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9,292,574 | 9 | 10 | 9. A computer-implemented method, comprising: determining, by a computing system, a tactical query configured to enable pulling business event data from a database to a query engine; configuring, based at least in part on an indication of the business event data to be displayed, the query engine with the tactical query; receiving a first request, from a user associated with the business event data, associated with generating an active visualization of the business event data only for the user, the first request to activate the visualization comprising at least a request to collapse the business event data into one or more objects and to update the one or more objects based at least in part on a user-specified time interval; converting at runtime, by the computing system at runtime, the tactical query to a continuous query configured to enable a stream of the business event data of the user to be pushed to the query engine and to enable generation of one or more hybrid queries for executing with a combination of the continuous query and a scheduled database query; registering a listening service to receive data pushed from the stream of the business event data; executing the continuous query against the stream of business event data; receiving, during execution of the continuous query, a second request to change a dimension of the continuous query; changing the dimension of the continuous query via a dashboard at runtime based at least in part on the second request; and providing a user interface configured to display the active visualization based at least in part on the streaming business event data pushed to the query engine. | 9. A computer-implemented method, comprising: determining, by a computing system, a tactical query configured to enable pulling business event data from a database to a query engine; configuring, based at least in part on an indication of the business event data to be displayed, the query engine with the tactical query; receiving a first request, from a user associated with the business event data, associated with generating an active visualization of the business event data only for the user, the first request to activate the visualization comprising at least a request to collapse the business event data into one or more objects and to update the one or more objects based at least in part on a user-specified time interval; converting at runtime, by the computing system at runtime, the tactical query to a continuous query configured to enable a stream of the business event data of the user to be pushed to the query engine and to enable generation of one or more hybrid queries for executing with a combination of the continuous query and a scheduled database query; registering a listening service to receive data pushed from the stream of the business event data; executing the continuous query against the stream of business event data; receiving, during execution of the continuous query, a second request to change a dimension of the continuous query; changing the dimension of the continuous query via a dashboard at runtime based at least in part on the second request; and providing a user interface configured to display the active visualization based at least in part on the streaming business event data pushed to the query engine. 10. The computer-implemented method of claim 9 , further comprising receiving a third request to apply a filter to the continuous query or to change a dimension of the continuous query. | 0.573733 |
8,271,264 | 1 | 10 | 1. A system for knowledge representation in a computer that can enable natural language communication with a computer, the system comprising: at least one hardware processor; at least one database configured to store at least one table, the at least one table configured to store associations between concepts in a body of text and associated concept identifiers; and a builder interfaced with the database, the builder configured to, when executed by the at least one hardware processor, construct a table that represents knowledge defined by a body of text comprising words and punctuation, the construction of the table comprising assigning a unique identifier to an observation concept defined by the body of text, building a tree comprising a plurality of sub-concepts by breaking the observation concept into sub-concepts by identifying a subject concept, a seam concept, and a relative concept, and joining sub-concepts into higher order sub-concepts until two or more sub-concepts join to form the concept, wherein said joining comprises constructing a binary concept by either joining the subject concept and the seam concept or joining the seam concept and the relative concept, and constructing a first higher order sub-concept by joining either the relative concept or the subject concept with the binary concept, assigning unique identifiers to each of the plurality of sub-concepts including the subject concept, the seam concept, the relative concept, the binary concept, and the first higher order sub-concept, wherein the unique identifiers assigned to the observation concept and each of the plurality of sub-concepts are generated according to the same scheme, and storing each of the concept and plurality of sub-concepts in a row in the at least one table, wherein each row comprises the concept or sub-concept, the unique identifier assigned to the concept or sub-concept, and the unique identifiers assigned to two or more lower order sub-concepts, if any, which were joined to form the concept or sub-concept; wherein the plurality of sub-concepts comprise at least each of the words and punctuation in the body of text. | 1. A system for knowledge representation in a computer that can enable natural language communication with a computer, the system comprising: at least one hardware processor; at least one database configured to store at least one table, the at least one table configured to store associations between concepts in a body of text and associated concept identifiers; and a builder interfaced with the database, the builder configured to, when executed by the at least one hardware processor, construct a table that represents knowledge defined by a body of text comprising words and punctuation, the construction of the table comprising assigning a unique identifier to an observation concept defined by the body of text, building a tree comprising a plurality of sub-concepts by breaking the observation concept into sub-concepts by identifying a subject concept, a seam concept, and a relative concept, and joining sub-concepts into higher order sub-concepts until two or more sub-concepts join to form the concept, wherein said joining comprises constructing a binary concept by either joining the subject concept and the seam concept or joining the seam concept and the relative concept, and constructing a first higher order sub-concept by joining either the relative concept or the subject concept with the binary concept, assigning unique identifiers to each of the plurality of sub-concepts including the subject concept, the seam concept, the relative concept, the binary concept, and the first higher order sub-concept, wherein the unique identifiers assigned to the observation concept and each of the plurality of sub-concepts are generated according to the same scheme, and storing each of the concept and plurality of sub-concepts in a row in the at least one table, wherein each row comprises the concept or sub-concept, the unique identifier assigned to the concept or sub-concept, and the unique identifiers assigned to two or more lower order sub-concepts, if any, which were joined to form the concept or sub-concept; wherein the plurality of sub-concepts comprise at least each of the words and punctuation in the body of text. 10. The system of claim 1 , wherein each row of the at least one table further comprises a field comprising a response, if any, associated with the corresponding concept or sub-concept. | 0.756579 |
10,083,154 | 1 | 3 | 1. A mobile hand-held device, comprising: a processor; a wireless communications device, to facilitate wireless communication with a network that supports access to the Internet; a touch-sensitive display; and flash memory, operatively coupled to the processor, in which a plurality of instructions are stored comprising a plurality of software components including an HTML rendering engine, wherein the instructions are configured to be executed by the processor to enable the mobile hand-held device to, receive an HTML document including HTML code and cascading style sheet (CSS) code and content associated with the HTML document, the HTML code comprising a plurality of HTML elements including at least one HTML paragraph element, at least one HTML image element, and at least one HTML hyperlink element; process the HTML document with the HTML rendering engine to render a first representation of the HTML document having an interpreted page layout, functionality, and design of the content associated with the HTML document that is in accordance with the HTML code and CSS code, wherein rendering the first representation of the HTML document includes, parsing the HTML document to identify the plurality of HTML elements; logically grouping content associated with HTML elements into HTML objects; generating page layout information including a bounding box for each HTML object; and storing information that links each HTML object with its corresponding page layout information, wherein the page layout information further includes information from which a page layout location of each of the bounding boxes can be determined; translate the first representation of the HTML document to generate a scalable vector representation of the HTML document wherein generating the scalable vector representation includes, defining a primary datum corresponding to the interpreted page layout; for each HTML object, defining an object datum corresponding to a layout location datum for the HTML object's bounding box; generating a vector from the primary datum to the object datum for the HTML object's bounding box; and creating a reference that links the HTML object to the vector that is generated; and render the scalable vector representation of the HTML document on the touch-sensitive display using a first scale factor to display the HTML document at a first zoom level under which the HTML document is displayed to fit across a width of the touch-sensitive display, wherein the scalable vector representation of the HTML document is configured to enable a user to view the HTML document at one or more user-defined zoom levels by rendering the scalable vector representation on the touch-sensitive display using one or more respective scale factors in response to associated user inputs made via the touch-sensitive display, and wherein the interpreted page layout, functionality, and design of the content associated with the HTML document is preserved at each of the first zoom level and the one or more user-defined zoom levels. | 1. A mobile hand-held device, comprising: a processor; a wireless communications device, to facilitate wireless communication with a network that supports access to the Internet; a touch-sensitive display; and flash memory, operatively coupled to the processor, in which a plurality of instructions are stored comprising a plurality of software components including an HTML rendering engine, wherein the instructions are configured to be executed by the processor to enable the mobile hand-held device to, receive an HTML document including HTML code and cascading style sheet (CSS) code and content associated with the HTML document, the HTML code comprising a plurality of HTML elements including at least one HTML paragraph element, at least one HTML image element, and at least one HTML hyperlink element; process the HTML document with the HTML rendering engine to render a first representation of the HTML document having an interpreted page layout, functionality, and design of the content associated with the HTML document that is in accordance with the HTML code and CSS code, wherein rendering the first representation of the HTML document includes, parsing the HTML document to identify the plurality of HTML elements; logically grouping content associated with HTML elements into HTML objects; generating page layout information including a bounding box for each HTML object; and storing information that links each HTML object with its corresponding page layout information, wherein the page layout information further includes information from which a page layout location of each of the bounding boxes can be determined; translate the first representation of the HTML document to generate a scalable vector representation of the HTML document wherein generating the scalable vector representation includes, defining a primary datum corresponding to the interpreted page layout; for each HTML object, defining an object datum corresponding to a layout location datum for the HTML object's bounding box; generating a vector from the primary datum to the object datum for the HTML object's bounding box; and creating a reference that links the HTML object to the vector that is generated; and render the scalable vector representation of the HTML document on the touch-sensitive display using a first scale factor to display the HTML document at a first zoom level under which the HTML document is displayed to fit across a width of the touch-sensitive display, wherein the scalable vector representation of the HTML document is configured to enable a user to view the HTML document at one or more user-defined zoom levels by rendering the scalable vector representation on the touch-sensitive display using one or more respective scale factors in response to associated user inputs made via the touch-sensitive display, and wherein the interpreted page layout, functionality, and design of the content associated with the HTML document is preserved at each of the first zoom level and the one or more user-defined zoom levels. 3. The mobile hand-held device of claim 1 , wherein the mobile hand-held device is a hand-held computer. | 0.902622 |
9,318,108 | 2 | 23 | 2. A method for implementing an automated assistant on one or more computing devices having one or more processors and memory, the method comprising: at the one or more computing devices: invoking the automated assistant; causing a first output to be displayed, wherein the first output comprises a plurality of core competencies of the automated assistant and an example of a natural language input for invoking each of the plurality of core competencies; at an input device, receiving user input; interpreting the received user input to derive a representation of user intent; identifying at least one task based at least in part on the derived representation of user intent; calling at least one service for performing the identified task; and causing a second output to be displayed based on data received from the at least one called service; wherein the first output is displayed prior to receiving the user input. | 2. A method for implementing an automated assistant on one or more computing devices having one or more processors and memory, the method comprising: at the one or more computing devices: invoking the automated assistant; causing a first output to be displayed, wherein the first output comprises a plurality of core competencies of the automated assistant and an example of a natural language input for invoking each of the plurality of core competencies; at an input device, receiving user input; interpreting the received user input to derive a representation of user intent; identifying at least one task based at least in part on the derived representation of user intent; calling at least one service for performing the identified task; and causing a second output to be displayed based on data received from the at least one called service; wherein the first output is displayed prior to receiving the user input. 23. The method of claim 2 , wherein one of the plurality of core competencies is getting a weather forecast. | 0.907057 |
