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8,965,919 | 3 | 4 | 3. The method of 1 , further comprising: receiving another text string; determining that the other text string and the modified text string are associated with the similar concept; and determining one or more search results for the other text string by using the modified text string. | 3. The method of 1 , further comprising: receiving another text string; determining that the other text string and the modified text string are associated with the similar concept; and determining one or more search results for the other text string by using the modified text string. 4. The method of claim 3 , where the plurality of terms in the text string and a plurality of terms in the other text string are the same. | 0.5 |
7,483,947 | 8 | 9 | 8. The system of claim 1 , the character-only format is a text-only format. | 8. The system of claim 1 , the character-only format is a text-only format. 9. The system of claim 8 , the message in text-only format is processed to analyze a word or plurality of words for at least one of font size, brightness, special formatting, and placement in a link. | 0.5 |
9,082,310 | 50 | 55 | 50. The non-transitory computer-readable medium of claim 34 , wherein the method further comprises: instructions to automatically generate a first answer to the first question instance based on the first question instance and the data set. | 50. The non-transitory computer-readable medium of claim 34 , wherein the method further comprises: instructions to automatically generate a first answer to the first question instance based on the first question instance and the data set. 55. The non-transitory computer-readable medium of claim 50 , wherein the first answer includes at least one pointer to at least one portion of the data set relied upon in the instructions to automatically generate a first answer to generate the first answer. | 0.750962 |
8,805,083 | 18 | 19 | 18. The method as recited in claim 17 , wherein said simultaneous sparse approximation is of a greedy adaptive decomposition (GAD) type, said candidate spectral components being established within the general dictionary, said candidate spectral components each being defined either as a continuous function or as a discrete vector. | 18. The method as recited in claim 17 , wherein said simultaneous sparse approximation is of a greedy adaptive decomposition (GAD) type, said candidate spectral components being established within the general dictionary, said candidate spectral components each being defined either as a continuous function or as a discrete vector. 19. The method as recited in claim 18 , wherein at least one set of selectively grouped image data vectors are disposed in spatially contiguous manner within the spatial image plane. | 0.745098 |
8,914,284 | 1 | 4 | 1. A method of converting and transmitting audio information, comprising: receiving spoken audio input; converting the received spoken audio input into digital data that is representative of the received spoken audio input, wherein converting the received spoken audio input into digital data comprises creating a stream of digital data pockets, each digital data packet having a payload of data representative of a portion of the received spoken audio input; generating a textual representation of the received spoken audio input; inserting portions of the textual representation of the received spoken audio input into one or more headers of the digital data packets; and transmitting corresponding portions of the digital data and the textual representation to a destination device at substantially the same time. | 1. A method of converting and transmitting audio information, comprising: receiving spoken audio input; converting the received spoken audio input into digital data that is representative of the received spoken audio input, wherein converting the received spoken audio input into digital data comprises creating a stream of digital data pockets, each digital data packet having a payload of data representative of a portion of the received spoken audio input; generating a textual representation of the received spoken audio input; inserting portions of the textual representation of the received spoken audio input into one or more headers of the digital data packets; and transmitting corresponding portions of the digital data and the textual representation to a destination device at substantially the same time. 4. The method of claim 1 , wherein generating a textual representation of the received spoken audio input comprises: extracting phonemes from the received spoken audio input; and generating a textual representation of the extracted phonemes. | 0.630368 |
9,971,893 | 9 | 10 | 9. A computer program product, comprising one or more computer readable hardware storage devices having computer readable program code stored therein, said program code containing instructions executable by one or more processors of a computer system to implement a method, said method comprising: a first computer executing a plurality of text blocks of code derived from a script from a web page in response to a request for the web page from a client computer, said text blocks executed sequentially in a sequential order, wherein the script is a first text block of the plurality of text blocks, the execution of one text block of the plurality of text blocks by the first computer generating a new text block of code; and said first computer determining that the new text block includes malicious code and in response, said first computer preventing transmission of the web page to the client computer. | 9. A computer program product, comprising one or more computer readable hardware storage devices having computer readable program code stored therein, said program code containing instructions executable by one or more processors of a computer system to implement a method, said method comprising: a first computer executing a plurality of text blocks of code derived from a script from a web page in response to a request for the web page from a client computer, said text blocks executed sequentially in a sequential order, wherein the script is a first text block of the plurality of text blocks, the execution of one text block of the plurality of text blocks by the first computer generating a new text block of code; and said first computer determining that the new text block includes malicious code and in response, said first computer preventing transmission of the web page to the client computer. 10. The computer program product of claim 9 , said method comprising: said first computer copying each text block to an output file in a data storage area of the first computer, wherein thy: first text block is copied before another text block of the plurality of text blocks is copied. | 0.5 |
8,793,646 | 1 | 6 | 1. A method comprising: reading a stereotype of a first profile from a computer readable storage medium, wherein the stereotype defines constraints to be applied to a model associated with the first profile; determining that the stereotype indicates a second profile and a third profile; accessing the second profile and the third profile; and aggregating 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. | 1. A method comprising: reading a stereotype of a first profile from a computer readable storage medium, wherein the stereotype defines constraints to be applied to a model associated with the first profile; determining that the stereotype indicates a second profile and a third profile; accessing the second profile and the third profile; and aggregating 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. 6. The method of claim 1 , wherein the modeling language comprises the unified modeling language. | 0.733516 |
8,752,011 | 1 | 7 | 1. A method for automatically generating a user interface for a computer program using programming patterns, the method comprising: analyzing application objects of an application computer program to identify programming patterns, wherein each programming pattern is a relationship among signatures of application methods in one of the application objects, and wherein the signatures of the application methods comprise public interfaces of the application methods; automatically generating a user interface for the computer program, wherein automatically generating a user interface includes providing for at least one of a user and a programmer of the computer program to customize mappings between the application objects and user interface elements, wherein the user interface elements include at least one of user interface widgets and speech grammar rules, wherein the identified programming patterns include at least one of an undo pattern, a structure pattern, a graphical pattern, a validation pattern, and a precondition pattern, and wherein the undo pattern identifies, for each application method a pattern-based executed-command-object that can undo/redo the method, wherein the pattern-based executed-command-object comprises an executed-command object that uses at least one of: (a) relationships among the signatures of the application methods in and (b) antonym dictionaries to implement the undo and redo operations, and wherein the executed-command object is an object that provides operations to undo and redo each application method. | 1. A method for automatically generating a user interface for a computer program using programming patterns, the method comprising: analyzing application objects of an application computer program to identify programming patterns, wherein each programming pattern is a relationship among signatures of application methods in one of the application objects, and wherein the signatures of the application methods comprise public interfaces of the application methods; automatically generating a user interface for the computer program, wherein automatically generating a user interface includes providing for at least one of a user and a programmer of the computer program to customize mappings between the application objects and user interface elements, wherein the user interface elements include at least one of user interface widgets and speech grammar rules, wherein the identified programming patterns include at least one of an undo pattern, a structure pattern, a graphical pattern, a validation pattern, and a precondition pattern, and wherein the undo pattern identifies, for each application method a pattern-based executed-command-object that can undo/redo the method, wherein the pattern-based executed-command-object comprises an executed-command object that uses at least one of: (a) relationships among the signatures of the application methods in and (b) antonym dictionaries to implement the undo and redo operations, and wherein the executed-command object is an object that provides operations to undo and redo each application method. 7. The method of claim 1 wherein the precondition pattern identifies a precondition method of one of the application methods, wherein the precondition method is a Boolean parameterless method that determines if the associated application method is currently enabled. | 0.807525 |
9,189,064 | 2 | 3 | 2. The method of claim 1 , further comprising: obtaining additional user gaze information; and executing the display event based on the additional user gaze information. | 2. The method of claim 1 , further comprising: obtaining additional user gaze information; and executing the display event based on the additional user gaze information. 3. The method of claim 2 , wherein executing the display event includes one or more of adding a user interface object to a display, removing a user interface object from a display, and animating a user interface object on a display. | 0.5 |
8,694,385 | 1 | 7 | 1. A computer-implemented method for identifying items in response to a query, comprising: under control of one or more computer systems configured with executable instructions, receiving a first query from a first user, the first query including one or more query terms; generating a first query result including one or more items corresponding to the first query; for each respective item in the first query result, determining a ranking value using one or more rating scores, each rating score corresponding to a respective query term and depending at least in part on a first frequency with which selection actions are performed by previous users with respect to the respective item, the selection actions being performed against previous query results generated in response to previous queries that include the respective query term; and presenting at least a portion of the first query result for display to the first user according to the ranking values. | 1. A computer-implemented method for identifying items in response to a query, comprising: under control of one or more computer systems configured with executable instructions, receiving a first query from a first user, the first query including one or more query terms; generating a first query result including one or more items corresponding to the first query; for each respective item in the first query result, determining a ranking value using one or more rating scores, each rating score corresponding to a respective query term and depending at least in part on a first frequency with which selection actions are performed by previous users with respect to the respective item, the selection actions being performed against previous query results generated in response to previous queries that include the respective query term; and presenting at least a portion of the first query result for display to the first user according to the ranking values. 7. The computer-implemented method of claim 1 , wherein the selection actions are performed by previous users corresponding to a first demographic group. | 0.698819 |
7,895,240 | 1 | 2 | 1. A method for managing information comprising: generating a first database in a first memory device; storing, by an administrator via a server system, a plurality of predefined questions in the first database, wherein the plurality of predefined questions relate to project information and include at least a first predefined question and a second predefined question; storing, by the administrator, a plurality of predefined answer options related to the project information, wherein each predefined answer option corresponds to one of the plurality of predefined questions; associating, by the administrator, each of the plurality of predefined answer options with a task by pre-defining, within the first database, a task to be performed based on each of the plurality of predefined answer options; associating, by the administrator, a plurality of tools used to complete a task with each task, wherein said plurality of tools includes at least one expert on a task; providing, via a computer, to a user, the plurality of predefined questions and the plurality of predefined answer options; receiving a plurality of answers from the user, wherein the plurality of answers are chosen by the user from the provided plurality of predefined answer options, and wherein at least one answer option associated with the second predefined question is modified based on an answer from the first predefined question from the user, wherein modifying at least one answer option comprises at least one of adding at least one answer option associated with the second predefined question and removing at least one answer option associated with the second predefined question; determining, by the computer, a task and tools based on the plurality of answers provided by the user; creating at least one additional database in a second memory device based on the plurality of predefined answer options; associating the first database with the at least one additional database based on the plurality of answers provided by the user without making a change to at least one source code; populating the at least one additional database with the determined task; and prompting the user to customize the determined task within the at least one additional database, without changing the at least one source code, after the at least one additional database has been populated. | 1. A method for managing information comprising: generating a first database in a first memory device; storing, by an administrator via a server system, a plurality of predefined questions in the first database, wherein the plurality of predefined questions relate to project information and include at least a first predefined question and a second predefined question; storing, by the administrator, a plurality of predefined answer options related to the project information, wherein each predefined answer option corresponds to one of the plurality of predefined questions; associating, by the administrator, each of the plurality of predefined answer options with a task by pre-defining, within the first database, a task to be performed based on each of the plurality of predefined answer options; associating, by the administrator, a plurality of tools used to complete a task with each task, wherein said plurality of tools includes at least one expert on a task; providing, via a computer, to a user, the plurality of predefined questions and the plurality of predefined answer options; receiving a plurality of answers from the user, wherein the plurality of answers are chosen by the user from the provided plurality of predefined answer options, and wherein at least one answer option associated with the second predefined question is modified based on an answer from the first predefined question from the user, wherein modifying at least one answer option comprises at least one of adding at least one answer option associated with the second predefined question and removing at least one answer option associated with the second predefined question; determining, by the computer, a task and tools based on the plurality of answers provided by the user; creating at least one additional database in a second memory device based on the plurality of predefined answer options; associating the first database with the at least one additional database based on the plurality of answers provided by the user without making a change to at least one source code; populating the at least one additional database with the determined task; and prompting the user to customize the determined task within the at least one additional database, without changing the at least one source code, after the at least one additional database has been populated. 2. The method in accordance with claim 1 wherein at least one of said generating and said creating is performed without making a change to at least one source code. | 0.870458 |
9,579,057 | 7 | 10 | 7. A computer program product (CPP) tangibly embodied in a non-transitory computer readable storage device and containing instructions that, when executed, cause a processor to perform operations to determine an optimal treatment plan by measuring personal degrees of expression of facial features in terms of Specific features, Relative distances, Elevations, Depression, Interacting features, and Coactivated distances (SREDIC) scores specifying expression intensity of individual Facial Expression Activated Markers (FEAMs) that are functionally classified and analyzed as personal relative distances between features, facial deformations and co-activated features before and after for using agents or procedures capable of modifying FEAMs, the operations comprising: receiving an image file of a human face, the image file corresponding to a facial expression desired to be changed by a user; sending for display on a display device the received image file; receiving, from the user, information representative of a desired degree of change in the expression intensity of one or more selected Facial-Expression Activation Markers (FEAMs) to obtain a more desirable facial expression; retrieving a SREDIC score that is associated with the selected one or more FEAMs, wherein the SREDIC score is based on personal relative distances between features, facial deformations and co-activated features of the user associated with the selected FEAMs, and corresponding facial muscles or facial muscle groups, each of the corresponding facial muscles or facial muscle groups having an activation intensity level specified in terms of the degree and gradation level of FEAMs expressions; retrieving psychophysiological states whose SREDIC scores are shared with, or functionally related to corresponding facial muscles or facial muscle groups of the selected SREDIC score; receiving image files corresponding with the retrieved psycho-physiological states; receiving, from the user, information representative of desired changes in the activation intensity of the FEAMs for two or more of the retrieved expressions of psychophysiological states; and, generating, in response to the SREDIC score, the retrieved expressions of psychophysiological states, and the received desired degree of change in the expression intensity, a treatment program comprising one or more treatment locations, each of the one or more treatment locations targeting one of the one or more treatments for optimally approximating the desired facial expression while producing optimized corresponding changes in the expression of each of two or more psycho-physiological states, each of the one or more treatment locations targeting one of the one or more selected FEAMs and corresponding facial muscles or facial muscle groups of a SREDIC score functionally associated with the one of the one or more selected FEAMs, each of the one or more treatment locations having an associated treatment and dosage information. | 7. A computer program product (CPP) tangibly embodied in a non-transitory computer readable storage device and containing instructions that, when executed, cause a processor to perform operations to determine an optimal treatment plan by measuring personal degrees of expression of facial features in terms of Specific features, Relative distances, Elevations, Depression, Interacting features, and Coactivated distances (SREDIC) scores specifying expression intensity of individual Facial Expression Activated Markers (FEAMs) that are functionally classified and analyzed as personal relative distances between features, facial deformations and co-activated features before and after for using agents or procedures capable of modifying FEAMs, the operations comprising: receiving an image file of a human face, the image file corresponding to a facial expression desired to be changed by a user; sending for display on a display device the received image file; receiving, from the user, information representative of a desired degree of change in the expression intensity of one or more selected Facial-Expression Activation Markers (FEAMs) to obtain a more desirable facial expression; retrieving a SREDIC score that is associated with the selected one or more FEAMs, wherein the SREDIC score is based on personal relative distances between features, facial deformations and co-activated features of the user associated with the selected FEAMs, and corresponding facial muscles or facial muscle groups, each of the corresponding facial muscles or facial muscle groups having an activation intensity level specified in terms of the degree and gradation level of FEAMs expressions; retrieving psychophysiological states whose SREDIC scores are shared with, or functionally related to corresponding facial muscles or facial muscle groups of the selected SREDIC score; receiving image files corresponding with the retrieved psycho-physiological states; receiving, from the user, information representative of desired changes in the activation intensity of the FEAMs for two or more of the retrieved expressions of psychophysiological states; and, generating, in response to the SREDIC score, the retrieved expressions of psychophysiological states, and the received desired degree of change in the expression intensity, a treatment program comprising one or more treatment locations, each of the one or more treatment locations targeting one of the one or more treatments for optimally approximating the desired facial expression while producing optimized corresponding changes in the expression of each of two or more psycho-physiological states, each of the one or more treatment locations targeting one of the one or more selected FEAMs and corresponding facial muscles or facial muscle groups of a SREDIC score functionally associated with the one of the one or more selected FEAMs, each of the one or more treatment locations having an associated treatment and dosage information. 10. The computer program product of claim 7 , further comprising instructions that, when executed, send control commands to the image capture device and receive image files from an image capture device. | 0.651724 |
9,298,778 | 1 | 7 | 1. A computer implemented method, comprising: receiving a stream of content including a plurality of content items; retrieving a plurality of related content items; identifying a topic for at least one of the plurality of the related content items; ranking the topics by relevance to a user and one of the plurality of content items; associating the topic to the content item in the stream of content where the topic is ranked as being relevant to the content item; generating a marker for the topic; generating a user interface including one or more tiles and the generated marker rendered with at least one tile, the one or more tiles being an element on the user interface, each of the one or more tiles corresponding to a content item in the stream of content, and the generated marker being presented as a hash tag rendered with the at least one tile and representing association with the content item on the tile providing the user interface for display; translating a user input from the user interface to navigation of the user interface; and updating the user interface based on the user input navigation and placement of the marker. | 1. A computer implemented method, comprising: receiving a stream of content including a plurality of content items; retrieving a plurality of related content items; identifying a topic for at least one of the plurality of the related content items; ranking the topics by relevance to a user and one of the plurality of content items; associating the topic to the content item in the stream of content where the topic is ranked as being relevant to the content item; generating a marker for the topic; generating a user interface including one or more tiles and the generated marker rendered with at least one tile, the one or more tiles being an element on the user interface, each of the one or more tiles corresponding to a content item in the stream of content, and the generated marker being presented as a hash tag rendered with the at least one tile and representing association with the content item on the tile providing the user interface for display; translating a user input from the user interface to navigation of the user interface; and updating the user interface based on the user input navigation and placement of the marker. 7. The method of claim 1 wherein a vector and a direction of input are used to update the generated user interface to show in situ with the stream of content, control or status information. | 0.622 |
8,180,751 | 8 | 9 | 8. A tangible computer readable storage medium having instructions for causing a computer to execute a method, comprising: identifying documents that include a name of an individual; comparing the documents with articles in an encyclopedia; summarizing the documents with content from the articles in the encyclopedia to build a user profile of the individual; and using the user profile to respond to search queries. | 8. A tangible computer readable storage medium having instructions for causing a computer to execute a method, comprising: identifying documents that include a name of an individual; comparing the documents with articles in an encyclopedia; summarizing the documents with content from the articles in the encyclopedia to build a user profile of the individual; and using the user profile to respond to search queries. 9. The tangible computer readable storage medium of claim 8 further comprising, using titles of the articles in the encyclopedia to provide summaries for the documents. | 0.79759 |
8,566,305 | 3 | 4 | 3. The method of claim 1 , further comprising: applying a set of detection conditions to the at least one of the plurality of messages containing data that matches the data in at least one of the specified columns. | 3. The method of claim 1 , further comprising: applying a set of detection conditions to the at least one of the plurality of messages containing data that matches the data in at least one of the specified columns. 4. The method of claim 3 , wherein applying the set of detection conditions comprises: determining whether a sender of the at least one of the plurality of messages has a history of prior violations. | 0.592213 |
8,150,838 | 6 | 10 | 6. A method comprising: receive a first query with a first query data format and a second query with a second query data format, the first query data format being distinct from the second query data format; generate a common metadata based query object by converting the first query and the second query into a common metadata format that includes first metadata for the first query, second metadata for the second query, first data associated with the first query, and second data associated with the second query; wherein the metadata includes a condition value for a condition in the query; extract first the metadata and the second metadata from the common metadata based query object; generate a first application specific query based on the first metadata and a first application to which the first query is intended; generate a second application specific query based on the second metadata and a second application to which the second query is intended; and wherein the application is configured for a specific enterprise information system. | 6. A method comprising: receive a first query with a first query data format and a second query with a second query data format, the first query data format being distinct from the second query data format; generate a common metadata based query object by converting the first query and the second query into a common metadata format that includes first metadata for the first query, second metadata for the second query, first data associated with the first query, and second data associated with the second query; wherein the metadata includes a condition value for a condition in the query; extract first the metadata and the second metadata from the common metadata based query object; generate a first application specific query based on the first metadata and a first application to which the first query is intended; generate a second application specific query based on the second metadata and a second application to which the second query is intended; and wherein the application is configured for a specific enterprise information system. 10. The method of claim 6 , wherein the metadata includes a condition type for a condition in the query. | 0.638889 |
