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9,639,517 | 2 | 3 | 2. The method of claim 1 , further comprising: the computer providing, responsive to receiving the updated view object tree, a viewable image of the view object as modified by the specified edited content on an output device. | 2. The method of claim 1 , further comprising: the computer providing, responsive to receiving the updated view object tree, a viewable image of the view object as modified by the specified edited content on an output device. 3. The method of claim 2 further comprising: the computer, responsive to an editing operation creating a new external document on the edit screen, synchronizing a new managed external document with a new external document on the edit screen in order to create the managed external document corresponding to the external document. | 0.5 |
7,853,555 | 9 | 10 | 9. The apparatus of claim 6 wherein the circuitry to select the subset of the components comprises circuitry to select at least one of: a lexer, a transcoder, a translator, a morphological analyzer, a word list, a corrector, and an optical character recognition (OCR) device. | 9. The apparatus of claim 6 wherein the circuitry to select the subset of the components comprises circuitry to select at least one of: a lexer, a transcoder, a translator, a morphological analyzer, a word list, a corrector, and an optical character recognition (OCR) device. 10. The apparatus of claim 9 wherein circuitry to select the subset of the components comprises circuitry to select at least one of: an enterprise service management (ESM) component, a discovery services component, a messaging services component, a collaboration services component, a mediation services component, a storage services component, a security services component, an application services component, and a user assistant services component. | 0.5 |
7,958,138 | 1 | 2 | 1. A method for using a computer system, in response to a reader's request for display of electronic text, to automatically identify and provide additional reading material related to concepts referred to within said electronic text comprising, in sequence, the steps of: a) on a server system, via a network, accepting a request for electronic text from a client system; b) formulating a search request for additional reading material related to at least one concept in a text section of said electronic text, wherein said search request includes at least one term that was not provided to said server system by said client system; and c) via a network, along with said electronic text, providing instructions to said client system that when executed: i) cause said search request to be transmitted via a computer network, resulting in the search of an index, said search resulting in identification of related material; and ii) provide to said client system an indicator of said related material to be presented in the same presentation as the requested electronic text; wherein: said index contains a plurality of terms by which it may be searched; substantially all terms in said index are associated with at least one pointer to a text section; and at least one term in said index is associated with a plurality of pointers, at least two of said plurality of pointers pointing to different text sections. | 1. A method for using a computer system, in response to a reader's request for display of electronic text, to automatically identify and provide additional reading material related to concepts referred to within said electronic text comprising, in sequence, the steps of: a) on a server system, via a network, accepting a request for electronic text from a client system; b) formulating a search request for additional reading material related to at least one concept in a text section of said electronic text, wherein said search request includes at least one term that was not provided to said server system by said client system; and c) via a network, along with said electronic text, providing instructions to said client system that when executed: i) cause said search request to be transmitted via a computer network, resulting in the search of an index, said search resulting in identification of related material; and ii) provide to said client system an indicator of said related material to be presented in the same presentation as the requested electronic text; wherein: said index contains a plurality of terms by which it may be searched; substantially all terms in said index are associated with at least one pointer to a text section; and at least one term in said index is associated with a plurality of pointers, at least two of said plurality of pointers pointing to different text sections. 2. The method of claim 1 , wherein the request of step (a) is signaled by a user of the client system by selecting a link on a web page. | 0.797015 |
8,538,982 | 1 | 18 | 1. A computer-implemented method, comprising: while receiving a first text input entered in a search engine query input field by a first user, and before the first user has submitted the first text input as a search request: deriving, in a data processing system, a first dominant query from the first text input, wherein deriving the first dominant query includes: determining that the first text input is missing information needed to trigger an answer box; obtaining the needed information from user profile data for the first user, including analyzing the user profile data for the first user to determine that a particular category of answer box is relevant to the first user; and generating the first dominant query from the first text input, the needed information, and the particular category of answer box; obtaining, by the system, content for a first answer box associated with the first dominant query; and presenting the first answer box to the first user. | 1. A computer-implemented method, comprising: while receiving a first text input entered in a search engine query input field by a first user, and before the first user has submitted the first text input as a search request: deriving, in a data processing system, a first dominant query from the first text input, wherein deriving the first dominant query includes: determining that the first text input is missing information needed to trigger an answer box; obtaining the needed information from user profile data for the first user, including analyzing the user profile data for the first user to determine that a particular category of answer box is relevant to the first user; and generating the first dominant query from the first text input, the needed information, and the particular category of answer box; obtaining, by the system, content for a first answer box associated with the first dominant query; and presenting the first answer box to the first user. 18. The method of claim 1 , wherein: the first answer box is static; and obtaining content for the first answer box comprises obtaining content for the static first answer box from a data store storing content for static answer boxes. | 0.779661 |
4,839,634 | 15 | 30 | 15. A portable interactive electronic writing device, comprising: input pen means configured to be held in the hand of a user; non-mechanical, non-emissive display means comprising a plurality of display elements including display electrode means for operating electro-optic material located between the display electrode means, the display means being alternatively operable in two modes, including a first mode in which the display electrode means is activated to excite the electro-optic material therebetween for displaying textual information and a second mode in which the display electrode means is electrically coupled with the input pen means manipulated by the user proximate the display means along a path to form text characters; pen sense control means associated with the display means and responsive to electrical coupling of the display electrode means with the input pen means for producing position signals corresponding to positions of the input pen means with respect to the display means as the user manipulates the input pen means along the path; and display control means connected to the pen sense control means and display means and responsive to the position signals for energizing selected display electrode means of the display elements to display the text characters corresponding to the path followed by the input pen means; whereby text characters are hand-entered by the user directly onto the display means. | 15. A portable interactive electronic writing device, comprising: input pen means configured to be held in the hand of a user; non-mechanical, non-emissive display means comprising a plurality of display elements including display electrode means for operating electro-optic material located between the display electrode means, the display means being alternatively operable in two modes, including a first mode in which the display electrode means is activated to excite the electro-optic material therebetween for displaying textual information and a second mode in which the display electrode means is electrically coupled with the input pen means manipulated by the user proximate the display means along a path to form text characters; pen sense control means associated with the display means and responsive to electrical coupling of the display electrode means with the input pen means for producing position signals corresponding to positions of the input pen means with respect to the display means as the user manipulates the input pen means along the path; and display control means connected to the pen sense control means and display means and responsive to the position signals for energizing selected display electrode means of the display elements to display the text characters corresponding to the path followed by the input pen means; whereby text characters are hand-entered by the user directly onto the display means. 30. The device of claim 15 wherein the display electrode means includes a segmented backplane. | 0.970789 |
6,073,135 | 6 | 7 | 6. The method of claim 1 further comprising receiving the name of a particular Web page, searching the checkpoints to locate a closest checkpoint, scanning the delta encoding names from the closest checkpoint to obtain the unique identification associated with the particular Web page, and indexing the array by the unique identifications to obtain the inlist and outlist of the particular Web page. | 6. The method of claim 1 further comprising receiving the name of a particular Web page, searching the checkpoints to locate a closest checkpoint, scanning the delta encoding names from the closest checkpoint to obtain the unique identification associated with the particular Web page, and indexing the array by the unique identifications to obtain the inlist and outlist of the particular Web page. 7. The method of claim 6 further comprising storing a list of pointers, there being one pointer for each unique identification, each pointer identifying the closest checkpoint for a particular unique identification. | 0.5 |
7,743,082 | 12 | 15 | 12. One or more computer readable storage media storing computer-executable instructions, which when executed by a processor comprising: searching the selected document library to locate documents having property information that matches the search criteria; receiving a document for storing in association with a selected document library file system folder, the selected document library file system folder is associated with a selected document library from among a plurality of document libraries, each document library among the plurality of document libraries comprising a document library database, a document library file system folder, and documents included within the document library file system folder, wherein each document library of the plurality of document libraries has a corresponding set of properties that apply to the type of documents that are associated with that document library; associating the set of properties corresponding to the selected document library with the document such that the document is associated with a consistent set of properties applied to all documents stored in association with the selected document library, and such that each document in the selected document library has the consistent set of properties that make such documents specific to only the selected document library; writing property value information for at least some of the properties in the set to the document library database of the selected document library that includes an entry for the document to relate the property value information to the document; and storing the document in the selected document library file system folder of the selected document library, such that the document and all other document stored in the selected document library file system folder have consistent properties making such documents specific to the selected document library in which the documents are all stored. | 12. One or more computer readable storage media storing computer-executable instructions, which when executed by a processor comprising: searching the selected document library to locate documents having property information that matches the search criteria; receiving a document for storing in association with a selected document library file system folder, the selected document library file system folder is associated with a selected document library from among a plurality of document libraries, each document library among the plurality of document libraries comprising a document library database, a document library file system folder, and documents included within the document library file system folder, wherein each document library of the plurality of document libraries has a corresponding set of properties that apply to the type of documents that are associated with that document library; associating the set of properties corresponding to the selected document library with the document such that the document is associated with a consistent set of properties applied to all documents stored in association with the selected document library, and such that each document in the selected document library has the consistent set of properties that make such documents specific to only the selected document library; writing property value information for at least some of the properties in the set to the document library database of the selected document library that includes an entry for the document to relate the property value information to the document; and storing the document in the selected document library file system folder of the selected document library, such that the document and all other document stored in the selected document library file system folder have consistent properties making such documents specific to the selected document library in which the documents are all stored. 15. The computer-readable media of claim 12 further comprising: receiving a request to search the selected document library for documents having property information that matches search criteria; searching the selected document library to locate documents having property information that matches the search criteria; and in response to searching the selected document library, returning a result of the search. | 0.535068 |
7,580,957 | 1 | 3 | 1. A structured data storage device configured to allow viewing or updating, from an external device, of structured data file stored in a storage medium built in the structured data storage device, comprising: a storage means for storing, into the storage medium, the structured data file having structured data, and an index file having index information for use to search the structured data; a detecting means for detecting whether or not the stored structured data file has been updated by the external device; and an index information generating means for analyzing, when the detecting means detects that the stored structured data file has been updated, the updated structured data file, generate new index information relating to the structured data included in the updated structured data file, and update the stored index file using the new index information, wherein the structured data has a plurality of data units identically configured with hierarchically structured elements, each data unit comprises a reference element positioned at the top of the respective data units, and one or more search elements positioned below the reference element, the index information comprises a first index component and a second index component, the first index component links together information which identifies the reference element, information which identifies a structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies respective search elements positioned below the identified reference element, and content information of the respective search elements, the second index component links together information which identifies respective search elements, content information of the respective search elements, and information which identifies a reference element having the respective search elements, the index information generating means detects a reference element included in the structured data in the updated structured data file, analyzes the updated structured data file by detecting a search element positioned below the detected reference element, and generates the new index information comprising a new first index component and a new second index component, the index information generating means links together, as the new first index component, information which identifies the detected reference element, information which identifies the updated structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies the detected search element positioned below the identified reference element, and content information of the detected search element, and the index information generating means links together, as the new second index component, information which identifies the detected search element, content information of the respective search elements, and information which identifies the detected reference element having the respective search elements. | 1. A structured data storage device configured to allow viewing or updating, from an external device, of structured data file stored in a storage medium built in the structured data storage device, comprising: a storage means for storing, into the storage medium, the structured data file having structured data, and an index file having index information for use to search the structured data; a detecting means for detecting whether or not the stored structured data file has been updated by the external device; and an index information generating means for analyzing, when the detecting means detects that the stored structured data file has been updated, the updated structured data file, generate new index information relating to the structured data included in the updated structured data file, and update the stored index file using the new index information, wherein the structured data has a plurality of data units identically configured with hierarchically structured elements, each data unit comprises a reference element positioned at the top of the respective data units, and one or more search elements positioned below the reference element, the index information comprises a first index component and a second index component, the first index component links together information which identifies the reference element, information which identifies a structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies respective search elements positioned below the identified reference element, and content information of the respective search elements, the second index component links together information which identifies respective search elements, content information of the respective search elements, and information which identifies a reference element having the respective search elements, the index information generating means detects a reference element included in the structured data in the updated structured data file, analyzes the updated structured data file by detecting a search element positioned below the detected reference element, and generates the new index information comprising a new first index component and a new second index component, the index information generating means links together, as the new first index component, information which identifies the detected reference element, information which identifies the updated structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies the detected search element positioned below the identified reference element, and content information of the detected search element, and the index information generating means links together, as the new second index component, information which identifies the detected search element, content information of the respective search elements, and information which identifies the detected reference element having the respective search elements. 3. The structured data storage device according to claim 1 , further comprising a deletion means for deleting elements of the structured data, in accordance with externally specified elements-to-be-deleted information, wherein the deletion means: specifies a search element of a candidate for deletion and content information of the search element of the candidate for deletion, in accordance with the externally specified elements-to-be-deleted information; extracts, from the second index component, a pair of information which identifies the specified search element and content information of the specified search element; extracts, from the second index component, information which is associated with the extracted pair and identifies the reference element; extracts, from the first index component, information which identifies the structured data file, the information being associated with the information which identifies the extracted reference element, and information which identifies the position of the reference element; reads the reference element from the structured data file identified by the information which identifies the extracted structured data file and the information which identifies the position of the extracted reference element; deletes at least one of the elements positioned below the read reference element; and causes the storage means to store again the structured data file with the elements already deleted, into the storage medium, and causes the index information generating means to analyze the structured data file with the elements already deleted to update the index information. | 0.553542 |
9,535,983 | 1 | 3 | 1. A method comprising: an act of accessing a set of text samples, each having a corresponding text sample identifier; for each of at least some of the set of text samples, an act of preparing the text sample, the act of preparing the text sample comprising: an act of parsing a plurality of text components from the text sample; and for each of at least some of the parsed plurality of text components, an act of identifying the text component, the act of identifying the text component comprising: an act of determining if the text component is already correlated to a text component identifier, the text component identifier representing the content while being distinguished from the content; if the text component is already correlated to a text component identifier, assigning the text component identifier to the text component and such that when two text components are the same then the two text components will be assigned a same text component identifier; if the text component is not already correlated to a text component identifier, assigning a new text component identifier to the text component; and an act of creating a text component entry comprising a) the text sample identifier for the text sample from which the text component was parsed, and b) the assigned text component identifier; an act of creating a text sample entry group comprising a plurality of text component entries corresponding to text components parsed from the text sample, and such that the plurality of text component entries are sorted by sequence of the corresponding text component within the text sample; and an act of storing a plurality of text sample entry groups created by performance of the act of preparing the text sample for each of the at least some of the set of text samples, wherein the pluarity of text samples entries are stored in a text component entry table that includes a duplicate set of text component entries having a same text sample identifier and component identifier pairing. | 1. A method comprising: an act of accessing a set of text samples, each having a corresponding text sample identifier; for each of at least some of the set of text samples, an act of preparing the text sample, the act of preparing the text sample comprising: an act of parsing a plurality of text components from the text sample; and for each of at least some of the parsed plurality of text components, an act of identifying the text component, the act of identifying the text component comprising: an act of determining if the text component is already correlated to a text component identifier, the text component identifier representing the content while being distinguished from the content; if the text component is already correlated to a text component identifier, assigning the text component identifier to the text component and such that when two text components are the same then the two text components will be assigned a same text component identifier; if the text component is not already correlated to a text component identifier, assigning a new text component identifier to the text component; and an act of creating a text component entry comprising a) the text sample identifier for the text sample from which the text component was parsed, and b) the assigned text component identifier; an act of creating a text sample entry group comprising a plurality of text component entries corresponding to text components parsed from the text sample, and such that the plurality of text component entries are sorted by sequence of the corresponding text component within the text sample; and an act of storing a plurality of text sample entry groups created by performance of the act of preparing the text sample for each of the at least some of the set of text samples, wherein the pluarity of text samples entries are stored in a text component entry table that includes a duplicate set of text component entries having a same text sample identifier and component identifier pairing. 3. The method in accordance with claim 1 , further comprising: an act of performing a search on the plurality of text sample entry groups. | 0.64433 |
9,349,368 | 1 | 10 | 1. A computer-implemented method, comprising: determining, by one or more computer processors, that a particular computing device received a message that was transmitted to the particular computing device over a network; providing, by the one or more computer processors, the message to a first application program that is associated with the message; determining, by the one or more computer processors and based on a determination of whether a context of the particular computing device satisfies a particular criterion, whether to cause the particular computing device to present an audible notification that the particular computing device received the message; causing, by the one or more computer processors and responsive to determining that the context of the particular computing device satisfies the particular criterion, the particular computing device to present the audible notification that the particular computing device received the message; identifying, by the one or more computer processors, that the particular computing device is to wait, after the particular computing device has presented the audible notification, for an audible user response to the presentation of the audible notification; starting, by the one or more computer processors and responsive to the presentation of the audible notification and having identified that the particular computer device is to wait for the audible user response to the presentation of the audible notification, a first pre-defined time period during which the particular computing device is to listen for the audible user response to the presentation of the audible notification; recording, during the first pre-defined time period, a first audible user response to the presentation of the audible notification; determining, by the one or more processors, that the first audible user response includes one or more words that identify a command for the first application program to perform in response to the presentation of the audible notification; causing, by the one or more processors, the first application program to perform the command responsive to determining that the first audible user response includes the one or more words that identify the command for the first application program to perform; determining, by the one or more computer processors, that the particular computing device received a second message that was transmitted to the particular computing device over a network; providing, by the one or more computer processors, the second message to a second application program that is associated with the second message; causing, by the one or more computer processors, the particular computing device to present a second audible notification that the particular computing device received the second message; and starting, by the one or more computer processors and responsive to the presentation of the second audible notification, a second pre-defined time period during which the particular computing device is to listen for a second audible user response to the presentation of the second audible notification, wherein attributes of the particular computing device specify that the first application program is assigned the first pre-defined time period and that the second application program is assigned the second pre-defined time period, wherein the first pre-defined time period has a different length than a length of the second pre-defined time period. | 1. A computer-implemented method, comprising: determining, by one or more computer processors, that a particular computing device received a message that was transmitted to the particular computing device over a network; providing, by the one or more computer processors, the message to a first application program that is associated with the message; determining, by the one or more computer processors and based on a determination of whether a context of the particular computing device satisfies a particular criterion, whether to cause the particular computing device to present an audible notification that the particular computing device received the message; causing, by the one or more computer processors and responsive to determining that the context of the particular computing device satisfies the particular criterion, the particular computing device to present the audible notification that the particular computing device received the message; identifying, by the one or more computer processors, that the particular computing device is to wait, after the particular computing device has presented the audible notification, for an audible user response to the presentation of the audible notification; starting, by the one or more computer processors and responsive to the presentation of the audible notification and having identified that the particular computer device is to wait for the audible user response to the presentation of the audible notification, a first pre-defined time period during which the particular computing device is to listen for the audible user response to the presentation of the audible notification; recording, during the first pre-defined time period, a first audible user response to the presentation of the audible notification; determining, by the one or more processors, that the first audible user response includes one or more words that identify a command for the first application program to perform in response to the presentation of the audible notification; causing, by the one or more processors, the first application program to perform the command responsive to determining that the first audible user response includes the one or more words that identify the command for the first application program to perform; determining, by the one or more computer processors, that the particular computing device received a second message that was transmitted to the particular computing device over a network; providing, by the one or more computer processors, the second message to a second application program that is associated with the second message; causing, by the one or more computer processors, the particular computing device to present a second audible notification that the particular computing device received the second message; and starting, by the one or more computer processors and responsive to the presentation of the second audible notification, a second pre-defined time period during which the particular computing device is to listen for a second audible user response to the presentation of the second audible notification, wherein attributes of the particular computing device specify that the first application program is assigned the first pre-defined time period and that the second application program is assigned the second pre-defined time period, wherein the first pre-defined time period has a different length than a length of the second pre-defined time period. 10. The computer-implemented method of claim 1 , wherein: the first application program is associated with an attribute that specifies that the particular computer device is to wait, after the particular computing device has presented the audible notification, for the audible user response to the presentation of the audible notification, a third application program is associated with an attribute that specifies that the particular computer device is to not wait, after the particular computing device has presented a third audible notification to receipt of a third message, for an audible response to the presentation of the third audible notification, and the method further comprises: determining, by the one or more computer processors, that the particular computing device received the third message; providing, by the one or more computer processors, the third message to a third application program that is associated with the third message; causing, by the one or more computer processors, the particular computing device to present the third audible notification that the particular computing device received the third message; and identifying, by the one or more computer processors, that the particular computing device is to not wait for the audible user response to the presentation of the third audible notification. | 0.5 |