9,679,558 | 14 | 18 | 14. A computerized system for training a language model for a target domain using style, content, and statistical data from one or more data sources comprising: one or more computer processors; computer memory storing computer-useable instructions that, when used by the one or more computer processors, cause the one or more computer processors to perform operations comprising: accessing a portion of a knowledge graph corresponding to the target domain, wherein the target domain corresponds to a category of entities, the portion of the knowledge graph further corresponding to one or more entities in the target domain; identifying the one or more data sources that correspond to the portion of the knowledge graph and the targeted domain; determining style data, content data, and statistical data in the one or more data sources; extracting the style data, the content data, and the statistical data from the one or more data sources; integrating the style data, the content data, and the statistical data extracted from the one or more data sources; assigning a probability to at least a portion of one or more entities corresponding to the portion of the knowledge graph, based on the statistical data; and utilizing the style data, the content data, and the assigned probabilities to train the language model for the conversational language input, thereby forming an improved language model; and utilizing the improved language model for automatic language recognition, conversational understanding (CU), or spoken language understanding (SLU). | 14. A computerized system for training a language model for a target domain using style, content, and statistical data from one or more data sources comprising: one or more computer processors; computer memory storing computer-useable instructions that, when used by the one or more computer processors, cause the one or more computer processors to perform operations comprising: accessing a portion of a knowledge graph corresponding to the target domain, wherein the target domain corresponds to a category of entities, the portion of the knowledge graph further corresponding to one or more entities in the target domain; identifying the one or more data sources that correspond to the portion of the knowledge graph and the targeted domain; determining style data, content data, and statistical data in the one or more data sources; extracting the style data, the content data, and the statistical data from the one or more data sources; integrating the style data, the content data, and the statistical data extracted from the one or more data sources; assigning a probability to at least a portion of one or more entities corresponding to the portion of the knowledge graph, based on the statistical data; and utilizing the style data, the content data, and the assigned probabilities to train the language model for the conversational language input, thereby forming an improved language model; and utilizing the improved language model for automatic language recognition, conversational understanding (CU), or spoken language understanding (SLU). 18. The computerized system of claim 14 , wherein the one or more data sources include a query click log, a web document, a user feed, a web search, a multimodal data source, or user-interactional data source. | 0.692647 |
8,522,203 | 1 | 5 | 1. A computer-implemented method, comprising: associating an event with an object of a form using a form creation application module; generating, using a script generator associated with the form creation application module, a script to perform a function during use of the form based on the event and the object, the script including one or more snippets, each snippet including a header having an edit verification value and an identification associated with the script; using a processor, associating data with the script, wherein the data comprises a management flag indicating whether or not a script manager should manage the script; after the generating of the script, parsing the script, using the script generator, to determine whether the script has been edited outside of the script generator, the parsing linking the one or more snippets to the script based on the identification found in each snippet header, whereby the modification of one of the edit verification values results in all snippets in the script being removed from management; and in response to a determination that the script has been edited outside of the script generator, modifying the management flag to indicate the script manager should not manage the script. | 1. A computer-implemented method, comprising: associating an event with an object of a form using a form creation application module; generating, using a script generator associated with the form creation application module, a script to perform a function during use of the form based on the event and the object, the script including one or more snippets, each snippet including a header having an edit verification value and an identification associated with the script; using a processor, associating data with the script, wherein the data comprises a management flag indicating whether or not a script manager should manage the script; after the generating of the script, parsing the script, using the script generator, to determine whether the script has been edited outside of the script generator, the parsing linking the one or more snippets to the script based on the identification found in each snippet header, whereby the modification of one of the edit verification values results in all snippets in the script being removed from management; and in response to a determination that the script has been edited outside of the script generator, modifying the management flag to indicate the script manager should not manage the script. 5. The method of claim 1 , wherein the script comprises a plurality of snippets, wherein each of the snippets comprises a header with an object identification (ID), and wherein the object ID is equal for each of the snippets of the script. | 0.776217 |
9,141,695 | 1 | 4 | 1. A method for creating a playlist based on a search query, wherein the playlist comprises a plurality of audio microposts, the method being implemented in a computer that includes one or more physical processors programmed with one or more computer program instructions that, when executed by the one or more physical processors, programs the computer to perform the method, the method comprising: obtaining, by the computer, a search query comprising one or more hashtags and/or keywords; obtaining, by the computer, a plurality of audio microposts that are associated with the one or more hashtags and/or keywords, wherein each individual audio micropost of the plurality of audio microposts is associated with a run time length that is less than a predetermined time limit; ranking, by the computer, the plurality of audio microposts based on one or more ranking criteria; determining, by computer, a playback order of the plurality of audio microposts based on the ranking; creating, by the computer, a playlist comprising the plurality of audio microposts arranged based on the playback order; causing, by the computer, a playback of the playlist to occur in accordance with the playback order; receiving, by the computer, a new audio input during the playback; generating, by the computer, a new audio micropost based on the new audio input; obtaining, by the computer, an indication that the new audio input is associated with the one or more hashtags and/or keywords; associating, by the computer, the new audio micropost with the playlist based on the indication; and automatically adding, by the computer, the new audio micropost to the playlist based on the association; and receiving, by the computer, authorization information from a user, the authorization information comprising an indication of whether one or more other users are authorized to generate audio microposts to the playlist. | 1. A method for creating a playlist based on a search query, wherein the playlist comprises a plurality of audio microposts, the method being implemented in a computer that includes one or more physical processors programmed with one or more computer program instructions that, when executed by the one or more physical processors, programs the computer to perform the method, the method comprising: obtaining, by the computer, a search query comprising one or more hashtags and/or keywords; obtaining, by the computer, a plurality of audio microposts that are associated with the one or more hashtags and/or keywords, wherein each individual audio micropost of the plurality of audio microposts is associated with a run time length that is less than a predetermined time limit; ranking, by the computer, the plurality of audio microposts based on one or more ranking criteria; determining, by computer, a playback order of the plurality of audio microposts based on the ranking; creating, by the computer, a playlist comprising the plurality of audio microposts arranged based on the playback order; causing, by the computer, a playback of the playlist to occur in accordance with the playback order; receiving, by the computer, a new audio input during the playback; generating, by the computer, a new audio micropost based on the new audio input; obtaining, by the computer, an indication that the new audio input is associated with the one or more hashtags and/or keywords; associating, by the computer, the new audio micropost with the playlist based on the indication; and automatically adding, by the computer, the new audio micropost to the playlist based on the association; and receiving, by the computer, authorization information from a user, the authorization information comprising an indication of whether one or more other users are authorized to generate audio microposts to the playlist. 4. The method of claim 1 , wherein the one or more ranking criteria comprise a relevance of the plurality of audio microposts to the search query and/or one or more metadata tags associated with the plurality of audio microposts. | 0.793694 |
8,756,231 | 8 | 9 | 8. The system of claim 6 , wherein documents in the clustered hierarchical data structure are initially provided by a publisher. | 8. The system of claim 6 , wherein documents in the clustered hierarchical data structure are initially provided by a publisher. 9. The system of claim 8 , wherein the documents are each learned based on search queries and feedback. | 0.5 |
9,152,622 | 9 | 13 | 9. A personalized machine translation system, the system comprising: a feedback processor that receives translator feedback regarding machine translations generated by a machine translation system for a translator, the machine translation system using a translation methodology; a feedback classifier that determines translator feedback that improves translations generated by the machine translation system, the translator feedback comprising a triple having a source unit, a translation unit of the source unit, and a correction unit; a dictionary pusher that incorporates the translator feedback into the translation methodology of the machine translation system to personalize the translation methodology; and a dictionary extractor that: constructs a first translation table that comprises pairs of source units and correction units; extracts dictionary entries from the translator feedback by: preparing the pairs for alignment, aligning words included in the pairs, and extracting first phrase pairs based upon word alignment; constructs a second translation table that comprises pairs of source units and translation units; and extracts dictionary entries from the translator feedback by: preparing the pairs for alignment, aligning words included in the pairs, and extracting second phrase pairs based upon word alignment; and filters the first and second phrase pairs by: selecting first and second phrase pairs having a threshold amount of words included in the phrase, selecting first and second phrase pairs that have terminal words which are aligned, and storing the selected first and second phrase pairs in a translation phrase table that resides on a data repository. | 9. A personalized machine translation system, the system comprising: a feedback processor that receives translator feedback regarding machine translations generated by a machine translation system for a translator, the machine translation system using a translation methodology; a feedback classifier that determines translator feedback that improves translations generated by the machine translation system, the translator feedback comprising a triple having a source unit, a translation unit of the source unit, and a correction unit; a dictionary pusher that incorporates the translator feedback into the translation methodology of the machine translation system to personalize the translation methodology; and a dictionary extractor that: constructs a first translation table that comprises pairs of source units and correction units; extracts dictionary entries from the translator feedback by: preparing the pairs for alignment, aligning words included in the pairs, and extracting first phrase pairs based upon word alignment; constructs a second translation table that comprises pairs of source units and translation units; and extracts dictionary entries from the translator feedback by: preparing the pairs for alignment, aligning words included in the pairs, and extracting second phrase pairs based upon word alignment; and filters the first and second phrase pairs by: selecting first and second phrase pairs having a threshold amount of words included in the phrase, selecting first and second phrase pairs that have terminal words which are aligned, and storing the selected first and second phrase pairs in a translation phrase table that resides on a data repository. 13. The system according to claim 9 , wherein the translator feedback includes corrections that are received from the translator relative to a previous translation generated by the machine translation system. | 0.733333 |