9,965,561 | 1 | 2 | 1. A method of collecting search data from a plurality of user computing devices, the method comprising: sending, by one or more first computing devices to a second computing device, a browser-executable component, wherein the browser-executable component is configured to be executed in response to a browser accessing a search engine, wherein the browser-executable component is further configured to obtain usage data corresponding to a search query and to generate a search record for transmission to the one or more first computing devices; receiving, by the one or more first computing devices, the search record, wherein the search record includes the usage data obtained by the browser-executable component, the search record including one or more of a code corresponding to an instance of execution of the browser-executable component, location information, or a selected parameter; and storing, by the one or more first computing devices, search activity data as a collection of search records that includes the search record, wherein the search records in the search activity data are indexed in a manner that does not identify a user of the second computing device. | 1. A method of collecting search data from a plurality of user computing devices, the method comprising: sending, by one or more first computing devices to a second computing device, a browser-executable component, wherein the browser-executable component is configured to be executed in response to a browser accessing a search engine, wherein the browser-executable component is further configured to obtain usage data corresponding to a search query and to generate a search record for transmission to the one or more first computing devices; receiving, by the one or more first computing devices, the search record, wherein the search record includes the usage data obtained by the browser-executable component, the search record including one or more of a code corresponding to an instance of execution of the browser-executable component, location information, or a selected parameter; and storing, by the one or more first computing devices, search activity data as a collection of search records that includes the search record, wherein the search records in the search activity data are indexed in a manner that does not identify a user of the second computing device. 2. The method of claim 1 , wherein the search records in the search activity data are indexed using an ID field for a log entry number that does not identify a user of the second computing device. | 0.679739 |
9,405,855 | 1 | 2 | 1. A computer-implemented method comprising: accessing a data graph stored in memory of a database management system, wherein the data graph comprises a first plurality of vertices; receiving a query graph, wherein the query graph comprises a second plurality of vertices, and wherein the query graph causes the database management system to retrieve data from the data graph as specified in the query graph; executing in the database management system, the query graph against the data graph stored in the memory, wherein the execution generates an empty data set indicating data specified in the query graph does not exist in the data graph when the data specified in the query graph exists in the data graph; and based on the empty data set, generating a discovered component and a missing component of the query graph, wherein the discovered component includes a first vertex from the first and second plurality of vertices, and the missing component includes a second vertex from the second plurality of vertices that causes the database management system to generate the empty data set when executing the query graph. | 1. A computer-implemented method comprising: accessing a data graph stored in memory of a database management system, wherein the data graph comprises a first plurality of vertices; receiving a query graph, wherein the query graph comprises a second plurality of vertices, and wherein the query graph causes the database management system to retrieve data from the data graph as specified in the query graph; executing in the database management system, the query graph against the data graph stored in the memory, wherein the execution generates an empty data set indicating data specified in the query graph does not exist in the data graph when the data specified in the query graph exists in the data graph; and based on the empty data set, generating a discovered component and a missing component of the query graph, wherein the discovered component includes a first vertex from the first and second plurality of vertices, and the missing component includes a second vertex from the second plurality of vertices that causes the database management system to generate the empty data set when executing the query graph. 2. The computer-implemented method of claim 1 , further comprising: receiving a query specifying the data in the data graph; and converting the query into the query graph. | 0.784635 |
10,061,476 | 1 | 6 | 1. A non-transitory computer readable storage medium comprising instructions for enabling a user to select one or more items from a plurality of items, the medium comprising instructions that, when executed on a computer system, cause the computer system to at least: access through the computer system the plurality of items for selection by the user; present through a user interface of the computer system to the user one or more selectable mood identifiers for selection by the user, wherein each selectable mood identifier among the one or more selectable mood identifiers includes a first range of intensities of at least one mood; enable the user to select a first point within the first range; automatically generate a first span around the first point, the first span including a first subrange of additional points within at least the first range on at least one side of the first point; in response to the user selection, search with the computer system the plurality of items, each item among the plurality of items having been assigned one or more pre-determined mood identifiers by an entity other than the user, wherein each pre-determined mood identifier among the one or more pre-determined mood identifiers includes a second span representing a set of additional points within at least a second range of intensities of at least one mood; as a result of the search, generate a list of items corresponding to the one or more items where the order of the list of items is based on a level of correspondence between at least the first span of the one or more selectable mood identifiers selected by the user and at least the second span of the pre-determined mood identifiers assigned to the items; and present to the user through the user interface the list of items. | 1. A non-transitory computer readable storage medium comprising instructions for enabling a user to select one or more items from a plurality of items, the medium comprising instructions that, when executed on a computer system, cause the computer system to at least: access through the computer system the plurality of items for selection by the user; present through a user interface of the computer system to the user one or more selectable mood identifiers for selection by the user, wherein each selectable mood identifier among the one or more selectable mood identifiers includes a first range of intensities of at least one mood; enable the user to select a first point within the first range; automatically generate a first span around the first point, the first span including a first subrange of additional points within at least the first range on at least one side of the first point; in response to the user selection, search with the computer system the plurality of items, each item among the plurality of items having been assigned one or more pre-determined mood identifiers by an entity other than the user, wherein each pre-determined mood identifier among the one or more pre-determined mood identifiers includes a second span representing a set of additional points within at least a second range of intensities of at least one mood; as a result of the search, generate a list of items corresponding to the one or more items where the order of the list of items is based on a level of correspondence between at least the first span of the one or more selectable mood identifiers selected by the user and at least the second span of the pre-determined mood identifiers assigned to the items; and present to the user through the user interface the list of items. 6. The non-transitory computer readable storage medium as recited in claim 1 , further comprising instructions that cause the computer system to present through the user interface one or more categories associated with the one or more items for selection by the user that will limit the plurality of items to a distinct group of items. | 0.656057 |
7,640,267 | 1 | 36 | 1. A method of semantically representing a target entity using a semantic object, the method comprising: identifying a set of meta-tags having associated metadata entries to represent attributes associated with the target entity in the semantic object, the semantic object being stored on a computer-readable storage medium; wherein at least one meta-tag of the set of meta-tags is defined using an ontology; storing in a metadata entry in the semantic object on the computer-readable storage medium an attribute including an access policy that specifies how the semantic object is shared over a network; sharing, over a network, the semantic object with a user via a computational device in accordance with the access policy of the semantic object; displaying the semantic object on a display screen of the computational device; creating a second semantic object to represent information resource or tacit information, the second semantic object comprising meta-tags which identify semantic information and rules regarding at least one of: how the second semantic object (i) interacts with, (ii) is manipulated by, and (iii) is displayed to human beings and automated processes; seeking to detect the information resource containing information that is represented by the second semantic object; linking the second semantic object to the information resource to represent the information resource using the second semantic object; wherein the second semantic object is configured to have a link to or from any number of other semantic objects. | 1. A method of semantically representing a target entity using a semantic object, the method comprising: identifying a set of meta-tags having associated metadata entries to represent attributes associated with the target entity in the semantic object, the semantic object being stored on a computer-readable storage medium; wherein at least one meta-tag of the set of meta-tags is defined using an ontology; storing in a metadata entry in the semantic object on the computer-readable storage medium an attribute including an access policy that specifies how the semantic object is shared over a network; sharing, over a network, the semantic object with a user via a computational device in accordance with the access policy of the semantic object; displaying the semantic object on a display screen of the computational device; creating a second semantic object to represent information resource or tacit information, the second semantic object comprising meta-tags which identify semantic information and rules regarding at least one of: how the second semantic object (i) interacts with, (ii) is manipulated by, and (iii) is displayed to human beings and automated processes; seeking to detect the information resource containing information that is represented by the second semantic object; linking the second semantic object to the information resource to represent the information resource using the second semantic object; wherein the second semantic object is configured to have a link to or from any number of other semantic objects. 36. The method of claim 1 , wherein, the semantic object represents streaming media. | 0.874627 |
8,433,237 | 11 | 16 | 11. A method implemented on a computing device having a processor for determining a learner's final grade in an academic course, comprising: using the computing device having the processor to perform the following: selecting a type of natural interaction forum to assess a learner's knowledge of subject matter; attaching a rubric to the selected natural interaction forum, the rubric being used as a benchmark for assessing the learner's knowledge; assigning to the learner a natural interaction assignment that uses the selected natural interaction forum; assessing the learner's knowledge based on the learner's posts in the selected natural interaction forum using a participation metric that measures both statistically and visually a participation of the learner in the natural interactions forum to generate assessment results for the learner; computing a single score from the assessment results corresponding to the learner's grade on the natural interaction assignment; integrating the learner's grade on the natural interaction assignment into a formal gradebook; and producing a final grade for the learner based at least on the learner's grade on the natural interaction assignment. | 11. A method implemented on a computing device having a processor for determining a learner's final grade in an academic course, comprising: using the computing device having the processor to perform the following: selecting a type of natural interaction forum to assess a learner's knowledge of subject matter; attaching a rubric to the selected natural interaction forum, the rubric being used as a benchmark for assessing the learner's knowledge; assigning to the learner a natural interaction assignment that uses the selected natural interaction forum; assessing the learner's knowledge based on the learner's posts in the selected natural interaction forum using a participation metric that measures both statistically and visually a participation of the learner in the natural interactions forum to generate assessment results for the learner; computing a single score from the assessment results corresponding to the learner's grade on the natural interaction assignment; integrating the learner's grade on the natural interaction assignment into a formal gradebook; and producing a final grade for the learner based at least on the learner's grade on the natural interaction assignment. 16. The method of claim 11 , further comprising: using a natural language processing technique to examine learner's post in the selected natural interaction forum for specific topics and keywords that are contained in the rubric; defining results of examination using the natural language processing technique as a natural language processing metric; and assessing the learner's knowledge using the natural language processing metric. | 0.57451 |
8,965,881 | 13 | 17 | 13. A computer system for searching an index, wherein the index has a numeric matrix format, the system comprising: a processing device that receives a search request and executes a plurality of modules to search an index, wherein the index comprises numeric code that includes grammar embedded rules, said modules including: a Normalizer module that converts the search request comprising at least one search term in a format usable with the numeric matrix format; a search module that compares the converted search request and the index, and forms a plurality of blocks, wherein each block defines a match between the index and the search term; and a Processor module that determines the relevance for each match using its associated block; wherein the search module comprises: a Refiner module that operates with a Processor module to normalize a relevance score for documents of different lengths, and manages large documents. | 13. A computer system for searching an index, wherein the index has a numeric matrix format, the system comprising: a processing device that receives a search request and executes a plurality of modules to search an index, wherein the index comprises numeric code that includes grammar embedded rules, said modules including: a Normalizer module that converts the search request comprising at least one search term in a format usable with the numeric matrix format; a search module that compares the converted search request and the index, and forms a plurality of blocks, wherein each block defines a match between the index and the search term; and a Processor module that determines the relevance for each match using its associated block; wherein the search module comprises: a Refiner module that operates with a Processor module to normalize a relevance score for documents of different lengths, and manages large documents. 17. The system of claim 13 , wherein the match is between the search item and a portion of the document. | 0.784232 |
10,162,920 | 1 | 3 | 1. A computer-implemented method for performing out of order name resolution in an electronic design language comprising: receiving, one or more design units associated with an electronic design; registering the one or more design units in a registry database; performing local name resolution for each element reference within at least one of the one or more design units, wherein performing local name resolution is performed out of order as it is not constrained to an order of declarations; in response to registering, identifying at least one element reference upon which local name resolution was not performed and obtaining an appropriate element reference from the registry database; reviewing at least one secondary design unit for one or more local declarations; and performing local name resolution for one or more remaining element references using a design hierarchy. | 1. A computer-implemented method for performing out of order name resolution in an electronic design language comprising: receiving, one or more design units associated with an electronic design; registering the one or more design units in a registry database; performing local name resolution for each element reference within at least one of the one or more design units, wherein performing local name resolution is performed out of order as it is not constrained to an order of declarations; in response to registering, identifying at least one element reference upon which local name resolution was not performed and obtaining an appropriate element reference from the registry database; reviewing at least one secondary design unit for one or more local declarations; and performing local name resolution for one or more remaining element references using a design hierarchy. 3. The computer-implemented method of claim 1 , wherein the element reference is at least one of a package, a class, a class object, a module instance, a function, and a method. | 0.59589 |
8,001,128 | 8 | 11 | 8. The system of claim 7 wherein the processor is configured to: implement an approximation algorithm as a utility of the DBMS. | 8. The system of claim 7 wherein the processor is configured to: implement an approximation algorithm as a utility of the DBMS. 11. The system of claim 8 wherein the DBMS is a relational database system. | 0.857414 |
7,668,372 | 12 | 19 | 12. A method of transforming a template document using a read document, the method including: associating a stored template document with a read document, wherein the stored template document includes at least one field, and wherein the read document includes data; automatically extracting at least some of the data from the read document, wherein the extracted data is located in at least one region of the read document that correspond to the at least one field of the stored template document; displaying the read document on a display screen; receiving an input that associates a region of the read document with a chosen field; and generating a template document, wherein: the template document is a new template document and is transformed to incorporate the chosen field associated with the read document, or the template document is the stored template document and is transformed to incorporate the chosen field associated with the read document. | 12. A method of transforming a template document using a read document, the method including: associating a stored template document with a read document, wherein the stored template document includes at least one field, and wherein the read document includes data; automatically extracting at least some of the data from the read document, wherein the extracted data is located in at least one region of the read document that correspond to the at least one field of the stored template document; displaying the read document on a display screen; receiving an input that associates a region of the read document with a chosen field; and generating a template document, wherein: the template document is a new template document and is transformed to incorporate the chosen field associated with the read document, or the template document is the stored template document and is transformed to incorporate the chosen field associated with the read document. 19. A method according to claim 12 wherein generating the template document includes displaying the stored template document on a display screen and receiving an input to incorporate the chosen field into the stored template document. | 0.766 |
9,953,634 | 9 | 14 | 9. A system for passive training for automatic speech recognition, comprising: at least one processor; and a memory communicatively coupled to the at least one processor, the memory storing instructions which when executed by the at least one processor perform a method comprising: maintaining both a first model and a second model that are configured to detect a spoken keyword or a key phrase in spoken utterances, wherein the spoken utterances comprise words and/or phrases spoken by a user; utilizing only the first model, the first model being a speaker-independent model, to detect the spoken keyword or the key phrase in spoken utterances until the second model has been trained; passively training the second model, using the spoken utterances comprising words and/or phrases spoken by the user, to detect the spoken keyword or the key phrase in the spoken utterances; and in response to completion of the passive training, wherein completion requires performing the passive training with a plurality of the spoken utterances satisfying a predetermined set of criteria, switching from utilizing only the first, speaker-independent model to utilizing only the second, passively trained model to detect the spoken keyword or the key phrase in the spoken utterances, wherein passively training the second model includes selecting at least one utterance from the spoken utterances comprising words and/or phrases spoken by the user according to at least one predetermined criterion, and wherein the at least one pre-determined criterion includes one or more of a determination that a signal-to-noise ratio level of the selected utterance is below a pre-determined level and a determination that a duration of the selected utterance is below a pre-determined time period. | 9. A system for passive training for automatic speech recognition, comprising: at least one processor; and a memory communicatively coupled to the at least one processor, the memory storing instructions which when executed by the at least one processor perform a method comprising: maintaining both a first model and a second model that are configured to detect a spoken keyword or a key phrase in spoken utterances, wherein the spoken utterances comprise words and/or phrases spoken by a user; utilizing only the first model, the first model being a speaker-independent model, to detect the spoken keyword or the key phrase in spoken utterances until the second model has been trained; passively training the second model, using the spoken utterances comprising words and/or phrases spoken by the user, to detect the spoken keyword or the key phrase in the spoken utterances; and in response to completion of the passive training, wherein completion requires performing the passive training with a plurality of the spoken utterances satisfying a predetermined set of criteria, switching from utilizing only the first, speaker-independent model to utilizing only the second, passively trained model to detect the spoken keyword or the key phrase in the spoken utterances, wherein passively training the second model includes selecting at least one utterance from the spoken utterances comprising words and/or phrases spoken by the user according to at least one predetermined criterion, and wherein the at least one pre-determined criterion includes one or more of a determination that a signal-to-noise ratio level of the selected utterance is below a pre-determined level and a determination that a duration of the selected utterance is below a pre-determined time period. 14. The system of claim 9 , wherein a threshold of detecting the keyword or the key phrase by the second model is narrower than a threshold of detecting the keyword or the key phrase by the first model. | 0.514423 |
9,967,297 | 1 | 7 | 1. A non-transitory computer-readable medium embodying a program executable in a computing device, wherein, when executed, the program causes the computing device to at least: identify a plurality of third party profiles corresponding to a plurality of third party users based at least in part on at least one third party selection criterion, the at least one third party selection criterion being received from a first network page rendered on a client device, wherein identifying the plurality of third party profiles based at least in part on the at least one third party selection criterion comprises comparing a plurality of significant terms extracted from a first profile and a second profile associated with a single user account to a respective description for individual ones of the plurality of third party profiles, the plurality of significant terms being extracted from the first profile and the second profile based at least in part on identifying at least one of a grammatically emphasized term or a frequently used term; generate a second network page associated with a topic received from the client device, the second network page comprising a user interface to facilitate an input of a plurality of suggestions from at least one of a plurality of devices associated with the plurality of third party users, wherein the plurality of suggestions are associated with at least one item offered by an electronic commerce system; and cause the second network page to be transmitted to the client device and the plurality of devices associated with the plurality of third party users. | 1. A non-transitory computer-readable medium embodying a program executable in a computing device, wherein, when executed, the program causes the computing device to at least: identify a plurality of third party profiles corresponding to a plurality of third party users based at least in part on at least one third party selection criterion, the at least one third party selection criterion being received from a first network page rendered on a client device, wherein identifying the plurality of third party profiles based at least in part on the at least one third party selection criterion comprises comparing a plurality of significant terms extracted from a first profile and a second profile associated with a single user account to a respective description for individual ones of the plurality of third party profiles, the plurality of significant terms being extracted from the first profile and the second profile based at least in part on identifying at least one of a grammatically emphasized term or a frequently used term; generate a second network page associated with a topic received from the client device, the second network page comprising a user interface to facilitate an input of a plurality of suggestions from at least one of a plurality of devices associated with the plurality of third party users, wherein the plurality of suggestions are associated with at least one item offered by an electronic commerce system; and cause the second network page to be transmitted to the client device and the plurality of devices associated with the plurality of third party users. 7. The non-transitory computer-readable medium of claim 1 , wherein identifying the plurality of third party profiles based at least in part on the at least one third party selection criterion comprises comparing a first percentage of similarity of the first profile and a second percentage of similarity of the second profile with the plurality of third party profiles. | 0.538653 |
7,991,768 | 10 | 18 | 10. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions. | 10. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions. 18. The one or more non-transitory machine-readable media of claim 10 , wherein: the normalized query includes a plurality of extract operators, none of which appear in said query; each extract operator of the plurality of extract operators takes as input a different normalized path expression of the plurality of normalized path expressions; and using the path-subsetted XML index to process the plurality of normalized path expressions comprises rewriting each extract operator to use the path-subsetted XML index. | 0.694083 |
