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8,396,856 | 1 | 2 | 1. A method of building, managing, and sharing a searchable personalized database, the method comprising: enabling users with personal computers having a local storage system and access to the Internet to create selectively shareable personalized databases of a plurality of selected source files, including files originating from the user's local storage system, files located in access-restricted databases, accessed through the Internet, to which the users have obtained personalized access permission, and selectively shareable files the users create; enabling users to annotate files in their personalized databases and incorporating those annotations into the personalized databases; generating one or more word level inverted indices of the personalized databases to support text searching of database source files and in-context highlighting of search terms during display of database source files; enabling users to register selected ones of a plurality of selectively shareable personalized databases; enabling users to unregister selected ones of a plurality of selectively shareable personalized databases; selectively searching registered ones of the plurality of personalized databases, using the one or more indices, according to a search criterion, to locate words and phrases in the source files of the registered databases; and sending information for the display of at least portions of files in the plurality of selected source files that meet the search criterion with in-context highlighting of search terms consistent with the search criterion. | 1. A method of building, managing, and sharing a searchable personalized database, the method comprising: enabling users with personal computers having a local storage system and access to the Internet to create selectively shareable personalized databases of a plurality of selected source files, including files originating from the user's local storage system, files located in access-restricted databases, accessed through the Internet, to which the users have obtained personalized access permission, and selectively shareable files the users create; enabling users to annotate files in their personalized databases and incorporating those annotations into the personalized databases; generating one or more word level inverted indices of the personalized databases to support text searching of database source files and in-context highlighting of search terms during display of database source files; enabling users to register selected ones of a plurality of selectively shareable personalized databases; enabling users to unregister selected ones of a plurality of selectively shareable personalized databases; selectively searching registered ones of the plurality of personalized databases, using the one or more indices, according to a search criterion, to locate words and phrases in the source files of the registered databases; and sending information for the display of at least portions of files in the plurality of selected source files that meet the search criterion with in-context highlighting of search terms consistent with the search criterion. 2. The method of claim 1 , wherein enabling users to annotate files includes enabling users to create a hyperlink from selected text within a selected file to a destination file, wherein user-selection of said hyperlink opens up the destination file. | 0.5 |
7,650,282 | 1 | 10 | 1. A method for processing acoustically-based events according to a predefined plurality of component events, each component event having a recognition model and having corresponding distributions of recognition scores resulting from application of the recognition model to acoustically-based events, the method comprising: accepting data characterizing a detected instance of an acoustically-based event that is represented by a set of component events, said data including a first recognition score for said detected instance of the acoustically-based event; accepting, for each recognition model of a component event, a plurality of distributions of recognition scores, each distribution of recognition scores for a recognition model being associated with a corresponding different class of a plurality of possible classes, the possible classes including at least a class of true occurrences; and scoring the detected instance of the acoustically-based event, including computing a second recognition score for said detected instance of the acoustically-based event using (i) the accepted distributions of recognition scores for the set of component events used to represent the acoustically-based event, and (ii) the first recognition score for the acoustically-based event. | 1. A method for processing acoustically-based events according to a predefined plurality of component events, each component event having a recognition model and having corresponding distributions of recognition scores resulting from application of the recognition model to acoustically-based events, the method comprising: accepting data characterizing a detected instance of an acoustically-based event that is represented by a set of component events, said data including a first recognition score for said detected instance of the acoustically-based event; accepting, for each recognition model of a component event, a plurality of distributions of recognition scores, each distribution of recognition scores for a recognition model being associated with a corresponding different class of a plurality of possible classes, the possible classes including at least a class of true occurrences; and scoring the detected instance of the acoustically-based event, including computing a second recognition score for said detected instance of the acoustically-based event using (i) the accepted distributions of recognition scores for the set of component events used to represent the acoustically-based event, and (ii) the first recognition score for the acoustically-based event. 10. The method of claim 1 wherein scoring the detected instance of the acoustically-based event includes computing the second recognition score to characterize a degree to which the first recognition score is consistent with the distributions for the component events in the true occurrence class. | 0.5 |
7,617,178 | 7 | 8 | 7. A peer-to-peer file sharing client for moving a file from background file sharing to foreground file sharing and preventing duplicate downloads in a peer-to-peer file sharing network, the peer-to-peer file sharing client comprising: a processor; and a memory, wherein the memory contains instructions which, when executed by the processor, cause the processor to: receive at least one file fragment of a file from a background swarm for background file sharing; responsive to a user-generated request to move the file from background file sharing to foreground file sharing, identify the at least one file fragment stored locally; and request at least one remaining file fragment from the background swarm, wherein the background swarm becomes a foreground swarm, wherein requesting at least one remaining file fragment from the background swarm comprises sending a request to a tracker for a peer list. | 7. A peer-to-peer file sharing client for moving a file from background file sharing to foreground file sharing and preventing duplicate downloads in a peer-to-peer file sharing network, the peer-to-peer file sharing client comprising: a processor; and a memory, wherein the memory contains instructions which, when executed by the processor, cause the processor to: receive at least one file fragment of a file from a background swarm for background file sharing; responsive to a user-generated request to move the file from background file sharing to foreground file sharing, identify the at least one file fragment stored locally; and request at least one remaining file fragment from the background swarm, wherein the background swarm becomes a foreground swarm, wherein requesting at least one remaining file fragment from the background swarm comprises sending a request to a tracker for a peer list. 8. The peer-to-peer file sharing client of claim 7 , wherein identifying the at least one file fragment stored locally comprises: initiating a local request for file fragments; sending a handshake message to self to check for available file fragments; and exchanging messages to self to request and respond for the at least one file fragment stored locally. | 0.5 |
7,543,274 | 10 | 11 | 10. The method of claim 9 , wherein the various equivalent implementations are mathematically equivalent to the process-based specification. | 10. The method of claim 9 , wherein the various equivalent implementations are mathematically equivalent to the process-based specification. 11. The method of claim 10 , wherein the various equivalent implementations are provable equivalent to the process-based specification. | 0.5 |
9,646,000 | 6 | 7 | 6. The search system as recited in claim 5 , wherein the at least one matched record is a completely matched record completely matching all of the at least one keyword or a partially matched record partially matching at least one of the at least one keyword. | 6. The search system as recited in claim 5 , wherein the at least one matched record is a completely matched record completely matching all of the at least one keyword or a partially matched record partially matching at least one of the at least one keyword. 7. The search system as recited in claim 6 , wherein the search interface unit sequentially outputs the completely matched record and the partially matched record, and a priority of the completely matched record is higher than a priority of the partially matched record. | 0.5 |
6,134,235 | 36 | 53 | 36. A method of bridging a first communications network having a payload subnetwork and a signaling subnetwork with a second communications network that is packet-switched, comprising the steps of: a. establishing a first communications link to the payload subnetwork of the first communications network for communicating payload information; b. establishing a second communications link to the signaling subnetwork of the first communications network for communicating signaling information in accordance with a signaling protocol associated with the signaling subnetwork; c. establishing a third communications link to the second communications network for communicating information in accordance with a communications protocol associated with the second communications network; and d. coordinating the transfer of information between the first communications network and the second communications network using the first communications link, the second communications link and the third communications link, wherein the step of coordinating the transfer of information between the first communications network and the second communications network includes initiating at least one of the tasks of communications session setup, communications session tear down, bridging of two communications requests or routing of a communications to a communications access point in one of the first communications network or the second communications network. | 36. A method of bridging a first communications network having a payload subnetwork and a signaling subnetwork with a second communications network that is packet-switched, comprising the steps of: a. establishing a first communications link to the payload subnetwork of the first communications network for communicating payload information; b. establishing a second communications link to the signaling subnetwork of the first communications network for communicating signaling information in accordance with a signaling protocol associated with the signaling subnetwork; c. establishing a third communications link to the second communications network for communicating information in accordance with a communications protocol associated with the second communications network; and d. coordinating the transfer of information between the first communications network and the second communications network using the first communications link, the second communications link and the third communications link, wherein the step of coordinating the transfer of information between the first communications network and the second communications network includes initiating at least one of the tasks of communications session setup, communications session tear down, bridging of two communications requests or routing of a communications to a communications access point in one of the first communications network or the second communications network. 53. The method according to claim 36, further comprising the step of universal messaging, said step of universal messaging including the integration of e-mail messages, facsimile messages, and voice messages into a common mailbox. | 0.820313 |
9,569,327 | 10 | 17 | 10. A method for processing alerts transmitted by at least one device, the method comprising: training a categorization model, comprising: receiving sample alert descriptions as text, the sample alert descriptions being representative of types of new alerts to be processed by the trained categorization model, and receiving a manually-assigned category in a predefined taxonomy for each sample alert description, extracting a set of words from each sample alert description, and training the categorization model with the set of words and the manually-assigned category of each of the sample alert descriptions to assign each word in a remaining set of words of a new alert description to a given category in the taxonomy or probabilistically over all categories and based on the word assignments, to assign an overall category to the new alert description; receiving at least one new alert, transmitted by the at least one device, the new alert using predefined codes and text to define a problem with the associated device outputting the new alert, the new alert including a new alert description in a natural language; extracting a set of words from the new alert description related to a condition of the associated device; with a processor, categorizing the new alert description into to one of the predetermined set of alert categories with the trained categorization model, based on the extracted set of words from the new alert description, and outputting the categorized alert description. | 10. A method for processing alerts transmitted by at least one device, the method comprising: training a categorization model, comprising: receiving sample alert descriptions as text, the sample alert descriptions being representative of types of new alerts to be processed by the trained categorization model, and receiving a manually-assigned category in a predefined taxonomy for each sample alert description, extracting a set of words from each sample alert description, and training the categorization model with the set of words and the manually-assigned category of each of the sample alert descriptions to assign each word in a remaining set of words of a new alert description to a given category in the taxonomy or probabilistically over all categories and based on the word assignments, to assign an overall category to the new alert description; receiving at least one new alert, transmitted by the at least one device, the new alert using predefined codes and text to define a problem with the associated device outputting the new alert, the new alert including a new alert description in a natural language; extracting a set of words from the new alert description related to a condition of the associated device; with a processor, categorizing the new alert description into to one of the predetermined set of alert categories with the trained categorization model, based on the extracted set of words from the new alert description, and outputting the categorized alert description. 17. A computer program product comprising a non-transitory recording medium which stores instructions for performing the method of claim 10 . | 0.901261 |
7,957,969 | 1 | 6 | 1. A system for generating base forms for a non-native language in a speech-based system trained for processing a native language, the system comprising: a text processing system configured to receive input textual data containing both native language and non-native language words, the text processing system configured to identify the native language and non-native language words within the textual data, to generate a native phonetic transcription of the native language words using phonetic units of the native language, and to generate a non-native phonetic transcription of the non-native language words using phonetic units of the non-native language; a pronunciation generator configured to generate a native pronunciation of the non-native language words using phonetic units of the native language by mapping the phonetic units of the non-native phonetic transcription to acoustically similar phonetic units of the native language; and a memory configured to store the input textual data with the corresponding native phonetic transcription of the native language words and the mapped native pronunciation of the non-native language words in a native phonetic lexicon. | 1. A system for generating base forms for a non-native language in a speech-based system trained for processing a native language, the system comprising: a text processing system configured to receive input textual data containing both native language and non-native language words, the text processing system configured to identify the native language and non-native language words within the textual data, to generate a native phonetic transcription of the native language words using phonetic units of the native language, and to generate a non-native phonetic transcription of the non-native language words using phonetic units of the non-native language; a pronunciation generator configured to generate a native pronunciation of the non-native language words using phonetic units of the native language by mapping the phonetic units of the non-native phonetic transcription to acoustically similar phonetic units of the native language; and a memory configured to store the input textual data with the corresponding native phonetic transcription of the native language words and the mapped native pronunciation of the non-native language words in a native phonetic lexicon. 6. The system of claim 1 wherein the pronunciation generator is further configured to generate an alternative pronunciation of at least one of the non-native language words, the alternative pronunciation reflecting a pronunciation that may be better understood by a speaker of the native language than the native pronunciation. | 0.560484 |
9,098,473 | 11 | 19 | 11. A system for accessing an out-space user interface for a program, comprising: a processor; a display; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured to: display a document editor including an in-space actuator and an out-space actuator; in response to receiving a selection of the in-space actuator, display the in-space user interface comprising an in-space user interface area comprising in-space user interface elements and a document display area to display a document, wherein the in-space user interface area comprises a ribbon comprising ribbon tabs and authoring features for authoring the content of the document; and in response to receiving a selection of the out-space actuator, remove at least a portion of the in-space user interface elements displayed in the in-space user interface area, and display the out-space user interface within the document display area, the out-space user interface comprising out-space user interface elements that when selected do not affect the content of the document, and wherein the out-space user interface elements include non-authoring features associated with the document in the document display area. | 11. A system for accessing an out-space user interface for a program, comprising: a processor; a display; and a memory having computer-executable instructions stored thereon, wherein the computer-executable instructions are configured to: display a document editor including an in-space actuator and an out-space actuator; in response to receiving a selection of the in-space actuator, display the in-space user interface comprising an in-space user interface area comprising in-space user interface elements and a document display area to display a document, wherein the in-space user interface area comprises a ribbon comprising ribbon tabs and authoring features for authoring the content of the document; and in response to receiving a selection of the out-space actuator, remove at least a portion of the in-space user interface elements displayed in the in-space user interface area, and display the out-space user interface within the document display area, the out-space user interface comprising out-space user interface elements that when selected do not affect the content of the document, and wherein the out-space user interface elements include non-authoring features associated with the document in the document display area. 19. The system of claim 11 , wherein the out-space actuator is actuated in response to a single actuation. | 0.890041 |
8,316,301 | 12 | 15 | 12. A method of topic based segmenting of video sequences, the method comprising: detecting, using at least one processing device, a plurality of key-frames based on character information from video sequences including a plurality of frames to determine the detected key-frames as start-shots for each topic; and creating a topic list based on the start-shots for each topic, wherein the determination of the start-shots determines the detected key-frames corresponding to a total number of main characters appearing in the video sequences and the total number of main characters is determined by analyzing an electronic program guide (EPG) signal and character clustering. | 12. A method of topic based segmenting of video sequences, the method comprising: detecting, using at least one processing device, a plurality of key-frames based on character information from video sequences including a plurality of frames to determine the detected key-frames as start-shots for each topic; and creating a topic list based on the start-shots for each topic, wherein the determination of the start-shots determines the detected key-frames corresponding to a total number of main characters appearing in the video sequences and the total number of main characters is determined by analyzing an electronic program guide (EPG) signal and character clustering. 15. The method of claim 12 , wherein the determination of the start-shots comprises: detecting a scene change from the frames included in the video sequences to determine frames belonging to a respective scene and obtaining the total number of main characters appearing in the video sequences; detecting faces from the determined frames belonging to the respective scene to determine face detection frames; and clustering the determined face detection frames according to the main characters corresponding to the total number of main characters to determine the face detection frames as key-frames. | 0.5 |
5,579,224 | 4 | 7 | 4. The method of claim 3, wherein the selectively extracting step extracts each section of the second language document which contains a corresponding word of each first language character string according the first and second language correspondence dictionary, and selectively extracts each corresponding second language character string according to a level of correspondence between a section of the first language document from which each first language character string is extracted and each section of the corresponding second language document to which each corresponding second language character string belongs. | 4. The method of claim 3, wherein the selectively extracting step extracts each section of the second language document which contains a corresponding word of each first language character string according the first and second language correspondence dictionary, and selectively extracts each corresponding second language character string according to a level of correspondence between a section of the first language document from which each first language character string is extracted and each section of the corresponding second language document to which each corresponding second language character string belongs. 7. The method of claim 4, wherein the selectively extracting step extracts each corresponding second language character string from each section of the corresponding second language document which has a corresponding word for an object of each first language character string as an object of each corresponding second language character string. | 0.595294 |
7,593,843 | 28 | 32 | 28. A method of determining a score for a word string, the method comprising: using a processor to compute an input semantic structure having a plurality of nodes that relate to an input word string; using the processor to obtain a set of transfer mappings, each of the set of transfer mappings including an input semantic side that describes at least one node of the input semantic structure; and using the processor to score each of the set of transfer mappings which cover at least a select node of the input semantic structure with a target language model that provides a probability of sequences of nodes appearing in an output semantic structure having a plurality of nodes that relate to an output word string, wherein scoring each transfer mapping comprises combining the highest scoring mappings for each child node of the select node not covered by the transfer mapping with the score of the transfer mapping; and using the processor to select the highest scoring transfer mappings of the set of transfer mappings which cover at least the select node to compute the output semantic structure that relates to the output word string. | 28. A method of determining a score for a word string, the method comprising: using a processor to compute an input semantic structure having a plurality of nodes that relate to an input word string; using the processor to obtain a set of transfer mappings, each of the set of transfer mappings including an input semantic side that describes at least one node of the input semantic structure; and using the processor to score each of the set of transfer mappings which cover at least a select node of the input semantic structure with a target language model that provides a probability of sequences of nodes appearing in an output semantic structure having a plurality of nodes that relate to an output word string, wherein scoring each transfer mapping comprises combining the highest scoring mappings for each child node of the select node not covered by the transfer mapping with the score of the transfer mapping; and using the processor to select the highest scoring transfer mappings of the set of transfer mappings which cover at least the select node to compute the output semantic structure that relates to the output word string. 32. The method of claim 28 , wherein scoring the input word string with a target language model comprises scoring the input word string with the target language model in speech recognition. | 0.652574 |
9,910,921 | 10 | 15 | 10. A computer program product for keyword enhancement, said computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to receive an initial keyword list comprising one or more keywords; computer readable program code configured to harvest, using the initial keyword list, information from one or more social media information feeds and ascertain a plurality of events from the harvested information, the events having a location and time; computer readable program code configured to cluster, using at least one of the one or more keywords as a cluster center, the events based on location and time, each cluster being represented by a feature vector, wherein each feature vector comprises a set of keywords, the location, and the time associated with the cluster; computer readable program code configured to identify a temporal evolution state of the event and updating the feature vector associated with the cluster with the temporal evolution state; and computer readable program code configured to update the set of keywords associated with each cluster, wherein the updating the set of keywords comprises removing one or more keywords for event clusters identified as declining based upon the temporal evolution state of the event and adding one or more keywords for event clusters identified as growing based upon the temporal evolution state of the event; the updating the set of keywords comprising accepting the updated feature vector associated with the cluster, generating a candidate list, and comparing information from one or more social media information feeds with the candidate list to generate new keywords for growing event clusters. | 10. A computer program product for keyword enhancement, said computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to receive an initial keyword list comprising one or more keywords; computer readable program code configured to harvest, using the initial keyword list, information from one or more social media information feeds and ascertain a plurality of events from the harvested information, the events having a location and time; computer readable program code configured to cluster, using at least one of the one or more keywords as a cluster center, the events based on location and time, each cluster being represented by a feature vector, wherein each feature vector comprises a set of keywords, the location, and the time associated with the cluster; computer readable program code configured to identify a temporal evolution state of the event and updating the feature vector associated with the cluster with the temporal evolution state; and computer readable program code configured to update the set of keywords associated with each cluster, wherein the updating the set of keywords comprises removing one or more keywords for event clusters identified as declining based upon the temporal evolution state of the event and adding one or more keywords for event clusters identified as growing based upon the temporal evolution state of the event; the updating the set of keywords comprising accepting the updated feature vector associated with the cluster, generating a candidate list, and comparing information from one or more social media information feeds with the candidate list to generate new keywords for growing event clusters. 15. The computer program product according to claim 10 , wherein said computer readable program code is configured to update the initial keyword list with the one or more new keywords. | 0.686007 |