8,499,290 | 11 | 12 | 11. The computer program product as recited in claim 7 , further comprising computer-executable instructions that, when executed, cause the computer system to translate the semantic tree into source code in one or more different programming languages. | 11. The computer program product as recited in claim 7 , further comprising computer-executable instructions that, when executed, cause the computer system to translate the semantic tree into source code in one or more different programming languages. 12. The computer program product as recited in claim 11 , further computer-executable instructions that, when executed, cause the computer system to compile the source code from one of the different programming languages into an executable program. | 0.5 |
8,447,139 | 8 | 11 | 8. An information processing system for detecting objects in a digital image, the information processing system comprising: a memory; a processor communicatively coupled to the memory; and an object detection system communicatively coupled to the memory and the processor, the object detection system configured to perform a method comprising: receiving at least one image representing at least one frame of a video sequence comprising zero or more objects of at least one desired object type; placing a sliding window of different window sizes at different locations in the at least one image; applying, for each window size and each location, a cascaded classifier comprising a plurality of increasingly accurate layers, each layer comprising a plurality of classifiers; evaluating, at each layer in the plurality of increasingly accurate layers, an area of the at least one image within a current sliding window using one or more weak classifiers in the plurality of classifiers based on at least one of Haar features and Histograms of Oriented Gradients (HOG) features, wherein an output of each weak classifier is a weak decision as to whether the area of the at least one image within the current sliding window comprises an instance of an object of the desired object type; identifying, based on the evaluating, a location within the image of the zero or more objects associated with the desired object type; and training each weak classifier in the plurality of classifiers based on Haar features and HOG features, wherein a selection of a subsequent weak classifier during the training is based on the subsequent weak classifier that provides a strongest separation between desired object types than other available weak classifiers independent of the subsequent weak classifier being associated with one of a Haar feature and a HOG feature. | 8. An information processing system for detecting objects in a digital image, the information processing system comprising: a memory; a processor communicatively coupled to the memory; and an object detection system communicatively coupled to the memory and the processor, the object detection system configured to perform a method comprising: receiving at least one image representing at least one frame of a video sequence comprising zero or more objects of at least one desired object type; placing a sliding window of different window sizes at different locations in the at least one image; applying, for each window size and each location, a cascaded classifier comprising a plurality of increasingly accurate layers, each layer comprising a plurality of classifiers; evaluating, at each layer in the plurality of increasingly accurate layers, an area of the at least one image within a current sliding window using one or more weak classifiers in the plurality of classifiers based on at least one of Haar features and Histograms of Oriented Gradients (HOG) features, wherein an output of each weak classifier is a weak decision as to whether the area of the at least one image within the current sliding window comprises an instance of an object of the desired object type; identifying, based on the evaluating, a location within the image of the zero or more objects associated with the desired object type; and training each weak classifier in the plurality of classifiers based on Haar features and HOG features, wherein a selection of a subsequent weak classifier during the training is based on the subsequent weak classifier that provides a strongest separation between desired object types than other available weak classifiers independent of the subsequent weak classifier being associated with one of a Haar feature and a HOG feature. 11. The information processing system of claim 8 , wherein the method further comprises: visually indicating, in response to the identifying, the location of the zero or more objects. | 0.864444 |
9,891,792 | 12 | 25 | 12. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the interactive software system and obtaining user interaction activity data indicating the users' interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the interactive software system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data associated with the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the interactive software system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the interactive software system and obtaining current user interaction activity data indicating the current user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the interactive software system; correlating the biometric data associated with the current user with the current user's interaction activity data; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the current user; and presenting the customized interactive software system user experience to the current user. | 12. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the interactive software system and obtaining user interaction activity data indicating the users' interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the interactive software system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data associated with the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the interactive software system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the interactive software system and obtaining current user interaction activity data indicating the current user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the interactive software system; correlating the biometric data associated with the current user with the current user's interaction activity data; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the current user; and presenting the customized interactive software system user experience to the current user. 25. The method for building and utilizing interactive software system predictive models using biometric data of claim 12 , wherein determining that a current user of the interactive software system is a user of one of the identified user categories is based, at least in part, on personality data acquired from the user's own characterization of themselves. | 0.883789 |
9,348,854 | 9 | 19 | 9. A method of performing XBRL taxonomy migration comprising: receiving an XBRL document having XBRL tags of a first version of a first XBRL taxonomy; migrating, by a processor, the received XBRL document to a second version of the first XBRL taxonomy by replacing XBRL concepts of the first version of the first XBRL taxonomy in the received XBRL document with XBRL concepts of the second version of the first XBRL taxonomy such that the migrated XBRL document no longer uses the first version of the first XBRL taxonomy, each of the first version of the first XBRL taxonomy and the second version of the first XBRL taxonomy including a base taxonomy and optionally one or more extensions of the base taxonomy, wherein the migrating includes maintaining tags from the received XBRL document that are of a second XBRL taxonomy in the migrated XBRL document, the second XBRL taxonomy being different from the first XBRL taxonomy and tags of the second XBRL taxonomy being simultaneously included with the XBRL tags of the first XBRL taxonomy in the received XBRL document. | 9. A method of performing XBRL taxonomy migration comprising: receiving an XBRL document having XBRL tags of a first version of a first XBRL taxonomy; migrating, by a processor, the received XBRL document to a second version of the first XBRL taxonomy by replacing XBRL concepts of the first version of the first XBRL taxonomy in the received XBRL document with XBRL concepts of the second version of the first XBRL taxonomy such that the migrated XBRL document no longer uses the first version of the first XBRL taxonomy, each of the first version of the first XBRL taxonomy and the second version of the first XBRL taxonomy including a base taxonomy and optionally one or more extensions of the base taxonomy, wherein the migrating includes maintaining tags from the received XBRL document that are of a second XBRL taxonomy in the migrated XBRL document, the second XBRL taxonomy being different from the first XBRL taxonomy and tags of the second XBRL taxonomy being simultaneously included with the XBRL tags of the first XBRL taxonomy in the received XBRL document. 19. The method of claim 9 , wherein the migrating comprises a one-to-one mapping in which a deprecated XBRL concept of the first version of the first XBRL taxonomy is mapped to an equivalent XBRL concept of the second version of the first XBRL taxonomy having a different name. | 0.870075 |
9,224,112 | 9 | 10 | 9. A computer program product, comprising a non-transitory computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a computer processor of an enterprise content management (ECM) computer system implements a method, said method comprising: receiving, by said computer processor, data associated with a subscriber; registering, by said computer processor based on said data, said subscriber with said ECM computing system; connecting, by said computer processor, devices belonging to said subscriber to said ECM computing system via an Intranet, wherein said devices comprise computing devices and storage devices; connecting, by said computer processor, end user systems associated with said subscriber to said ECM computing system via said Intranet, wherein said end user systems comprise service tools, documentation systems, and storage systems; connecting, by said computer processor, database and repository systems associated with said subscriber to said ECM computing system via said Intranet, wherein said database and repository systems comprise a database, an enterprise content management metadata system, and past search results; retrieving, by said computer processor from said devices, said end user systems, and said database and repository systems, metadata associated with content retrieved by said subscriber via said devices and said end user systems; analyzing, by said computer processor, said metadata, wherein said analyzing comprises: executing a text analytics process with respect to said metadata; executing a Web analytics process with respect to said metadata; and performing an analysis of said metadata with respect to dates of creation and modification of said content, a frequency of said modification being performed with respect to time periods, and numbers of shares of said content via emails; classifying, by said computer processor based on said analyzing said metadata, said content into formal content and informal content, wherein said formal content comprises content that has been uploaded to a primary repository of said ECM computing system, and wherein said informal content comprises content that has not been uploaded to said primary repository of said ECM computing system; monitoring, by said computer processor, multiple searches for additional content initiated by said subscriber; generating, by said computer processor for said subscriber based on said monitoring and results of said classifying, multifaceted search results associated with said formal content and said informal content; and presenting, by said computer processor to said subscriber, said multifaceted search results. | 9. A computer program product, comprising a non-transitory computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a computer processor of an enterprise content management (ECM) computer system implements a method, said method comprising: receiving, by said computer processor, data associated with a subscriber; registering, by said computer processor based on said data, said subscriber with said ECM computing system; connecting, by said computer processor, devices belonging to said subscriber to said ECM computing system via an Intranet, wherein said devices comprise computing devices and storage devices; connecting, by said computer processor, end user systems associated with said subscriber to said ECM computing system via said Intranet, wherein said end user systems comprise service tools, documentation systems, and storage systems; connecting, by said computer processor, database and repository systems associated with said subscriber to said ECM computing system via said Intranet, wherein said database and repository systems comprise a database, an enterprise content management metadata system, and past search results; retrieving, by said computer processor from said devices, said end user systems, and said database and repository systems, metadata associated with content retrieved by said subscriber via said devices and said end user systems; analyzing, by said computer processor, said metadata, wherein said analyzing comprises: executing a text analytics process with respect to said metadata; executing a Web analytics process with respect to said metadata; and performing an analysis of said metadata with respect to dates of creation and modification of said content, a frequency of said modification being performed with respect to time periods, and numbers of shares of said content via emails; classifying, by said computer processor based on said analyzing said metadata, said content into formal content and informal content, wherein said formal content comprises content that has been uploaded to a primary repository of said ECM computing system, and wherein said informal content comprises content that has not been uploaded to said primary repository of said ECM computing system; monitoring, by said computer processor, multiple searches for additional content initiated by said subscriber; generating, by said computer processor for said subscriber based on said monitoring and results of said classifying, multifaceted search results associated with said formal content and said informal content; and presenting, by said computer processor to said subscriber, said multifaceted search results. 10. The computer program product of claim 9 , wherein said method further comprises: downloading, by said computer processor in accordance with said multifaceted search results, relevant formal content from said primary repository. | 0.759375 |
9,256,587 | 10 | 11 | 10. The website editor of claim 7 , wherein the website menu comprises a menu item, the menu item comprising one or more of a link to a webpage of the website, an external link, and a link for performing an operation. | 10. The website editor of claim 7 , wherein the website menu comprises a menu item, the menu item comprising one or more of a link to a webpage of the website, an external link, and a link for performing an operation. 11. The website editor of claim 10 , wherein the link to a webpage of the website comprises a link to a gallery webpage. | 0.5 |
9,633,078 | 1 | 3 | 1. A computer-implemented method comprising: receiving a request to compute identifiers for tuples of one or more recursively defined relations; and performing the following operations until no new tuples are generated for any of the one or more recursively defined relations: selecting one or more of the recursively defined relations to evaluate, performing one or more iterations of recursive evaluation for each of the selected one or more relations, computing respective keys for each tuple of any new tuples, wherein each key for each tuple is computed using each element of one or more elements of the tuple, determining, for each key computed for each new tuple, whether the key occurs in a respective cache of keys for a relation of the tuple, for each key that occurs in the cache of keys, obtaining a tuple for the key from the cache and adding the obtained tuple to a new relation; for each key that does not occur in the cache of keys, generating a new identifier for the key, adding, to a new relation for each key of each tuple of any keys that do not occur in the cache of keys for a relation, a new tuple comprising (1) elements of the tuple and (2) the new identifier for the key, and adding each key for each new tuple that does not occur in the cache of keys for the relation of the tuple to the cache of keys for the relation. | 1. A computer-implemented method comprising: receiving a request to compute identifiers for tuples of one or more recursively defined relations; and performing the following operations until no new tuples are generated for any of the one or more recursively defined relations: selecting one or more of the recursively defined relations to evaluate, performing one or more iterations of recursive evaluation for each of the selected one or more relations, computing respective keys for each tuple of any new tuples, wherein each key for each tuple is computed using each element of one or more elements of the tuple, determining, for each key computed for each new tuple, whether the key occurs in a respective cache of keys for a relation of the tuple, for each key that occurs in the cache of keys, obtaining a tuple for the key from the cache and adding the obtained tuple to a new relation; for each key that does not occur in the cache of keys, generating a new identifier for the key, adding, to a new relation for each key of each tuple of any keys that do not occur in the cache of keys for a relation, a new tuple comprising (1) elements of the tuple and (2) the new identifier for the key, and adding each key for each new tuple that does not occur in the cache of keys for the relation of the tuple to the cache of keys for the relation. 3. The method of claim 1 , wherein selecting one or more of the recursively defined relations to evaluate comprises selecting multiple recursively defined relations to evaluate. | 0.692708 |
9,986,390 | 1 | 3 | 1. A telephone, comprising: a first user interface part for the telephone that has a display screen, a microphone, a camera, and a processor, the telephone operating for making and receiving calls, the processor operating to use the camera and microphone to record a first picture and sound of a user speaking, and the processor operating to set the first picture and sound of the user speaking as being a customized message that includes at least the picture and sound as two different forms of media that are combined together; and and the processor operating to play the customized message sent as part of an outgoing communication to another user who is being contacted by the user, in place of a numerical caller ID, wherein the telephone also operates for sending text messages, the processor operating to use the camera and microphone to record a second picture and sound of the user speaking, which is different than the first picture and sound of the user speaking, and using said second picture and sound to form a second customized message for texts, and to send the second customized message to said another user who is receiving a text message from the user. | 1. A telephone, comprising: a first user interface part for the telephone that has a display screen, a microphone, a camera, and a processor, the telephone operating for making and receiving calls, the processor operating to use the camera and microphone to record a first picture and sound of a user speaking, and the processor operating to set the first picture and sound of the user speaking as being a customized message that includes at least the picture and sound as two different forms of media that are combined together; and and the processor operating to play the customized message sent as part of an outgoing communication to another user who is being contacted by the user, in place of a numerical caller ID, wherein the telephone also operates for sending text messages, the processor operating to use the camera and microphone to record a second picture and sound of the user speaking, which is different than the first picture and sound of the user speaking, and using said second picture and sound to form a second customized message for texts, and to send the second customized message to said another user who is receiving a text message from the user. 3. The telephone as in claim 1 , wherein the first user interface part also includes an editor which allows changing parts of the greeting. | 0.568323 |
8,522,130 | 2 | 4 | 2. The method of claim 1 : wherein the user input specifies content of the document at the indicated location within the document; and wherein adding the note to the note region in the note object comprises copying the specified content into the note region, the specified content associating the note region with the section of the document. | 2. The method of claim 1 : wherein the user input specifies content of the document at the indicated location within the document; and wherein adding the note to the note region in the note object comprises copying the specified content into the note region, the specified content associating the note region with the section of the document. 4. The method of claim 2 , wherein the document is associated with licensing rights relating to the copying of the specified content, the method further comprising: deauthorizing, based on the licensing rights, the copying of the specified content into the note region. | 0.516187 |
10,061,862 | 1 | 4 | 1. A computer implemented method for creating a compact tree node representation of an extensible markup language (XML) document, the method comprising: creating a compact tree node representation of an extensible markup language (XML) document by: allocating a first portion of memory of a main memory of a computer to store a first memory block for storing an in-memory instance of an XML tree index data structure for the XML document, the in-memory instance of the XML tree index data structure comprising an array of rows in which each row holds a node identifier, one or more pointers referencing to one or more children nodes, allocating a second portion of the memory of the main memory of the computer to store one or more separate data structures for storing at least a portion of the node data for the XML document, the one or more separate data structures each storing a different type of node data; traversing the XML document from a first node to a final node and through at least one intermediate node; and processing traversed nodes of the XML document, the processing comprising: in determining a traversed node is an element node, adding the element node to the first portion of the main memory and copying an element name of the element node into the one or more separate data structures for storing at least a portion of the node data; in determining the traversed node is a text node, populating a text node index into the first portion of the main memory and copying text node values into the one or more separate data structures for storing at least a portion of the node data, the text node values copied being accessible via the text node index; in determining the traversed node is an attribute node, populating an attribute node index into the first portion of the main memory and copying an attribute name and attribute value into the one or more separate data structures, the attribute value copied being accessible via the attribute node index. | 1. A computer implemented method for creating a compact tree node representation of an extensible markup language (XML) document, the method comprising: creating a compact tree node representation of an extensible markup language (XML) document by: allocating a first portion of memory of a main memory of a computer to store a first memory block for storing an in-memory instance of an XML tree index data structure for the XML document, the in-memory instance of the XML tree index data structure comprising an array of rows in which each row holds a node identifier, one or more pointers referencing to one or more children nodes, allocating a second portion of the memory of the main memory of the computer to store one or more separate data structures for storing at least a portion of the node data for the XML document, the one or more separate data structures each storing a different type of node data; traversing the XML document from a first node to a final node and through at least one intermediate node; and processing traversed nodes of the XML document, the processing comprising: in determining a traversed node is an element node, adding the element node to the first portion of the main memory and copying an element name of the element node into the one or more separate data structures for storing at least a portion of the node data; in determining the traversed node is a text node, populating a text node index into the first portion of the main memory and copying text node values into the one or more separate data structures for storing at least a portion of the node data, the text node values copied being accessible via the text node index; in determining the traversed node is an attribute node, populating an attribute node index into the first portion of the main memory and copying an attribute name and attribute value into the one or more separate data structures, the attribute value copied being accessible via the attribute node index. 4. The method of claim 1 , wherein the one or more separate data structures are hash tables. | 0.966176 |
9,237,420 | 1 | 6 | 1. A system for providing geographic information, comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device including a headset including at least a digital compass being adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, a geographical feature, and a location of interest to a user, and a Global Positioning System (GPS) enabled device connectable to the database from a remote location, wherein the GPS enabled device includes at least one of a controller, with the controller being adapted to provide requested information according to local queries and distal queries, wherein the local queries relate to local characteristics of at least one of the object, the geographic feature, and the location, wherein the distal queries relate to distant characteristics that are not in purview of the local characteristics, wherein, in response to at least one query of the local and distal queries, the controller is further adapted to select and order query results based on two-dimensional (2D) or three-dimensional (3D) query windows and weigh the query results based on predetermined relationships to the 2D or 3D query windows, and a position sensor to determine a location of the mobile device and retrieve, with respect to the object, geographic feature, or location of interest to the user, geographic information from the database. | 1. A system for providing geographic information, comprising: a database containing geographic information, the database accessible via a network connection; and a mobile device including a headset including at least a digital compass being adapted to orient the mobile device pointing in a direction to intersect a particular one of an object, a geographical feature, and a location of interest to a user, and a Global Positioning System (GPS) enabled device connectable to the database from a remote location, wherein the GPS enabled device includes at least one of a controller, with the controller being adapted to provide requested information according to local queries and distal queries, wherein the local queries relate to local characteristics of at least one of the object, the geographic feature, and the location, wherein the distal queries relate to distant characteristics that are not in purview of the local characteristics, wherein, in response to at least one query of the local and distal queries, the controller is further adapted to select and order query results based on two-dimensional (2D) or three-dimensional (3D) query windows and weigh the query results based on predetermined relationships to the 2D or 3D query windows, and a position sensor to determine a location of the mobile device and retrieve, with respect to the object, geographic feature, or location of interest to the user, geographic information from the database. 6. The system of claim 1 , wherein the controller is further adapted to retrieve a portion of the geographic information from the database based on a combination of the first location of the mobile device, the pointing direction of the mobile device, the one query including a thematic query, wherein the geographic information relates to the particular one of the object, the geographical feature, and the location. | 0.5 |
9,466,286 | 6 | 7 | 6. A non-transitory computer-readable storage medium storing instructions that when executed by a processor cause the processor to: receive a first audio signal including a representation of a first utterance; determine a first similarity score for the first utterance, wherein the first similarity score indicates a similarity between the representation of the first utterance and a representation of a defined word or phrase; determine that the first similarity score does not satisfy a first similarity acceptance criterion and does satisfy a second similarity acceptance criterion; modify the first similarity acceptance criterion for a period of time; receive a second audio signal including a representation of a second utterance within the period of time; determine a second similarity score for the second utterance, wherein the second similarity score indicates a similarity between the representation of the second utterance and the representation of the defined word or phrase; and change a state of an electronic device based at least in part on a determination that the second similarity score satisfies the modified first similarity acceptance criterion. | 6. A non-transitory computer-readable storage medium storing instructions that when executed by a processor cause the processor to: receive a first audio signal including a representation of a first utterance; determine a first similarity score for the first utterance, wherein the first similarity score indicates a similarity between the representation of the first utterance and a representation of a defined word or phrase; determine that the first similarity score does not satisfy a first similarity acceptance criterion and does satisfy a second similarity acceptance criterion; modify the first similarity acceptance criterion for a period of time; receive a second audio signal including a representation of a second utterance within the period of time; determine a second similarity score for the second utterance, wherein the second similarity score indicates a similarity between the representation of the second utterance and the representation of the defined word or phrase; and change a state of an electronic device based at least in part on a determination that the second similarity score satisfies the modified first similarity acceptance criterion. 7. The non-transitory computer-readable storage medium of claim 6 , wherein modifying the first similarity acceptance criterion includes lowering a similarity threshold associated with the first similarity acceptance criterion. | 0.723171 |