9,253,436 | 2 | 4 | 2. The video playback device according to claim 1 , wherein the text-list-display-after-video-playback control unit includes a specific text repeat display control unit which controls to hide the sound-attached video portion for the specific text and display the specific text for a predetermined time length after each time the sound-attached video portion for the specific text is played. | 2. The video playback device according to claim 1 , wherein the text-list-display-after-video-playback control unit includes a specific text repeat display control unit which controls to hide the sound-attached video portion for the specific text and display the specific text for a predetermined time length after each time the sound-attached video portion for the specific text is played. 4. The video playback device according to claim 2 , wherein the specific text repeat display control unit includes a predetermined time length setting control unit which controls to set the predetermined time length according to a length of the specific text. | 0.602761 |
8,239,206 | 3 | 4 | 3. The computer program product of claim 1 , wherein the data represents an audio recording of the orally-provided voice query, and wherein the orally-provided voice query was received by the computing device in response to a user selection of a button that is provided by the computing device for submitting voice queries. | 3. The computer program product of claim 1 , wherein the data represents an audio recording of the orally-provided voice query, and wherein the orally-provided voice query was received by the computing device in response to a user selection of a button that is provided by the computing device for submitting voice queries. 4. The computer program product of claim 3 , wherein a content of the textual query includes words of a human-understandable language. | 0.5 |
7,769,739 | 11 | 12 | 11. The method of claim 10 , wherein the received search query comprises a search parameter; wherein the search result comprises at least one item if the at least one item is listed in the selected list of items and the at least one item satisfies the search parameter. | 11. The method of claim 10 , wherein the received search query comprises a search parameter; wherein the search result comprises at least one item if the at least one item is listed in the selected list of items and the at least one item satisfies the search parameter. 12. The method of claim 11 , wherein the search parameter comprises a name of the item. | 0.5 |
8,306,965 | 12 | 13 | 12. The computer readable medium of claim 11 , the method further comprising identifying at least one category of documents in the search results, and wherein the number of experts that have tagged each of the plurality of documents comprise a number of experts that have tagged each of the plurality of documents as belonging to the at least one category. | 12. The computer readable medium of claim 11 , the method further comprising identifying at least one category of documents in the search results, and wherein the number of experts that have tagged each of the plurality of documents comprise a number of experts that have tagged each of the plurality of documents as belonging to the at least one category. 13. The computer readable medium of claim 12 , wherein the provider device deems a user an expert by receiving a tag specified by the user for each of a plurality of documents in at least one search result set, the user indicating therewith that the tagged documents belong to at least one category of documents and communicating the tagged documents to a plurality of other users, wherein the provider device deems the user an expert based on a number of other users that agree with the tags specified by the user. | 0.5 |
9,703,982 | 7 | 11 | 7. An electronic signature system that comprises: a document repository storing (a) a document comprising a plurality of document terms, (b) instructions for generating a recorded assent to the document terms, and (c) metadata indicating a status of the document with respect to a workflow; a configuration module configured to generate the instructions in response to a request received from a document originator, wherein the instructions define a verbal assent and a gesticulated assent; and an interactivity module configured to receive a recorded assent from a document recipient, wherein the recorded assent comprises an audiovisual recording of the verbal assent and the gesticulated assent, and wherein the interactivity module is further configured to authenticate the recorded assent based at least in part on a voiceprint extracted from the verbal assent. | 7. An electronic signature system that comprises: a document repository storing (a) a document comprising a plurality of document terms, (b) instructions for generating a recorded assent to the document terms, and (c) metadata indicating a status of the document with respect to a workflow; a configuration module configured to generate the instructions in response to a request received from a document originator, wherein the instructions define a verbal assent and a gesticulated assent; and an interactivity module configured to receive a recorded assent from a document recipient, wherein the recorded assent comprises an audiovisual recording of the verbal assent and the gesticulated assent, and wherein the interactivity module is further configured to authenticate the recorded assent based at least in part on a voiceprint extracted from the verbal assent. 11. The electronic signature system of claim 7 , further comprising a document status module configured to define a logical association between the authenticated recorded assent and the document. | 0.766746 |
9,619,118 | 15 | 21 | 15. A non-transitory computer readable medium storing instructions, the instructions when executed by a processor causing the processor to: display, on a touchscreen of a user device, a first browse wheel having a circular shape and comprising a plurality of category regions within the first browse wheel, each category region associated with an application category and having a visual representation of the associated application category; receive a user selection of an application category, the user selection of the application category comprising a touchscreen interaction with the first browse wheel; display, in response to the received user selection, a second browse wheel having a circular shape and comprising a plurality of subcategory regions within the second browse wheel, each subcategory region associated with an application subcategory of the selected application category and including a visual representation of the associated application subcategory, wherein a center of the second browse wheel is at location of the touchscreen; receive a user selection of an application subcategory, the user selection of the application subcategory comprising a touchscreen interaction with the second browse wheel; generate, in response to the received user selection of the application subcategory, an application search query using the selected application category and the selected application subcategory; and in response to receiving search results corresponding to the application search query, display a search results interface, wherein the search results interface includes: a set of applications specified by the search results; and only a portion of the second browse wheel, wherein the portion of the second browse wheel (i) is centered at a second location of the touchscreen that is different than the first location, (ii) is less than an entirety of the second browse wheel, (iii) includes at least the subcategory region associated with the selected application subcategory, and (iv) is adjoining an edge of the touchscreen of the user device. | 15. A non-transitory computer readable medium storing instructions, the instructions when executed by a processor causing the processor to: display, on a touchscreen of a user device, a first browse wheel having a circular shape and comprising a plurality of category regions within the first browse wheel, each category region associated with an application category and having a visual representation of the associated application category; receive a user selection of an application category, the user selection of the application category comprising a touchscreen interaction with the first browse wheel; display, in response to the received user selection, a second browse wheel having a circular shape and comprising a plurality of subcategory regions within the second browse wheel, each subcategory region associated with an application subcategory of the selected application category and including a visual representation of the associated application subcategory, wherein a center of the second browse wheel is at location of the touchscreen; receive a user selection of an application subcategory, the user selection of the application subcategory comprising a touchscreen interaction with the second browse wheel; generate, in response to the received user selection of the application subcategory, an application search query using the selected application category and the selected application subcategory; and in response to receiving search results corresponding to the application search query, display a search results interface, wherein the search results interface includes: a set of applications specified by the search results; and only a portion of the second browse wheel, wherein the portion of the second browse wheel (i) is centered at a second location of the touchscreen that is different than the first location, (ii) is less than an entirety of the second browse wheel, (iii) includes at least the subcategory region associated with the selected application subcategory, and (iv) is adjoining an edge of the touchscreen of the user device. 21. The non-transitory computer readable medium of claim 15 , further comprising instructions that when executed cause the processor to: display a price selection element presenting the user with a plurality of price ranges; and receiving a user selection of a price range, the user selection comprising a touchscreen interaction with the price selection element; wherein generating the application search query comprises generating the application search query using the selected price range. | 0.777728 |
9,507,792 | 1 | 6 | 1. A content management system for extracting portions of content objects for semi-automated answer identifications, the content management system comprising: a file receiver that detects a set of assessment content objects for processing, each assessment content object of the set of assessment content objects including content-object data arranged according to a spatial arrangement, each assessment content object of the set of assessment content objects being associated with an identifier corresponding to a student; a record classifier that, for each assessment content object of the set of assessment content objects, determines that the assessment content object corresponds to an identifier of a template for a particular assessment, the template identifying a segment-position specification that at least partly defines an area in which an answer for a question is to have been provided; a parsing engine that, for each assessment content object of the set of assessment content objects: identifies a portion of the content-object data as corresponding to an answer area for the question based on the segment-position specification and the spatial arrangement; and extracts the portion of the content-object data; a response classifier that: evaluates the portion of the content-object data to identify an answer indicated in the portion of the content-object data; determines an evaluation quality metric reflecting a confidence in the identification of the answer; and determines whether a quality criterion is satisfied based on the evaluation quality metric; and an interface engine that: facilitates a presentation that includes: multiple portions of content-object data, the multiple portions of content-object data having extracted from multiple assessment content objects from the set of assessment content objects, each portion of the multiple portion being associated with a determination that the quality criterion is not satisfied; and a tool that receives external input identifying an answer indicated in one or more portions of the multiple portions; and receives an input corresponding to an identification of an answer indicated in a portion of the one or more portions; wherein the response classifier further stores, upon receiving the input, the answer in association with the identifier of the student associated with the assessment content object from which the portion was extracted. | 1. A content management system for extracting portions of content objects for semi-automated answer identifications, the content management system comprising: a file receiver that detects a set of assessment content objects for processing, each assessment content object of the set of assessment content objects including content-object data arranged according to a spatial arrangement, each assessment content object of the set of assessment content objects being associated with an identifier corresponding to a student; a record classifier that, for each assessment content object of the set of assessment content objects, determines that the assessment content object corresponds to an identifier of a template for a particular assessment, the template identifying a segment-position specification that at least partly defines an area in which an answer for a question is to have been provided; a parsing engine that, for each assessment content object of the set of assessment content objects: identifies a portion of the content-object data as corresponding to an answer area for the question based on the segment-position specification and the spatial arrangement; and extracts the portion of the content-object data; a response classifier that: evaluates the portion of the content-object data to identify an answer indicated in the portion of the content-object data; determines an evaluation quality metric reflecting a confidence in the identification of the answer; and determines whether a quality criterion is satisfied based on the evaluation quality metric; and an interface engine that: facilitates a presentation that includes: multiple portions of content-object data, the multiple portions of content-object data having extracted from multiple assessment content objects from the set of assessment content objects, each portion of the multiple portion being associated with a determination that the quality criterion is not satisfied; and a tool that receives external input identifying an answer indicated in one or more portions of the multiple portions; and receives an input corresponding to an identification of an answer indicated in a portion of the one or more portions; wherein the response classifier further stores, upon receiving the input, the answer in association with the identifier of the student associated with the assessment content object from which the portion was extracted. 6. The content management system for extracting portions of content objects for semi-automated answer identifications as recited in claim 1 , wherein each of the multiple portions corresponds to an answer area for a same question. | 0.806397 |