9,760,837 | 1 | 2 | 1. A depth detection apparatus comprising: a memory storing raw time-of-flight sensor data received from a time-of-flight sensor; and a processor comprising a trained machine learning component having been trained using training data pairs, a training data pair comprising at least one simulated raw time-of-flight sensor frame and a corresponding simulated ground truth depth map; the trained machine learning component configured to compute in a single stage, for an item of the stored raw time-of-flight sensor data, a depth map of a surface depicted by the item, by pushing the item through the trained machine learning component. | 1. A depth detection apparatus comprising: a memory storing raw time-of-flight sensor data received from a time-of-flight sensor; and a processor comprising a trained machine learning component having been trained using training data pairs, a training data pair comprising at least one simulated raw time-of-flight sensor frame and a corresponding simulated ground truth depth map; the trained machine learning component configured to compute in a single stage, for an item of the stored raw time-of-flight sensor data, a depth map of a surface depicted by the item, by pushing the item through the trained machine learning component. 2. The apparatus of claim 1 the trained machine learning component having been trained using simulated raw time-of-flight sensor frames which incorporate simulated multi-path interference. | 0.776722 |
8,498,871 | 1 | 5 | 1. A system for facilitating free form dictation and constrained speech recognition and/or structured transcription among users having heterogeneous system protocols the system comprising: at least one system transaction manager using a uniform system protocol, adapted to receive a verified streamed speech information request from at least one user employing a first user legacy protocol, and configured to route a response to one or more users employing a second user legacy protocol, the speech information request comprised of free form dictation of spoken text and commands and the response comprised of a transcription of spoken text; a user interface capable of bi-directional communication with the system transaction manager and supporting dictation applications, including prompts to direct user dictation in response to user system protocol commands and system transaction manager commands the user interface being in bi-directional communication with the systems transaction manager; and, at least one speech recognition and/or transcription engine communicating with the system systems transaction manager wherein the speech recognition and/or transcription engine is configured to receive the speech information request containing spoken text and commands for constrained speech recognition transmitted by the systems transaction manager, to generate structured transcription in response to the speech information request, and to transmit the response comprised of structured transcription to the system transaction manager. | 1. A system for facilitating free form dictation and constrained speech recognition and/or structured transcription among users having heterogeneous system protocols the system comprising: at least one system transaction manager using a uniform system protocol, adapted to receive a verified streamed speech information request from at least one user employing a first user legacy protocol, and configured to route a response to one or more users employing a second user legacy protocol, the speech information request comprised of free form dictation of spoken text and commands and the response comprised of a transcription of spoken text; a user interface capable of bi-directional communication with the system transaction manager and supporting dictation applications, including prompts to direct user dictation in response to user system protocol commands and system transaction manager commands the user interface being in bi-directional communication with the systems transaction manager; and, at least one speech recognition and/or transcription engine communicating with the system systems transaction manager wherein the speech recognition and/or transcription engine is configured to receive the speech information request containing spoken text and commands for constrained speech recognition transmitted by the systems transaction manager, to generate structured transcription in response to the speech information request, and to transmit the response comprised of structured transcription to the system transaction manager. 5. The system of claim 1 wherein said first user legacy protocol is the same as or different than the second user legacy protocol. | 0.88676 |
7,912,715 | 7 | 11 | 7. A method according to claim 1 , wherein, for templates not included in said selected templates, distortion measures computed with respect to a different feature vector are included in said set of distortion measures. | 7. A method according to claim 1 , wherein, for templates not included in said selected templates, distortion measures computed with respect to a different feature vector are included in said set of distortion measures. 11. A method according to claim 7 , wherein said different feature vector is a feature vector compared to the first number of templates from the template set being closest to the current feature vector according to a predefined distance measure. | 0.5 |
7,755,646 | 2 | 3 | 2. The method according to claim 1 , further comprising: for images containing a plurality of graphical representations, determining a morphology of the plurality of graphical representations with respect to each other; and assigning lexical representations of the relative positions of the plurality of graphical representations. | 2. The method according to claim 1 , further comprising: for images containing a plurality of graphical representations, determining a morphology of the plurality of graphical representations with respect to each other; and assigning lexical representations of the relative positions of the plurality of graphical representations. 3. The method according to claim 2 , wherein assigning lexical representations of the plurality of graphical representations further comprises assigning lexical representations pertaining to which of the graphical representations are in contact with which of the graphical representations and which of the graphical representations are in contact with at least one border of a respective image. | 0.5 |
9,083,767 | 16 | 17 | 16. The computer program product of claim 10 , wherein the code when executed performs further steps comprising: weighting the measure of likelihood for the third-party content object associated with the interest of the second user, the weighted measure of likelihood describing whether the first user is interested in the third-party content object. | 16. The computer program product of claim 10 , wherein the code when executed performs further steps comprising: weighting the measure of likelihood for the third-party content object associated with the interest of the second user, the weighted measure of likelihood describing whether the first user is interested in the third-party content object. 17. The computer program product of claim 16 , wherein the code when executed performs further steps comprising: varying the weight applied to the measure of likelihood based on a measure of closeness between the first user and the second user. | 0.5 |
9,213,938 | 19 | 21 | 19. A non-transitory computer-readable medium having encoded thereon executable instructions that, when executed by at least one processor, cause the at least one processor to carry out a method for guidance and navigation of an autonomous vehicle, the autonomous vehicle comprising at least one camera, the method comprising: processing a plurality of images of an environment of the autonomous vehicle captured using the at least one camera of the autonomous vehicle over a period of time to track one or more objects within the environment, wherein processing the plurality of images to track the one or more objects in the environment comprises processing at least two images of the plurality of images to estimate a pose of a first object in the environment, wherein processing the at least two images to estimate the pose of the first object comprises: identifying matching feature points between sequential images; generating hypotheses for a pose component of the pose of the first object; identifying a mode of a probability mass function associated with the hypotheses; extracting low-noise hypotheses; and averaging the low-noise hypotheses to obtain an estimate for the pose component of the pose of the first object. | 19. A non-transitory computer-readable medium having encoded thereon executable instructions that, when executed by at least one processor, cause the at least one processor to carry out a method for guidance and navigation of an autonomous vehicle, the autonomous vehicle comprising at least one camera, the method comprising: processing a plurality of images of an environment of the autonomous vehicle captured using the at least one camera of the autonomous vehicle over a period of time to track one or more objects within the environment, wherein processing the plurality of images to track the one or more objects in the environment comprises processing at least two images of the plurality of images to estimate a pose of a first object in the environment, wherein processing the at least two images to estimate the pose of the first object comprises: identifying matching feature points between sequential images; generating hypotheses for a pose component of the pose of the first object; identifying a mode of a probability mass function associated with the hypotheses; extracting low-noise hypotheses; and averaging the low-noise hypotheses to obtain an estimate for the pose component of the pose of the first object. 21. The computer-readable medium of claim 19 , wherein extracting low-noise hypotheses comprises identifying the hypotheses that are within a predetermined distance of the mode. | 0.79274 |
7,552,145 | 9 | 16 | 9. A system for storing telecommunications data, comprising: a computer system that implements a Graphic User Interface (GUI), the GUI provides selection of a set of criteria, the selected set of criteria includes attributes of a business rule; a computer-readable storage medium that stores a data warehouse, the data warehouse including client data; and a computer-readable storage medium that stores a batch-driven integrated rules module, the batch-driven integrated rules module communicates with the GUI and receives the selected set of criteria, the batch-driven integrated rules module comprises: a rules database that maps the attributes of the selected set of criteria to rules in the rules database, the rules database iteratively utilizes a collection of look-up tables and conditional logic to map the attributes of the selected set of criteria to the rules in the rules database; a script generator that communicates with the rules database and compiles code from the rules in the rules database that were mapped to by the rules database to automatically generate a script for the business rule, and the generated script is loaded in the rules database; a batch tool that extracts the client data from the data warehouse into a batch; and a rules engine that applies the script to the batch to transform the client data according to the business rule, the rules engine further saves the transformed client data into the data warehouse. | 9. A system for storing telecommunications data, comprising: a computer system that implements a Graphic User Interface (GUI), the GUI provides selection of a set of criteria, the selected set of criteria includes attributes of a business rule; a computer-readable storage medium that stores a data warehouse, the data warehouse including client data; and a computer-readable storage medium that stores a batch-driven integrated rules module, the batch-driven integrated rules module communicates with the GUI and receives the selected set of criteria, the batch-driven integrated rules module comprises: a rules database that maps the attributes of the selected set of criteria to rules in the rules database, the rules database iteratively utilizes a collection of look-up tables and conditional logic to map the attributes of the selected set of criteria to the rules in the rules database; a script generator that communicates with the rules database and compiles code from the rules in the rules database that were mapped to by the rules database to automatically generate a script for the business rule, and the generated script is loaded in the rules database; a batch tool that extracts the client data from the data warehouse into a batch; and a rules engine that applies the script to the batch to transform the client data according to the business rule, the rules engine further saves the transformed client data into the data warehouse. 16. The system according to claim 9 , wherein the criteria includes default attributes of the business rule. | 0.790698 |
9,880,987 | 17 | 18 | 17. The computer system of claim 10 , wherein a third parameter included in a third document associated with the current workflow matches the first parameter, and the parameterization module is configured to modify a value associated with a third node in the parameter tree that corresponds to the third parameter. | 17. The computer system of claim 10 , wherein a third parameter included in a third document associated with the current workflow matches the first parameter, and the parameterization module is configured to modify a value associated with a third node in the parameter tree that corresponds to the third parameter. 18. The computer system of claim 17 , wherein the first node and the third node are bound to a first variable and the parameterization module is configured to determine that the first variable is modified; in response, modify the value associated with the first node and the value associated with the third node accordingly. | 0.5 |
10,027,688 | 2 | 5 | 2. The method of claim 1 , further comprising, calculating a suspiciousness score based on the total number of queries to the at least one domain name during the time period and the total number of distinct source IP addresses that queried the at least one domain name during the time period, wherein the classifying the at least one domain name as at least one of malicious, suspicious, and legitimate is further based on the suspiciousness score. | 2. The method of claim 1 , further comprising, calculating a suspiciousness score based on the total number of queries to the at least one domain name during the time period and the total number of distinct source IP addresses that queried the at least one domain name during the time period, wherein the classifying the at least one domain name as at least one of malicious, suspicious, and legitimate is further based on the suspiciousness score. 5. The method of claim 2 , wherein the at least one domain name is ranked based on the suspiciousness score, and wherein the classifying the at least one domain name as at least one of malicious, suspicious, and legitimate is further based the ranking being above a predetermined threshold. | 0.5 |
9,940,935 | 7 | 10 | 7. A voiceprint recognition system, comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the processors to perform operations comprising: establishing a first-level Deep Neural Network (DNN) model based on unlabeled speech data, the unlabeled speech data containing no speaker labels and the first-level DNN model specifying a plurality of basic voiceprint features for the unlabeled speech data; establishing a second-level DNN model by tuning the first-level DNN model based on labeled speech data, the labeled speech data containing speech samples with respective speaker labels, wherein the second-level DNN model specifies a plurality of high-level voiceprint features, the high-level voiceprint features including at least one of formant features and fundamental frequency features; using the second-level DNN model, registering a first high-level voiceprint feature sequence for a user based on a registration speech sample received from the user; and performing speaker verification for the user based on the first high-level voiceprint feature sequence registered for the user, further comprising: receiving, from the user, a test speech sample; obtaining a second high-level voiceprint feature sequence based on the test speech sample using the first-level DNN model and the second-level DNN model in sequence; determining a distance between the second high-level voiceprint feature sequence and the first high-level voiceprint feature sequence registered for the user; and in accordance with a determination that the distance between the second high-level voiceprint feature sequence and the first high-level voiceprint feature sequence is less than a preset threshold, automatically, without user intervention, verifying the identity of the user. | 7. A voiceprint recognition system, comprising: one or more processors; and memory storing instructions that, when executed by the one or more processors, cause the processors to perform operations comprising: establishing a first-level Deep Neural Network (DNN) model based on unlabeled speech data, the unlabeled speech data containing no speaker labels and the first-level DNN model specifying a plurality of basic voiceprint features for the unlabeled speech data; establishing a second-level DNN model by tuning the first-level DNN model based on labeled speech data, the labeled speech data containing speech samples with respective speaker labels, wherein the second-level DNN model specifies a plurality of high-level voiceprint features, the high-level voiceprint features including at least one of formant features and fundamental frequency features; using the second-level DNN model, registering a first high-level voiceprint feature sequence for a user based on a registration speech sample received from the user; and performing speaker verification for the user based on the first high-level voiceprint feature sequence registered for the user, further comprising: receiving, from the user, a test speech sample; obtaining a second high-level voiceprint feature sequence based on the test speech sample using the first-level DNN model and the second-level DNN model in sequence; determining a distance between the second high-level voiceprint feature sequence and the first high-level voiceprint feature sequence registered for the user; and in accordance with a determination that the distance between the second high-level voiceprint feature sequence and the first high-level voiceprint feature sequence is less than a preset threshold, automatically, without user intervention, verifying the identity of the user. 10. The system of claim 7 , wherein establishing the second-level DNN model by tuning the first-level DNN model based on labeled speech data comprises: applying maximum cross entropy rules to train the first-level DNN model based on the labeled speech data. | 0.738289 |
8,965,886 | 23 | 24 | 23. The nontransitory computer readable medium recited in claim 21 , further comprising associating metadata with the one or more objects. | 23. The nontransitory computer readable medium recited in claim 21 , further comprising associating metadata with the one or more objects. 24. The nontransitory computer readable medium recited in claim 23 , wherein the preliminary relevance is determined at least in part based on the metadata. | 0.5 |
9,417,709 | 2 | 4 | 2. The system according to claim 1 , characterized in that, said processor is further configured to: calculate a rough matching degree between words stored in said memory device according to the ideal sliding trajectory features and said user-sliding trajectory features set. | 2. The system according to claim 1 , characterized in that, said processor is further configured to: calculate a rough matching degree between words stored in said memory device according to the ideal sliding trajectory features and said user-sliding trajectory features set. 4. The system according to claim 2 , characterized in that, said processor is further configured to apply an incremental calculation method or a prefix matching method to calculate the rough matching degree. | 0.816814 |
9,069,750 | 15 | 22 | 15. One or more non-transitory computer-readable media having computer-executable instructions, which when executed perform steps, comprising: identifying one or more previously analyzed and indexed corpuses of natural language texts, each corpus including a plurality of sentences and indexes where indexes include indexes of meanings of linguistic parameters of the sentences and of their lexical units and their relations; wherein the linguistic parameters comprise semantic parameters determined based on syntactico-semantic analysis of at least one sentence in the corpuses; and the syntactico-semantic analysis of the at least one sentence comprises performing a rough syntactic analysis of the at least one sentence generating a graph of generalized constituents of the at least one sentence; performing a precise syntactic analysis on the graph of generalized constituents by generating one or more syntactic trees and determining a syntactic structure of the at least one sentence, wherein the performing of the precise syntactic analysis comprises assessing parts of the one or more syntactic trees using prior and statistical ratings, and generating the one or more syntactic trees in an order of decreasing assessment; semantically analyzing the syntactic structure of the sentence generating a language-independent semantic structure of the at least one sentence; generating one or more of the parameters based on the language-independent semantic structure of the at least one sentence; creating a query for searching sentences satisfying the query; searching for sentences of the previously analyzed and indexed corpuses satisfying the query; and displaying the sentences satisfying the query. | 15. One or more non-transitory computer-readable media having computer-executable instructions, which when executed perform steps, comprising: identifying one or more previously analyzed and indexed corpuses of natural language texts, each corpus including a plurality of sentences and indexes where indexes include indexes of meanings of linguistic parameters of the sentences and of their lexical units and their relations; wherein the linguistic parameters comprise semantic parameters determined based on syntactico-semantic analysis of at least one sentence in the corpuses; and the syntactico-semantic analysis of the at least one sentence comprises performing a rough syntactic analysis of the at least one sentence generating a graph of generalized constituents of the at least one sentence; performing a precise syntactic analysis on the graph of generalized constituents by generating one or more syntactic trees and determining a syntactic structure of the at least one sentence, wherein the performing of the precise syntactic analysis comprises assessing parts of the one or more syntactic trees using prior and statistical ratings, and generating the one or more syntactic trees in an order of decreasing assessment; semantically analyzing the syntactic structure of the sentence generating a language-independent semantic structure of the at least one sentence; generating one or more of the parameters based on the language-independent semantic structure of the at least one sentence; creating a query for searching sentences satisfying the query; searching for sentences of the previously analyzed and indexed corpuses satisfying the query; and displaying the sentences satisfying the query. 22. The one or more non-transitory computer-readable media of claim 15 , wherein the query for searching is expressed in terms of one or more requested parameters, one or more of which may be indefinite, or may be defined by means of one or more variables, or may be defined as a range of meanings of these variables. | 0.661325 |
9,158,775 | 1 | 12 | 1. A method for generating a stream of content for a user in real time, the method comprising: generating a model based on at least one interest of the user and at least one prior action from a group of heterogeneous data sources; receiving a request from the user for a real-time content stream; determining contextual cues surrounding the request including a time of day and a geographic location of the user associated with the request; retrieving fresh content items from the heterogeneous data sources based upon recency; storing and indexing the fresh content items in a real-time index; querying the heterogeneous data sources using search terms based on the real-time index and the contextual cues for a set of candidate content items; determining interestingness of each candidate content item to the user based on social relevance and an interest match of each item to the user; computing a first score for each candidate content item in the set using the model and based upon the interestingness of each candidate content item to the user; computing a threshold based at least in part on an extent of an increase in popularity within a geographic area and quality of content items having a similar subject in the geographic area; determining whether the first score for each candidate content item in the set exceeds the threshold; generating the stream of content in real-time from the set of candidate content items responsive to the first score for each candidate content item in the set exceeding the threshold; and adjusting the threshold based on activities including generating the stream of content. | 1. A method for generating a stream of content for a user in real time, the method comprising: generating a model based on at least one interest of the user and at least one prior action from a group of heterogeneous data sources; receiving a request from the user for a real-time content stream; determining contextual cues surrounding the request including a time of day and a geographic location of the user associated with the request; retrieving fresh content items from the heterogeneous data sources based upon recency; storing and indexing the fresh content items in a real-time index; querying the heterogeneous data sources using search terms based on the real-time index and the contextual cues for a set of candidate content items; determining interestingness of each candidate content item to the user based on social relevance and an interest match of each item to the user; computing a first score for each candidate content item in the set using the model and based upon the interestingness of each candidate content item to the user; computing a threshold based at least in part on an extent of an increase in popularity within a geographic area and quality of content items having a similar subject in the geographic area; determining whether the first score for each candidate content item in the set exceeds the threshold; generating the stream of content in real-time from the set of candidate content items responsive to the first score for each candidate content item in the set exceeding the threshold; and adjusting the threshold based on activities including generating the stream of content. 12. The method of claim 1 , wherein computing the first score for each candidate content item uses geographic information related to at least one candidate content item. | 0.698214 |
7,543,189 | 2 | 3 | 2. A method as claimed in claim 1 wherein the step of determining includes dynamically querying the application program for the support file. | 2. A method as claimed in claim 1 wherein the step of determining includes dynamically querying the application program for the support file. 3. A method as claimed in claim 2 wherein the step of dynamically querying includes: determining the second language from displayed text of the application program; determining the resource name and URL for the second language; and locating support file according to determined resource name and second language. | 0.5 |
5,555,343 | 1 | 5 | 1. A text processor for a text-to-speech converter comprising: a parser for accepting a text stream, for parsing the text stream to detect an unspoken character having a first characteristic, an unspoken character having a second characteristic, and spoken characters, and for not altering the spoken characters in the text stream; a text generator, responsive to detection of an unspoken character having the first characteristic, for generating a pre-designated text sequence, and for replacing, in the text stream, said unspoken character having said first characteristic with said pre-designated text sequence; and a speech command generator, responsive to detection of an unspoken character having a second characteristic, for generating pre-designated speech commands. | 1. A text processor for a text-to-speech converter comprising: a parser for accepting a text stream, for parsing the text stream to detect an unspoken character having a first characteristic, an unspoken character having a second characteristic, and spoken characters, and for not altering the spoken characters in the text stream; a text generator, responsive to detection of an unspoken character having the first characteristic, for generating a pre-designated text sequence, and for replacing, in the text stream, said unspoken character having said first characteristic with said pre-designated text sequence; and a speech command generator, responsive to detection of an unspoken character having a second characteristic, for generating pre-designated speech commands. 5. A text processor according to claim 1, further comprising a look-up table, wherein said text generator generates text in accordance with said look-up table. | 0.670124 |