9,342,798 | 1 | 3 | 1. A computer-implemented method comprising: receiving a plurality of training data records, wherein each training data record includes an input data portion and an output data portion and data specifying a training data type that corresponds to the training records; based on the training data type, identifying a set of one or more training functions that are included in a repository of training functions and that are compatible with the training data type, wherein identifying the set of training functions comprises: inputting the training data type as input into one or more trained predictive models, each trained predictive model being trained to determine whether a category of training functions is compatible with the training data type; receiving one or more predictive outputs from the one or more trained predictive models; and identifying the set of training functions based on the one or more predictive outputs; and using the training data records and the identified set of training functions obtained from the repository of training functions to train one or more predictive models. | 1. A computer-implemented method comprising: receiving a plurality of training data records, wherein each training data record includes an input data portion and an output data portion and data specifying a training data type that corresponds to the training records; based on the training data type, identifying a set of one or more training functions that are included in a repository of training functions and that are compatible with the training data type, wherein identifying the set of training functions comprises: inputting the training data type as input into one or more trained predictive models, each trained predictive model being trained to determine whether a category of training functions is compatible with the training data type; receiving one or more predictive outputs from the one or more trained predictive models; and identifying the set of training functions based on the one or more predictive outputs; and using the training data records and the identified set of training functions obtained from the repository of training functions to train one or more predictive models. 3. The method of claim 1 , further comprising: generating a score for each of the one or more trained predictive models, where each score represents an estimation of the effectiveness of the respective trained predictive model; and selecting a first trained predictive model from among the one or more trained predictive models based on the generated scores. | 0.62395 |
9,696,969 | 7 | 9 | 7. A system, comprising: a memory, communicatively coupled to a processor, the memory storing the computer-executable components comprising: an editor component configured to: infer a first industrial programming language of a plurality of industrial programming languages to utilize for programming an industrial controller and infer a second industrial programming language of the plurality of industrial programming languages to utilize in combination with the first industrial programming language for programming the industrial controller to create a custom programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises user tendencies associated with respective industrial programming languages of the industrial programming languages; and combine at least a portion of the first industrial programming language with at least another portion of the second industrial programming language to create the custom programming language for programming the industrial controller, wherein the first industrial programming language, the industrial second programming language and the custom programming language are disparate. | 7. A system, comprising: a memory, communicatively coupled to a processor, the memory storing the computer-executable components comprising: an editor component configured to: infer a first industrial programming language of a plurality of industrial programming languages to utilize for programming an industrial controller and infer a second industrial programming language of the plurality of industrial programming languages to utilize in combination with the first industrial programming language for programming the industrial controller to create a custom programming language that is optimal for programming the industrial controller based upon at least one criteria comprising a code function to be implemented in the industrial controller, wherein the at least one criteria further comprises user tendencies associated with respective industrial programming languages of the industrial programming languages; and combine at least a portion of the first industrial programming language with at least another portion of the second industrial programming language to create the custom programming language for programming the industrial controller, wherein the first industrial programming language, the industrial second programming language and the custom programming language are disparate. 9. The system of claim 7 , wherein at least one of the first industrial programming language or the industrial second programming language relates to an IEC61131 standard. | 0.765753 |
9,720,738 | 1 | 9 | 1. A computer-implemented machine learning method for scheduling a computational task by a scheduling entity in a datacenter environment, wherein the datacenter includes a plurality of computing entities and the scheduling entity includes a first and second parameter processing entities, the method comprising: receiving feedback information from the datacenter by the scheduling entity, wherein the feedback information includes: historical selections of the plurality of computing entities for processing historical computing tasks, and historical processing results of the historical computing tasks as processed by the historical computing entities; receiving and processing at the first parameter processing entity incoming data corresponding to a new computational task to be processed by the datacenter environment, wherein the incoming data includes: a set of computational task parameters specifying characteristics of the new computational task, and a set of computational tasks requirements specifying criteria which have to be fulfilled by a computer entity for processing the new computational task; receiving and processing at the second parameter processing entity a first and second set of computing entity parameters; wherein the first set of computing entity parameters specifies characteristics of the computing entities of the plurality of computing entities, and the second set of computing entity parameters specifies load parameters of the plurality of computing entities; providing processing result from the first and second parameter processing entities to machine logic of the scheduling entity; identifying, by a self-learning mechanism of the scheduling entity based on the processing result and the feedback information, features from one or more computing entities among the plurality of computing entities that have similar characteristics to the received set of computing entity parameters in the processing result; creating a contextual model that corresponds to the identified features of the one or more of the computing entities; responsive to detecting changes in the information deriving from the received feedback information, the processing result from the first and second parameter processing entities, and the created contextual model, modifying the set of identified features by increasing or decreasing the effect of one or more parameters; selecting, by machine logic of the scheduling entity, one or more computing entities of the plurality of computing entities for processing the new computational task based, at least in part, upon: the processing result from the first parameter processing entity, the processing result from the second parameter entity, the received feedback information, and the created contextual model; and processing the computational task on the selected one or more computing entities. | 1. A computer-implemented machine learning method for scheduling a computational task by a scheduling entity in a datacenter environment, wherein the datacenter includes a plurality of computing entities and the scheduling entity includes a first and second parameter processing entities, the method comprising: receiving feedback information from the datacenter by the scheduling entity, wherein the feedback information includes: historical selections of the plurality of computing entities for processing historical computing tasks, and historical processing results of the historical computing tasks as processed by the historical computing entities; receiving and processing at the first parameter processing entity incoming data corresponding to a new computational task to be processed by the datacenter environment, wherein the incoming data includes: a set of computational task parameters specifying characteristics of the new computational task, and a set of computational tasks requirements specifying criteria which have to be fulfilled by a computer entity for processing the new computational task; receiving and processing at the second parameter processing entity a first and second set of computing entity parameters; wherein the first set of computing entity parameters specifies characteristics of the computing entities of the plurality of computing entities, and the second set of computing entity parameters specifies load parameters of the plurality of computing entities; providing processing result from the first and second parameter processing entities to machine logic of the scheduling entity; identifying, by a self-learning mechanism of the scheduling entity based on the processing result and the feedback information, features from one or more computing entities among the plurality of computing entities that have similar characteristics to the received set of computing entity parameters in the processing result; creating a contextual model that corresponds to the identified features of the one or more of the computing entities; responsive to detecting changes in the information deriving from the received feedback information, the processing result from the first and second parameter processing entities, and the created contextual model, modifying the set of identified features by increasing or decreasing the effect of one or more parameters; selecting, by machine logic of the scheduling entity, one or more computing entities of the plurality of computing entities for processing the new computational task based, at least in part, upon: the processing result from the first parameter processing entity, the processing result from the second parameter entity, the received feedback information, and the created contextual model; and processing the computational task on the selected one or more computing entities. 9. The method according to claim 1 , wherein the scheduling entity, the first parameter processing entity, and the second parameter processing entity receive the computational task parameters and adapt to modify the computational task parameters by applying an arithmetic operation or generate a modified computational task parameter by combining two or more computational task parameters based on an arithmetic operation or adapt at least one computational task parameter and add the adapted computational task parameter alongside with the original computational task parameter. | 0.5 |
7,522,046 | 6 | 7 | 6. The system of claim 1 , wherein the document state comprises an environmental condition of the document. | 6. The system of claim 1 , wherein the document state comprises an environmental condition of the document. 7. The system of claim 6 , wherein the environmental condition comprises illumination. | 0.5 |
9,549,042 | 17 | 18 | 17. The non-transitory processor-readable medium of claim 16 , wherein the Bluetooth® features comprise record features and stability features. | 17. The non-transitory processor-readable medium of claim 16 , wherein the Bluetooth® features comprise record features and stability features. 18. The non-transitory processor-readable medium of claim 17 , wherein the record features comprise at least one of the count features, the entropy features and the semantic features, and the stability features comprise a measure of stability of neighboring information units from the multiple electronic devices based on at least one similarity metric. | 0.5 |
8,170,197 | 1 | 8 | 1. A system for providing automated call center post-call processing, comprising: a call processor to automatically process a call through a call center by executing a customer support scenario controlled by an agent via one or more scripts; a sliding control to vary a level of automation used in executing the customer support scenario by altering a course of at least one of the scripts; a post-call processor to identify verbal speech utterances from a speaker in a stream of user messages recorded during the customer support scenario and parsed from the call; a database to store the stream of user messages maintained by the call center; and a command processor to process the user messages following completion of the call comprising identifying aspects of the call, wherein the aspects comprise at least one of a general flow of the call and one or more characteristics of the speaker, and to manipulate at least one of the verbal speech utterances, wherein the manipulation comprises at least one of ranking the at least one verbal speech utterance and editing the at least one verbal speech utterance. | 1. A system for providing automated call center post-call processing, comprising: a call processor to automatically process a call through a call center by executing a customer support scenario controlled by an agent via one or more scripts; a sliding control to vary a level of automation used in executing the customer support scenario by altering a course of at least one of the scripts; a post-call processor to identify verbal speech utterances from a speaker in a stream of user messages recorded during the customer support scenario and parsed from the call; a database to store the stream of user messages maintained by the call center; and a command processor to process the user messages following completion of the call comprising identifying aspects of the call, wherein the aspects comprise at least one of a general flow of the call and one or more characteristics of the speaker, and to manipulate at least one of the verbal speech utterances, wherein the manipulation comprises at least one of ranking the at least one verbal speech utterance and editing the at least one verbal speech utterance. 8. A system according to claim 1 , wherein the call comprises one of an incoming call into the call center, an outgoing call from the call center, and an on-going call with the call center. | 0.5 |
8,880,402 | 1 | 2 | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; and (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value. | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user; (b) processing said input speech to obtain at least one parameter value; and (c) determining the user's level of experience with using automatic speech recognition, using the at least one parameter value. 2. The speech recognition method of claim 1 , wherein step (c) further comprises calculating a score using said at least one parameter value. | 0.833726 |
8,755,612 | 1 | 4 | 1. A method comprising: automatically identifying a screen control in a user interface; applying optical character recognition to read a text that is displayed on the screen control in an image of the user interface; automatically comparing the displayed text to a character string that is designated for the screen control; and if part of the character string is not included in the displayed text, identifying the displayed text as truncated text. | 1. A method comprising: automatically identifying a screen control in a user interface; applying optical character recognition to read a text that is displayed on the screen control in an image of the user interface; automatically comparing the displayed text to a character string that is designated for the screen control; and if part of the character string is not included in the displayed text, identifying the displayed text as truncated text. 4. The method of claim 1 , wherein automatically identifying the screen control comprises sequentially selecting each screen control from a plurality of identified screen controls. | 0.577465 |
7,788,085 | 16 | 17 | 16. A method to replace a source string in a document with a target string, comprising: preprocessing textual content, via a computer, to: 1) tokenize text in said document, 2) collect information concerning morphological information, part-of-speech disambiguation, syntactic dependencies, anaphoric dependencies and semantic relationships in the textual content and 2) label the document with such information, wherein said tokenizing includes multiword tokenization wherein textual input is tokenized into non-isolated units; selecting a target string, via the computer, that is placed at one or more locations within the document; selecting a source string, via the computer, to replace the target string; selecting one of more of a part of speech, a gender, and a number for each of the target string and the source string, via the computer, for replacement in the document; morpho-syntactically disambiguating textual content of the target and source strings, via the computer, using two levels of analysis: 1) examining the parts-of-speech on their own, and if ambiguities are found, 2) examining each occurrence of said source string in the textual content of the document; identifying a set of string dependencies by detecting grammatical dependencies between strings in the textual content of the document via the computer; disambiguating one or more of gender, number, or part of speech and prompting a user to provide user-specified disambiguation, via the computer, if the source string or the target string have one or more of various possible meanings, genders, and numbers; identifying occurrences of the source string in the document, via the computer, that satisfy the user specifications; identifying string relations from the set of string dependencies, via the computer, that define direct or indirect links, or both, to the source string; replacing each occurrences of the source string in the document, via the computer, that satisfy the user specifications with the target string; correcting grammatical and anaphoric inconsistencies, beyond the phrase level, in the string relations in the document, via the computer, that are introduced when the source string is replaced with the target string; and outputting the document; wherein the disambiguation of the source string or the target string is performed before replacing each occurrences of the source string in the document that satisfy the user specifications with the target string. | 16. A method to replace a source string in a document with a target string, comprising: preprocessing textual content, via a computer, to: 1) tokenize text in said document, 2) collect information concerning morphological information, part-of-speech disambiguation, syntactic dependencies, anaphoric dependencies and semantic relationships in the textual content and 2) label the document with such information, wherein said tokenizing includes multiword tokenization wherein textual input is tokenized into non-isolated units; selecting a target string, via the computer, that is placed at one or more locations within the document; selecting a source string, via the computer, to replace the target string; selecting one of more of a part of speech, a gender, and a number for each of the target string and the source string, via the computer, for replacement in the document; morpho-syntactically disambiguating textual content of the target and source strings, via the computer, using two levels of analysis: 1) examining the parts-of-speech on their own, and if ambiguities are found, 2) examining each occurrence of said source string in the textual content of the document; identifying a set of string dependencies by detecting grammatical dependencies between strings in the textual content of the document via the computer; disambiguating one or more of gender, number, or part of speech and prompting a user to provide user-specified disambiguation, via the computer, if the source string or the target string have one or more of various possible meanings, genders, and numbers; identifying occurrences of the source string in the document, via the computer, that satisfy the user specifications; identifying string relations from the set of string dependencies, via the computer, that define direct or indirect links, or both, to the source string; replacing each occurrences of the source string in the document, via the computer, that satisfy the user specifications with the target string; correcting grammatical and anaphoric inconsistencies, beyond the phrase level, in the string relations in the document, via the computer, that are introduced when the source string is replaced with the target string; and outputting the document; wherein the disambiguation of the source string or the target string is performed before replacing each occurrences of the source string in the document that satisfy the user specifications with the target string. 17. The method according to claim 16 , further comprising: identifying a set of string dependencies, via the computer, by detecting anaphoric dependencies between strings in the textual content of the document; and correcting anaphoric inconsistencies in the string relations in the document, via the computer, that are introduced when the source string is replaced with the target string. | 0.5 |
8,874,589 | 3 | 6 | 3. The method of claim 1 , wherein receiving performance statistics data comprises receiving performance statistics data for a randomly selected subset of the second plurality of network device identifiers having a similarity score greater than or equal to the threshold similarity score value. | 3. The method of claim 1 , wherein receiving performance statistics data comprises receiving performance statistics data for a randomly selected subset of the second plurality of network device identifiers having a similarity score greater than or equal to the threshold similarity score value. 6. The method of claim 3 , further comprising interpolating the performance statistics data responsive to determining a distribution of the performance statistics data does not cover the designated performance target. | 0.5 |
9,570,077 | 10 | 13 | 10. One or more computer-readable storage devices storing instructions that when executed by a processor, cause performance of operations that comprise: receiving, by a computing device, a first voice input that includes one or more first words; generating, by the computing device, first data that represents the one or more first words of the first voice input, wherein the first data represents an audio recording of the first voice input; identifying that the one or more first words of the first voice input have been reserved for a particular third-party application program that is installed on the computing device; receiving, by the computing device, a second voice input that that follows the first voice input and that includes one or more second words; generating, by the computing device, second data that represents the one or more second words of the second voice input, wherein the second data represents text of the one or more second words of the second voice input; and providing, as a result of having identified that the one or more first words of the first voice input are reserved for the particular third-party application program, the second data that represents the one or more second words of the second voice input to the particular third-party application program. | 10. One or more computer-readable storage devices storing instructions that when executed by a processor, cause performance of operations that comprise: receiving, by a computing device, a first voice input that includes one or more first words; generating, by the computing device, first data that represents the one or more first words of the first voice input, wherein the first data represents an audio recording of the first voice input; identifying that the one or more first words of the first voice input have been reserved for a particular third-party application program that is installed on the computing device; receiving, by the computing device, a second voice input that that follows the first voice input and that includes one or more second words; generating, by the computing device, second data that represents the one or more second words of the second voice input, wherein the second data represents text of the one or more second words of the second voice input; and providing, as a result of having identified that the one or more first words of the first voice input are reserved for the particular third-party application program, the second data that represents the one or more second words of the second voice input to the particular third-party application program. 13. The one or more computer-readable storage devices of claim 10 , wherein the particular third-party application program was installed on the computing device from an installation file that the computing device received over a network, in response to the computing device receiving user input that requests transmission of the installation file over the network. | 0.754386 |
7,596,574 | 17 | 19 | 17. The computer system of claim 1 comprising a facet analysis component for defining the faceted data set for sharing among a plurality of domains of information, said facet analysis component configured to receive input information and discover the facets, facet attributes, and facet attribute hierarchies of the input information, said input information comprising at least one of information of any of the domains to be classified and feedback from respective domain concept taxonomy information. | 17. The computer system of claim 1 comprising a facet analysis component for defining the faceted data set for sharing among a plurality of domains of information, said facet analysis component configured to receive input information and discover the facets, facet attributes, and facet attribute hierarchies of the input information, said input information comprising at least one of information of any of the domains to be classified and feedback from respective domain concept taxonomy information. 19. The computer system of claim 17 comprising: (a) a first computer system including the facet analysis component for defining the shared faceted data set, said facet analysis component further defining from the shared faceted data set a domain-specific faceted data set for a domain to be classified; and (b) a second computer system including a classification synthesis component for building the dimensional concept taxonomies for one or more domains, said synthesis component defining the concept definitions and expressing the dimensional concept relationships between the concepts for each of the one or more domains to be classified in accordance with the respective domain-specific faceted data set. | 0.5 |
7,814,042 | 46 | 50 | 46. A computer-implemented method of processing a query, comprising: receiving the query, wherein the query comprises one or more query blocks; determining multiple starting queries based on the query and one or more heuristics; for each starting query of the multiple starting queries: establishing said each starting query as a local-best query; determining a set of candidate queries and costs, wherein the costs include a cost for each candidate query in the set of candidate queries, wherein each candidate query in the set of candidate queries is determined based on the local-best query and an alternative state for a particular query block of the one or more query blocks, and wherein, if a specific cost for a specific candidate query satisfies a first particular mathematical relationship with a local-best cost for the local-best query, then establishing the specific candidate query as the local-best query; wherein each candidate query in the set of candidate queries is semantically equivalent to the query; choosing a particular query from a set of local-best queries based on costs for each query in the set of local-best queries, wherein the set of local-best queries comprises the local-best query for each set of candidate queries; and executing the particular query in response to a request to execute the query; wherein the method is performed by one or more computing devices. | 46. A computer-implemented method of processing a query, comprising: receiving the query, wherein the query comprises one or more query blocks; determining multiple starting queries based on the query and one or more heuristics; for each starting query of the multiple starting queries: establishing said each starting query as a local-best query; determining a set of candidate queries and costs, wherein the costs include a cost for each candidate query in the set of candidate queries, wherein each candidate query in the set of candidate queries is determined based on the local-best query and an alternative state for a particular query block of the one or more query blocks, and wherein, if a specific cost for a specific candidate query satisfies a first particular mathematical relationship with a local-best cost for the local-best query, then establishing the specific candidate query as the local-best query; wherein each candidate query in the set of candidate queries is semantically equivalent to the query; choosing a particular query from a set of local-best queries based on costs for each query in the set of local-best queries, wherein the set of local-best queries comprises the local-best query for each set of candidate queries; and executing the particular query in response to a request to execute the query; wherein the method is performed by one or more computing devices. 50. The method of claim 46 , wherein the method further comprises: for each starting query of the multiple starting queries, determining the local-best cost based on the local-best query; and wherein determining the set of candidate queries and costs comprises: for each query block of one or more particular query blocks of the one or more query blocks in the starting query: determining a particular alternative state of the query block; determining a current query based on the local-best query and the particular alternative state of the query block; determining a current cost based on the current query; if the current cost satisfies the first particular mathematical relationship with the local-best cost, then: establishing the current query as the local-best query; and establishing the current cost as the local-best cost. | 0.5 |