8,832,542 | 1 | 5 | 1. A method for providing a hyperlink on a network, the method comprising: capturing an image of at least one character fixed in a medium; determining a letter of an alphabet corresponding to the at least one character; identifying at least one symbol applied onto a portion of the determined letter; determining a type of the identified at least one symbol and a location for the identified at least one symbol on the determined letter; determining a numerical value for the identified at least one symbol based on the determined letter, determined type of the at least one symbol and location of the identified at least one symbol on the determined letter; looking up in a database a hyperlink corresponding to the numerical value; and presenting the hyperlink on a display device. | 1. A method for providing a hyperlink on a network, the method comprising: capturing an image of at least one character fixed in a medium; determining a letter of an alphabet corresponding to the at least one character; identifying at least one symbol applied onto a portion of the determined letter; determining a type of the identified at least one symbol and a location for the identified at least one symbol on the determined letter; determining a numerical value for the identified at least one symbol based on the determined letter, determined type of the at least one symbol and location of the identified at least one symbol on the determined letter; looking up in a database a hyperlink corresponding to the numerical value; and presenting the hyperlink on a display device. 5. The method as in claim 1 , wherein the at least one symbol is a hatch mark, at least one dot, a line, a bolded element or a combination thereof. | 0.667421 |
7,844,999 | 20 | 28 | 20. A non-transitory machine-readable medium having stored thereon data representing instructions that, when executed by a processor, cause the processor to perform operations comprising: accessing a message in a message log, wherein the message log associates a host identifier with the message, the host identifier being an identifier of a host that sent the message to the message log; accessing a host-specific list of multiple parsers associated with the host identifier associated with the message; attempting to parse the message using a first parser in the host-specific list; responsive to unsuccessful parsing using the first parser, attempting to parse the message using a second parser in the host-specific list; responsive to unsuccessful parsing using all the parsers in the host-specific list: attempting to parse the message using a parser in a comprehensive list of multiple parsers; and responsive to successful parsing using the parser in the comprehensive list, adding the parser to the host-specific list. | 20. A non-transitory machine-readable medium having stored thereon data representing instructions that, when executed by a processor, cause the processor to perform operations comprising: accessing a message in a message log, wherein the message log associates a host identifier with the message, the host identifier being an identifier of a host that sent the message to the message log; accessing a host-specific list of multiple parsers associated with the host identifier associated with the message; attempting to parse the message using a first parser in the host-specific list; responsive to unsuccessful parsing using the first parser, attempting to parse the message using a second parser in the host-specific list; responsive to unsuccessful parsing using all the parsers in the host-specific list: attempting to parse the message using a parser in a comprehensive list of multiple parsers; and responsive to successful parsing using the parser in the comprehensive list, adding the parser to the host-specific list. 28. The non-transitory machine-readable medium of claim 20 , wherein attempting to parse the message using the parsers from the host-specific list of multiple parsers proceeds according to a hierarchy of more specific parsers to more general parsers. | 0.586093 |
7,992,130 | 1 | 9 | 1. A program transformation system, comprising: a processor coupled to a memory, the processor configured to execute the following computer-executable components stored in the memory: a code generation component that generates semantically equivalent code in a class-less scripting language from an object-oriented programming language representation of a hierarchy of one or more classes or interfaces and a virtual constructor component that produces a dispatch construct that captures class and/or interface method implementation to facilitate dynamic dispatch. | 1. A program transformation system, comprising: a processor coupled to a memory, the processor configured to execute the following computer-executable components stored in the memory: a code generation component that generates semantically equivalent code in a class-less scripting language from an object-oriented programming language representation of a hierarchy of one or more classes or interfaces and a virtual constructor component that produces a dispatch construct that captures class and/or interface method implementation to facilitate dynamic dispatch. 9. The system of claim 1 , the representation is intermediate language code. | 0.838983 |
8,156,144 | 11 | 15 | 11. A metadata search interface system comprising: a first component for accessing a configuration file for said metadata search interface and determining a display element corresponding to a predicate of a query, said first component further for displaying said display element in said metadata search interface, said predicate supporting full text searches and corresponding to a where clause that supports multiple nested predicate types; and a second component at least partially executed by a processor for accessing a value describing a search parameter and for accessing a control associated with said predicate which describes a correlation between said value and said predicate of said metadata search interface, said second component further for automatically generating a metadata query based upon said predicate and said value. | 11. A metadata search interface system comprising: a first component for accessing a configuration file for said metadata search interface and determining a display element corresponding to a predicate of a query, said first component further for displaying said display element in said metadata search interface, said predicate supporting full text searches and corresponding to a where clause that supports multiple nested predicate types; and a second component at least partially executed by a processor for accessing a value describing a search parameter and for accessing a control associated with said predicate which describes a correlation between said value and said predicate of said metadata search interface, said second component further for automatically generating a metadata query based upon said predicate and said value. 15. The metadata search interface system of claim 11 wherein said first component dynamically creates said metadata search interface in runtime by accessing at least one of said control via a reflection library. | 0.556723 |
7,870,142 | 1 | 2 | 1. A method for extracting meta data from a digital media storage device in a vehicle over a communication link between a control module of the vehicle and the digital media storage device, the method comprising: retrieving meta data from the digital media storage device over the communication link using the control module of the vehicle, the meta data associated with a media file from the digital media storage device, the meta data comprising text data; comparing the text data with a plurality of stored data entries using the control module; providing to a processing module, for user a interface, a phonemic representation for the text data based on a pre-stored phonemic representation associated with a stored data entry when the text data matches the stored data entry, the phonemic representation provided by a memory device of the control module; storing the meta data in the memory device of the vehicle; and creating a link between the stored meta data and the phonemic representation for the text data; and maintaining the link in the memory device across power cycles of the control module and using the link in the memory device to provide for phoneme-based speech recognition of the stored meta data. | 1. A method for extracting meta data from a digital media storage device in a vehicle over a communication link between a control module of the vehicle and the digital media storage device, the method comprising: retrieving meta data from the digital media storage device over the communication link using the control module of the vehicle, the meta data associated with a media file from the digital media storage device, the meta data comprising text data; comparing the text data with a plurality of stored data entries using the control module; providing to a processing module, for user a interface, a phonemic representation for the text data based on a pre-stored phonemic representation associated with a stored data entry when the text data matches the stored data entry, the phonemic representation provided by a memory device of the control module; storing the meta data in the memory device of the vehicle; and creating a link between the stored meta data and the phonemic representation for the text data; and maintaining the link in the memory device across power cycles of the control module and using the link in the memory device to provide for phoneme-based speech recognition of the stored meta data. 2. The method according to claim 1 , further comprising: generating a new phonemic representation based on the text data when the text data does not match at least one of the stored data entries. | 0.76335 |
9,558,739 | 1 | 3 | 1. A method of adapting a speech system of a vehicle, comprising: logging speech data from the speech system; processing the speech data for a pattern of a user competence associated with an interaction behavior; processing the pattern of user competence for parameters and measurements; calculating at least one setting based on the parameters and measurements of the pattern; and updating an interaction sequence based on the at least one setting, wherein the updating comprises updating the interaction sequence to include more system initiative after repeated errors by the user or the speech system are identified, and updating the interaction sequence to include more user initiative after it is determined that the user learned an interaction pattern. | 1. A method of adapting a speech system of a vehicle, comprising: logging speech data from the speech system; processing the speech data for a pattern of a user competence associated with an interaction behavior; processing the pattern of user competence for parameters and measurements; calculating at least one setting based on the parameters and measurements of the pattern; and updating an interaction sequence based on the at least one setting, wherein the updating comprises updating the interaction sequence to include more system initiative after repeated errors by the user or the speech system are identified, and updating the interaction sequence to include more user initiative after it is determined that the user learned an interaction pattern. 3. The method of claim 1 wherein the parameters and measurements are associated with at least one of task completion success, recurring errors of the user, and recurring errors of the speech system. | 0.765403 |
10,067,792 | 1 | 5 | 1. A hardware finite automata manager, comprising: a service manager; and an engine manager configured to be in communication with the service manager, wherein the service manager is effective to: identify at least one executable instruction associated with a particular core of a multi-core processor, wherein the engine manager is effective to: determine that a hardware finite automaton is available, wherein the hardware finite automaton is configured to perform a network processing task, wherein the hardware finite automaton includes a plurality of shift registers and a plurality of logic gates; in response to the determination that the hardware finite automaton is available, select at least one program instruction based on a pre-fetch hardware finite automata design, wherein the pre-fetch hardware finite automata design is selected based on the at least one executable instruction, and wherein the at least one program instruction is configured to instruct the hardware finite automaton to pre-fetch data for the particular core; and transmit the at least one program instruction to the hardware finite automaton, wherein the transmission of the at least one program instruction includes programming the hardware finite automaton to pre-fetch the data for the particular core, before the at least one executable instruction is executed by the particular core, and wherein selecting the at least one program instruction includes: identifying executable instructions associated with a particular core of the multi-core processor; determining that the hardware finite automaton is available, wherein the hardware finite automaton is configured to perform a network processing task, and wherein the hardware finite automaton includes a plurality of shift registers and a plurality of logic gates; in response to the determination that the hardware finite automaton is available, selecting at least one program instruction based on a pre-fetch hardware finite automata design, wherein the pre-fetch hardware finite automata design is selected based on the executable instructions, and wherein the at least one program instruction is configured to instruct the hardware finite automaton to pre-fetch data for the particular core; and transmitting the at least one program instruction to the hardware finite automaton, wherein transmitting the at least one program instruction includes programming the hardware finite automaton to pre-fetch the data for the particular core, before the executable instructions are executed by the particular core, to reduce latency for the particular core to wait for the data. | 1. A hardware finite automata manager, comprising: a service manager; and an engine manager configured to be in communication with the service manager, wherein the service manager is effective to: identify at least one executable instruction associated with a particular core of a multi-core processor, wherein the engine manager is effective to: determine that a hardware finite automaton is available, wherein the hardware finite automaton is configured to perform a network processing task, wherein the hardware finite automaton includes a plurality of shift registers and a plurality of logic gates; in response to the determination that the hardware finite automaton is available, select at least one program instruction based on a pre-fetch hardware finite automata design, wherein the pre-fetch hardware finite automata design is selected based on the at least one executable instruction, and wherein the at least one program