9,588,679 | 8 | 12 | 8. A method, implemented at a computer system that includes one or more processors, for rendering web page content, the method comprising: creating a layout viewport that identifies a portion of content of a web page that is available for display in a web browser and how the portion of content is to be laid out within the layout viewport, the portion of content including a fixed position user interface element that retains a fixed position within the layout viewport as the portion of content changes due to the layout viewport being scrolled over the content of the web page; creating a visual viewport that overlaps the layout viewport and that renders at least a part of the portion of content identified by the layout viewport, wherein the visual viewport is moveable and sizable within and independent of the layout viewport; and enabling interaction between the visual viewport and the layout viewport, including: rendering the fixed position user interface element based at least on identifying that a size and a position of the visual viewport causes the visual viewport to overlap a portion of the layout viewport containing the fixed position user interface element; subsequent to rendering the fixed position user interface element, detecting a condition in which an overlay user interface is to be displayed; reducing the size of the visual viewport to accommodate a detected size of the overlay user interface; and rendering the overlay user interface instead of the fixed position user interface element, based at least on the reduced the size of the visual viewport causing it to no longer overlap the portion of the layout viewport containing the fixed position user interface element, and based at least on the overlay user interface overlapping the portion of the layout viewport containing the fixed position user interface element. | 8. A method, implemented at a computer system that includes one or more processors, for rendering web page content, the method comprising: creating a layout viewport that identifies a portion of content of a web page that is available for display in a web browser and how the portion of content is to be laid out within the layout viewport, the portion of content including a fixed position user interface element that retains a fixed position within the layout viewport as the portion of content changes due to the layout viewport being scrolled over the content of the web page; creating a visual viewport that overlaps the layout viewport and that renders at least a part of the portion of content identified by the layout viewport, wherein the visual viewport is moveable and sizable within and independent of the layout viewport; and enabling interaction between the visual viewport and the layout viewport, including: rendering the fixed position user interface element based at least on identifying that a size and a position of the visual viewport causes the visual viewport to overlap a portion of the layout viewport containing the fixed position user interface element; subsequent to rendering the fixed position user interface element, detecting a condition in which an overlay user interface is to be displayed; reducing the size of the visual viewport to accommodate a detected size of the overlay user interface; and rendering the overlay user interface instead of the fixed position user interface element, based at least on the reduced the size of the visual viewport causing it to no longer overlap the portion of the layout viewport containing the fixed position user interface element, and based at least on the overlay user interface overlapping the portion of the layout viewport containing the fixed position user interface element. 12. The method of claim 8 , wherein movement of the visual viewport also causes the layout viewport to be moved. | 0.864407 |
8,060,456 | 1 | 2 | 1. One or more processor-accessible tangible media comprising processor-executable instructions for training a search result ranker, wherein the processor-executable instructions, when executed, direct a system to perform acts comprising: inferring user interests from user interactions with search results for a particular query, the search results including identifiers that comprise uniform resource locators (URLs); determining respective relevance scores associated with respective query-identifier pairs of the search results, each respective relevance score comprising a respective probability of the respective identifier being skipped by a user; formulating query-identifier-relevance score triplets from the respective relevance scores associated with the respective query-identifier pairs; submitting the query-identifier-relevance score triplets as training samples to a search result ranker; and training the search result ranker as a learning machine with multiple training samples comprising the query-identifier-relevance score triplets. | 1. One or more processor-accessible tangible media comprising processor-executable instructions for training a search result ranker, wherein the processor-executable instructions, when executed, direct a system to perform acts comprising: inferring user interests from user interactions with search results for a particular query, the search results including identifiers that comprise uniform resource locators (URLs); determining respective relevance scores associated with respective query-identifier pairs of the search results, each respective relevance score comprising a respective probability of the respective identifier being skipped by a user; formulating query-identifier-relevance score triplets from the respective relevance scores associated with the respective query-identifier pairs; submitting the query-identifier-relevance score triplets as training samples to a search result ranker; and training the search result ranker as a learning machine with multiple training samples comprising the query-identifier-relevance score triplets. 2. The one or more processor-accessible tangible media as recited in claim 1 , wherein the user interactions comprise one or more of: identifier selection, dwell time on an item corresponding to a selected identifier, viewing of an identifier of a search result, or skipping an identifier of a search result. | 0.5 |
9,241,223 | 6 | 8 | 6. The method of claim 1 , further comprising converting the composite audible signal data into a plurality of time-frequency units, wherein the time dimension of each time-frequency unit includes at least one of a plurality of time intervals, and wherein the frequency dimension of each time-frequency unit includes at least one of a plurality of sub-bands. | 6. The method of claim 1 , further comprising converting the composite audible signal data into a plurality of time-frequency units, wherein the time dimension of each time-frequency unit includes at least one of a plurality of time intervals, and wherein the frequency dimension of each time-frequency unit includes at least one of a plurality of sub-bands. 8. The method of claim 6 , wherein converting the composite audible signal data into the plurality of time-frequency units includes applying a Fast Fourier Transform to one or more of the respective audible signal data components. | 0.760417 |
8,527,584 | 5 | 6 | 5. A method of claim 2 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following: at least one determination that the first and second recommendation models include at least one token-based recommendation model and at least one collaborative recommendation model; user account information, user profile information, user context information, or a combination thereof associated with the device, the first deployment, the second deployment, a central server associated with the service, or a combination thereof; and a processing of the user account information, the user profile information, the user context information, or a combination thereof to determine at least one user collaborative model for use with the at least one collaborative recommendation model. | 5. A method of claim 2 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following: at least one determination that the first and second recommendation models include at least one token-based recommendation model and at least one collaborative recommendation model; user account information, user profile information, user context information, or a combination thereof associated with the device, the first deployment, the second deployment, a central server associated with the service, or a combination thereof; and a processing of the user account information, the user profile information, the user context information, or a combination thereof to determine at least one user collaborative model for use with the at least one collaborative recommendation model. 6. A method of claim 5 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following: a processing of one or more user tokens from the at least one token-based recommendation model for comparison against one or more other tokens associated with one or more other collaborative recommendation models; and a selection of the at least one user collaborative recommendation model from among the one or more other collaborative recommendation models based, at least in part, on the comparison. | 0.5 |
10,013,729 | 16 | 19 | 16. A computer system comprising: a computer processor; a non-transitory computer readable storage medium, storing instructions program product comprising a non-transitory computer-readable storage medium storing instructions for: storing a plurality of events and user interactions performed by users of a social networking system with the plurality of events; associating a set of events of the plurality of events with a category; selecting a set of users associated with the set of events, comprising, for each event from the set of events: identifying users performing user interactions with the event, for each identified user, determining a measure of user interactions of the user with the event, wherein the measure of user interactions of the user with the event is based on a frequency of interaction of the user with the event, and including the user in the set of users, responsive to the measure of user interactions of the user with the event exceeding a threshold; selecting a set of candidate events associated with the set of users, based on user interactions of users from the set of users with the candidate events determining whether each candidate event is associated with the category based on keyword occurrences in content associated with each candidate event; and providing information describing a particular event to a user for performing an action, the information provided based on the category. | 16. A computer system comprising: a computer processor; a non-transitory computer readable storage medium, storing instructions program product comprising a non-transitory computer-readable storage medium storing instructions for: storing a plurality of events and user interactions performed by users of a social networking system with the plurality of events; associating a set of events of the plurality of events with a category; selecting a set of users associated with the set of events, comprising, for each event from the set of events: identifying users performing user interactions with the event, for each identified user, determining a measure of user interactions of the user with the event, wherein the measure of user interactions of the user with the event is based on a frequency of interaction of the user with the event, and including the user in the set of users, responsive to the measure of user interactions of the user with the event exceeding a threshold; selecting a set of candidate events associated with the set of users, based on user interactions of users from the set of users with the candidate events determining whether each candidate event is associated with the category based on keyword occurrences in content associated with each candidate event; and providing information describing a particular event to a user for performing an action, the information provided based on the category. 19. The computer system of claim 16 , wherein an interaction of a user with an event comprises one or more of the user indicating via an RSVP message whether the user will be attending the event, the user posting information related to the event, the user retrieving a time and location of the event, and the user posting a comment on the event. | 0.5 |
8,726,256 | 21 | 22 | 21. A computer comprising: a memory having software stored thereon; and a processor communicatively coupled to the memory, wherein the software, when executed by the processor, causes the processor to: convert a quantification into an automaton, wherein convert includes unroll the quantification to control an in-degree or an out-degree of the automaton; and convert the automaton into machine code corresponding to a target device. | 21. A computer comprising: a memory having software stored thereon; and a processor communicatively coupled to the memory, wherein the software, when executed by the processor, causes the processor to: convert a quantification into an automaton, wherein convert includes unroll the quantification to control an in-degree or an out-degree of the automaton; and convert the automaton into machine code corresponding to a target device. 22. The computer of claim 21 , wherein the software causes the processor to control the in-degree and out-degree by trading off in-transitions for out-transitions in the automaton. | 0.5 |
8,768,885 | 19 | 20 | 19. A server comprising: a non-transitory machine-readable medium to store an electronic document that is edit accessible by a plurality of users from client devices communicatively coupled to the server; and a control module to provide the electronic document for presentation to a user of the plurality of users that have edit access to the electronic document as part of a collaborative editing of the electronic document, to invoke a lock to prevent edit access by other users of the multiple users of the electronic document in response to the receiving of an input from the device of the user to edit the electronic document that prevents edit access by other users of the plurality of users that have edit access to the electronic document, to send a save confirmation to the device of the user based on saving content provided by the device; and to receive a release from the device of the user in response to the device receiving the save confirmation. | 19. A server comprising: a non-transitory machine-readable medium to store an electronic document that is edit accessible by a plurality of users from client devices communicatively coupled to the server; and a control module to provide the electronic document for presentation to a user of the plurality of users that have edit access to the electronic document as part of a collaborative editing of the electronic document, to invoke a lock to prevent edit access by other users of the multiple users of the electronic document in response to the receiving of an input from the device of the user to edit the electronic document that prevents edit access by other users of the plurality of users that have edit access to the electronic document, to send a save confirmation to the device of the user based on saving content provided by the device; and to receive a release from the device of the user in response to the device receiving the save confirmation. 20. The server of claim 19 , wherein the control module further comprises transmitting a release command to devices of the other users of the plurality of user based on the received release from the device of the user. | 0.5 |
7,945,600 | 13 | 14 | 13. A system comprising: a memory configured to store a plurality of electronic documents; and a processor; wherein the processor is configured to: generate a summary representation of each electronic document in the plurality of electronic documents, the summary representation representing a summary of content of the electronic document; filter the plurality of electronic documents based upon their summary representations to generate a filtered subset; organize the electronic documents in the filtered subset into a hierarchical collection of folders, the organizing comprising: determining similarity metrics between the electronic documents in the filtered subset based upon their summary representations; determining concepts associated with the electronic documents in the filtered subset based upon their summary representations; and grouping the electronic documents in the filtered subset into the hierarchical collection of folders based upon the similarity metrics and the concepts; and assign, based upon a set of rules pertaining to document similarity, a number to each electronic document in the filtered subset by traversing the hierarchical collection of folders, such that when the electronic documents in the filtered subset are sorted based upon the assigned numbers to generate a sorted list of electronic documents, related electronic documents occur consecutively in the sorted list of electronic documents. | 13. A system comprising: a memory configured to store a plurality of electronic documents; and a processor; wherein the processor is configured to: generate a summary representation of each electronic document in the plurality of electronic documents, the summary representation representing a summary of content of the electronic document; filter the plurality of electronic documents based upon their summary representations to generate a filtered subset; organize the electronic documents in the filtered subset into a hierarchical collection of folders, the organizing comprising: determining similarity metrics between the electronic documents in the filtered subset based upon their summary representations; determining concepts associated with the electronic documents in the filtered subset based upon their summary representations; and grouping the electronic documents in the filtered subset into the hierarchical collection of folders based upon the similarity metrics and the concepts; and assign, based upon a set of rules pertaining to document similarity, a number to each electronic document in the filtered subset by traversing the hierarchical collection of folders, such that when the electronic documents in the filtered subset are sorted based upon the assigned numbers to generate a sorted list of electronic documents, related electronic documents occur consecutively in the sorted list of electronic documents. 14. The system of claim 13 further comprising an output device, wherein the processor is configured to: display a graphical user interface (GUI) on the output device to facilitate review of the electronic documents in the filtered subset, the GUI comprising: a first region displaying the hierarchical collection of folders; a second region displaying a list of electronic documents grouped in a selected folder from the hierarchical collection of folders; a third region displaying a first electronic document selected from the list of electronic documents. | 0.571429 |
8,879,695 | 6 | 11 | 6. The system of claim 5 , wherein transcribing of the message comprises use of a set of transcription rules, wherein the transcription rules comprise a set of transcription exceptions. | 6. The system of claim 5 , wherein transcribing of the message comprises use of a set of transcription rules, wherein the transcription rules comprise a set of transcription exceptions. 11. The system of claim 6 , wherein the set of transcription rules is associated with the class of service of the subscriber. | 0.537037 |
8,265,991 | 19 | 21 | 19. A computer readable medium storing a computer program which when executed places an online purchase order, the computer program for execution by a client device from which the purchase order originates, the computer program comprising: a set of instructions for downloading, at the client device, programming instructions for determining applicability of a discount type for the purchase order, the programming instructions being downloaded from a set of server computers connected to the client device through a network; a set of instructions for executing said downloaded programming instructions to determine the applicability of the discount type to the purchase order such that for multiple changes to the purchase order said programming instructions are executed at the client device multiple times to determine the applicability of the discount type without requiring new programming instructions to be downloaded through the network, said determining automatically done without human intervention and without downloading further instructions from the set of server computers; a set of instructions for receiving changes to the purchase order; a set of instructions for executing said downloaded programming instructions to determine the applicability of the discount type to the changed purchase order without downloading new programming instructions through the network; and a set of instructions for placing the online purchase order to the set of server computers through the network in accordance with the applicability of the discount type determined at the client device. | 19. A computer readable medium storing a computer program which when executed places an online purchase order, the computer program for execution by a client device from which the purchase order originates, the computer program comprising: a set of instructions for downloading, at the client device, programming instructions for determining applicability of a discount type for the purchase order, the programming instructions being downloaded from a set of server computers connected to the client device through a network; a set of instructions for executing said downloaded programming instructions to determine the applicability of the discount type to the purchase order such that for multiple changes to the purchase order said programming instructions are executed at the client device multiple times to determine the applicability of the discount type without requiring new programming instructions to be downloaded through the network, said determining automatically done without human intervention and without downloading further instructions from the set of server computers; a set of instructions for receiving changes to the purchase order; a set of instructions for executing said downloaded programming instructions to determine the applicability of the discount type to the changed purchase order without downloading new programming instructions through the network; and a set of instructions for placing the online purchase order to the set of server computers through the network in accordance with the applicability of the discount type determined at the client device. 21. The computer readable medium of claim 19 , wherein: the programming instructions comprise a rule engine implemented by rule programming, the rule engine comprising a set of rules and a processing relationship between a plurality of rules in the set of rules; and executing the downloaded programming instructions comprises applying the rule engine to product and order information associated with the purchase order to determine applicability of the discount type and to determine a discount value when the discount type is applicable to the order. | 0.5 |
10,108,612 | 11 | 20 | 11. A method for translating text on an electronic device, comprising: at the electronic device having a touch sensitive screen: receiving a first text of a first language entered via a first virtual keyboard on the touch sensitive screen, the first virtual keyboard comprising characters of the first language; in response to detecting a change in physical orientation of the electronic device from a first orientation to a second orientation: causing translation of the first text to a first translated text of a second language, and displaying, on the touch sensitive screen, the first translated text and a second virtual keyboard comprising characters of the second language; receiving a second text of the second language entered via the second virtual keyboard on the touch sensitive screen; and in response to detecting a change in the physical orientation of the electronic device from the second orientation back to the first orientation: causing translation of the second text to a second translated text of the first language, and displaying, on the touch sensitive screen, the second translated text and the first virtual keyboard. | 11. A method for translating text on an electronic device, comprising: at the electronic device having a touch sensitive screen: receiving a first text of a first language entered via a first virtual keyboard on the touch sensitive screen, the first virtual keyboard comprising characters of the first language; in response to detecting a change in physical orientation of the electronic device from a first orientation to a second orientation: causing translation of the first text to a first translated text of a second language, and displaying, on the touch sensitive screen, the first translated text and a second virtual keyboard comprising characters of the second language; receiving a second text of the second language entered via the second virtual keyboard on the touch sensitive screen; and in response to detecting a change in the physical orientation of the electronic device from the second orientation back to the first orientation: causing translation of the second text to a second translated text of the first language, and displaying, on the touch sensitive screen, the second translated text and the first virtual keyboard. 20. The method of claim 11 , further comprising: in response to detecting the change in the physical orientation of the electronic device from the first orientation to the second orientation, displaying a prompt for a user to select any one of a plurality of languages to which the first text is to be translated. | 0.838493 |
9,621,578 | 26 | 27 | 26. A non-transitory computer-readable storage medium having computer-executable instructions which, when executed by one or more computer processors, causes the one or more computer processors to detect a network activity of interest, the computer-executable instructions comprising instructions for: (a) obtaining a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; (b) creating a combined packet from at least two network packets of the plurality of network packets, wherein creating the combined packet comprises converting, bitwise, content from a portion of a first network packet and a portion of a second network packet into a plurality of integers, wherein the first network packet represents a communication from a first node to a second node, and wherein the second network packet represents a communication from the second node to the first node; (c) obtaining a meta-expression that: comprises a plurality of integers in an order, and corresponds to presence of the network activity of interest in network traffic; determining whether the meta-expression obtained in (c) appears in the combined packet created in (b); and initiating an operation based in response to determining that the meta-expressions obtained in (c) appears in the combined packet created in (b). | 26. A non-transitory computer-readable storage medium having computer-executable instructions which, when executed by one or more computer processors, causes the one or more computer processors to detect a network activity of interest, the computer-executable instructions comprising instructions for: (a) obtaining a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; (b) creating a combined packet from at least two network packets of the plurality of network packets, wherein creating the combined packet comprises converting, bitwise, content from a portion of a first network packet and a portion of a second network packet into a plurality of integers, wherein the first network packet represents a communication from a first node to a second node, and wherein the second network packet represents a communication from the second node to the first node; (c) obtaining a meta-expression that: comprises a plurality of integers in an order, and corresponds to presence of the network activity of interest in network traffic; determining whether the meta-expression obtained in (c) appears in the combined packet created in (b); and initiating an operation based in response to determining that the meta-expressions obtained in (c) appears in the combined packet created in (b). 27. The non-transitory computer-readable medium of claim 26 , wherein the determining comprises: determining whether the plurality of integers, which are ordered, of the meta-expression obtained in (c) appear in the combined packet created in (b) in the same order. | 0.818244 |
6,052,657 | 1 | 11 | 1. A method for segmenting a stream of text into segments using a plurality of language models, the stream of text including a sequence of blocks of text, the method comprising: scoring the blocks of text against the language models to generate language model scores for the blocks of text, the language model score for a block of text against a language model indicating a correlation between the block of text and the language model; generating language model sequence scores for different sequences of language models to which a sequence of blocks of text may correspond, a language model sequence score being a function of the scores of a sequence of blocks of text against a sequence of language models; selecting a sequence of language models that satisfies a predetermined condition; and identifying segment boundaries in the stream of text that correspond to language model transitions in the selected sequence of language models. | 1. A method for segmenting a stream of text into segments using a plurality of language models, the stream of text including a sequence of blocks of text, the method comprising: scoring the blocks of text against the language models to generate language model scores for the blocks of text, the language model score for a block of text against a language model indicating a correlation between the block of text and the language model; generating language model sequence scores for different sequences of language models to which a sequence of blocks of text may correspond, a language model sequence score being a function of the scores of a sequence of blocks of text against a sequence of language models; selecting a sequence of language models that satisfies a predetermined condition; and identifying segment boundaries in the stream of text that correspond to language model transitions in the selected sequence of language models. 11. The method of claim 1, wherein a block of text comprises a paragraph. | 0.894203 |
9,600,616 | 3 | 4 | 3. The computer-implemented method of claim 2 wherein generating the simulation and the formal model based on the driver further comprises: generating one of a model for formal. | 3. The computer-implemented method of claim 2 wherein generating the simulation and the formal model based on the driver further comprises: generating one of a model for formal. 4. The computer-implemented method of claim 3 , further comprising generating an assertion for formal. | 0.5 |
