, returning an indication of a plurality of matching objects in the corpus that encompass the first entity along with an indication of the corresponding action encompassed by the matching objects; and otherwise, returning an indication of a plurality of matching objects in the corpus that encompass the desired grammatical relationship. | 1. A method in a computer system for performing a relationship search of a corpus of documents, each document having at least one sentence, comprising: receiving a relationship search query that designates a desired grammatical relationship between a first entity and at least one of a second entity or an action; transforming the search query into a Boolean expression; under control of the computer system, automatically determining a set of data objects that match the Boolean expression using a keyword-style search of a data structure that indexes terms of the documents in a memory of the computer system by including, for at least some of a plurality of terms, grammatical relationship information that specifies that the corresponding term is a subject, object, or modifier of another term, and including for at least one of the plurality of terms having the included grammatical relationship information, semantic information that specifies an entity type that identifies the term as a type of person, location, or thing; when the received relationship search query designates a desired grammatical relationship between the first entity and any action, returning an indication of a plurality of matching objects in the corpus that encompass the first entity along with an indication of the corresponding action encompassed by the matching objects; and otherwise, returning an indication of a plurality of matching objects in the corpus that encompass the desired grammatical relationship. 9. The method of claim 1 wherein the designated at least one second entity or the action indicates a desire to match any action and a desire to match any second entity. | 0.743119 |
9,618,919 | 1 | 24 | 1. A method of generating linear models for an aircraft engine system, the method comprising: determining, offline, a set of linear models for the aircraft engine system by linearization of a nonlinear model of the aircraft engine system at selected operating points or from desired data; analyzing, offline, accuracy of each linear model and eliminating inaccurate linear models therefrom to provide a residual set of the linear engine models; generating, offline, linear models corresponding to grid points of one or more rectangular lookup tables based on the residual set of the linear engine models; associating, offline, lookup table grid points or the residual set of the linear engine models with selected scheduling variables; and generating, offline, algorithmic software for the aircraft engine system therefrom such that the linear models for the aircraft engine system generated offline form a basis for online scheduling of linear models. | 1. A method of generating linear models for an aircraft engine system, the method comprising: determining, offline, a set of linear models for the aircraft engine system by linearization of a nonlinear model of the aircraft engine system at selected operating points or from desired data; analyzing, offline, accuracy of each linear model and eliminating inaccurate linear models therefrom to provide a residual set of the linear engine models; generating, offline, linear models corresponding to grid points of one or more rectangular lookup tables based on the residual set of the linear engine models; associating, offline, lookup table grid points or the residual set of the linear engine models with selected scheduling variables; and generating, offline, algorithmic software for the aircraft engine system therefrom such that the linear models for the aircraft engine system generated offline form a basis for online scheduling of linear models. 24. The method according to claim 1 , wherein the basis for online scheduling of linear models comprises interpolating using lookup tables for each element generated using a grid of linear models rendered rectangular with respect to a selected set of scheduling variables using element by element interpolation or a polytopic approach. | 0.593447 |
10,083,691 | 1 | 9 | 1. A computer-implemented system for transcription error reduction, comprising: a database to store a stream of audio data comprising utterances, wherein each utterance is assigned a transcribed value and a confidence score; and a server comprising a central processing unit, memory, an input port to receive the utterances, and an output port, wherein the central processing unit is configured to perform the following steps: identify those utterances with confidence scores that fall below a confidence threshold as questionable utterances; place at least one of the questionable utterances into a pool of related utterances also determined to be questionable; determine whether the pool satisfies a size threshold within a predetermined amount of time; obtain a sample of the questionable utterances in the pool when the pool satisfies the size threshold within the predetermined amount of time; and provide the sample of questionable utterances to at least one human transcriber for verification, wherein the steps reduce an amount of manual transcription required by a transcription system. | 1. A computer-implemented system for transcription error reduction, comprising: a database to store a stream of audio data comprising utterances, wherein each utterance is assigned a transcribed value and a confidence score; and a server comprising a central processing unit, memory, an input port to receive the utterances, and an output port, wherein the central processing unit is configured to perform the following steps: identify those utterances with confidence scores that fall below a confidence threshold as questionable utterances; place at least one of the questionable utterances into a pool of related utterances also determined to be questionable; determine whether the pool satisfies a size threshold within a predetermined amount of time; obtain a sample of the questionable utterances in the pool when the pool satisfies the size threshold within the predetermined amount of time; and provide the sample of questionable utterances to at least one human transcriber for verification, wherein the steps reduce an amount of manual transcription required by a transcription system. 9. A system according to claim 1 , wherein the central processing unit adjusts one or more of a size of the sample, the size threshold of the pool, and the predetermined time based on a type of the stream of the audio data and an accuracy of transcription required of the audio data. | 0.686947 |
4,145,570 | 1 | 3 | 1. A teleprinter system for Arabic-Farsi languages comprising: means for generating a succession of 5-bit codes each representing an Arabic character of the Arabic-Farsi language or one of a plurality of standard teleprinter characters including teleprinter numerals, punctuation, and command characters, without regard to the form of the Arabic characters; means for inserting one of at least three 5-bit codes into the succession of 5-bit character codes to identify at least one subsequent character code as being in one of at least three predetermined groups of characters associated with the inserted one of the three 5-bit codes; means for receiving and storing the 5-bit code for at least two successive characters; means responsive to the stored 5-bit codes for classifying each received character as one of a plurality of predetermined character types; means for generating a second code identifying each stored 5-bit code representing an Arabic character as one of four possible Arabic character forms in response to the classified type of the character immediately preceding and immediately following the first stored of the characters; means for displaying in its proper form and position each Arabic character represented by a stored 5-bit code in response to said second code and the stored 5-bit code, including means for displaying successive characters in the same position in response to an indication from the classifying means that a character to be displayed is of a character type for which the display position is not to change. | 1. A teleprinter system for Arabic-Farsi languages comprising: means for generating a succession of 5-bit codes each representing an Arabic character of the Arabic-Farsi language or one of a plurality of standard teleprinter characters including teleprinter numerals, punctuation, and command characters, without regard to the form of the Arabic characters; means for inserting one of at least three 5-bit codes into the succession of 5-bit character codes to identify at least one subsequent character code as being in one of at least three predetermined groups of characters associated with the inserted one of the three 5-bit codes; means for receiving and storing the 5-bit code for at least two successive characters; means responsive to the stored 5-bit codes for classifying each received character as one of a plurality of predetermined character types; means for generating a second code identifying each stored 5-bit code representing an Arabic character as one of four possible Arabic character forms in response to the classified type of the character immediately preceding and immediately following the first stored of the characters; means for displaying in its proper form and position each Arabic character represented by a stored 5-bit code in response to said second code and the stored 5-bit code, including means for displaying successive characters in the same position in response to an indication from the classifying means that a character to be displayed is of a character type for which the display position is not to change. 3. The teleprinter system of claim 1 wherein the six Arabic letters (with dots as shown in FIG. 9a) are coded as a 5-bit code specifying a dot followed by a 5-bit code specifying the corresponding one of the forms (without the dots as shown in FIG. 9b). | 0.786318 |
7,886,228 | 9 | 12 | 9. A computer-readable storage medium, having instructions stored therein, which when executed, cause a computer system to perform a method comprising: creating, in a display area of a screen of a device, a first set of reduced graphical representations that represent a plurality of digital media objects using one or more other sets of reduced graphical representations accessible using one or more other display areas of the screen, the one or more other display areas comprising a first display area, a second display area, and a third display area; associating audio with the first set of reduced graphical representations, such that the plurality of digital media objects and audio are capable of being played back subsequently; displaying in the first area, a first, second, and third track, the first track displaying images that are stored on the device, the second track displaying images of authored stories, each authored story including a sequence of digital media objects selected by an individual and having audio associated with at least one of the digital media objects in the sequence, the third track displaying one or more images associated with a story being authored on the device and having audio associated with at least one of the one or more images; displaying in the second area, a larger version of an image corresponding to a thumbnail image selected in any of the three tracks in the first area; and displaying in the third area, a representation of one or more audio clips associated with the image being displayed in the second area. | 9. A computer-readable storage medium, having instructions stored therein, which when executed, cause a computer system to perform a method comprising: creating, in a display area of a screen of a device, a first set of reduced graphical representations that represent a plurality of digital media objects using one or more other sets of reduced graphical representations accessible using one or more other display areas of the screen, the one or more other display areas comprising a first display area, a second display area, and a third display area; associating audio with the first set of reduced graphical representations, such that the plurality of digital media objects and audio are capable of being played back subsequently; displaying in the first area, a first, second, and third track, the first track displaying images that are stored on the device, the second track displaying images of authored stories, each authored story including a sequence of digital media objects selected by an individual and having audio associated with at least one of the digital media objects in the sequence, the third track displaying one or more images associated with a story being authored on the device and having audio associated with at least one of the one or more images; displaying in the second area, a larger version of an image corresponding to a thumbnail image selected in any of the three tracks in the first area; and displaying in the third area, a representation of one or more audio clips associated with the image being displayed in the second area. 12. The computer-readable storage medium of claim 9 , wherein the method further comprises displaying a list of a plurality of audio capable of being selected and associated with a digital media object. | 0.644366 |
6,161,092 | 25 | 42 | 25. A processor readable storage medium having processor readable code embodied on said processor readable storage medium, said processor readable code for programming a processor to perform a method comprising the steps of: receiving data for a set of traffic incidents, said data including a set of parameters; identifying groups of files that store speech for describing said incidents, each group of files is associated with at least one of said incidents, said step of identifying comprises the steps of: accessing a first parameter having a first value, accessing information directly correlating values of said first parameter to references to audio files, determining whether said information directly correlates said first value to a first reference to an audio file, identifying, as part of a first group of files, a first audio file if said information directly correlates said first value to said first reference to said first audio file, and identifying, as part of said first group of files, a second audio file if said information does not direct correlate said first value to any reference to an audio file; and automatically presenting said stored speech from each group of files. | 25. A processor readable storage medium having processor readable code embodied on said processor readable storage medium, said processor readable code for programming a processor to perform a method comprising the steps of: receiving data for a set of traffic incidents, said data including a set of parameters; identifying groups of files that store speech for describing said incidents, each group of files is associated with at least one of said incidents, said step of identifying comprises the steps of: accessing a first parameter having a first value, accessing information directly correlating values of said first parameter to references to audio files, determining whether said information directly correlates said first value to a first reference to an audio file, identifying, as part of a first group of files, a first audio file if said information directly correlates said first value to said first reference to said first audio file, and identifying, as part of said first group of files, a second audio file if said information does not direct correlate said first value to any reference to an audio file; and automatically presenting said stored speech from each group of files. 42. A method according to claim 25, wherein: said step of automatically presenting includes presenting an audio/visual program that includes said stored speech, said audio/visual program does not require user interaction during presentation. | 0.5 |
9,159,077 | 17 | 18 | 17. The apparatus of claim 15 wherein the scaling/weighting processor is configured to calculate a representative mean value for each descriptive attribute j, configured to calculate a standard deviation x j for each descriptive attribute j, configured to determine a difference between each original value x i,j and the representative mean value x j for each descriptive attribute j to form a corresponding set of intermediate values {dot over (x)} i,j for each descriptive attribute j, configured to divide each intermediate value {dot over (x)} i,j for each descriptive attribute j by the standard deviation σ j for the corresponding descriptive attribute j to form a corresponding set of scaled values {acute over (x)} i,j for each descriptive attribute j with the common base represented by zero mean and unity variance, and configured to form a covariance matrix Σ from the scaled values {acute over (x)} i,j for the plurality of descriptive attributes j. | 17. The apparatus of claim 15 wherein the scaling/weighting processor is configured to calculate a representative mean value for each descriptive attribute j, configured to calculate a standard deviation x j for each descriptive attribute j, configured to determine a difference between each original value x i,j and the representative mean value x j for each descriptive attribute j to form a corresponding set of intermediate values {dot over (x)} i,j for each descriptive attribute j, configured to divide each intermediate value {dot over (x)} i,j for each descriptive attribute j by the standard deviation σ j for the corresponding descriptive attribute j to form a corresponding set of scaled values {acute over (x)} i,j for each descriptive attribute j with the common base represented by zero mean and unity variance, and configured to form a covariance matrix Σ from the scaled values {acute over (x)} i,j for the plurality of descriptive attributes j. 18. The apparatus of claim 17 wherein: the scaling/weighting processor is configured to find the first scaling factor U j 1 for the first attribute j 1 from the covariance matrix Σ in relation to the first edge i 1 and associated with a first edge-attribute pair i 1 ,j 1 , configured to find the second scaling factor U j 2 for the second attribute j 2 from the covariance matrix Σ in relation to the first edge i 1 and associated with a second edge-attribute pair i 1 ,j 2 , configured to find the first weighting factor Λ j 1 for the first attribute j 1 from the covariance matrix Σ in relation to the first edge i 1 and associated with the first edge-attribute pair i 1 ,j 1 , and configured to find the second weighting factor Λ j 2 for the second attribute j 2 from the covariance matrix Σ in relation to the first edge i 1 and associated with the second edge-attribute pair i 1 ,j 2 ; and the composite tie metric processor is configured to multiply the original value x i 1 ,j 1 for the first edge-attribute pair i 1 ,j 1 by the first scaling factor U j 1 and the first weighting factor Λ j 1 to form a first tie attribute component S j 1 for the first edge configured to multiply the original value x i 1 ,j 2 for the second edge-attribute pair i 1 ,j 2 by the second scaling factor U j 2 and the second weighting factor Λ j 2 to form a second tie attribute component S j 2 for the first edge i 1 , and configured to sum the first tie attribute component S j 1 and the second tie attribute component S j 2 to obtain a normalized composite tie metric S i 1 for the first edge i 1 . | 0.5 |
8,787,819 | 22 | 23 | 22. The non-transitory computer readable storage medium of claim 16 , the method further comprising tracking user submissions. | 22. The non-transitory computer readable storage medium of claim 16 , the method further comprising tracking user submissions. 23. The non-transitory computer readable storage medium of claim 22 , wherein the user is evaluated based on the tracked user submissions. | 0.5 |
9,092,409 | 17 | 24 | 17. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: searching a data element for user generated text that includes one or more apparent textual geo-annotations associated with the data element and input by a user indicating a location of interest; searching the data element for geocode information specifying a geographic location of the data element; determining a location proximity of (i) a geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element; calculating a level-of-detail score for the data element based on the apparent geo-annotations in the user generated text and the location proximity of (i) the geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element, wherein the level-of-detail score is a score corresponding to a geographic level of detail associated with the data element; determining that the score exceeds a threshold level-of-detail score, and in response initiating modification of the map to include a reference to the data element, wherein the reference is placed on the map at a location corresponding to the data element; and storing the modified map including the reference to the data element in a memory device for subsequent presentation. | 17. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: searching a data element for user generated text that includes one or more apparent textual geo-annotations associated with the data element and input by a user indicating a location of interest; searching the data element for geocode information specifying a geographic location of the data element; determining a location proximity of (i) a geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element; calculating a level-of-detail score for the data element based on the apparent geo-annotations in the user generated text and the location proximity of (i) the geographic location for each of the one or more apparent geo-annotations to (ii) the geographic location of the geocode information of the data element, wherein the level-of-detail score is a score corresponding to a geographic level of detail associated with the data element; determining that the score exceeds a threshold level-of-detail score, and in response initiating modification of the map to include a reference to the data element, wherein the reference is placed on the map at a location corresponding to the data element; and storing the modified map including the reference to the data element in a memory device for subsequent presentation. 24. The non-transitory computer readable storage medium of claim 17 , calculating the level-of-detail score is based as a function of at least one of: mentions of a place name; a number of page views; a user-provided rating; a black list of locations; a white list of locations; a number of user comments; a number of characters in a title or description; and a date when content of the data element was uploaded. | 0.5 |