9,904,673 | 8 | 13 | 8. A system, comprising: one or more processors; a memory operatively coupled to said one or more processors; program instructions stored in said memory, said program instructions being executable by said one or more processors to perform operations for assisting the authoring of electronic messages, said operations comprising: invoking machine-implemented electronic messaging logic, said electronic messaging logic including user-interface object logic operable to display a user-interface object and invoke machine-implemented conversation advisor logic in response to user activation of said user-interface logic; initiating the creation of an electronic message using said electronic messaging logic, said electronic message being stored in digital form in a computer memory; invoking said conversation advisor logic in response to activation of said user-interface logic by an author of said electronic message; said conversation advisor logic accessing said electronic message in said computer memory; said conversation advisor logic inspecting one or more fields of said electronic message to identify intended recipients of said electronic message; said conversation advisor logic gathering and analyzing historical data relating to a conversation history in one or more previous electronic messages that links said author of said electronic message to said intended recipients, said gathering and analyzing of historical data including extracting and storing message content from said one or more previous electronic messages that is indicative of historical semantic styles and guidelines have been used in the past by said author to converse with said intended recipients via one or more electronic message applications; said conversation advisor logic sorting, tagging and storing said message content in a computer database as a sorted/tagged dataset that represents said historical data, said historical data being arranged in individual database entries that are each specific to a particular one of said intended recipients or to said intended recipients as a group; said conversation advisor logic being operable to populate some or all of said sorted/tagged dataset with data entries containing said historical data in advance of said electronic message being created by periodically searching for new electronic messages created by said electronic messaging logic and extracting said message content therefrom; said conversation advisor logic being operable to supplement said sorted/tagged dataset with one or more additional database entries during creation of said electronic message to account for any of said intended recipients who are not represented by existing database entries in said sorted/tagged dataset; said conversation advisor logic performing semantic analysis on said electronic message to extract words and phrases representing recipient fitness information that is indicative of whether said electronic message is appropriate for said intended recipients by virtue of being inconsistent with said historical data; said conversation advisor logic generating a fitness result for said electronic message by comparing said recipient fitness information to said historical data and identifying inconsistencies between said words and phrases represented by said recipient fitness information and said historical semantic styles and guidelines represented by said historical data; and said conversation advisor logic outputting said fitness result for viewing on an electronic display device associated with said author of said electronic message. | 8. A system, comprising: one or more processors; a memory operatively coupled to said one or more processors; program instructions stored in said memory, said program instructions being executable by said one or more processors to perform operations for assisting the authoring of electronic messages, said operations comprising: invoking machine-implemented electronic messaging logic, said electronic messaging logic including user-interface object logic operable to display a user-interface object and invoke machine-implemented conversation advisor logic in response to user activation of said user-interface logic; initiating the creation of an electronic message using said electronic messaging logic, said electronic message being stored in digital form in a computer memory; invoking said conversation advisor logic in response to activation of said user-interface logic by an author of said electronic message; said conversation advisor logic accessing said electronic message in said computer memory; said conversation advisor logic inspecting one or more fields of said electronic message to identify intended recipients of said electronic message; said conversation advisor logic gathering and analyzing historical data relating to a conversation history in one or more previous electronic messages that links said author of said electronic message to said intended recipients, said gathering and analyzing of historical data including extracting and storing message content from said one or more previous electronic messages that is indicative of historical semantic styles and guidelines have been used in the past by said author to converse with said intended recipients via one or more electronic message applications; said conversation advisor logic sorting, tagging and storing said message content in a computer database as a sorted/tagged dataset that represents said historical data, said historical data being arranged in individual database entries that are each specific to a particular one of said intended recipients or to said intended recipients as a group; said conversation advisor logic being operable to populate some or all of said sorted/tagged dataset with data entries containing said historical data in advance of said electronic message being created by periodically searching for new electronic messages created by said electronic messaging logic and extracting said message content therefrom; said conversation advisor logic being operable to supplement said sorted/tagged dataset with one or more additional database entries during creation of said electronic message to account for any of said intended recipients who are not represented by existing database entries in said sorted/tagged dataset; said conversation advisor logic performing semantic analysis on said electronic message to extract words and phrases representing recipient fitness information that is indicative of whether said electronic message is appropriate for said intended recipients by virtue of being inconsistent with said historical data; said conversation advisor logic generating a fitness result for said electronic message by comparing said recipient fitness information to said historical data and identifying inconsistencies between said words and phrases represented by said recipient fitness information and said historical semantic styles and guidelines represented by said historical data; and said conversation advisor logic outputting said fitness result for viewing on an electronic display device associated with said author of said electronic message. 13. The system of claim 8 , wherein said fitness result output comprises advice to said author of said electronic message concerning instances wherein said recipient fitness information is inconsistent with said intended recipients. | 0.741648 |
8,903,718 | 1 | 4 | 1. A lossless method of storing characters, words and phrases including the words, in real-time in a data structure for providing real-time predictive output of characters, words and/or phrases in response to user input text data, the method comprising: receiving user input text data comprising at least one of characters, words and phrases, one entity at a time in sequence; storing a plurality of phrases in a memory, one entity at a time in sequence, each in a phrase data structure, each phrase in said phrase data structure having a unique phrase identifier identifying an instance of a phrase and comprising a sequence of words of the phrase, wherein some of said phrase data structures further comprise subphrase identifier data, said subphrase identifier data comprising a phrase identifier identifying a portion of a phrase of a phrase data structure which corresponds to some or all of another phrase stored in a said phase data structure one or more records, each phrase comprising a record for each neighbouring pair of words in said phrase, each record defining data for neighbouring words in said phrase, each record comprising: said phrase identifier, a first neighbouring word in said phrase, a subsequent neighbouring word in said phrase and data indicating a relationship between said first and subsequent neighbouring words in said record; identifying, via a processor, a previous use of a subphrase in said user input text data, a said previous use of said subphrase corresponding to some or all of a phrase stored in said phrase data structure, and retrieving said phrase identifier for said previous use of said subphrase in response to said identification; and storing data for a subsequently input phrase in the memory, said phrase including said subphrase from said user input text data including said subphrase in said data structure as a combination of one or more said records and a subphrase record, said subphrase record comprising said phrase identifier identifying for said phrase containing said subphrase, a start word of said subphrase, an end word of said subphrase, a remainder of said subsequently input phrase after removal of said subphrase, and data indicating a relationship between said reminder of said subsequently input phrase and said subphrase start and end words of said subphrase, and subphrase identifier data, said subphrase identifier data comprising said phrase identifier identifying said phrase containing said previous use of said subphrase. | 1. A lossless method of storing characters, words and phrases including the words, in real-time in a data structure for providing real-time predictive output of characters, words and/or phrases in response to user input text data, the method comprising: receiving user input text data comprising at least one of characters, words and phrases, one entity at a time in sequence; storing a plurality of phrases in a memory, one entity at a time in sequence, each in a phrase data structure, each phrase in said phrase data structure having a unique phrase identifier identifying an instance of a phrase and comprising a sequence of words of the phrase, wherein some of said phrase data structures further comprise subphrase identifier data, said subphrase identifier data comprising a phrase identifier identifying a portion of a phrase of a phrase data structure which corresponds to some or all of another phrase stored in a said phase data structure one or more records, each phrase comprising a record for each neighbouring pair of words in said phrase, each record defining data for neighbouring words in said phrase, each record comprising: said phrase identifier, a first neighbouring word in said phrase, a subsequent neighbouring word in said phrase and data indicating a relationship between said first and subsequent neighbouring words in said record; identifying, via a processor, a previous use of a subphrase in said user input text data, a said previous use of said subphrase corresponding to some or all of a phrase stored in said phrase data structure, and retrieving said phrase identifier for said previous use of said subphrase in response to said identification; and storing data for a subsequently input phrase in the memory, said phrase including said subphrase from said user input text data including said subphrase in said data structure as a combination of one or more said records and a subphrase record, said subphrase record comprising said phrase identifier identifying for said phrase containing said subphrase, a start word of said subphrase, an end word of said subphrase, a remainder of said subsequently input phrase after removal of said subphrase, and data indicating a relationship between said reminder of said subsequently input phrase and said subphrase start and end words of said subphrase, and subphrase identifier data, said subphrase identifier data comprising said phrase identifier identifying said phrase containing said previous use of said subphrase. 4. A method according to claim 1 , wherein said identifying of said previous use of said subphrase comprises identifying greater than a threshold count of instances of said previous use of said subphrase. | 0.627737 |
7,908,280 | 1 | 3 | 1. A method comprising: receiving search criteria from a user, said search criteria including a free text entry query and a domain identifier identifying a domain; determining to request a search of a first corpus of documents to identify a first set of documents; receiving a first result set for the first corpus of documents, the first result set identifying the first set of documents in order of relevance; determining to request a search of a second corpus of documents to identify a second set of documents; receiving a second result set for the second corpus of documents, the second result set identifying the second set of documents in order of relevance; determining to merge sort the first and second result sets to produce a new result set that is ordered in relevance; and wherein determining to merge sort is based on a relevancy of the search criteria; and wherein the determined scores for each of the identified documents include a document-to-location relevance score, a document-to-text relevance score, and an abstract quality score; and combining the document-to-location relevance scores, the document-to-text, and the abstract quality score to generate a combined relevance score for the identified document. | 1. A method comprising: receiving search criteria from a user, said search criteria including a free text entry query and a domain identifier identifying a domain; determining to request a search of a first corpus of documents to identify a first set of documents; receiving a first result set for the first corpus of documents, the first result set identifying the first set of documents in order of relevance; determining to request a search of a second corpus of documents to identify a second set of documents; receiving a second result set for the second corpus of documents, the second result set identifying the second set of documents in order of relevance; determining to merge sort the first and second result sets to produce a new result set that is ordered in relevance; and wherein determining to merge sort is based on a relevancy of the search criteria; and wherein the determined scores for each of the identified documents include a document-to-location relevance score, a document-to-text relevance score, and an abstract quality score; and combining the document-to-location relevance scores, the document-to-text, and the abstract quality score to generate a combined relevance score for the identified document. 3. A method of claim 1 , further comprising determining to accept a designation by the user of a designated category, wherein each of the documents corresponding to the plurality of document identifiers further includes information that falls within the designated category. | 0.668281 |
7,885,987 | 1 | 16 | 1. A method for managing a plurality of attributes in association with a plurality of electronic documents and a plurality of attribute types, implemented by a computer system, said method comprising at least one of sequential, non-sequential and sequence-independent steps in the computer system of: (A) providing, in the computer system, a first data storage having a group of a plurality of documents including at least one document; (B) accepting, from an input device, a user's selection of a plurality of attributes to be associated with a single pre-determined attribute type for the at least one document, the attribute type having parent and child attribute types, the selected attributes being predetermined and having different parent attributes, attribute types being predetermined and ordered in a predetermined tree-structure hierarchy; and (C) responsive to the selection of the attributes, automatically tagging, in the first data storage, the documents in the group including the at least one document, with the selected attributes, and with all attributes of all ancestors but not descendants or siblings according to the hierarchy of the selected attributes; and storing, in a second data storage, respective references in association with the selected attributes and the ancestor attributes, for later retrieval of individual documents in the group by searching the ancestor attributes instead of the selected attributes, the respective references uniquely indicating respective individual documents in the first data storage, wherein the at least one document is a data record including a plurality of fields, wherein the attribute and the attribute type are different from the fields in the document and contents of the fields. | 1. A method for managing a plurality of attributes in association with a plurality of electronic documents and a plurality of attribute types, implemented by a computer system, said method comprising at least one of sequential, non-sequential and sequence-independent steps in the computer system of: (A) providing, in the computer system, a first data storage having a group of a plurality of documents including at least one document; (B) accepting, from an input device, a user's selection of a plurality of attributes to be associated with a single pre-determined attribute type for the at least one document, the attribute type having parent and child attribute types, the selected attributes being predetermined and having different parent attributes, attribute types being predetermined and ordered in a predetermined tree-structure hierarchy; and (C) responsive to the selection of the attributes, automatically tagging, in the first data storage, the documents in the group including the at least one document, with the selected attributes, and with all attributes of all ancestors but not descendants or siblings according to the hierarchy of the selected attributes; and storing, in a second data storage, respective references in association with the selected attributes and the ancestor attributes, for later retrieval of individual documents in the group by searching the ancestor attributes instead of the selected attributes, the respective references uniquely indicating respective individual documents in the first data storage, wherein the at least one document is a data record including a plurality of fields, wherein the attribute and the attribute type are different from the fields in the document and contents of the fields. 16. The method of claim 1 , further comprising the step of exporting the tree structure hierarchy including the attributes and the attribute types. | 0.786957 |
7,672,845 | 1 | 7 | 1. A method for dynamically detecting topics during one of a speech and a call center conversation, comprising: predefining one or more keywords; associating information with the one or more keywords; detecting at least one of the one or more keywords during the speech or the call center conversation; after the predefining, the associating and detecting, checking whether one or more rules are associated with the one or more detected keywords; if so, processing the one or more rules; and further comprising one of: during the speech, utilizing an intelligent teleprompter and displaying the detected keywords and the information associated with the keywords and dynamically altering one or more panes of information of the intelligent teleprompter based upon the detected one or more keywords; and during the call center conversation, displaying the detected keywords and the information associated with the keywords uttered by a caller to a call center agent and displaying an indication that a topic area has been covered by removing or graying out a displayed word. | 1. A method for dynamically detecting topics during one of a speech and a call center conversation, comprising: predefining one or more keywords; associating information with the one or more keywords; detecting at least one of the one or more keywords during the speech or the call center conversation; after the predefining, the associating and detecting, checking whether one or more rules are associated with the one or more detected keywords; if so, processing the one or more rules; and further comprising one of: during the speech, utilizing an intelligent teleprompter and displaying the detected keywords and the information associated with the keywords and dynamically altering one or more panes of information of the intelligent teleprompter based upon the detected one or more keywords; and during the call center conversation, displaying the detected keywords and the information associated with the keywords uttered by a caller to a call center agent and displaying an indication that a topic area has been covered by removing or graying out a displayed word. 7. The method of claim 1 , wherein the one or more keywords comprise one or more phrases and the detecting detects the one or more phrases. | 0.742593 |
8,267,979 | 1 | 8 | 1. A dynamic spine stabilization device comprising: a bone anchor having a housing and a longitudinal axis; a cavity in the housing coaxial with the longitudinal axis; a post received in the cavity; the post having a retainer at a distal end and a mount at a proximal end; the retainer being secured in a pocket of the cavity of the housing such that the post may be deflected within the housing; a spring positioned in the cavity of the housing between the post and the housing such that deflection of the post causes compression of the spring in a direction parallel to the longitudinal axis; and wherein the spring applies a force upon the post pushing the post towards a position in which the post is coaxial with the longitudinal axis. | 1. A dynamic spine stabilization device comprising: a bone anchor having a housing and a longitudinal axis; a cavity in the housing coaxial with the longitudinal axis; a post received in the cavity; the post having a retainer at a distal end and a mount at a proximal end; the retainer being secured in a pocket of the cavity of the housing such that the post may be deflected within the housing; a spring positioned in the cavity of the housing between the post and the housing such that deflection of the post causes compression of the spring in a direction parallel to the longitudinal axis; and wherein the spring applies a force upon the post pushing the post towards a position in which the post is coaxial with the longitudinal axis. 8. The device of claim 1 , wherein said spring has an isotropic deflection profile. | 0.89878 |
9,959,341 | 15 | 18 | 15. At least one computer-readable medium having encoded thereon instructions which, when executed by at least one processor, cause the at least one processor to perform a method comprising acts of: processing an input text to identify a plurality of semantic patterns that match the input text, wherein, for at least one semantic pattern of the plurality of semantic patterns: the at least one semantic pattern comprises a valency frame having a plurality of valency frame components; the plurality of valency frame components correspond, respectively, to a plurality of semantic entities identified from the at least one input text; and the plurality of semantic entities occur in a common context within the at least one input text; and using statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns, wherein, for the at least one semantic pattern, the statistical information comprises at least one measure of mutual information derived from the training data. | 15. At least one computer-readable medium having encoded thereon instructions which, when executed by at least one processor, cause the at least one processor to perform a method comprising acts of: processing an input text to identify a plurality of semantic patterns that match the input text, wherein, for at least one semantic pattern of the plurality of semantic patterns: the at least one semantic pattern comprises a valency frame having a plurality of valency frame components; the plurality of valency frame components correspond, respectively, to a plurality of semantic entities identified from the at least one input text; and the plurality of semantic entities occur in a common context within the at least one input text; and using statistical information derived from training data to associate a respective weight with each semantic pattern of the plurality of semantic patterns, wherein, for the at least one semantic pattern, the statistical information comprises at least one measure of mutual information derived from the training data. 18. The at least one computer-readable medium of claim 15 , wherein: the common context in which the plurality of semantic entities occur corresponds to a valency structure controlled by a controlling valency frame component of the valency frame. | 0.640351 |
8,666,967 | 10 | 12 | 10. A system for managing an applications and data space, the system comprising: one or more processors; and memory to store instructions executable by the one or more processors, the memory to store layers comprising: a strategy layer to: decide that a received query statement pertains to a non-standard query after determining that the query statement does not correlate to a standard query that represents a baseline level of query information and is scheduled for execution, identify, from a plurality of servers, one or more servers executing an application associated with the received query statement, identify event tracing modules associated with the received query statement, group the event tracing modules to generate one or more module groups, and formulate one or more custom queries for individual module groups of the one or more module groups based on the query statement for the non-standard query; and a query scheduler layer to schedule issuance of the one or more custom queries to one or more query response modules associated with the applications and data space that comprises the plurality of servers. | 10. A system for managing an applications and data space, the system comprising: one or more processors; and memory to store instructions executable by the one or more processors, the memory to store layers comprising: a strategy layer to: decide that a received query statement pertains to a non-standard query after determining that the query statement does not correlate to a standard query that represents a baseline level of query information and is scheduled for execution, identify, from a plurality of servers, one or more servers executing an application associated with the received query statement, identify event tracing modules associated with the received query statement, group the event tracing modules to generate one or more module groups, and formulate one or more custom queries for individual module groups of the one or more module groups based on the query statement for the non-standard query; and a query scheduler layer to schedule issuance of the one or more custom queries to one or more query response modules associated with the applications and data space that comprises the plurality of servers. 12. The system of claim 10 , wherein the one or more query response modules comprises an operating system level event tracing module. | 0.69213 |
9,741,058 | 1 | 3 | 1. An apparatus for programmatically analyzing a consumer review, the apparatus comprising: a processor configured to programmatically access, via a networked device, one or more consumer reviews for a commercial entity or a commercial object; a consumer review processing engine programmed to programmatically identify an attribute descriptor in the one or more consumer reviews, and programmatically generate a sentiment score associated with the one or more consumer reviews, wherein programmatic generation of the sentiment score comprises: using a natural language processing engine to programmatically parse the consumer review into a set of sentences; using the natural language processing engine to programmatically parse each sentence in the set of sentences into a set of words; for each word in the set of words in each sentence, programmatically generating a word sentiment score; for each sentence in the set of sentences, programmatically generating a sentence sentiment score, the sentence sentiment score generated based on word sentiment scores associated with words in the sentence, wherein programmatically generating the sentence sentiment scores includes applying a machine learning algorithm to determine a relationship between the sentence sentiment score and the word sentiment scores associated with the words in the sentence; and programmatically generating the sentiment score by combining sentence sentiment scores associated with the set of sentences in the consumer review; and a non-transitory computer-readable storage device configured to store the attribute descriptor and the sentiment score in association with the commercial entity or the commercial object. | 1. An apparatus for programmatically analyzing a consumer review, the apparatus comprising: a processor configured to programmatically access, via a networked device, one or more consumer reviews for a commercial entity or a commercial object; a consumer review processing engine programmed to programmatically identify an attribute descriptor in the one or more consumer reviews, and programmatically generate a sentiment score associated with the one or more consumer reviews, wherein programmatic generation of the sentiment score comprises: using a natural language processing engine to programmatically parse the consumer review into a set of sentences; using the natural language processing engine to programmatically parse each sentence in the set of sentences into a set of words; for each word in the set of words in each sentence, programmatically generating a word sentiment score; for each sentence in the set of sentences, programmatically generating a sentence sentiment score, the sentence sentiment score generated based on word sentiment scores associated with words in the sentence, wherein programmatically generating the sentence sentiment scores includes applying a machine learning algorithm to determine a relationship between the sentence sentiment score and the word sentiment scores associated with the words in the sentence; and programmatically generating the sentiment score by combining sentence sentiment scores associated with the set of sentences in the consumer review; and a non-transitory computer-readable storage device configured to store the attribute descriptor and the sentiment score in association with the commercial entity or the commercial object. 3. The apparatus of claim 1 , wherein the sentiment score is associated with the attribute descriptor. | 0.936725 |
8,412,512 | 8 | 10 | 8. A computer program product comprising a non-transitory computer readable medium storing a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: receiving social feed data and a request from a first user for a translation, the social feed data configured to cause a client to display a first social feed in a first language; determining a social context for the translation, the social context including which relationships are associated with the social feed data using a social graph, wherein the social graph comprises relationships between the first user and at least one second user; receiving a user input from the first user specifying a particular relationship for which the social feed data should be translated; determining a relationship between the first user and the second user based at least in part on the social context for the translation and whether the relationship matches the particular relationship specified by the user input; determining a first portion of the first social feed for translation based at least in part on whether the relationship between the first user and the second user matches the particular relationship, the first portion including one or more portions of the social feed data associated with the second user; translating the social feed data that is associated with the first portion of the first social feed so that the translated social feed data causes the client to display the first portion translated into one or more second languages based at least in part on the request and the social context; and transmitting the translated social feed data to the client for the first user to view. | 8. A computer program product comprising a non-transitory computer readable medium storing a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: receiving social feed data and a request from a first user for a translation, the social feed data configured to cause a client to display a first social feed in a first language; determining a social context for the translation, the social context including which relationships are associated with the social feed data using a social graph, wherein the social graph comprises relationships between the first user and at least one second user; receiving a user input from the first user specifying a particular relationship for which the social feed data should be translated; determining a relationship between the first user and the second user based at least in part on the social context for the translation and whether the relationship matches the particular relationship specified by the user input; determining a first portion of the first social feed for translation based at least in part on whether the relationship between the first user and the second user matches the particular relationship, the first portion including one or more portions of the social feed data associated with the second user; translating the social feed data that is associated with the first portion of the first social feed so that the translated social feed data causes the client to display the first portion translated into one or more second languages based at least in part on the request and the social context; and transmitting the translated social feed data to the client for the first user to view. 10. The computer program product of claim 8 , wherein the request is a subset command that includes a first indication that only the first portion of the first social feed should be translated and a second indication of what language the first social feed should be translated into. | 0.607242 |