8,499,238 | 2 | 3 | 2. A method according to claim 1 , wherein the model identifies specific relationships between the elements of the model, and each of the model elements has defined properties, and wherein: at least some of the documents include first and second types of text; the first type of text is retrieved from the properties of the model elements; the second type of text is reproduced verbatim from a template; and the structure of the documents is derived from the structure of the model. | 2. A method according to claim 1 , wherein the model identifies specific relationships between the elements of the model, and each of the model elements has defined properties, and wherein: at least some of the documents include first and second types of text; the first type of text is retrieved from the properties of the model elements; the second type of text is reproduced verbatim from a template; and the structure of the documents is derived from the structure of the model. 3. A method according to claim 2 , wherein the step of providing information includes the step of the user editing the first type of text in one said document; wherein said editing results in a change to one of the properties of the model elements, and leads to the refreshing of said one property wherever said one property is repeated in all of the documents. | 0.534794 |
8,060,491 | 16 | 18 | 16. The apparatus of claim 15 , wherein the text associated with the content items comprises tag data input by one or more users. | 16. The apparatus of claim 15 , wherein the text associated with the content items comprises tag data input by one or more users. 18. The apparatus of claim 16 , wherein the semantic information includes location data. | 0.81893 |
8,352,491 | 1 | 2 | 1. A computer program product comprising a computer readable storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method of searching a web service registry system by use of a search module, said method comprising: a search controller of the search module, executed by the processor, receiving a service name through the web service registry system interface, through which the web service registry system communicates with components external to the web service registry system, wherein the web service registry system comprises the search module, the web service registry system interface, and a service registry program product, wherein the search module comprises the search controller, a name parser, a dictionary, and a name composer, wherein the search controller is configured to communicate with the service registry program product via a first internal interface comprising an application programming interface (API) inherent to the service registry program product, wherein the search controller is configured to communicate with the name parser, the dictionary, and the name composer via a second internal interface, a third internal interface, and a fourth internal interface, respectively, wherein the second internal interface, the third internal interface, and the fourth internal interface are uniform within the search module, such that the search controller orchestrates operations of the service registry program product and the name parser, the dictionary, and the name composer of the search module by use of the first internal interface, the second internal interface, the third internal interface, and the fourth internal interface, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; performing, by said processor, a first search of the service registry program product with the received service name and subsequently determining that the received service name does not have a service description associated with the received service name in the service registry program product; coordinating, by said processor, a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and discovering, by said processor, the service description is associated with the candidate service name within the service registry program product and subsequently outputting the discovered service description through the web service registry system interfaces, said coordinating comprising: sending the received service name to the name parser of the search module via the second internal interface and subsequently receiving a component word list from the name parser via the second internal interface, wherein the component word list comprises all words constituting the received service name; sending the component word list to the dictionary of the search module via the third internal interface and subsequently receiving a respective synonym list for each word in the component word list from the dictionary via the third internal interface, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; sending the respective synonym list to the name composer of the search module via the fourth internal interface and subsequently receiving the candidate service name from the name composer via the fourth internal interface; and sending a second search request for the service description associated with the candidate service name to the service registry program product via the first internal interface and subsequently receiving the service description in response to the second search request via the first internal interface. | 1. A computer program product comprising a computer readable storage device having a computer readable program code embodied therein, said computer readable program code containing instructions that, upon being executed by a processor of a computer system, perform a method of searching a web service registry system by use of a search module, said method comprising: a search controller of the search module, executed by the processor, receiving a service name through the web service registry system interface, through which the web service registry system communicates with components external to the web service registry system, wherein the web service registry system comprises the search module, the web service registry system interface, and a service registry program product, wherein the search module comprises the search controller, a name parser, a dictionary, and a name composer, wherein the search controller is configured to communicate with the service registry program product via a first internal interface comprising an application programming interface (API) inherent to the service registry program product, wherein the search controller is configured to communicate with the name parser, the dictionary, and the name composer via a second internal interface, a third internal interface, and a fourth internal interface, respectively, wherein the second internal interface, the third internal interface, and the fourth internal interface are uniform within the search module, such that the search controller orchestrates operations of the service registry program product and the name parser, the dictionary, and the name composer of the search module by use of the first internal interface, the second internal interface, the third internal interface, and the fourth internal interface, and wherein the service registry program product comprises at least one service description searchable by a respectively associated service name; performing, by said processor, a first search of the service registry program product with the received service name and subsequently determining that the received service name does not have a service description associated with the received service name in the service registry program product; coordinating, by said processor, a second search of the service registry program product with a candidate service name by use of the search module, wherein the candidate service name is semantically and syntactically interchangeable with the received service name such that the candidate service name identifies the service description associated with the received service name within the service registry program product; and discovering, by said processor, the service description is associated with the candidate service name within the service registry program product and subsequently outputting the discovered service description through the web service registry system interfaces, said coordinating comprising: sending the received service name to the name parser of the search module via the second internal interface and subsequently receiving a component word list from the name parser via the second internal interface, wherein the component word list comprises all words constituting the received service name; sending the component word list to the dictionary of the search module via the third internal interface and subsequently receiving a respective synonym list for each word in the component word list from the dictionary via the third internal interface, wherein the respective synonym list comprises at least one synonym of said each word in the component word list; sending the respective synonym list to the name composer of the search module via the fourth internal interface and subsequently receiving the candidate service name from the name composer via the fourth internal interface; and sending a second search request for the service description associated with the candidate service name to the service registry program product via the first internal interface and subsequently receiving the service description in response to the second search request via the first internal interface. 2. The computer program product of claim 1 , said performing the first search comprising: sending a first search request for the service description associated with the received service name to the service registry program product through the first internal interface; and receiving a null from the service registry program product through the first internal interface in response to the first search request, wherein the service registry program product returns the null upon failing to find the service description associated with the received service name. | 0.738051 |
6,073,135 | 1 | 2 | 1. A computerized method for representing the connectivity of Web pages, the Web pages including links between the Web pages, the links and Web pages being identified by names, comprising: sorting the names of the Web pages in a memory; delta encoding the sorted names while periodically storing full names as checkpoints in the memory, each delta encoded name and checkpoint having an assigned unique identification; twice sorting a list of pairs of identifications that represent the links between the Web page, each pair of identifications including a first identification and a second identification, first according to the first identification of each pair to produce an inlist, and second according to the second identification of each pair to produce an outlist; storing an array of elements in the memory, there being one array element for each Web page, each element including a first pointer to one of the checkpoints, a second pointer to an associated inlist of the Web page, and a third pointer to an associated outlist of the Web page; and indexing the array by a particular identification to locate connected Web pages. | 1. A computerized method for representing the connectivity of Web pages, the Web pages including links between the Web pages, the links and Web pages being identified by names, comprising: sorting the names of the Web pages in a memory; delta encoding the sorted names while periodically storing full names as checkpoints in the memory, each delta encoded name and checkpoint having an assigned unique identification; twice sorting a list of pairs of identifications that represent the links between the Web page, each pair of identifications including a first identification and a second identification, first according to the first identification of each pair to produce an inlist, and second according to the second identification of each pair to produce an outlist; storing an array of elements in the memory, there being one array element for each Web page, each element including a first pointer to one of the checkpoints, a second pointer to an associated inlist of the Web page, and a third pointer to an associated outlist of the Web page; and indexing the array by a particular identification to locate connected Web pages. 2. The method of claim 1 wherein the names are uniform resource locators of the Web pages, and the uniform resource locators are sorted lexicographically. | 0.807018 |
8,972,434 | 1 | 5 | 1. A computer program product comprising at least one non-transitory computer-readable storage medium storing computer-executable code for a travel reservation search engine to execute search requests, the computer-executable code comprising: a query interface module configured to receive from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; a constraint evaluation module configured to: select at least one additional constraint not included in the search request; construct a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; and construct a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and a website query module configured to execute the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting. | 1. A computer program product comprising at least one non-transitory computer-readable storage medium storing computer-executable code for a travel reservation search engine to execute search requests, the computer-executable code comprising: a query interface module configured to receive from a user a search request for travel reservation information, the search request including at least one first constraint to be met by results returned by a search; a constraint evaluation module configured to: select at least one additional constraint not included in the search request; construct a first query based on the at least one first constraint and the at least one additional constraint such that fewer search results are obtained in response to executing the first query than would be obtained in response to executing a query constructed without the at least one additional constraint; and construct a second query based on the at least one first search constraint without the at least one additional constraint; wherein the select at least one additional constraint is performed based on an estimated execution time of the first query with the at least one additional constraint; and a website query module configured to execute the first query to obtain first phase query results and the second query to obtain second phase query results, wherein the first phase query results and the second phase query results are non-intersecting. 5. The of claim 1 , wherein the at least one additional constraint is selected to achieve a minimum threshold probability that the first query will return a successful result, and wherein the first query is constructed to have a probability of returning a successful search result that satisfies the minimum threshold probability, the probability determined based on one or more queries previously executed that included the at least one additional constraint. | 0.621087 |
9,894,368 | 1 | 3 | 1. An apparatus for decoding a significance map, the apparatus comprising: a decoder configured to extract, from a data stream, the significance map indicating positions of significant transform coefficients within a transform coefficient block, wherein the decoder is to extract first-type syntax elements and second-type syntax elements based on context-adaptive entropy decoding, and the first-type syntax elements indicate, for associated positions within the transform coefficient block, whether at each respective associated position a significant transform coefficient is present and each of the second-type syntax elements relates to a value of the significant transform coefficient at a respective associated position within the transform coefficient block; and an associator configured to associate the extracted first-type syntax elements to the positions of the transform coefficient block in a scan order, wherein the decoder is configured to use, in context-adaptively entropy decoding the first-type syntax elements, contexts which are selected for each of the first-type syntax elements, wherein the context for a current first-type syntax element being decoded is selected in accordance with a combination of the scan order and a number of positions of the significant transform coefficients within the transform coefficient block related to previously extracted first-type syntax elements in a neighborhood of the current first-type syntax element. | 1. An apparatus for decoding a significance map, the apparatus comprising: a decoder configured to extract, from a data stream, the significance map indicating positions of significant transform coefficients within a transform coefficient block, wherein the decoder is to extract first-type syntax elements and second-type syntax elements based on context-adaptive entropy decoding, and the first-type syntax elements indicate, for associated positions within the transform coefficient block, whether at each respective associated position a significant transform coefficient is present and each of the second-type syntax elements relates to a value of the significant transform coefficient at a respective associated position within the transform coefficient block; and an associator configured to associate the extracted first-type syntax elements to the positions of the transform coefficient block in a scan order, wherein the decoder is configured to use, in context-adaptively entropy decoding the first-type syntax elements, contexts which are selected for each of the first-type syntax elements, wherein the context for a current first-type syntax element being decoded is selected in accordance with a combination of the scan order and a number of positions of the significant transform coefficients within the transform coefficient block related to previously extracted first-type syntax elements in a neighborhood of the current first-type syntax element. 3. The apparatus according to claim 1 , wherein the decoder is further configured to map the number of positions to a context index of a set of possible context indices. | 0.74 |
8,538,808 | 1 | 9 | 1. A computer-implemented method for testing a plurality of candidate creatives, the method comprising: placing, by a media exchange server, the plurality of candidate creatives on a queue coupled with the media exchange server configured to interface prospective buyers and sellers of the candidate creatives; inspecting, by the server, technical attributes of each candidate creative when at a front of the queue with at least one test node before delivery to a publisher, wherein inspecting comprises the server: generating a creative vector containing the candidate creative; launching a browser by a test daemon of the at least one test node; loading the creative vector into the browser; and executing a test suite on the candidate creative by constituent elements of the test node; determining, by the server, that a first of the candidate creatives is a fixed creative comprising constituent elements that do not change each time a creative vector thereof is loaded into a browser; delivering, by the server, the fixed candidate creative directly to the publisher from the server; re-inspecting, by the server, the technical attributes of a second of the candidate creatives that remain in the queue after one or more previous inspections by the server, comprising detecting a hidden technical attribute detectable under unknown specified circumstances; and rejecting delivery of the second candidate creative to the publisher by the server as a result of detecting the hidden technical attribute. | 1. A computer-implemented method for testing a plurality of candidate creatives, the method comprising: placing, by a media exchange server, the plurality of candidate creatives on a queue coupled with the media exchange server configured to interface prospective buyers and sellers of the candidate creatives; inspecting, by the server, technical attributes of each candidate creative when at a front of the queue with at least one test node before delivery to a publisher, wherein inspecting comprises the server: generating a creative vector containing the candidate creative; launching a browser by a test daemon of the at least one test node; loading the creative vector into the browser; and executing a test suite on the candidate creative by constituent elements of the test node; determining, by the server, that a first of the candidate creatives is a fixed creative comprising constituent elements that do not change each time a creative vector thereof is loaded into a browser; delivering, by the server, the fixed candidate creative directly to the publisher from the server; re-inspecting, by the server, the technical attributes of a second of the candidate creatives that remain in the queue after one or more previous inspections by the server, comprising detecting a hidden technical attribute detectable under unknown specified circumstances; and rejecting delivery of the second candidate creative to the publisher by the server as a result of detecting the hidden technical attribute. 9. The method of claim 1 , wherein placing the plurality of candidate creatives on the queue comprises placing the candidate creatives on both a low-priority queue and on a high-priority queue, wherein priority is determined based on historical data comprising data indicating whether or not the candidate creatives have been associated with undesirable technical attributes. | 0.541565 |
8,131,547 | 1 | 5 | 1. A method for automatic segmentation of speech to generate a speech inventory, the method comprising: initializing, via a processor, a Hidden Markov Model (HMM) using seed input data; performing a segmentation of the HMM into speech units to generate phone labels; correcting, via the processor, the segmentation of the speech units by performing the steps: re-estimating the HMM based on a current version of the phone labels; embedded re-estimating of the HMM; and updating the current version of the phone labels using spectral boundary correction. | 1. A method for automatic segmentation of speech to generate a speech inventory, the method comprising: initializing, via a processor, a Hidden Markov Model (HMM) using seed input data; performing a segmentation of the HMM into speech units to generate phone labels; correcting, via the processor, the segmentation of the speech units by performing the steps: re-estimating the HMM based on a current version of the phone labels; embedded re-estimating of the HMM; and updating the current version of the phone labels using spectral boundary correction. 5. The method of claim 1 , further comprising adjusting boundaries of the phone labels within specified time windows. | 0.897727 |
8,073,868 | 8 | 29 | 8. A computer implemented method for generating search queries using visual manipulation of search terms to facilitate a search process over a data network, comprising: receiving an initial search query as a visual representation, said visual representation includes at least one search term as an initial graphical icon; scanning over said network and, based on said scan, providing at least a list of related terms associated with said initial search query, wherein said related terms are being provided as additional graphical icons, wherein the scanning includes obtaining relationships involving said related terms and data entities at different locations in said data network, and organizing said related terms, said relationships, and said data entities in at least one data structure that represents said relationships in said data network, wherein the data structure is organized, based on at least one of data network analysis and expert knowledge, wherein the data entities in said data network are analyzed in accordance with statistical correlations of word frequencies, location, and dates within the data network; enabling a user to visually manipulate said initial search query by visually placing one or more of said initial graphical icon and said additional graphical icons respective of one or more related terms to be included in a new refined search query in a plurality of graphical operators, each of said plurality of graphical operators applies a different operation on related terms placed therein, wherein said visual manipulation results in a new visual representation of graphical icons respective of said one or more related terms and interrelationships of said graphical icons with said plurality of graphical operators; and generating said new refined search query by applying said plurality of graphical operators on said one or more of related terms, thereby modifying said initial search query according to said visual manipulation. | 8. A computer implemented method for generating search queries using visual manipulation of search terms to facilitate a search process over a data network, comprising: receiving an initial search query as a visual representation, said visual representation includes at least one search term as an initial graphical icon; scanning over said network and, based on said scan, providing at least a list of related terms associated with said initial search query, wherein said related terms are being provided as additional graphical icons, wherein the scanning includes obtaining relationships involving said related terms and data entities at different locations in said data network, and organizing said related terms, said relationships, and said data entities in at least one data structure that represents said relationships in said data network, wherein the data structure is organized, based on at least one of data network analysis and expert knowledge, wherein the data entities in said data network are analyzed in accordance with statistical correlations of word frequencies, location, and dates within the data network; enabling a user to visually manipulate said initial search query by visually placing one or more of said initial graphical icon and said additional graphical icons respective of one or more related terms to be included in a new refined search query in a plurality of graphical operators, each of said plurality of graphical operators applies a different operation on related terms placed therein, wherein said visual manipulation results in a new visual representation of graphical icons respective of said one or more related terms and interrelationships of said graphical icons with said plurality of graphical operators; and generating said new refined search query by applying said plurality of graphical operators on said one or more of related terms, thereby modifying said initial search query according to said visual manipulation. 29. The method of claim 8 , wherein said visual placing of said graphical icons in said plurality of graphical operators includes at least one of: visual confining, dragging-and-dropping, visual positioning, and graphics marking of said graphical icons. | 0.711187 |
8,873,813 | 1 | 13 | 1. A method for recognition of faces from a still image or video frame, said method comprising: receiving a still image or video frame through an input interface; preprocessing said still image or video frame; recognizing a first class of image for said still image or video frame; if said first class of image for said still image or video frame comprises face or human, then sending said still image or video frame to a face recognizer module; said face recognizer module accessing a first basis function from a first library of basis functions, stored in a first basis function storage, corresponding to a first component of face; said face recognizer module accessing a second basis function from a second library of basis functions, stored in a second basis function storage, corresponding to a second component of face; a computing processor applying said first basis function across said still image or video frame to detect said first component of face; said computing processor applying said second basis function across said still image or video frame to detect said second component of face; said computing processor accessing a relationship between said first component of face and said second component of face; assigning a first node and a second node on a relational web to represent said first component of face and said second component of face, respectively; assigning a first branch connecting said first node and said second node on said relational web to represent said relationship between said first component of face and said second component of face; assigning a first Z-factor, a second Z-factor, and a third Z-factor to said first node, said second node, and said first branch, respectively; wherein Z-factor is a mathematical set of factors comprising one or more of reliability factor, confidence factor, truth factor, expertise factor, bias factor, knowledge factor, usefulness factor, and relevance factor; said computing processor analyzing said first Z-factor, said second Z-factor, and said third Z-factor for said first node, said second node, and said first branch; said computing processor detecting one or more faces in said still image or video frame, with a fourth Z-factor, based on said analysis step; said computing processor comparing said detected one or more faces with said fourth Z-factor against a library of faces, each with its own said Z-factor, stored in a first face storage; if said detected one or more faces match or correspond to a first face in said library of faces, then outputting identity or identification number of said first face, as identification for said detected one or more faces from said still image or video frame, along with a fifth Z-factor corresponding to said matching or correspondence to said first face. | 1. A method for recognition of faces from a still image or video frame, said method comprising: receiving a still image or video frame through an input interface; preprocessing said still image or video frame; recognizing a first class of image for said still image or video frame; if said first class of image for said still image or video frame comprises face or human, then sending said still image or video frame to a face recognizer module; said face recognizer module accessing a first basis function from a first library of basis functions, stored in a first basis function storage, corresponding to a first component of face; said face recognizer module accessing a second basis function from a second library of basis functions, stored in a second basis function storage, corresponding to a second component of face; a computing processor applying said first basis function across said still image or video frame to detect said first component of face; said computing processor applying said second basis function across said still image or video frame to detect said second component of face; said computing processor accessing a relationship between said first component of face and said second component of face; assigning a first node and a second node on a relational web to represent said first component of face and said second component of face, respectively; assigning a first branch connecting said first node and said second node on said relational web to represent said relationship between said first component of face and said second component of face; assigning a first Z-factor, a second Z-factor, and a third Z-factor to said first node, said second node, and said first branch, respectively; wherein Z-factor is a mathematical set of factors comprising one or more of reliability factor, confidence factor, truth factor, expertise factor, bias factor, knowledge factor, usefulness factor, and relevance factor; said computing processor analyzing said first Z-factor, said second Z-factor, and said third Z-factor for said first node, said second node, and said first branch; said computing processor detecting one or more faces in said still image or video frame, with a fourth Z-factor, based on said analysis step; said computing processor comparing said detected one or more faces with said fourth Z-factor against a library of faces, each with its own said Z-factor, stored in a first face storage; if said detected one or more faces match or correspond to a first face in said library of faces, then outputting identity or identification number of said first face, as identification for said detected one or more faces from said still image or video frame, along with a fifth Z-factor corresponding to said matching or correspondence to said first face. 13. The method for recognition of faces from a still image or video frame as recited in claim 1 , said method comprising: emailing a file or data to a subset of people recognized in said still image or video frame. | 0.664577 |