8,224,826 | 14 | 15 | 14. The system of claim 13 , wherein each of the digital signatures associated with the digital content items of the first group further includes a respective assertion made by the first agent that specifies a role of the first agent with respect to the associated digital content item of the first group, and wherein the reputation score for the first agent is further a function of the assertions. | 14. The system of claim 13 , wherein each of the digital signatures associated with the digital content items of the first group further includes a respective assertion made by the first agent that specifies a role of the first agent with respect to the associated digital content item of the first group, and wherein the reputation score for the first agent is further a function of the assertions. 15. The system of claim 14 , wherein the role is selected from the group consisting of author, editor, publisher, and reviewer. | 0.5 |
8,825,821 | 1 | 9 | 1. A computer-based method for selection of a runtime stack for deployment of a Web Service, comprising: generating, at a computer server, policy assertions for a Web Service to be deployed; providing, at a computer server, a scoring mechanism dynamically unique for each available runtime stack in which the ability of a stack to support each of a plurality of policy assertions is scored with a numerical value; applying, at a computer server, the scoring mechanism dynamically unique for each available runtime stack to the policy assertions for the Web Service to be deployed; and selecting, at a computer server, a stack based on the results of applying the dynamically unique scoring mechanism for each available runtime stack. | 1. A computer-based method for selection of a runtime stack for deployment of a Web Service, comprising: generating, at a computer server, policy assertions for a Web Service to be deployed; providing, at a computer server, a scoring mechanism dynamically unique for each available runtime stack in which the ability of a stack to support each of a plurality of policy assertions is scored with a numerical value; applying, at a computer server, the scoring mechanism dynamically unique for each available runtime stack to the policy assertions for the Web Service to be deployed; and selecting, at a computer server, a stack based on the results of applying the dynamically unique scoring mechanism for each available runtime stack. 9. The method of claim 1 , wherein the scoring mechanism gives a positive value if a policy assertion is supported and a negative value if a policy assertion is not supported by a stack. | 0.655556 |
8,482,529 | 10 | 15 | 10. An input method used in a computer input system with a storage unit, the input method comprising: storing a symbol permutation order, four carry radices and a phonetic database in the storage unit, wherein the phonetic database records multiple character pronunciations and a coding number corresponding to each of the character pronunciations, each of the coding numbers is generated by applying a mathematical operation on four symbol representative numbers representing the character pronunciation, the symbol permutation order and the four carry radices, the four carry radices have a one-to-one correspondence to an amount of initial consonants, an amount of head vowels, an amount of vowels and an amount of tones of the phonetic notation symbol and each of the four carry radices is a positive integer, and the character pronunciations are stored in the phonetic database according to the corresponding coding numbers; receiving an input of at least a phonetic notation; obtaining four input symbol representative numbers representing the phonetic notation; calculating a number according to the four carry radices, the symbol permutation order and the four input symbol representative numbers; obtaining at least a Chinese character corresponding to the character pronunciation corresponding to the coding number in accordance with the number as at least a candidate character; and selecting one of the candidate characters as an input character according to a selecting command. | 10. An input method used in a computer input system with a storage unit, the input method comprising: storing a symbol permutation order, four carry radices and a phonetic database in the storage unit, wherein the phonetic database records multiple character pronunciations and a coding number corresponding to each of the character pronunciations, each of the coding numbers is generated by applying a mathematical operation on four symbol representative numbers representing the character pronunciation, the symbol permutation order and the four carry radices, the four carry radices have a one-to-one correspondence to an amount of initial consonants, an amount of head vowels, an amount of vowels and an amount of tones of the phonetic notation symbol and each of the four carry radices is a positive integer, and the character pronunciations are stored in the phonetic database according to the corresponding coding numbers; receiving an input of at least a phonetic notation; obtaining four input symbol representative numbers representing the phonetic notation; calculating a number according to the four carry radices, the symbol permutation order and the four input symbol representative numbers; obtaining at least a Chinese character corresponding to the character pronunciation corresponding to the coding number in accordance with the number as at least a candidate character; and selecting one of the candidate characters as an input character according to a selecting command. 15. The input method according to claim 10 , wherein the step of calculating the numbers according to the four carry radices, the symbol permutation order and the four input symbol representative numbers comprises: arranging the four input symbol representative numbers according to the symbol permutation order; defining a carry sequence of the four carry radices according to the symbol permutation order and the relations between the four carry radices and the amount of the initial consonants, the amount of the head vowels, the amount of the vowels and the amount of the tones; converting the arranged four input symbol representative numbers to a decimal number according to the four carry radices and the carry sequence; and taking the decimal number as the number. | 0.5 |
9,201,876 | 1 | 9 | 1. A computer implemented method of determining a co-occurrence relationship between words in a corpus of word groupings, comprising: identifying a plurality of word pairs from a vocabulary of words; determining, utilizing one or more processors, a co-occurrence probability for each of the word pairs in a corpus having a plurality of word groupings, each of the co-occurrence probability is based on the probability of co-occurrence of a single of the word pairs in a single of the word groupings; wherein determining the co-occurrence probability for a word pair of the word pairs comprises determining a weighted count of the word groupings in which the word pair is present, wherein a word grouping of the word groupings in which the word pair is present is from a document, and wherein the weight of the contribution of the word grouping to the weighted count is based on at least two of frequency of occurrence, field weighting, and decorations of both words of the word pair in the document; determining, utilizing one or more processors, a co-occurrence consistency for each of the word pairs by comparing the co-occurrence probability for each of the word pairs to an incidental occurrence probability for each of the word pairs, the incidental occurrence probability for each of the word pairs being specific to a respective of the word pairs; creating a co-occurrence consistency matrix with the co-occurrence consistency for each of the word pairs; receiving, by a search engine, a query submitted to the search engine by a user, the query including a word grouping having a plurality of word grouping words; identifying, by the search engine and based on the co-occurrence consistency matrix, the co-occurrence consistency for each of a plurality of the word pairs in the word grouping words; performing, by the search engine, a link analysis on the word grouping words utilizing the identified co-occurrence consistencies for the plurality of the word pairs in the word grouping words as weighting factors in the link analysis; assigning, by the search engine, a contextual weight to each of a plurality of the word grouping words based on the link analysis; and providing, by the search engine and based on the assigned contextual weights, results to the query submitted to the search engine by the user. | 1. A computer implemented method of determining a co-occurrence relationship between words in a corpus of word groupings, comprising: identifying a plurality of word pairs from a vocabulary of words; determining, utilizing one or more processors, a co-occurrence probability for each of the word pairs in a corpus having a plurality of word groupings, each of the co-occurrence probability is based on the probability of co-occurrence of a single of the word pairs in a single of the word groupings; wherein determining the co-occurrence probability for a word pair of the word pairs comprises determining a weighted count of the word groupings in which the word pair is present, wherein a word grouping of the word groupings in which the word pair is present is from a document, and wherein the weight of the contribution of the word grouping to the weighted count is based on at least two of frequency of occurrence, field weighting, and decorations of both words of the word pair in the document; determining, utilizing one or more processors, a co-occurrence consistency for each of the word pairs by comparing the co-occurrence probability for each of the word pairs to an incidental occurrence probability for each of the word pairs, the incidental occurrence probability for each of the word pairs being specific to a respective of the word pairs; creating a co-occurrence consistency matrix with the co-occurrence consistency for each of the word pairs; receiving, by a search engine, a query submitted to the search engine by a user, the query including a word grouping having a plurality of word grouping words; identifying, by the search engine and based on the co-occurrence consistency matrix, the co-occurrence consistency for each of a plurality of the word pairs in the word grouping words; performing, by the search engine, a link analysis on the word grouping words utilizing the identified co-occurrence consistencies for the plurality of the word pairs in the word grouping words as weighting factors in the link analysis; assigning, by the search engine, a contextual weight to each of a plurality of the word grouping words based on the link analysis; and providing, by the search engine and based on the assigned contextual weights, results to the query submitted to the search engine by the user. 9. The method of claim 1 , wherein the word groupings include at least one of tags for images, tags for videos, ad keywords, words from queries, words from documents, and words from social networking posts. | 0.599222 |
8,370,130 | 1 | 5 | 1. A pattern database building apparatus, comprising: a sentence analysis unit for segmenting an input corpus into example sentences with reference to a phrase dictionary and performing morpheme analysis and syntax analysis on the segmented example sentences; a hierarchy describing unit for describing hierarchy of the example sentences based on results of the morpheme analysis and the syntax analysis; a class transformation unit for performing class transformation on the example sentences, whose hierarchy has been described, with reference to a thesaurus/ontology and a classification rule dictionary; and a semantic representation pattern determination unit for marking optional expressions for the example sentences that have undergone the class transformation, deleting meaningless expressions and additional information, converting the example sentences into their base form, deleting morphemic tags or symbols to determine a semantic representation pattern of the example sentences, and storing the determined semantic representation pattern in a database. | 1. A pattern database building apparatus, comprising: a sentence analysis unit for segmenting an input corpus into example sentences with reference to a phrase dictionary and performing morpheme analysis and syntax analysis on the segmented example sentences; a hierarchy describing unit for describing hierarchy of the example sentences based on results of the morpheme analysis and the syntax analysis; a class transformation unit for performing class transformation on the example sentences, whose hierarchy has been described, with reference to a thesaurus/ontology and a classification rule dictionary; and a semantic representation pattern determination unit for marking optional expressions for the example sentences that have undergone the class transformation, deleting meaningless expressions and additional information, converting the example sentences into their base form, deleting morphemic tags or symbols to determine a semantic representation pattern of the example sentences, and storing the determined semantic representation pattern in a database. 5. The pattern database building apparatus of claim 1 , wherein the additional information includes at least one of aspect, modality, tense, and sentence pattern. | 0.776243 |
7,764,202 | 8 | 9 | 8. A computer readable medium including instructions that, when executed by a processing system, cause the processing system to perform a method comprising: receiving an input stream of characters; parsing the input stream into a plurality of strings each of which include one or more of the characters, wherein each parsed string is a longest match to a string entry in a data structure; and transforming the input stream into an output stream that includes a first portion having literal values of the characters and a separate and distinct second portion having index values corresponding to string entries in the data structure that match parsed strings from the input stream. | 8. A computer readable medium including instructions that, when executed by a processing system, cause the processing system to perform a method comprising: receiving an input stream of characters; parsing the input stream into a plurality of strings each of which include one or more of the characters, wherein each parsed string is a longest match to a string entry in a data structure; and transforming the input stream into an output stream that includes a first portion having literal values of the characters and a separate and distinct second portion having index values corresponding to string entries in the data structure that match parsed strings from the input stream. 9. The computer readable medium of claim 8 , wherein the output stream is divided into a first output stream that includes the first portion and a second output stream that includes the second portion. | 0.759569 |
9,224,149 | 22 | 27 | 22. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining identity information, with a portable program module, for a source of a webpage associated with a container document, the portable program module located in the container document; submitting, by the portable program module located in the container document, the identity information to a concept server storing keywords associated with the container document; receiving, by the portable program module located on the container document and from the concept server, in response to the submitted identity information, the keywords associated with the container document; selecting, by the portable program module located in the container document, a subset of the keywords received from the concept server based at least on one or more criteria specified by an author of the portable program module; submitting, by the portable program module located in the container document, a query to an item search server related to the subset of the keywords selected by the portable program module; and receiving, at the portable program module located in the container document, advertisements responsive to the query from the item search server for display. | 22. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: obtaining identity information, with a portable program module, for a source of a webpage associated with a container document, the portable program module located in the container document; submitting, by the portable program module located in the container document, the identity information to a concept server storing keywords associated with the container document; receiving, by the portable program module located on the container document and from the concept server, in response to the submitted identity information, the keywords associated with the container document; selecting, by the portable program module located in the container document, a subset of the keywords received from the concept server based at least on one or more criteria specified by an author of the portable program module; submitting, by the portable program module located in the container document, a query to an item search server related to the subset of the keywords selected by the portable program module; and receiving, at the portable program module located in the container document, advertisements responsive to the query from the item search server for display. 27. The medium of claim 22 , wherein the operations further comprise formatting the advertisements for the display. | 0.694149 |
9,967,228 | 11 | 14 | 11. An electronic device comprising: a sensor for generating time-variant data indicative of an environmental condition; a processor; and a memory comprising instructions for causing the processor to encode the time-variant data indicative of the environmental condition using a message format, the message format comprising: one or more resources fields that each identifies a resource to be imported into the time-variant data; one or more records that represent data samples comprising the time-variant data being exchanged in the message; a descriptor field corresponding to at least one respective record of the one or more records and containing metadata describing the time-variant data contained within the at least one record; and a description field having a human-readable string to describe from where the time-variant data samples are derived. | 11. An electronic device comprising: a sensor for generating time-variant data indicative of an environmental condition; a processor; and a memory comprising instructions for causing the processor to encode the time-variant data indicative of the environmental condition using a message format, the message format comprising: one or more resources fields that each identifies a resource to be imported into the time-variant data; one or more records that represent data samples comprising the time-variant data being exchanged in the message; a descriptor field corresponding to at least one respective record of the one or more records and containing metadata describing the time-variant data contained within the at least one record; and a description field having a human-readable string to describe from where the time-variant data samples are derived. 14. The electronic device of claim 11 , wherein the descriptor field includes a stream periodicity indicator that indicates whether the time-variant data in a stream is periodic or aperiodic using a flag, wherein when the flag is positive, the flag indicates that the stream is periodic, and when the flag is negative, the flag indicates that the stream is aperiodic having irregular intervals of time between samples in the stream. | 0.518931 |