6,105,044 | 32 | 37 | 32. The data processing system of claim 31, wherein the received portion includes a starting point element, the starting point element having been selected according to the indicated starting point; and wherein the data processing component includes: means for providing a plurality of property specifications for type names utilized for elements in the digital document; means for receiving an identity of any ancestor elements of the starting point element; and means for applying a property specification corresponding to the type name of ancestor elements identified for each selected element to the text content of each selected element to produce the digital form. | 32. The data processing system of claim 31, wherein the received portion includes a starting point element, the starting point element having been selected according to the indicated starting point; and wherein the data processing component includes: means for providing a plurality of property specifications for type names utilized for elements in the digital document; means for receiving an identity of any ancestor elements of the starting point element; and means for applying a property specification corresponding to the type name of ancestor elements identified for each selected element to the text content of each selected element to produce the digital form. 37. The data processing system of claim 32, further comprising: a second data access component that provides access to a web that stores an annotation to an element in the digital document, said web including, for each annotation, the unique element identifier of the annotated element and an indication of the annotation; and wherein the means for applying property specifications to the text content of an element includes means for searching the web for the unique element identifier of the element and means for generating an indication that the element has an annotation if the element identifier for the element is found in the web. | 0.5 |
9,484,012 | 1 | 6 | 1. A speech synthesis dictionary generation apparatus for generating a speech synthesis dictionary containing a model of an object speaker based on speech data of the object speaker, the apparatus comprising processing circuitry coupled to a memory, the processing circuitry being configured to: analyze the speech data and generate a speech database containing data representing characteristics of utterance by the object speaker; generate the model of the object speaker by performing speaker adaptation of converting a predetermined base model to be closer to characteristics of the object speaker based on the speech database; accept designation of a target speaker level that is a speaker level to be targeted, the speaker level representing at least one of a speaker's utterance skill and a speaker's native level in a language of the speech synthesis dictionary; and determine a value of a parameter related to fidelity of reproduction of speaker properties in the speaker adaptation, in accordance with a relationship between the designated target speaker level and an object speaker level that is the speaker level of the object speaker, wherein the determining determines the value of the parameter so that the fidelity is lower when the designated target speaker level is higher than the object speaker level, compared to when the designated target speaker level is not higher than the object speaker level, and the generating of the model of the object speaker performs the speaker adaptation in accordance with the value of the parameter determined at the determining. | 1. A speech synthesis dictionary generation apparatus for generating a speech synthesis dictionary containing a model of an object speaker based on speech data of the object speaker, the apparatus comprising processing circuitry coupled to a memory, the processing circuitry being configured to: analyze the speech data and generate a speech database containing data representing characteristics of utterance by the object speaker; generate the model of the object speaker by performing speaker adaptation of converting a predetermined base model to be closer to characteristics of the object speaker based on the speech database; accept designation of a target speaker level that is a speaker level to be targeted, the speaker level representing at least one of a speaker's utterance skill and a speaker's native level in a language of the speech synthesis dictionary; and determine a value of a parameter related to fidelity of reproduction of speaker properties in the speaker adaptation, in accordance with a relationship between the designated target speaker level and an object speaker level that is the speaker level of the object speaker, wherein the determining determines the value of the parameter so that the fidelity is lower when the designated target speaker level is higher than the object speaker level, compared to when the designated target speaker level is not higher than the object speaker level, and the generating of the model of the object speaker performs the speaker adaptation in accordance with the value of the parameter determined at the determining. 6. The apparatus according to claim 1 , wherein the parameter is a parameter that defines the number of conversion matrices used for conversion of the base model in the speaker adaptation such that as the number of conversion matrices is smaller, the fidelity becomes lower. | 0.819022 |
8,806,401 | 14 | 17 | 14. A system for reasonable functional verification of a design of an integrated circuit (IC), the system comprising: a processing unit; a storage coupled to the processing unit; and, a memory coupled to the processing unit, the memory containing instructions that when executed by the processing unit: retrieve from storage a description of the design of at least a portion of the IC; bring the at least a portion of the IC in the received description to a state close to a suspected point of failure respective of a setup for failure (SFF) property; execute a set of instructions by functional verification of the at least a portion of the design of the IC from the suspected point of failure respective of at least a trigger for failure (TFF) property; and, providing a report respective of a result of execution of the functional verification. | 14. A system for reasonable functional verification of a design of an integrated circuit (IC), the system comprising: a processing unit; a storage coupled to the processing unit; and, a memory coupled to the processing unit, the memory containing instructions that when executed by the processing unit: retrieve from storage a description of the design of at least a portion of the IC; bring the at least a portion of the IC in the received description to a state close to a suspected point of failure respective of a setup for failure (SFF) property; execute a set of instructions by functional verification of the at least a portion of the design of the IC from the suspected point of failure respective of at least a trigger for failure (TFF) property; and, providing a report respective of a result of execution of the functional verification. 17. The system of claim 14 , wherein the retrieve from storage a description of at least a portion of the design of the IC further comprises a selection of the at least a portion of the design of the IC. | 0.699704 |
8,498,515 | 24 | 25 | 24. An apparatus for reproducing text subtitle streams, the apparatus comprising: a decoder configured to decode the at least one text subtitle stream received from an external source, each text subtitle stream including text data to be displayed within a region of a display screen, first information specifying a global style of the region, and second information specifying a local style for a portion of the text data; and a controller configured to read a playlist including at least one playitem and first and second subplayitems, the playitem specifying a time based playing interval from an in-time until an out-time associated with at least one audio/video stream, the first subplayitem specifying a time based playing interval from an in-time until an out-time associated with the at least one text subtitle stream, the first subplayitem for a reproducing of the text subtitle stream being synchronized with the playitem, the second subplayitem for a reproduction of browsable slideshow being not synchronized with the playitem and to control the decoder to decode the text subtitle stream using the first information and the second information. | 24. An apparatus for reproducing text subtitle streams, the apparatus comprising: a decoder configured to decode the at least one text subtitle stream received from an external source, each text subtitle stream including text data to be displayed within a region of a display screen, first information specifying a global style of the region, and second information specifying a local style for a portion of the text data; and a controller configured to read a playlist including at least one playitem and first and second subplayitems, the playitem specifying a time based playing interval from an in-time until an out-time associated with at least one audio/video stream, the first subplayitem specifying a time based playing interval from an in-time until an out-time associated with the at least one text subtitle stream, the first subplayitem for a reproducing of the text subtitle stream being synchronized with the playitem, the second subplayitem for a reproduction of browsable slideshow being not synchronized with the playitem and to control the decoder to decode the text subtitle stream using the first information and the second information. 25. The apparatus of claim 24 , wherein the global style comprises a plurality of display properties including font-related display properties required for displaying the text data, and the local style comprises at least one of the font-related display properties applied for the portion of the text data. | 0.5 |
8,495,735 | 13 | 15 | 13. The method as recited in claim 12 , further including the step of using the processor to adjust said similarity value in response to the severity of a phishing attack upon a legitimate website. | 13. The method as recited in claim 12 , further including the step of using the processor to adjust said similarity value in response to the severity of a phishing attack upon a legitimate website. 15. The method as recited in claim 13 , wherein said step of using the processor portion to compare said hash value set to prior saved hash value sets comprises the formula: J ( A , B ) = A ⋂ B A ⋃ B . | 0.684783 |
8,650,188 | 15 | 17 | 15. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations in response to a request to create a retargeting set by a content item provider, comprising: providing a code segment that upon execution by a browser causes the browser to submit interaction data indicating that the code segment was executed, the interaction data including a set identifier for the retargeting set and a user identifier for the user device that caused execution of the code segment; storing, in relation to the set identifier for the retargeting set, any interaction data submitted in response to an execution of the code segment, wherein the user identifier for the user device that caused execution of the code segment is stored as a retargeted identifier corresponding to that user identifier; receiving a request for a content item to be provided with a search results page, the request including data indicative of a search query that was submitted by a user device and a particular user identifier for the user device; identifying a plurality of keyword targeted content items that are eligible for presentation with the search results page, each of the eligible keyword targeted content items being a content item that is eligible for presentation based on the search query matching a targeting keyword for the keyword targeted content item; determining that one or more retargeted content items are eligible for presentation with the search results page, each of the retargeted content items being a content item that is eligible for presentation with the search results page based on: the search query matching a targeting keyword for the retargeted content item; and the particular user identifier matching the retargeted identifier that is included in the stored retargeting set, each retargeted identifier in the stored retargeting set being a user identifier that was received with interaction data indicating that a pre-specified user interaction which facilitates targeting retargeted content items previously occurred; selecting, based at least in part on bids that are associated with each of the keyword targeted content items that are eligible for presentation and each of the one or more retargeted content items that are eligible for presentation, a responsive content item to be presented with the search results page; and providing data specifying the responsive content item. | 15. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations in response to a request to create a retargeting set by a content item provider, comprising: providing a code segment that upon execution by a browser causes the browser to submit interaction data indicating that the code segment was executed, the interaction data including a set identifier for the retargeting set and a user identifier for the user device that caused execution of the code segment; storing, in relation to the set identifier for the retargeting set, any interaction data submitted in response to an execution of the code segment, wherein the user identifier for the user device that caused execution of the code segment is stored as a retargeted identifier corresponding to that user identifier; receiving a request for a content item to be provided with a search results page, the request including data indicative of a search query that was submitted by a user device and a particular user identifier for the user device; identifying a plurality of keyword targeted content items that are eligible for presentation with the search results page, each of the eligible keyword targeted content items being a content item that is eligible for presentation based on the search query matching a targeting keyword for the keyword targeted content item; determining that one or more retargeted content items are eligible for presentation with the search results page, each of the retargeted content items being a content item that is eligible for presentation with the search results page based on: the search query matching a targeting keyword for the retargeted content item; and the particular user identifier matching the retargeted identifier that is included in the stored retargeting set, each retargeted identifier in the stored retargeting set being a user identifier that was received with interaction data indicating that a pre-specified user interaction which facilitates targeting retargeted content items previously occurred; selecting, based at least in part on bids that are associated with each of the keyword targeted content items that are eligible for presentation and each of the one or more retargeted content items that are eligible for presentation, a responsive content item to be presented with the search results page; and providing data specifying the responsive content item. 17. The computer storage medium of claim 15 , wherein the program comprises instructions that cause the data processing apparatus to perform operations further comprising: identifying a set of retargeted content items having targeting keywords that are matched by the search query; and removing from the set of retargeted content items at least one retargeted content item having a retargeting set that does not include a retargeted identifier that matches the user identifier from the request. | 0.76742 |
9,756,170 | 11 | 18 | 11. A method comprising: displaying message text in a message received at an apparatus over a communications network; receiving an input at the apparatus indicating a first keyword of the displayed message text; identifying, by a controller in the apparatus, a category associated with the first keyword, the identified category being one of a plurality of categories of keywords, each category associated with an operation and with at least one keyword; and performing the operation associated with the identified category to generate a response message including information corresponding to the first keyword; and transmitting the response message from the apparatus over the communications network. | 11. A method comprising: displaying message text in a message received at an apparatus over a communications network; receiving an input at the apparatus indicating a first keyword of the displayed message text; identifying, by a controller in the apparatus, a category associated with the first keyword, the identified category being one of a plurality of categories of keywords, each category associated with an operation and with at least one keyword; and performing the operation associated with the identified category to generate a response message including information corresponding to the first keyword; and transmitting the response message from the apparatus over the communications network. 18. A method according to claim 11 further comprising: parsing the message text to find keywords; displaying these found keywords as marked and receiving said input indicating at least one of said found and marked keywords. | 0.629568 |
7,809,734 | 5 | 8 | 5. A method for transcoding digital content, the method comprising: storing annotations in a database system to be used in a transcoding process, said annotation data is stored in annotation files that are prepared for units of digital contents, the annotation data including descriptions for the transcoding process, the descriptions being correlated with a layout of elements in the digital contents, the database system configured to select the annotation data based on correlation between the layout of the digital content and the descriptions of the annotations; and transcoding by at least one computer processor the digital content based on a selected annotation stored in the database. | 5. A method for transcoding digital content, the method comprising: storing annotations in a database system to be used in a transcoding process, said annotation data is stored in annotation files that are prepared for units of digital contents, the annotation data including descriptions for the transcoding process, the descriptions being correlated with a layout of elements in the digital contents, the database system configured to select the annotation data based on correlation between the layout of the digital content and the descriptions of the annotations; and transcoding by at least one computer processor the digital content based on a selected annotation stored in the database. 8. The method according to claim 5 , wherein, if multiple annotations that can be applied to the digital content are found, the database system selects the annotation that includes the descriptions of a plurality of elements in the digital contents. | 0.5 |
9,911,143 | 2 | 5 | 2. An event-collection-and-event-processing system comprising: one or more computer systems, each having one or more processors, one or more memories, and one or more mass-storage devices; an event-collection subsystem, operating within one or more of the one or more computer systems, which: receives encoded data from one or more browser applications, executing on one or more remote user computers, the encoded data event generated by instrumentation within one or more instrumented web pages processed and rendered for display by the one or more browser applications; processes the received encoded data to produce a set of initially processed events, each of the set of initially processed events having an initial number of data entities; and stores the set of initially processed events in one or more of the one or more memories; an abstraction layer, operating within one or more of the one or more computer systems, that: receives the set of initially processed events from the event-collection subsystem; further processes the set of initially processed events to generate a corresponding set of processed events, each processed event in the set of processed events having a data entity that represents a topic assignment output assigned to the processed event, the further processing including: accessing a set of current distributions, the set of current distributions including: a regular-word distribution associated with a global topic; a seed-word distribution associated with the global topic; for each of a set of topics, a regular-word distribution associated with the topic; and for each of the set of topics, a seed-word distribution associated with the topic, the seed-word distribution associated with the topic including, for each seed word a plurality of seed words, a quantity indicating a number of observations where the seed word was included in an event and was associated with the topic; performing a set of iteration operations that include: for each word of a plurality of words in the set of initially processed events: determining, based on the set of current distributions, whether the word corresponds to a regular word or a seed word; determining, based on the set of current distributions, whether the word corresponds to a global topic or a discovered topic; and updating the set of current distributions based on, for each word of the plurality of words, the determination as to whether the word corresponds to a regular word or a seed word and the determination as to whether the word corresponds to a global topic or a discovered topic; and based on one or more iterations of the set of iteration operations, identifying, for each initially processed event in the set of initially processed events, the topic-assignment output to be represented in a processed event in the set of processed events corresponding to the initially processed event, and an event-consuming application, operating within one or more of the one or more computer systems, that receives the topic-assignment outputs of the set of initially processed events from the abstraction layer and uses the topic-assignment outputs processed events to produce one or more results. | 2. An event-collection-and-event-processing system comprising: one or more computer systems, each having one or more processors, one or more memories, and one or more mass-storage devices; an event-collection subsystem, operating within one or more of the one or more computer systems, which: receives encoded data from one or more browser applications, executing on one or more remote user computers, the encoded data event generated by instrumentation within one or more instrumented web pages processed and rendered for display by the one or more browser applications; processes the received encoded data to produce a set of initially processed events, each of the set of initially processed events having an initial number of data entities; and stores the set of initially processed events in one or more of the one or more memories; an abstraction layer, operating within one or more of the one or more computer systems, that: receives the set of initially processed events from the event-collection subsystem; further processes the set of initially processed events to generate a corresponding set of processed events, each processed event in the set of processed events having a data entity that represents a topic assignment output assigned to the processed event, the further processing including: accessing a set of current distributions, the set of current distributions including: a regular-word distribution associated with a global topic; a seed-word distribution associated with the global topic; for each of a set of topics, a regular-word distribution associated with the topic; and for each of the set of topics, a seed-word distribution associated with the topic, the seed-word distribution associated with the topic including, for each seed word a plurality of seed words, a quantity indicating a number of observations where the seed word was included in an event and was associated with the topic; performing a set of iteration operations that include: for each word of a plurality of words in the set of initially processed events: determining, based on the set of current distributions, whether the word corresponds to a regular word or a seed word; determining, based on the set of current distributions, whether the word corresponds to a global topic or a discovered topic; and updating the set of current distributions based on, for each word of the plurality of words, the determination as to whether the word corresponds to a regular word or a seed word and the determination as to whether the word corresponds to a global topic or a discovered topic; and based on one or more iterations of the set of iteration operations, identifying, for each initially processed event in the set of initially processed events, the topic-assignment output to be represented in a processed event in the set of processed events corresponding to the initially processed event, and an event-consuming application, operating within one or more of the one or more computer systems, that receives the topic-assignment outputs of the set of initially processed events from the abstraction layer and uses the topic-assignment outputs processed events to produce one or more results. 5. The event-collection-and-event-processing system of claim 2 , wherein a word of the plurality of words in the event comprises a key/value pair. | 0.93766 |
9,286,295 | 5 | 7 | 5. The method of claim 1 , further comprising uploading the video, audio or other file onto a cloud based file storage system; and storing a unique alpha numeric code and URL link with the uploaded file; and storing such submitted file and its associated multi-layer scannable tag until the user or systems administrator decides to delete or otherwise remove the submitted file. | 5. The method of claim 1 , further comprising uploading the video, audio or other file onto a cloud based file storage system; and storing a unique alpha numeric code and URL link with the uploaded file; and storing such submitted file and its associated multi-layer scannable tag until the user or systems administrator decides to delete or otherwise remove the submitted file. 7. A method of claim 5 , wherein the stored video, audio, or other file may be password protected or otherwise secured for the benefit of the one who has submitted the file. | 0.544737 |
9,129,303 | 1 | 8 | 1. A method of sharing locations of users participating in a social networking service at a geographic location and communicating app related information of users participating in the social networking service, the method executed by a computer system and comprising: receiving location information and text descriptive information from a mobile device of a first user of the social networking service, the location information representing a geographic location of the first user, the text descriptive information manually provided by the first user on an input module of the mobile device; associating the location information with the text descriptive information of the first user in a database; sending the text descriptive information and the location information of the first user to a second user for display; operating at least one social network application server for interacting with users of the social network application service, wherein at least some of the users of the social network application service are users of wireless computing devices; providing a first mobile application for interacting with the social network application service via communication with the at least one social network application server, the first mobile application providing social network application operations independent of operations of a separate browser application, wherein (i) the first mobile application is further operable to employ geolocation functions of a respective wireless device to communicate geolocation information to one or more servers of hardware and software of the social network application, (ii) the first mobile application is programmed to upload photos to a respective user account with text descriptive information manually entered by the respective user for posting on a webpage of the social network application for the respective user, and (iii) at least some entries of text descriptive information communicated from the first mobile application and received by the one or more servers of the social network application are indicative of current activities of respective users; logging activities of users of the social network application using at least information received from the first mobile application; receiving app usage information, by one or more servers of hardware and software, from a plurality of second mobile applications of different types executing on respective wireless computing devices that is generated independently of user initiated web browsing operations, wherein (i) each of the plurality of second mobile applications includes code for installation on respective wireless computing devices for application operations on respective wireless computing devices, (ii) the plurality of second mobile applications include at least mobile gaming applications that include code for conducting gaming operations without employing a separate browser application on the respective wireless computing device for gaming operations, (iii) the plurality of second mobile applications include mobile digital content applications for accessing digital content from a respective library of digital content without employing a separate browser application on the respective wireless computing device for digital content presentation operations, (iv) the plurality of second mobile application include shopping-related mobile applications for completing shopping operations without employing a separate browser application on the respective wireless computing device for shopping operations, and (v) the second plurality of mobile applications are functionally integrated with the social network application service to share social network user activities and user activities of the second plurality of applications; combining app usage information from the second plurality of mobile applications with social network application information, wherein the combining comprises correlating non-social network application activities to respective identities in the social network application service and wherein the app usage information from the plurality of second mobile applications includes app-specific postings that differ depending on a respective mobile application or mobile application type; presenting combined activity listings to viewing users in one or more respective webpages by one or more web servers; and providing centralized app specific advertising, by one or more servers of hardware and software, for the plurality of second mobile applications, wherein the centralized app specific advertising includes providing rankings of apps including an analysis of app popularity in relation to app usage across an aggregate population of users of the plurality of second mobile applications and wherein the ranking of apps includes determining app usage information within the aggregate population relative to different demographic parameters. | 1. A method of sharing locations of users participating in a social networking service at a geographic location and communicating app related information of users participating in the social networking service, the method executed by a computer system and comprising: receiving location information and text descriptive information from a mobile device of a first user of the social networking service, the location information representing a geographic location of the first user, the text descriptive information manually provided by the first user on an input module of the mobile device; associating the location information with the text descriptive information of the first user in a database; sending the text descriptive information and the location information of the first user to a second user for display; operating at least one social network application server for interacting with users of the social network application service, wherein at least some of the users of the social network application service are users of wireless computing devices; providing a first mobile application for interacting with the social network application service via communication with the at least one social network application server, the first mobile application providing social network application operations independent of operations of a separate browser application, wherein (i) the first mobile application is further operable to employ geolocation functions of a respective wireless device to communicate geolocation information to one or more servers of hardware and software of the social network application, (ii) the first mobile application is programmed to upload photos to a respective user account with text descriptive information manually entered by the respective user for posting on a webpage of the social network application for the respective user, and (iii) at least some entries of text descriptive information communicated from the first mobile application and received by the one or more servers of the social network application are indicative of current activities of respective users; logging activities of users of the social network application using at least information received from the first mobile application; receiving app usage information, by one or more servers of hardware and software, from a plurality of second mobile applications of different types executing on respective wireless computing devices that is generated independently of user initiated web browsing operations, wherein (i) each of the plurality of second mobile applications includes code for installation on respective wireless computing devices for application operations on respective wireless computing devices, (ii) the plurality of second mobile applications include at least mobile gaming applications that include code for conducting gaming operations without employing a separate browser application on the respective wireless computing device for gaming operations, (iii) the plurality of second mobile applications include mobile digital content applications for accessing digital content from a respective library of digital content without employing a separate browser application on the respective wireless computing device for digital content presentation operations, (iv) the plurality of second mobile application include shopping-related mobile applications for completing shopping operations without employing a separate browser application on the respective wireless computing device for shopping operations, and (v) the second plurality of mobile applications are functionally integrated with the social network application service to share social network user activities and user activities of the second plurality of applications; combining app usage information from the second plurality of mobile applications with social network application information, wherein the combining comprises correlating non-social network application activities to respective identities in the social network application service and wherein the app usage information from the plurality of second mobile applications includes app-specific postings that differ depending on a respective mobile application or mobile application type; presenting combined activity listings to viewing users in one or more respective webpages by one or more web servers; and providing centralized app specific advertising, by one or more servers of hardware and software, for the plurality of second mobile applications, wherein the centralized app specific advertising includes providing rankings of apps including an analysis of app popularity in relation to app usage across an aggregate population of users of the plurality of second mobile applications and wherein the ranking of apps includes determining app usage information within the aggregate population relative to different demographic parameters. 8. The method of claim 1 further comprising: generating analytic data that is reflective of tendencies of respective users to engage in identified real-world activities based on app usage information. | 0.516908 |