7,680,857 | 17 | 19 | 17. A method in a help system for providing help information to a user, the method comprising: providing a help file that includes an entry for each topic, each entry having a title, content, and some of the entries having data derived from failed user queries, a user query being a query submitted by a user for searching the help file to identify topics relevant to the user query and a failed user query being a user query in which the identified topics after being presented to the user were considered to be not relevant to the user query; receiving a user query; and searching the provided help file for a topic that matches the received user query, a match determined based at least in part on a comparison of the received user query to the data derived from failed user queries so that a topic that would not be identified as being relevant to the received user based on the title and the content of the topic is identified as being relevant based on the data of the topic derived from the failed user queries. | 17. A method in a help system for providing help information to a user, the method comprising: providing a help file that includes an entry for each topic, each entry having a title, content, and some of the entries having data derived from failed user queries, a user query being a query submitted by a user for searching the help file to identify topics relevant to the user query and a failed user query being a user query in which the identified topics after being presented to the user were considered to be not relevant to the user query; receiving a user query; and searching the provided help file for a topic that matches the received user query, a match determined based at least in part on a comparison of the received user query to the data derived from failed user queries so that a topic that would not be identified as being relevant to the received user based on the title and the content of the topic is identified as being relevant based on the data of the topic derived from the failed user queries. 19. The method of claim 17 wherein the data derived from the failed user queries includes the failed user queries. | 0.734884 |
9,323,811 | 8 | 10 | 8. One or more computer-readable hardware storage device having embedded therein a set of instructions which, when executed by one or more processors of a computer, causes the computer to execute operations comprising: receiving a user query; obtaining analysis of a query log of user query sessions on a publication system, wherein the user query sessions comprise a plurality of high frequency queries and low frequency queries, query transitions and purchase-related events; based on the user query, generating by at least one computer processor, from the analysis of the query log, a set of transition scores comprising transition scores for ordered pairs of high frequency queries and low frequency queries, based on transition from a query of an ordered pair of queries to a purchase-related event of the ordered pair of queries; building a set of query suggestions for high frequency queries from the transition scores by a score accumulation process; determining whether the transition score for at least one member of the set of query suggestions meets a predetermined confidence threshold; providing to a client machine, in response to the received user query, a list of query suggestions for high frequency queries that have transition scores that meet the predetermined confidence threshold; generating, from the analysis, similarity metrics for suggestions for low frequency queries; determining whether the similarity metric for a suggestion for a low frequency query meets a predetermined similarity metric; and providing to a client machine, in response to the received user query, a list of low frequency query suggestions having metrics that meet the predetermined similarity metric but do not meet the predetermined confidence threshold. | 8. One or more computer-readable hardware storage device having embedded therein a set of instructions which, when executed by one or more processors of a computer, causes the computer to execute operations comprising: receiving a user query; obtaining analysis of a query log of user query sessions on a publication system, wherein the user query sessions comprise a plurality of high frequency queries and low frequency queries, query transitions and purchase-related events; based on the user query, generating by at least one computer processor, from the analysis of the query log, a set of transition scores comprising transition scores for ordered pairs of high frequency queries and low frequency queries, based on transition from a query of an ordered pair of queries to a purchase-related event of the ordered pair of queries; building a set of query suggestions for high frequency queries from the transition scores by a score accumulation process; determining whether the transition score for at least one member of the set of query suggestions meets a predetermined confidence threshold; providing to a client machine, in response to the received user query, a list of query suggestions for high frequency queries that have transition scores that meet the predetermined confidence threshold; generating, from the analysis, similarity metrics for suggestions for low frequency queries; determining whether the similarity metric for a suggestion for a low frequency query meets a predetermined similarity metric; and providing to a client machine, in response to the received user query, a list of low frequency query suggestions having metrics that meet the predetermined similarity metric but do not meet the predetermined confidence threshold. 10. The one or more hardware storage device of claim 8 , the operations further comprising mixing and ranking the set of query suggestions in accordance with a user behavior that is to be influenced. | 0.631481 |
9,715,548 | 1 | 2 | 1. A computer-implemented method executed by one or more processors, the method comprising: receiving, by the one or more processors, a search query, the search query being provided by a user; receiving, by the one or more processors, one or more search results that are responsive to the search query, the one or more search results being respectively representative of one or more resources; processing, by the one or more processors, one or more triggering rules based on at least one of the search query and the search results, a triggering rule defining a set of conditions where, if each condition is true, at least one user-specific data record is to be displayed with the one or more search results; determining, based on processing the one or more triggering rules, that a set of user-specific data records is to be displayed in a search results page with the search results, the set of user-specific data records comprising one or more user-specific data records that are specific to the user that provided the search query, and the set of user-specific data records is provided based on a plurality of data records stored in a data repository; determining a display prominence of at least one user-specific data record in the set of user-specific data records, the display prominence comprising one of a plurality of locations within the search results page, and indicating a prominence of the at least one user-specific data record when displayed in the search results page, at least one location being within a search results pane, within which the one or more search results are also displayed, wherein determining display prominence comprises: determining that a user-specific data record specifies an event that occurs in the future relative to a time that the query was submitted, and a time of the event; determining a time difference based on the time of the event specified by the user-specific data record and the time the query was submitted; if the time difference meets a threshold time difference, setting the display prominence to a first value in response that indicates the data record is not to be prominently displayed; and if the time difference does not meet the threshold time difference, setting the display prominence set to a second value that indicates the data record is to be prominently displayed; and providing the search results and the set of user-specific data records for display, the at least one user-specific data record being displayed based on the display prominence. | 1. A computer-implemented method executed by one or more processors, the method comprising: receiving, by the one or more processors, a search query, the search query being provided by a user; receiving, by the one or more processors, one or more search results that are responsive to the search query, the one or more search results being respectively representative of one or more resources; processing, by the one or more processors, one or more triggering rules based on at least one of the search query and the search results, a triggering rule defining a set of conditions where, if each condition is true, at least one user-specific data record is to be displayed with the one or more search results; determining, based on processing the one or more triggering rules, that a set of user-specific data records is to be displayed in a search results page with the search results, the set of user-specific data records comprising one or more user-specific data records that are specific to the user that provided the search query, and the set of user-specific data records is provided based on a plurality of data records stored in a data repository; determining a display prominence of at least one user-specific data record in the set of user-specific data records, the display prominence comprising one of a plurality of locations within the search results page, and indicating a prominence of the at least one user-specific data record when displayed in the search results page, at least one location being within a search results pane, within which the one or more search results are also displayed, wherein determining display prominence comprises: determining that a user-specific data record specifies an event that occurs in the future relative to a time that the query was submitted, and a time of the event; determining a time difference based on the time of the event specified by the user-specific data record and the time the query was submitted; if the time difference meets a threshold time difference, setting the display prominence to a first value in response that indicates the data record is not to be prominently displayed; and if the time difference does not meet the threshold time difference, setting the display prominence set to a second value that indicates the data record is to be prominently displayed; and providing the search results and the set of user-specific data records for display, the at least one user-specific data record being displayed based on the display prominence. 2. The computer-implemented method of claim 1 , wherein the display prominence indicates a position of the at least one user-specific data record within the search results page. | 0.784146 |
5,555,343 | 80 | 81 | 80. Apparatus for converting text into speech comprising: a memory for storing plural format templates, each of said plural format templates having both format data and at least one wild card field, said memory also storing pre-designated text which corresponds to format data for each format template; a parser for parsing a text stream to determine whether a character string in the text stream matches one of the plural format templates, for parsing the text stream to detect spoken characters, and for not altering the spoken characters in the text stream; a text generator responsive to a determination by said parser that a character string in the text stream matches one of the plural templates by replacing, the text stream, format data from the character string which matches format data from said one of the plural templates with corresponding pre-designated text, said text generator leaving unaltered text in the character string corresponding to each wild card field; and a text-to-speech converter for converting the text stream, including the replaced pre-designated text and the unaltered text, into speech. | 80. Apparatus for converting text into speech comprising: a memory for storing plural format templates, each of said plural format templates having both format data and at least one wild card field, said memory also storing pre-designated text which corresponds to format data for each format template; a parser for parsing a text stream to determine whether a character string in the text stream matches one of the plural format templates, for parsing the text stream to detect spoken characters, and for not altering the spoken characters in the text stream; a text generator responsive to a determination by said parser that a character string in the text stream matches one of the plural templates by replacing, the text stream, format data from the character string which matches format data from said one of the plural templates with corresponding pre-designated text, said text generator leaving unaltered text in the character string corresponding to each wild card field; and a text-to-speech converter for converting the text stream, including the replaced pre-designated text and the unaltered text, into speech. 81. Apparatus according to claim 80, further comprising a speech command generator, and wherein said memory also stores speech commands associated with said pre-designated text, said speech command generator generating pre-designated speech commands in response to a matching character string. | 0.5 |
8,478,584 | 1 | 2 | 1. A method for performing a task in a natural language processing (NLP) system, comprising: processing text to obtain a plurality of numerical encodings, wherein the text comprises a plurality of entities, wherein each of the plurality of numerical encodings is associated with one of the plurality of entities, and wherein the text is derived from an utterance; populating a task list with each of the plurality of numerical encodings that have a length less than a pre-determined length; populating a variable list with each of the plurality of numerical encodings that have a length greater than a pre-determined length; selecting a numerical encoding from the task list, wherein the numerical encoding identifies a task in a domain-specific schema; determining that the variable list does not include a variable value required to perform the task; generating a sentence to obtain the variable value associated with a variable, wherein the variable is associated with a second numerical encoding, and wherein the second numerical encoding includes the numerical encoding; transmitting the sentence to a user device; in response to the transmitting, receiving the variable value for the variable in response to the dialogue sentence; and performing the task using the variable value. | 1. A method for performing a task in a natural language processing (NLP) system, comprising: processing text to obtain a plurality of numerical encodings, wherein the text comprises a plurality of entities, wherein each of the plurality of numerical encodings is associated with one of the plurality of entities, and wherein the text is derived from an utterance; populating a task list with each of the plurality of numerical encodings that have a length less than a pre-determined length; populating a variable list with each of the plurality of numerical encodings that have a length greater than a pre-determined length; selecting a numerical encoding from the task list, wherein the numerical encoding identifies a task in a domain-specific schema; determining that the variable list does not include a variable value required to perform the task; generating a sentence to obtain the variable value associated with a variable, wherein the variable is associated with a second numerical encoding, and wherein the second numerical encoding includes the numerical encoding; transmitting the sentence to a user device; in response to the transmitting, receiving the variable value for the variable in response to the dialogue sentence; and performing the task using the variable value. 2. The method of claim 1 , further comprising: receiving user audio packets comprising the utterance from the user device; and converting the user audio packets to text. | 0.743939 |
7,603,267 | 10 | 16 | 10. A computer-implemented method of training a natural language understanding (NLU) model, comprising: obtaining a schema indicative of a task to be completed, the schema including a plurality of slots and a plurality of preterminals, wherein each of the plurality of slots is configured to be filled with terms from a natural language input that are associated with the task, and wherein each of the preterminals comprises at least one of a preamble and postamble associated with one or more of the slots, the preterminals being configured to be filled with portions of the natural language input; generating a plurality of segmentations of training data, for the plurality of slots and the plurality of preterminals from the schema, wherein generating a plurality of segmentations comprises associating one or more of the slots and one or more of the preterminals with portions of the training data; training a plurality of statistical models using a processor for selected preterminals of the plurality of preterminals corresponding to at least one of the segmentations, wherein the plurality of statistical models are configured to map terms from the natural language input to the selected preterminals, wherein training the plurality of statistical models comprises generating a statistical model for each of the plurality of selected preterminals comprising: selecting a first preterminal; generating a first statistical model for the selected first preterminal using the portion of the training data associated with the selected first preterminal as training data for the first statistical model; selecting a second preterminal; and generating a second statistical model for the selected second preterminal using the portion of the training data associated with the selected second preterminal as training data for the second statistical model; and training a rules based grammar using a processor for a selected slot of the plurality of slots corresponding to at least one of the segmentations, wherein the rules based grammar is configured to be used to map terms from the natural language input to the selected slot. | 10. A computer-implemented method of training a natural language understanding (NLU) model, comprising: obtaining a schema indicative of a task to be completed, the schema including a plurality of slots and a plurality of preterminals, wherein each of the plurality of slots is configured to be filled with terms from a natural language input that are associated with the task, and wherein each of the preterminals comprises at least one of a preamble and postamble associated with one or more of the slots, the preterminals being configured to be filled with portions of the natural language input; generating a plurality of segmentations of training data, for the plurality of slots and the plurality of preterminals from the schema, wherein generating a plurality of segmentations comprises associating one or more of the slots and one or more of the preterminals with portions of the training data; training a plurality of statistical models using a processor for selected preterminals of the plurality of preterminals corresponding to at least one of the segmentations, wherein the plurality of statistical models are configured to map terms from the natural language input to the selected preterminals, wherein training the plurality of statistical models comprises generating a statistical model for each of the plurality of selected preterminals comprising: selecting a first preterminal; generating a first statistical model for the selected first preterminal using the portion of the training data associated with the selected first preterminal as training data for the first statistical model; selecting a second preterminal; and generating a second statistical model for the selected second preterminal using the portion of the training data associated with the selected second preterminal as training data for the second statistical model; and training a rules based grammar using a processor for a selected slot of the plurality of slots corresponding to at least one of the segmentations, wherein the rules based grammar is configured to be used to map terms from the natural language input to the selected slot. 16. The method of claim 10 wherein the training data comprises semantically annotated training data and further comprising: accessing a probabilistic library grammar; and adapting probabilities in the probabilistic library grammar based on the semantically annotated training data. | 0.809878 |
8,290,963 | 19 | 21 | 19. An article comprising one or more computer-readable data storage media storing program code operable to cause one or more machines to perform operations, the operations comprising: identifying, in a machine-readable index, a first sentence fragment and a second sentence fragment that are both associated with a same first information item, wherein the first information item is a concept, wherein the machine-readable index comprises a plurality of information items and sentence fragments associated with respective of the information items; in response to identifying that the first sentence fragment and the second sentence fragment are both associated with a same first information item, identifying a paraphrase pair in the first and second sentence fragments; repeating the identifying of the first sentence fragment and the second sentence fragment and the identifying of the paraphrase pair to identify a plurality of paraphrase pairs; and determining a frequency of occurrence value for each of the paraphrase pairs in the plurality of paraphrase pairs, wherein the frequency of occurrence value embodies the frequency at which each paraphrase pair appears in the plurality of paraphrase pairs, wherein the paraphrase pair comprises a first paraphrase and a second paraphrase, the first paraphrase comprises a proper subset of the words in the first sentence fragment, the second paraphrase comprises a proper subset of the words in the second sentence fragment, and the first paraphrase and the second paraphrase are in a same language, have a same or a similar meaning, and are not identical. | 19. An article comprising one or more computer-readable data storage media storing program code operable to cause one or more machines to perform operations, the operations comprising: identifying, in a machine-readable index, a first sentence fragment and a second sentence fragment that are both associated with a same first information item, wherein the first information item is a concept, wherein the machine-readable index comprises a plurality of information items and sentence fragments associated with respective of the information items; in response to identifying that the first sentence fragment and the second sentence fragment are both associated with a same first information item, identifying a paraphrase pair in the first and second sentence fragments; repeating the identifying of the first sentence fragment and the second sentence fragment and the identifying of the paraphrase pair to identify a plurality of paraphrase pairs; and determining a frequency of occurrence value for each of the paraphrase pairs in the plurality of paraphrase pairs, wherein the frequency of occurrence value embodies the frequency at which each paraphrase pair appears in the plurality of paraphrase pairs, wherein the paraphrase pair comprises a first paraphrase and a second paraphrase, the first paraphrase comprises a proper subset of the words in the first sentence fragment, the second paraphrase comprises a proper subset of the words in the second sentence fragment, and the first paraphrase and the second paraphrase are in a same language, have a same or a similar meaning, and are not identical. 21. The article of claim 19 , further comprising: identifying, by the system, a subset of the plurality of paraphrase pairs having a frequency of occurrence value above a threshold; and adding, by the system, the subset of the plurality of paraphrase pairs to a machine-readable data collection. | 0.728361 |
9,443,511 | 73 | 84 | 73. A non-transitory computer-readable medium comprising instructions for recognizing an input environmental sound at a server, the instructions causing a processor to perform operations comprising: if a confidence level determined by a client device and associated with a first label associated with an input environmental sound received at the client device is less than a first confidence threshold: accessing a server database including a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; receiving, from the client device, an input sound model representing the input environmental sound; determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; selecting a second label from one or more labels, of the plurality of labels, associated with the one or more sound models; associating the second label with the input environmental sound based on a confidence level of the second label; and sending the second label or an indication of a failure in recognizing the input environmental sound to the client device based on the confidence level of the second label. | 73. A non-transitory computer-readable medium comprising instructions for recognizing an input environmental sound at a server, the instructions causing a processor to perform operations comprising: if a confidence level determined by a client device and associated with a first label associated with an input environmental sound received at the client device is less than a first confidence threshold: accessing a server database including a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; receiving, from the client device, an input sound model representing the input environmental sound; determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; selecting a second label from one or more labels, of the plurality of labels, associated with the one or more sound models; associating the second label with the input environmental sound based on a confidence level of the second label; and sending the second label or an indication of a failure in recognizing the input environmental sound to the client device based on the confidence level of the second label. 84. The non-transitory computer-readable medium of claim 73 , wherein selecting the second label comprises: grouping the one or more sound models into one or more sets of sound models based on the one or more labels; calculating a sum of the similarity values of sound models in each of the one or more sets to determine a largest sum; and selecting a particular label associated with a set of the one or more sets having the largest sum. | 0.5 |
8,712,774 | 21 | 23 | 21. A system for creating a text string, the system comprising: an initialization component configured to: receive a first time-indexed text string generated from an audio input by a first automated speech recognition system; receive a second time-indexed text string generated from the audio input by a second automated speech recognition system; and correlate the first and second time-indexed text strings based at least in part on a comparison between the first and second time-indexed text strings to compensate for time difference between the first and second time-indexed text strings; and a string generation component configured to: create an improved text string, wherein the improved text string is generated from a comparison between the first and second time-indexed text strings, and wherein the improved text string includes at least one word that matches between the first time-indexed text string and the second time-indexed text string. | 21. A system for creating a text string, the system comprising: an initialization component configured to: receive a first time-indexed text string generated from an audio input by a first automated speech recognition system; receive a second time-indexed text string generated from the audio input by a second automated speech recognition system; and correlate the first and second time-indexed text strings based at least in part on a comparison between the first and second time-indexed text strings to compensate for time difference between the first and second time-indexed text strings; and a string generation component configured to: create an improved text string, wherein the improved text string is generated from a comparison between the first and second time-indexed text strings, and wherein the improved text string includes at least one word that matches between the first time-indexed text string and the second time-indexed text string. 23. The method of claim 21 , wherein the first automated speech recognition system and the second automated speech recognition system comprise different automated speech recognition systems. | 0.713855 |
8,849,034 | 19 | 20 | 19. A method comprising: drawing one or more strokes of a current desired character using a stylus on a current handwriting task area in a touch screen, wherein one of the drawn one or more strokes is a head-line stroke and is a last drawn stroke of the current desired character; inputting an associated data of the one or more strokes via the touch screen into a handwriting recognition engine; computing stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope; determining a trigger stroke in the drawn one or more strokes of the current desired character that can be used to trigger character recognition based as a function of the computed stroke recognition characteristics of each of the drawn one or more strokes, wherein the trigger stroke is the head-line stroke which is drawn substantially parallel to the horizontal reference line; and triggering character recognition for the drawn current desired character by the handwriting recognition engine upon determining the trigger stroke. | 19. A method comprising: drawing one or more strokes of a current desired character using a stylus on a current handwriting task area in a touch screen, wherein one of the drawn one or more strokes is a head-line stroke and is a last drawn stroke of the current desired character; inputting an associated data of the one or more strokes via the touch screen into a handwriting recognition engine; computing stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope; determining a trigger stroke in the drawn one or more strokes of the current desired character that can be used to trigger character recognition based as a function of the computed stroke recognition characteristics of each of the drawn one or more strokes, wherein the trigger stroke is the head-line stroke which is drawn substantially parallel to the horizontal reference line; and triggering character recognition for the drawn current desired character by the handwriting recognition engine upon determining the trigger stroke. 20. The method of claim 19 , further comprising: producing a current candidate character upon triggering the character recognition by the handwriting recognition engine in the current handwriting task area; and displaying the current candidate character in the current handwriting task area. | 0.580692 |