9,646,247 | 1 | 2 | 1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: in response to receiving an input question, identify a set of temporal characteristics for a set of candidate answers for the input question; associate an initial confidence score with each candidate answer of the set of candidate answers; refine each initial confidence score associated with each candidate answer in the set of initial candidate answers based on the set of temporal characteristics, wherein each confidence score associated with each candidate answer is refined based on the set of temporal characteristics using a reference time of the input question and a respective reference time associated with the candidate answer thereby forming a temporally refined confidence score associated with the candidate answer, wherein the temporally refined confidence score associated with the candidate answer is identified by: generating a distance value in terms of years for the respective reference time associated with the candidate answer and the reference time of the input question; determining a multiplier value with which to weight the confidence score associated with the candidate answer using the distance value using multiplier function: Multiplier value=1/(2*distance value+0.5); determining a sentiment value of the candidate answer to weight the determined multiplier value; and determining a final weight value for the temporally refined confidence score associated with the candidate answer using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer; and provide a set of candidate answers with the temporally refined confidence scores to the user. | 1. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: in response to receiving an input question, identify a set of temporal characteristics for a set of candidate answers for the input question; associate an initial confidence score with each candidate answer of the set of candidate answers; refine each initial confidence score associated with each candidate answer in the set of initial candidate answers based on the set of temporal characteristics, wherein each confidence score associated with each candidate answer is refined based on the set of temporal characteristics using a reference time of the input question and a respective reference time associated with the candidate answer thereby forming a temporally refined confidence score associated with the candidate answer, wherein the temporally refined confidence score associated with the candidate answer is identified by: generating a distance value in terms of years for the respective reference time associated with the candidate answer and the reference time of the input question; determining a multiplier value with which to weight the confidence score associated with the candidate answer using the distance value using multiplier function: Multiplier value=1/(2*distance value+0.5); determining a sentiment value of the candidate answer to weight the determined multiplier value; and determining a final weight value for the temporally refined confidence score associated with the candidate answer using the multiplier value, the sentiment value, and the initial confidence score associated with the initial candidate answer; and provide a set of candidate answers with the temporally refined confidence scores to the user. 2. The computer program product of claim 1 , wherein the final weight value is determined using a distance function:
Final Weight=Initial confidence score*Multiplier Value*Sentiment Value. | 0.5 |
9,411,710 | 7 | 10 | 7. A system for testing a computer application, the system comprising: a test script repository including computer readable storage medium having stored thereon computer executable test scripts; and a test server coupled to the test script repository, the test server including a processor executing instructions for testing the computer application, the instructions including: identifying components of a version of the application, said components including one or more components that are one of new and modified, wherein each of the one or more components corresponds to a keyword; generating a keyword matrix of the identified application components, the keyword matrix having a set of all identified application components as a first dimension and a set of the one or more components that are one of new and modified as a second dimension, wherein the keyword matrix comprises the keywords; performing a search in the test script repository with respect to components listed as at least one of the first and second dimensions, said test script repository including test scripts referencing at least some of the identified components, and determining a result of the search; populating the keyword matrix with test case identification numbers in the search result, the test case identification numbers corresponding to test scripts that refer to the at least some of the identified components of the application; and based on the populated keyword matrix, identifying one or more of (a) gaps in test case coverage for the version of the application, and (b) one or more test cases covering the version of the application. | 7. A system for testing a computer application, the system comprising: a test script repository including computer readable storage medium having stored thereon computer executable test scripts; and a test server coupled to the test script repository, the test server including a processor executing instructions for testing the computer application, the instructions including: identifying components of a version of the application, said components including one or more components that are one of new and modified, wherein each of the one or more components corresponds to a keyword; generating a keyword matrix of the identified application components, the keyword matrix having a set of all identified application components as a first dimension and a set of the one or more components that are one of new and modified as a second dimension, wherein the keyword matrix comprises the keywords; performing a search in the test script repository with respect to components listed as at least one of the first and second dimensions, said test script repository including test scripts referencing at least some of the identified components, and determining a result of the search; populating the keyword matrix with test case identification numbers in the search result, the test case identification numbers corresponding to test scripts that refer to the at least some of the identified components of the application; and based on the populated keyword matrix, identifying one or more of (a) gaps in test case coverage for the version of the application, and (b) one or more test cases covering the version of the application. 10. The system of claim 7 wherein each test script comprises a keyword table including a set of the at least some of the identified components of the application. | 0.544944 |
9,063,926 | 2 | 8 | 2. The method of claim 1 , further comprising parsing based on the type of the entity. | 2. The method of claim 1 , further comprising parsing based on the type of the entity. 8. The method of claim 2 , wherein parsing further comprises parsing based on the type of the entity and optionally auxiliary information. | 0.5 |
8,751,243 | 14 | 15 | 14. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine to transmit a notification of context change requiring update of a database of a user terminal, wherein the database stores a plurality of phrases corresponding to a particular language and the update includes one or more phrases, corresponding to one or more of the plurality of phrases, to be added to the database based at least upon a present or anticipated context, and receive the update to the database in response to the notification, wherein one or more of the one or more phrases comprise a string of words, wherein the update further includes at least one phrase to be added to the database that is based, at least in part, on a detected environmental condition, and wherein the update further specifies removal of one or more phrases corresponding to the particular language that is determined to be irrelevant based, at least in part, on the context change. | 14. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine to transmit a notification of context change requiring update of a database of a user terminal, wherein the database stores a plurality of phrases corresponding to a particular language and the update includes one or more phrases, corresponding to one or more of the plurality of phrases, to be added to the database based at least upon a present or anticipated context, and receive the update to the database in response to the notification, wherein one or more of the one or more phrases comprise a string of words, wherein the update further includes at least one phrase to be added to the database that is based, at least in part, on a detected environmental condition, and wherein the update further specifies removal of one or more phrases corresponding to the particular language that is determined to be irrelevant based, at least in part, on the context change. 15. An apparatus of claim 14 , wherein the apparatus is further caused to: detect whether stored phrases corresponding to the particular language cover the present or anticipated context of the user terminal. | 0.5 |
7,720,827 | 23 | 25 | 23. A method for mapping changes to network models in a meta-data library comprising: receiving at least one or more changes associated with one or more telecommunication models; linking one or more portions of one or more stored telecommunication models to the received changes; generating one or more maps of the linked portions; generating one or more transformation models using one or more of the generated maps; and forwarding the one or more transformation models to a mediation unit to enable the generation of one or more normalized models. | 23. A method for mapping changes to network models in a meta-data library comprising: receiving at least one or more changes associated with one or more telecommunication models; linking one or more portions of one or more stored telecommunication models to the received changes; generating one or more maps of the linked portions; generating one or more transformation models using one or more of the generated maps; and forwarding the one or more transformation models to a mediation unit to enable the generation of one or more normalized models. 25. The method as in claim 23 further operable to link the portions on a portion-by-portion basis. | 0.821818 |
8,644,755 | 10 | 11 | 10. Software for managing offline presentation of electronic learning materials, the software comprising computer readable instructions embodied on tangible media and operable when executed to: generate electronic learning materials for offline presentation, wherein the electronic learning materials include a plurality of knowledge items; assign the plurality of knowledge items to a plurality of identification strings, wherein each of the plurality of knowledge items is mapped to a different identification string in the plurality of identification strings; store the assignment between the plurality of knowledge items to the plurality of identification strings; transmit to a learner device the generated electronic learning materials and the plurality of identification strings, wherein the plurality of identification strings are presented to the learner during offline presentation in connection with completion of assigned knowledge items; receive, from a user device different from the learner device, an identification string from the plurality of identification strings, wherein the identification string is presented to the learner during the offline presentation of in connection with completion of an assigned knowledge item in the generated electronic learning materials, and the learner transmits the identification string using the user device different from the learner device; and determine progress of the learner with respect to the generated electronic learning materials based on comparing the received identification string to the stored assignment of identification strings. | 10. Software for managing offline presentation of electronic learning materials, the software comprising computer readable instructions embodied on tangible media and operable when executed to: generate electronic learning materials for offline presentation, wherein the electronic learning materials include a plurality of knowledge items; assign the plurality of knowledge items to a plurality of identification strings, wherein each of the plurality of knowledge items is mapped to a different identification string in the plurality of identification strings; store the assignment between the plurality of knowledge items to the plurality of identification strings; transmit to a learner device the generated electronic learning materials and the plurality of identification strings, wherein the plurality of identification strings are presented to the learner during offline presentation in connection with completion of assigned knowledge items; receive, from a user device different from the learner device, an identification string from the plurality of identification strings, wherein the identification string is presented to the learner during the offline presentation of in connection with completion of an assigned knowledge item in the generated electronic learning materials, and the learner transmits the identification string using the user device different from the learner device; and determine progress of the learner with respect to the generated electronic learning materials based on comparing the received identification string to the stored assignment of identification strings. 11. The software of claim 10 further operable to identifying a listing of words, wherein assigning the plurality of identification strings includes selecting at least one word from the listing of words. | 0.795547 |
8,396,586 | 35 | 36 | 35. The method of claim 34 , wherein the at least one criterion comprises a document being a no call bill. | 35. The method of claim 34 , wherein the at least one criterion comprises a document being a no call bill. 36. The method of claim 35 , wherein the at least one criterion comprises a document being a suspect bill. | 0.5 |
9,779,080 | 1 | 4 | 1. A method for text auto-correction, the method comprising: receiving an input text string on an electronic text input interface device, the input text string comprising N words and a categorical topic; generating a subsequent text string comprising a plurality of N−1 subsequent words forming a subsequent phrase within the categorical topic by determining probabilities that the N−1 subsequent words follow the N words in the input test string; generating a preceding text string comprising a plurality of N−1 preceding words forming a preceding phrase for the input text string within the categorical topic by determining probabilities that the N−1 preceding words following precede the N words in the input test string; creating a corrected text string by inserting the preceding phrase before the input text string and appending the subsequent phrase after the input text string; and displaying the corrected text string on the electronic text input interface device. | 1. A method for text auto-correction, the method comprising: receiving an input text string on an electronic text input interface device, the input text string comprising N words and a categorical topic; generating a subsequent text string comprising a plurality of N−1 subsequent words forming a subsequent phrase within the categorical topic by determining probabilities that the N−1 subsequent words follow the N words in the input test string; generating a preceding text string comprising a plurality of N−1 preceding words forming a preceding phrase for the input text string within the categorical topic by determining probabilities that the N−1 preceding words following precede the N words in the input test string; creating a corrected text string by inserting the preceding phrase before the input text string and appending the subsequent phrase after the input text string; and displaying the corrected text string on the electronic text input interface device. 4. The method of claim 1 , wherein: the step of receiving the input text string comprises: receiving the N words comprising a first language; and translating the N words to a second language; and the steps of generating the subsequent text string and the preceding text string further comprise generating a subsequent text string comprising a plurality of N−1 subsequent words in the second language forming a subsequent phrase and generating a preceding text string comprising a plurality of N−1 preceding words in the second language forming a preceding phrase. | 0.5 |
8,332,382 | 23 | 27 | 23. A non-transitory computer-readable medium containing instructions executable by one or more processors, the instructions comprising: one or more instructions that, when executed by the one or more processors, cause the one or more processors to: receive a search query; obtain, for the search query, articles and respective scores; identify, using one or more processors, for an article, a source with which the score is associated; determine, using one or more processors, a score for the source, the score being based on polling one or more users to request the one or more users to provide a metric that represents an evaluation of a source and based on a length of time between an occurrence of an event and publication, by the source, of another article associated with the event; and adjust, using one or more processors, the score of the article based on the score for the source. | 23. A non-transitory computer-readable medium containing instructions executable by one or more processors, the instructions comprising: one or more instructions that, when executed by the one or more processors, cause the one or more processors to: receive a search query; obtain, for the search query, articles and respective scores; identify, using one or more processors, for an article, a source with which the score is associated; determine, using one or more processors, a score for the source, the score being based on polling one or more users to request the one or more users to provide a metric that represents an evaluation of a source and based on a length of time between an occurrence of an event and publication, by the source, of another article associated with the event; and adjust, using one or more processors, the score of the article based on the score for the source. 27. The computer-readable medium of claim 23 , where the score for the source is further based on a number of entities, associated with the source, that are associated with only one article in a cluster of related articles. | 0.756018 |
6,151,604 | 26 | 27 | 26. The system of claim 25 further including querying means, said querying means further including: means for locating said index record according to the query of a user; means for retrieving at least one logical cell in said table pointed to by said located index record. | 26. The system of claim 25 further including querying means, said querying means further including: means for locating said index record according to the query of a user; means for retrieving at least one logical cell in said table pointed to by said located index record. 27. The system of claim 26 wherein said index locating means includes means for locating said index record pointed to by said at least one retrieved logical cell. | 0.5 |
8,041,738 | 12 | 14 | 12. The system of claim 9 , wherein the strongly typed variable comprises a people type variable that associates the tag with a person or group of people, wherein the tag is configured to be used to provide at least one or more of email functionality or instant messaging functionality, and wherein the people type variable associates the tag with the person or group of people by associating the unique ID with the tag. | 12. The system of claim 9 , wherein the strongly typed variable comprises a people type variable that associates the tag with a person or group of people, wherein the tag is configured to be used to provide at least one or more of email functionality or instant messaging functionality, and wherein the people type variable associates the tag with the person or group of people by associating the unique ID with the tag. 14. The system of claim 12 , wherein the unique ID comprises an email address. | 0.541176 |
8,732,758 | 1 | 11 | 1. A method for recommending television programming to a user, comprising: monitoring, using a processor within user television equipment, which television programming is being viewed by the user; automatically identifying, using the processor, a currently viewed program based on the monitoring, wherein the currently viewed program has a plurality of program attributes each included within a respective attribute category; determining that a user has selected an attribute category of actor as a criterion for recommending programs; automatically identifying an actor who performs in the currently viewed program responsive to determining that the user has selected the attribute category of actor as a criterion for recommending programs; and recommending using the processor, another program having an actor that matches the identified actor of the currently viewed program. | 1. A method for recommending television programming to a user, comprising: monitoring, using a processor within user television equipment, which television programming is being viewed by the user; automatically identifying, using the processor, a currently viewed program based on the monitoring, wherein the currently viewed program has a plurality of program attributes each included within a respective attribute category; determining that a user has selected an attribute category of actor as a criterion for recommending programs; automatically identifying an actor who performs in the currently viewed program responsive to determining that the user has selected the attribute category of actor as a criterion for recommending programs; and recommending using the processor, another program having an actor that matches the identified actor of the currently viewed program. 11. The method of claim 1 further comprising: receiving an indication from the user, using an input device at the user television equipment, to change channels from a current channel in a given direction; and in response to the indication to change channels, tuning to an adjacent channel nearest the current channel in the given direction that is associated with the identified program using an adaptive flip feature. | 0.5 |