instruction is configured to instruct the hardware finite automaton to pre-fetch data for the particular core; and transmit the at least one program instruction to the hardware finite automaton, wherein the transmission of the at least one program instruction includes programming the hardware finite automaton to pre-fetch the data for the particular core, before the at least one executable instruction is executed by the particular core, and wherein selecting the at least one program instruction includes: identifying executable instructions associated with a particular core of the multi-core processor; determining that the hardware finite automaton is available, wherein the hardware finite automaton is configured to perform a network processing task, and wherein the hardware finite automaton includes a plurality of shift registers and a plurality of logic gates; in response to the determination that the hardware finite automaton is available, selecting at least one program instruction based on a pre-fetch hardware finite automata design, wherein the pre-fetch hardware finite automata design is selected based on the executable instructions, and wherein the at least one program instruction is configured to instruct the hardware finite automaton to pre-fetch data for the particular core; and transmitting the at least one program instruction to the hardware finite automaton, wherein transmitting the at least one program instruction includes programming the hardware finite automaton to pre-fetch the data for the particular core, before the executable instructions are executed by the particular core, to reduce latency for the particular core to wait for the data. 5. The hardware finite automata manager of claim 1 , wherein: the at least one executable instruction includes first executable instructions, the particular core is a first core of the multi-core processor, and the engine manager is further effective to, prior to selection of the at least one program instruction: identify second executable instructions associated with a second core of the multi-core processor; determine a first number of cache misses experienced by the first core in execution of the first executable instructions; determine a second number of cache misses experienced by the second core in execution of the second executable instructions; and assign the hardware finite automaton to the first core based on the first and second numbers of cache misses. | 0.5 |
7,818,333 | 5 | 6 | 5. The method of claim 4 further comprising the step of assigning penalties when disfavored matches occur in applying the input address to the one or more branches of the parsing tree. | 5. The method of claim 4 further comprising the step of assigning penalties when disfavored matches occur in applying the input address to the one or more branches of the parsing tree. 6. The method of claim 5 further comprising ranking the one or more parsing tree branches that include matches based on the assigned penalties. | 0.5 |
7,647,299 | 23 | 25 | 23. The apparatus of claim 17 wherein each of the search results have a score. | 23. The apparatus of claim 17 wherein each of the search results have a score. 25. The apparatus of claim 23 wherein the method further includes 3) scoring, using at least the search result scores and further using at least one of (i) ad performance information, (ii) ad price information (iii) advertiser quality information, and (iv) user information, at least some of the retrieved at least one advertisement. | 0.5 |
9,478,216 | 8 | 13 | 8. A device comprising memory storing instructions that, when executed by a computer processor of the device, cause the device to perform a method of speech recognition comprising: processing a speech input to produce a sequence of representative speech vectors; and performing a first recognition pass using a first acoustic model to produce at least one intermediate recognition hypothesis corresponding to the speech input; performing a second recognition pass using a second acoustic model to re-evaluate the at least one intermediate recognition hypothesis and produce a final recognition result corresponding to the speech input; and wherein the second recognition pass is a generic recognition pass that is based on a generic speech recognition arrangement using generic acoustic modeling of a broad general class of input speech; and wherein the first recognition pass is an adapted recognition pass that is based on a speech adapted arrangement using pre-adapted acoustic modeling of a specific sub-class of the general class of input speech. | 8. A device comprising memory storing instructions that, when executed by a computer processor of the device, cause the device to perform a method of speech recognition comprising: processing a speech input to produce a sequence of representative speech vectors; and performing a first recognition pass using a first acoustic model to produce at least one intermediate recognition hypothesis corresponding to the speech input; performing a second recognition pass using a second acoustic model to re-evaluate the at least one intermediate recognition hypothesis and produce a final recognition result corresponding to the speech input; and wherein the second recognition pass is a generic recognition pass that is based on a generic speech recognition arrangement using generic acoustic modeling of a broad general class of input speech; and wherein the first recognition pass is an adapted recognition pass that is based on a speech adapted arrangement using pre-adapted acoustic modeling of a specific sub-class of the general class of input speech. 13. The device according to claim 8 wherein the speech adapted arrangement is based on adapted feature transforms and the first and second recognition passes use the same acoustic models. | 0.66726 |
7,676,851 | 1 | 14 | 1. A headwear piece comprising: a crown defining an opening into which a wearer's head can be directed; and a brim/bill projecting away from the crown, the crown having an inside surface for engaging a wearer's head directed into the opening to thereby maintain the headwear piece in an operative position upon the wearer's head, the crown and brim/bill further having an exposed outside surface to which ornamentation is applied, the ornamentation comprising bullion wire that is applied to the exposed outside surface so as to define at least a part of a viewable component that comprises at least one of: a) a scene; b) a logo; c) a design; d) a word; e) a letter; and f) a depiction of a: i) person; ii) place; and/or iii) thing, wherein the ornamentation comprises a discrete shape with an area bounded by a border, and the ornamentation comprises: a) wire that is at least one of bullion wire and non-bullion wire applied in a first pattern comprising substantially straight, substantially parallel, adjacent lengths of the at least one of bullion wire and non-bullion wire within the area bounded by the border that collectively contiguously cover a substantial portion of the area bounded by the border; and b) bullion wire applied in a second pattern comprising substantially straight, substantially parallel, adjacent lengths of bullion wire within the area bounded by the border and overlying the first pattern, wherein the lengths of bullion wire in the second pattern are transverse to the lengths of wire in the first pattern and collectively contiguously cover a substantial portion of the area bounded by the border, a plurality of the lengths of the bullion wire in the second pattern each spanning across a plurality of the lengths of the wire in the first pattern without being interwoven with the spanned plurality of lengths of wire in the first pattern. | 1. A headwear piece comprising: a crown defining an opening into which a wearer's head can be directed; and a brim/bill projecting away from the crown, the crown having an inside surface for engaging a wearer's head directed into the opening to thereby maintain the headwear piece in an operative position upon the wearer's head, the crown and brim/bill further having an exposed outside surface to which ornamentation is applied, the ornamentation comprising bullion wire that is applied to the exposed outside surface so as to define at least a part of a viewable component that comprises at least one of: a) a scene; b) a logo; c) a design; d) a word; e) a letter; and f) a depiction of a: i) person; ii) place; and/or iii) thing, wherein the ornamentation comprises a discrete shape with an area bounded by a border, and the ornamentation comprises: a) wire that is at least one of bullion wire and non-bullion wire applied in a first pattern comprising substantially straight, substantially parallel, adjacent lengths of the at least one of bullion wire and non-bullion wire within the area bounded by the border that collectively contiguously cover a substantial portion of the area bounded by the border; and b) bullion wire applied in a second pattern comprising substantially straight, substantially parallel, adjacent lengths of bullion wire within the area bounded by the border and overlying the first pattern, wherein the lengths of bullion wire in the second pattern are transverse to the lengths of wire in the first pattern and collectively contiguously cover a substantial portion of the area bounded by the border, a plurality of the lengths of the bullion wire in the second pattern each spanning across a plurality of the lengths of the wire in the first pattern without being interwoven with the spanned plurality of lengths of wire in the first pattern. 14. The headwear piece according to claim 1 wherein a substance is applied to the exposed outside surface to visually facilitate placement of the bullion wire upon the exposed outside surface. | 0.692308 |
7,627,555 | 1 | 9 | 1. A computer program product of use at a computer system the computer program product for implementing a method for data mining on a multidimensional data cube, the computer program product comprising one or more computer storage media having stored thereon computer-executable instructions that, when executed at a processor, cause the computer system to perform the method, including performing the following: access multidimensional data; access multidimensional expressions defining how to view the multidimensional data as a multidimensional data cube; access data mining extensions for performing data mining on data residing in the multidimensional data cube; integrate the multidimensional expressions and the data mining extensions into input for data mining model creation; create a data mining model trained on the multidimensional data from the input; store the data mining model; perform data predictions against data contained in the multidimensional data cube by data mining the multidimensional data cube in accordance with the data mining model, data mining including performing data mining operations on portions of data contained in the multidimensional data cube in accordance with a multidimensional query element. | 1. A computer program product of use at a computer system the computer program product for implementing a method for data mining on a multidimensional data cube, the computer program product comprising one or more computer storage media having stored thereon computer-executable instructions that, when executed at a processor, cause the computer system to perform the method, including performing the following: access multidimensional data; access multidimensional expressions defining how to view the multidimensional data as a multidimensional data cube; access data mining extensions for performing data mining on data residing in the multidimensional data cube; integrate the multidimensional expressions and the data mining extensions into input for data mining model creation; create a data mining model trained on the multidimensional data from the input; store the data mining model; perform data predictions against data contained in the multidimensional data cube by data mining the multidimensional data cube in accordance with the data mining model, data mining including performing data mining operations on portions of data contained in the multidimensional data cube in accordance with a multidimensional query element. 9. The computer program product of claim 1 , further comprising computer-executable instructions that, when executed, cause the computer system to provide a language schema for integrating the multidimensional expressions and the data mining extensions; and wherein computer-executable instructions that, when executed, cause the computer system to integrate the multidimensional expressions and the data mining extensions into input for data mining model creation comprise computer-executable instructions that, when executed, cause the computer system to integrate the multidimensional expressions and the data mining extensions into input for data mining model creation in accordance with the provided language schema. | 0.5 |
9,058,242 | 1 | 20 | 1. A method of optimizing a web page for search engines, the method comprising: compiling web analytical data; determining, using a processor, a recommended modification to at least one parameter of a web document associated with the web page, the recommended modification to improve an organic search ranking of the web page for a search query performed in one or more of the search engines, the determination made based upon the web analytical data; applying, in a user interface, the recommended modification to the at least one parameter of the associated web document; generating an event log comprising one or more events representing one or more initiatives affecting the organic search ranking of the web page, and corresponding event data containing timing information corresponding to the one or more initiatives; generating at least one data graph of historical search rank data including the organic search ranking of the web page for the search query over time; identifying a feature or trend in the at least one data graph; automatically correlating, using the processor, the event data with the feature or trend identified in the at least one data graph to automatically identify the one or more events causing the feature or trend in the at least one data graph; and displaying, in the user interface, the at least one data graph automatically annotated with the event data correlated with the feature or trend. | 1. A method of optimizing a web page for search engines, the method comprising: compiling web analytical data; determining, using a processor, a recommended modification to at least one parameter of a web document associated with the web page, the recommended modification to improve an organic search ranking of the web page for a search query performed in one or more of the search engines, the determination made based upon the web analytical data; applying, in a user interface, the recommended modification to the at least one parameter of the associated web document; generating an event log comprising one or more events representing one or more initiatives affecting the organic search ranking of the web page, and corresponding event data containing timing information corresponding to the one or more initiatives; generating at least one data graph of historical search rank data including the organic search ranking of the web page for the search query over time; identifying a feature or trend in the at least one data graph; automatically correlating, using the processor, the event data with the feature or trend identified in the at least one data graph to automatically identify the one or more events causing the feature or trend in the at least one data graph; and displaying, in the user interface, the at least one data graph automatically annotated with the event data correlated with the feature or trend. 20. The method of claim 1 , wherein the event data comprises timing data for at least one of the applied modification to the at least one parameter of the associated web document, timing data for the publication of new web documents associated with the web page, timing data for social bookmarking of the associated web document, and timing data for social sharing mentions of the associated web document. | 0.5 |