9,146,989 | 11 | 19 | 11. A computer-readable non-transitory storage medium configured with data and with instructions that when executed by at least one processor in a cloud computing environment and/or a cloud storage environment causes the processor(s) to perform a process for digital good library comparison, the process comprising: obtaining a first dataset, namely, first electronic organizational data and first electronic history data associated with a first library of digital goods; obtaining a second dataset, namely, second electronic organizational data and second electronic history data associated with a second library of digital goods; automatically comparing at least a portion of the first dataset with at least a portion of the second dataset; reporting at least one of the following results: a shared multiple natural languages presence, a shared genre frequency change, a shared artist frequency change, a shared digital good frequency change, a shared outlier presence, a shared recommendable goods presence; and wherein the process operates in a cloud computing environment and/or a cloud storage environment to perform at least one of the obtaining, comparing, or reporting steps, and the process reports at least one of the following shared recommendable goods presence results: at least a specified percent of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified percent is a predetermined percent; at least a specified percent of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified percent is determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; at least a specified number of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified number is a predetermined number; at least a specified number of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified number is determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset. | 11. A computer-readable non-transitory storage medium configured with data and with instructions that when executed by at least one processor in a cloud computing environment and/or a cloud storage environment causes the processor(s) to perform a process for digital good library comparison, the process comprising: obtaining a first dataset, namely, first electronic organizational data and first electronic history data associated with a first library of digital goods; obtaining a second dataset, namely, second electronic organizational data and second electronic history data associated with a second library of digital goods; automatically comparing at least a portion of the first dataset with at least a portion of the second dataset; reporting at least one of the following results: a shared multiple natural languages presence, a shared genre frequency change, a shared artist frequency change, a shared digital good frequency change, a shared outlier presence, a shared recommendable goods presence; and wherein the process operates in a cloud computing environment and/or a cloud storage environment to perform at least one of the obtaining, comparing, or reporting steps, and the process reports at least one of the following shared recommendable goods presence results: at least a specified percent of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified percent is a predetermined percent; at least a specified percent of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified percent is determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset; at least a specified number of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified number is a predetermined number; at least a specified number of library entries in one dataset support a recommendation of library entry(ies) in the other dataset under an automated recommendation system, wherein the specified number is determined at least in part by comparing at least a portion of the first dataset with at least a portion of the second dataset. 19. The configured medium of claim 11 , wherein each library has an owner with at least one identity, such as an online identity and an offline identity, and the process further comprises at least one of the following: partially disclosing to each library owner at least one identity of the other library owner; partially disclosing only one library owner's identity(ies); fully disclosing to each library owner at least one identity of the other library owner; fully disclosing only one library owner's identity(ies). | 0.603369 |
7,765,271 | 67 | 68 | 67. A system coupled to a network, the system operated by at least one user, the system comprising: a plurality of subsystems coupled to the network, the subsystems having respective client devices capable of displaying document data included within respective hypertext mark-up language (HTML) documents displayed on corresponding web browsers thereof, at least one of the subsystems including a scanner coupled to a respective client device, the scanner generating the document data by scanning a document in print form based on a first command from a user entered into the web browser of the client device coupled to the scanner, the client device receiving the document data from the scanner and generating a display of the document data in the web browser thereof, the client device transmitting the document data based on a second command from the user entered into the web browser of the client device; at least one server coupled to the network, the server receiving the document data from the client device over the network using a destination address specified in an address field of the web browser of the client device; and a database storage unit coupled to the server, the database storage unit separate from the server, the database storage unit storing the document data so that the subsystems can access the document data. | 67. A system coupled to a network, the system operated by at least one user, the system comprising: a plurality of subsystems coupled to the network, the subsystems having respective client devices capable of displaying document data included within respective hypertext mark-up language (HTML) documents displayed on corresponding web browsers thereof, at least one of the subsystems including a scanner coupled to a respective client device, the scanner generating the document data by scanning a document in print form based on a first command from a user entered into the web browser of the client device coupled to the scanner, the client device receiving the document data from the scanner and generating a display of the document data in the web browser thereof, the client device transmitting the document data based on a second command from the user entered into the web browser of the client device; at least one server coupled to the network, the server receiving the document data from the client device over the network using a destination address specified in an address field of the web browser of the client device; and a database storage unit coupled to the server, the database storage unit separate from the server, the database storage unit storing the document data so that the subsystems can access the document data. 68. A system as claimed in claim 67 , wherein the network includes an internetwork. | 0.5 |
7,680,777 | 1 | 11 | 1. A computerized search and presentation method for a set of items, comprising: assigning one or more Attributes to each item in the set of items; further assigning to each Attribute, and to no item, a single Kind; creating assignments between Attributes and Kinds, where the assignments assign to each Attribute a single Kind, and to each Kind an arbitrary number of Attributes; assigning to each Kind at least one scheme of transitive implications among the Attributes such that each Kind is associated with several Attributes; determining which Attributes of each Kind are broad Attributes, broad Attributes being Attributes that do not within the set of items imply any other Attribute; presenting to a user a list of Kinds by which the set of items are to be grouped; upon accepting the user's selection of one or more Kinds, listing one or more broad Attributes of that Kind; upon accepting the user's selection of one or more broad Attributes, presenting information about a subset of items having the selected one or more broad Attributes; wherein Kinds are not assigned to items. | 1. A computerized search and presentation method for a set of items, comprising: assigning one or more Attributes to each item in the set of items; further assigning to each Attribute, and to no item, a single Kind; creating assignments between Attributes and Kinds, where the assignments assign to each Attribute a single Kind, and to each Kind an arbitrary number of Attributes; assigning to each Kind at least one scheme of transitive implications among the Attributes such that each Kind is associated with several Attributes; determining which Attributes of each Kind are broad Attributes, broad Attributes being Attributes that do not within the set of items imply any other Attribute; presenting to a user a list of Kinds by which the set of items are to be grouped; upon accepting the user's selection of one or more Kinds, listing one or more broad Attributes of that Kind; upon accepting the user's selection of one or more broad Attributes, presenting information about a subset of items having the selected one or more broad Attributes; wherein Kinds are not assigned to items. 11. The method of claim 1 , wherein graphical means are provided by which the user may specify the presence or absence of a particular Attribute or Kind as conditions constraining what items may belong to the set of items. | 0.744828 |
9,965,460 | 11 | 13 | 11. A computer program product comprising a computer usable non-transitory medium having a computer readable program code embedded therein for controlling a data processing apparatus, the computer readable program code configured to cause the data processing apparatus to execute a process for handwriting recognition, the process comprising: receiving and processing document data to obtain paragraphs and sentences, each sentence comprising one or more words; for each sentence of the document data, obtaining an NLP (Natural Language Processing) result relating to a sentence, wherein the NLP result comprises NER (Named Entity Recognition), POS (Part of Speech) and dependency of each word of the sentence, removing at least one word from the sentence based on the NLP result, grouping the remaining words of the sentence into one or more terms, wherein each term is either a word or a multi-word phrase, and storing the terms on a list; applying a frequency analysis to the terms on the list; for each paragraph of the document data, identifying terms whose occurrences in the paragraph meet a first threshold, forming a cluster for the paragraph based on a co-occurrence analysis of the identified terms, and evaluating a connectivity of the formed cluster; excluding at least one paragraph based on the connectivity of the formed clusters; selecting terms that occur in at least two remaining paragraphs; calculating a score for each of the selected terms; and based on the scores of the selected terms, outputting one or more top terms as keywords representing the document data. | 11. A computer program product comprising a computer usable non-transitory medium having a computer readable program code embedded therein for controlling a data processing apparatus, the computer readable program code configured to cause the data processing apparatus to execute a process for handwriting recognition, the process comprising: receiving and processing document data to obtain paragraphs and sentences, each sentence comprising one or more words; for each sentence of the document data, obtaining an NLP (Natural Language Processing) result relating to a sentence, wherein the NLP result comprises NER (Named Entity Recognition), POS (Part of Speech) and dependency of each word of the sentence, removing at least one word from the sentence based on the NLP result, grouping the remaining words of the sentence into one or more terms, wherein each term is either a word or a multi-word phrase, and storing the terms on a list; applying a frequency analysis to the terms on the list; for each paragraph of the document data, identifying terms whose occurrences in the paragraph meet a first threshold, forming a cluster for the paragraph based on a co-occurrence analysis of the identified terms, and evaluating a connectivity of the formed cluster; excluding at least one paragraph based on the connectivity of the formed clusters; selecting terms that occur in at least two remaining paragraphs; calculating a score for each of the selected terms; and based on the scores of the selected terms, outputting one or more top terms as keywords representing the document data. 13. The computer program product of claim 11 , wherein the frequency analysis comprises: for each term on the list, counting its occurrences in the document data to obtain a frequency of the term, and calculating a frequency score for the term based on its frequency. | 0.609649 |
8,566,363 | 1 | 5 | 1. A method for expanding an ontology, the method comprising: identifying, by a processing device, the ontology, the ontology including a plurality of terms including concept terms and role terms; disambiguating, by the processing device, the plurality of terms in the ontology using a lexical database to identify additional senses, wherein disambiguating the plurality of terms in the ontology further comprises identifying a term sense for each of the plurality of terms; determining a plurality of sense sets from the lexical database, wherein each of the plurality of sense sets includes at least one element; identifying a relatedness score between the term sense identified for each of the plurality of terms in the ontology and elements in the plurality of sense sets, wherein each element in the plurality of sense sets having a corresponding relatedness score that exceeds a predetermined relatedness score is included in the additional senses; and expanding, by the processing device, the ontology with the additional senses by adding at least one of the additional senses to the ontology. | 1. A method for expanding an ontology, the method comprising: identifying, by a processing device, the ontology, the ontology including a plurality of terms including concept terms and role terms; disambiguating, by the processing device, the plurality of terms in the ontology using a lexical database to identify additional senses, wherein disambiguating the plurality of terms in the ontology further comprises identifying a term sense for each of the plurality of terms; determining a plurality of sense sets from the lexical database, wherein each of the plurality of sense sets includes at least one element; identifying a relatedness score between the term sense identified for each of the plurality of terms in the ontology and elements in the plurality of sense sets, wherein each element in the plurality of sense sets having a corresponding relatedness score that exceeds a predetermined relatedness score is included in the additional senses; and expanding, by the processing device, the ontology with the additional senses by adding at least one of the additional senses to the ontology. 5. The method of claim 1 , wherein the plurality of sense sets include one or more of: a hypernym sense set; a hyponym sense set; a holonym sense set; a meronym sense set; a troponym sense set; a participle sense set; or a root adjective sense set. | 0.5 |
9,955,019 | 8 | 10 | 8. The method of claim 1 , wherein the document comprises a web page, and wherein said determining the country of origin comprises examining the language of text on the web page. | 8. The method of claim 1 , wherein the document comprises a web page, and wherein said determining the country of origin comprises examining the language of text on the web page. 10. The method of claim 8 , wherein the examining further comprises executing a language recognizer component to recognize the language of preselected words in the text on the web page. | 0.5 |
8,752,183 | 14 | 22 | 14. A system for testing a vulnerability of a web site, comprising: a processor; and a non-transitory computer readable medium having instructions embedded therein, the instructions executable by a processor and configured to: receive a first set of addresses, identify a second set of addresses by analyzing the first set of web pages located at the first set of addresses, and identify a third set of addresses by analyzing a first set of document object models (DOMs) associated with the first set of web pages and a second set of web pages located at the second set of addresses; probe a third set of web pages for presence of a set of vulnerabilities using a document object model (DOM) analysis script to analyze a second set of document object models (DOMs) associated with the third set of web pages as a set of attack vectors is applied to the third set of web pages, and determine presence of the set of vulnerabilities for the third set of web pages based on a result from the probing, wherein the third set of web pages is located at the first, second, and third sets of addresses, wherein the DOM analysis script is inserted into the third set of web pages, and wherein the attack vectors are designed to exploit a vulnerability of a web page. | 14. A system for testing a vulnerability of a web site, comprising: a processor; and a non-transitory computer readable medium having instructions embedded therein, the instructions executable by a processor and configured to: receive a first set of addresses, identify a second set of addresses by analyzing the first set of web pages located at the first set of addresses, and identify a third set of addresses by analyzing a first set of document object models (DOMs) associated with the first set of web pages and a second set of web pages located at the second set of addresses; probe a third set of web pages for presence of a set of vulnerabilities using a document object model (DOM) analysis script to analyze a second set of document object models (DOMs) associated with the third set of web pages as a set of attack vectors is applied to the third set of web pages, and determine presence of the set of vulnerabilities for the third set of web pages based on a result from the probing, wherein the third set of web pages is located at the first, second, and third sets of addresses, wherein the DOM analysis script is inserted into the third set of web pages, and wherein the attack vectors are designed to exploit a vulnerability of a web page. 22. The system of claim 14 , wherein the tested vulnerability comprises a document object model (DOM)-based Cross-Site Scripting (DOMXSS) vulnerability. | 0.745819 |
8,185,087 | 1 | 2 | 1. A method of providing 911 equivalent data emergency services to an emergency data initiator using a non-persistent connection, comprising: associating a request for location, relating to a non-persistent emergency data message, with a geo-location; modifying a format of said non-persistent emergency data message to formulate an emergency services provider formatted non-persistent emergency data message; routing, toward an appropriate emergency services provider, said emergency services provider formatted non-persistent emergency data message; and staging location information, for said emergency services provider format modified non-persistent emergency data message, for use by said appropriate emergency services provider. | 1. A method of providing 911 equivalent data emergency services to an emergency data initiator using a non-persistent connection, comprising: associating a request for location, relating to a non-persistent emergency data message, with a geo-location; modifying a format of said non-persistent emergency data message to formulate an emergency services provider formatted non-persistent emergency data message; routing, toward an appropriate emergency services provider, said emergency services provider formatted non-persistent emergency data message; and staging location information, for said emergency services provider format modified non-persistent emergency data message, for use by said appropriate emergency services provider. 2. The method of providing 911 equivalent data emergency services to an emergency data initiator using a non-persistent connection according to claim 1 , wherein said useable format comprises: a canned voice message. | 0.573123 |
7,949,718 | 15 | 17 | 15. The computer-readable medium of claim 14 , the program further causing the computer to perform at least the following: compare the generated Bayesian probability value with a predefined threshold value. | 15. The computer-readable medium of claim 14 , the program further causing the computer to perform at least the following: compare the generated Bayesian probability value with a predefined threshold value. 17. The computer-readable medium of claim 15 , the program further causing the computer to perform at least the following: categorize the received email message as non-spam in response to the Bayesian probability value being not greater than the predefined threshold value. | 0.5 |
7,664,734 | 30 | 37 | 30. A computer system for generating multiple implicit search queries, comprising: a memory; a processor; a monitoring module stored in the memory and executable by the processor to identify a plurality of events responsive to monitoring real-time user interactions with a client device; a user-context attributes module stored in the memory and executable by the processor to identify a plurality of user-context attributes based at least in part on the plurality of events, wherein the plurality of user-context attributes indicate aspects of real-time user interactions with the client device; a search query module stored in the memory and executable by the processor to generate implicit search queries comprising terms, wherein the terms are based at least in part on the plurality of user-context attributes; a search results module stored in the memory and executable by the processor to receive a plurality of search results generated responsive to the plurality of implicit search queries; and a display module stored in the memory and executable by the processor to update a display of search results responsive to receiving the plurality of search results. | 30. A computer system for generating multiple implicit search queries, comprising: a memory; a processor; a monitoring module stored in the memory and executable by the processor to identify a plurality of events responsive to monitoring real-time user interactions with a client device; a user-context attributes module stored in the memory and executable by the processor to identify a plurality of user-context attributes based at least in part on the plurality of events, wherein the plurality of user-context attributes indicate aspects of real-time user interactions with the client device; a search query module stored in the memory and executable by the processor to generate implicit search queries comprising terms, wherein the terms are based at least in part on the plurality of user-context attributes; a search results module stored in the memory and executable by the processor to receive a plurality of search results generated responsive to the plurality of implicit search queries; and a display module stored in the memory and executable by the processor to update a display of search results responsive to receiving the plurality of search results. 37. The system of claim 30 , wherein the search results comprise a first search result set and the display module for updating a display of search results responsive to receiving the plurality of search results is adapted to combine the first result set with a second result set, the second result set comprised of results from previously generated search queries. | 0.538071 |
8,504,923 | 16 | 17 | 16. The non-transitory computer readable memory of claim 14 , further comprising: an event engine to notify an application of the plurality of applications of the occurrence of an event. | 16. The non-transitory computer readable memory of claim 14 , further comprising: an event engine to notify an application of the plurality of applications of the occurrence of an event. 17. The non-transitory computer readable memory of claim 16 , wherein the event engine is further to: register a function to call to notify the application of the occurrence of the event; and call the registered function to notify the application of the occurrence of the event. | 0.5 |
8,212,695 | 1 | 2 | 1. A method for generating a hierarchical data structure associated with a plurality of arbitrary-length bit strings, the method comprising: a) for each of the plurality of arbitrary-length bit strings within a group, hashing the arbitrary-length bit string, using a selected hash function from a plurality of hash functions, to generate a hash value representing an n-bit binary address defining a location of a virtual bin; b) for each of n bit locations, determining a bit location count of all of the generated n-bit binary addresses; c) determining a representative bit location corresponding to one of the n bit locations; d) storing an indication of the hash function and the representative bit location; e) for each of the plurality of arbitrary-length bit strings, assigning the arbitrary-length bit string to one of a first group and a second group using a bit value at the representative bit location of its hash value, wherein the arbitrary-length bit string is assigned to a first group if the bit value is of a fist bit value and a second group if the bit value is of a second bit value; f) for each of the groups, repeating acts (a) through (e) to generate two further sub-groups until each of the two further sub-groups has one or no assigned arbitrary-length bit string; and g) storing, for each of the plurality of arbitrary-length bit strings, the arbitrary-length bit string or a pointer thereto, in a memory location defined by a concatenation of the bit values. | 1. A method for generating a hierarchical data structure associated with a plurality of arbitrary-length bit strings, the method comprising: a) for each of the plurality of arbitrary-length bit strings within a group, hashing the arbitrary-length bit string, using a selected hash function from a plurality of hash functions, to generate a hash value representing an n-bit binary address defining a location of a virtual bin; b) for each of n bit locations, determining a bit location count of all of the generated n-bit binary addresses; c) determining a representative bit location corresponding to one of the n bit locations; d) storing an indication of the hash function and the representative bit location; e) for each of the plurality of arbitrary-length bit strings, assigning the arbitrary-length bit string to one of a first group and a second group using a bit value at the representative bit location of its hash value, wherein the arbitrary-length bit string is assigned to a first group if the bit value is of a fist bit value and a second group if the bit value is of a second bit value; f) for each of the groups, repeating acts (a) through (e) to generate two further sub-groups until each of the two further sub-groups has one or no assigned arbitrary-length bit string; and g) storing, for each of the plurality of arbitrary-length bit strings, the arbitrary-length bit string or a pointer thereto, in a memory location defined by a concatenation of the bit values. 2. The method of claim 1 wherein the bit location count at a bit location is a summation of the number of bits having a first bit value at the bit location of all of the generated n-bit binary addresses. | 0.5 |