4,389,706 | 47 | 48 | 47. An industrial system or the like comprising: apparatus for implementing system operations; sensor means associated with the apparatus for generating signals indicative of the state of the system; a digital computer system having a memory; signal scanning means associated with said computer system and connecting to said sensor means for scanning said sensor signals periodically and including means for transferring a digital record of the status of the signals into the memory of said digital computer system; at least one machine readable signal-related event definition defining as an event either the periodic scanning or a particular change in the state of at least one sensor signal, including a designation which serves as a name for the event and also as a name for the signal, and including a reference to the location in said memory where the status record of the corresponding signal variable is stored; at least one machine readable job definition including at least one triggering reference to a designation which serves as a name for an event and for a signal and which is at least one event definition; loader means for operating said computer system to accept said event and job definitions and to store said definitions in said memory; trigger-connect means for operating said computer system to link job definitions but only those containing trigger references to designations, to locations in said memory that are in turn linked to the event definition and status data for the designated signals; means for operating said computer system to respond to the occurrence of a signal-related event by initiating execution of any and all job definitions which are linked to the status data and definition corresponding to that event; at least one job definition which contains a reference to a computer-system variable by designation which variable and which designation are not otherwise defined elsewhere within the computer system; and means for operating the computer system in response to the acceptance of said definition to assign a memory storage location to the variable so that a record of the variable status may be maintained in the memory to record the variable designation together with the storage location address, and to supply the storage space address to all other definitions which refer to the same variable by using the same designation. | 47. An industrial system or the like comprising: apparatus for implementing system operations; sensor means associated with the apparatus for generating signals indicative of the state of the system; a digital computer system having a memory; signal scanning means associated with said computer system and connecting to said sensor means for scanning said sensor signals periodically and including means for transferring a digital record of the status of the signals into the memory of said digital computer system; at least one machine readable signal-related event definition defining as an event either the periodic scanning or a particular change in the state of at least one sensor signal, including a designation which serves as a name for the event and also as a name for the signal, and including a reference to the location in said memory where the status record of the corresponding signal variable is stored; at least one machine readable job definition including at least one triggering reference to a designation which serves as a name for an event and for a signal and which is at least one event definition; loader means for operating said computer system to accept said event and job definitions and to store said definitions in said memory; trigger-connect means for operating said computer system to link job definitions but only those containing trigger references to designations, to locations in said memory that are in turn linked to the event definition and status data for the designated signals; means for operating said computer system to respond to the occurrence of a signal-related event by initiating execution of any and all job definitions which are linked to the status data and definition corresponding to that event; at least one job definition which contains a reference to a computer-system variable by designation which variable and which designation are not otherwise defined elsewhere within the computer system; and means for operating the computer system in response to the acceptance of said definition to assign a memory storage location to the variable so that a record of the variable status may be maintained in the memory to record the variable designation together with the storage location address, and to supply the storage space address to all other definitions which refer to the same variable by using the same designation. 48. A system in accordance with claim 47 in which a directory of all variable designations, including signal-name designations, is maintained within the computer system. | 0.597619 |
10,054,329 | 1 | 3 | 1. A computer-implemented method comprising: obtaining historical event data for events detected over a past period of time by sensors within a property; receiving a set of current event data for one or more events detected by one or more of the sensors within the property; determining that the set of current event data matches a pattern of events indicated by the historical event data; generating, based on the pattern of events, a confidence score for the set of current event data that indicates the likeliness that a person is not within the property; determining, based on analyzing a cost for performing an action and a convenience to a resident of the property for performing the action, a confidence threshold for the action; comparing the confidence score for the set of current event data to the confidence threshold for the action; based on comparing the confidence score for the set of current event data to the confidence threshold for the action, determining that the confidence score satisfies the confidence threshold; and in response to determining that the confidence score satisfies the confidence threshold for the action, performing the action. | 1. A computer-implemented method comprising: obtaining historical event data for events detected over a past period of time by sensors within a property; receiving a set of current event data for one or more events detected by one or more of the sensors within the property; determining that the set of current event data matches a pattern of events indicated by the historical event data; generating, based on the pattern of events, a confidence score for the set of current event data that indicates the likeliness that a person is not within the property; determining, based on analyzing a cost for performing an action and a convenience to a resident of the property for performing the action, a confidence threshold for the action; comparing the confidence score for the set of current event data to the confidence threshold for the action; based on comparing the confidence score for the set of current event data to the confidence threshold for the action, determining that the confidence score satisfies the confidence threshold; and in response to determining that the confidence score satisfies the confidence threshold for the action, performing the action. 3. The computer-implemented method of claim 1 , wherein receiving event data comprises: receiving one or more of motion sensor data, contact sensor data, or appliance usage data. | 0.801339 |
8,762,143 | 13 | 14 | 13. The system of claim 12 , wherein the background environment classification comprises one of office, airport, street, vehicle, train and home. | 13. The system of claim 12 , wherein the background environment classification comprises one of office, airport, street, vehicle, train and home. 14. The system of claim 13 , wherein the background environment is classified based on two levels comprising a first level from the listing of background environments in claim 13 and a second, finer, level based on specific geographic location. | 0.5 |
9,665,569 | 11 | 12 | 11. The method of claim 10 , further comprising: selecting the default language based on a language selection obtained during configuration. | 11. The method of claim 10 , further comprising: selecting the default language based on a language selection obtained during configuration. 12. The method of claim 11 , further comprising: translating the first plurality of UI strings from the default language into the first language; and translating the second plurality of UI strings from the default language into the second language. | 0.5 |
7,574,512 | 1 | 4 | 1. A method of communicating between an end automation device having a full or emulated HTTP server and a web browser in an Ethernet environment comprising the following computer implemented steps: sending an HTTP request message from said web browser to a process that encapsulates said request message in a MODBUS type protocol; transmitting said request message to said automation device; responding to said request message by said automation device with a reply message using the MODBUS type protocol; transmitting said reply message to said process; reformatting said reply message such that the message is understandable by said web browser; sending the reformatted reply message to said web browser. | 1. A method of communicating between an end automation device having a full or emulated HTTP server and a web browser in an Ethernet environment comprising the following computer implemented steps: sending an HTTP request message from said web browser to a process that encapsulates said request message in a MODBUS type protocol; transmitting said request message to said automation device; responding to said request message by said automation device with a reply message using the MODBUS type protocol; transmitting said reply message to said process; reformatting said reply message such that the message is understandable by said web browser; sending the reformatted reply message to said web browser. 4. The method of claim 1 wherein the request message uses HTTP and HTML. | 0.590909 |
9,892,094 | 13 | 19 | 13. A computing device comprising: a display; one or more processors; and one or more computer-readable media including instructions that, when executed by the one or more processors, program the one or more processors to: present, on the display, a first portion of content of an electronic version of a content item; receive, via a user interface, a first page label associated with a print version of the content item; determine, based at least in part on a data object, a first position in the content associated with the first page label, wherein the data object indicates associations between page labels from the print version and positions of respective portions of content in the electronic version; present, on the display, a second portion of content of the electronic version corresponding to the first position; receive a selection of a third portion of content of the electronic version as a selected portion; generate a textual citation corresponding to the selected portion; determine, from the data object, based at least in part on a second position associated with the selected portion, a second page label associated with the selected portion; and present the textual citation associated with selected portion, the textual citation including the second page label. | 13. A computing device comprising: a display; one or more processors; and one or more computer-readable media including instructions that, when executed by the one or more processors, program the one or more processors to: present, on the display, a first portion of content of an electronic version of a content item; receive, via a user interface, a first page label associated with a print version of the content item; determine, based at least in part on a data object, a first position in the content associated with the first page label, wherein the data object indicates associations between page labels from the print version and positions of respective portions of content in the electronic version; present, on the display, a second portion of content of the electronic version corresponding to the first position; receive a selection of a third portion of content of the electronic version as a selected portion; generate a textual citation corresponding to the selected portion; determine, from the data object, based at least in part on a second position associated with the selected portion, a second page label associated with the selected portion; and present the textual citation associated with selected portion, the textual citation including the second page label. 19. The computing device as recited in claim 13 , wherein the positions of the respective portions of content are expressed within the data object as at least one of: a number of bytes from a reference point of the electronic version; a number of characters from the reference point of the electronic version; or a number of words from the reference point of the electronic version. | 0.529557 |
8,793,646 | 8 | 13 | 8. A computer program product for aggregating constraints across profiles, the computer program product comprising: a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to, read a stereotype of a first profile, wherein the stereotype defines constraints to be applied to a model associated with the first profile; determine that the stereotype indicates a second profile and a third profile; access the second profile and the third profile; and aggregate a plurality of constraints from across the second profile and the third profile for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language. | 8. A computer program product for aggregating constraints across profiles, the computer program product comprising: a computer readable storage medium having computer usable program code embodied therewith, the computer usable program code comprising a computer usable program code configured to, read a stereotype of a first profile, wherein the stereotype defines constraints to be applied to a model associated with the first profile; determine that the stereotype indicates a second profile and a third profile; access the second profile and the third profile; and aggregate a plurality of constraints from across the second profile and the third profile for use as constraints for the stereotype of the first profile, wherein the profiles and the stereotype comport with semantics of a modeling language. 13. The computer program product of claim 8 , wherein the modeling language comprises the unified modeling language. | 0.741071 |
7,693,904 | 13 | 14 | 13. The method of claim 9 , wherein the step of determining the relation further comprises: generating relation index information between the first query and the second query, and the third query, by using the conditional probability information, the correlation information, and the click rate information. | 13. The method of claim 9 , wherein the step of determining the relation further comprises: generating relation index information between the first query and the second query, and the third query, by using the conditional probability information, the correlation information, and the click rate information. 14. The method of claim 13 , further comprising: selecting and sorting a predetermined number of third search queries according to a descending series of the relation index information, and recording the predetermined number of third search queries as a related search query corresponding to the first search query and the second search query, in a second database; receiving the second search query after receiving the first search query, from a user terminal; extracting the related search query corresponding to the first search query and the second query by referring to the second database; and providing the extracted related search query to the user terminal. | 0.5 |
7,602,518 | 12 | 17 | 12. A device comprising: an interface configured to receive a single user input to initiate performance of a first function with respect to the document, a first representation of the document being available to the device for use in performing the first function; and a function engine configured to perform the first function responsive to the single user input; and a storage engine configured to store a second representation of the document in a memory available to the device responsive to the single user input, the second representation of the document being stored in the memory without requiring further user input. | 12. A device comprising: an interface configured to receive a single user input to initiate performance of a first function with respect to the document, a first representation of the document being available to the device for use in performing the first function; and a function engine configured to perform the first function responsive to the single user input; and a storage engine configured to store a second representation of the document in a memory available to the device responsive to the single user input, the second representation of the document being stored in the memory without requiring further user input. 17. The device of claim 12 wherein the second representation of the document is storing transparent to a user providing the single user input. | 0.784195 |
7,761,856 | 6 | 8 | 6. An apparatus for defining expressions comprising: means for locating a generic string representation of an expression, the generic string representation including an identification of a programming language associated with the expression, the generic string to be converted into the expression prior to being processed by a computer system; means for accessing a data type definition corresponding to the programming language associated with the expression, the data type definition including a converter for converting the string representation of the expression into the expression, wherein the converter is further configured to convert a string representation of a numerical value into a corresponding numerical value, wherein the data type definition and the converter are included in a meta object model of an application; and means for generating an executable runtime representation of the expression based on the expression. | 6. An apparatus for defining expressions comprising: means for locating a generic string representation of an expression, the generic string representation including an identification of a programming language associated with the expression, the generic string to be converted into the expression prior to being processed by a computer system; means for accessing a data type definition corresponding to the programming language associated with the expression, the data type definition including a converter for converting the string representation of the expression into the expression, wherein the converter is further configured to convert a string representation of a numerical value into a corresponding numerical value, wherein the data type definition and the converter are included in a meta object model of an application; and means for generating an executable runtime representation of the expression based on the expression. 8. The apparatus of claim 6 , wherein the application is a language specification. | 0.813636 |
10,019,226 | 13 | 21 | 13. An apparatus, comprising: a subsystem, on a first device, implemented at least partially in hardware, that organizes machine data into a plurality of events, each event in the plurality of events being associated with a timestamp and including a portion of machine data that reflects activity in an information technology environment and that is produced by a component of that information technology environment; a subsystem, implemented at least partially in hardware, that receives, via a user interface, a user selection of a text value from displayed machine data associated with an event among the plurality of events, and automatically generates at least one extraction rule in response to the selection of the text value from machine data associated with the event; and a subsystem, implemented at least partially in hardware, that extracts at least one text value from at least one event in the plurality of events using the at least one extraction rule. | 13. An apparatus, comprising: a subsystem, on a first device, implemented at least partially in hardware, that organizes machine data into a plurality of events, each event in the plurality of events being associated with a timestamp and including a portion of machine data that reflects activity in an information technology environment and that is produced by a component of that information technology environment; a subsystem, implemented at least partially in hardware, that receives, via a user interface, a user selection of a text value from displayed machine data associated with an event among the plurality of events, and automatically generates at least one extraction rule in response to the selection of the text value from machine data associated with the event; and a subsystem, implemented at least partially in hardware, that extracts at least one text value from at least one event in the plurality of events using the at least one extraction rule. 21. The apparatus as recited in claim 13 , wherein the at least one extraction rule includes a regular expression. | 0.834783 |
8,825,613 | 11 | 16 | 11. A method comprising: receiving a first management pack at a database, the first management pack defining a structure of the first management pack and at least one second management pack; and storing the first management pack at the database in an instance space described by the first management pack. | 11. A method comprising: receiving a first management pack at a database, the first management pack defining a structure of the first management pack and at least one second management pack; and storing the first management pack at the database in an instance space described by the first management pack. 16. The method of claim 11 , wherein the first management pack specifies at least one of a management pack type definition or a management pack class definition that is associated with the at least one second management pack. | 0.560547 |