7,877,367 | 1 | 6 | 1. A computer implemented method of specifying queries comprising: posing an inquiry within context of a given model by receiving user input graphically specifying a query in a graphical user interface, the query being the inquiry applied against streaming data, and the model graphically modeling entities and information including details of the inquiry; utilizing an ontology and a natural language template respective to type of the inquiry in the model, during user construction of the query and outside of query execution generating a plain-text, natural language description of the query; and in the graphical user interface, displaying the generated plain-text, natural language description in a progressive summary, said displaying being during user construction of the query through the graphical user interface and before query execution, the generated plain-text, natural language description being different from graphical specification of the query. | 1. A computer implemented method of specifying queries comprising: posing an inquiry within context of a given model by receiving user input graphically specifying a query in a graphical user interface, the query being the inquiry applied against streaming data, and the model graphically modeling entities and information including details of the inquiry; utilizing an ontology and a natural language template respective to type of the inquiry in the model, during user construction of the query and outside of query execution generating a plain-text, natural language description of the query; and in the graphical user interface, displaying the generated plain-text, natural language description in a progressive summary, said displaying being during user construction of the query through the graphical user interface and before query execution, the generated plain-text, natural language description being different from graphical specification of the query. 6. The computer method as claimed in claim 1 wherein the streaming data has limited structure relative to databases and knowledgebases. | 0.575472 |
10,019,416 | 13 | 17 | 13. A computing device comprising: a communication interface; a processor; and a non-transitory computer-readable medium having stored thereon program instructions that when executed by the processor cause the computing device to perform a set of acts, the set of acts comprising: accessing, by the computing device, data defining multiple portions of a news article, wherein the multiple portions of the news article comprise at least one of a plurality of portions including text, an image, or a hyperlink; selecting, by the computing device, from the plurality of portions including text, a subset of the portions including text, wherein the selecting is based on each portion of the selected subset having a particular characteristic, wherein each portion of the selected subset having the particular characteristic comprises each portion of the selected subset representing text and each portion of the selected subset including content from at least one section from a predefined set of sections of the news article, and further wherein the content from the at least one section of the predefined set of sections is suitable for inclusion in an audible news story; based on the text included in the portions of the selected subset, generating, by the computing device, text-based second data that includes a concatenation of the text included in the portions of the selected subset; and providing, via the communication interface of the computing device, output based on the generated text-based second data. | 13. A computing device comprising: a communication interface; a processor; and a non-transitory computer-readable medium having stored thereon program instructions that when executed by the processor cause the computing device to perform a set of acts, the set of acts comprising: accessing, by the computing device, data defining multiple portions of a news article, wherein the multiple portions of the news article comprise at least one of a plurality of portions including text, an image, or a hyperlink; selecting, by the computing device, from the plurality of portions including text, a subset of the portions including text, wherein the selecting is based on each portion of the selected subset having a particular characteristic, wherein each portion of the selected subset having the particular characteristic comprises each portion of the selected subset representing text and each portion of the selected subset including content from at least one section from a predefined set of sections of the news article, and further wherein the content from the at least one section of the predefined set of sections is suitable for inclusion in an audible news story; based on the text included in the portions of the selected subset, generating, by the computing device, text-based second data that includes a concatenation of the text included in the portions of the selected subset; and providing, via the communication interface of the computing device, output based on the generated text-based second data. 17. The computing device of claim 13 , wherein the computing device is a first computing device, wherein providing, via the communication interface, output based on the generated text-based second data comprises transmitting, via the communication interface, to a second computing device, output based on the generated text-based second data. | 0.5 |
7,707,593 | 10 | 11 | 10. A computer system that communicates with an implementation module which accesses a host-environment module on behalf of content for enabling the content to interact with a selected hosting environment, the system comprising: a memory that stores an interaction interface module that indicates in the content at least one desired interaction with any one of a plurality of hosting environments, wherein the hosting environments include a browser environment and a window environment, and an interaction expression module that identifies the at least one desired interaction in the content for the implementation module without providing implementation instructions associated with the any one of the plurality of hosting environments; and a processor that processes the interaction interface module and the interaction expression module; wherein the interaction interface module and the interaction expression module comprise at least one of either one or more programmatic language statements, one or more declarative language statements, one or more extensible application markup oriented language (XAML) statements, or any other computer language statements, and wherein the implementation module identifies a selected hosting environment by examining a settings module associated with the implementation modules, references the host-environment module that is associated with the selected hosting environment, and references an object interface module that allows accessing the host-environment module by issuing at least one call on a browser environment module or a window environment module that becomes available when the selected hosting environment is selected. | 10. A computer system that communicates with an implementation module which accesses a host-environment module on behalf of content for enabling the content to interact with a selected hosting environment, the system comprising: a memory that stores an interaction interface module that indicates in the content at least one desired interaction with any one of a plurality of hosting environments, wherein the hosting environments include a browser environment and a window environment, and an interaction expression module that identifies the at least one desired interaction in the content for the implementation module without providing implementation instructions associated with the any one of the plurality of hosting environments; and a processor that processes the interaction interface module and the interaction expression module; wherein the interaction interface module and the interaction expression module comprise at least one of either one or more programmatic language statements, one or more declarative language statements, one or more extensible application markup oriented language (XAML) statements, or any other computer language statements, and wherein the implementation module identifies a selected hosting environment by examining a settings module associated with the implementation modules, references the host-environment module that is associated with the selected hosting environment, and references an object interface module that allows accessing the host-environment module by issuing at least one call on a browser environment module or a window environment module that becomes available when the selected hosting environment is selected. 11. The computer system as set forth in claim 10 wherein the implementation module accesses the host-environment module by issuing at least one call comprising at least one of either invoking at least one method, registering at least one event handler, or assigning at least one value to at least one attribute. | 0.5 |
9,124,590 | 17 | 19 | 17. An intelligent information providing method to a user terminal, the method comprising the steps of: (a) executing an application providing a memo pad, selecting an intent designation command, and obtaining a given word selected from a content recorded on the memo pad by a user; (b) enlarging and outputting the given word and designating the enlarged word as an intent and alternatively outputting an intent recommendation list for the selected word and designating the selected word by the user in the intent recommendation list as an intent, in accordance with a previously set intent designation type; and (c) registering the designated word as the intent, wherein the step of (b) comprises the steps of, when the intent designation type is a recommendation input type, recognizing the selected word to acquire similar words thereto, and outputting the similar words as the intent recommendation list to a given area on the memo pad, and designating the word selected by the user in the intent recommendation list as the intent. | 17. An intelligent information providing method to a user terminal, the method comprising the steps of: (a) executing an application providing a memo pad, selecting an intent designation command, and obtaining a given word selected from a content recorded on the memo pad by a user; (b) enlarging and outputting the given word and designating the enlarged word as an intent and alternatively outputting an intent recommendation list for the selected word and designating the selected word by the user in the intent recommendation list as an intent, in accordance with a previously set intent designation type; and (c) registering the designated word as the intent, wherein the step of (b) comprises the steps of, when the intent designation type is a recommendation input type, recognizing the selected word to acquire similar words thereto, and outputting the similar words as the intent recommendation list to a given area on the memo pad, and designating the word selected by the user in the intent recommendation list as the intent. 19. The intelligent information providing method according to claim 17 , further comprising the steps of: requesting an information management device to register the intent; and receiving the information related to the registered intent or the style information on a role model in a group related to the intent from the information management device, after the step of (b), and wherein the information related to the intent is formed of the information converted into templates in response to the intent of the user. | 0.5 |
4,695,977 | 2 | 3 | 2. The method of claim 1 further comprises the steps of: deactivating the execution of said first one of said scripts by said computer system by a third one of said scripts being executed by said computer system; and controlling a third operation in said process by the execution of said second one of said scripts by said computer system in response to said first signal upon the deactivation of the execution of said first one of said scripts. | 2. The method of claim 1 further comprises the steps of: deactivating the execution of said first one of said scripts by said computer system by a third one of said scripts being executed by said computer system; and controlling a third operation in said process by the execution of said second one of said scripts by said computer system in response to said first signal upon the deactivation of the execution of said first one of said scripts. 3. The method of claim 2 wherein said real-time telephone process assumes a plurality of states and each of said program scripts comprises a plurality of groups of instructions each of whose execution is determined by said computer system responding to one of the process states and one of the signals from the real-time telephone process, said executing step to control said first operation comprises the steps of responding to said first signal by said computer system's execution of one of said groups of instructions of said first one of said scripts upon said process being in one of said states; performing the control of said first operation by said computer system's execution of one of said program instructions of said group of instructions of said first one of said scripts; and said step of blocking comprises the step of stopping said computer system's execution of further groups of instructions in response to said first signal by execution of a second one of said instructions of said group of instructions of said first one of said script. | 0.5 |
8,234,263 | 1 | 3 | 1. A computer-implemented method for building a dynamic classification dictionary, the method comprising: analyzing, with a computing device, author-generated classification information regarding a document and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization; identifying, with a computing device, a method of access through which the document has been accessed from a content provider and assigning a set of third taxonomic nouns to characterize the document based upon the method of access; evaluating, with a computing device, attributes related to the method of access and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the method of access; processing, with a computing device, the document to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; and building, with a computing device, a dynamic classification dictionary by storing the composite set of taxonomic nouns. | 1. A computer-implemented method for building a dynamic classification dictionary, the method comprising: analyzing, with a computing device, author-generated classification information regarding a document and assigning a set of first taxonomic nouns to characterize the document based upon the author-generated classification information; examining, with a computing device, a user-generated tag from a client computer characterizing a portion of the document and assigning a set of second taxonomic nouns to characterize the document based upon the user-generated tag characterization; identifying, with a computing device, a method of access through which the document has been accessed from a content provider and assigning a set of third taxonomic nouns to characterize the document based upon the method of access; evaluating, with a computing device, attributes related to the method of access and assigning a set of fourth taxonomic nouns to characterize the document based upon the attributes related to the method of access; processing, with a computing device, the document to extract a set of fifth taxonomic nouns to characterize the document based upon a predetermined pattern rule; aggregating, with a computing device, the set of first taxonomic nouns, the set of second taxonomic nouns, the set of third taxonomic nouns, the set of fourth taxonomic nouns, and the set of fifth taxonomic nouns into a composite set of taxonomic nouns; and building, with a computing device, a dynamic classification dictionary by storing the composite set of taxonomic nouns. 3. The computer-implemented method for building a dynamic classification dictionary of claim 1 , further comprising: filtering the nouns in the dynamic classification dictionary using statistical attributes and heuristic filtering rules. | 0.591379 |
8,041,781 | 11 | 12 | 11. The method of claim 10 further comprising receiving content and context information to input into the web application document. | 11. The method of claim 10 further comprising receiving content and context information to input into the web application document. 12. The method of claim 11 further comprising storing the web application document on a web server. | 0.5 |
8,356,041 | 2 | 3 | 2. The method of claim 1 , comprising: receiving user input in a character entry field; and presenting the at least two terms from the first group of terms based upon the received user input. | 2. The method of claim 1 , comprising: receiving user input in a character entry field; and presenting the at least two terms from the first group of terms based upon the received user input. 3. The method of claim 2 , comprising inserting the generated phrase into the character entry field. | 0.689441 |
7,810,021 | 21 | 22 | 21. An apparatus for producing an electronic literary macramé of texts from a literary work, comprising: a computer, input means for the computer; display means for the computer; information storage and retrieval means for holding data and instructions for the computer; a repository for information connected to the computer; a set of files residing in the repository for information; a database program or spreadsheet program operating within the computer; a database supported by the database program or spreadsheet program for holding information concerning the characteristics of one or more scenes presented in the literary work; a set of processing control files residing in the repository for information, for linking the scenes of the literary work; a set of scene text files residing in the repository for information and containing the literary work; a set of reference text files residing in the repository for information and containing information supportive of the literary work; a set of link records residing in the repository for information and containing link information interconnecting the contents of the scene text files and reference text files; a set of utility programs and scripts operating within the computer for converting the set of scene text files into a set of scene hypertext files linking among scene text files of the literary work and linking to reference hypertext files and for converting the set of reference text files to reference hypertext files derived from the reference text files and linked among themselves and linked to the scene hypertext; a browser program operating within the computer for displaying interlinked hypertext files; and a set of display processing programs operating within the computer for adapting the presentation of interlinked hypertext files, wherein the database contains one or more data elements comprising attributes of each scene of a story and wherein the one or more data elements comprise for each scene: a scene title; a scene locale; a scene designator or identifier; the point of view from which the scene is rendered; the date and time of the scene within the narrative text; the copyright year of the writing of the scene; one or more keywords characterizing the scene; a designator of the chapter in which the scene appears; a designator of the section of the chapter in which the scene appears; the source file from which the scene text file is taken; the style of presentation required for the scene text; and the location or window of presentation required for the scene text file. | 21. An apparatus for producing an electronic literary macramé of texts from a literary work, comprising: a computer, input means for the computer; display means for the computer; information storage and retrieval means for holding data and instructions for the computer; a repository for information connected to the computer; a set of files residing in the repository for information; a database program or spreadsheet program operating within the computer; a database supported by the database program or spreadsheet program for holding information concerning the characteristics of one or more scenes presented in the literary work; a set of processing control files residing in the repository for information, for linking the scenes of the literary work; a set of scene text files residing in the repository for information and containing the literary work; a set of reference text files residing in the repository for information and containing information supportive of the literary work; a set of link records residing in the repository for information and containing link information interconnecting the contents of the scene text files and reference text files; a set of utility programs and scripts operating within the computer for converting the set of scene text files into a set of scene hypertext files linking among scene text files of the literary work and linking to reference hypertext files and for converting the set of reference text files to reference hypertext files derived from the reference text files and linked among themselves and linked to the scene hypertext; a browser program operating within the computer for displaying interlinked hypertext files; and a set of display processing programs operating within the computer for adapting the presentation of interlinked hypertext files, wherein the database contains one or more data elements comprising attributes of each scene of a story and wherein the one or more data elements comprise for each scene: a scene title; a scene locale; a scene designator or identifier; the point of view from which the scene is rendered; the date and time of the scene within the narrative text; the copyright year of the writing of the scene; one or more keywords characterizing the scene; a designator of the chapter in which the scene appears; a designator of the section of the chapter in which the scene appears; the source file from which the scene text file is taken; the style of presentation required for the scene text; and the location or window of presentation required for the scene text file. 22. The apparatus of claim 21 wherein the repository for information comprises one or more of any combination of the following: one or more hard disk drives; one or more main random access memory (RAM) units; one or more removable flash memory units; and one or more removable disk units. | 0.827338 |
8,981,971 | 1 | 4 | 1. A method for seismic exploration of the earth comprising the steps of applying to the earth a seismic input signal which is characterized by a seismic source wavelet I(t), recording a seismic trace f(t) in response to said seismic source wavelet, and transforming said seismic source wavelet I(t) into a zero-degree phase wavelet φ p (t) and a shifted 90 degree phase wavelet Ψ p (t), where the wavelets φ p (t) and Ψ p (t) span a two dimensional sub-space, creating a sub-space dictionary as
D s ={(φ p ,Ψ p )} pεΓ where Γ is a set of wavelets which are derived using φ p (t) wavelet and Ψ p (t) wavelet, and projecting said seismic trace f(t) onto said dictionary D s to find the best matching projection, with a residual determined after each projection matching, wherein the sum of said residuals determines the fidelity in data compression. | 1. A method for seismic exploration of the earth comprising the steps of applying to the earth a seismic input signal which is characterized by a seismic source wavelet I(t), recording a seismic trace f(t) in response to said seismic source wavelet, and transforming said seismic source wavelet I(t) into a zero-degree phase wavelet φ p (t) and a shifted 90 degree phase wavelet Ψ p (t), where the wavelets φ p (t) and Ψ p (t) span a two dimensional sub-space, creating a sub-space dictionary as
D s ={(φ p ,Ψ p )} pεΓ where Γ is a set of wavelets which are derived using φ p (t) wavelet and Ψ p (t) wavelet, and projecting said seismic trace f(t) onto said dictionary D s to find the best matching projection, with a residual determined after each projection matching, wherein the sum of said residuals determines the fidelity in data compression. 4. The method of claim 1 wherein said conventional existing wavelet dictionary includes Symlets. | 0.942925 |
7,996,222 | 6 | 10 | 6. A non-transitory machine-readable medium storing machine-executable instructions for performing a method comprising: (a) receiving data for a plurality of segments of a passage in a source voice, wherein the data for each segment of the plurality models a prosodic component of the source voice for that segment; (b) identifying a target voice entry in a codebook for each of the source voice passage segments, wherein each of the identified target voice entries models a prosodic component of a target voice for a different segment of codebook training material; and (c) generating a target voice version of the plurality of passage segments by altering the modeled source voice prosodic component for each segment to replicate the target voice prosodic component modeled by the target voice entry identified for that segment in (b), and wherein the codebook includes multiple source voice entries, each of the multiple source voice entries models a prosodic component of the source voice for a different segment of the codebook training material, each of the multiple source voice entries corresponds to a target voice entry modeling a prosodic component of the target voice for the segment of the codebook training material for which the corresponding source voice entry models the prosodic component of the source voice, operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing data for the source voice passage segment to one or more of the multiple source voice entries, each of the multiple source voice entries and its corresponding target voice entry includes a plurality of transform coefficients representing a contour for the modeled prosodic component, and operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing transform coefficients representing a contour for the prosodic component of the source voice passage segment to the transform coefficients for one or more of the multiple source voice entries. | 6. A non-transitory machine-readable medium storing machine-executable instructions for performing a method comprising: (a) receiving data for a plurality of segments of a passage in a source voice, wherein the data for each segment of the plurality models a prosodic component of the source voice for that segment; (b) identifying a target voice entry in a codebook for each of the source voice passage segments, wherein each of the identified target voice entries models a prosodic component of a target voice for a different segment of codebook training material; and (c) generating a target voice version of the plurality of passage segments by altering the modeled source voice prosodic component for each segment to replicate the target voice prosodic component modeled by the target voice entry identified for that segment in (b), and wherein the codebook includes multiple source voice entries, each of the multiple source voice entries models a prosodic component of the source voice for a different segment of the codebook training material, each of the multiple source voice entries corresponds to a target voice entry modeling a prosodic component of the target voice for the segment of the codebook training material for which the corresponding source voice entry models the prosodic component of the source voice, operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing data for the source voice passage segment to one or more of the multiple source voice entries, each of the multiple source voice entries and its corresponding target voice entry includes a plurality of transform coefficients representing a contour for the modeled prosodic component, and operation (b) includes, for each source voice passage segment, identifying a target voice entry by comparing transform coefficients representing a contour for the prosodic component of the source voice passage segment to the transform coefficients for one or more of the multiple source voice entries. 10. The non-transitory machine-readable medium of claim 6 , wherein the transform is a discrete cosine transform. | 0.949007 |
7,774,203 | 5 | 6 | 5. The audio signal segmentation algorithm according to claim 1 , wherein the estimation of the noise threshold further comprises: extracting a noise segment from the initial part of the audio signal; mixing the noise segment with one of a plurality of noiseless speech/music segments to a predetermined signal-to-noise ratio (SNR) to form a mixing audio segment; applying the audio activity detection step to the mixing audio segment to divide the mixing audio segment into at least one speech segment and at least one music segment by using a first threshold; and judging if the speech segment and the music segment match the noiseless speech/music segment and obtaining a result, if the result is yes, the first threshold being equal to the noise threshold, and if the result is no, adjusting the first threshold and repeating the audio activity detection step and the judging step on the mixing audio segment. | 5. The audio signal segmentation algorithm according to claim 1 , wherein the estimation of the noise threshold further comprises: extracting a noise segment from the initial part of the audio signal; mixing the noise segment with one of a plurality of noiseless speech/music segments to a predetermined signal-to-noise ratio (SNR) to form a mixing audio segment; applying the audio activity detection step to the mixing audio segment to divide the mixing audio segment into at least one speech segment and at least one music segment by using a first threshold; and judging if the speech segment and the music segment match the noiseless speech/music segment and obtaining a result, if the result is yes, the first threshold being equal to the noise threshold, and if the result is no, adjusting the first threshold and repeating the audio activity detection step and the judging step on the mixing audio segment. 6. The audio signal segmentation algorithm according to claim 5 , further comprising: mixing the noise segment and the other noiseless speech/music segments, respectively, and repeating the audio activity detection step and the judging step to obtain a plurality of thresholds; and comparing the thresholds with the first threshold to choose a smallest value as the noise threshold. | 0.5 |