8,214,736 | 40 | 41 | 40. The method of claim 37 , wherein a plurality of changes in page break position are recorded. | 40. The method of claim 37 , wherein a plurality of changes in page break position are recorded. 41. The method of claim 40 , wherein the sub-portion of the document's text is chosen from said plurality of recorded changes in page break positions. | 0.5 |
9,460,089 | 18 | 19 | 18. A method comprising: receiving, via a processing device, an electronic document having base characters, ruby characters, and markings comprising metadata instructions indicating how to render groups of ruby characters, wherein the markings are generated based at least in part on ruby types of the groups of ruby characters, and wherein the ruby types comprise at least one of a mono ruby, a group ruby, or a jukugo ruby; generating, via the processing device, a rendering layout of the base characters and the ruby characters based at least in part on the markings; and rendering, via the processing device, at least a portion of the electronic document according to the rendering layout. | 18. A method comprising: receiving, via a processing device, an electronic document having base characters, ruby characters, and markings comprising metadata instructions indicating how to render groups of ruby characters, wherein the markings are generated based at least in part on ruby types of the groups of ruby characters, and wherein the ruby types comprise at least one of a mono ruby, a group ruby, or a jukugo ruby; generating, via the processing device, a rendering layout of the base characters and the ruby characters based at least in part on the markings; and rendering, via the processing device, at least a portion of the electronic document according to the rendering layout. 19. The method of claim 18 , wherein the markings indicate at least one of how to position base characters and associated ruby characters at line boundaries or how to space base characters and associated ruby characters. | 0.662577 |
7,836,397 | 3 | 4 | 3. A document layout system comprising: a computer embodying: a candidate layout generator that constructs a plurality of candidate layouts for selected content; a layout quality tagger that tags the candidate layouts with overall layout quality criterion values using an overall layout quality criterion combining a set of component quality criteria as a weighted linear combination of kernels, each kernel corresponding to an inner product comparing component quality criteria values of a training layout with corresponding component quality criteria values of an input layout, the kernels corresponding to inner products between a first vector φ(x k ) and a second vector φ(x) where x k denotes a vector representing the component quality criteria values for training layout k, x denotes a vector representing the component quality criteria values for the input layout, and φ denotes a non-linear vector transform; and a layout selector that selects a layout for the selected content from amongst the candidate layouts based on the tagged overall layout quality criterion values. | 3. A document layout system comprising: a computer embodying: a candidate layout generator that constructs a plurality of candidate layouts for selected content; a layout quality tagger that tags the candidate layouts with overall layout quality criterion values using an overall layout quality criterion combining a set of component quality criteria as a weighted linear combination of kernels, each kernel corresponding to an inner product comparing component quality criteria values of a training layout with corresponding component quality criteria values of an input layout, the kernels corresponding to inner products between a first vector φ(x k ) and a second vector φ(x) where x k denotes a vector representing the component quality criteria values for training layout k, x denotes a vector representing the component quality criteria values for the input layout, and φ denotes a non-linear vector transform; and a layout selector that selects a layout for the selected content from amongst the candidate layouts based on the tagged overall layout quality criterion values. 4. The document layout system as set forth in claim 3 , wherein the set of component quality criteria include criteria selected from a group consisting of: color harmony, alignment, balance, uniformity, contrast, navigability, cost, white space, positions of bounding boxes of page zones, absolute color values, font size, header font size, body text font size, and title font size. | 0.5 |
8,255,217 | 9 | 11 | 9. The method of claim 8 , wherein the language model creation engine is part of a voice-driven system and the method further comprises the voice-driving search system: receiving a location of a user; selecting one of a plurality of language models stored in a language model database that covers an area including the location of the user; receiving an audio input provided by the user; and processing the audio input based at least in part upon the selected language model to determine a search request identified in the audio input. | 9. The method of claim 8 , wherein the language model creation engine is part of a voice-driven system and the method further comprises the voice-driving search system: receiving a location of a user; selecting one of a plurality of language models stored in a language model database that covers an area including the location of the user; receiving an audio input provided by the user; and processing the audio input based at least in part upon the selected language model to determine a search request identified in the audio input. 11. The method of claim 9 , wherein the steps performed by the voice-driven search system are performed by a mobile device-based voice-driven search system. | 0.5 |
9,002,830 | 7 | 11 | 7. A method of determining reliability of electronic documents associated with an event occurring in connection with a computing device, comprising, with a processor: composing a number of search queries based on text included in an event message, the event message being generated as a result of an occurrence within the computing device; searching for a number of electronic documents via a network, said searching performed based on the composed search queries; and ranking the electronic documents within results of the search based upon the reliability in addressing the event associated with the event message, in which ranking the electronic documents within results of the search comprises applying a quality of information (QOI) ranking criteria to the electronic documents within results of the search, in which applying a quality of information (QOI) ranking criteria to the electronic documents within results of the search comprises: extracting a number of attributes from the electronic documents within the results of the search; and ranking the electronic documents based on the extracted attributes. | 7. A method of determining reliability of electronic documents associated with an event occurring in connection with a computing device, comprising, with a processor: composing a number of search queries based on text included in an event message, the event message being generated as a result of an occurrence within the computing device; searching for a number of electronic documents via a network, said searching performed based on the composed search queries; and ranking the electronic documents within results of the search based upon the reliability in addressing the event associated with the event message, in which ranking the electronic documents within results of the search comprises applying a quality of information (QOI) ranking criteria to the electronic documents within results of the search, in which applying a quality of information (QOI) ranking criteria to the electronic documents within results of the search comprises: extracting a number of attributes from the electronic documents within the results of the search; and ranking the electronic documents based on the extracted attributes. 11. The method of claim 7 , in which the extracted attributes designate whether questions within the electronic documents were answered or not answered. | 0.928302 |
8,146,032 | 9 | 10 | 9. The method of claim 8 , wherein transforming the die stack into at least two separate dies involves: identifying a transform boundary between the first die and the second die; and separating the first die from the second die to create a first transformed die and a second transformed die, respectively, wherein the first transformed die includes the first die and at least one metal layer adjacent to the transform boundary in the second die; wherein the second transformed die includes the second die and at least one metal layer adjacent to the transform boundary in the first die; and wherein including at least one metal layer from an adjacent die facilitates maintaining equivalency between the two transformed dies and the die stack. | 9. The method of claim 8 , wherein transforming the die stack into at least two separate dies involves: identifying a transform boundary between the first die and the second die; and separating the first die from the second die to create a first transformed die and a second transformed die, respectively, wherein the first transformed die includes the first die and at least one metal layer adjacent to the transform boundary in the second die; wherein the second transformed die includes the second die and at least one metal layer adjacent to the transform boundary in the first die; and wherein including at least one metal layer from an adjacent die facilitates maintaining equivalency between the two transformed dies and the die stack. 10. The method of claim 9 , wherein the transform boundary can be: an interface between a top metal layer in the first die and a top metal layer in the second die in a face-to-face configuration of the 3D-IC die description; an interface between a back-side metal layer in the first die and a top metal layer in the second die in a face-to-back configuration of the 3D-IC die description; or an interface between a back-side metal layer in the first die and a back-side metal layer in the second die in a back-to-back configuration of the 3D-IC die description. | 0.5 |
8,856,236 | 33 | 35 | 33. A method of providing service to first party via a telephony connection, the method comprising the steps of: providing indication that a second party using an instant communications client desires to communicate with the first party using a messaging response system; providing communications among the first party and the second party, wherein the first party engages in communication using audio information via the telephony connection; receiving information from the first party relating to how charges associated with the use of the service are to be billed, wherein an account of the first party is identified by both a screen name of the first party and a service provider identifier associated with a service provider of the first party, and wherein the service provider is one of a plurality of service providers that can be used to access the messaging response system; and providing to the first party audio information corresponding to textual information from the second party, wherein an aspect of providing the audio information corresponding to the textual information is affected by preference information pertaining to at least one of the first party, the second party and the instant communications client and the aspect relates to a voice characteristic imparted to synthesized speech in the audio information. | 33. A method of providing service to first party via a telephony connection, the method comprising the steps of: providing indication that a second party using an instant communications client desires to communicate with the first party using a messaging response system; providing communications among the first party and the second party, wherein the first party engages in communication using audio information via the telephony connection; receiving information from the first party relating to how charges associated with the use of the service are to be billed, wherein an account of the first party is identified by both a screen name of the first party and a service provider identifier associated with a service provider of the first party, and wherein the service provider is one of a plurality of service providers that can be used to access the messaging response system; and providing to the first party audio information corresponding to textual information from the second party, wherein an aspect of providing the audio information corresponding to the textual information is affected by preference information pertaining to at least one of the first party, the second party and the instant communications client and the aspect relates to a voice characteristic imparted to synthesized speech in the audio information. 35. The method of claim 33 further comprising: receiving an indication from the first party as to whether the first party desires to communicate with the second party. | 0.551075 |
8,676,800 | 28 | 31 | 28. A system for generating information from a plurality of data items, the system comprising: a computing device; (a) a preprocessor executable in the computing device, the preprocessor being configured for: i. populating an aggregate data item with at least one of the plurality of data items; wherein each individual data item comprises original information including an attribute and a value, wherein the attribute of the individual data item is an identifier for the individual data item, wherein the aggregate data item is a form of derived attribute, wherein the derived attribute represents a transformation of a collection of individual data items into a single data item with a value, wherein said value of the derived attribute is an aggregate value comprising a map of attribute to value for each said individual data item within said collection of individual data items such that a derived attribute forms a single data item suitable for inferencing by a knowledge base, said single data item retaining the original information relating to each of the plurality of individual data items yet queried by the knowledge base as a whole to extract information regarding said individual data items; and ii. for constructing one or more other derived attributes from the plurality of data items; and (b) an information generator executable in the computing device, the information generator configured for generating the information using the derived attributes, wherein the information generator forms at least part of a decision support system, and wherein the information so generated falls into one or more of the following groups: i. textual information; ii. a machine instruction. | 28. A system for generating information from a plurality of data items, the system comprising: a computing device; (a) a preprocessor executable in the computing device, the preprocessor being configured for: i. populating an aggregate data item with at least one of the plurality of data items; wherein each individual data item comprises original information including an attribute and a value, wherein the attribute of the individual data item is an identifier for the individual data item, wherein the aggregate data item is a form of derived attribute, wherein the derived attribute represents a transformation of a collection of individual data items into a single data item with a value, wherein said value of the derived attribute is an aggregate value comprising a map of attribute to value for each said individual data item within said collection of individual data items such that a derived attribute forms a single data item suitable for inferencing by a knowledge base, said single data item retaining the original information relating to each of the plurality of individual data items yet queried by the knowledge base as a whole to extract information regarding said individual data items; and ii. for constructing one or more other derived attributes from the plurality of data items; and (b) an information generator executable in the computing device, the information generator configured for generating the information using the derived attributes, wherein the information generator forms at least part of a decision support system, and wherein the information so generated falls into one or more of the following groups: i. textual information; ii. a machine instruction. 31. A system defined by claim 28 wherein the derived attribute is one or more of the following: (a) an aggregate data item; (b) a text condenser attribute; (c) any other result of preprocessing data that extracts one or more high level concept data items from a plurality of data items thereby reducing data complexity. | 0.662791 |
9,971,841 | 7 | 9 | 7. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: develop source content using a source content taxonomy, using a content authoring service, and using a content architecture standard; store the source content in source content storage; assign one or more unique identifiers to the source content based on the source content taxonomy; generate Web content, wherein the Web content contains tags having references to the source content; insert the one or more unique identifiers into corresponding tags in the Web content; store the Web content in Web content storage; responsive to a user viewing from a Web server a page of Web content containing a given tag having a given unique identifier within the one or more unique identifiers, generate Web usage data recording the viewing of the page of Web content, wherein the given tag contains a reference to given item of content in the source content, wherein the reference to the given item of content comprises a uniform resource locator, and wherein inserting the one or more unique identifiers comprises inserting the given unique identifier into the uniform resource locator referencing the given item of content; and generate a Web metrics report based on the Web usage data, wherein the Web metrics report maps the viewing of the page of Web content to the source content taxonomy based on the given unique identifier. | 7. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: develop source content using a source content taxonomy, using a content authoring service, and using a content architecture standard; store the source content in source content storage; assign one or more unique identifiers to the source content based on the source content taxonomy; generate Web content, wherein the Web content contains tags having references to the source content; insert the one or more unique identifiers into corresponding tags in the Web content; store the Web content in Web content storage; responsive to a user viewing from a Web server a page of Web content containing a given tag having a given unique identifier within the one or more unique identifiers, generate Web usage data recording the viewing of the page of Web content, wherein the given tag contains a reference to given item of content in the source content, wherein the reference to the given item of content comprises a uniform resource locator, and wherein inserting the one or more unique identifiers comprises inserting the given unique identifier into the uniform resource locator referencing the given item of content; and generate a Web metrics report based on the Web usage data, wherein the Web metrics report maps the viewing of the page of Web content to the source content taxonomy based on the given unique identifier. 9. The computer program product of claim 7 , wherein the given tag uses the given unique identifier as a parameter for a non-HTML item of content. | 0.787791 |
8,332,350 | 6 | 7 | 6. The method of claim 5 , wherein the step (c1) comprises: (a6) receiving a notification from the document management system regarding adding the document to the document management system; (b6) evaluating each metadata rule by performing the comparison operation in said each metadata rule; and (c6) for said each metadata rule, applying the permission set to the document. | 6. The method of claim 5 , wherein the step (c1) comprises: (a6) receiving a notification from the document management system regarding adding the document to the document management system; (b6) evaluating each metadata rule by performing the comparison operation in said each metadata rule; and (c6) for said each metadata rule, applying the permission set to the document. 7. The method of claim 6 , wherein the step (c6) comprises changing an access control list in the document management system, the access control list including names of users having access to the document along with corresponding levels of access of the users. | 0.5 |
8,978,133 | 1 | 9 | 1. A method comprising: receiving a report from a target user of a social networking system identifying malicious activity performed on the social networking system and identifying an object maintained by the social networking system associated with the malicious activity; identifying objects connected to the target user through the social networking system and disabled by the social networking system; retrieving information describing a type of remedial action taken by the social networking system to disable one or more of the identified objects connected to the target user; calculating, by a computer processor, a disabled connectivity score for the target user based at least in part on the retrieved information, the disabled connectivity score indicating a trustworthiness of the report from the target user; and performing an action affecting the object identified by the report based on the calculated disabled connectivity score. | 1. A method comprising: receiving a report from a target user of a social networking system identifying malicious activity performed on the social networking system and identifying an object maintained by the social networking system associated with the malicious activity; identifying objects connected to the target user through the social networking system and disabled by the social networking system; retrieving information describing a type of remedial action taken by the social networking system to disable one or more of the identified objects connected to the target user; calculating, by a computer processor, a disabled connectivity score for the target user based at least in part on the retrieved information, the disabled connectivity score indicating a trustworthiness of the report from the target user; and performing an action affecting the object identified by the report based on the calculated disabled connectivity score. 9. The method of claim 1 , wherein the action comprises ignoring the report. | 0.942249 |
9,031,886 | 1 | 5 | 1. A method of providing domain-specific modules for domain-specific searches, the method comprising: specifying one or more input elements and one or more output elements for a domain-specific search in a domain, the domain including data that relates the one or more input elements to the one or more output elements; identifying one or more related elements corresponding to metadata in the domain for the one or more input elements or output elements; determining a data set corresponding to the one or more input elements, output elements, and related elements in the domain; and using the data set, by utilizing at least one processor, to train and test a domain-specific module that relates the one or more input elements, output elements and related elements, the domain-specific module operating to receive input values for the one or more input elements and provide output values for the one or more output elements, and the output elements identifying a relevant document related to the domain, the relevant document corresponding to a domain-specific search result for a search defined by the input values. | 1. A method of providing domain-specific modules for domain-specific searches, the method comprising: specifying one or more input elements and one or more output elements for a domain-specific search in a domain, the domain including data that relates the one or more input elements to the one or more output elements; identifying one or more related elements corresponding to metadata in the domain for the one or more input elements or output elements; determining a data set corresponding to the one or more input elements, output elements, and related elements in the domain; and using the data set, by utilizing at least one processor, to train and test a domain-specific module that relates the one or more input elements, output elements and related elements, the domain-specific module operating to receive input values for the one or more input elements and provide output values for the one or more output elements, and the output elements identifying a relevant document related to the domain, the relevant document corresponding to a domain-specific search result for a search defined by the input values. 5. The method of claim 1 , wherein the specifying of the one or more input elements and output elements includes accessing a business-object repository associated with the domain, the business-object repository including business objects having fields corresponding to the one or more input elements and output elements, and the identifying of the one or more related elements includes accessing the business-object repository to identify fields corresponding to the metadata, the metadata including one or more semantic labels related to the one or more input elements or output elements. | 0.5 |
8,533,223 | 1 | 6 | 1. A method comprising: identifying, at a processor, a candidate entity in a media content item, wherein the candidate entity is a potential identification of a first known entity, wherein the media content item comprises a plurality of words or phrases and wherein the candidate entity corresponds to a first word or first phrase of the plurality of words or phrases; performing a first categorization of the candidate entity based on a first set of factors, wherein the first categorization comprises categorizing at least one other candidate entity following the candidate entity in the media content item according to a sequence in which the media content item is to be consumed by a user, wherein the at least one other candidate entity corresponds to a second word or second phrase of the plurality of words or phrases; performing a second categorization of the candidate entity, after the first categorization, based on a second set of factors, wherein the second set of factors is different from the first set of factors and comprises, at least in part, results of the first categorization associated with the at least one other candidate entity; determining, after the second categorization, that the candidate entity is categorized with a plurality of known entities; in response to determining that the candidate entity is categorized with the plurality of known entities, selecting one of the plurality of known entities corresponding to the candidate entity, and tagging the candidate entity, based on the selection of the one of the plurality of known entities and separately from tagging the at least one other candidate entity, as identifying the selected one of the plurality of known entities. | 1. A method comprising: identifying, at a processor, a candidate entity in a media content item, wherein the candidate entity is a potential identification of a first known entity, wherein the media content item comprises a plurality of words or phrases and wherein the candidate entity corresponds to a first word or first phrase of the plurality of words or phrases; performing a first categorization of the candidate entity based on a first set of factors, wherein the first categorization comprises categorizing at least one other candidate entity following the candidate entity in the media content item according to a sequence in which the media content item is to be consumed by a user, wherein the at least one other candidate entity corresponds to a second word or second phrase of the plurality of words or phrases; performing a second categorization of the candidate entity, after the first categorization, based on a second set of factors, wherein the second set of factors is different from the first set of factors and comprises, at least in part, results of the first categorization associated with the at least one other candidate entity; determining, after the second categorization, that the candidate entity is categorized with a plurality of known entities; in response to determining that the candidate entity is categorized with the plurality of known entities, selecting one of the plurality of known entities corresponding to the candidate entity, and tagging the candidate entity, based on the selection of the one of the plurality of known entities and separately from tagging the at least one other candidate entity, as identifying the selected one of the plurality of known entities. 6. The method of claim 1 , wherein the first set of factors includes a word that immediately follows the candidate entity in the media content item. | 0.887367 |