9,538,252 | 8 | 11 | 8. A method for transcribing dialog associated with moving image content, the method comprising: storing, in a provider computer system including at least one electronic processor and at least one data storage device, a master version of moving image content; providing access to a copy of the master version of the moving image content by multiple client devices associated with multiple transcribers, wherein each client device includes at least one electronic processor and at least one data storage device; receiving, in the provider computer system, a request to transcribe the dialog associated with the master version of the moving image content; transmitting an interface to at least one of the multiple client devices, wherein the interface is programmed with instructions for: (i) requesting the copy of the master version of the moving image content from the provider computer system, (ii) interactively playing the moving image content, (iii) receiving input data representative of a transcription of the dialog associated with the master version of the moving image content, and (iv) receiving input data indicative of at least one starting time-stamp and at least one ending time-stamp for at least one segment of multiple segments of the transcription; receiving, in the provider computer system, the transcription of the at least one segment of the multiple segments, and the input data indicative of the at least one starting time-stamp and the at least one ending time-stamp for the at least one segment of the multiple segments of the transcription of the dialog associated with the master version of the moving image content; and storing, in the provider computer system, the transcription together with the starting and ending time-stamps for each segment of the multiple segments as a copy of the master version of the moving image content being reclassified as transcribed and time-stamped. | 8. A method for transcribing dialog associated with moving image content, the method comprising: storing, in a provider computer system including at least one electronic processor and at least one data storage device, a master version of moving image content; providing access to a copy of the master version of the moving image content by multiple client devices associated with multiple transcribers, wherein each client device includes at least one electronic processor and at least one data storage device; receiving, in the provider computer system, a request to transcribe the dialog associated with the master version of the moving image content; transmitting an interface to at least one of the multiple client devices, wherein the interface is programmed with instructions for: (i) requesting the copy of the master version of the moving image content from the provider computer system, (ii) interactively playing the moving image content, (iii) receiving input data representative of a transcription of the dialog associated with the master version of the moving image content, and (iv) receiving input data indicative of at least one starting time-stamp and at least one ending time-stamp for at least one segment of multiple segments of the transcription; receiving, in the provider computer system, the transcription of the at least one segment of the multiple segments, and the input data indicative of the at least one starting time-stamp and the at least one ending time-stamp for the at least one segment of the multiple segments of the transcription of the dialog associated with the master version of the moving image content; and storing, in the provider computer system, the transcription together with the starting and ending time-stamps for each segment of the multiple segments as a copy of the master version of the moving image content being reclassified as transcribed and time-stamped. 11. The method of claim 8 , wherein the interface is further programmed with a plurality of interactive elements. | 0.779297 |
7,990,556 | 25 | 28 | 25. A computing system comprising: a database device that (i) receives an identification request from a displaying device, wherein the identification request specifies an address of the displaying device, (ii) in response to receiving the identification request, transmits a session identifier to the displaying device, (iii) receives a session initiation request from a scanning device, wherein the session initiation request contains the session identifier and a scanning device identifier, wherein the scanning device identifier is unique to the scanning device, and wherein the scanning device and the displaying device each communicate independently with the computing system, and (iv) in response to receiving the session initiation request, the computing system creating an association between the session identifier, the scanning device identifier, and the address of the displaying device; and a content device that (i) receives a digital media request from the scanning device, wherein the digital media request contains information scanned by the scanning device that identifies requested digital media, and (ii) based on the information scanned by the scanning device and the association between the session identifier, the scanning device identifier, and the address of the displaying device, transmits the requested digital media to the displaying device. | 25. A computing system comprising: a database device that (i) receives an identification request from a displaying device, wherein the identification request specifies an address of the displaying device, (ii) in response to receiving the identification request, transmits a session identifier to the displaying device, (iii) receives a session initiation request from a scanning device, wherein the session initiation request contains the session identifier and a scanning device identifier, wherein the scanning device identifier is unique to the scanning device, and wherein the scanning device and the displaying device each communicate independently with the computing system, and (iv) in response to receiving the session initiation request, the computing system creating an association between the session identifier, the scanning device identifier, and the address of the displaying device; and a content device that (i) receives a digital media request from the scanning device, wherein the digital media request contains information scanned by the scanning device that identifies requested digital media, and (ii) based on the information scanned by the scanning device and the association between the session identifier, the scanning device identifier, and the address of the displaying device, transmits the requested digital media to the displaying device. 28. The computing system of claim 25 , wherein, after system storing the association between the session identifier, the scanning device identifier, and the address of the displaying device, the database device recording that the session identifier is owned by the scanning device and that other scanning devices may not become associated with this session identifier. | 0.5 |
7,734,622 | 1 | 10 | 1. A machine-implemented browsing method, comprising: performing a context search based on information associated with at least one media object, wherein the performing of the context search comprises searching a first database of indexed references to web pages and other documents based on search criteria derived from information extracted from the at least one media object, wherein the performing of the context search further comprises generating a context search query from information associated with the at least one media object, transmitting the context search query to a first search engine operable to query the first database in response to receipt of the context search query, and receiving a first search response from the first search engine; performing a context-sensitive search based on results of the context search, wherein the performing of the context-sensitive search comprises searching a second database of indexed references to web pages and other documents based on search criteria derived from the results of the context search, wherein the performing of the context-sensitive search further comprises generating a context-sensitive search query from the first search response, transmitting the context-sensitive search query to a second search engine operable to query the second database in response to receipt of the context-sensitive search query, and receiving a second search response from the second search engine; and presenting information derived from results of the context-sensitive search. | 1. A machine-implemented browsing method, comprising: performing a context search based on information associated with at least one media object, wherein the performing of the context search comprises searching a first database of indexed references to web pages and other documents based on search criteria derived from information extracted from the at least one media object, wherein the performing of the context search further comprises generating a context search query from information associated with the at least one media object, transmitting the context search query to a first search engine operable to query the first database in response to receipt of the context search query, and receiving a first search response from the first search engine; performing a context-sensitive search based on results of the context search, wherein the performing of the context-sensitive search comprises searching a second database of indexed references to web pages and other documents based on search criteria derived from the results of the context search, wherein the performing of the context-sensitive search further comprises generating a context-sensitive search query from the first search response, transmitting the context-sensitive search query to a second search engine operable to query the second database in response to receipt of the context-sensitive search query, and receiving a second search response from the second search engine; and presenting information derived from results of the context-sensitive search. 10. The method of claim 1 , further comprising presenting one or more media objects in a collection. | 0.748744 |
8,984,098 | 1 | 2 | 1. A computer-implemented method comprising: obtaining a group of candidate content items for one or more streams of content from heterogeneous data sources; generating, with one or more processors, a model for a user comprising an interest of the user and a prior interaction of the user with the heterogeneous data sources; computing, with the one or more processors, an interestingness score for each candidate content item in the group by combining properties of each candidate content item over single-attribute properties using the model and based upon interestingness of each candidate content item to the user and an extent to which the candidate content item's popularity has changed within a geographic area associated with the user; comparing the interestingness score for each candidate content item with a threshold for a first interest type and a second interest type to determine which candidate content items have an interestingness score that exceeds the threshold for the first interest type or the second interest type; organizing a first content item and a second content item that have an interestingness score that exceeds the threshold in a first stream of content; providing the first stream of content for presentation in a first direction to the user; generating a user interface for configuring the one or more streams of content, the user interface comprising the first content item, the second content item and a marker, the marker associated with the second content item for the user to request a third content item related to the second content item; and responsive to receiving a selection of the marker associated with the second content item from the user, organizing the second and third content items in a second stream of content, providing the second stream of content for presentation in a second direction to the user, and updating the user interface to include the second stream of content. | 1. A computer-implemented method comprising: obtaining a group of candidate content items for one or more streams of content from heterogeneous data sources; generating, with one or more processors, a model for a user comprising an interest of the user and a prior interaction of the user with the heterogeneous data sources; computing, with the one or more processors, an interestingness score for each candidate content item in the group by combining properties of each candidate content item over single-attribute properties using the model and based upon interestingness of each candidate content item to the user and an extent to which the candidate content item's popularity has changed within a geographic area associated with the user; comparing the interestingness score for each candidate content item with a threshold for a first interest type and a second interest type to determine which candidate content items have an interestingness score that exceeds the threshold for the first interest type or the second interest type; organizing a first content item and a second content item that have an interestingness score that exceeds the threshold in a first stream of content; providing the first stream of content for presentation in a first direction to the user; generating a user interface for configuring the one or more streams of content, the user interface comprising the first content item, the second content item and a marker, the marker associated with the second content item for the user to request a third content item related to the second content item; and responsive to receiving a selection of the marker associated with the second content item from the user, organizing the second and third content items in a second stream of content, providing the second stream of content for presentation in a second direction to the user, and updating the user interface to include the second stream of content. 2. The method of claim 1 , wherein the second content item is associated with the second type of interest, the method further comprising: receiving a selection of the second content item from the user; and modifying the model based on the second type of interest. | 0.595385 |
8,913,878 | 3 | 7 | 3. Device for providing a playable sequence which is modifiable, the modified sequence being provided in renderable manner, the device comprising: an input configured for obtaining playable objects, each object being independently playable, a providing unit configured to provide a plurality of defined functions, said functions applying playable effects to modify play of said playable objects, said playable objects being part of an underlying object-orientated model, said plurality of defined functions being provided to said playable objects as markup when selected, a time unit configured for adding time boundaries to said defined functions, to provide time bounded functions having respective beginning and end time boundaries, an ordering unit configured for ordering said defined time bounded functions with said objects into a sequence, thereby to place said objects with and without said functions at different times in said sequence, and a translation unit configured for applying translations to said playable objects in accordance with said playable effects, by rendering said playable objects in accordance with said markup, thereby to modify play of said playable objects at respective times within said sequence, said device thereby using said time boundaries and said ordering to combine a timeline synchronization framework with said underlying object-orientated model, wherein said sequence comprises multiple code blocks to be executed simultaneously within a timeline, the device configured to associate each of said multiple code blocks with a respective execution frame, and to associate each execution frame with a respective time graph, wherein said time graph comprises nodes and said nodes comprise invocation objects for invoking methods for said rendering. | 3. Device for providing a playable sequence which is modifiable, the modified sequence being provided in renderable manner, the device comprising: an input configured for obtaining playable objects, each object being independently playable, a providing unit configured to provide a plurality of defined functions, said functions applying playable effects to modify play of said playable objects, said playable objects being part of an underlying object-orientated model, said plurality of defined functions being provided to said playable objects as markup when selected, a time unit configured for adding time boundaries to said defined functions, to provide time bounded functions having respective beginning and end time boundaries, an ordering unit configured for ordering said defined time bounded functions with said objects into a sequence, thereby to place said objects with and without said functions at different times in said sequence, and a translation unit configured for applying translations to said playable objects in accordance with said playable effects, by rendering said playable objects in accordance with said markup, thereby to modify play of said playable objects at respective times within said sequence, said device thereby using said time boundaries and said ordering to combine a timeline synchronization framework with said underlying object-orientated model, wherein said sequence comprises multiple code blocks to be executed simultaneously within a timeline, the device configured to associate each of said multiple code blocks with a respective execution frame, and to associate each execution frame with a respective time graph, wherein said time graph comprises nodes and said nodes comprise invocation objects for invoking methods for said rendering. 7. The device of claim 3 , wherein said ordering unit comprises a layered model for layering said time bounded defined functions to define interrelationships between said functions. | 0.5 |
9,716,767 | 5 | 6 | 5. A system for pushing input resources, wherein the system comprises: one or more processors; and memory having instructions stored thereon, wherein the instructions, when executed by the one or more processors, cause the one or more processors to control a process, the process comprising: obtaining user characteristic information of a client terminal, the user characteristic information including user interest information or user position information; obtaining at least one input resource based on the user characteristic information; the input resources including at least one of input method skin, input method font, and input method font size; and pushing the at least one input resource to the client terminal, wherein: the user characteristic information is user interest information, and the process includes: obtaining at least one on-screen word entry of the client terminal; obtaining word frequency information of the at least one on-screen word entry; obtaining at least one target word entry based on the at least one on-screen word entry, the word frequency information of the at least one on-screen word entry, and a preset frequency threshold; obtaining the user interest information of the client terminal according to the at least one target word entry and a preset category dictionary, the preset category dictionary includes at least one interest category and at least one word entry included in each interest category; carrying out matching among all word entries in the preset category dictionary according to each target word entry; if there exists a word entry that matches with the target word entry, increasing a corresponding weight value of the interest category the word entry belongs to by 1; if there is no word entry that matches with the target word entry, obtaining a co-occurring word entry of the target word entry with a largest number of co-occurrences; carrying out matching among all word entries in the preset category dictionary according to the co-occurring word entry; increasing a corresponding weight value of the interest category the co-occurring word entry belongs to by 1; and obtaining the user interest information of the client terminal based on at least one interest category with a largest weight value. | 5. A system for pushing input resources, wherein the system comprises: one or more processors; and memory having instructions stored thereon, wherein the instructions, when executed by the one or more processors, cause the one or more processors to control a process, the process comprising: obtaining user characteristic information of a client terminal, the user characteristic information including user interest information or user position information; obtaining at least one input resource based on the user characteristic information; the input resources including at least one of input method skin, input method font, and input method font size; and pushing the at least one input resource to the client terminal, wherein: the user characteristic information is user interest information, and the process includes: obtaining at least one on-screen word entry of the client terminal; obtaining word frequency information of the at least one on-screen word entry; obtaining at least one target word entry based on the at least one on-screen word entry, the word frequency information of the at least one on-screen word entry, and a preset frequency threshold; obtaining the user interest information of the client terminal according to the at least one target word entry and a preset category dictionary, the preset category dictionary includes at least one interest category and at least one word entry included in each interest category; carrying out matching among all word entries in the preset category dictionary according to each target word entry; if there exists a word entry that matches with the target word entry, increasing a corresponding weight value of the interest category the word entry belongs to by 1; if there is no word entry that matches with the target word entry, obtaining a co-occurring word entry of the target word entry with a largest number of co-occurrences; carrying out matching among all word entries in the preset category dictionary according to the co-occurring word entry; increasing a corresponding weight value of the interest category the co-occurring word entry belongs to by 1; and obtaining the user interest information of the client terminal based on at least one interest category with a largest weight value. 6. The system according to claim 5 , wherein the user characteristic information is user position information, and the obtaining user characteristic information comprises: obtaining at least one piece of candidate position information of the client terminal; obtaining a number of occurrences of the at least one piece of candidate position information; obtaining at least one piece of target position information based on the at least one piece of candidate position information, the number of occurrences of the at least one piece of candidate position information, and a preset probability threshold; and obtaining the user positioning information of the client terminal based on the at least one piece of target position information. | 0.5 |