8,688,690 | 1 | 20 | 1. A computer-executable method for estimating a similarity level between a set of documents, the method comprising: extracting, from a set of documents, a set of semantic entities, wherein a respective semantic entity includes a meaningful sequence of characters; determining, for the respective semantic entity, a predefined word group to which the respective semantic entity belongs, wherein the predefined word group indicates a content category associated with the respective semantic entity; computing an inverse document frequency (IDF) value for the respective semantic entity; assigning a weight to the computed IDF value based on the predefined word group to which the respective semantic entity belongs; calculating the similarity level sim(A,B) between a respective document A in the set of documents and a target document B, based on weighted IDF values associated with one or more of the extracted semantic entities, wherein calculating the similarity level involves calculating: sim ⡠( A , B ) = 2 * ∑ e ∈ A ⋂ B ⢠( idf e * w e ) ∑ e ∈ A ⢠( idf e * w e ) + ∑ e ∈ B ⢠( idf e * w e ) , wherein idf e indicates an IDF value for an entity e, and wherein w e indicates a weight for entity e; and producing a result indicating documents that are similar to the target document based on the calculated similarity level. | 1. A computer-executable method for estimating a similarity level between a set of documents, the method comprising: extracting, from a set of documents, a set of semantic entities, wherein a respective semantic entity includes a meaningful sequence of characters; determining, for the respective semantic entity, a predefined word group to which the respective semantic entity belongs, wherein the predefined word group indicates a content category associated with the respective semantic entity; computing an inverse document frequency (IDF) value for the respective semantic entity; assigning a weight to the computed IDF value based on the predefined word group to which the respective semantic entity belongs; calculating the similarity level sim(A,B) between a respective document A in the set of documents and a target document B, based on weighted IDF values associated with one or more of the extracted semantic entities, wherein calculating the similarity level involves calculating: sim ⡠( A , B ) = 2 * ∑ e ∈ A ⋂ B ⢠( idf e * w e ) ∑ e ∈ A ⢠( idf e * w e ) + ∑ e ∈ B ⢠( idf e * w e ) , wherein idf e indicates an IDF value for an entity e, and wherein w e indicates a weight for entity e; and producing a result indicating documents that are similar to the target document based on the calculated similarity level. 20. The method of claim 1 , wherein calculating the similarity level between document A and document B involves calculating: sim ⡠( A , B ) = ∑ e ∈ A ⋂ B ⢠( idf e * w e ) ∑ e ∈ A ⋃ B ⢠( idf e * w e ) . | 0.747153 |
9,996,441 | 12 | 15 | 12. The system of claim 9 , wherein determining the candidate similarity score includes: determining that a text phrase on the first page matches a text phrase on the second page; and adding a first amount to the candidate similarity score based on the determination that the text phrase of the first page matches the text phrase on the second page. | 12. The system of claim 9 , wherein determining the candidate similarity score includes: determining that a text phrase on the first page matches a text phrase on the second page; and adding a first amount to the candidate similarity score based on the determination that the text phrase of the first page matches the text phrase on the second page. 15. The system of claim 12 , wherein the text phrase on the first page is located in a header of the first page or a title of the first page. | 0.837558 |
9,013,399 | 18 | 20 | 18. A method of controlling a processing system comprising the steps of: memorizing voice data from a portable terminal; generating data based on the voice data; transmitting the data to the portable terminal; and erasing the voice data after a predetermined period has passed. | 18. A method of controlling a processing system comprising the steps of: memorizing voice data from a portable terminal; generating data based on the voice data; transmitting the data to the portable terminal; and erasing the voice data after a predetermined period has passed. 20. The method of controlling the processing system of claim 18 , wherein the step of generating generates the data based on a positional data of the portable terminal. | 0.61991 |
10,002,330 | 12 | 16 | 12. A context-based co-operative learning method, comprising: identifying and indexing objects in accordance with pre-determined parameters of identification and indexing, using an identifier; defining parameters of identification in order to determine context topic and/or context theme of the objects based on identifiable features of the objects, using a context determinator; gathering sources of information in relation to or with reference to the identified objects, using an information sources gatherer; searching for the objects, in response to at least a user query, within the determined context topic and/or the determined context theme, using a searcher; building clusters of relevant objects and further adapted to build at least a cluster library based on pre-defined parameters of clustering the clusters, using a cluster data builder; mapping at least a context of the query for the searcher with the clusters from the cluster library to segregate and poll the objects in response to the search query in line with at least a determined context topic and/or the determined context theme, using a context mapper; and allowing multiple systems to co-operatively learn from each other based on determined context topic and/or determined context theme, using a co-operative learner. | 12. A context-based co-operative learning method, comprising: identifying and indexing objects in accordance with pre-determined parameters of identification and indexing, using an identifier; defining parameters of identification in order to determine context topic and/or context theme of the objects based on identifiable features of the objects, using a context determinator; gathering sources of information in relation to or with reference to the identified objects, using an information sources gatherer; searching for the objects, in response to at least a user query, within the determined context topic and/or the determined context theme, using a searcher; building clusters of relevant objects and further adapted to build at least a cluster library based on pre-defined parameters of clustering the clusters, using a cluster data builder; mapping at least a context of the query for the searcher with the clusters from the cluster library to segregate and poll the objects in response to the search query in line with at least a determined context topic and/or the determined context theme, using a context mapper; and allowing multiple systems to co-operatively learn from each other based on determined context topic and/or determined context theme, using a co-operative learner. 16. The method of claim 12 , wherein the defining parameters of identification includes defining a theme using a theme determinator based on an extracted parameter from a set of identified objects, wherein the extracted parameter includes at least one of, a local score of words that is computed, a global score of words, that is computed, based on similarity, a sentence score, that is computed, based on local score, global score, and normalization, and a situation representing primary context. | 0.627436 |
9,128,993 | 1 | 12 | 1. A computer-implemented method comprising: receiving a search query; identifying a plurality of matching resources, matching resources being resources that satisfy the search query; determining that a particular resource of the matching resources has an entry in a database of identified music web pages, wherein each music web page is a resource from which music content can be accessed, wherein each music web page includes markup language music data identifying one or more songs, and wherein each entry is associated with music data identifying one or more songs from a corresponding music web page; generating a presentation of respective search results for the plurality of matching resources, wherein each search result in the presentation includes a title, a snippet, and a link to a corresponding one of the matching resources, including generating, for the particular resource, a particular search result in the presentation having one or more secondary music search result links to respective music web pages in the database of identified music web pages; and providing the presentation of search results in response to the search query. | 1. A computer-implemented method comprising: receiving a search query; identifying a plurality of matching resources, matching resources being resources that satisfy the search query; determining that a particular resource of the matching resources has an entry in a database of identified music web pages, wherein each music web page is a resource from which music content can be accessed, wherein each music web page includes markup language music data identifying one or more songs, and wherein each entry is associated with music data identifying one or more songs from a corresponding music web page; generating a presentation of respective search results for the plurality of matching resources, wherein each search result in the presentation includes a title, a snippet, and a link to a corresponding one of the matching resources, including generating, for the particular resource, a particular search result in the presentation having one or more secondary music search result links to respective music web pages in the database of identified music web pages; and providing the presentation of search results in response to the search query. 12. The system of claim 1 , wherein the database of identified music web pages stores a identified music web pages and one or more respective elements of associated music data for each identified music web page. | 0.69242 |
10,026,047 | 1 | 7 | 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. 7. The system of claim 1 , wherein the crowd sourcing module is further configured to perform the function comprising transmitting a result of completion of the task to the requester. | 0.857698 |
8,782,046 | 14 | 15 | 14. The computer implemented method of claim 11 , further comprises: monitoring cycles of the at least trend; and predicting cyclic behavior of the at least trend based on similar past statistical trends. | 14. The computer implemented method of claim 11 , further comprises: monitoring cycles of the at least trend; and predicting cyclic behavior of the at least trend based on similar past statistical trends. 15. The computer implemented method of claim 14 , further comprising: predicting an expected volume of the at least trend at a given time; simultaneously tracking an actual volume of the at least trend; and computing a surprise factor to determine a general direction of the at least trend using a grading function. | 0.5 |
10,057,594 | 1 | 4 | 1. A method of video coding, the method comprising: obtaining a reference picture list associated with a current prediction unit; obtaining a candidate reference picture list from a plurality of candidate reference picture lists associated with a co-located prediction unit that is co-located with the current prediction unit; determining whether a motion vector scaling operation is associated with using the candidate reference picture list as a motion vector prediction reference picture list associated with the co-located prediction unit; and selecting the motion vector prediction reference picture list associated with the co-located prediction unit from the plurality of candidate reference picture lists based on the determining. | 1. A method of video coding, the method comprising: obtaining a reference picture list associated with a current prediction unit; obtaining a candidate reference picture list from a plurality of candidate reference picture lists associated with a co-located prediction unit that is co-located with the current prediction unit; determining whether a motion vector scaling operation is associated with using the candidate reference picture list as a motion vector prediction reference picture list associated with the co-located prediction unit; and selecting the motion vector prediction reference picture list associated with the co-located prediction unit from the plurality of candidate reference picture lists based on the determining. 4. The method of claim 1 , wherein the determining further comprising: determining that a motion vector scaling operation is not associated with using the candidate reference picture list as the motion vector prediction reference picture list associated with the co-located prediction unit on a condition that the candidate reference picture list has a same reference list index as the reference picture list associated with the current prediction unit. | 0.646646 |
8,015,543 | 20 | 36 | 20. A computer-readable medium comprising instructions, which when executed by a computer system causes the computer system to perform operations for a generating code based on a graphical model, the computer-readable medium comprising: instructions for translating the graphical model into a graphical model code, the graphical model code being compilable into an executable program and including a first graphical model code function, the first graphical model code function being a member of a group of graphical model code functions; instructions for receiving a selection of a first hardware specific library from a plurality of hardware specific libraries, the hardware specific libraries corresponding to one of at least a first target environment and a second target environment, the first hardware specific library corresponding to the first target environment; the hardware specific libraries comprising a plurality of relationships between the group of graphical model code functions and hardware specific functions, the hardware specific functions being compilable into object code for execution in the first target environment, and instructions for performing a lookup of the first graphical model code function in the first hardware specific library; instructions for obtaining a matched hardware specific function based on the lookup, the matched hardware specific function matching at least one property of the graphical model code function and being one of the hardware specific functions from the first hardware specific library; and instructions for modifying the graphical model code based on the matched hardware specific function. | 20. A computer-readable medium comprising instructions, which when executed by a computer system causes the computer system to perform operations for a generating code based on a graphical model, the computer-readable medium comprising: instructions for translating the graphical model into a graphical model code, the graphical model code being compilable into an executable program and including a first graphical model code function, the first graphical model code function being a member of a group of graphical model code functions; instructions for receiving a selection of a first hardware specific library from a plurality of hardware specific libraries, the hardware specific libraries corresponding to one of at least a first target environment and a second target environment, the first hardware specific library corresponding to the first target environment; the hardware specific libraries comprising a plurality of relationships between the group of graphical model code functions and hardware specific functions, the hardware specific functions being compilable into object code for execution in the first target environment, and instructions for performing a lookup of the first graphical model code function in the first hardware specific library; instructions for obtaining a matched hardware specific function based on the lookup, the matched hardware specific function matching at least one property of the graphical model code function and being one of the hardware specific functions from the first hardware specific library; and instructions for modifying the graphical model code based on the matched hardware specific function. 36. The computer-readable medium of claim 20 , wherein the hardware specific library is specified by a user. | 0.915493 |
9,471,581 | 1 | 7 | 1. A method for suggesting one or more autocompletions to a file name for a file to save, the method performed by a computer system, the method comprising: building an autocomplete dictionary based on text in a file by adding at least some text from the file to the autocomplete dictionary; receiving a request from a user to save the file; in response to the request from the user to save the file, the computer system presenting a user interface element for specifying a name for the file to be saved, the user interface element configured to receive text entry; receiving text entry from the user in the user interface element; submitting at least a portion of the text entry of the user to the autocomplete dictionary in order to search the autocomplete dictionary; in response to the search based on the portion of the text entry of the user, receiving from the autocomplete dictionary one or more proposed autocompletions, each of the one or more proposed autocompletions containing the portion of the text entry of the user as a prefix and at least one of the one or more proposed autocompletions containing text from the file; presenting, by the computer system, the one or more proposed autocompletions to the user. | 1. A method for suggesting one or more autocompletions to a file name for a file to save, the method performed by a computer system, the method comprising: building an autocomplete dictionary based on text in a file by adding at least some text from the file to the autocomplete dictionary; receiving a request from a user to save the file; in response to the request from the user to save the file, the computer system presenting a user interface element for specifying a name for the file to be saved, the user interface element configured to receive text entry; receiving text entry from the user in the user interface element; submitting at least a portion of the text entry of the user to the autocomplete dictionary in order to search the autocomplete dictionary; in response to the search based on the portion of the text entry of the user, receiving from the autocomplete dictionary one or more proposed autocompletions, each of the one or more proposed autocompletions containing the portion of the text entry of the user as a prefix and at least one of the one or more proposed autocompletions containing text from the file; presenting, by the computer system, the one or more proposed autocompletions to the user. 7. The method of claim 1 , wherein text from the file is added to the autocomplete dictionary only if the text exceeds a prominence threshold. | 0.812665 |
5,404,507 | 25 | 28 | 25. The system of claim 23 wherein the predetermined parameter comprises a closeness value indicator assigned to each record retrieved in the information database. | 25. The system of claim 23 wherein the predetermined parameter comprises a closeness value indicator assigned to each record retrieved in the information database. 28. The system of claim 25 wherein the highest closeness value indicator is assigned to the one of the retrieved records having the greater number of matching words and the fewer number of nonmatching words. | 0.535874 |
9,552,810 | 6 | 9 | 6. A computer program product for customizing speech recognition for users with language accents, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer to cause the computer to perform a method, comprising: identifying, using the computer, a spoken language of a user; receiving, using the computer, an indicator of a speech accent language initiated by the user using a computer, the indicator identifying the speech accent language and defining an influence of the speech accent language on the spoken language, the indicator is provided on an interface of the computer, and the indicator is adjustable by the user to identify the influence of the speech accent language on the spoken language, wherein the indicator includes a value identifying the speech accent language influence on the spoken language; setting speech recognition characteristics, using the computer, according to the spoken language and the indicator; adjusting, using the computer, an automatic speech recognition (ASR) conversion based on the speech recognition characteristics; converting the spoken language of the user into text using the automatic speech recognition conversion; and receiving an adjustable value on a numbered scale as part of the indicator to identify the influence of the speech accent language on the spoken language, the adjustable value being set by the user and identifying an amount of influence of the accent language on the spoken language. | 6. A computer program product for customizing speech recognition for users with language accents, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer to cause the computer to perform a method, comprising: identifying, using the computer, a spoken language of a user; receiving, using the computer, an indicator of a speech accent language initiated by the user using a computer, the indicator identifying the speech accent language and defining an influence of the speech accent language on the spoken language, the indicator is provided on an interface of the computer, and the indicator is adjustable by the user to identify the influence of the speech accent language on the spoken language, wherein the indicator includes a value identifying the speech accent language influence on the spoken language; setting speech recognition characteristics, using the computer, according to the spoken language and the indicator; adjusting, using the computer, an automatic speech recognition (ASR) conversion based on the speech recognition characteristics; converting the spoken language of the user into text using the automatic speech recognition conversion; and receiving an adjustable value on a numbered scale as part of the indicator to identify the influence of the speech accent language on the spoken language, the adjustable value being set by the user and identifying an amount of influence of the accent language on the spoken language. 9. The computer program product of claim 6 , wherein the indicator is adjustable by the user, and the user identifies the spoken language from multiple language options. | 0.5 |
9,703,548 | 1 | 17 | 1. An application server for generating project specific configuration data, the application server comprising: a processor for processing digital data; a memory device for storing digital data including computer program code, the memory device being coupled to the processor; a data interface for sending and receiving data across a data network, the data interface being coupled to the processor, a database connection for storing and retrieving digital data including a plurality of items of project template data representing at least one project template, wherein the processor is controlled by the computer program code to: receive, via the data interface, the project template data; store, using the database connection, the project template data; receive, via the data interface, question configuration data representing at least one question and at least one associated candidate answer; store, using the database connection, the question configuration data; receive, via the data interface, rule data representing a rule relating the project template data and the question configuration data; store, using the database connection, the rule data; send, via the data interface, question data from the question configuration data; receive, via the data interface, answer data in response to the question data; and generate project specific configuration data from the project template data in accordance with the answer data and the rule data, wherein the rule data maps the answer data to the items of project template data to select items of project template data, wherein the selected items of project template data are added to build the project configuration data. | 1. An application server for generating project specific configuration data, the application server comprising: a processor for processing digital data; a memory device for storing digital data including computer program code, the memory device being coupled to the processor; a data interface for sending and receiving data across a data network, the data interface being coupled to the processor, a database connection for storing and retrieving digital data including a plurality of items of project template data representing at least one project template, wherein the processor is controlled by the computer program code to: receive, via the data interface, the project template data; store, using the database connection, the project template data; receive, via the data interface, question configuration data representing at least one question and at least one associated candidate answer; store, using the database connection, the question configuration data; receive, via the data interface, rule data representing a rule relating the project template data and the question configuration data; store, using the database connection, the rule data; send, via the data interface, question data from the question configuration data; receive, via the data interface, answer data in response to the question data; and generate project specific configuration data from the project template data in accordance with the answer data and the rule data, wherein the rule data maps the answer data to the items of project template data to select items of project template data, wherein the selected items of project template data are added to build the project configuration data. 17. The application server as claimed in claim 1 , wherein the processor is further controlled by the computer program code to associate at least one rule with the at least one associated candidate answer. | 0.762731 |
9,990,425 | 12 | 13 | 12. The system of claim 11 , wherein the database of identified music web pages stores identified music web pages and one or more respective elements of associated music data for each identified music web page. | 12. The system of claim 11 , wherein the database of identified music web pages stores identified music web pages and one or more respective elements of associated music data for each identified music web page. 13. The system of claim 12 , wherein each music web page includes markup language music data identifying one or more songs. | 0.5 |
8,914,769 | 17 | 18 | 17. A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the method comprising: identifying a server data structure defined according to the first programming language; determining types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client; generating a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; and generating source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. | 17. A non-transitory computer readable medium embodying programmed instructions which, when executed by a processor, are operable for performing a method for generating source code to enable communication between a server defined according to a first programming language and a client defined according to a second programming language, the method comprising: identifying a server data structure defined according to the first programming language; determining types of the data structure that are not accessible via a runtime conversion library for communications between the server and the client; generating a revised data structure in the first programming language comprising types that are accessible via the runtime conversion library and that may be used to manipulate the inaccessible types; and generating source code in the second programming language for the client to access the revised data structure via the runtime conversion library, the source code correlating types of the revised data structure to the inaccessible types of the original data structure. 18. The medium of claim 17 further comprising: creating the types of the revised data structure by: recursively analyzing each inaccessible type to identify component types; determining component types that supported for use with the conversion library; and including the determined component types at the revised data structure. | 0.591811 |
7,805,740 | 1 | 5 | 1. A system for providing television advertisements based on a telephone conversation between two or more persons comprising: a speech recognition system for a telephone service configured to monitor a telephone conversation between two or more persons and to recognize key words and phrases spoken by one or more of the persons during the conversation; a database having one or more advertisements indexed by words and phrases; a search engine for querying the database based on key words and phrases recognized during the conversation; a television broadcast for a television service configured to integrate at least one advertisement from the database into the video feed to the television of at least one of the persons based on key words and phrases recognized during the conversation, wherein the television broadcast including the at least one advertisement is received during the telephone conversation. | 1. A system for providing television advertisements based on a telephone conversation between two or more persons comprising: a speech recognition system for a telephone service configured to monitor a telephone conversation between two or more persons and to recognize key words and phrases spoken by one or more of the persons during the conversation; a database having one or more advertisements indexed by words and phrases; a search engine for querying the database based on key words and phrases recognized during the conversation; a television broadcast for a television service configured to integrate at least one advertisement from the database into the video feed to the television of at least one of the persons based on key words and phrases recognized during the conversation, wherein the television broadcast including the at least one advertisement is received during the telephone conversation. 5. The system according to claim 1 , wherein the device used for receiving the television broadcast by at least one of the two or more persons is a television, monitor, display, or computer. | 0.716418 |
8,275,775 | 1 | 4 | 1. A computer-implemented method comprising: parsing a business intelligence query using a processor, the business intelligence query structured in an object access protocol format recognized by a plurality of business intelligence systems; identifying from the parsing a plurality of data elements and values of the data elements in the query; identifying a web service output field corresponding to each identified data element from a mapping of web service output fields to business intelligence query data element fields; restructuring the plurality of data elements and values into a plurality of requests, each request, when executed by the business intelligence system, causing the business intelligence system to identify a result and metadata in the business intelligence system corresponding to at least one of the data elements and values; sending the requests to the business intelligence system to be executed; receiving the identified results and metadata from the business intelligence system; identifying additional content in an enterprise services repository corresponding to an object in the received metadata of each request from a mapping of metadata objects to enterprise services repository content; and incorporating the identified web service output fields, the received identified results and metadata from the business intelligence system, and the identified additional content in the enterprise services repository into a data set output associating the web service output fields with respective identified results and metadata from the business intelligence system and respective identified additional content obtained from the enterprise services repository. | 1. A computer-implemented method comprising: parsing a business intelligence query using a processor, the business intelligence query structured in an object access protocol format recognized by a plurality of business intelligence systems; identifying from the parsing a plurality of data elements and values of the data elements in the query; identifying a web service output field corresponding to each identified data element from a mapping of web service output fields to business intelligence query data element fields; restructuring the plurality of data elements and values into a plurality of requests, each request, when executed by the business intelligence system, causing the business intelligence system to identify a result and metadata in the business intelligence system corresponding to at least one of the data elements and values; sending the requests to the business intelligence system to be executed; receiving the identified results and metadata from the business intelligence system; identifying additional content in an enterprise services repository corresponding to an object in the received metadata of each request from a mapping of metadata objects to enterprise services repository content; and incorporating the identified web service output fields, the received identified results and metadata from the business intelligence system, and the identified additional content in the enterprise services repository into a data set output associating the web service output fields with respective identified results and metadata from the business intelligence system and respective identified additional content obtained from the enterprise services repository. 4. The method of claim 1 , wherein a each mapping is adaptively suggested by a processor based on mappings previously applied to similar data elements and metadata objects. | 0.632479 |