7,615,768 | 4 | 5 | 4. A document original size detecting device comprising: a plurality of sensors each including a light emitting portion and a light receiving portion and respectively disposed as corresponding to different sizes of document originals to be placed on a transparent document platen, the light emitting portion and the light receiving portion being positioned above and below the transparent document platen, respectively; and a detecting section which determines a document original size based on outputs of the sensors; wherein the light emitting portion of each of the sensors emits light to illuminate at least two positions on a document placing region of the document platen on which a document original to be subjected to size detection is placed, and the detecting section determines the document original size based on whether or not the light receiving portion of each of the sensors detects the document original blocking the light in at least one of the two positions, wherein the light emitting portion of each of the sensors includes a light emitting element which emits a light beam on the document platen, and an illumination position moving section which moves an illumination position at which the light beam emitted from the light emitting element is incident on the document platen to the at least two positions, the at least two positions being aligned parallel to a reference line along which one edge of the document original is positioned on the document platen, and wherein the light receiving portion of each of the sensors includes a light receiving element which receives the light beam emitted from the light emitting element. | 4. A document original size detecting device comprising: a plurality of sensors each including a light emitting portion and a light receiving portion and respectively disposed as corresponding to different sizes of document originals to be placed on a transparent document platen, the light emitting portion and the light receiving portion being positioned above and below the transparent document platen, respectively; and a detecting section which determines a document original size based on outputs of the sensors; wherein the light emitting portion of each of the sensors emits light to illuminate at least two positions on a document placing region of the document platen on which a document original to be subjected to size detection is placed, and the detecting section determines the document original size based on whether or not the light receiving portion of each of the sensors detects the document original blocking the light in at least one of the two positions, wherein the light emitting portion of each of the sensors includes a light emitting element which emits a light beam on the document platen, and an illumination position moving section which moves an illumination position at which the light beam emitted from the light emitting element is incident on the document platen to the at least two positions, the at least two positions being aligned parallel to a reference line along which one edge of the document original is positioned on the document platen, and wherein the light receiving portion of each of the sensors includes a light receiving element which receives the light beam emitted from the light emitting element. 5. A document original size detecting device as set forth in claim 4 , wherein the illumination position moving section includes a movement mechanism which moves the light emitting element by a spring member. | 0.623188 |
9,171,060 | 15 | 16 | 15. A non-transitory machine-readable storage device, tangibly embodying a set of instructions that, when executed by at least one processor, causes the at least one processor to perform a set of operations comprising: enabling a user to adjust configuration settings for a transformation of primitives of a Semantic Web ontology language into primitives of a software modeling language, the primitives of the Semantic Web ontology language being part of an ontology; storing the adjusted configuration settings on a storage device; performing the transformation of primitives of the Semantic Web ontology language into primitives of the software modeling language using the adjusted configuration settings stored on the storage device, the performing of the transformation comprising: creating a metamodel; adding an instance of a metamodel class for a top-level class to the metamodel, the top-level class characterized by having no superclass and being a common superclass for all classes of the ontology; for each top class of a class hierarchy of the ontology, adding a corresponding instance of the metamodel class to the metamodel, each top class characterized by having no superclass; associating the top-level class with the instances of the metamodel class corresponding to each top class of the class hierarchy; and for each top class of the class hierarchy of the ontology, adding an annotation comprising a corresponding internationalized resource identifier (IRI) for the top class to the instance of the metamodel class for the top class, adding a corresponding instance of the metamodel class for each subclass of the top class to the metamodel, and associating the top class with the instances of the metamodel class corresponding to each subclass of the top class; and enabling a selection of the adjusted configuration settings stored on the storage device for use in a subsequent transformation of primitives of the Semantic Web ontology language into primitives of the software modeling language. | 15. A non-transitory machine-readable storage device, tangibly embodying a set of instructions that, when executed by at least one processor, causes the at least one processor to perform a set of operations comprising: enabling a user to adjust configuration settings for a transformation of primitives of a Semantic Web ontology language into primitives of a software modeling language, the primitives of the Semantic Web ontology language being part of an ontology; storing the adjusted configuration settings on a storage device; performing the transformation of primitives of the Semantic Web ontology language into primitives of the software modeling language using the adjusted configuration settings stored on the storage device, the performing of the transformation comprising: creating a metamodel; adding an instance of a metamodel class for a top-level class to the metamodel, the top-level class characterized by having no superclass and being a common superclass for all classes of the ontology; for each top class of a class hierarchy of the ontology, adding a corresponding instance of the metamodel class to the metamodel, each top class characterized by having no superclass; associating the top-level class with the instances of the metamodel class corresponding to each top class of the class hierarchy; and for each top class of the class hierarchy of the ontology, adding an annotation comprising a corresponding internationalized resource identifier (IRI) for the top class to the instance of the metamodel class for the top class, adding a corresponding instance of the metamodel class for each subclass of the top class to the metamodel, and associating the top class with the instances of the metamodel class corresponding to each subclass of the top class; and enabling a selection of the adjusted configuration settings stored on the storage device for use in a subsequent transformation of primitives of the Semantic Web ontology language into primitives of the software modeling language. 16. The device of claim 15 , wherein performing the transformation comprises generating Object Constraint Language (OCL) constraints for primitives of the software modeling language. | 0.696667 |
10,083,239 | 11 | 19 | 11. A non-transitory computer readable storage medium comprising instructions which when executed by a processor cause the processor to perform the steps of: determining one or more story generators for a viewing user of a social networking system; accessing a plurality of narrative data items comprising data stored within the social networking system related to the viewing user or a user connected to the viewing user in the social networking system selecting one or more of the narrative data items based on a relevance of each of the narrative data items to the viewing user; generating a plurality of candidate stories from the narrative data items using the one or more story generators, each of the plurality of candidate stories being associated with a story type of a plurality of story types, where two or more candidate stories of the plurality of candidate stories are associated with a same narrative data item; identifying the two or more candidate stories that are associated with the same narrative data item; responsive to the identifying, removing a subset of the two or more candidate stories from the plurality of candidate stories; selecting one or more of the plurality of candidate stories as selected stories for the viewing user; and sending a displayable representation of the selected stories to a client device for display to the viewing user. | 11. A non-transitory computer readable storage medium comprising instructions which when executed by a processor cause the processor to perform the steps of: determining one or more story generators for a viewing user of a social networking system; accessing a plurality of narrative data items comprising data stored within the social networking system related to the viewing user or a user connected to the viewing user in the social networking system selecting one or more of the narrative data items based on a relevance of each of the narrative data items to the viewing user; generating a plurality of candidate stories from the narrative data items using the one or more story generators, each of the plurality of candidate stories being associated with a story type of a plurality of story types, where two or more candidate stories of the plurality of candidate stories are associated with a same narrative data item; identifying the two or more candidate stories that are associated with the same narrative data item; responsive to the identifying, removing a subset of the two or more candidate stories from the plurality of candidate stories; selecting one or more of the plurality of candidate stories as selected stories for the viewing user; and sending a displayable representation of the selected stories to a client device for display to the viewing user. 19. The non-transitory computer readable storage medium of claim 11 , further comprising instructions which when executed by the processor cause the processor to perform the steps of: generating an affinity for each of the plurality of candidate stories, wherein each affinity comprises a measure of the relevance of a candidate story of the plurality of candidate stories to the viewing user; and generating a ranking of the plurality of candidate stories based on the affinity generated for each the plurality of stories, wherein selecting one or more of the plurality of candidate stories is based on the ranking. | 0.5 |
8,385,955 | 1 | 5 | 1. A method, comprising: a computer system receiving, via a web interface, a subscription preference relating to one or more message topics and a telephone number corresponding to a portable communication device capable of receiving text messages; in response to receiving the telephone number, the computer system generating an authorization code and causing a text message including the authorization code to be sent to the telephone number; receiving at the computer system, via the web interface, input that includes the authorization code; and in response to authenticating the authorization code, the computer system storing the subscription preference relating to the one or more message topics on a non-transitory computer readable storage medium, wherein the stored subscription preference indicates the computer system has permission to cause one or more text messages that include content directed to the one or more message topics to be sent to the telephone number corresponding to the portable communication device. | 1. A method, comprising: a computer system receiving, via a web interface, a subscription preference relating to one or more message topics and a telephone number corresponding to a portable communication device capable of receiving text messages; in response to receiving the telephone number, the computer system generating an authorization code and causing a text message including the authorization code to be sent to the telephone number; receiving at the computer system, via the web interface, input that includes the authorization code; and in response to authenticating the authorization code, the computer system storing the subscription preference relating to the one or more message topics on a non-transitory computer readable storage medium, wherein the stored subscription preference indicates the computer system has permission to cause one or more text messages that include content directed to the one or more message topics to be sent to the telephone number corresponding to the portable communication device. 5. The method of claim 1 , further comprising modifying the subscription preference to indicate that a user of the portable communication device wishes to receive content relating to one or more different message topics. | 0.776876 |
9,298,684 | 2 | 3 | 2. The method of claim 1 , wherein retrieving the native UI form specification from the PIM form storage further comprises retrieving the form markup file from which the native UI form specification was generated. | 2. The method of claim 1 , wherein retrieving the native UI form specification from the PIM form storage further comprises retrieving the form markup file from which the native UI form specification was generated. 3. The method of claim 2 , further comprising: for each of the two or more UI controls having an event subscription to a custom event handler, subscribing to the event specified in the event subscription for the UI control. | 0.5 |
7,663,603 | 1 | 5 | 1. A data communications device, comprising: a receiver for receiving items of textual information contained in an incoming text message, a data processor operable in response to the received items of textual information to automatically extract textual information directly from said incoming text message, a plurality of keys each associated with a respective plurality of different text characters, the keys being operable by the user to produce an ambiguous key sequence corresponding to an item of textual information, a memory configuration to store different ones of said ambiguous key sequences and to associate with each thereof at least one item of said extracted textual information corresponding to the ambiguous key sequence, wherein the data processor is operable in response to the user actuating the keys to produce one of the ambiguous key sequences, to retrieve the extracted textual information associated therewith from the memory configuration to permit the user to disambiguate the produced key sequence, wherein the receiver is coupled to the memory configuration, and is operable to identify, based on knowledge of the association of text characters to the plurality of keys, an ambiguous key sequence corresponding to an item of the received textual information in said incoming text message, and to store the item of received textual information in the memory configuration such that it is associated with the identified ambiguous key sequence. | 1. A data communications device, comprising: a receiver for receiving items of textual information contained in an incoming text message, a data processor operable in response to the received items of textual information to automatically extract textual information directly from said incoming text message, a plurality of keys each associated with a respective plurality of different text characters, the keys being operable by the user to produce an ambiguous key sequence corresponding to an item of textual information, a memory configuration to store different ones of said ambiguous key sequences and to associate with each thereof at least one item of said extracted textual information corresponding to the ambiguous key sequence, wherein the data processor is operable in response to the user actuating the keys to produce one of the ambiguous key sequences, to retrieve the extracted textual information associated therewith from the memory configuration to permit the user to disambiguate the produced key sequence, wherein the receiver is coupled to the memory configuration, and is operable to identify, based on knowledge of the association of text characters to the plurality of keys, an ambiguous key sequence corresponding to an item of the received textual information in said incoming text message, and to store the item of received textual information in the memory configuration such that it is associated with the identified ambiguous key sequence. 5. A device according to claim 1 , wherein the text message is an SMS message or an MMS message. | 0.84 |
9,619,580 | 16 | 18 | 16. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to associate a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object, wherein the specific subject-matter for a particular data store in the data structure overlaps a subject-matter of another data store in the data structure, and wherein the particular data store and said another data store are data repositories of different sets of integrated text files; second program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; third program instructions to receive, from a requester, a request for data from said at least one specific data store that is associated with the synthetic context-based object; and fourth program instructions to return, to the requester, data from said at least one specific data store that is associated with the synthetic context-based object; and wherein the first, second, third, and fourth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 16. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to associate a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object, wherein the specific subject-matter for a particular data store in the data structure overlaps a subject-matter of another data store in the data structure, and wherein the particular data store and said another data store are data repositories of different sets of integrated text files; second program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; third program instructions to receive, from a requester, a request for data from said at least one specific data store that is associated with the synthetic context-based object; and fourth program instructions to return, to the requester, data from said at least one specific data store that is associated with the synthetic context-based object; and wherein the first, second, third, and fourth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. 18. The computer system of claim 16 , wherein the specific subject-matter for a particular data store in the data structure is exclusive to only said particular data store. | 0.824847 |
4,742,516 | 14 | 21 | 14. A method for transmitting voice information from at least one broadcasting station to a plurality of receivers, comprising the steps of: composing information packets each of which includes a text portion including a sequence of words and symbols and a classification code signifying a substance of the text portion; converting the information packets into digital signals; transmitting one time the information packets substantially as digital signals via a transmitting medium in succession; receiving at at least one of said receivers having at least one classification code stored therein, said transmitted information packets, said stored classification codes being changed, added as a new classification code or deleted by a user for signifying the substance of the text portion the user wishes to receive; selecting received information packets with a classification code corresponding to the stored classification code at said at least one receiver; accumulating in said at least one receiver selected information packets having a classification code matching the classification code previously stored in said receiver; and conveying to a user information corresponding to the texts of the accumulated information packets by at least one of visually displaying said information and enunciating said information over a speaker at each receiver according to an output order determined by said at least one receiver. | 14. A method for transmitting voice information from at least one broadcasting station to a plurality of receivers, comprising the steps of: composing information packets each of which includes a text portion including a sequence of words and symbols and a classification code signifying a substance of the text portion; converting the information packets into digital signals; transmitting one time the information packets substantially as digital signals via a transmitting medium in succession; receiving at at least one of said receivers having at least one classification code stored therein, said transmitted information packets, said stored classification codes being changed, added as a new classification code or deleted by a user for signifying the substance of the text portion the user wishes to receive; selecting received information packets with a classification code corresponding to the stored classification code at said at least one receiver; accumulating in said at least one receiver selected information packets having a classification code matching the classification code previously stored in said receiver; and conveying to a user information corresponding to the texts of the accumulated information packets by at least one of visually displaying said information and enunciating said information over a speaker at each receiver according to an output order determined by said at least one receiver. 21. A method according to claim 14 wherein said step of transmitting comprises the steps of transmitting by a first broadcasting station having a wide broadcasting area and transmitting by a second broadcasting station having a narrow broadcasting area by time multiplexing the digital signals corresponding to said information packets. | 0.533333 |
9,459,848 | 3 | 5 | 3. A system, comprising: a hardware processor; a compiler for a first language, a first abstract syntax tree by parsing source code written in the first language or a domain specific language based on the first language; a compiler for a second language, a data representation type converter for converting the first abstract syntax tree to a second abstract syntax tree of the compiler for the second language using a conversion table from data representation types in the first language to data representation types in the second language, wherein the compiler for the second language, when a compilation error occurs, generates a special node for error processing, using a hardware processor, in the second abstract syntax tree and stores in the special node an error token indicating information of the compilation error; and wherein said compiler for the second language, when unparsing, outputs the error token stored in the special node is output, in the form of source code written in the first language. | 3. A system, comprising: a hardware processor; a compiler for a first language, a first abstract syntax tree by parsing source code written in the first language or a domain specific language based on the first language; a compiler for a second language, a data representation type converter for converting the first abstract syntax tree to a second abstract syntax tree of the compiler for the second language using a conversion table from data representation types in the first language to data representation types in the second language, wherein the compiler for the second language, when a compilation error occurs, generates a special node for error processing, using a hardware processor, in the second abstract syntax tree and stores in the special node an error token indicating information of the compilation error; and wherein said compiler for the second language, when unparsing, outputs the error token stored in the special node is output, in the form of source code written in the first language. 5. The system of claim 3 , wherein said data representation type converter converts the first abstract syntax tree to the second abstract syntax tree while disregarding helper classes for assisting in the conversion. | 0.555556 |
10,157,220 | 1 | 2 | 1. A computer program product for a search engine, the computer program product comprising: one or more computer-readable storage media and program instructions of the search engine stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to receive a search expression; program instructions to extract, using a search term extractor of the search engine, two or more query terms of the search expression; program instructions to determine two or more nodes representing a first term of the two or more query terms and at least one node representing a second term of the two or more query terms, wherein the two or more nodes each have an associated text for search term expansion and represent at least one concept in a semantic graph of nodes that represents a domain of semantically related concepts; program instructions to determine a center of focus within the semantic graph for the two or more nodes based, at least in part, on a spreading activation in the semantic graph; program instructions to determine a contextual relevance for the two or more nodes with respect to the center of focus based, at least in part, on an assessment of semantic similarity for the two or more nodes with respect to the center of focus; program instructions to select for a query term, which is included in the two or more query terms of the search expression, at least one node from the two or more nodes based, at least in part, on a contextual relevance between the at least one node and the determined center of focus; program instructions to generate an expanded search expression by expanding the search expression using an associated text of the at least one node; and program instructions to generate, by the search engine, an output of search results by executing a search using the expanded search expression. | 1. A computer program product for a search engine, the computer program product comprising: one or more computer-readable storage media and program instructions of the search engine stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to receive a search expression; program instructions to extract, using a search term extractor of the search engine, two or more query terms of the search expression; program instructions to determine two or more nodes representing a first term of the two or more query terms and at least one node representing a second term of the two or more query terms, wherein the two or more nodes each have an associated text for search term expansion and represent at least one concept in a semantic graph of nodes that represents a domain of semantically related concepts; program instructions to determine a center of focus within the semantic graph for the two or more nodes based, at least in part, on a spreading activation in the semantic graph; program instructions to determine a contextual relevance for the two or more nodes with respect to the center of focus based, at least in part, on an assessment of semantic similarity for the two or more nodes with respect to the center of focus; program instructions to select for a query term, which is included in the two or more query terms of the search expression, at least one node from the two or more nodes based, at least in part, on a contextual relevance between the at least one node and the determined center of focus; program instructions to generate an expanded search expression by expanding the search expression using an associated text of the at least one node; and program instructions to generate, by the search engine, an output of search results by executing a search using the expanded search expression. 2. The computer program product according to claim 1 wherein program instructions to select for a query term, which is included in the two or more query terms of the search expression, at least one node from the two or more nodes based, at least in part, on a contextual relevance between the at least one node and the determined center of focus include: program instructions to select a determined node with a greatest contextual relevance for each query term. | 0.587657 |
9,020,804 | 22 | 23 | 22. A system comprising: a sentence aligner which aligns sentences of a target document in a target language with respective sentences of a source document in a source language; a source term tagger which tags terms of each source sentence which meet criteria for at least one class of candidate terms, each of the candidate terms comprising a contiguous subsequence of words of the source sentence; a word aligner which, for a pair of sentences aligned by the sentence aligner and tagged with the source term tagger, generates an alignment between the words of a target sentence and the words of the source sentence, the word aligner using a probabilistic model which models conditional probability distributions for alignments between words of the source sentence and words of the target sentence and generating an optimal alignment based on the probabilistic model, the word aligner enforcing a contiguity constraint which requires that all the words of the target sentence which are aligned with one of the candidate terms identified by the term tagger form a contiguous subsequence of the target sentence. | 22. A system comprising: a sentence aligner which aligns sentences of a target document in a target language with respective sentences of a source document in a source language; a source term tagger which tags terms of each source sentence which meet criteria for at least one class of candidate terms, each of the candidate terms comprising a contiguous subsequence of words of the source sentence; a word aligner which, for a pair of sentences aligned by the sentence aligner and tagged with the source term tagger, generates an alignment between the words of a target sentence and the words of the source sentence, the word aligner using a probabilistic model which models conditional probability distributions for alignments between words of the source sentence and words of the target sentence and generating an optimal alignment based on the probabilistic model, the word aligner enforcing a contiguity constraint which requires that all the words of the target sentence which are aligned with one of the candidate terms identified by the term tagger form a contiguous subsequence of the target sentence. 23. The system of claim 22 , further comprising: a term extractor which extracts contiguous subsequences of the target sentences that are aligned to a common source candidate term; and a filter which, filters the extracted contiguous subsequences to remove contiguous subsequences which are less probable translations of the common candidate term. | 0.5 |