7,831,995 | 1 | 6 | 1. A method, executing on hardware, for implementing security in a web application, wherein the web application is executed in a web application language execution environment within a web server, the method comprising: establishing at least one inbound tagging rule for tagging objects entering the web application language execution environment, referred to as inbound objects, according to a respective source of each of the inbound objects; assigning a tag to at least one of the inbound objects being operated on by the web application language execution environment based on the at least one inbound tagging rule; establishing at least one security rule for performing security actions on at least one object that is outbound from the web application language execution environment, referred to as outbound objects, according to a respective tag of each of the outbound objects; and performing a security action on the at least one outbound object being operated on by the web application language execution environment based on the at least one security rule, wherein the detection of the attack comprises a lexical analysis of the data of the object being operated on by the web application language execution environment checking the tags assigned to the outbound object. | 1. A method, executing on hardware, for implementing security in a web application, wherein the web application is executed in a web application language execution environment within a web server, the method comprising: establishing at least one inbound tagging rule for tagging objects entering the web application language execution environment, referred to as inbound objects, according to a respective source of each of the inbound objects; assigning a tag to at least one of the inbound objects being operated on by the web application language execution environment based on the at least one inbound tagging rule; establishing at least one security rule for performing security actions on at least one object that is outbound from the web application language execution environment, referred to as outbound objects, according to a respective tag of each of the outbound objects; and performing a security action on the at least one outbound object being operated on by the web application language execution environment based on the at least one security rule, wherein the detection of the attack comprises a lexical analysis of the data of the object being operated on by the web application language execution environment checking the tags assigned to the outbound object. 6. The method of claim 1 , wherein the at least one security rule for performing security actions on outbound objects is established according to a respective destination of each of the outbound objects. | 0.759479 |
10,095,749 | 5 | 6 | 5. The method of claim 1 , further comprising: annotating entries in the ranked result set to indicate boosted entries. | 5. The method of claim 1 , further comprising: annotating entries in the ranked result set to indicate boosted entries. 6. The method of claim 5 , wherein annotating the entries includes marking information in entries with highlighting or bolding. | 0.5 |
9,710,786 | 1 | 6 | 1. A system for a knowledge management system comprising: a processor; and a memory that contains instructions that are readable by the processor and cause the processor to: receive a query that indicates at least one legal topic from a hierarchy of legal topics; provide a response to the query indicating each work-product document and each case law document that matches the at least one legal topic, wherein the processor is operable to, prior to providing the response: retrieve each work-product document that matches the at least one legal topic from a first database; and retrieve each case law document that matches the at least one legal topic from a second database; determine a validity status of at least one case cited within each work-product document, resulting in a validity indicator, the validity indicator for each work-product document indicating the validity status of the at least one case; indicate, in the response provided to the query, a reliability of each work-product document using the validity indicator and a rating indicator for each work-product document, the rating indicator for each work-product document indicating a user rating of each work-product document based on previous users of each work-product document; index each work-product document according to the hierarchy of legal topics based on at least one legal citation and a set of text; index each case law document according to the hierarchy of legal topics; receive a second query for a particular case law document; and provide a second response to the second query indicating each work-product document which includes at least one legal citation associated with the particular case law document according to a depth-of-treatment value, the depth-of-treatment value indicates a degree to which each work-product document evaluates the particular case law document. | 1. A system for a knowledge management system comprising: a processor; and a memory that contains instructions that are readable by the processor and cause the processor to: receive a query that indicates at least one legal topic from a hierarchy of legal topics; provide a response to the query indicating each work-product document and each case law document that matches the at least one legal topic, wherein the processor is operable to, prior to providing the response: retrieve each work-product document that matches the at least one legal topic from a first database; and retrieve each case law document that matches the at least one legal topic from a second database; determine a validity status of at least one case cited within each work-product document, resulting in a validity indicator, the validity indicator for each work-product document indicating the validity status of the at least one case; indicate, in the response provided to the query, a reliability of each work-product document using the validity indicator and a rating indicator for each work-product document, the rating indicator for each work-product document indicating a user rating of each work-product document based on previous users of each work-product document; index each work-product document according to the hierarchy of legal topics based on at least one legal citation and a set of text; index each case law document according to the hierarchy of legal topics; receive a second query for a particular case law document; and provide a second response to the second query indicating each work-product document which includes at least one legal citation associated with the particular case law document according to a depth-of-treatment value, the depth-of-treatment value indicates a degree to which each work-product document evaluates the particular case law document. 6. The system recited in claim 1 , wherein the processor further converts the work-product document into a markup language. | 0.823276 |
8,620,912 | 1 | 13 | 1. A method for ranking an ad, comprising: retrieving an initial video frame set comprising one or more initial video frames based upon a query image; identifying one or more related video frames related to at least one initial video frame of the initial video frame set to create an expanded video frame set comprising one or more video frames, the one or more video frames of the expanded video frame set comprising at least some initial video frames and at least some related video frames, the expanded video frame set not comprising the query image; grouping at least some of the one or more video frames of the expanded video frame set into one or more clusters; and ranking an ad based upon an ad feature of the ad corresponding to a cluster feature of a cluster, at least some of at least one of the retrieving, the identifying, the grouping, or the ranking implemented at least in part via a processing unit. | 1. A method for ranking an ad, comprising: retrieving an initial video frame set comprising one or more initial video frames based upon a query image; identifying one or more related video frames related to at least one initial video frame of the initial video frame set to create an expanded video frame set comprising one or more video frames, the one or more video frames of the expanded video frame set comprising at least some initial video frames and at least some related video frames, the expanded video frame set not comprising the query image; grouping at least some of the one or more video frames of the expanded video frame set into one or more clusters; and ranking an ad based upon an ad feature of the ad corresponding to a cluster feature of a cluster, at least some of at least one of the retrieving, the identifying, the grouping, or the ranking implemented at least in part via a processing unit. 13. The method of claim 1 , the ranking comprising: executing a multimodal Dirichlet Process Mixture Sets model upon the ad using the one or more clusters. | 0.699612 |
9,189,954 | 24 | 26 | 24. A system for controlling a radio device, comprising: a gesture pad configured to modify an operation of the radio device, wherein the gesture pad distinguishes between a plurality of fingers used for a gesture, recognizes the orientation of the distinguished finger, and performs a function that is dependent on the distinguished finger and its orientation. | 24. A system for controlling a radio device, comprising: a gesture pad configured to modify an operation of the radio device, wherein the gesture pad distinguishes between a plurality of fingers used for a gesture, recognizes the orientation of the distinguished finger, and performs a function that is dependent on the distinguished finger and its orientation. 26. The system of claim 24 , further comprising a voice control component configured to modify a first operation of the radio device, wherein the first operation comprises one of: jumping to a current broadcast point; jumping to a point in a buffered content; indicating a preference for an output audio content of the radio; saving a copy of an audio content; or modifying an input signal type, wherein the input signal type comprises AM, FM, HD, Satellite, Wi-Fi, Saved, CD, MP3, iPod, or Flash. | 0.5 |
9,852,625 | 9 | 10 | 9. Method according to claim 2 wherein the tutorial message is selected based on the accumulated goal fulfillment. | 9. Method according to claim 2 wherein the tutorial message is selected based on the accumulated goal fulfillment. 10. Method according to claim 9 , wherein the plurality of tutorial messages comprises a plurality of tutorial messages of different degree of detail for each tutorial task. | 0.5 |
9,519,870 | 1 | 3 | 1. One or more computer storage media storing computer-executable instructions that, when executed by one or more computing devices, cause the one or more computing devices to perform operations comprising: accessing a seed list containing positive sample entities that belong to an entity class; accessing a background entity list containing negative sample entities that do not belong to the entity class; identifying clicked URLs from search click logs for at least a portion of the positive sample entities and negative sample entities; identifying search result URLs for at least a portion of the positive sample entities and negative sample entities; identifying attributes from an entity graph for at least a portion of the positive sample entities and negative sample entities; training a classifier model using the clicked URLs, search result URLs, and attributes from the entity graph as features of the positive sample entities and negative sample entities; and using the classifier model to weight entities in a candidate dictionary to provide weightings for the entities from the candidate dictionary. | 1. One or more computer storage media storing computer-executable instructions that, when executed by one or more computing devices, cause the one or more computing devices to perform operations comprising: accessing a seed list containing positive sample entities that belong to an entity class; accessing a background entity list containing negative sample entities that do not belong to the entity class; identifying clicked URLs from search click logs for at least a portion of the positive sample entities and negative sample entities; identifying search result URLs for at least a portion of the positive sample entities and negative sample entities; identifying attributes from an entity graph for at least a portion of the positive sample entities and negative sample entities; training a classifier model using the clicked URLs, search result URLs, and attributes from the entity graph as features of the positive sample entities and negative sample entities; and using the classifier model to weight entities in a candidate dictionary to provide weightings for the entities from the candidate dictionary. 3. The one or more computer storage media of claim 1 , wherein the background entity list is generated based on information from at least one selected from the following: an existing entity graph and training data from a spoken language understanding system. | 0.618343 |
8,799,765 | 1 | 5 | 1. A digital computing device for viewing shared annotations of at least one electronic reference document, the device comprising a digital memory, a display, a user input interface, and a network interface; and said computing device being configured to: receive, over a network, via the network interface, a digital location identifier for navigation to a shared reading location with an associated annotation, said digital location identifier specifying the shared reading location within a version of the electronic reference document and does not include the version of the electronic reference document; upon receipt of a selection to navigate to the shared reading location, determine if a user of the digital computing device has sufficient rights to use a copy of the electronic reference document referenced by the digital location identifier, and, if the user does not have sufficient rights, (i) provide a prompt with an option for the user to purchase said rights, (ii) responsive to confirmation of the purchase of the rights to use the copy of the electronic reference document, receive the copy of the electronic reference document, and (iii) store the copy of the electronic reference document in the digital memory; and upon successful confirmation of the user's rights to use the copy of the electronic reference document and responsive to the selection to navigate to the shared reading location (i) determining that the content referenced by the digital location identifier exists in the copy of the reference document, (ii) displaying at least a portion of the copy of the electronic reference document at the shared reading location and the associated annotation within the copy of the electronic reference document at the shared reading location. | 1. A digital computing device for viewing shared annotations of at least one electronic reference document, the device comprising a digital memory, a display, a user input interface, and a network interface; and said computing device being configured to: receive, over a network, via the network interface, a digital location identifier for navigation to a shared reading location with an associated annotation, said digital location identifier specifying the shared reading location within a version of the electronic reference document and does not include the version of the electronic reference document; upon receipt of a selection to navigate to the shared reading location, determine if a user of the digital computing device has sufficient rights to use a copy of the electronic reference document referenced by the digital location identifier, and, if the user does not have sufficient rights, (i) provide a prompt with an option for the user to purchase said rights, (ii) responsive to confirmation of the purchase of the rights to use the copy of the electronic reference document, receive the copy of the electronic reference document, and (iii) store the copy of the electronic reference document in the digital memory; and upon successful confirmation of the user's rights to use the copy of the electronic reference document and responsive to the selection to navigate to the shared reading location (i) determining that the content referenced by the digital location identifier exists in the copy of the reference document, (ii) displaying at least a portion of the copy of the electronic reference document at the shared reading location and the associated annotation within the copy of the electronic reference document at the shared reading location. 5. The computing device of claim 1 , wherein the annotation comprises at least one of: one or more words, one or more numerals, a mathematical formula, a graphical image, a link to a location, a universal resource locator (URL) address, a script, and highlighting of selected text. | 0.627321 |
8,892,441 | 1 | 4 | 1. A method comprising: overgenerating potential pronunciations by converting portions of symbolic input into a number of possible lexical pronunciation variants based on an established set of conversion rules, wherein the symbolic input comprises labeled speech data; identifying, via a processor of a computing device, potential pronunciations in a speech recognition context to yield identified potential pronunciations; and storing the identified potential pronunciations in a lexicon. | 1. A method comprising: overgenerating potential pronunciations by converting portions of symbolic input into a number of possible lexical pronunciation variants based on an established set of conversion rules, wherein the symbolic input comprises labeled speech data; identifying, via a processor of a computing device, potential pronunciations in a speech recognition context to yield identified potential pronunciations; and storing the identified potential pronunciations in a lexicon. 4. The method of claim 1 , wherein the labeled speech data is implicitly labeled. | 0.714789 |
8,805,829 | 6 | 7 | 6. The system of claim 5 , wherein: determining the similarity measure comprises determining a divergence that measures the difference between the probabilities of the selection vector of the first search query and the probabilities of the selection vector of the second search query. | 6. The system of claim 5 , wherein: determining the similarity measure comprises determining a divergence that measures the difference between the probabilities of the selection vector of the first search query and the probabilities of the selection vector of the second search query. 7. The system of claim 6 , wherein determining a divergence comprises: determining a first divergence of the probabilities of the selection vector for the first search query from the probabilities of the selection vector for the second search query; determining a second divergence of the probabilities of the selection vector for the second search query from the probabilities of the selection vector for the first search query; and averaging the first divergence and the second divergence to determine similarity measure. | 0.5 |
8,423,888 | 7 | 8 | 7. A document converting method for converting a first structured document to a second structured document different in structure from the first structured document, comprising: reading a template indicating a structure of the second structured document and described in a same language with the second structured document; displaying a design represented by the read template on a screen of a display device; allowing a user to specify an element or an element content configuring the template in the displayed design; allowing the user to define a correspondence definition indicating correspondence between an element in the first structured document and an element in the template by corresponding a tag of a element in the first structured document with a position of the specified element or element content in the displayed design; converting the template and the first structured document into tree structure objects, respectively; searching the specified element or the specified element content from the tree structure object of the template, sequentially searching the element described in the correspondence definition from the searched element or element content in the tree structure object of the template as a start point, and generating a tree structure object of the template which comprises the element sequentially-searched element; searching an element described in the correspondence definition from the tree structure object of the first structured document; and entering, when the element detected by searching from the tree structure object of the first structured document having a child element and a corresponding element in the template having a defined parent element, the generated tree structure of the template into the tree object of the template according to the number of child elements, and replacing, when the element detected by searching from the tree structure object of the first structured document having only an element content and a corresponding element in the template having no child element, the element content of the detected element with the specified element content in the template. | 7. A document converting method for converting a first structured document to a second structured document different in structure from the first structured document, comprising: reading a template indicating a structure of the second structured document and described in a same language with the second structured document; displaying a design represented by the read template on a screen of a display device; allowing a user to specify an element or an element content configuring the template in the displayed design; allowing the user to define a correspondence definition indicating correspondence between an element in the first structured document and an element in the template by corresponding a tag of a element in the first structured document with a position of the specified element or element content in the displayed design; converting the template and the first structured document into tree structure objects, respectively; searching the specified element or the specified element content from the tree structure object of the template, sequentially searching the element described in the correspondence definition from the searched element or element content in the tree structure object of the template as a start point, and generating a tree structure object of the template which comprises the element sequentially-searched element; searching an element described in the correspondence definition from the tree structure object of the first structured document; and entering, when the element detected by searching from the tree structure object of the first structured document having a child element and a corresponding element in the template having a defined parent element, the generated tree structure of the template into the tree object of the template according to the number of child elements, and replacing, when the element detected by searching from the tree structure object of the first structured document having only an element content and a corresponding element in the template having no child element, the element content of the detected element with the specified element content in the template. 8. The document converting method according to claim 7 , wherein displaying includes displaying the template read from the template storage device, and allowing the user to specify on a display screen an element or an element content configuring the template. | 0.5 |