8,473,513 | 1 | 7 | 1. An apparatus comprising: one or more processors; and a computer readable storage medium having computer readable program code embodied therewith and executable by the one or more processors, the computer readable program code comprising: computer readable program code configured to accept an XML document stream; computer readable program code configured to apply a query twig to the XML document stream; computer readable program code configured to extract tuples from the XML document stream based on the query twig and, during streaming of the XML document stream, proactively limit a quantity of extracted tuples via foregoing: extraction of duplicate tuples; and extraction of tuples that do not satisfy query twig criteria; and computer readable program code configured to store, at a non-leaf node in the query twig, information about a child node, and to employ the information in the limiting a quantity of extracted tuples, wherein the information includes state information about the child node, the state information conveying information that relates to at least one node in the XML document stream; said computer readable program code being configured to pre-compute partial results during streaming of an XML document, wherein the XML document stream used to pre-compute partial results is not buffered towards computing a final result; said computer readable program code being configured to accept the XML document stream of a size that exceeds available memory. | 1. An apparatus comprising: one or more processors; and a computer readable storage medium having computer readable program code embodied therewith and executable by the one or more processors, the computer readable program code comprising: computer readable program code configured to accept an XML document stream; computer readable program code configured to apply a query twig to the XML document stream; computer readable program code configured to extract tuples from the XML document stream based on the query twig and, during streaming of the XML document stream, proactively limit a quantity of extracted tuples via foregoing: extraction of duplicate tuples; and extraction of tuples that do not satisfy query twig criteria; and computer readable program code configured to store, at a non-leaf node in the query twig, information about a child node, and to employ the information in the limiting a quantity of extracted tuples, wherein the information includes state information about the child node, the state information conveying information that relates to at least one node in the XML document stream; said computer readable program code being configured to pre-compute partial results during streaming of an XML document, wherein the XML document stream used to pre-compute partial results is not buffered towards computing a final result; said computer readable program code being configured to accept the XML document stream of a size that exceeds available memory. 7. The apparatus according to claim 1 , wherein said computer readable program code is configured to store, at a non-leaf node in the query twig, index information about a child node. | 0.653409 |
8,903,709 | 11 | 13 | 11. The method of claim 8 wherein the designating comprises automatically designating the third document as a source document based upon a policy. | 11. The method of claim 8 wherein the designating comprises automatically designating the third document as a source document based upon a policy. 13. The method of claim 11 wherein the designating comprises automatically designating the third document as a source document based upon effectiveness. | 0.509677 |
8,838,603 | 1 | 4 | 1. A computer-implemented method comprising: providing a partial query term to multiple data provider modules, each data provider module being adapted to search at least one data source using the partial query term; receiving a plurality of search suggestion items responsive to the partial query term from two or more of the data provider modules; grouping the plurality of search suggestion items into a plurality of groups, each group corresponding to at least one data provider module, wherein the grouping is based on the data provider module from which each search suggestion item was received; and providing for display a representation of each group associated with at least one data provider module and one or more of the respective search suggestion items included in the associated group through a user interface. | 1. A computer-implemented method comprising: providing a partial query term to multiple data provider modules, each data provider module being adapted to search at least one data source using the partial query term; receiving a plurality of search suggestion items responsive to the partial query term from two or more of the data provider modules; grouping the plurality of search suggestion items into a plurality of groups, each group corresponding to at least one data provider module, wherein the grouping is based on the data provider module from which each search suggestion item was received; and providing for display a representation of each group associated with at least one data provider module and one or more of the respective search suggestion items included in the associated group through a user interface. 4. The computer-implemented method of claim 1 , further comprising: receiving data indicating a user selection identifying one of the search suggestion items from the user interface; and rendering a status bar indicating the user selection, wherein the status bar comprises at least one action control, a number and a type of the at least one action control being based on a type of the search suggestion item identified by the user selection. | 0.5 |
4,539,653 | 17 | 22 | 17. The automatic typographic page formatter set forth in claim 1 wherein said named area control means includes section named area control means coupled to said first means and said receiving means for formatting received text signals to section named areas and for placing same onto a page within predetermined ones of said vertical portions; and page/body named control area means in said named area control means coupled to said first means and said receiving means for formatting text signals to an indeterminate length in page or body named areas and having first placement means for placing predetermined ones of said named areas anywhere on the page independent of said portions and having second placement means for placing text signals formatted to body ones of said named areas to body ones of said portions; and means in said first means coupled to said named area control means for indicating which of said portions are body ones of said portions. | 17. The automatic typographic page formatter set forth in claim 1 wherein said named area control means includes section named area control means coupled to said first means and said receiving means for formatting received text signals to section named areas and for placing same onto a page within predetermined ones of said vertical portions; and page/body named control area means in said named area control means coupled to said first means and said receiving means for formatting text signals to an indeterminate length in page or body named areas and having first placement means for placing predetermined ones of said named areas anywhere on the page independent of said portions and having second placement means for placing text signals formatted to body ones of said named areas to body ones of said portions; and means in said first means coupled to said named area control means for indicating which of said portions are body ones of said portions. 22. The automatic typographic page formatter set forth in claim 17, wherein said first one embedded commands selectively include an ON parameter, an OFF parameter, a PUT parameter and means in said section named area control means responsive to the PUT parameter to place all text from predetermined ones of said section named areas onto one or more pages being formatted and said named area control means being responsive to the ON parameter to format ensuing received text signals to a designated named area and having means responsive to the OFF parameter to terminate such formatting of text signals to a named area. | 0.549419 |
8,799,767 | 1 | 5 | 1. A method comprising: providing a computing device; receiving, by the computing device, medical status data generated by a monitoring device, the medical status data representing a physiological characteristic of a patient; generating, by the computing device, a script file by applying a transformation to the medical status data, the transformation specified by an Extensible Stylesheet Language Transformation (XSLT) document; executing, by the computing device, the script file; receiving responses from a plurality of receiver systems, each of the responses indicating whether each of the receiver systems successfully received data sent by the computing device; determining whether one or more of the receiver systems is an authority, wherein one receiver system is an authority when operation of the monitoring device is effected by whether the one receiver system successfully received the data; disregarding one or more of the responses when one or more of the receiver systems is not an authority; setting, when one response is a first response received from receiver systems to which the computing device has sent data and the one receiver system is an authority, an overall response to the response; setting, when the one response is not the first response received from the receiver systems to which the computing device sent data and the one receiver system is an authority, the overall response to a result of performing a logical “and” operation on the response and the overall response; and sending the overall response to the monitoring device when the computing device has received responses from each of the receiver systems to which the computing device sent data. | 1. A method comprising: providing a computing device; receiving, by the computing device, medical status data generated by a monitoring device, the medical status data representing a physiological characteristic of a patient; generating, by the computing device, a script file by applying a transformation to the medical status data, the transformation specified by an Extensible Stylesheet Language Transformation (XSLT) document; executing, by the computing device, the script file; receiving responses from a plurality of receiver systems, each of the responses indicating whether each of the receiver systems successfully received data sent by the computing device; determining whether one or more of the receiver systems is an authority, wherein one receiver system is an authority when operation of the monitoring device is effected by whether the one receiver system successfully received the data; disregarding one or more of the responses when one or more of the receiver systems is not an authority; setting, when one response is a first response received from receiver systems to which the computing device has sent data and the one receiver system is an authority, an overall response to the response; setting, when the one response is not the first response received from the receiver systems to which the computing device sent data and the one receiver system is an authority, the overall response to a result of performing a logical “and” operation on the response and the overall response; and sending the overall response to the monitoring device when the computing device has received responses from each of the receiver systems to which the computing device sent data. 5. The method of claim 1 , wherein executing the script file comprises: generating result data; and storing, by the computing device, the result data in a file. | 0.703704 |
7,494,046 | 29 | 30 | 29. The method according to claim 21 wherein the stack includes at least one currency sheet, and further comprising: (e) separating the at least one currency sheet individually from the stack through operation of the unstack device; (f) storing the at least one currency sheet separated in step (e) in at least one currency sheet holding device in the housing. | 29. The method according to claim 21 wherein the stack includes at least one currency sheet, and further comprising: (e) separating the at least one currency sheet individually from the stack through operation of the unstack device; (f) storing the at least one currency sheet separated in step (e) in at least one currency sheet holding device in the housing. 30. The method according to claim 29 and further comprising: (g) crediting an account for the at least one currency sheet through operation of the machine. | 0.5 |
8,682,574 | 11 | 14 | 11. The computer-implemented method of claim 8 , wherein the target attribute is a road familiarity attribute. | 11. The computer-implemented method of claim 8 , wherein the target attribute is a road familiarity attribute. 14. The computer-implemented method of claim 11 , the method further comprising providing a visual indicator of a route familiarity level to the user. | 0.672489 |
7,685,118 | 1 | 10 | 1. A method for solving a problem comprising: receiving a user query problem description which comprises at least one of a structured user query problem description or a non-structured user query problem description, said structured user query problem description comprising a formal semantic representation of said user query problem description, said formal semantic representation comprising fields; parsing said user query problem description when said user query problem description is a said non-structured user query problem description, to create said structured user query problem description; semantically expanding said formal semantic representation of said user query problem description based on an ontology knowledge base to obtain a semantic expansion of said formal semantic representation of said user query problem description, wherein said ontology knowledge base comprises a database of a plurality of terms, each of said plurality of terms being classified as at least one of a term-concept or a term-verb, wherein two or more of said plurality of terms are related with one another representing a knowledge domain, said semantic expansion having a type comprising a kind-of expansion and at least one of a synonym expansion or an association expansion on at least one term in said formal semantic representation of said user query problem description, wherein said kind-of expansion comprises a hypernym to hyponym expansion; searching an expert knowledge base using said semantic expansion to obtain a solutions list including at least one solution for said user query problem description, each said solution comprising fields, said at least one solution having a semantic relation to said user query problem description determined based on said type of semantic expansion; semantically sorting said solutions list based on said semantic relation of said at least one solution to said user query problem description; wherein said semantically sorting comprises sorting said solutions list based on solution types, wherein said solution types comprise: a precise solution comprising said fields exactly coinciding with or a synonym of said fields of said structured user query problem description; a particular solution comprising at least one said field more specific than a corresponding field of said structured user query problem description; a general solution comprising at least one said field generalizing the corresponding field of said structured user query problem description; and an analogous solution comprising at least one said field associated with the corresponding field of said structured user query problem description; and storing said solutions list in a computer-readable storage medium. | 1. A method for solving a problem comprising: receiving a user query problem description which comprises at least one of a structured user query problem description or a non-structured user query problem description, said structured user query problem description comprising a formal semantic representation of said user query problem description, said formal semantic representation comprising fields; parsing said user query problem description when said user query problem description is a said non-structured user query problem description, to create said structured user query problem description; semantically expanding said formal semantic representation of said user query problem description based on an ontology knowledge base to obtain a semantic expansion of said formal semantic representation of said user query problem description, wherein said ontology knowledge base comprises a database of a plurality of terms, each of said plurality of terms being classified as at least one of a term-concept or a term-verb, wherein two or more of said plurality of terms are related with one another representing a knowledge domain, said semantic expansion having a type comprising a kind-of expansion and at least one of a synonym expansion or an association expansion on at least one term in said formal semantic representation of said user query problem description, wherein said kind-of expansion comprises a hypernym to hyponym expansion; searching an expert knowledge base using said semantic expansion to obtain a solutions list including at least one solution for said user query problem description, each said solution comprising fields, said at least one solution having a semantic relation to said user query problem description determined based on said type of semantic expansion; semantically sorting said solutions list based on said semantic relation of said at least one solution to said user query problem description; wherein said semantically sorting comprises sorting said solutions list based on solution types, wherein said solution types comprise: a precise solution comprising said fields exactly coinciding with or a synonym of said fields of said structured user query problem description; a particular solution comprising at least one said field more specific than a corresponding field of said structured user query problem description; a general solution comprising at least one said field generalizing the corresponding field of said structured user query problem description; and an analogous solution comprising at least one said field associated with the corresponding field of said structured user query problem description; and storing said solutions list in a computer-readable storage medium. 10. The method of claim 1 , wherein a relation of two or more of said plurality of terms classified as a term-concept includes at least one of a direct synonym, a kind-of or an association. | 0.807143 |
9,792,014 | 3 | 4 | 3. The method of claim 1 , further comprising; determining a context of item state and providing action commands for the in-place menu according to the item state. | 3. The method of claim 1 , further comprising; determining a context of item state and providing action commands for the in-place menu according to the item state. 4. The method of claim 3 , wherein the item comprises an email item; and the item state comprises read or unread. | 0.5 |
9,645,997 | 1 | 4 | 1. An apparatus comprising: a network interface configured to send messages; one or more processors configured to identify media content that has been at least partially played at a media playback device within a recent period of time; a display mechanism configured to display, within a message composition interface, an arrangement of phrases selected based on the identified media content; an input mechanism configured to receive selection input that selects a particular phrase from the arrangement; wherein the one or more processors are further configured to insert the particular phrase into a message being composed within the message composition interface responsive to the input mechanism receiving the selection input; wherein the network interface is further configured to receive, from a server system, metadata describing the identified media content; wherein the one or more processors are further configured to select at least one of the phrases for inclusion in the arrangement from the metadata describing the identified media content, including at least one of: a title, actor or actress name, writer name, air date or time, channel, clip, or image. | 1. An apparatus comprising: a network interface configured to send messages; one or more processors configured to identify media content that has been at least partially played at a media playback device within a recent period of time; a display mechanism configured to display, within a message composition interface, an arrangement of phrases selected based on the identified media content; an input mechanism configured to receive selection input that selects a particular phrase from the arrangement; wherein the one or more processors are further configured to insert the particular phrase into a message being composed within the message composition interface responsive to the input mechanism receiving the selection input; wherein the network interface is further configured to receive, from a server system, metadata describing the identified media content; wherein the one or more processors are further configured to select at least one of the phrases for inclusion in the arrangement from the metadata describing the identified media content, including at least one of: a title, actor or actress name, writer name, air date or time, channel, clip, or image. 4. The apparatus of claim 1 , further comprising: wherein the network interface is further configured to receive, from a server system, popularity scores for at least a first set of phrases, relative to the identified media content; wherein the one or more processors are further configured to generate the arrangement based at least on the popularity scores. | 0.680605 |
9,690,754 | 15 | 20 | 15. A non-transitory computer readable storage medium comprising computer readable program code that when executed by a processor causes the processor to perform operations comprising: providing a document creation and idea development interface including an input section and a document preview section; providing a structure chart template within said input section wherein said structure chart template comprises a plurality of labeled input blocks; receiving input via said plurality of labeled input blocks within said structure chart template comprising at least one of text, graphics, images, and charts, which conveys said ideas; requiring entry of said input into each of said labeled input blocks with three rules associated with said at least one labeled input block; configuring said labeled input blocks to include an expandable quick guide; generating a plurality of logically organized sentences to form a document configured to facilitate user understanding from said received input and said structure chart template; displaying said document in said document preview section of said document creation interface; and exporting said document for use by at least one other application. | 15. A non-transitory computer readable storage medium comprising computer readable program code that when executed by a processor causes the processor to perform operations comprising: providing a document creation and idea development interface including an input section and a document preview section; providing a structure chart template within said input section wherein said structure chart template comprises a plurality of labeled input blocks; receiving input via said plurality of labeled input blocks within said structure chart template comprising at least one of text, graphics, images, and charts, which conveys said ideas; requiring entry of said input into each of said labeled input blocks with three rules associated with said at least one labeled input block; configuring said labeled input blocks to include an expandable quick guide; generating a plurality of logically organized sentences to form a document configured to facilitate user understanding from said received input and said structure chart template; displaying said document in said document preview section of said document creation interface; and exporting said document for use by at least one other application. 20. The non-transitory computer readable storage medium of claim 15 wherein said expandable quick guide comprises a link to a tutorial providing instructions related to the input to be provided by said user. | 0.600386 |
9,699,249 | 1 | 12 | 1. A method, performed by a client, to dynamically generate an application programming interface that enables the client to access a service provided by a server, the method comprising: receiving a request to connect to the server that provides the service, and in response thereto, connecting to the server; downloading an interface definition language file, wherein the interface definition languages file defines the service; generating interface metadata based on the interface definition language file, wherein the interface metadata includes methods, data types, and messages supported by the server; storing the generated interface metadata in a local memory or storage of the client; and in response to a request to execute a method of the service: generating instructions which implement interface bindings for the method based on the stored interface metadata, and executing the method, wherein the executing of the method includes exchanging messages with the server and receiving a result of the method execution from the server. | 1. A method, performed by a client, to dynamically generate an application programming interface that enables the client to access a service provided by a server, the method comprising: receiving a request to connect to the server that provides the service, and in response thereto, connecting to the server; downloading an interface definition language file, wherein the interface definition languages file defines the service; generating interface metadata based on the interface definition language file, wherein the interface metadata includes methods, data types, and messages supported by the server; storing the generated interface metadata in a local memory or storage of the client; and in response to a request to execute a method of the service: generating instructions which implement interface bindings for the method based on the stored interface metadata, and executing the method, wherein the executing of the method includes exchanging messages with the server and receiving a result of the method execution from the server. 12. The method of claim 1 , wherein the service exposes virtualization functionality. | 0.852431 |
9,665,713 | 1 | 9 | 1. A computer-implemented method for improved zero-day malware detection comprising: receiving, at a computer that includes one or more processors and memory, a set of training files which are each known to be either malign or benign, wherein the training files comprise one or more types of computer files; partitioning, using the one or more computer processors, the set of training files into a plurality of categories wherein the categories are based on a type of file in each category; and training, using the one or more computer processors, category-specific classifiers that distinguish between malign and benign files in a category of files, wherein the training comprises: selecting one of the plurality of categories of training files, wherein each of the one or more categories corresponds to a type of file; identifying features present in the training files in the selected category of training files, wherein the identifying identifies n-gram features and the n-gram features include n-bytes of code; evaluating the identified features to determine the identified features most effective at distinguishing between malign and benign files; and building a category-specific classifier based on the evaluated features. | 1. A computer-implemented method for improved zero-day malware detection comprising: receiving, at a computer that includes one or more processors and memory, a set of training files which are each known to be either malign or benign, wherein the training files comprise one or more types of computer files; partitioning, using the one or more computer processors, the set of training files into a plurality of categories wherein the categories are based on a type of file in each category; and training, using the one or more computer processors, category-specific classifiers that distinguish between malign and benign files in a category of files, wherein the training comprises: selecting one of the plurality of categories of training files, wherein each of the one or more categories corresponds to a type of file; identifying features present in the training files in the selected category of training files, wherein the identifying identifies n-gram features and the n-gram features include n-bytes of code; evaluating the identified features to determine the identified features most effective at distinguishing between malign and benign files; and building a category-specific classifier based on the evaluated features. 9. The method of claim 1 wherein the partitioning further includes creating a category for each new type of file encountered in the set of training files. | 0.800518 |
8,849,787 | 16 | 17 | 16. A computer implemented method of identifying persons related to a query, comprising: processing a query to obtain a query result; dividing the query result into a number of different sections; identifying a set of people based on a number of co-occurrences of a name identifying a person and a subject matter of the query within one of the different sections; ranking the set of people based at least in part on the number of co-occurrences; identifying relationships, from the query result, between at least some of the people in the set of people, by: identifying topics that co-occur in the query result with different people in the set of people; and identifying people in the set of people, that co-occur with each other in a given section of the query result; re-ranking the set of people based on the identified relationships; and generating an output based on the re-ranking. | 16. A computer implemented method of identifying persons related to a query, comprising: processing a query to obtain a query result; dividing the query result into a number of different sections; identifying a set of people based on a number of co-occurrences of a name identifying a person and a subject matter of the query within one of the different sections; ranking the set of people based at least in part on the number of co-occurrences; identifying relationships, from the query result, between at least some of the people in the set of people, by: identifying topics that co-occur in the query result with different people in the set of people; and identifying people in the set of people, that co-occur with each other in a given section of the query result; re-ranking the set of people based on the identified relationships; and generating an output based on the re-ranking. 17. The method of claim 16 , wherein the query result includes documents and related metadata, wherein the identification of the set of people is based at least in part on the related metadata, and wherein the query result is divided into sections having a fixed number of words. | 0.605932 |