8,082,270 | 1 | 2 | 1. A computer implemented method of progressively relaxing search terms provided by a user for finding matches of said search terms in a database, comprising the steps of: storing data of predefined types into a plurality of first data fields of a multicolumn table in said database, wherein said data is obtained by uniquely modifying data previously stored in a plurality of second data fields in the database, wherein said previously stored data is modified based on said predefined types of the previously stored data, wherein the predefined types comprise name, street address, city, state, zip, and country; accepting a plurality of the search terms of the predefined types from said user, wherein length of said accepted search terms is computed; comparing the accepted search terms with said stored data in said first data fields to find exact matches, if said length of the accepted search terms is greater than a predefined value; modifying the accepted search terms to structure first alternative queries if said exact matches are not found, wherein each of the accepted search terms is modified uniquely based on the predefined types of the accepted search terms; comparing said structured first alternative queries with the stored data in the first data fields to find exact matches; modifying the first alternative queries to structure second alternative queries if said exact matches are not found, wherein each of the first alternative queries is modified uniquely based on the predefined types of the first alternative queries, and wherein said steps of modifying the accepted search terms and modifying the first alternative queries comprise concatenating and compensating for spelling errors, typographical errors, punctuation errors, phonological ambiguity, and non standard querying; and comparing by the comparison module said structured second alternative queries with the stored data in the first data fields to find approximate matches; whereby said modification of the search terms and the first alternative queries to structure the first alternative queries and the second alternative queries respectively enables progressive relaxation of the search terms for finding matches of the search terms in the database. | 1. A computer implemented method of progressively relaxing search terms provided by a user for finding matches of said search terms in a database, comprising the steps of: storing data of predefined types into a plurality of first data fields of a multicolumn table in said database, wherein said data is obtained by uniquely modifying data previously stored in a plurality of second data fields in the database, wherein said previously stored data is modified based on said predefined types of the previously stored data, wherein the predefined types comprise name, street address, city, state, zip, and country; accepting a plurality of the search terms of the predefined types from said user, wherein length of said accepted search terms is computed; comparing the accepted search terms with said stored data in said first data fields to find exact matches, if said length of the accepted search terms is greater than a predefined value; modifying the accepted search terms to structure first alternative queries if said exact matches are not found, wherein each of the accepted search terms is modified uniquely based on the predefined types of the accepted search terms; comparing said structured first alternative queries with the stored data in the first data fields to find exact matches; modifying the first alternative queries to structure second alternative queries if said exact matches are not found, wherein each of the first alternative queries is modified uniquely based on the predefined types of the first alternative queries, and wherein said steps of modifying the accepted search terms and modifying the first alternative queries comprise concatenating and compensating for spelling errors, typographical errors, punctuation errors, phonological ambiguity, and non standard querying; and comparing by the comparison module said structured second alternative queries with the stored data in the first data fields to find approximate matches; whereby said modification of the search terms and the first alternative queries to structure the first alternative queries and the second alternative queries respectively enables progressive relaxation of the search terms for finding matches of the search terms in the database. 2. The computer implemented method of claim 1 , further comprising a step of ranking said found matches based on accuracy of the found matches. | 0.5 |
10,026,047 | 1 | 4 | 1. A system for crowd sourcing tasks, comprising: a processor; a crowd sourcing module operating on the processor, the crowd sourcing module being configured to cause the processor to perform a set of functions comprising: identifying a group of potential candidates for crowd sourcing, wherein each candidate of the group of potential candidates is identified based on the candidate being expected to accept an offer for performance of a certain type of task, the certain type of task being at least performable within a predetermined range of time; receiving a request to perform a particular task from a requester; determining if the particular task corresponds to the certain type of task; and transmitting an offer for performance of the particular task to a subgroup of the group of potential candidates in response to the particular task corresponding to the certain type of task, wherein transmitting the offer for performance of the particular task to the subgroup of the group of potential candidates comprises: determining when any candidates of the group of potential candidates are currently performing the same task or similar task to the particular task, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that are currently performing the same task or the similar task; determining when any candidates of the group of potential candidates have a history of completing the same task or the similar task to the particular task faster than other candidates, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that have the history of completing the same task or the similar task faster than the other candidates; determining when a particular candidate of the group of potential candidates has completed a specific task, and transmitting the offer for performance of the particular task to the particular candidate in response to the particular candidate having completed the specific task, wherein the specific task is related to the particular task being offered; and determining when any candidates of the group of potential candidates have reached a predefined quota of one of a total time in performing a group of tasks during a set time period or a number of tasks performed during the set time period, and not transmitting an offer for performance of another task to any candidates of the group of potential candidates that have reached the predefined quota until a next set time period, wherein the next set time period is configurable by a user based on a policy. | 1. A system for crowd sourcing tasks, comprising: a processor; a crowd sourcing module operating on the processor, the crowd sourcing module being configured to cause the processor to perform a set of functions comprising: identifying a group of potential candidates for crowd sourcing, wherein each candidate of the group of potential candidates is identified based on the candidate being expected to accept an offer for performance of a certain type of task, the certain type of task being at least performable within a predetermined range of time; receiving a request to perform a particular task from a requester; determining if the particular task corresponds to the certain type of task; and transmitting an offer for performance of the particular task to a subgroup of the group of potential candidates in response to the particular task corresponding to the certain type of task, wherein transmitting the offer for performance of the particular task to the subgroup of the group of potential candidates comprises: determining when any candidates of the group of potential candidates are currently performing the same task or similar task to the particular task, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that are currently performing the same task or the similar task; determining when any candidates of the group of potential candidates have a history of completing the same task or the similar task to the particular task faster than other candidates, and transmitting the offer for performance of the particular task to the subgroup of potential candidates that have the history of completing the same task or the similar task faster than the other candidates; determining when a particular candidate of the group of potential candidates has completed a specific task, and transmitting the offer for performance of the particular task to the particular candidate in response to the particular candidate having completed the specific task, wherein the specific task is related to the particular task being offered; and determining when any candidates of the group of potential candidates have reached a predefined quota of one of a total time in performing a group of tasks during a set time period or a number of tasks performed during the set time period, and not transmitting an offer for performance of another task to any candidates of the group of potential candidates that have reached the predefined quota until a next set time period, wherein the next set time period is configurable by a user based on a policy. 4. The system of claim 1 , wherein the crowd sourcing module is further configured for delegating the particular task to another candidate in response to the particular task not being completed by an accepting candidate within a predetermined time period, wherein the particular task is delegated to the other candidate based on at least one of a skill of the other candidate and an availability of the other candidate. | 0.674184 |
8,959,116 | 5 | 6 | 5. The non-transitory machine readable medium of claim 3 , wherein the object representation is a first object representation, wherein the document is further stored as a second, different object representation comprising a second set of object nodes arranged in a second tree structure, the object nodes in the second object representation also referencing ranges of indices in the content stream. | 5. The non-transitory machine readable medium of claim 3 , wherein the object representation is a first object representation, wherein the document is further stored as a second, different object representation comprising a second set of object nodes arranged in a second tree structure, the object nodes in the second object representation also referencing ranges of indices in the content stream. 6. The non-transitory machine readable medium of claim 5 , wherein the second tree structure is a style tree structure, wherein the set of instructions for converting further comprises a set of instructions for transforming the outputted content according to nodes in the style tree structure. | 0.5 |
8,855,797 | 34 | 39 | 34. A computer readable, non-transitory storage medium having at least one computer-executable component for providing synchronized content, the at least one computer-executable component comprising: a content synchronization module operative, during output of a first content and an associated second content, to: maintain, based at least in part on synchronization information, synchronization between an output pointer of the second content and an associated position of the first content, wherein the associated position of the first content advances during output of the first content, and wherein the output pointer indicates a position within the second content corresponding to a current output position of the first content; obtain an input pointer that references a location within the second content; during advancement of the output pointer, determine, independent of the obtained input pointer, a position of the output pointer corresponding to the current output position of the first content; and modify an attribute associated with the output of the first content based at least in part on a difference between the determined position of the output pointer and the location within the second content referenced by the input pointer. | 34. A computer readable, non-transitory storage medium having at least one computer-executable component for providing synchronized content, the at least one computer-executable component comprising: a content synchronization module operative, during output of a first content and an associated second content, to: maintain, based at least in part on synchronization information, synchronization between an output pointer of the second content and an associated position of the first content, wherein the associated position of the first content advances during output of the first content, and wherein the output pointer indicates a position within the second content corresponding to a current output position of the first content; obtain an input pointer that references a location within the second content; during advancement of the output pointer, determine, independent of the obtained input pointer, a position of the output pointer corresponding to the current output position of the first content; and modify an attribute associated with the output of the first content based at least in part on a difference between the determined position of the output pointer and the location within the second content referenced by the input pointer. 39. The computer-readable, non-transitory storage medium of claim 34 , wherein modifying an attribute associated with the output of the first content comprises at least one of: outputting the first content at a first rate if the difference between the determined position of the output pointer and the location within the second content referenced by the input pointer satisfies a first threshold value for a first predetermined length of time; outputting the first content at a second rate if the difference between the determined position of the output pointer and the location within the second content referenced by the input pointer satisfies a second threshold value for a second predetermined length of time, wherein the second rate is faster than the first rate; or outputting the first content at a third rate if the difference between the determined position of the output pointer and the location within the second content referenced by the input pointer satisfies a third threshold value for a third predetermined length of time, wherein the third rate is faster than the second rate. | 0.5 |
9,177,540 | 12 | 16 | 12. A machine-readable storage medium storing machine-executable instructions for causing a processor to perform a method of conforming an audio input to a musical key, the method comprising: receiving an audio input; determining a musical key of the audio input; sequentially for each consecutive note of the audio input, determining a pitch value for a preceding note and a subsequent note and an interval between the preceding note and the subsequent note of the audio input, selecting a plurality of alternative subsequent notes for each subsequent note based on the determined musical key and the determined pitch value of the subsequent note, scoring each interval between each alternative subsequent note and each respective note of a selected plurality of alternative subsequent notes corresponding to the preceding note based on the interval between the preceding note and the subsequent note of the audio input, selecting a best interval for each alternative subsequent note based on the scored intervals, determining a probability of each alternative subsequent note following each respective note of the selected plurality of subsequent notes corresponding to the preceding note based on analysis of a selection of existing musical compositions, and selecting a best-match note for each note of the audio input based on the best intervals of all of the plurality of notes of the audio input and the determined probabilities of all the plurality of notes of the audio input; and conforming each note of the audio input to a frequency of each respective best-match note. | 12. A machine-readable storage medium storing machine-executable instructions for causing a processor to perform a method of conforming an audio input to a musical key, the method comprising: receiving an audio input; determining a musical key of the audio input; sequentially for each consecutive note of the audio input, determining a pitch value for a preceding note and a subsequent note and an interval between the preceding note and the subsequent note of the audio input, selecting a plurality of alternative subsequent notes for each subsequent note based on the determined musical key and the determined pitch value of the subsequent note, scoring each interval between each alternative subsequent note and each respective note of a selected plurality of alternative subsequent notes corresponding to the preceding note based on the interval between the preceding note and the subsequent note of the audio input, selecting a best interval for each alternative subsequent note based on the scored intervals, determining a probability of each alternative subsequent note following each respective note of the selected plurality of subsequent notes corresponding to the preceding note based on analysis of a selection of existing musical compositions, and selecting a best-match note for each note of the audio input based on the best intervals of all of the plurality of notes of the audio input and the determined probabilities of all the plurality of notes of the audio input; and conforming each note of the audio input to a frequency of each respective best-match note. 16. The machine-readable storage medium of claim 12 , wherein the audio input is live audio input. | 0.8775 |
8,484,377 | 5 | 7 | 5. A processing system for prepending nonce labels to DNS queries, the system comprising: at least one processor; a nonce label analyzer module associated with the at least one processor, the nonce label analyzer module being configured: to evaluate whether a log stored in memory contains at least one past entry of a domain name resolution query to a name server for a full domain name that resulted in a positive reply indicating that the full domain name did exist, to determine whether the log contains at least one recent entry of the domain name resolution query to the name server for the full domain name that resulted in a negative reply indicating that the full domain name did not exist, if it is determined that the log contains the at least one past entry of the domain name resolution query, to determine whether querying the name server with a nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that the log contains the at least one recent entry of the domain name resolution query, to determine whether querying the name server with a nonce label prepended query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that querying the name server with the nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, and to flag the full domain name as inappropriate for nonce label prepending, if it is determined that querying the name server with a nonce label prepended query for the full domain name currently results in the negative reply indicating that the full domain name does not exist. | 5. A processing system for prepending nonce labels to DNS queries, the system comprising: at least one processor; a nonce label analyzer module associated with the at least one processor, the nonce label analyzer module being configured: to evaluate whether a log stored in memory contains at least one past entry of a domain name resolution query to a name server for a full domain name that resulted in a positive reply indicating that the full domain name did exist, to determine whether the log contains at least one recent entry of the domain name resolution query to the name server for the full domain name that resulted in a negative reply indicating that the full domain name did not exist, if it is determined that the log contains the at least one past entry of the domain name resolution query, to determine whether querying the name server with a nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that the log contains the at least one recent entry of the domain name resolution query, to determine whether querying the name server with a nonce label prepended query for the full domain name currently results in the positive reply indicating that the full domain name exists, if it is determined that querying the name server with the nonce-less query for the full domain name currently results in the positive reply indicating that the full domain name exists, and to flag the full domain name as inappropriate for nonce label prepending, if it is determined that querying the name server with a nonce label prepended query for the full domain name currently results in the negative reply indicating that the full domain name does not exist. 7. The processing system of claim 5 , wherein the log is a DNS resolver log. | 0.751634 |
8,671,364 | 1 | 4 | 1. An apparatus, comprising: a logic device; and an information visualization application operative on the logic device, the information visualization application comprising a multivariable presentation component arranged to generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level, the selectable GUI element of the hierarchical level positioned adjacent to the decomposed GUI elements of the different hierarchical level when the selectable GUI element is selected for decomposition. | 1. An apparatus, comprising: a logic device; and an information visualization application operative on the logic device, the information visualization application comprising a multivariable presentation component arranged to generate a multivariable decomposition visualization to present hierarchical information for a response variable and multiple reporting variables defined for the response variable in a single user interface view, the multivariable decomposition visualization comprising multiple graphical user interface (GUI) elements each representing a reporting variable value of multiple reporting variables for multiple hierarchical levels, with a GUI element of a reporting variable value of a reporting variable of a hierarchical level selectable for decomposition into multiple GUI elements representing reporting variable values of a different reporting variable for a different hierarchical level, the selectable GUI element of the hierarchical level positioned adjacent to the decomposed GUI elements of the different hierarchical level when the selectable GUI element is selected for decomposition. 4. The apparatus of claim 1 , the multivariable presentation component operative to receive a control directive selecting the selectable GUI element of the hierarchical level for decomposition into decomposed GUI elements of the different hierarchical level. | 0.8 |
10,146,994 | 4 | 6 | 4. A method of generating a text line classifier, the method comprising: selecting a plurality of text characters from a font reservoir; varying an aspect of the plurality of text characters to form a plurality of character samples; randomly arranging a number of character samples from the plurality of character samples to form a line of character samples; varying an aspect of the line of character samples to form a line of text characters; and extracting from the line of text characters one or more of a gradient orientation histogram feature, a gradient magnitude histogram feature, a pixel histogram feature, and a pixel histogram change feature. | 4. A method of generating a text line classifier, the method comprising: selecting a plurality of text characters from a font reservoir; varying an aspect of the plurality of text characters to form a plurality of character samples; randomly arranging a number of character samples from the plurality of character samples to form a line of character samples; varying an aspect of the line of character samples to form a line of text characters; and extracting from the line of text characters one or more of a gradient orientation histogram feature, a gradient magnitude histogram feature, a pixel histogram feature, and a pixel histogram change feature. 6. The method of claim 4 , wherein: the text characters in the line of text characters have a same size, a same rotation angle, and a same font; and more than half of the text characters in the line of text characters are commonly used characters. | 0.5 |
8,527,278 | 14 | 18 | 14. A system of intelligent home automation, comprising: a parser analyzer that considers three hypotheses as to what a speaker means but can short circuit consideration of the hypotheses if it detects a strong imperative structure; memory structures including structures concerning term, phrase, relation and including knowledge structures, a question answering routine capable of accessing memory structures to store declarations, responding to commands by controlling home circuits and generating natural language responses to natural language queries by converting queries into declarations in conjunction with the parser analyzer and searching the knowledge structures for similar declarations that end with an answer or represent an answer, the question answering routine also capable of accessing data from global telecommunications system to respond to queries from a home user and storing such data in the knowledge structures for use in natural language responses; software capable of identification of a visitor to the home based on a signal from the visitor; a speaker for announcing the identity of the visitors in natural language to a home user, and hardware connected to home circuits that control objects. | 14. A system of intelligent home automation, comprising: a parser analyzer that considers three hypotheses as to what a speaker means but can short circuit consideration of the hypotheses if it detects a strong imperative structure; memory structures including structures concerning term, phrase, relation and including knowledge structures, a question answering routine capable of accessing memory structures to store declarations, responding to commands by controlling home circuits and generating natural language responses to natural language queries by converting queries into declarations in conjunction with the parser analyzer and searching the knowledge structures for similar declarations that end with an answer or represent an answer, the question answering routine also capable of accessing data from global telecommunications system to respond to queries from a home user and storing such data in the knowledge structures for use in natural language responses; software capable of identification of a visitor to the home based on a signal from the visitor; a speaker for announcing the identity of the visitors in natural language to a home user, and hardware connected to home circuits that control objects. 18. The system of claim 14 , wherein even after being prompted to analyze what the home user says, the system, at designated time intervals, moves to sleep mode wherein the system does not do anything or analyze what the home user says unless the home user designates an emergency. | 0.5 |
8,494,837 | 10 | 11 | 10. The method of claim 9 , wherein the method steps further comprise: creating a subset H of highest confidence scores; adding the translations in subset H directly to the parallel corpus; creating a subset L of lowest confidence scores; presenting subset L to human translators for correction; and adding human corrections to the parallel corpus. | 10. The method of claim 9 , wherein the method steps further comprise: creating a subset H of highest confidence scores; adding the translations in subset H directly to the parallel corpus; creating a subset L of lowest confidence scores; presenting subset L to human translators for correction; and adding human corrections to the parallel corpus. 11. The method of claim 10 , wherein the step of presenting the subset L to human translators for correction comprises presenting a Graphical User Interface (GUI) to the translator, the GUI providing at least the items in subset L, a window to make translation corrections, and an update button. | 0.5 |
8,892,992 | 11 | 12 | 11. A method for defining a structure for a document comprising a plurality of primitive elements, the method comprising: defining an indirectly sorted first array that stores sorted indices of a second array of difference values, wherein the difference values indicate differences between sorted attribute values of different primitive elements, the primitive elements being defined in terms of the attribute values; using the indirectly sorted first array to generate a plurality of different partition sets at different distance scales for the plurality of primitive elements; from the plurality of partition sets, selecting an optimal partition set based on a set of optimization measures; and grouping the plurality of primitive elements using the optimal partition set in order to associate a subset of the primitive elements as a structured element in the document. | 11. A method for defining a structure for a document comprising a plurality of primitive elements, the method comprising: defining an indirectly sorted first array that stores sorted indices of a second array of difference values, wherein the difference values indicate differences between sorted attribute values of different primitive elements, the primitive elements being defined in terms of the attribute values; using the indirectly sorted first array to generate a plurality of different partition sets at different distance scales for the plurality of primitive elements; from the plurality of partition sets, selecting an optimal partition set based on a set of optimization measures; and grouping the plurality of primitive elements using the optimal partition set in order to associate a subset of the primitive elements as a structured element in the document. 12. The method of claim 11 , wherein the plurality of primitive elements are a set of glyphs in the document, the attribute values are location values of the primitive elements in the document, and the subsets of primitive elements are words in the document. | 0.5 |