8,381,119 | 1 | 2 | 1. A touchscreen keyboard for a pictographic language, comprising: a touchscreen display; and a display controller programmed to display a first arrangement of pictographic characters on the touchscreen display, the first arrangement comprising a plurality of characters of the pictographic language, wherein the first arrangement comprises a plurality of discrete regions arranged in a matrix form, each of the regions displaying a respective one of groups of characters selected from the plurality of characters, each of the regions including 15 characters arranged in 3 columns and 5 rows, wherein the display controller is further programmed to display characters in a matrix form in a respective one of the regions, wherein characters in at least one of the regions have the same first phonetic sound as one another, and wherein the regions are arranged at positions corresponding to positions of keys of a QWERTY keyboard, such that the first phonetic sounds of the characters of the regions substantially correspond to the phonetic sounds of letters on the keys of the QWERTY keyboard. | 1. A touchscreen keyboard for a pictographic language, comprising: a touchscreen display; and a display controller programmed to display a first arrangement of pictographic characters on the touchscreen display, the first arrangement comprising a plurality of characters of the pictographic language, wherein the first arrangement comprises a plurality of discrete regions arranged in a matrix form, each of the regions displaying a respective one of groups of characters selected from the plurality of characters, each of the regions including 15 characters arranged in 3 columns and 5 rows, wherein the display controller is further programmed to display characters in a matrix form in a respective one of the regions, wherein characters in at least one of the regions have the same first phonetic sound as one another, and wherein the regions are arranged at positions corresponding to positions of keys of a QWERTY keyboard, such that the first phonetic sounds of the characters of the regions substantially correspond to the phonetic sounds of letters on the keys of the QWERTY keyboard. 2. The system of claim 1 , wherein the pictographic characters are Chinese characters. | 0.891139 |
8,868,540 | 1 | 6 | 1. A method of suggesting links for a search query in an enterprise system, comprising: receiving a rule index in an enterprise system, wherein the rule index provides rule patterns for associating links with queries; receiving a search request from a user comprising a query string that includes a set of query tokens, wherein the user has been authorized to search by a first authentication performed by the enterprise system; in response to the search request: generating and displaying search results; and generating and displaying one or more suggested links to documents, where the suggested links are to documents which have not been crawled by the enterprise system; wherein generating the suggested links comprises: generating, using the processor, variations of the set of query tokens; and applying, using the processor, the rule index to variations of the set of query tokens; wherein applying the rule index further comprises matching a variation of the set of query tokens to one or more rule index entries to identify at least one related link, wherein the at least one related link is not included in the search results; submitting information about the user to a provider of the one or more suggested links, wherein the provider performs a second authentication of the user; selecting one or more related links to display as suggested links when the second authentication is successful; and providing the user with a message other than the suggested content when the second authentication fails. | 1. A method of suggesting links for a search query in an enterprise system, comprising: receiving a rule index in an enterprise system, wherein the rule index provides rule patterns for associating links with queries; receiving a search request from a user comprising a query string that includes a set of query tokens, wherein the user has been authorized to search by a first authentication performed by the enterprise system; in response to the search request: generating and displaying search results; and generating and displaying one or more suggested links to documents, where the suggested links are to documents which have not been crawled by the enterprise system; wherein generating the suggested links comprises: generating, using the processor, variations of the set of query tokens; and applying, using the processor, the rule index to variations of the set of query tokens; wherein applying the rule index further comprises matching a variation of the set of query tokens to one or more rule index entries to identify at least one related link, wherein the at least one related link is not included in the search results; submitting information about the user to a provider of the one or more suggested links, wherein the provider performs a second authentication of the user; selecting one or more related links to display as suggested links when the second authentication is successful; and providing the user with a message other than the suggested content when the second authentication fails. 6. The method of claim 1 , wherein: applying the rule index to variations of the set of query tokens includes matching based on at least one of synonyms, uni-grams, bi-grams, tri-grams, and quoted phrases. | 0.635231 |
9,069,862 | 1 | 5 | 1. A computer-implemented method of performing a relationship-based search, the method comprising: receiving a user query from a user, the user query including a reference to a query object; processing the user query into a plurality of sub-queries for information related to the query object, each sub-query being for a corresponding one of a plurality of information sources; submitting the plurality of sub-queries to the plurality of information sources; receiving search results for the plurality of sub-queries from the information sources, each search result identifying (a) a search result object related to the query object and (b) a type of relationship indicating a type of relevancy of the search result to the search query; organizing the search results into a plurality of categories based on types of objects identified in the search results, wherein each of the plurality of categories includes a respective type of objects, the plurality of categories including a first category comprising a first subset of search results with a first object type and a second category comprising a second subset of search results with a second object type; organizing the first subset of search results in the first category into a plurality of buckets based on types of relationships indicating types of relevancy of the first subset of search results to the search query, each bucket including search results with a respective type of relationship with the search query, the plurality of buckets including a first bucket comprising a first further subset of the first subset of search results in the first category with a first type of relationship with the search query and a second bucket comprising a second further subset of the first subset of search results in the first category with a second type of relationship with the search query; and providing the search results organized into the plurality of categories, the provided search results including the first subset of search results in the first category organized into the plurality of buckets for presentation to the user. | 1. A computer-implemented method of performing a relationship-based search, the method comprising: receiving a user query from a user, the user query including a reference to a query object; processing the user query into a plurality of sub-queries for information related to the query object, each sub-query being for a corresponding one of a plurality of information sources; submitting the plurality of sub-queries to the plurality of information sources; receiving search results for the plurality of sub-queries from the information sources, each search result identifying (a) a search result object related to the query object and (b) a type of relationship indicating a type of relevancy of the search result to the search query; organizing the search results into a plurality of categories based on types of objects identified in the search results, wherein each of the plurality of categories includes a respective type of objects, the plurality of categories including a first category comprising a first subset of search results with a first object type and a second category comprising a second subset of search results with a second object type; organizing the first subset of search results in the first category into a plurality of buckets based on types of relationships indicating types of relevancy of the first subset of search results to the search query, each bucket including search results with a respective type of relationship with the search query, the plurality of buckets including a first bucket comprising a first further subset of the first subset of search results in the first category with a first type of relationship with the search query and a second bucket comprising a second further subset of the first subset of search results in the first category with a second type of relationship with the search query; and providing the search results organized into the plurality of categories, the provided search results including the first subset of search results in the first category organized into the plurality of buckets for presentation to the user. 5. The method of claim 1 , wherein the first category includes search results that identify people type objects, the query object identifies a person, and the types of relationships include at least one of: people included in email threads with the person, people with meetings in common with the person, people belonging to a same organization as the person, and people sharing a postal address with the person. | 0.685976 |
9,633,275 | 1 | 4 | 1. A computer-implemented method for extracting pixel-level micro-features from image data captured by a video camera, the method comprising: receiving the image data; identifying a set of pixels in the image data associated with a foreground patch that depicts a foreground object; evaluating appearance values of the pixels included in the set of pixels to compute a plurality of micro-feature values representing the foreground object, each based on at least one pixel-level characteristic of the foreground patch, wherein the micro-feature values are computed independent of training data that defines a plurality of object types; generating a micro-feature vector that includes the plurality of micro-feature values; classifying the foreground object as depicting an object type as based on the micro-feature vector, wherein the object type is determined by mapping the micro-feature vector to a cluster in a self-organizing map (SOM) adaptive resonance theory (ART) network generated from a plurality of micro-feature vectors; and updating one or more cluster properties associated with the cluster based on the plurality of micro-feature values in the generated micro-feature vector. | 1. A computer-implemented method for extracting pixel-level micro-features from image data captured by a video camera, the method comprising: receiving the image data; identifying a set of pixels in the image data associated with a foreground patch that depicts a foreground object; evaluating appearance values of the pixels included in the set of pixels to compute a plurality of micro-feature values representing the foreground object, each based on at least one pixel-level characteristic of the foreground patch, wherein the micro-feature values are computed independent of training data that defines a plurality of object types; generating a micro-feature vector that includes the plurality of micro-feature values; classifying the foreground object as depicting an object type as based on the micro-feature vector, wherein the object type is determined by mapping the micro-feature vector to a cluster in a self-organizing map (SOM) adaptive resonance theory (ART) network generated from a plurality of micro-feature vectors; and updating one or more cluster properties associated with the cluster based on the plurality of micro-feature values in the generated micro-feature vector. 4. The computer-implemented method of claim 1 , wherein one of the computed micro-feature values is set to predetermined value indicating that the computed micro-feature value is not valid when a threshold value is not met. | 0.636808 |