8,732,173 | 8 | 13 | 8. A classification hierarchy regeneration method comprising: clustering a data group associated with a hierarchical classification; generating a classification group obtained by extracting a classification which appears in a cluster with a frequency more than a number defined in advance from classifications corresponding to respective data in the cluster; calculating a degree of cooccurrence of two classifications selected from the classification group; regenerating a hierarchy of the classification, based on the classification group and the degree of cooccurrence; calculating the degree of cooccurrence based on a cooccurrence frequency which is the number of data in which two classifications cooccur, and the number of data belonging to each classification; determining whether the above two classifications are in inclusion relationship or in same-meaning relationship, on the basis of the degree of cooccurrence; regenerating the hierarchy of classification on the basis of a determination result indicating whether the two classifications are in inclusion relationship or in same-meaning relationship; and generating the classification group by extracting a classification in which the number of data belonging to the classification is more than a number defined in advance from the classifications corresponding to the respective data in the cluster, wherein when classifications in the generated classification group are separated in the hierarchy of the classification by at least a predefined distance, the clustering unit generates classification groups by dividing the classification group. | 8. A classification hierarchy regeneration method comprising: clustering a data group associated with a hierarchical classification; generating a classification group obtained by extracting a classification which appears in a cluster with a frequency more than a number defined in advance from classifications corresponding to respective data in the cluster; calculating a degree of cooccurrence of two classifications selected from the classification group; regenerating a hierarchy of the classification, based on the classification group and the degree of cooccurrence; calculating the degree of cooccurrence based on a cooccurrence frequency which is the number of data in which two classifications cooccur, and the number of data belonging to each classification; determining whether the above two classifications are in inclusion relationship or in same-meaning relationship, on the basis of the degree of cooccurrence; regenerating the hierarchy of classification on the basis of a determination result indicating whether the two classifications are in inclusion relationship or in same-meaning relationship; and generating the classification group by extracting a classification in which the number of data belonging to the classification is more than a number defined in advance from the classifications corresponding to the respective data in the cluster, wherein when classifications in the generated classification group are separated in the hierarchy of the classification by at least a predefined distance, the clustering unit generates classification groups by dividing the classification group. 13. The classification hierarchy regeneration method according to claim 8 , further comprising: changing at least one condition of a condition of the degree of cooccurrence for regenerating the hierarchy of classification and a condition for generating a classification group when the regenerated classification hierarchy does not satisfy a requirement defined in advance, and instructing to re-update the regenerated classification hierarchy, and wherein generating a classification group obtained by extracting a classification satisfying the changed condition, and regenerating the hierarchy of classification based on the changed condition. | 0.555249 |
7,734,468 | 30 | 31 | 30. The apparatus of claim 28 , wherein the dialog analyzer comprises: an analyzer that analyzes the user speech into speech elements; a keyword extractor that extracts sentence pattern information, modal information, and discourse marker information using the speech elements; a sentence pattern database that stores information on speech acts and dialog turns resulting from the sentence pattern information, the modal information, and the discourse marker information; and a sentence pattern searcher that searches the sentence pattern database using the sentence pattern information, the modal information, and the discourse marker information to generate the first dialog turn information. | 30. The apparatus of claim 28 , wherein the dialog analyzer comprises: an analyzer that analyzes the user speech into speech elements; a keyword extractor that extracts sentence pattern information, modal information, and discourse marker information using the speech elements; a sentence pattern database that stores information on speech acts and dialog turns resulting from the sentence pattern information, the modal information, and the discourse marker information; and a sentence pattern searcher that searches the sentence pattern database using the sentence pattern information, the modal information, and the discourse marker information to generate the first dialog turn information. 31. The apparatus of claim 30 , wherein the speech element analyzed by the analyzer includes morphemes. | 0.878251 |
9,390,240 | 13 | 14 | 13. The information handling system of claim 12 , comprising determining whether the user has permission to access the retrieved data. | 13. The information handling system of claim 12 , comprising determining whether the user has permission to access the retrieved data. 14. The information handling system of claim 13 , wherein the receiving comprises receiving from the user at least one of: a set of one or more search parameters; and a text-based query. | 0.71118 |
8,694,530 | 21 | 25 | 21. A computer readable hardware medium with executable instructions stored thereon, which when executed by a computer processor, cause said computer to execute a method for searching for electronic documents, and providing a search result in response to a search query, the method comprising: receiving a search query from a user, said search query having at least one search query term and receiving a user defined sense to said search system for said one query term; electronically determining a canonical sense of said at least one search query term; displaying alternative senses in which said at least one search query term is used, and receiving the user's selection of at least one the alternative sense; electronically identifying a plurality of alternative terms from a cluster of terms belonging to a same canonical word sense for the at least one search query term based on the user's selection of the at least one alternative sense; electronically displaying said identified plurality of alternative terms for the user; and electronically executing a search for electronic documents that satisfy at least one of said search query term and the plurality of alternative terms. | 21. A computer readable hardware medium with executable instructions stored thereon, which when executed by a computer processor, cause said computer to execute a method for searching for electronic documents, and providing a search result in response to a search query, the method comprising: receiving a search query from a user, said search query having at least one search query term and receiving a user defined sense to said search system for said one query term; electronically determining a canonical sense of said at least one search query term; displaying alternative senses in which said at least one search query term is used, and receiving the user's selection of at least one the alternative sense; electronically identifying a plurality of alternative terms from a cluster of terms belonging to a same canonical word sense for the at least one search query term based on the user's selection of the at least one alternative sense; electronically displaying said identified plurality of alternative terms for the user; and electronically executing a search for electronic documents that satisfy at least one of said search query term and the plurality of alternative terms. 25. The computer readable medium of claim 21 , further comprising displaying for the user, a part-of-speech in which said at least one search query term is presumed to be used. | 0.830769 |
9,304,657 | 4 | 5 | 4. The method of claim 1 , wherein the one or more image files are from a plurality of image files associated with a user, the method further comprising: assigning the one or more textual tags to a second image file from the plurality of image files associated with the user based on a comparison of one or more properties of the one or more image files and the second image file. | 4. The method of claim 1 , wherein the one or more image files are from a plurality of image files associated with a user, the method further comprising: assigning the one or more textual tags to a second image file from the plurality of image files associated with the user based on a comparison of one or more properties of the one or more image files and the second image file. 5. The method of claim 4 , wherein the one or more properties of the one or more image files and the second image file are selected from the following group: file name, file location, file metadata, file creation date, file size, geographical location of a place where the image was captured, and file image analysis results. | 0.5 |
9,740,674 | 15 | 16 | 15. The computer-implemented method of claim 14 , wherein receiving the selection of the formatted cell comprises a user moving a cursor over the cell and clicking a mouse button to select the cell. | 15. The computer-implemented method of claim 14 , wherein receiving the selection of the formatted cell comprises a user moving a cursor over the cell and clicking a mouse button to select the cell. 16. The computer-implemented method of claim 15 , further comprising, in response to the user moving the cursor over the cell, modifying a visual representation of the cursor. | 0.5 |
9,978,067 | 5 | 9 | 5. A method for mitigating digital abuse and/or digital fraud occurring using online services, the method comprising: receiving, via an application program interface, a request for a global digital threat score, the global digital threat score indicating a likelihood of digital fraud and/or digital abuse; collecting digital event data, via a network, from at least one remote source of digital event data, wherein the digital event data comprises data relating to one or more activities and/or events performed using one or more online services of a service provider; using the collected digital event data as input into a machine learning system of a digital threat mitigation platform, the machine learning system comprising one or more computing servers implementing a primary machine learning ensemble that predicts the likelihood of digital fraud and/or digital abuse from the collected digital event data; generating by the machine learning system the global digital threat score based on the input of the collected digital event data, wherein the global digital threat score is agnostic to a category of digital abuse type; identifying a sub-request for a specific digital threat score for a digital abuse type, wherein the digital abuse type relates to one of a plurality of digital abuse types defined by digital fraud and/or digital abuse activities that is committed by an online user of the online services of the service provider; in response to identifying the sub-request, generating by a machine learning classifier a digital abuse label that identifies one specific digital abuse type of a plurality of specific digital abuse types based on the collected digital event data, wherein the one specific digital abuse type indicates a category of digital fraud or digital abuse activity that was perpetrated in the collected digital event data by a user; using the generated digital abuse label to warp the primary machine learning ensemble to a secondary machine learning ensemble that generates a specific digital threat score for the one specific digital abuse type based on the input of the collected digital event data, wherein the specific digital threat score indicates a probability or likelihood that the one specific digital abuse type was committed by the user; transmitting, via a score application program interface, the specific digital threat score for the identified digital abuse type in response to the sub-request. | 5. A method for mitigating digital abuse and/or digital fraud occurring using online services, the method comprising: receiving, via an application program interface, a request for a global digital threat score, the global digital threat score indicating a likelihood of digital fraud and/or digital abuse; collecting digital event data, via a network, from at least one remote source of digital event data, wherein the digital event data comprises data relating to one or more activities and/or events performed using one or more online services of a service provider; using the collected digital event data as input into a machine learning system of a digital threat mitigation platform, the machine learning system comprising one or more computing servers implementing a primary machine learning ensemble that predicts the likelihood of digital fraud and/or digital abuse from the collected digital event data; generating by the machine learning system the global digital threat score based on the input of the collected digital event data, wherein the global digital threat score is agnostic to a category of digital abuse type; identifying a sub-request for a specific digital threat score for a digital abuse type, wherein the digital abuse type relates to one of a plurality of digital abuse types defined by digital fraud and/or digital abuse activities that is committed by an online user of the online services of the service provider; in response to identifying the sub-request, generating by a machine learning classifier a digital abuse label that identifies one specific digital abuse type of a plurality of specific digital abuse types based on the collected digital event data, wherein the one specific digital abuse type indicates a category of digital fraud or digital abuse activity that was perpetrated in the collected digital event data by a user; using the generated digital abuse label to warp the primary machine learning ensemble to a secondary machine learning ensemble that generates a specific digital threat score for the one specific digital abuse type based on the input of the collected digital event data, wherein the specific digital threat score indicates a probability or likelihood that the one specific digital abuse type was committed by the user; transmitting, via a score application program interface, the specific digital threat score for the identified digital abuse type in response to the sub-request. 9. The method of claim 5 , further comprises: generating one or more digital threat scores for one or more cognate digital abuse types, wherein generating the one or more digital threat score for the one or more cognate digital abuse types includes: (i) analyzing the request for the global digital threat score to identify the sub-request for the digital threat score for the digital abuse type; (ii) using a predefined mapping of a plurality of digital abuse types to determine one or more cognate digital abuse types to the digital abuse type of the sub-request, the predefined mapping indicating a relationship between two or more of the plurality of the digital abuse types; and (iii) generating a digital threat score for each of the one or more cognate digital abuse types. | 0.535714 |
8,229,912 | 1 | 8 | 1. A method, comprising: receiving a search query comprising at least one query term; identifying a plurality of source documents based on the at least one query term; identifying a relevant portion of a first source document in the plurality of source documents; identifying a view window appropriate to depict the relevant portion of the first source document, wherein an image size of the view window is smaller than an image size of the first source document; rendering a search results image for the relevant portion of the first source document, the search results image having boundaries corresponding to the view window; and rendering the source document in such a way that the portion of the document contained within the view window is visually distinguishable from the remainder of the document; and providing a set of search results, the set of search results including the search results image. | 1. A method, comprising: receiving a search query comprising at least one query term; identifying a plurality of source documents based on the at least one query term; identifying a relevant portion of a first source document in the plurality of source documents; identifying a view window appropriate to depict the relevant portion of the first source document, wherein an image size of the view window is smaller than an image size of the first source document; rendering a search results image for the relevant portion of the first source document, the search results image having boundaries corresponding to the view window; and rendering the source document in such a way that the portion of the document contained within the view window is visually distinguishable from the remainder of the document; and providing a set of search results, the set of search results including the search results image. 8. A computer readable medium comprising processor executable instructions operable to, when executed, perform the method of claim 1 . | 0.779605 |
8,838,605 | 31 | 40 | 31. An apparatus comprising: memory; one or more computers configured to: parse patent data to generate a set of nodes; select at least one node of the set of nodes; determine initial links from meta data associated with the patent data for the at least one node; create links among the set of nodes based on the metadata; identify a set of seed nodes; determine a community structure for the set of seed nodes, the community structure including a plurality of communities; and assign concepts to the plurality of communities, wherein determining the community structure comprises: initiating a percolation message from a source node of a linked network, the linked network comprising a plurality of nodes and a plurality of edges, each edge connecting at least two of the plurality of nodes, wherein a node is a neighbor if the node is connected to another node in the plurality of nodes by an edge, wherein the percolation message comprises a percolation probability and an identifier of the source node, and wherein initiating a percolation message from the source node comprises transmitting the percolation message to each neighbor of the source node with the percolation probability; propagating the percolation message through the linked network, wherein propagating the percolation message through the linked network comprises: transmitting the percolation message from each node that receives the percolation message to each neighbor of each node that receives the percolation message; and transmitting a response to the source node from each node that receives the percolation message; collecting each response to the percolation message at the source node; and storing a list of nodes that transmitted the response at the source node. | 31. An apparatus comprising: memory; one or more computers configured to: parse patent data to generate a set of nodes; select at least one node of the set of nodes; determine initial links from meta data associated with the patent data for the at least one node; create links among the set of nodes based on the metadata; identify a set of seed nodes; determine a community structure for the set of seed nodes, the community structure including a plurality of communities; and assign concepts to the plurality of communities, wherein determining the community structure comprises: initiating a percolation message from a source node of a linked network, the linked network comprising a plurality of nodes and a plurality of edges, each edge connecting at least two of the plurality of nodes, wherein a node is a neighbor if the node is connected to another node in the plurality of nodes by an edge, wherein the percolation message comprises a percolation probability and an identifier of the source node, and wherein initiating a percolation message from the source node comprises transmitting the percolation message to each neighbor of the source node with the percolation probability; propagating the percolation message through the linked network, wherein propagating the percolation message through the linked network comprises: transmitting the percolation message from each node that receives the percolation message to each neighbor of each node that receives the percolation message; and transmitting a response to the source node from each node that receives the percolation message; collecting each response to the percolation message at the source node; and storing a list of nodes that transmitted the response at the source node. 40. The apparatus of claim 31 , wherein the set of seed nodes is selected from the group consisting of keywords, description, related patent numbers, a company, a person, prior art and topic. | 0.72076 |
9,104,312 | 15 | 16 | 15. A computing system configured to perform data input, the system comprising: one or more processors; a memory; a touch sensitive input configured to: receive, using the one or more processors, a first user input as part of a gesture, wherein the gesture comprises at least a first input selection that represents less than an entire word and a second input selection; and wherein the gesture is a continuous stroke across a virtual keyboard from a first simulated key across one or more other simulated keys; an input recognition module configured to: identify, in the first user input, a bend from the first input selection to a current input location along the gesture; determine that the bend indicates a third input selection that represents a portion of the word between the first input selection and the second input selection; assign to the bend a directional classification from a discrete set of directional classifications; determine one or more candidates for the third input selection based on the candidates for the third input selection being in a direction, relative to the first input selection, corresponding to the assigned directional classification; and determine, using the one or more processors, one or more possible word suggestions based upon the first input selection and the one or more candidates for the third input selection, wherein the one or more possible word suggestions are determined prior to receiving the second input selection; and a display configured to provide the possible word suggestions to the user. | 15. A computing system configured to perform data input, the system comprising: one or more processors; a memory; a touch sensitive input configured to: receive, using the one or more processors, a first user input as part of a gesture, wherein the gesture comprises at least a first input selection that represents less than an entire word and a second input selection; and wherein the gesture is a continuous stroke across a virtual keyboard from a first simulated key across one or more other simulated keys; an input recognition module configured to: identify, in the first user input, a bend from the first input selection to a current input location along the gesture; determine that the bend indicates a third input selection that represents a portion of the word between the first input selection and the second input selection; assign to the bend a directional classification from a discrete set of directional classifications; determine one or more candidates for the third input selection based on the candidates for the third input selection being in a direction, relative to the first input selection, corresponding to the assigned directional classification; and determine, using the one or more processors, one or more possible word suggestions based upon the first input selection and the one or more candidates for the third input selection, wherein the one or more possible word suggestions are determined prior to receiving the second input selection; and a display configured to provide the possible word suggestions to the user. 16. The computing system of claim 15 , wherein the one or more candidates for the third input selection are determined without regard for the proximity of the bend to a representation of the third input selection. | 0.554393 |
9,177,346 | 11 | 12 | 11. A system comprising: one or more hardware processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to: receive an indication of a first user action by a first user; and when the indication is received: analyze content of the first user action; determine a topic of the first user action based at least in part on the analysis; determine whether the tropic is trending; determine whether the first user has indicated a preference to exclude posts associated with the topic or a category associated with the topic; and in response to a determining that the topic is trending and there is no indication, then: notify the first user that the tropic is trending; identify a second user action by a second user that relates to the topic; determine whether the first user has indicated a preference to exclude posts associated with the second user; and in response to a determining that there is no indication of the preference, send to the first user information associated with the second user action with a graphical user interface (GUI) element configured to enable the first user to interact with the second user action. | 11. A system comprising: one or more hardware processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to: receive an indication of a first user action by a first user; and when the indication is received: analyze content of the first user action; determine a topic of the first user action based at least in part on the analysis; determine whether the tropic is trending; determine whether the first user has indicated a preference to exclude posts associated with the topic or a category associated with the topic; and in response to a determining that the topic is trending and there is no indication, then: notify the first user that the tropic is trending; identify a second user action by a second user that relates to the topic; determine whether the first user has indicated a preference to exclude posts associated with the second user; and in response to a determining that there is no indication of the preference, send to the first user information associated with the second user action with a graphical user interface (GUI) element configured to enable the first user to interact with the second user action. 12. The system of claim 11 , wherein: the first and second users are users of a social-networking system; and determining whether the topic is trending comprises determining whether the topic is trending across an entirety of the social-networking system. | 0.750977 |
8,302,008 | 8 | 9 | 8. A computer system comprising: one or more processors and one or more computer-readable, non-transitory storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to access a FLASH presentation (FLAPRE) markup language (FLML) document representing a user-created FLASH presentation, wherein the user-created FLASH presentation comprises at least a plurality of content elements and format definitions; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to translate the FLML document into code usable by a FLASH animation engine, wherein the translating of the FLML document comprises validating the FLML document against a predefined document model; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to render the translated FLML document in a display area, wherein FLASH refers to a format in conformance with the ADOBE FLASH specification as it existed at a time of this disclosure's filing, wherein the accessing, translating, and rendering of the FLML document is performed by a FLAPRE player, wherein the FLAPRE player is a FLASH software application, wherein the FLAPRE player is FLASH BASED and cannot render a FLASH presentation encoded within a .SWF file wherein the program instructions to render the translated FLML document further comprises program instructions to: determine a need to render a content element of the FLASH presentation, wherein data associated with said content element is contained in an electronic file external to and separate from the FLML document, wherein a location of the electronic file is defined within the FLML document; and access the data of the electronic file in real-time and in response to the determined need. | 8. A computer system comprising: one or more processors and one or more computer-readable, non-transitory storage devices; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to access a FLASH presentation (FLAPRE) markup language (FLML) document representing a user-created FLASH presentation, wherein the user-created FLASH presentation comprises at least a plurality of content elements and format definitions; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to translate the FLML document into code usable by a FLASH animation engine, wherein the translating of the FLML document comprises validating the FLML document against a predefined document model; and program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to render the translated FLML document in a display area, wherein FLASH refers to a format in conformance with the ADOBE FLASH specification as it existed at a time of this disclosure's filing, wherein the accessing, translating, and rendering of the FLML document is performed by a FLAPRE player, wherein the FLAPRE player is a FLASH software application, wherein the FLAPRE player is FLASH BASED and cannot render a FLASH presentation encoded within a .SWF file wherein the program instructions to render the translated FLML document further comprises program instructions to: determine a need to render a content element of the FLASH presentation, wherein data associated with said content element is contained in an electronic file external to and separate from the FLML document, wherein a location of the electronic file is defined within the FLML document; and access the data of the electronic file in real-time and in response to the determined need. 9. The system, of claim 8 , wherein the code generated by the translation of the FLML document is ACTIONSCRIPT code, wherein the ACTIONSCRIPT code is utilized by the FLASH animation engine for the rendering of the FLML document, wherein ACTIONSCRIPT refers to a format as it existed at a time of this disclosure's filing. | 0.5 |
8,245,133 | 1 | 8 | 1. A method of generating a customized document about a product, comprising: a) providing a user with a document manager input interface on a computer, the input interface including a definition manager module, an electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) on the computer, defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module; c) on the computer, creating the customized document from the document definition using the definition manager module; d) on the computer, storing the customized document in a relational database; e) on the computer, editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) on the computer, deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) on the computer, modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) on the computer, establishing effectivity associations using the effectivity interface module; i) in response to the user making a change to a given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, and (iv) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document. | 1. A method of generating a customized document about a product, comprising: a) providing a user with a document manager input interface on a computer, the input interface including a definition manager module, an electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) on the computer, defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module; c) on the computer, creating the customized document from the document definition using the definition manager module; d) on the computer, storing the customized document in a relational database; e) on the computer, editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) on the computer, deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) on the computer, modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) on the computer, establishing effectivity associations using the effectivity interface module; i) in response to the user making a change to a given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, and (iv) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document. 8. The method of claim 1 , further comprising: publishing the customized document by performing the steps of: converting the customized document into an extensible markup language document; forwarding the extensible markup language document to an extensible style sheet transform; and outputting the extensible markup language document from the extensible style sheet transform as a published document. | 0.5 |
8,533,130 | 1 | 11 | 1. An apparatus comprising: a memory; a processor operatively coupled to the memory; and a neural network comprising: a plurality of word neurons; a plurality of sentence neurons; at least one document neuron; a plurality of first connections between at least a portion of the plurality of word neurons and the plurality of sentence neurons; and a plurality of second connections between at least a portion of the word neurons and the at least one document neuron, wherein the neural network is configured to excite a first sentence neuron of the plurality of sentence neurons in response to excitation of the at least one document neuron; wherein the processor is configured to change a position of the plurality of word neurons on a display based on an input, and wherein the change in the position of one word neuron changes annotation corresponding to at least one of the plurality of sentence neurons. | 1. An apparatus comprising: a memory; a processor operatively coupled to the memory; and a neural network comprising: a plurality of word neurons; a plurality of sentence neurons; at least one document neuron; a plurality of first connections between at least a portion of the plurality of word neurons and the plurality of sentence neurons; and a plurality of second connections between at least a portion of the word neurons and the at least one document neuron, wherein the neural network is configured to excite a first sentence neuron of the plurality of sentence neurons in response to excitation of the at least one document neuron; wherein the processor is configured to change a position of the plurality of word neurons on a display based on an input, and wherein the change in the position of one word neuron changes annotation corresponding to at least one of the plurality of sentence neurons. 11. The apparatus of claim 1 , wherein the processor is configured to regulate a sum of all activity of all active neurons of the neural network that are excited at any given time. | 0.673913 |
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