8,434,013 | 9 | 16 | 9. A non-transitory machine readable storage medium, comprising: instructions for causing one or more processors to render a first computer code portion of a file in a first section of a user interface, wherein the file comprises computer code in a textual form, wherein the file comprises the first computer code portion and a second computer code portion that is functionally contained within the first computer code portion; instructions for causing one or more processors to process the computer code in the file to extract one or more non-textual aspects of the computer code; instructions for causing one or more processors to generate a topographic image to graphically represent the one or more non-textual aspects of the computer code, wherein generating the topographic image comprises positioning a second image portion corresponding to the second computer code portion within a first image portion corresponding to the first computer code portion to indicate that the second computer code portion is functionally contained within the first computer code portion, wherein the topographic image provides a graphical representation for all of the computer code in the file, and wherein the one or more non-textual aspects of the computer code comprises a functional aspect of the computer code; instructions for causing one or more processors to render the topographic image in a second section of the user interface; instructions for causing one or more processors to receive an indication of user selection at a first position in the topographic image; instructions for causing one or more processors to correlate the first position with a second position in the file; and instructions for causing one or more processors to render a second portion of the file in the first section of the user interface, wherein the second position is within the second portion of the file. | 9. A non-transitory machine readable storage medium, comprising: instructions for causing one or more processors to render a first computer code portion of a file in a first section of a user interface, wherein the file comprises computer code in a textual form, wherein the file comprises the first computer code portion and a second computer code portion that is functionally contained within the first computer code portion; instructions for causing one or more processors to process the computer code in the file to extract one or more non-textual aspects of the computer code; instructions for causing one or more processors to generate a topographic image to graphically represent the one or more non-textual aspects of the computer code, wherein generating the topographic image comprises positioning a second image portion corresponding to the second computer code portion within a first image portion corresponding to the first computer code portion to indicate that the second computer code portion is functionally contained within the first computer code portion, wherein the topographic image provides a graphical representation for all of the computer code in the file, and wherein the one or more non-textual aspects of the computer code comprises a functional aspect of the computer code; instructions for causing one or more processors to render the topographic image in a second section of the user interface; instructions for causing one or more processors to receive an indication of user selection at a first position in the topographic image; instructions for causing one or more processors to correlate the first position with a second position in the file; and instructions for causing one or more processors to render a second portion of the file in the first section of the user interface, wherein the second position is within the second portion of the file. 16. The non-transitory machine readable storage medium of claim 9 , wherein the instructions for causing one or more processors to render the topographic image in a second section of the user interface include instructions for causing one or more processors to make the topographic image visible in its entirety in the second section of the user interface; and further comprising instructions for causing one or more processors to repeat the instructions for causing the one or more processors to process the computer code in the file extract one or more non-textual aspects of the computer code through the instructions for causing one or more processors to render a second portion of the file in the first section of the user interface in response to receiving an indication that the file has been edited. | 0.5 |
8,926,672 | 20 | 23 | 20. In a spinal fixation structure having a bone anchor and a closure, the anchor for holding a spinal fixation longitudinal connecting member, the anchor having an open receiver with spaced apart arms defining a longitudinal connecting member receiving channel therebetween and the closure sized for being received within the channel and adapted for rotation and advancement into the channel between the arms to capture a portion of the longitudinal connecting member in the channel, the improvement comprising: a) a closure guide and advancement flange form extending helically along the closure and about a central axis of the closure, the flange form having a pitch of between 0.045 and 0.055 inches, and having a crest portion with a first axial height and a root portion having a second axial height, the first height measured from a top of an upwardly extending toe of the flange form to a stab flank and taken substantially along a crest surface of the flange form, the second height measured from a load flank of the flange form to the stab flank and taken substantially along a root surface of the flange form, the first height being one of slightly less and substantially equal to the second height, the flange form having a splay control ramp surface located between the toe and the load flank running substantially at an oblique angle with respect to a radius of the closure running perpendicular to the closure axis; and b) a discontinuous receiver guide and advancement flange form extending helically about and along an inner surface of each receiver arm, the receiver flang form having a cooperating splay control ramp engaging the closure flange form control ramp during mating of the closure flange form with the receiver flange form, the receiver flange form having a clearance surfaces disposed in close spaced relation to the closure toe, the toe remaining unloaded during mating engagement and torquing of the closure flange form with the receiver flange form. | 20. In a spinal fixation structure having a bone anchor and a closure, the anchor for holding a spinal fixation longitudinal connecting member, the anchor having an open receiver with spaced apart arms defining a longitudinal connecting member receiving channel therebetween and the closure sized for being received within the channel and adapted for rotation and advancement into the channel between the arms to capture a portion of the longitudinal connecting member in the channel, the improvement comprising: a) a closure guide and advancement flange form extending helically along the closure and about a central axis of the closure, the flange form having a pitch of between 0.045 and 0.055 inches, and having a crest portion with a first axial height and a root portion having a second axial height, the first height measured from a top of an upwardly extending toe of the flange form to a stab flank and taken substantially along a crest surface of the flange form, the second height measured from a load flank of the flange form to the stab flank and taken substantially along a root surface of the flange form, the first height being one of slightly less and substantially equal to the second height, the flange form having a splay control ramp surface located between the toe and the load flank running substantially at an oblique angle with respect to a radius of the closure running perpendicular to the closure axis; and b) a discontinuous receiver guide and advancement flange form extending helically about and along an inner surface of each receiver arm, the receiver flang form having a cooperating splay control ramp engaging the closure flange form control ramp during mating of the closure flange form with the receiver flange form, the receiver flange form having a clearance surfaces disposed in close spaced relation to the closure toe, the toe remaining unloaded during mating engagement and torquing of the closure flange form with the receiver flange form. 23. The improvement of claim 20 wherein a pitch of the closure flange form ranges from between about 0.040 inches and about 0.120 inches. | 0.5 |
10,120,952 | 1 | 2 | 1. An application specification system, comprising: a computing device having a processor and memory wherein the processor implements an information management system having a storage unit; the storage unit having an application definition language that has an XML schema definition that defines computational and data access aspects of an application, the application hosting a web presence on the computing device, the XML schema definition of the application definition language provides a consistent definition of the computational and data access aspects of an application used to develop a new web application running on a third party system; the storage unit having one or more cells with each cell having one or more components wherein each component defines computational and data access aspects of an application and one or more presentations wherein each presentation defines a user interface for a particular application, each cell further comprising one or more lines of XML code, each component further comprising one or more lines of XML code, each web presence further comprising one or more lines of XML code, each component further comprises a widget that comprises one or more lines of XML code and component further comprises an action item that comprises one or more lines of XML code; wherein the web presence performs one or more applications that is instantiated from a cell instance that has one or more components, one or more presentations and content associated with the cell instance, the one or more applications of the web presence are defined by the application definition language and one or more components of the cell instance and the user interface of the one or more applications are defined by the one or more presentations of the cell instance wherein the one or more applications are configured to operate on the content associated with the cell instance; and wherein the web presence is one of a web site, one or more web pages and a web service. | 1. An application specification system, comprising: a computing device having a processor and memory wherein the processor implements an information management system having a storage unit; the storage unit having an application definition language that has an XML schema definition that defines computational and data access aspects of an application, the application hosting a web presence on the computing device, the XML schema definition of the application definition language provides a consistent definition of the computational and data access aspects of an application used to develop a new web application running on a third party system; the storage unit having one or more cells with each cell having one or more components wherein each component defines computational and data access aspects of an application and one or more presentations wherein each presentation defines a user interface for a particular application, each cell further comprising one or more lines of XML code, each component further comprising one or more lines of XML code, each web presence further comprising one or more lines of XML code, each component further comprises a widget that comprises one or more lines of XML code and component further comprises an action item that comprises one or more lines of XML code; wherein the web presence performs one or more applications that is instantiated from a cell instance that has one or more components, one or more presentations and content associated with the cell instance, the one or more applications of the web presence are defined by the application definition language and one or more components of the cell instance and the user interface of the one or more applications are defined by the one or more presentations of the cell instance wherein the one or more applications are configured to operate on the content associated with the cell instance; and wherein the web presence is one of a web site, one or more web pages and a web service. 2. The system of claim 1 , wherein each component further comprises a variable associated with the component wherein the variable is recalculated automatically, wherein the variable further comprises a formula portion that specifies a value of the variable and wherein the formula further comprises a situated query to retrieve data from the same cell or from other cells and a context for the situated query is specified by the particular cell or within the situated query. | 0.615883 |
8,635,066 | 6 | 7 | 6. The computer-implemented method of claim 1 , further comprising determining that speech input is initiated when the facial image sequence indicates that a particular speaker begins to utter sounds. | 6. The computer-implemented method of claim 1 , further comprising determining that speech input is initiated when the facial image sequence indicates that a particular speaker begins to utter sounds. 7. The computer-implemented method of claim 6 , further comprising determining that the speech input is terminated when a facial image of the particular speaker moves out of the view of a camera of the electronic device or when the facial image sequence indicates that the particular speaker has not uttered sounds for a predetermined period of time. | 0.5 |
8,654,940 | 10 | 14 | 10. A method for extending a voice server to add text exchange capabilities, the method comprising acts of: during an interactive dialogue between a text exchange client and a speech enabled application executing on a VoiceXML server, dynamically translating output text that is automatically generated in response to text received from the text exchange client and is grammatically part of a conversational language into corresponding text that is grammatically part of a text exchange specific language, wherein the corresponding text comprises at least one letter and/or at least one emoticon; and sending the translated output text to the text exchange client. | 10. A method for extending a voice server to add text exchange capabilities, the method comprising acts of: during an interactive dialogue between a text exchange client and a speech enabled application executing on a VoiceXML server, dynamically translating output text that is automatically generated in response to text received from the text exchange client and is grammatically part of a conversational language into corresponding text that is grammatically part of a text exchange specific language, wherein the corresponding text comprises at least one letter and/or at least one emoticon; and sending the translated output text to the text exchange client. 14. The method of claim 10 , wherein the text output is dynamically translated into corresponding output text using a user configurable translation table. | 0.764526 |
7,752,501 | 21 | 26 | 21. A computer program product for performing dynamic globalization verification testing of a software user interface, comprising: one or more machine readable storage media; programming instructions provided by said machine readable storage media for programming a data processing platform to support global verification testing of a software user interface, as by: identifying one or more user interface controls in said software user interface having text strings that have been pseudo translated; generating one or more applicable test cases that test for display defects stemming from said pseudo translations; executing said test cases; and logging defects discovered by executing said test cases. | 21. A computer program product for performing dynamic globalization verification testing of a software user interface, comprising: one or more machine readable storage media; programming instructions provided by said machine readable storage media for programming a data processing platform to support global verification testing of a software user interface, as by: identifying one or more user interface controls in said software user interface having text strings that have been pseudo translated; generating one or more applicable test cases that test for display defects stemming from said pseudo translations; executing said test cases; and logging defects discovered by executing said test cases. 26. A computer program product in accordance with claim 21 wherein said one or more applicable test cases are generated by categorizing said one or more user interface controls by type. | 0.641473 |
10,052,769 | 1 | 25 | 1. A humanoid robot, comprising: i) at least one sensor selected from a group comprising audio sensors and visual sensors of events generated by at least one user of said robot, ii) at least one event recognition module at the output of said at least one sensor and, iii) at least one module for generating events towards said at least one user, a module for dialog with said at least one user, said dialog module receiving as input the outputs of said at least one recognition module and producing outputs to said event generation module selected from a group including speech, movements, expressions and emotions, wherein said robot further includes an artificial intelligence engine configured for controlling the outputs of the event generation module according to a context of dialog and variables defining emotions of the robot as a series of expressions between a neutral state and a terminal state, an evolution between said neutral state and said terminal state being triggered by a pulse generated as a function of time and of one or more of the outputs of the at least a sensor, the event recognition module, the dialog module and the event generation module. | 1. A humanoid robot, comprising: i) at least one sensor selected from a group comprising audio sensors and visual sensors of events generated by at least one user of said robot, ii) at least one event recognition module at the output of said at least one sensor and, iii) at least one module for generating events towards said at least one user, a module for dialog with said at least one user, said dialog module receiving as input the outputs of said at least one recognition module and producing outputs to said event generation module selected from a group including speech, movements, expressions and emotions, wherein said robot further includes an artificial intelligence engine configured for controlling the outputs of the event generation module according to a context of dialog and variables defining emotions of the robot as a series of expressions between a neutral state and a terminal state, an evolution between said neutral state and said terminal state being triggered by a pulse generated as a function of time and of one or more of the outputs of the at least a sensor, the event recognition module, the dialog module and the event generation module. 25. The humanoid robot of claim 1 , wherein the variables further define one or more of resources available to the robot or system constraints applied to the robot. | 0.790816 |
9,094,691 | 3 | 5 | 3. The method of claim 1 , wherein: providing the mapping table comprises: selecting the mapping table from a plurality of candidate mapping tables according to a coding context, wherein the coding context is derived from a previously coded syntax element value; and providing the probability table comprises: selecting the probability table from a plurality of candidate probability tables according to the coding context. | 3. The method of claim 1 , wherein: providing the mapping table comprises: selecting the mapping table from a plurality of candidate mapping tables according to a coding context, wherein the coding context is derived from a previously coded syntax element value; and providing the probability table comprises: selecting the probability table from a plurality of candidate probability tables according to the coding context. 5. The method of claim 3 , wherein selecting the mapping table and selecting the probability table are performed only when a predetermined criterion is satisfied. | 0.542373 |
9,659,005 | 27 | 28 | 27. The system of claim 26 , wherein: the one or more text processors and the semantic database are connected via a first communication network; and the one or more query processors and the semantic database are connected via a second communication network. | 27. The system of claim 26 , wherein: the one or more text processors and the semantic database are connected via a first communication network; and the one or more query processors and the semantic database are connected via a second communication network. 28. The system of claim 27 , wherein the first communication network is same as the second communication network. | 0.529167 |
9,025,738 | 1 | 8 | 1. A method comprising: receiving a voice message intended for a recipient user, the voice message being in a first language; receiving, from the recipient user, a retrieval code to retrieve the voice message in a second language; translating, via a processor and based on the retrieval code, the voice message into the second language, to yield a translated voice message; and providing the translated voice message to the recipient user. | 1. A method comprising: receiving a voice message intended for a recipient user, the voice message being in a first language; receiving, from the recipient user, a retrieval code to retrieve the voice message in a second language; translating, via a processor and based on the retrieval code, the voice message into the second language, to yield a translated voice message; and providing the translated voice message to the recipient user. 8. The method of claim 1 , wherein the receiving of the voice message, the receiving of the retrieval code, the translating of the voice message, and the providing of the translated voice message are performed on a server. | 0.50885 |
8,271,256 | 11 | 18 | 11. A non-transitory computer readable medium comprising software instructions to optimize MOSFET device production, wherein the software instructions comprise instructions for causing a computer to perform: calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution. | 11. A non-transitory computer readable medium comprising software instructions to optimize MOSFET device production, wherein the software instructions comprise instructions for causing a computer to perform: calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution. 18. The computer readable medium of claim 11 , further comprising: defining earliest and latest arrival times; defining delays and output slews based on the key independent parameters and the theoretical extracted parameters; using a statistical characterization tool to simulate delay arcs at random process points; generating a response surface model to describe deviations in local variations; storing results in an accessible format; and identifying and correcting circuits violating statistical requirements. | 0.625547 |
7,512,627 | 5 | 6 | 5. The system of claim 4 , wherein said reporting engine is configured to facilitate reporting of at least one of course retention rates, course evaluations, faculty evaluations, enrollment, student performance, faculty response times, help desk response times, and course run rates. | 5. The system of claim 4 , wherein said reporting engine is configured to facilitate reporting of at least one of course retention rates, course evaluations, faculty evaluations, enrollment, student performance, faculty response times, help desk response times, and course run rates. 6. The system of claim 5 , wherein said benchmarking engine is configured to facilitate comparison of said internal data with said aggregate data related to at least one of student retention, student enrollment, course completion, student satisfaction, student to faculty ratios, learning outcomes, and student performance. | 0.5 |
9,245,254 | 6 | 7 | 6. The method of claim 4 , the semantic content including a name, event, or entity mentioned by a speaker. | 6. The method of claim 4 , the semantic content including a name, event, or entity mentioned by a speaker. 7. The method of claim 6 , further comprising: processing voice messages from the multiple persons to generate voice print data for each of the multiple persons, wherein each of the voice messages is a telephone voice mail message stored by a voice mail service in association with a sender telephone number; and performing reverse directory lookups using the sender telephone numbers to determine names of speakers associated with the voice messages. | 0.5 |
8,561,205 | 21 | 22 | 21. A method for distributing an electronic document comprising: maintaining a memory configured to store the electronic document; associating with a copy of the electronic document one or more rights, wherein each of said rights defines an action capable of being performed on at least a portion of the copy of the electronic document, wherein the associating step is performed by a central distribution system; and providing the copy of the electronic document in a form that allows a first client to exercise the one or more rights associated with the copy of the electronic document, wherein one of the rights associated with the copy of the electronic document includes the ability of the first client to share with a second client rights to at least a portion of a body of content of the electronic document to enable the second client to access the shared content based on rights derived from the first client through an act of said sharing even if the second client is not otherwise entitled to access the shared content, and wherein said second client receives said at least a portion of said shared body of content from said central server only after the second client's rights to receive the shared content, as derived from the first client, are exercised by the second client such that the exercise of such rights by said second client directly causes the shared content to be delivered to the second client. | 21. A method for distributing an electronic document comprising: maintaining a memory configured to store the electronic document; associating with a copy of the electronic document one or more rights, wherein each of said rights defines an action capable of being performed on at least a portion of the copy of the electronic document, wherein the associating step is performed by a central distribution system; and providing the copy of the electronic document in a form that allows a first client to exercise the one or more rights associated with the copy of the electronic document, wherein one of the rights associated with the copy of the electronic document includes the ability of the first client to share with a second client rights to at least a portion of a body of content of the electronic document to enable the second client to access the shared content based on rights derived from the first client through an act of said sharing even if the second client is not otherwise entitled to access the shared content, and wherein said second client receives said at least a portion of said shared body of content from said central server only after the second client's rights to receive the shared content, as derived from the first client, are exercised by the second client such that the exercise of such rights by said second client directly causes the shared content to be delivered to the second client. 22. The method of claim 21 wherein one of the one or more rights defines the scope of the action capable of being performed. | 0.70892 |
8,719,262 | 14 | 19 | 14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. | 14. A system comprising: a server, including a processor, to: identify documents relating to a query; generate a plurality of substrings from the query; calculate, for a particular substring of the plurality of substrings, a value relating to one or more documents, of the identified documents, that contain the particular substring; determine that the calculated value for the particular substring satisfies a particular threshold associated with identifying compounds; select, for a semantic unit, the particular substring from the plurality of substrings based on the calculated value for the particular substring satisfying the particular threshold; and obtain a refined list of documents by refining the identified documents based on the semantic unit. 19. The system of claim 14 , where the server is further to: provide information based on the refined list of documents. | 0.810726 |
8,209,333 | 1 | 4 | 1. A computer-implemented method of assessing the suitability of particular key phrases for use in providing contextually-relevant content to users, the method comprising: identifying a key phrase that appears on a page of a site; and generating a score for the key phrase based at least partly on view counts of social media content items associated with the key phrase, said social media content items being accessible to users on one or more social media sites that are separate from said site, said score representing a suitability of the key phrase for selecting contextually relevant content to present on the page, wherein generating the score comprises assessing, based at least partly on the view counts of social media content items, a rate of change in a popularity level of the key phrase; said method performed by a computer system that comprises one or more computers. | 1. A computer-implemented method of assessing the suitability of particular key phrases for use in providing contextually-relevant content to users, the method comprising: identifying a key phrase that appears on a page of a site; and generating a score for the key phrase based at least partly on view counts of social media content items associated with the key phrase, said social media content items being accessible to users on one or more social media sites that are separate from said site, said score representing a suitability of the key phrase for selecting contextually relevant content to present on the page, wherein generating the score comprises assessing, based at least partly on the view counts of social media content items, a rate of change in a popularity level of the key phrase; said method performed by a computer system that comprises one or more computers. 4. The method of claim 1 , wherein the social media content items include videos that are available for viewing on at least one social media site. | 0.746528 |
7,849,439 | 8 | 9 | 8. The system of claim 7 wherein said rendering engine receives said drawing commands and generates said sequence diagram representing said flow described by said received data. | 8. The system of claim 7 wherein said rendering engine receives said drawing commands and generates said sequence diagram representing said flow described by said received data. 9. The system of claim 8 wherein said sequence diagram is provided via a graphical user interface that allows a user to edit said received data on-screen and generate another sequence diagram on demand that reflects a change made to said received data. | 0.5 |