9,652,799 | 1 | 2 | 1. A method comprising: receiving, from a user, a text input expressing a question asking for recommendation of a product having a first requested characteristic and a second requested characteristic; identifying a product having the first requested characteristic, at least in part by locating in an ontology a node corresponding to the first requested characteristic, and traversing a relationship in the ontology from the node corresponding to the first requested characteristic to a node corresponding to the product; analyzing, using a natural language analysis component implemented via at least one processor, a plurality of product reviews comprising natural language text evaluations of the product identified from the ontology as having the first requested characteristic, including analyzing the natural language in at least one passage of text in at least one product review of the plurality of product reviews to determine whether the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic; in response to determining via the natural language analysis that the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic, identifying the at least one passage of text in the at least one product review as providing supporting evidence for the product in answer to the question; generating, in response to the question, an answer that identifies the product having the first and second requested characteristics for recommendation to the user; and presenting to the user, in response to the text input, the answer and the at least one passage in the at least one product review identified as providing supporting evidence for the answer. | 1. A method comprising: receiving, from a user, a text input expressing a question asking for recommendation of a product having a first requested characteristic and a second requested characteristic; identifying a product having the first requested characteristic, at least in part by locating in an ontology a node corresponding to the first requested characteristic, and traversing a relationship in the ontology from the node corresponding to the first requested characteristic to a node corresponding to the product; analyzing, using a natural language analysis component implemented via at least one processor, a plurality of product reviews comprising natural language text evaluations of the product identified from the ontology as having the first requested characteristic, including analyzing the natural language in at least one passage of text in at least one product review of the plurality of product reviews to determine whether the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic; in response to determining via the natural language analysis that the natural language in the at least one passage of text has a meaning indicating that the product also has the second requested characteristic, identifying the at least one passage of text in the at least one product review as providing supporting evidence for the product in answer to the question; generating, in response to the question, an answer that identifies the product having the first and second requested characteristics for recommendation to the user; and presenting to the user, in response to the text input, the answer and the at least one passage in the at least one product review identified as providing supporting evidence for the answer. 2. The method of claim 1 , wherein the at least one product review comprises an evaluation of the product made by a purchaser of the product. | 0.833333 |
8,893,082 | 1 | 12 | 1. A computer-implemented method for facilitating the development and execution of a software program, comprising: obtaining a type interval for a generic type parameter of an implementation of an overloaded function; selecting an inference direction for the generic type parameter based on a variance of the generic type parameter, wherein the inference direction is an upward inference direction or a downward inference direction; and using the type interval and the inference direction to perform type inference on the generic type parameter, wherein doing so comprises: propagating one or more limits associated with the type interval through a set of constraints associated with the generic type parameter based on the inference direction; when the type interval is non-empty after the one or more limits are propagated through the set of constraints, choosing a binding for the generic type parameter based on the inference direction; and when the type interval is empty after the one or more limits are propagated through the set of constraints, determining that the implementation is not applicable to a function call associated with the overloaded function and the type interval. | 1. A computer-implemented method for facilitating the development and execution of a software program, comprising: obtaining a type interval for a generic type parameter of an implementation of an overloaded function; selecting an inference direction for the generic type parameter based on a variance of the generic type parameter, wherein the inference direction is an upward inference direction or a downward inference direction; and using the type interval and the inference direction to perform type inference on the generic type parameter, wherein doing so comprises: propagating one or more limits associated with the type interval through a set of constraints associated with the generic type parameter based on the inference direction; when the type interval is non-empty after the one or more limits are propagated through the set of constraints, choosing a binding for the generic type parameter based on the inference direction; and when the type interval is empty after the one or more limits are propagated through the set of constraints, determining that the implementation is not applicable to a function call associated with the overloaded function and the type interval. 12. The non-transitory computer-readable storage medium of claim 1 , wherein propagating the one or more limits through the set of constraints based on the inference direction involves: performing a first propagation of the one or more limits to update one or more upper limits in the type interval and one or more lower limits in type intervals of one or more generic type parameters related to the generic type parameter; and when the inference direction is the upward inference direction, performing a second propagation of the one or more limits to further update the one or more upper limits. | 0.5 |
9,478,145 | 1 | 2 | 1. A method implemented by a question answer system that includes a memory and a processor, the method comprising: training an unreasonable answer filter using a set of training questions, a set of training answers corresponding to the set of training questions, and a set of unreasonable answers corresponding to the set of training questions; computing, by the unreasonable answer filter, one or more unreasonable answer probabilities of one or more ranked answers in a set of ranked answers, wherein each of the one or more unreasonable answer probabilities indicate a likelihood that its corresponding ranked answer is an incorrect answer to a question; determining, by the unreasonable answer filter, that at least one of the one or more unreasonable answer probabilities reaches a threshold, indicating that their one or more corresponding ranked answers are one or more unreasonable answers to the question; removing the one or more unreasonable answers from the set of ranked answers, resulting in a modified set of ranked answers; and providing the modified set of ranked answers to a user. | 1. A method implemented by a question answer system that includes a memory and a processor, the method comprising: training an unreasonable answer filter using a set of training questions, a set of training answers corresponding to the set of training questions, and a set of unreasonable answers corresponding to the set of training questions; computing, by the unreasonable answer filter, one or more unreasonable answer probabilities of one or more ranked answers in a set of ranked answers, wherein each of the one or more unreasonable answer probabilities indicate a likelihood that its corresponding ranked answer is an incorrect answer to a question; determining, by the unreasonable answer filter, that at least one of the one or more unreasonable answer probabilities reaches a threshold, indicating that their one or more corresponding ranked answers are one or more unreasonable answers to the question; removing the one or more unreasonable answers from the set of ranked answers, resulting in a modified set of ranked answers; and providing the modified set of ranked answers to a user. 2. The method of claim 1 wherein, prior to computing the set of unreasonable answer probabilities, the method further comprises: analyzing the question by the question answer system, wherein the analyzing results in a set of candidate answers; ranking the set of candidate answers, resulting in the set of ranked answers; and wherein the removing of the one or more unreasonable answers is performed by the unreasonable answer filter subsequent to the ranking of set of candidate answers. | 0.662983 |
9,298,680 | 9 | 10 | 9. The method according to claim 1 , further comprising: saving an indication of the grouping of the selected hypertext documents, closing the selected hypertext documents, retrieving the indication of the grouping of the selected hypertext documents, and re-opening the selected hypertext documents by displaying the selected hypertext documents in the arrangement corresponding to the grouping thereof. | 9. The method according to claim 1 , further comprising: saving an indication of the grouping of the selected hypertext documents, closing the selected hypertext documents, retrieving the indication of the grouping of the selected hypertext documents, and re-opening the selected hypertext documents by displaying the selected hypertext documents in the arrangement corresponding to the grouping thereof. 10. The method according to claim 9 , further comprising: monitoring at least one performance metric of the data processing system, wherein saving the indication of the grouping of the selected hypertext documents and closing the selected hypertext documents are performed in response to a detection of a low performance condition according to the at least one performance metric. | 0.5 |
8,639,785 | 7 | 11 | 7. A server device comprising: a non-transitory storage device having tangibly embodied thereon instructions associated with a context management routine; and one or more processors coupled to the non-transitory storage device and operable to execute the instructions associated with the context management routine to perform a method comprising: receiving from an Internet-enabled mobile device a HyperText Transport Protocol (HTTP) request relating to a service supported by the server device, wherein the HTTP request contains therein an unsolicited cookie including data indicative of one or more of (a) information regarding an end user of the Internet-enabled mobile device, (b) information regarding the Internet-enabled mobile device, (c) information regarding a location of the Internet-enabled mobile device and (d) information regarding a network to which the Internet-enabled mobile device is connected; generating contextual menu information based at least in part on the unsolicited cookie; and causing the Internet-enabled mobile device to dynamically reconfigure a browser menu of the Internet-enabled mobile device by returning to the Internet-enabled mobile device, responsive to the HTTP request, a HyperText Markup Language (HTML) file having embedded therein the contextual menu information. | 7. A server device comprising: a non-transitory storage device having tangibly embodied thereon instructions associated with a context management routine; and one or more processors coupled to the non-transitory storage device and operable to execute the instructions associated with the context management routine to perform a method comprising: receiving from an Internet-enabled mobile device a HyperText Transport Protocol (HTTP) request relating to a service supported by the server device, wherein the HTTP request contains therein an unsolicited cookie including data indicative of one or more of (a) information regarding an end user of the Internet-enabled mobile device, (b) information regarding the Internet-enabled mobile device, (c) information regarding a location of the Internet-enabled mobile device and (d) information regarding a network to which the Internet-enabled mobile device is connected; generating contextual menu information based at least in part on the unsolicited cookie; and causing the Internet-enabled mobile device to dynamically reconfigure a browser menu of the Internet-enabled mobile device by returning to the Internet-enabled mobile device, responsive to the HTTP request, a HyperText Markup Language (HTML) file having embedded therein the contextual menu information. 11. The server device of claim 7 , wherein the information regarding a location of the Internet-enabled mobile device includes a geographic location associated with a wireless access point, a network or a cell tower with which the Internet-enabled mobile device is connected. | 0.5 |
6,112,304 | 26 | 32 | 26. A computer system implementing an ecosystem computing architecture, the computer system comprising: an operational environment for distributed computing processes here termed denizens, each denizen including a configuration portion an origin portion, and an executable portion, each denizen performing at least one step on itself, the operational environment including at least two locations, each location providing access to a processor for executing instructions and providing a memory accessible to the processor for storing instructions; a transport means for denizens to travel between the locations; and at least one denizen that is a user denizen which receives instructions, evaluates different locations in the operational environment in view of the received instructions, selects a location based on that evaluation, moves itself to the selected location, and executes at least a portion of the received instructions at the selected location. | 26. A computer system implementing an ecosystem computing architecture, the computer system comprising: an operational environment for distributed computing processes here termed denizens, each denizen including a configuration portion an origin portion, and an executable portion, each denizen performing at least one step on itself, the operational environment including at least two locations, each location providing access to a processor for executing instructions and providing a memory accessible to the processor for storing instructions; a transport means for denizens to travel between the locations; and at least one denizen that is a user denizen which receives instructions, evaluates different locations in the operational environment in view of the received instructions, selects a location based on that evaluation, moves itself to the selected location, and executes at least a portion of the received instructions at the selected location. 32. The computer system of claim 26, wherein at least one denizen includes platform-independent portable code. | 0.710526 |