9,110,883 | 1 | 2 | 1. A machine-implemented clause mapping method to expand an input of semantically-interpretable syntactic representation(SISR) set of clauses obtained from a digitally encoded natural language source text and from an SISR knowledge base clauses related to the source text, into an output target set of clauses in SISR format, for natural language understanding (NLU), wherein a lexicon data base comprising SISR semantic lexicons is accessed in the process of the said clause mapping, wherein the SISR of a natural language (NL) text is a representation of standard templates and fields, wherein each of the existent clauses of the said NL text is represented in a single SISR entry, wherein each clause of the said existent clauses is represented in its complete, independent and declarative form and in the active voice, and in a complement-free (unless obligatory) manner and without the linking expressions and the conjunctions external to the clause and represented also in terms of units, wherein a unit comprises one or more words, and wherein each SISR entry comprises: An entry identifier A clause of the said existent clauses The complements of the clause of the said existent clauses, represented in terms of the said units Annotations wherein the said annotations are data comprising information related the SISR entry and its components, wherein an SISR semantic lexicon is a lexicon having a list of SISR clauses entries on one side (list side) and corresponding one or more meaning of each clause of the said list in one or more SISR entries for each meaning on the other side (meaning side), wherein a clause entry on the list side has at least one variable unit in common with a at least one clause entry of every one of the meaning entries on the meaning side, wherein a variable unit symbolizes a unit category, said method comprising steps of: (a) determining relevant SISR semantic lexicons in a lexicon data base and searching for matching entries in the relevant lexicons for an input set of clauses in SISR format, (entry searching step) (b) selecting for each variable unit in the SISR clauses matched in step (a) its corresponding literal in the clauses of the input set, (symbol substitution step) (c) computing using the output of step (b) a plurality of clause annotations and generating a set of clauses in SISR format, (clause optimizing step) (d) adding the output of step (c) together with the input to the target set, (e) performing multiple iterations of steps (a) through (d) by feeding back the target set as input to step (a), and (f) generating the target set as output once steps (a) through (e) are completed. | 1. A machine-implemented clause mapping method to expand an input of semantically-interpretable syntactic representation(SISR) set of clauses obtained from a digitally encoded natural language source text and from an SISR knowledge base clauses related to the source text, into an output target set of clauses in SISR format, for natural language understanding (NLU), wherein a lexicon data base comprising SISR semantic lexicons is accessed in the process of the said clause mapping, wherein the SISR of a natural language (NL) text is a representation of standard templates and fields, wherein each of the existent clauses of the said NL text is represented in a single SISR entry, wherein each clause of the said existent clauses is represented in its complete, independent and declarative form and in the active voice, and in a complement-free (unless obligatory) manner and without the linking expressions and the conjunctions external to the clause and represented also in terms of units, wherein a unit comprises one or more words, and wherein each SISR entry comprises: An entry identifier A clause of the said existent clauses The complements of the clause of the said existent clauses, represented in terms of the said units Annotations wherein the said annotations are data comprising information related the SISR entry and its components, wherein an SISR semantic lexicon is a lexicon having a list of SISR clauses entries on one side (list side) and corresponding one or more meaning of each clause of the said list in one or more SISR entries for each meaning on the other side (meaning side), wherein a clause entry on the list side has at least one variable unit in common with a at least one clause entry of every one of the meaning entries on the meaning side, wherein a variable unit symbolizes a unit category, said method comprising steps of: (a) determining relevant SISR semantic lexicons in a lexicon data base and searching for matching entries in the relevant lexicons for an input set of clauses in SISR format, (entry searching step) (b) selecting for each variable unit in the SISR clauses matched in step (a) its corresponding literal in the clauses of the input set, (symbol substitution step) (c) computing using the output of step (b) a plurality of clause annotations and generating a set of clauses in SISR format, (clause optimizing step) (d) adding the output of step (c) together with the input to the target set, (e) performing multiple iterations of steps (a) through (d) by feeding back the target set as input to step (a), and (f) generating the target set as output once steps (a) through (e) are completed. 2. The clause mapping method of claim 1 wherein the lexicon database comprises end terms SISR semantic lexicons, wherein an end terms SISR semantic lexicon is a lexicon having end term clauses on the mapping side and not having end term clauses on the list side, wherein an end term clause is a clause banned from mapping. | 0.5 |
10,007,662 | 56 | 75 | 56. A method of extracting a second sequence, comprising the steps of: receiving a first sequence (S′); retrieving a dual SSM Sequence Model (SSM) Matrix generated from the first sequence and a second sequence (D(S″, S′)); extracting the second sequence (S″) from the dual SSM Matrix (D(S″, S′)) and a first histogram vector (h′) of the first sequence (S′). | 56. A method of extracting a second sequence, comprising the steps of: receiving a first sequence (S′); retrieving a dual SSM Sequence Model (SSM) Matrix generated from the first sequence and a second sequence (D(S″, S′)); extracting the second sequence (S″) from the dual SSM Matrix (D(S″, S′)) and a first histogram vector (h′) of the first sequence (S′). 75. The method of claim 56 , adapted for analysis of biological sequences, wherein the step of receiving a first sequence (S′) comprises the step of receiving a DNA sequence, and wherein the step of retrieving comprises the step of retrieving a dual SSM Matrix generated from the DNA sequence and an additional property that is associated with the DNA sequence (D(S″, S′)), and wherein the step of extracting comprises the step of extracting the additional property that matches the DNA sequence from the step of receiving. | 0.5 |
9,858,600 | 8 | 9 | 8. A method comprising: configuring a data contract definition of a universal tag via a console server, wherein the data contract definition specifies: data events and corresponding event data to collect from a designated website accessed by a user at a user device, and client-defined transformation rules and taxonomy rules for interpreting the collected event data to generate a user profile corresponding to the user, the user profile including key-value pairs and categorizations; storing the data contract definition as a corresponding updated data contract in a database; identifying, via a listening server, the updated data contract in the database; generating, via the listening server, run time code instructions based on the updated data contract; receiving, at a presentation server, the runtime code from the listening server to instantiate a runtime endpoint at the presentation server; collecting, at the presentation server during runtime, event data from the designated website, the event data specified by the data contract definition; applying the transformations to the collected event data, categorizing the transformed event data based on the applied taxonomy rules, and storing the transformed event data in the corresponding user profile at a profile server; wherein collecting event data includes providing a universal tag script, via the presentation server, for running in the context of the designated website to instantiate a universal tag to: collect event data from the designated website, and report the collected event data to the runtime endpoint for applying the transformation and taxonomy rules; and wherein applying the transformations to the collected event data includes performing an iterative loop via the runtime endpoint on the presentation server, the iterative loop comprising: automatically determining, via a data provider servlet application, a list of runtime transformation applications corresponding to data contracts corresponding to a particular provider ID; performing, via a runtime transform application, the appropriate transformations on event-value pairs; and for each event-value pair, return a key-value pair and appropriate category identification for storage at a runtime user profile application. | 8. A method comprising: configuring a data contract definition of a universal tag via a console server, wherein the data contract definition specifies: data events and corresponding event data to collect from a designated website accessed by a user at a user device, and client-defined transformation rules and taxonomy rules for interpreting the collected event data to generate a user profile corresponding to the user, the user profile including key-value pairs and categorizations; storing the data contract definition as a corresponding updated data contract in a database; identifying, via a listening server, the updated data contract in the database; generating, via the listening server, run time code instructions based on the updated data contract; receiving, at a presentation server, the runtime code from the listening server to instantiate a runtime endpoint at the presentation server; collecting, at the presentation server during runtime, event data from the designated website, the event data specified by the data contract definition; applying the transformations to the collected event data, categorizing the transformed event data based on the applied taxonomy rules, and storing the transformed event data in the corresponding user profile at a profile server; wherein collecting event data includes providing a universal tag script, via the presentation server, for running in the context of the designated website to instantiate a universal tag to: collect event data from the designated website, and report the collected event data to the runtime endpoint for applying the transformation and taxonomy rules; and wherein applying the transformations to the collected event data includes performing an iterative loop via the runtime endpoint on the presentation server, the iterative loop comprising: automatically determining, via a data provider servlet application, a list of runtime transformation applications corresponding to data contracts corresponding to a particular provider ID; performing, via a runtime transform application, the appropriate transformations on event-value pairs; and for each event-value pair, return a key-value pair and appropriate category identification for storage at a runtime user profile application. 9. The method of claim 8 , further comprising: generating a console user interface (UI) at the console server for inputting the client-defined transformation rules and taxonomy rules, and generating an event inspector tool on the listening server for defining context-specific data events for collection on a webpage visited by a user device. | 0.735703 |
7,831,426 | 1 | 16 | 1. A network based interactive speech system adapted for responding to speech-based queries concerning a set of topic entries, the system comprising: a speech recognition engine adapted to generate recognized speech utterance data from speech data associated with a speech-based query from a speaker concerning one of the set of topic entries; a first routine executing on a server system and adapted to perform natural language processing on said recognized speech utterance data to identify a selected set of phrases related to the set of topic entries; a second routine executing on the server system and adapted to convert said selected set of phrases from the first routine into a search query suitable for identifying a first group of one or more topic entries corresponding to said speech-based query; wherein words and/or phrases in said search query can be assigned different weightings determined by said first routine from said recognized speech utterance data; and a third routine executing on the server system adapted to evaluate said first group of one or more topic entries and to identify a single topic entry responsive to said speech-based query; wherein third routine can consider words and/or phrases in said search query which are not in said set of topic entries; and wherein information corresponding to a single topic entry taken from said first group can be determined and presented in real-time by the interactive speech system automatically as a response best matching said speech-based query. | 1. A network based interactive speech system adapted for responding to speech-based queries concerning a set of topic entries, the system comprising: a speech recognition engine adapted to generate recognized speech utterance data from speech data associated with a speech-based query from a speaker concerning one of the set of topic entries; a first routine executing on a server system and adapted to perform natural language processing on said recognized speech utterance data to identify a selected set of phrases related to the set of topic entries; a second routine executing on the server system and adapted to convert said selected set of phrases from the first routine into a search query suitable for identifying a first group of one or more topic entries corresponding to said speech-based query; wherein words and/or phrases in said search query can be assigned different weightings determined by said first routine from said recognized speech utterance data; and a third routine executing on the server system adapted to evaluate said first group of one or more topic entries and to identify a single topic entry responsive to said speech-based query; wherein third routine can consider words and/or phrases in said search query which are not in said set of topic entries; and wherein information corresponding to a single topic entry taken from said first group can be determined and presented in real-time by the interactive speech system automatically as a response best matching said speech-based query. 16. The interactive speech system of claim 1 , wherein the system evaluates whether to process said speech query locally at the server system or whether to process said speech query at least in part on another server system. | 0.698925 |
8,380,698 | 1 | 20 | 1. A method including: receiving an aspect and a request from a user, the aspect being used to describe a data item and the request to solicit at least one candidate value to associate with the aspect; identifying a string of text in a database based on the aspect, the identifying the string of text including one or more actions selected from a group of actions consisting of identifying the aspect in the string of text, identifying a synonym of the aspect in the string of text, identifying an acronym of the aspect in the string of text, and identifying an alternate spelling of the aspect in the string of text, the database being a sample of data items from a first database that is utilized by a plurality of buyers and a plurality of sellers that utilize a network-based marketplace, the sample of data items including a seasonal sample; analyzing the string of text based on the aspect to identify at least one candidate value in the string of text, the at least one candidate value including a first candidate value; communicating the at least one candidate value to the user; receiving a rule including an aspect-value pair including the aspect and the first candidate value; publishing the rule in a production environment; associating the aspect-value pair to a first data item based on the published rule, the associating including concatenating the aspect-value pair to the first data item responsive to identifying the first candidate value in the first data item to generate the first data item including the concatenated aspect-value pair; receiving a first query; associating the aspect-value pair to the first query based on the rule; and identifying the first data item including the concatenated aspect-value pair for inclusion in an interface based on the associating the aspect-value pair to the first query based on the first rule; receiving a request to publish a dictionary for a particular domain in a preview environment in the network-based marketplace, the preview environment is being utilized to test a rule before the rule is applied to at least one of the first data item and the first query in a production environment, the dictionary including a plurality of domain rules being utilized to associate a first category on the network-based marketplace with a first product type, and the first category and the first product type further being associated with the first data item for sale on the network-based marketplace. | 1. A method including: receiving an aspect and a request from a user, the aspect being used to describe a data item and the request to solicit at least one candidate value to associate with the aspect; identifying a string of text in a database based on the aspect, the identifying the string of text including one or more actions selected from a group of actions consisting of identifying the aspect in the string of text, identifying a synonym of the aspect in the string of text, identifying an acronym of the aspect in the string of text, and identifying an alternate spelling of the aspect in the string of text, the database being a sample of data items from a first database that is utilized by a plurality of buyers and a plurality of sellers that utilize a network-based marketplace, the sample of data items including a seasonal sample; analyzing the string of text based on the aspect to identify at least one candidate value in the string of text, the at least one candidate value including a first candidate value; communicating the at least one candidate value to the user; receiving a rule including an aspect-value pair including the aspect and the first candidate value; publishing the rule in a production environment; associating the aspect-value pair to a first data item based on the published rule, the associating including concatenating the aspect-value pair to the first data item responsive to identifying the first candidate value in the first data item to generate the first data item including the concatenated aspect-value pair; receiving a first query; associating the aspect-value pair to the first query based on the rule; and identifying the first data item including the concatenated aspect-value pair for inclusion in an interface based on the associating the aspect-value pair to the first query based on the first rule; receiving a request to publish a dictionary for a particular domain in a preview environment in the network-based marketplace, the preview environment is being utilized to test a rule before the rule is applied to at least one of the first data item and the first query in a production environment, the dictionary including a plurality of domain rules being utilized to associate a first category on the network-based marketplace with a first product type, and the first category and the first product type further being associated with the first data item for sale on the network-based marketplace. 20. The method of claim 1 , further including receiving a request to publish the rule to the production environment in the network-based marketplace. | 0.780882 |
9,251,166 | 17 | 20 | 17. A non-transitory machine-readable storage medium having machine executable instructions embedded thereon, which when executed by a processor of a machine, cause the machine to perform operations comprising: retrieving a plurality of search queries; generating a plurality of search query nodes that represent one or more of the plurality of search queries; creating a visual representation of the search query nodes where one or more connections between the search query nodes indicate one or more relationships between two or more of the plurality of search queries; partitioning the visual representation into a plurality of tiles, each tile representing a defined portion of a rendering of the visual representation, each tile configured to be accessed independently of one or more other tiles of the plurality of tiles; and selecting a tile containing one of the plurality of search query nodes corresponding to the submitted search query, from the plurality of tiles, and one or more tiles surrounding the identified tile. | 17. A non-transitory machine-readable storage medium having machine executable instructions embedded thereon, which when executed by a processor of a machine, cause the machine to perform operations comprising: retrieving a plurality of search queries; generating a plurality of search query nodes that represent one or more of the plurality of search queries; creating a visual representation of the search query nodes where one or more connections between the search query nodes indicate one or more relationships between two or more of the plurality of search queries; partitioning the visual representation into a plurality of tiles, each tile representing a defined portion of a rendering of the visual representation, each tile configured to be accessed independently of one or more other tiles of the plurality of tiles; and selecting a tile containing one of the plurality of search query nodes corresponding to the submitted search query, from the plurality of tiles, and one or more tiles surrounding the identified tile. 20. The machine-readable storage medium of claim 17 , wherein the creating of the visual representation includes generating edges between representations of search queries based on the relationships between queries of the plurality of search queries. | 0.736287 |
10,025,564 | 1 | 6 | 1. A processor-implemented method of generating and implementing intuitively comfortable frames of task appropriate frames of reference for multiple dimensions of context constraints for related sets of objects within an integrated development environment (IDE), the processor-implemented method comprising: identifying, by one or more processors, a first hierarchical set of context constraints for a first object, wherein the first hierarchical set of context constraints for the first object includes multiple facets of context, and wherein the multiple facets of context comprise an operational environment context describing an operating system and hardware platform that must be used by the first object; depicting, by one or more processors, the first hierarchical set of context constraints for the first object on the IDE, wherein the first hierarchical set of context constraints is depicted by utilizing a visual metaphor selected by a user, wherein the visual metaphor selected by the user is a hierarchical stack of planes and pillars, wherein a top plane represents a top context for the first object, wherein a pillar connects the top plane to a lower plane that represents a lower context for the first object, and wherein the lower context supports the top context just as the lower plane supports the top plane via the pillar; receiving, by one or more processors, a first zoom-in input from the user, wherein the first zoom-in input is for a first context constraint in the first hierarchical set of context constraints; in response to receiving the first zoom-in input, one or more processors placing the IDE in mention mode, wherein use of the first hierarchical set of context constraints against the first object is disabled while the IDE is in mention mode; in response to the IDE being placed in mention mode, displaying, by one or more processors, detail of the first context constraint on the IDE; and receiving, by one or more processors, changes to the first context constraint that are input by the user from the IDE to create a modified first context constraint on the first object. | 1. A processor-implemented method of generating and implementing intuitively comfortable frames of task appropriate frames of reference for multiple dimensions of context constraints for related sets of objects within an integrated development environment (IDE), the processor-implemented method comprising: identifying, by one or more processors, a first hierarchical set of context constraints for a first object, wherein the first hierarchical set of context constraints for the first object includes multiple facets of context, and wherein the multiple facets of context comprise an operational environment context describing an operating system and hardware platform that must be used by the first object; depicting, by one or more processors, the first hierarchical set of context constraints for the first object on the IDE, wherein the first hierarchical set of context constraints is depicted by utilizing a visual metaphor selected by a user, wherein the visual metaphor selected by the user is a hierarchical stack of planes and pillars, wherein a top plane represents a top context for the first object, wherein a pillar connects the top plane to a lower plane that represents a lower context for the first object, and wherein the lower context supports the top context just as the lower plane supports the top plane via the pillar; receiving, by one or more processors, a first zoom-in input from the user, wherein the first zoom-in input is for a first context constraint in the first hierarchical set of context constraints; in response to receiving the first zoom-in input, one or more processors placing the IDE in mention mode, wherein use of the first hierarchical set of context constraints against the first object is disabled while the IDE is in mention mode; in response to the IDE being placed in mention mode, displaying, by one or more processors, detail of the first context constraint on the IDE; and receiving, by one or more processors, changes to the first context constraint that are input by the user from the IDE to create a modified first context constraint on the first object. 6. The processor-implemented method of claim 1 , further comprising: depicting, on the IDE and by one or more processors, only a context constraint that is at a top of the first hierarchical set of context constraints while the first hierarchical set of context constraints are being currently enforced against the first object that is presently executing. | 0.815161 |
9,286,295 | 15 | 19 | 15. An apparatus for tagging, the apparatus comprising a memory storing instructions which, when processed by one or more processors, cause: generating a multi-layer scannable tag that comprises a plurality of unique scannable layers; receiving an indication that the multi-layer scannable tag has been scanned by a first user; assigning a layer of the multi-layer scannable tag to the first user; receiving an image, audio, video, or other file from the first user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; linking the multi-layer scannable tag with the location in cloud storage using the URL link; tagging the image, audio, video, or other file with said multi-layer scannable tag; wherein such tagging is accomplished by means of the use of a mobile application, computer program or similar electronic device; receiving an indication that the multi-layer scannable tag has been scanned by a second user; assigning another layer of the multi-layer scannable tag to the second user; receiving an image, audio, video, or other file from the second user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; and linking the multi-layer scannable tag with the location in cloud storage using the URL link. | 15. An apparatus for tagging, the apparatus comprising a memory storing instructions which, when processed by one or more processors, cause: generating a multi-layer scannable tag that comprises a plurality of unique scannable layers; receiving an indication that the multi-layer scannable tag has been scanned by a first user; assigning a layer of the multi-layer scannable tag to the first user; receiving an image, audio, video, or other file from the first user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; linking the multi-layer scannable tag with the location in cloud storage using the URL link; tagging the image, audio, video, or other file with said multi-layer scannable tag; wherein such tagging is accomplished by means of the use of a mobile application, computer program or similar electronic device; receiving an indication that the multi-layer scannable tag has been scanned by a second user; assigning another layer of the multi-layer scannable tag to the second user; receiving an image, audio, video, or other file from the second user; storing the image, audio, video, or other file in a location in cloud storage; generating one unique URL link wherein that URL link is associated with the multi-layer scannable tag, the URL link also pointing to the location in cloud storage; and linking the multi-layer scannable tag with the location in cloud storage using the URL link. 19. The apparatus of claim 15 , the apparatus further comprising memory storing instructions which, when processed by one or more processors, cause generation of an interface wherein users may view through said interface their submitted video, photos or other files and the scannable tag and alpha numeric text code tagged and associated with each image. | 0.623404 |