4,633,430 | 8 | 9 | 8. In an information processing system including keyboard means for entering document data and document manipulation commands, processor means for operating upon said documents and means for displaying said documents, means for controlling operations of said system, comprising: document memory means for storing segments of a document being operated upon, document control means, including buffer means for transferring said document data between said document memory means and said keyboard and display means, document access means for storing and providing information identifying the locations in said document memory means of segments of a said document currently being operated upon, and information identifying the locations in said buffer means of said document data to be transferred between said document memory means and said keyboard and display means, document manipulation means, including memory means for storing and providing document operations to be performed upon said document segments and said document data, supervisory control means, including system supervisory operation memory means for storing and providing supervisory operation routines for controlling supervisory operations of said system, and means responsive to operation of said keyboard means for providing operation vectors identifying document operations to be performed upon said document data and said document segments and supervisory operations to be performed by said system, said processor means being responsive to said operation vectors for reading and performing corresponding said document operation and supervisory operation routines, and responsive to said document operation routines for reading said location information from said document access means for locating said document segments and data to be operated upon in said document memory means and said buffer means. wherein, the only routines which perform operations upon said document segments residing in said document memory means are said document operation routines, said document operation routines access said document segments and data residing in said document memory means and said buffer means only through said location information residing in said document access means, and said document segments and data transferred between said document memory means and said keyboard and display means only through said buffer means, said supervisory control means further including keystroke processing means, including means for accepting and classifying keystroke inputs from said keyboard means, and state table means for storing said operation vectors, said state table means responsive to state information and to operation of said classifying means for relating said state information and said keystroke classifications to said corresponding operation vectors and providing said corresponding operation vectors to be written into an execution pointer means, and stack means for storing state information identifying state of execution of said document operation and supervisory operation routines, said processor means being responsive to execution of said routines for writing said state information identifying state of execution of said routines into said stack means and reading said state information identifying state of execution of said routines from said stack means, including supervisory stack means for storing type of routine information and said operation vector of said current document operation routine and the operation vectors of interrupted said document operation routines, and document operation stack means for storing certain of said interrupted document operation routines, and control interface means, including execution pointer means for storing said operation vectors, said processor means being responsive to said keyboard inputs and to said execution of said current routine for writing said operation vectors into said execution pointer means and reading said operation vectors from said execution pointer means, and said state table means. | 8. In an information processing system including keyboard means for entering document data and document manipulation commands, processor means for operating upon said documents and means for displaying said documents, means for controlling operations of said system, comprising: document memory means for storing segments of a document being operated upon, document control means, including buffer means for transferring said document data between said document memory means and said keyboard and display means, document access means for storing and providing information identifying the locations in said document memory means of segments of a said document currently being operated upon, and information identifying the locations in said buffer means of said document data to be transferred between said document memory means and said keyboard and display means, document manipulation means, including memory means for storing and providing document operations to be performed upon said document segments and said document data, supervisory control means, including system supervisory operation memory means for storing and providing supervisory operation routines for controlling supervisory operations of said system, and means responsive to operation of said keyboard means for providing operation vectors identifying document operations to be performed upon said document data and said document segments and supervisory operations to be performed by said system, said processor means being responsive to said operation vectors for reading and performing corresponding said document operation and supervisory operation routines, and responsive to said document operation routines for reading said location information from said document access means for locating said document segments and data to be operated upon in said document memory means and said buffer means. wherein, the only routines which perform operations upon said document segments residing in said document memory means are said document operation routines, said document operation routines access said document segments and data residing in said document memory means and said buffer means only through said location information residing in said document access means, and said document segments and data transferred between said document memory means and said keyboard and display means only through said buffer means, said supervisory control means further including keystroke processing means, including means for accepting and classifying keystroke inputs from said keyboard means, and state table means for storing said operation vectors, said state table means responsive to state information and to operation of said classifying means for relating said state information and said keystroke classifications to said corresponding operation vectors and providing said corresponding operation vectors to be written into an execution pointer means, and stack means for storing state information identifying state of execution of said document operation and supervisory operation routines, said processor means being responsive to execution of said routines for writing said state information identifying state of execution of said routines into said stack means and reading said state information identifying state of execution of said routines from said stack means, including supervisory stack means for storing type of routine information and said operation vector of said current document operation routine and the operation vectors of interrupted said document operation routines, and document operation stack means for storing certain of said interrupted document operation routines, and control interface means, including execution pointer means for storing said operation vectors, said processor means being responsive to said keyboard inputs and to said execution of said current routine for writing said operation vectors into said execution pointer means and reading said operation vectors from said execution pointer means, and said state table means. 9. The document processing means of claim 8, wherein said document operation routines are selected and assembled from a predetermined library of routines. | 0.5 |
9,268,866 | 1 | 5 | 1. A method of providing rewards based on interactions with annotations, the method being implemented by a computer system that includes one or more physical processors executing one or more computer program instructions which, when executed, perform the method, the method comprising: receiving, at the computer system, a first annotation provided by a first user during a presentation of a first content item, wherein the first annotation corresponds to a reference time at which a product or service appears in the first content item, and wherein the first annotation is provided by the first user via a user device different from the computer system; identifying, by the computer system, in the first annotation, a reference referring to the product or service; modifying, by the computer system, the first annotation to include a mechanism that enables a transaction related to the product or service, wherein the first annotation is modified to include the mechanism based on the identification of the reference; associating, by the computer system, the modified first annotation with a first user account of the first user; providing, by the computer system, based on the corresponding reference time, a presentation of the modified first annotation during one or more presentations of the first content item to other users such that the mechanism is available for use by the other users via the modified first annotation during the one or more presentations of the first content item; monitoring, by the computer system, during the one or more presentations of the first content item, use of the mechanism by the other users via the modified first annotation; and determining, by the computer system, a reward to be provided to the first user account based on the monitored use of the mechanism by the other users via the modified first annotation. | 1. A method of providing rewards based on interactions with annotations, the method being implemented by a computer system that includes one or more physical processors executing one or more computer program instructions which, when executed, perform the method, the method comprising: receiving, at the computer system, a first annotation provided by a first user during a presentation of a first content item, wherein the first annotation corresponds to a reference time at which a product or service appears in the first content item, and wherein the first annotation is provided by the first user via a user device different from the computer system; identifying, by the computer system, in the first annotation, a reference referring to the product or service; modifying, by the computer system, the first annotation to include a mechanism that enables a transaction related to the product or service, wherein the first annotation is modified to include the mechanism based on the identification of the reference; associating, by the computer system, the modified first annotation with a first user account of the first user; providing, by the computer system, based on the corresponding reference time, a presentation of the modified first annotation during one or more presentations of the first content item to other users such that the mechanism is available for use by the other users via the modified first annotation during the one or more presentations of the first content item; monitoring, by the computer system, during the one or more presentations of the first content item, use of the mechanism by the other users via the modified first annotation; and determining, by the computer system, a reward to be provided to the first user account based on the monitored use of the mechanism by the other users via the modified first annotation. 5. The method of claim 1 , wherein the reference referring to the product or service comprises a product or service type identifier associated with the product or service, and wherein modifying the first annotation comprises supplementing, based on identification of the product or service type identifier, the product or service type identifier with the mechanism in the first annotation. | 0.702599 |
6,105,021 | 1 | 7 | 1. A method for a thorough search of a distributed document database, comprising the steps of: receiving a search request including search parameters and a search starting point; adding a document found at the search starting point to a processing list; determining whether a next document in the processing list is a plain text document or a compressed document; if the next document is a compressed document, decompressing the next document to produce a plain text version of the next document; searching the plain text version of the next document according to the search parameters and for references to other documents; appending documents referenced by the next document to the processing list; repeating the determining, decompressing, searching and appending steps until inspection of the processing list is concluded; and returning a list of processed documents which meet the search criteria to a user. | 1. A method for a thorough search of a distributed document database, comprising the steps of: receiving a search request including search parameters and a search starting point; adding a document found at the search starting point to a processing list; determining whether a next document in the processing list is a plain text document or a compressed document; if the next document is a compressed document, decompressing the next document to produce a plain text version of the next document; searching the plain text version of the next document according to the search parameters and for references to other documents; appending documents referenced by the next document to the processing list; repeating the determining, decompressing, searching and appending steps until inspection of the processing list is concluded; and returning a list of processed documents which meet the search criteria to a user. 7. The method as recited in claim 1 wherein the method is performed at a web server and the list of processed documents which meet the search criteria is returned to a web client. | 0.600446 |
9,070,366 | 8 | 14 | 8. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text corresponding to a request of a user; processing the text in a first natural language understanding (“NLU”) module to generate a first interpretation of the transcription, and in a second NLU module to generate a second interpretation of the transcription, wherein first NLU module is associated with a first domain, and the second NLU module is associated with a second domain, wherein the first interpretation is associated with a first score indicative of whether the first interpretation corresponds to an action requested by the user, and wherein the second interpretation is associated with a second score indicative of whether the second interpretation corresponds to the action requested by the user; selecting the first interpretation based at least partly on the first score and the second score; and generating a response based at least partly on the first interpretation. | 8. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, receiving text corresponding to a request of a user; processing the text in a first natural language understanding (“NLU”) module to generate a first interpretation of the transcription, and in a second NLU module to generate a second interpretation of the transcription, wherein first NLU module is associated with a first domain, and the second NLU module is associated with a second domain, wherein the first interpretation is associated with a first score indicative of whether the first interpretation corresponds to an action requested by the user, and wherein the second interpretation is associated with a second score indicative of whether the second interpretation corresponds to the action requested by the user; selecting the first interpretation based at least partly on the first score and the second score; and generating a response based at least partly on the first interpretation. 14. The computer-implemented method of claim 8 , wherein processing the text in the first NLU module comprises performing named entity recognition on the text to recognize one or more named entities, and wherein the one or more named entities are associated with an actionable intent of the user in making the request. | 0.5 |
7,966,204 | 5 | 7 | 5. A system for processing an insurance claim based on different types of documents related to the insurance claim, comprising: a processor; and a memory storing computer instructions which, when executed by the processor, cause the system to perform a method for processing an insurance claim, the method comprising: receiving, by a text analyzer, at least two different types of documents corresponding to the insurance claim, and automatically processing, by the text analyzer, the text of each document according to its document type, using a specialized insurance dictionary, to extract data elements; and assigning, by a rules engine, a value to each of the data elements, the value reflecting each data element's relevance to claim subrogation potential, and evaluating, by the rules engine, the values assigned to the data elements to determine whether the insurance claim has subrogation potential. | 5. A system for processing an insurance claim based on different types of documents related to the insurance claim, comprising: a processor; and a memory storing computer instructions which, when executed by the processor, cause the system to perform a method for processing an insurance claim, the method comprising: receiving, by a text analyzer, at least two different types of documents corresponding to the insurance claim, and automatically processing, by the text analyzer, the text of each document according to its document type, using a specialized insurance dictionary, to extract data elements; and assigning, by a rules engine, a value to each of the data elements, the value reflecting each data element's relevance to claim subrogation potential, and evaluating, by the rules engine, the values assigned to the data elements to determine whether the insurance claim has subrogation potential. 7. The system of claim 5 , wherein one of the documents is a sentence textual group document, and wherein the text analyzer processes the text of the sentence textual group document according to the grammatical roles of words in the sentence textual group document. | 0.509259 |
7,752,609 | 9 | 10 | 9. The computer-implemented method of claim 6 further comprising executing one or more scripts against the nanocode model to a reference nanocode model to identify flaws in the executable software code. | 9. The computer-implemented method of claim 6 further comprising executing one or more scripts against the nanocode model to a reference nanocode model to identify flaws in the executable software code. 10. The computer-implemented method of claim 9 wherein the scripts comprise one or more of search instructions, control instructions and data flow instructions. | 0.5 |
8,027,276 | 1 | 7 | 1. A conferencing method comprising: receiving first endpoint data for a first conference type from a first endpoint; determining whether at least one second endpoint is participating in a conference with the first endpoint; determining a second conference type for transmitting the received first endpoint data to the at least one second endpoint, the determining the second conference type comprising reading a second conference type identifier from a memory, the second conference type identifier specifying the second conference type for the at least one second endpoint participating in the conference with the first endpoint; determining whether the second conference type is different than the first conference type; selecting a conversion program based on whether the second conference type is different than the first conference type, the conversion program converting the received first endpoint data to second endpoint data that is compatible with the second conference type; reading a first endpoint identifier for the first endpoint; transmitting the converted received first endpoint data to the at least one second endpoint, the transmitted data comprising the first endpoint identifier for the first endpoint; receiving second endpoint data from the at least one second endpoint; the conversion program converting the received second endpoint data to first endpoint data that is compatible with the first conference type; reading a second endpoint identifier for the at least one second endpoint; and transmitting the converted received second endpoint data to the first endpoint, the transmitted second endpoint data comprising the second endpoint identifier for the at least one second endpoint; and wherein the conversion program converting the received second endpoint data to the first endpoint data that is compatible with the first conference type comprises the conversion program utilizing a conversion parameter if the first conference type is a voice conference and the second conference type is a text messaging conference; and wherein the conversion parameter comprises predetermined voice attributes based on the second endpoint identifier of the at least one second endpoint that are independent of a voice of a user of the at least one second endpoint; and wherein the conversion program converting the received first endpoint data to the second endpoint data that is compatible with the second conference type comprises the conversion program utilizing aiding data if the second conference type is a text messaging conference and the first conference type is a voice conference; and wherein the aiding data comprises a model of stored voice data for a user of the first endpoint. | 1. A conferencing method comprising: receiving first endpoint data for a first conference type from a first endpoint; determining whether at least one second endpoint is participating in a conference with the first endpoint; determining a second conference type for transmitting the received first endpoint data to the at least one second endpoint, the determining the second conference type comprising reading a second conference type identifier from a memory, the second conference type identifier specifying the second conference type for the at least one second endpoint participating in the conference with the first endpoint; determining whether the second conference type is different than the first conference type; selecting a conversion program based on whether the second conference type is different than the first conference type, the conversion program converting the received first endpoint data to second endpoint data that is compatible with the second conference type; reading a first endpoint identifier for the first endpoint; transmitting the converted received first endpoint data to the at least one second endpoint, the transmitted data comprising the first endpoint identifier for the first endpoint; receiving second endpoint data from the at least one second endpoint; the conversion program converting the received second endpoint data to first endpoint data that is compatible with the first conference type; reading a second endpoint identifier for the at least one second endpoint; and transmitting the converted received second endpoint data to the first endpoint, the transmitted second endpoint data comprising the second endpoint identifier for the at least one second endpoint; and wherein the conversion program converting the received second endpoint data to the first endpoint data that is compatible with the first conference type comprises the conversion program utilizing a conversion parameter if the first conference type is a voice conference and the second conference type is a text messaging conference; and wherein the conversion parameter comprises predetermined voice attributes based on the second endpoint identifier of the at least one second endpoint that are independent of a voice of a user of the at least one second endpoint; and wherein the conversion program converting the received first endpoint data to the second endpoint data that is compatible with the second conference type comprises the conversion program utilizing aiding data if the second conference type is a text messaging conference and the first conference type is a voice conference; and wherein the aiding data comprises a model of stored voice data for a user of the first endpoint. 7. The method of claim 1 wherein the transmitting the converted received first endpoint data to the at least one second endpoint and the transmitting the converted received second endpoint data to the first endpoint comprise transmitting using at least one of Session Initiation Protocol (SIP), SIP for Instant Messaging and Presence Leveraging Extensions (SIMPLE), or Jabber protocol. | 0.515113 |
10,152,757 | 8 | 9 | 8. A computer-implemented data processing method of providing one or more activities to subsequent viewers of a piece of multimedia in a time-shifted manner according to an activity map, comprising: identifying, by one or more activity management servers, a plurality of segments that make up a piece of multimedia; receiving, by the one or more activity management servers, a plurality of activities from one or more users prior to a first time, each particular activity of the plurality of activities being associated with a respective particular segment of the plurality of segments; generating, by the one or more activity management servers, an activity map for the piece of multimedia based at least in part on the plurality of segments, the activity map indicating: the association between each particular activity of the plurality of activities and the respective particular segment of the plurality of segments; and one or more associations between one or more particular activities of the plurality of activities and one or more other activities of the plurality of activities; receiving, by the one or more activity management servers, from a client device, a first request to display one or more activities associated with the piece of multimedia; in response to the first request, generating a graphical display of the one or more activities associated with the piece multimedia based at least in part on the activity map, the graphical display comprising a word cloud generated based at least in part on a graphic density of one or more particular words that appear in the one or more activities; and causing the client device to display the graphical display. | 8. A computer-implemented data processing method of providing one or more activities to subsequent viewers of a piece of multimedia in a time-shifted manner according to an activity map, comprising: identifying, by one or more activity management servers, a plurality of segments that make up a piece of multimedia; receiving, by the one or more activity management servers, a plurality of activities from one or more users prior to a first time, each particular activity of the plurality of activities being associated with a respective particular segment of the plurality of segments; generating, by the one or more activity management servers, an activity map for the piece of multimedia based at least in part on the plurality of segments, the activity map indicating: the association between each particular activity of the plurality of activities and the respective particular segment of the plurality of segments; and one or more associations between one or more particular activities of the plurality of activities and one or more other activities of the plurality of activities; receiving, by the one or more activity management servers, from a client device, a first request to display one or more activities associated with the piece of multimedia; in response to the first request, generating a graphical display of the one or more activities associated with the piece multimedia based at least in part on the activity map, the graphical display comprising a word cloud generated based at least in part on a graphic density of one or more particular words that appear in the one or more activities; and causing the client device to display the graphical display. 9. The computer-implemented data processing method of claim 8 , the method further comprising: receiving, by the one or more activity management servers, one or more additional activities, each particular one of the one or more additional activities being associated with a respective particular segment of the plurality of segments; and as the system receives each particular one of the one or more additional activities, substantially continuously updating, by the one or more activity management servers, the activity map to indicate: the association between each particular one of the one or more additional activities and the respective particular segment; and one or more associations between the one or more additional activities and the plurality of activities. | 0.5 |
9,531,649 | 7 | 8 | 7. The computer-implemented method of claim 1 , wherein: querying the first domain to determine that the username in the electronic message is not a valid username for the first domain is performed without an author of the electronic message specifying that the username in the electronic message is not a valid username for the first domain, and querying the second domain to determined that the username in the electronic message is a valid username for the second domain is performed without the author of the electronic message specifying that the username in the electronic message is a valid username for the second domain. | 7. The computer-implemented method of claim 1 , wherein: querying the first domain to determine that the username in the electronic message is not a valid username for the first domain is performed without an author of the electronic message specifying that the username in the electronic message is not a valid username for the first domain, and querying the second domain to determined that the username in the electronic message is a valid username for the second domain is performed without the author of the electronic message specifying that the username in the electronic message is a valid username for the second domain. 8. The computer-implemented method of claim 7 , further comprising selecting the first domain as a domain to use in the determination that the username in the electronic message is not a valid username for the first domain, as a result of the computing system identifying that the electronic message was authored by a first user of a messaging service that logged into the messaging service using a particular user account that included a particular username and the first domain. | 0.5 |
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