7,543,758 | 3 | 4 | 3. The method of claim 1 , further comprising: identifying, from among the multiplicity of regions of the electronically stored document, regions which are distinguishable from all the other regions in the multiplicity of regions, by the automated processing component, without addition of disambiguating information. | 3. The method of claim 1 , further comprising: identifying, from among the multiplicity of regions of the electronically stored document, regions which are distinguishable from all the other regions in the multiplicity of regions, by the automated processing component, without addition of disambiguating information. 4. The method of claim 3 , further comprising: adding no disambiguating information to the regions which are distinguishable from all the other regions of the electronically stored document. | 0.5 |
9,786,284 | 13 | 14 | 13. A computing device comprising: one or more computer processors; one or more computer-readable media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising: receiving, via a network interface of the computing device, a wideband speech feature from a remote entity; determining an estimate of a narrowband speech feature based on the wideband speech feature; providing the estimate of the narrowband speech feature to a speech recognizer trained on the narrowband speech features; receiving, from the speech recognizer, speech-recognition results based on the estimate of the narrowband speech feature; assembling the speech recognition results received from the speech recognizer; and transmitting, via the network interface to the remote entity and for output or display by the remote entity, the assembled speech-recognition results based on the estimate of the narrowband speech feature. | 13. A computing device comprising: one or more computer processors; one or more computer-readable media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising: receiving, via a network interface of the computing device, a wideband speech feature from a remote entity; determining an estimate of a narrowband speech feature based on the wideband speech feature; providing the estimate of the narrowband speech feature to a speech recognizer trained on the narrowband speech features; receiving, from the speech recognizer, speech-recognition results based on the estimate of the narrowband speech feature; assembling the speech recognition results received from the speech recognizer; and transmitting, via the network interface to the remote entity and for output or display by the remote entity, the assembled speech-recognition results based on the estimate of the narrowband speech feature. 14. A computing device as described in claim 13 , wherein the operations further comprise providing the speech-recognition results of the speech recognizer trained on narrowband speech features to a search engine, receiving search results from the search engine, and transmitting the search results to the remote entity. | 0.5 |
7,570,261 | 1 | 4 | 1. A computer-implemented system configured to maintain and cause a display of a virtual city model of an actual city, said system comprising: at least one data storage device which stores a plurality of instructions and stores data representing: (a) a plurality of city elements, the city elements being three-dimensional representations of actual elements within an actual boundary of the actual city, at least one of said city elements including an image skin applied to a three-dimensional structure, at least two of said city elements being anchor city elements, said anchor city elements representing spaced-apart actual elements having identifiable architectural characteristics within said actual city, said anchor city elements encouraging a user to explore any city elements between said anchor city elements, said boundary displayable by a display device and said city elements displayable by the display device within said display of the boundary, (b) at least one advertiser information set predetermined to be associated with at least a portion of at least one of said city elements, wherein said city element represents a place of business of an advertiser, and (c) a boundary display effect, said boundary display effect being configured to increasingly obscure an area outside said boundary; and at least one processor configured to execute said instructions to: enable the advertiser to lease at least one advertiser information set such that, upon each payment of a recurring predetermined lease fee during a corresponding lease period, the advertiser controls at least a portion of the data of the advertiser information set associated with said portion of said city element, and enable the user of the virtual city model to: (a) select a viewing angle from a plurality of different viewing angles for viewing the city elements within the boundary displayable by the display device, (b) navigate the different city elements within the boundary displayable by the display device at each selected viewing angle, (c) select at least a portion of each of a plurality of the city elements, (d) cause a display of at least a portion of the advertiser information set associated with the selected portion of the city element, and (e) display the boundary display effect as the area outside said boundary. | 1. A computer-implemented system configured to maintain and cause a display of a virtual city model of an actual city, said system comprising: at least one data storage device which stores a plurality of instructions and stores data representing: (a) a plurality of city elements, the city elements being three-dimensional representations of actual elements within an actual boundary of the actual city, at least one of said city elements including an image skin applied to a three-dimensional structure, at least two of said city elements being anchor city elements, said anchor city elements representing spaced-apart actual elements having identifiable architectural characteristics within said actual city, said anchor city elements encouraging a user to explore any city elements between said anchor city elements, said boundary displayable by a display device and said city elements displayable by the display device within said display of the boundary, (b) at least one advertiser information set predetermined to be associated with at least a portion of at least one of said city elements, wherein said city element represents a place of business of an advertiser, and (c) a boundary display effect, said boundary display effect being configured to increasingly obscure an area outside said boundary; and at least one processor configured to execute said instructions to: enable the advertiser to lease at least one advertiser information set such that, upon each payment of a recurring predetermined lease fee during a corresponding lease period, the advertiser controls at least a portion of the data of the advertiser information set associated with said portion of said city element, and enable the user of the virtual city model to: (a) select a viewing angle from a plurality of different viewing angles for viewing the city elements within the boundary displayable by the display device, (b) navigate the different city elements within the boundary displayable by the display device at each selected viewing angle, (c) select at least a portion of each of a plurality of the city elements, (d) cause a display of at least a portion of the advertiser information set associated with the selected portion of the city element, and (e) display the boundary display effect as the area outside said boundary. 4. The computer-implemented system of claim 1 , wherein the actual city is selected from the group consisting of: a real city, a real town, a real village, a real province, a real county, a real state, a real country, a real ward, a real community, a real university campus, and a real college campus. | 0.715501 |
8,327,315 | 4 | 6 | 4. The method of claim 2 , further comprising: determining when an entry on the browser tree is selected; and determining whether the entry selected is a circuit design constraint group or a circuit design constraint. | 4. The method of claim 2 , further comprising: determining when an entry on the browser tree is selected; and determining whether the entry selected is a circuit design constraint group or a circuit design constraint. 6. The method of claim 4 , wherein for a selection that is a circuit design constraint group, when an existing circuit design group is added to or removed from the circuit design constraint group through the graphical user interface, the design object store updated accordingly. | 0.742115 |
8,577,913 | 1 | 3 | 1. A method for query suggestion, performed on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors to perform the method, comprising: at the server system: receiving an original query from a client distinct from the server system; identifying one or more segments in the original query; identifying an anchor segment of the one or more segments in the original query, wherein the anchor segment is identified based on cursor placement within the original query, and identifying zero or more remaining segments of the original query, excluding the anchor segment; identifying one or more sibling segments associated with the anchor segment, wherein the one or more sibling segments are identified by the server system to be semantically distinct from anchor segment; identifying one or more query refinement candidates, wherein a respective query refinement candidate includes a respective sibling segment in place of the anchor segment and includes the remaining segments, if any, of the original query; sending to the client for presentation information including one or more of the query refinement candidates; receiving from the client one or more deleted characters from the original query and any remaining characters from the original query, the remaining characters consisting of characters of the original query which are not deleted characters; and reconstructing the original query from the deleted characters and the remaining characters; wherein the one or more sibling segments are identified using an algorithm that identifies sibling segments that are conceptually related to the anchor segment; and wherein, when the original query includes two or more segments, including the anchor segment and one or more remaining segments, identifying the one or more query refinement candidates comprises: forming potential query refinement candidates from the identified sibling segments and the one or more remaining segments; and excluding from the identified one or more query refinement candidates any of the potential refinement candidates not present in a predefined database of historical complete queries. | 1. A method for query suggestion, performed on a server system having one or more processors and memory storing one or more programs for execution by the one or more processors to perform the method, comprising: at the server system: receiving an original query from a client distinct from the server system; identifying one or more segments in the original query; identifying an anchor segment of the one or more segments in the original query, wherein the anchor segment is identified based on cursor placement within the original query, and identifying zero or more remaining segments of the original query, excluding the anchor segment; identifying one or more sibling segments associated with the anchor segment, wherein the one or more sibling segments are identified by the server system to be semantically distinct from anchor segment; identifying one or more query refinement candidates, wherein a respective query refinement candidate includes a respective sibling segment in place of the anchor segment and includes the remaining segments, if any, of the original query; sending to the client for presentation information including one or more of the query refinement candidates; receiving from the client one or more deleted characters from the original query and any remaining characters from the original query, the remaining characters consisting of characters of the original query which are not deleted characters; and reconstructing the original query from the deleted characters and the remaining characters; wherein the one or more sibling segments are identified using an algorithm that identifies sibling segments that are conceptually related to the anchor segment; and wherein, when the original query includes two or more segments, including the anchor segment and one or more remaining segments, identifying the one or more query refinement candidates comprises: forming potential query refinement candidates from the identified sibling segments and the one or more remaining segments; and excluding from the identified one or more query refinement candidates any of the potential refinement candidates not present in a predefined database of historical complete queries. 3. The method of claim 1 , wherein after an anchor segment has been identified, user initiated deletion of characters in the anchor segment does not affect the identification of the one or more sibling segments. | 0.848854 |
10,127,284 | 1 | 5 | 1. A system, comprising: one or more computer processors; and a memory containing a program which when executed by the processors performs an operation comprising: identifying a first variable in a source code of a question answering (QA) system; upon determining that a weight applied to a value of the first variable by a first rule in the source code increases a confidence score for candidate answers generated by the QA system beyond a threshold: computing an influence score for the first variable based on: (i) the weight applied to the value of the first variable by the first rule in the source code, (ii) a number of rules specifying weights applied to values of the first attribute, (iii) a location of the first attribute in each rule, (iv) a number of times the first variable is used in each rule, (v) a type of operation applied to the value of the first variable by each respective rule, and (vi) an identified phase of a processing pipeline of the QA system in which each respective rule is applied; computing an importance score for the first variable based at least in part on the computed influence score; and upon determining that the importance score exceeds a predefined threshold, storing an indication that the first variable is an important variable relative to other variables specified in the source code; receiving, by the QA system, a case that does not specify a value for the first variable; and refraining, by the QA system, from processing the case. | 1. A system, comprising: one or more computer processors; and a memory containing a program which when executed by the processors performs an operation comprising: identifying a first variable in a source code of a question answering (QA) system; upon determining that a weight applied to a value of the first variable by a first rule in the source code increases a confidence score for candidate answers generated by the QA system beyond a threshold: computing an influence score for the first variable based on: (i) the weight applied to the value of the first variable by the first rule in the source code, (ii) a number of rules specifying weights applied to values of the first attribute, (iii) a location of the first attribute in each rule, (iv) a number of times the first variable is used in each rule, (v) a type of operation applied to the value of the first variable by each respective rule, and (vi) an identified phase of a processing pipeline of the QA system in which each respective rule is applied; computing an importance score for the first variable based at least in part on the computed influence score; and upon determining that the importance score exceeds a predefined threshold, storing an indication that the first variable is an important variable relative to other variables specified in the source code; receiving, by the QA system, a case that does not specify a value for the first variable; and refraining, by the QA system, from processing the case. 5. The system of claim 1 , wherein the confidence score specifies a level of confidence that a response to a case generated by the deep question answering system is correct, wherein the source code comprises a current source code of the QA system. | 0.823319 |
9,406,029 | 13 | 17 | 13. A method, comprising: identifying, in response to a triggering event associated with a workload of a storage system, a proposed solution comprising one or more actions to be performed; predicting, for the proposed solution, a value of an output metric for the workload using a mapping function for the output metric based on a plurality of input metric values for a foreground workload and a plurality of input metric values for a set of background workloads of the storage system, the mapping function produced using a machine learning algorithm; and generating, by a processor circuit, an evaluation value for the proposed solution based on the predicted value of the output metric. | 13. A method, comprising: identifying, in response to a triggering event associated with a workload of a storage system, a proposed solution comprising one or more actions to be performed; predicting, for the proposed solution, a value of an output metric for the workload using a mapping function for the output metric based on a plurality of input metric values for a foreground workload and a plurality of input metric values for a set of background workloads of the storage system, the mapping function produced using a machine learning algorithm; and generating, by a processor circuit, an evaluation value for the proposed solution based on the predicted value of the output metric. 17. The method of claim 13 , the triggering event comprising a violation of a service level objective (SLO) for the workload. | 0.836387 |
9,536,006 | 16 | 17 | 16. The computer storage medium of claim 15 , wherein determining that the first responsive resource is associated with enrichment information comprises: identifying responsive enrichment information, responsive enrichment information being enrichment information that is responsive to the query; and determining that the first responsive resource is associated with the responsive enrichment information. | 16. The computer storage medium of claim 15 , wherein determining that the first responsive resource is associated with enrichment information comprises: identifying responsive enrichment information, responsive enrichment information being enrichment information that is responsive to the query; and determining that the first responsive resource is associated with the responsive enrichment information. 17. The computer storage medium of claim 16 , wherein identifying the responsive enrichment information is performed in parallel with identifying the responsive resources. | 0.5 |
8,027,973 | 15 | 20 | 15. A computing device for determining the relevance of questions related to a queried question, comprising: a data store storing a collection of questions, each question having a topic of one or more terms and a focus of one or more terms; a memory storing computer-executable instructions of: a first component that receives a queried question having terms; a second component that identifies a queried topic and a queried focus of the queried question; and a third component that, for each of a plurality of questions of the collection, generates a score indicating the relevance of the question to the queried question using a language model of the topic of the question and a language model of the focus of the question; and a processor that executes the computer-executable instructions stored in the memory. | 15. A computing device for determining the relevance of questions related to a queried question, comprising: a data store storing a collection of questions, each question having a topic of one or more terms and a focus of one or more terms; a memory storing computer-executable instructions of: a first component that receives a queried question having terms; a second component that identifies a queried topic and a queried focus of the queried question; and a third component that, for each of a plurality of questions of the collection, generates a score indicating the relevance of the question to the queried question using a language model of the topic of the question and a language model of the focus of the question; and a processor that executes the computer-executable instructions stored in the memory. 20. The computing device of claim 15 wherein the third component that generates the scores factors in a translation probability that a term of the queried question is a translation of a term of a question. | 0.586694 |