10,152,469 | 1 | 9 | 1. A method implemented by a computing device comprising: adding at least one form control into a document for a host program module via a analytics plug-in for the host program module designed to obtain analytics data for the document through a connection established by the analytics plug-in with a marketing service; populating via the analytic plug-in, the at least one form control with filter parameters that include existing market segments, each market segment being a combination of segment parameters that describe information about a corresponding market segment, the at least one form control being selectable to cause retrieval of a corresponding sub-set of analytics data from the marketing service for inclusion in the document, wherein said sub-set of analytics data comprises a new and different combination of existing filtered analytics data; responsive to a selection of filter parameters from the at least one form control, querying the marketing service to obtain the corresponding sub-set of analytics data; and inserting the corresponding sub-set of analytics data into the document, wherein the analytics plug-in includes: analytics component that performs operations from within the host program module to facilitate analytics report creation, establish data connections to the marketing service, execute queries for analytics data and sub-sets of analytics data from the marketing service, and select the filter parameters to constrain the queries to selected segment, metrics, and time periods; and a bridge component that provides a communication interface between the analytics component and host program module. | 1. A method implemented by a computing device comprising: adding at least one form control into a document for a host program module via a analytics plug-in for the host program module designed to obtain analytics data for the document through a connection established by the analytics plug-in with a marketing service; populating via the analytic plug-in, the at least one form control with filter parameters that include existing market segments, each market segment being a combination of segment parameters that describe information about a corresponding market segment, the at least one form control being selectable to cause retrieval of a corresponding sub-set of analytics data from the marketing service for inclusion in the document, wherein said sub-set of analytics data comprises a new and different combination of existing filtered analytics data; responsive to a selection of filter parameters from the at least one form control, querying the marketing service to obtain the corresponding sub-set of analytics data; and inserting the corresponding sub-set of analytics data into the document, wherein the analytics plug-in includes: analytics component that performs operations from within the host program module to facilitate analytics report creation, establish data connections to the marketing service, execute queries for analytics data and sub-sets of analytics data from the marketing service, and select the filter parameters to constrain the queries to selected segment, metrics, and time periods; and a bridge component that provides a communication interface between the analytics component and host program module. 9. The method as described in claim 1 , wherein the one or more form controls are provided as built-in functionality of the host program module that is invoked via the analytics plugin. | 0.63 |
10,114,818 | 1 | 6 | 1. A method comprising: performing a generic web crawl to identify a first webpage in a first language having a link thereon which points to a second webpage in a second language, wherein the first webpage and the second webpage comprise a bilingual website; based on an analysis of parameters on the first webpage comprising at least two of: the link pointing to the second webpage, a title, a link neighborhood, a link context and data indicating a separate version of the first webpage, classifying the first webpage as a root page and as an entry point for the bilingual website via the link to the second webpage; performing a bidirectional web crawl between the first webpage and the second webpage to identify the first webpage and the second webpage as the bilingual website, the bidirectional web crawl utilizing classifications of links to avoid links having a low respective relevance; extracting information pairs from the first webpage and the second webpage for use in a language translation model, the information pairs comprising at least one of a word pair, a paragraph pair and a sentence pair; and updating a statistical model with domain representative data using the information pairs. | 1. A method comprising: performing a generic web crawl to identify a first webpage in a first language having a link thereon which points to a second webpage in a second language, wherein the first webpage and the second webpage comprise a bilingual website; based on an analysis of parameters on the first webpage comprising at least two of: the link pointing to the second webpage, a title, a link neighborhood, a link context and data indicating a separate version of the first webpage, classifying the first webpage as a root page and as an entry point for the bilingual website via the link to the second webpage; performing a bidirectional web crawl between the first webpage and the second webpage to identify the first webpage and the second webpage as the bilingual website, the bidirectional web crawl utilizing classifications of links to avoid links having a low respective relevance; extracting information pairs from the first webpage and the second webpage for use in a language translation model, the information pairs comprising at least one of a word pair, a paragraph pair and a sentence pair; and updating a statistical model with domain representative data using the information pairs. 6. The method of claim 1 , wherein the bidirectional web crawl considers back links and forward links. | 0.89901 |
9,754,040 | 15 | 23 | 15. A system, comprising: a non-transitory computer memory; and at least one hardware processor interoperably coupled with the non-transitory computer memory and configured to perform operations including: receiving, from a first client device, an identification of user group configuration settings for a user group comprising a plurality of users, the user group configuration settings identifying (i) a first plurality of content items available to be retrieved from a first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group; receiving, from a second client device that is different than the first client device, data identifying personal configuration settings that personalize a web page of the user group for a first user, the personal configuration settings for the first user specifying a second plurality of content items selected by the first user to be retrieved from a second plurality of remote content provider servers and to be included in the web page of the user group personalized for the first user; receiving, from the second client device, a request that identifies the web page of the user group, wherein the request includes a universal resource locator (URL) identifying the user group; in response to receiving the request that identifies the web page of the user group, determining, at least partly based on parsing the URL, that (i) the web page requested is for the user group, (ii) a user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received; in response to determining that (i) the web page requested is for the user group, (ii) the user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received, generating a first personal web page in accordance with both the user group configuration settings for the user group that identify (i) the first plurality of content items available to be retrieved from the first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group, and the personal configuration settings that personalize the web page of the user group to the first user, the first personal web page including: one or more visualizations of one or more of a first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; and one or more visualizations of a second plurality of content modules that provide the second plurality of content items from the second plurality of remote content provider servers; and sending the first personal web page over a network to the second client device. | 15. A system, comprising: a non-transitory computer memory; and at least one hardware processor interoperably coupled with the non-transitory computer memory and configured to perform operations including: receiving, from a first client device, an identification of user group configuration settings for a user group comprising a plurality of users, the user group configuration settings identifying (i) a first plurality of content items available to be retrieved from a first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group; receiving, from a second client device that is different than the first client device, data identifying personal configuration settings that personalize a web page of the user group for a first user, the personal configuration settings for the first user specifying a second plurality of content items selected by the first user to be retrieved from a second plurality of remote content provider servers and to be included in the web page of the user group personalized for the first user; receiving, from the second client device, a request that identifies the web page of the user group, wherein the request includes a universal resource locator (URL) identifying the user group; in response to receiving the request that identifies the web page of the user group, determining, at least partly based on parsing the URL, that (i) the web page requested is for the user group, (ii) a user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received; in response to determining that (i) the web page requested is for the user group, (ii) the user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received, generating a first personal web page in accordance with both the user group configuration settings for the user group that identify (i) the first plurality of content items available to be retrieved from the first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group, and the personal configuration settings that personalize the web page of the user group to the first user, the first personal web page including: one or more visualizations of one or more of a first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; and one or more visualizations of a second plurality of content modules that provide the second plurality of content items from the second plurality of remote content provider servers; and sending the first personal web page over a network to the second client device. 23. The system of claim 15 , the operations further comprising storing at least a portion of the user group configuration settings in a dynamic table. | 0.894811 |
8,610,744 | 2 | 4 | 2. The method of claim 1 , wherein: said determining the combined perpendicular and parallel motions of the change in position of the stylus comprises determining the stylus moving closer to the surface of the tablet device while moving parallel above the surface of the tablet device; and said initiating the combined zoom and pan display comprises zooming in on a portion of the digital image while panning the digital image in a direction of the parallel motion. | 2. The method of claim 1 , wherein: said determining the combined perpendicular and parallel motions of the change in position of the stylus comprises determining the stylus moving closer to the surface of the tablet device while moving parallel above the surface of the tablet device; and said initiating the combined zoom and pan display comprises zooming in on a portion of the digital image while panning the digital image in a direction of the parallel motion. 4. The method of claim 2 , wherein said initiating the combined zoom and pan display comprises zooming in on the portion of the digital image over which the stylus was positioned when the stylus moved closer to the tablet device. | 0.5 |
7,805,397 | 10 | 11 | 10. The method according to claim 1 , further comprising the step of interacting with a client device. | 10. The method according to claim 1 , further comprising the step of interacting with a client device. 11. The method according to claim 10 , wherein the client device is wireless. | 0.5 |
9,373,330 | 3 | 4 | 3. The method of claim 1 further comprising receiving, by a computer system, a set of signals corresponding to the speech utterances; and wherein representing the respective uncertainties of acoustic coverage in memory and computationally efficient manners include: computing, for each speech utterance of the set of speech utterances, a corresponding identity vector (i-vector), a diagonalized approximation of a covariance matrix of the corresponding i-vector, and a diagonalized approximation of an equivalent precision matrix associated with the corresponding i-vector; and further wherein: computing the score is based on the i-vectors, the diagonalized approximations of covariance matrices, and the diagonalized approximations of equivalent precision matrices computed, the score being indicative of a likelihood of a correspondence between the set of utterances received and a speaker. | 3. The method of claim 1 further comprising receiving, by a computer system, a set of signals corresponding to the speech utterances; and wherein representing the respective uncertainties of acoustic coverage in memory and computationally efficient manners include: computing, for each speech utterance of the set of speech utterances, a corresponding identity vector (i-vector), a diagonalized approximation of a covariance matrix of the corresponding i-vector, and a diagonalized approximation of an equivalent precision matrix associated with the corresponding i-vector; and further wherein: computing the score is based on the i-vectors, the diagonalized approximations of covariance matrices, and the diagonalized approximations of equivalent precision matrices computed, the score being indicative of a likelihood of a correspondence between the set of utterances received and a speaker. 4. The method of claim 3 , wherein computing the score includes computing the score for each speaker of a number of speakers known to the computer system, and the method further comprises: determining an identifier corresponding to the speaker having the highest score. | 0.849215 |
9,983,859 | 1 | 15 | 1. A computer system implemented method for deploying data science transformations from a development computing environment into a production computing environment, comprising: receiving, with one or more first computing systems, first transformation data representing one or more first transformations defined in a first programming language, the one or more first transformations operable on one or more operands to generate one or more results, wherein the one or more first computing systems are a development computing environment; receiving second transformation data representing one or more second transformations defined in a second programming language, the one or more second transformations operable on the one or more operands to generate the one or more results, wherein each of the one or more second transformations defined in the second programming language mirrors a corresponding one of the one or more first transformations defined in the first programming language, further wherein the second transformation data includes one or more configuration parameters for configuring physical and/or virtual resources to execute one or more transformations; associating the first transformation data with the second transformation data in a transformations data structure to associate the one or more first transformations with the one or more second transformations; storing the transformations data structure to one or more sections of memory associated with the one or more computing systems; receiving macro-transformation data representing a macro-transformation in the first programming language, the macro-transformation being a combination of multiple ones of the one or more first transformations that are logically connected to receive operand data for the macro-transformation and are logically connected to provide output data from the macro-transformation; compiling the first programming language macro-transformation data to generate executable code for the macro-transformation in the second programming language to enable deployment of the macro-transformation into one or more second computing systems while preserving a relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation, wherein compiling the macro-transformation data at least partially includes accessing contents of the transformations data structure that is stored in the one or more sections of memory; and deploying the executable code to the one or more second computing systems to enable the one or more second computing systems to interpret and execute the macro-transformation in the second programming language to provide services to a plurality of users that is at least partially based on a functionality of the macro-transformation, wherein the one or more second computing systems are the production environment. | 1. A computer system implemented method for deploying data science transformations from a development computing environment into a production computing environment, comprising: receiving, with one or more first computing systems, first transformation data representing one or more first transformations defined in a first programming language, the one or more first transformations operable on one or more operands to generate one or more results, wherein the one or more first computing systems are a development computing environment; receiving second transformation data representing one or more second transformations defined in a second programming language, the one or more second transformations operable on the one or more operands to generate the one or more results, wherein each of the one or more second transformations defined in the second programming language mirrors a corresponding one of the one or more first transformations defined in the first programming language, further wherein the second transformation data includes one or more configuration parameters for configuring physical and/or virtual resources to execute one or more transformations; associating the first transformation data with the second transformation data in a transformations data structure to associate the one or more first transformations with the one or more second transformations; storing the transformations data structure to one or more sections of memory associated with the one or more computing systems; receiving macro-transformation data representing a macro-transformation in the first programming language, the macro-transformation being a combination of multiple ones of the one or more first transformations that are logically connected to receive operand data for the macro-transformation and are logically connected to provide output data from the macro-transformation; compiling the first programming language macro-transformation data to generate executable code for the macro-transformation in the second programming language to enable deployment of the macro-transformation into one or more second computing systems while preserving a relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation, wherein compiling the macro-transformation data at least partially includes accessing contents of the transformations data structure that is stored in the one or more sections of memory; and deploying the executable code to the one or more second computing systems to enable the one or more second computing systems to interpret and execute the macro-transformation in the second programming language to provide services to a plurality of users that is at least partially based on a functionality of the macro-transformation, wherein the one or more second computing systems are the production environment. 15. The computer system implemented method of claim 1 , wherein the macro-transformation is an analytics model. | 0.925901 |
8,065,143 | 11 | 12 | 11. The computer-implemented method of claim 10 , further comprising receiving the non-speech data using a wireless connection. | 11. The computer-implemented method of claim 10 , further comprising receiving the non-speech data using a wireless connection. 12. The computer-implemented method of claim 11 , wherein the non-speech data comprises punctuation, symbols or typeface data. | 0.5 |
8,849,034 | 29 | 30 | 29. An apparatus for handwriting recognition trigger comprising: a touch screen and a pen for drawing one or more strokes of a desired sub-word unit, wherein one of the drawn one or more strokes is a first head-line stroke and is a last drawn stroke in the drawn one or more strokes of the desired sub-word unit; a handwriting recognition engine coupled to the touch screen that is responsive to the one or more strokes of the desired sub-word unit, wherein the handwriting recognition engine computes stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope, determines a first trigger stroke in the drawn one or more strokes of the desired sub-word unit that can be used to trigger the desired sub-word unit recognition based as a function of the computed stroke recognition characteristics of each of the multiple drawn strokes, wherein the first trigger stroke is the first head-line stroke which is drawn substantially parallel to the horizontal reference line, and triggers sub-word unit recognition for the drawn one or more strokes based on the determined first trigger stroke, and wherein the handwriting recognition engine to produce a first candidate sub-word unit upon triggering the sub-word unit recognition; and a display device coupled to the handwriting recognition engine to display the produced first candidate sub-word unit. | 29. An apparatus for handwriting recognition trigger comprising: a touch screen and a pen for drawing one or more strokes of a desired sub-word unit, wherein one of the drawn one or more strokes is a first head-line stroke and is a last drawn stroke in the drawn one or more strokes of the desired sub-word unit; a handwriting recognition engine coupled to the touch screen that is responsive to the one or more strokes of the desired sub-word unit, wherein the handwriting recognition engine computes stroke recognition characteristics of each of the drawn one or more strokes with reference to a horizontal reference line, wherein the stroke recognition characteristics are selected from the group comprising aspect ratio and slope, determines a first trigger stroke in the drawn one or more strokes of the desired sub-word unit that can be used to trigger the desired sub-word unit recognition based as a function of the computed stroke recognition characteristics of each of the multiple drawn strokes, wherein the first trigger stroke is the first head-line stroke which is drawn substantially parallel to the horizontal reference line, and triggers sub-word unit recognition for the drawn one or more strokes based on the determined first trigger stroke, and wherein the handwriting recognition engine to produce a first candidate sub-word unit upon triggering the sub-word unit recognition; and a display device coupled to the handwriting recognition engine to display the produced first candidate sub-word unit. 30. The apparatus of claim 29 , wherein the stylus selects the displayed first candidate sub-word unit by touching the displayed first candidate sub-word unit. | 0.925978 |
7,734,996 | 1 | 24 | 1. Documentation browsing apparatus characterized by comprising: correspondence generating means for generating correspondence between voices or images included in audio data or image data and a document included in document data; association displaying means for displaying the voices or the images included in said audio data or said image data and a document included in said document data associated with each other based on said correspondence; document updating means for updating said document data based on user editing instruction; and matching means for establishing a matching between a document and sounds or images; wherein said correspondence generating means comprises: means for generating association information based on said matching established by said matching means; relationship recalculation instruction means for outputting recalculation instruction information for instructing recalculation of relationship between a document and voices or images and letting the matching means recalculate said relationship when said document data is updated. | 1. Documentation browsing apparatus characterized by comprising: correspondence generating means for generating correspondence between voices or images included in audio data or image data and a document included in document data; association displaying means for displaying the voices or the images included in said audio data or said image data and a document included in said document data associated with each other based on said correspondence; document updating means for updating said document data based on user editing instruction; and matching means for establishing a matching between a document and sounds or images; wherein said correspondence generating means comprises: means for generating association information based on said matching established by said matching means; relationship recalculation instruction means for outputting recalculation instruction information for instructing recalculation of relationship between a document and voices or images and letting the matching means recalculate said relationship when said document data is updated. 24. A documentation browsing robot comprising documentation browsing apparatus described in claim 1 . | 0.928973 |
9,967,159 | 25 | 26 | 25. The device of claim 24 , wherein the processor readable memory further comprises one or more additional instructions that, when executed by the processor, further cause the processor to communicate a deployment approval notification to the second computing device. | 25. The device of claim 24 , wherein the processor readable memory further comprises one or more additional instructions that, when executed by the processor, further cause the processor to communicate a deployment approval notification to the second computing device. 26. The device of claim 25 , wherein the processor readable memory further comprises one or more additional instructions that, when executed by the processor, further cause the processor to deploy the workload only when the deployment approval notification is relayed back by the second computing device. | 0.5 |
9,652,450 | 1 | 2 | 1. A computer-implemented method for automatically extracting claim candidates from complex sentences, the method executed by a processor of the computer comprising the steps of: (a) providing a parse tree of a text sample to be analyzed; (b) disassembling the parse tree into a set of basic meaning-bearing clauses; (c) assembling clauses of the set of basic clauses into a set of complex coherent statements based on permissible syntactic structures; (d) testing the complex statements and discarding those statements that are not coherent when considered alone; (e) discarding those complex statements that either do not provide additional information about a subject, or are too complex; (f) removing information from a complex statement that provides supportive details about the subject; and (g) discarding statements that restrict their subject, so that the subject cannot be generalized encompass a broader subject. | 1. A computer-implemented method for automatically extracting claim candidates from complex sentences, the method executed by a processor of the computer comprising the steps of: (a) providing a parse tree of a text sample to be analyzed; (b) disassembling the parse tree into a set of basic meaning-bearing clauses; (c) assembling clauses of the set of basic clauses into a set of complex coherent statements based on permissible syntactic structures; (d) testing the complex statements and discarding those statements that are not coherent when considered alone; (e) discarding those complex statements that either do not provide additional information about a subject, or are too complex; (f) removing information from a complex statement that provides supportive details about the subject; and (g) discarding statements that restrict their subject, so that the subject cannot be generalized encompass a broader subject. 2. The method of claim 1 , further comprising ranking remaining statements based on their complexity, wherein a set of candidate statements ranked according to their complexity is output. | 0.801064 |
8,693,942 | 4 | 6 | 4. The method of claim 1 , further comprising encoding said at least one question using a third parameter comprising question type classification. | 4. The method of claim 1 , further comprising encoding said at least one question using a third parameter comprising question type classification. 6. The method of claim 4 , wherein said acts of encoding comprise assigning a multi-digit code to said at least one question, each of said digits corresponding to respective ones of said parameters, the value of each of said digit representing a particular type of parameter. | 0.5 |
6,138,128 | 4 | 5 | 4. The method of claim 1, further including the steps of: displaying a visual indication of each of the lists of web pages; and indicating in conjunction with the displayed visual indication of each of the lists of web pages whether the visited web page is included in the list. | 4. The method of claim 1, further including the steps of: displaying a visual indication of each of the lists of web pages; and indicating in conjunction with the displayed visual indication of each of the lists of web pages whether the visited web page is included in the list. 5. The method of claim 4 wherein the displaying step displays, for each list of web pages, information about a distinctive character reflecting the common subject matter of the web pages in the list. | 0.5 |
8,977,536 | 1 | 6 | 1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct. | 1. A method comprising: executing instructions stored in memory via a processor of a language engine for: training the language engine to train for statistical machine translation; training the language engine when to use statistical machine translation by applying a machine learning method to a bilingual text that has been annotated with the output of a non-statistical translation component along with information identifying the type of the translation component; translating information from a first language to a second language using at least two translation components, wherein at least one translation component is a non-statistical translation component, each of the at least two translation components capable of translating equivalent phrases, each of the at least two translation components being selected based upon evaluation of an annotated training corpus, the annotated training corpus comprising substrings in the first language that have been annotated to associate the substrings with one or more translation components that are to be utilized to translate the substrings; and automatically selecting a preferred component from the at least two translation components, the preferred component providing a translation having a highest probability of being correct. 6. A method as in claim 1 , wherein a first component of the at least two translation components comprises a statistical translator and a second component of the at least two translation components comprises a nonstatistical translator for proper nouns. | 0.653425 |
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