9,356,940 | 1 | 5 | 1. A method for providing system security and access based on multi-dimensional location characteristics, comprising: collecting contextual information characterizing a specific location during a first time period utilizing a contextual data collection device (CDCD), wherein the contextual information indicates specific characteristics of the location and is collected at the location, and wherein the contextual information includes range information from a single perspective to at least two key materials located at the specific location, and wherein the contextual information further includes measured effect data acquired using dual frequency measurements of dielectric content of intervening material, wherein the measured effect data is a measured effect of the intervening materials on radio frequency (RF) signals received at the CDCD from a remote RF source; creating a contextual location fingerprint (CLF) based on the collected contextual information, wherein the CLF is a data space of values mapped over specific period of time; collecting new contextual information at a location occupied by a device to be verified during a second time period, wherein the new contextual information includes range information from the single perspective to at least two of the key materials located at the specific location; and comparing the new contextual information to the CLF and authenticating the device when the new contextual information is within predefined parameters of the CLF. | 1. A method for providing system security and access based on multi-dimensional location characteristics, comprising: collecting contextual information characterizing a specific location during a first time period utilizing a contextual data collection device (CDCD), wherein the contextual information indicates specific characteristics of the location and is collected at the location, and wherein the contextual information includes range information from a single perspective to at least two key materials located at the specific location, and wherein the contextual information further includes measured effect data acquired using dual frequency measurements of dielectric content of intervening material, wherein the measured effect data is a measured effect of the intervening materials on radio frequency (RF) signals received at the CDCD from a remote RF source; creating a contextual location fingerprint (CLF) based on the collected contextual information, wherein the CLF is a data space of values mapped over specific period of time; collecting new contextual information at a location occupied by a device to be verified during a second time period, wherein the new contextual information includes range information from the single perspective to at least two of the key materials located at the specific location; and comparing the new contextual information to the CLF and authenticating the device when the new contextual information is within predefined parameters of the CLF. 5. A method as recited in claim 1 , wherein a key material is a door. | 0.758741 |
9,348,915 | 6 | 7 | 6. A computer-implemented method comprising: determining, by a computing device, popularity values for a plurality of content items based on a corresponding type of content item, wherein a popularity value for a first type of content item is determined differently than a popularity value for a second type of content item; receiving a search query; modifying the popularity values based on the search query; comparing a first modified popularity value of a first content item of at least two content items to a second modified popularity value of a second content item of the at least two content items; in response to determining that the first modified popularity value is equal to the second modified popularity value, ranking the first content item and the second content item based on a factor other than modified popularity value; and in response to the ranking, returning a ranked list of the at least two content items of the plurality of content items as results for the search query. | 6. A computer-implemented method comprising: determining, by a computing device, popularity values for a plurality of content items based on a corresponding type of content item, wherein a popularity value for a first type of content item is determined differently than a popularity value for a second type of content item; receiving a search query; modifying the popularity values based on the search query; comparing a first modified popularity value of a first content item of at least two content items to a second modified popularity value of a second content item of the at least two content items; in response to determining that the first modified popularity value is equal to the second modified popularity value, ranking the first content item and the second content item based on a factor other than modified popularity value; and in response to the ranking, returning a ranked list of the at least two content items of the plurality of content items as results for the search query. 7. The computer-implemented method of claim 6 , wherein the search query is received prior to determining the corresponding popularity values for the at least two content items. | 0.719048 |
9,672,246 | 1 | 10 | 1. A method, comprising: storing a plurality of timeslicing tables corresponding with a time-dependent attribute in a database, the plurality of timeslicing tables includes a first timeslicing table corresponding with the time-dependent attribute over a first time period and a second timeslicing table corresponding with the time-dependent attribute over a second time period, the plurality of timeslicing tables includes a third timeslicing table corresponding with the time-dependent attribute over a third time period; detecting a data update to the time-dependent attribute within the first time period; determining a historical rate of data updates associated with the time-dependent attribute over the first time period and the second time period; detecting that the historical rate of data updates associated with the time-dependent attribute over the first time period and the second time period is greater than an updating threshold; replacing the first timeslicing table and the second timeslicing table within the database with a character large object representation for the time-dependent attribute over the first time period and the second time period in response to detecting that the historical rate of data updates associated with the time-dependent attribute over the first time period and the second time period is greater than the updating threshold; acquiring a query for one or more data values associated with the time-dependent attribute; retrieving the third timeslicing table corresponding with the time-dependent attribute from the database in response to acquiring the query, the third timeslicing table corresponding with the time-dependent attribute over the third time period is stored as a binary large object within the database; retrieving the character large object representation for the time-dependent attribute over the first time period and the second time period from the database in response to acquiring the query, the character large object representation for the time-dependent attribute over the first time period and the second time period is stored as a character large object within the database; generating a plurality of segments using the character large object representation for the time-dependent attribute; determining the one or more data values associated with the time-dependent attribute using the plurality of segments and the third timeslicing table; and outputting the one or more data values associated with the time-dependent attribute. | 1. A method, comprising: storing a plurality of timeslicing tables corresponding with a time-dependent attribute in a database, the plurality of timeslicing tables includes a first timeslicing table corresponding with the time-dependent attribute over a first time period and a second timeslicing table corresponding with the time-dependent attribute over a second time period, the plurality of timeslicing tables includes a third timeslicing table corresponding with the time-dependent attribute over a third time period; detecting a data update to the time-dependent attribute within the first time period; determining a historical rate of data updates associated with the time-dependent attribute over the first time period and the second time period; detecting that the historical rate of data updates associated with the time-dependent attribute over the first time period and the second time period is greater than an updating threshold; replacing the first timeslicing table and the second timeslicing table within the database with a character large object representation for the time-dependent attribute over the first time period and the second time period in response to detecting that the historical rate of data updates associated with the time-dependent attribute over the first time period and the second time period is greater than the updating threshold; acquiring a query for one or more data values associated with the time-dependent attribute; retrieving the third timeslicing table corresponding with the time-dependent attribute from the database in response to acquiring the query, the third timeslicing table corresponding with the time-dependent attribute over the third time period is stored as a binary large object within the database; retrieving the character large object representation for the time-dependent attribute over the first time period and the second time period from the database in response to acquiring the query, the character large object representation for the time-dependent attribute over the first time period and the second time period is stored as a character large object within the database; generating a plurality of segments using the character large object representation for the time-dependent attribute; determining the one or more data values associated with the time-dependent attribute using the plurality of segments and the third timeslicing table; and outputting the one or more data values associated with the time-dependent attribute. 10. The method of claim 1 , wherein: the plurality of segments includes a first segment and a second segment, the determining the one or more data values comprises adding a product of a rate of the first segment and a fraction of a duration of the first segment to the product of a rate of the second segment and a fraction of a duration of the second segment. | 0.776398 |
9,530,070 | 1 | 6 | 1. An apparatus comprising a non-transitory computer readable storage medium storing a program having instructions which when executed by a processor will cause the processor to parse text in complex graphical images, the instructions of the program for: obtaining a series of blocks of text from a complex graphical image along with associated location coordinates, identifying a location within the complex graphical image, and bounding box data, indicating a size for each block of text within the complex graphical image, for each block of the series; generating location scores for each of the series of blocks of text using locations within the complex graphical image such that blocks closest to a lower, right-hand corner receive a location score of 1.0 and blocks closest to an upper, left hand corner receive a location score of 0.0 with interpolation used to generate location scores for those blocks located in between; generating size scores for each of the series of blocks of text using sizes of each of the series of blocks of text such that largest size blocks receive a size score of 1.0 and smallest size blocks receives a size score of 0.0 with interpolation used to generate size scores for those blocks with sizes in between; weighting each location score by multiplying by a location weighting to create a weighted location score; weighting each size score by multiplying by a size weighting to create a weighted size score; linearly summing each of the weighted location score and the weighted size score to derive an overall score for each block of text of the series; identifying a highest score text block associated with a highest overall score as the most likely to be a desired text block; and repeating each instruction above for each page of a multi-page document made up of a series of complex graphical images. | 1. An apparatus comprising a non-transitory computer readable storage medium storing a program having instructions which when executed by a processor will cause the processor to parse text in complex graphical images, the instructions of the program for: obtaining a series of blocks of text from a complex graphical image along with associated location coordinates, identifying a location within the complex graphical image, and bounding box data, indicating a size for each block of text within the complex graphical image, for each block of the series; generating location scores for each of the series of blocks of text using locations within the complex graphical image such that blocks closest to a lower, right-hand corner receive a location score of 1.0 and blocks closest to an upper, left hand corner receive a location score of 0.0 with interpolation used to generate location scores for those blocks located in between; generating size scores for each of the series of blocks of text using sizes of each of the series of blocks of text such that largest size blocks receive a size score of 1.0 and smallest size blocks receives a size score of 0.0 with interpolation used to generate size scores for those blocks with sizes in between; weighting each location score by multiplying by a location weighting to create a weighted location score; weighting each size score by multiplying by a size weighting to create a weighted size score; linearly summing each of the weighted location score and the weighted size score to derive an overall score for each block of text of the series; identifying a highest score text block associated with a highest overall score as the most likely to be a desired text block; and repeating each instruction above for each page of a multi-page document made up of a series of complex graphical images. 6. The apparatus of claim 1 further wherein the instructions of the program are further for: filtering out blocks of text that do not incorporate a word from a language; generating a length score for each of the series of blocks of text such that those text blocks that contain the most characters receive length scores of 1.0 and those blocks with the fewest characters receive length scores of 0.0 with interpolation used to generate length scores for those blocks with lengths in between; weighting each length score by multiplying by a length weighting to create a weighted length score; and linearly summing the overall score and the weighted length score to derive the overall score for each block of text of the series before identifying the highest score text block associated with the highest overall score as the most likely to be the desired text block. | 0.5 |
9,405,448 | 4 | 7 | 4. A method according to claim 3 , further comprising: identifying one or more patterns in the another data channel by: assigning an importance level to one or more unexpected patterns; and identifying one or more significant patterns of the one or more unexpected patterns, wherein a significant pattern is an unexpected pattern. | 4. A method according to claim 3 , further comprising: identifying one or more patterns in the another data channel by: assigning an importance level to one or more unexpected patterns; and identifying one or more significant patterns of the one or more unexpected patterns, wherein a significant pattern is an unexpected pattern. 7. A method according to claim 4 , further comprising: generating the graph based on the graphical output, wherein the graph comprises at least a portion of the data channel that contains the one or more key events, the another data channel that contains the one or more significant events and the one or more contextual channels, the at least a portion of the one or more key events, the one or more significant events and the one or more contextual channels being annotated by the one or more phrases. | 0.5 |
9,846,726 | 10 | 16 | 10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to: receive a search phrase submitted in association with a user profile with a online system; generate, from the search phrase, a structured query that includes a first object with a first object attribute that is connected to a second object in the online system; store the structured query in association with the user profile; perform, at a first time, a first search by the online system identifying a first set of objects matching the structured query; generate, for the structured query, a list of links to the first set of objects; perform, at a second time, a second search by the online system identifying a second set of objects matching the structured query; and update the list of links for the structured query to include links to the second set of objects. | 10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to: receive a search phrase submitted in association with a user profile with a online system; generate, from the search phrase, a structured query that includes a first object with a first object attribute that is connected to a second object in the online system; store the structured query in association with the user profile; perform, at a first time, a first search by the online system identifying a first set of objects matching the structured query; generate, for the structured query, a list of links to the first set of objects; perform, at a second time, a second search by the online system identifying a second set of objects matching the structured query; and update the list of links for the structured query to include links to the second set of objects. 16. The non-transitory computer readable storage medium of claim 10 , wherein the instructions when executed by the computing device further cause the computing device to: update a reverse index to include an identifier for the search phrase, the reverse index storing a plurality of search phrase identifiers based on the first object and the second object in the search phrases. | 0.555035 |
9,972,300 | 1 | 8 | 1. A method for generating synthesized speech using parametric models, the method comprising the steps of: a. selecting sentences from a database of speech audio files, wherein the sentences comprise a plurality of phonemes; b. identifying a total sum of instance outliers for each of the plurality of phonemes, wherein the instance outliers comprise fundamental frequency based outliers and group delay based outliers; c. ignoring the sentences wherein the total sum of instance outliers exceeds a sentence outlier threshold and retaining sentences wherein the total sum of instance outliers meets the sentence outlier threshold; d. using the retained sentences to generate trained Hidden Markov Models; e. generating a plurality of context dependent Hidden Markov Models using the trained Hidden Markov Models, spectrum parameters, and excitation parameters, wherein the spectrum parameters and excitation parameters are extracted from the database of speech audio files using the trained Hidden Markov Models; f. analyzing a selected text and generating text excitation parameters and text spectral parameters using the plurality of context dependent Hidden Markov Models; g. generating a text excitation signal using the text excitation parameters; and h. generating a synthesized speech waveform by passing the text excitation signal and text spectral parameters into a synthesis filter. | 1. A method for generating synthesized speech using parametric models, the method comprising the steps of: a. selecting sentences from a database of speech audio files, wherein the sentences comprise a plurality of phonemes; b. identifying a total sum of instance outliers for each of the plurality of phonemes, wherein the instance outliers comprise fundamental frequency based outliers and group delay based outliers; c. ignoring the sentences wherein the total sum of instance outliers exceeds a sentence outlier threshold and retaining sentences wherein the total sum of instance outliers meets the sentence outlier threshold; d. using the retained sentences to generate trained Hidden Markov Models; e. generating a plurality of context dependent Hidden Markov Models using the trained Hidden Markov Models, spectrum parameters, and excitation parameters, wherein the spectrum parameters and excitation parameters are extracted from the database of speech audio files using the trained Hidden Markov Models; f. analyzing a selected text and generating text excitation parameters and text spectral parameters using the plurality of context dependent Hidden Markov Models; g. generating a text excitation signal using the text excitation parameters; and h. generating a synthesized speech waveform by passing the text excitation signal and text spectral parameters into a synthesis filter. 8. The method of claim 1 wherein the step of identifying group delay based outliers further comprises: a. generating syllable alignments for each of the plurality of phonemes using a speech recognition system and a phoneme model; b. making adjustments to the syllable alignments using group delay algorithms; c. splitting the syllable alignments and analyzing the split syllable assignments for pooling information; d. generating phoneme boundaries for each of the split syllables using the phoneme model; e. determining likelihood values for each of the generated phoneme boundaries, wherein the likelihood values comprise log-likelihood values; f. determining whether generating the syllable alignment has failed or if the likelihood value is too small; and g. identifying a sum of instance outliers for each of the generated phoneme boundaries. | 0.5 |
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