10,031,839 | 15 | 20 | 15. A method, comprising: obtaining, by a device, text to be processed to extract one or more constraints corresponding to an object in the text, the one or more constraints defining values permitted to be associated with the object; associating, by the device, part-of-speech tags with words in the text; extracting, by the device, the one or more constraints based on associating the part-of-speech tags with the words and identifying one or more patterns in the text, generating, by the device, one or more equations based on the one or more constraints; generating, by the device and based on the one or more constraints, positive test data and negative test data for testing values for the object, the positive test data including a first value that satisfies each of the one or more constraints based on the one or more equations, and the negative test data including a second value that violates at least one of the one or more constraints based on the one or more equations; receiving, by the device, existing test data from a memory location; applying, by the device, the positive test data, the negative test data, and the existing test data to a system that is designed based on the text for at least one of: improving software accuracy, reducing security issues, or conserving processing resources; validating, by the device, a classification of the existing test data as having a positive classification or a negative classification; and providing, by the device, for display on a user interface and based on applying the positive test data, the negative test data, and the existing test data, information that identifies: a first particular constraint that the positive test data satisfies, a second particular constraint that the negative test data violates, and the validation of the classification of the existing test data. | 15. A method, comprising: obtaining, by a device, text to be processed to extract one or more constraints corresponding to an object in the text, the one or more constraints defining values permitted to be associated with the object; associating, by the device, part-of-speech tags with words in the text; extracting, by the device, the one or more constraints based on associating the part-of-speech tags with the words and identifying one or more patterns in the text, generating, by the device, one or more equations based on the one or more constraints; generating, by the device and based on the one or more constraints, positive test data and negative test data for testing values for the object, the positive test data including a first value that satisfies each of the one or more constraints based on the one or more equations, and the negative test data including a second value that violates at least one of the one or more constraints based on the one or more equations; receiving, by the device, existing test data from a memory location; applying, by the device, the positive test data, the negative test data, and the existing test data to a system that is designed based on the text for at least one of: improving software accuracy, reducing security issues, or conserving processing resources; validating, by the device, a classification of the existing test data as having a positive classification or a negative classification; and providing, by the device, for display on a user interface and based on applying the positive test data, the negative test data, and the existing test data, information that identifies: a first particular constraint that the positive test data satisfies, a second particular constraint that the negative test data violates, and the validation of the classification of the existing test data. 20. The method of claim 15 , where extracting the one or more constraints comprises: extracting the one or more constraints based on inferring a numeric value in the text. | 0.698944 |
8,600,975 | 1 | 13 | 1. A computer-implemented method comprising: decomposing, by at least one processor of a computer system, a search query that includes three or more words into a plurality of candidate phrasifications, including different groupings of words of the search query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the search query; scoring, by at least one of the processors of the computer system, at least two of the candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, and wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases, and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; selecting, by at least one of the processors of the computer system and based on scores of the candidate phrasifications, a subset of the candidate phrasification; and executing a query of a document indexing, by at least one of the processors of the computer system, using the selected subset of candidate phrasifications, wherein the query comprises the component phrases of each selected phrasification. | 1. A computer-implemented method comprising: decomposing, by at least one processor of a computer system, a search query that includes three or more words into a plurality of candidate phrasifications, including different groupings of words of the search query, each candidate phrasification comprising a disjoint union of component phrases, and each component phrase including at least one word or related word of the search query; scoring, by at least one of the processors of the computer system, at least two of the candidate phrasifications, wherein the candidate phrasifications include one or more component phrases, and wherein the scoring is based on a probability of occurrence of each of the candidate phrasification's component phrases, and is based on the number of component phrases constituting the candidate phrasification, wherein candidate phrasifications having relatively fewer component phrases are weighted higher than candidate phrasifications having relatively more component phrases; selecting, by at least one of the processors of the computer system and based on scores of the candidate phrasifications, a subset of the candidate phrasification; and executing a query of a document indexing, by at least one of the processors of the computer system, using the selected subset of candidate phrasifications, wherein the query comprises the component phrases of each selected phrasification. 13. The method of claim 1 , further comprising: executing the search query by using the selected phrasifications to identify documents containing component phrases of the selected phrasifications. | 0.852632 |
7,880,730 | 22 | 56 | 22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device. | 22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device. 56. The system of claim 22 , further comprising an input means associated with a Cancel function, wherein when the current input sequence includes at least one interaction and said input means is used, said selection component removes one or more of said at least one identified candidate object from presentation to the user. | 0.654661 |
8,208,765 | 1 | 10 | 1. A document image processing apparatus comprising: a character image feature dictionary for storing image features of character images in units of character; a character string clipping portion for clipping character images in units of character string composed of a plurality of characters from an inputted document image; an image feature extracting portion for extracting an image feature of each character image which is obtained by dividing character images of character string clipped by the character string clipping portion, for each of the characters; a feature similarity measurement portion for selecting N (N>1, integer) pieces of character images in descending order of degree of similarity of image feature as candidate characters, from the character image feature dictionary which stores image features of character image in units of character based on the image features of each of the character images extracted by the image feature extracting portion, preparing a first index matrix of M×N cells where M (M>1, integer) represents a number of characters in the clipped character string, and preparing a second index matrix of character strings including a meaningful character string which is formed by adjusting candidate character strings by application of a lexical analysis using a predetermined language model to the candidate character strings composed of a plurality of candidate characters constituting a first column of the first index matrix; an index information storing portion for storing the second index matrix prepared by the feature similarity measurement portion, so as to correspond to the inputted document image; and a searching section for searching, in a searching operation, the index information storing portion in units of search character constituting a search keyword of an inputted search formula, to take out the document image which includes the second index matrix containing the search character, wherein a position-based correlation value is set for each of the elements in the second index matrix, and the searching section comprises: an index matrix search processing portion for searching the index information storing portion for the second index matrix in units of search character constituting the search keyword to detect the second index matrix containing the search characters, and storing in a storing portion, information of matching position of search characters in the second index matrix together with information of the document images having the second index matrix; a degree-of-correlation calculating portion for calculating a degree of correlation between the search keyword and the second index matrix by accumulating correlation values of the respective search characters according to the information of matching position stored in the storing portion; and an order determining portion for determining a take-out order of document image based on the calculated result of the degree-of-correlation calculating portion. | 1. A document image processing apparatus comprising: a character image feature dictionary for storing image features of character images in units of character; a character string clipping portion for clipping character images in units of character string composed of a plurality of characters from an inputted document image; an image feature extracting portion for extracting an image feature of each character image which is obtained by dividing character images of character string clipped by the character string clipping portion, for each of the characters; a feature similarity measurement portion for selecting N (N>1, integer) pieces of character images in descending order of degree of similarity of image feature as candidate characters, from the character image feature dictionary which stores image features of character image in units of character based on the image features of each of the character images extracted by the image feature extracting portion, preparing a first index matrix of M×N cells where M (M>1, integer) represents a number of characters in the clipped character string, and preparing a second index matrix of character strings including a meaningful character string which is formed by adjusting candidate character strings by application of a lexical analysis using a predetermined language model to the candidate character strings composed of a plurality of candidate characters constituting a first column of the first index matrix; an index information storing portion for storing the second index matrix prepared by the feature similarity measurement portion, so as to correspond to the inputted document image; and a searching section for searching, in a searching operation, the index information storing portion in units of search character constituting a search keyword of an inputted search formula, to take out the document image which includes the second index matrix containing the search character, wherein a position-based correlation value is set for each of the elements in the second index matrix, and the searching section comprises: an index matrix search processing portion for searching the index information storing portion for the second index matrix in units of search character constituting the search keyword to detect the second index matrix containing the search characters, and storing in a storing portion, information of matching position of search characters in the second index matrix together with information of the document images having the second index matrix; a degree-of-correlation calculating portion for calculating a degree of correlation between the search keyword and the second index matrix by accumulating correlation values of the respective search characters according to the information of matching position stored in the storing portion; and an order determining portion for determining a take-out order of document image based on the calculated result of the degree-of-correlation calculating portion. 10. The document image processing apparatus of claim 1 , wherein when the information of matching position indicates that the search character is found in adjacent rows in the second index matrix, the degree-of-correlation calculating portion accumulates correlation values of the respective adjacent rows after weighted by a degree-of-correlation weighting factor for rows. | 0.524173 |
10,114,863 | 1 | 4 | 1. A method for suggesting a search query based on terms, the method comprising: receiving, via a processor, a search query having at least a first term; identifying a plurality of related terms having a relationship to the first term, based on prior search queries; determining to ignore a first related term of the plurality of related terms, based on the first related term having not been observed with the first term over a specified time interval; and generating a plurality of predictive suggestions for completing the search query, wherein none of the plurality of predictive suggestions includes the ignored first related term, wherein a first of the plurality of predictive suggestions includes at least the first term, and wherein a second of the plurality of predictive suggestions includes an identified semantic equivalent of the first term and a second related term of the plurality of related terms, wherein the identified semantic equivalent is synonymous with the first term. | 1. A method for suggesting a search query based on terms, the method comprising: receiving, via a processor, a search query having at least a first term; identifying a plurality of related terms having a relationship to the first term, based on prior search queries; determining to ignore a first related term of the plurality of related terms, based on the first related term having not been observed with the first term over a specified time interval; and generating a plurality of predictive suggestions for completing the search query, wherein none of the plurality of predictive suggestions includes the ignored first related term, wherein a first of the plurality of predictive suggestions includes at least the first term, and wherein a second of the plurality of predictive suggestions includes an identified semantic equivalent of the first term and a second related term of the plurality of related terms, wherein the identified semantic equivalent is synonymous with the first term. 4. The method of claim 1 , wherein at least one of the plurality of predictive suggestions specifies a suggested search query that includes at least one of the plurality of related terms preceding the first term. | 0.797323 |
8,527,260 | 20 | 21 | 20. The system of claim 17 , further comprising: program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to store an indication of selections requested to have original replacement language by a plurality of users; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to analyze the selections by the plurality of users to determine frequency of requests for a particular section; and in response to the program instructions to determine that the frequency of requests for the particular section exceeds a threshold, program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to perform a remedial action for the particular selection. | 20. The system of claim 17 , further comprising: program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to store an indication of selections requested to have original replacement language by a plurality of users; program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to analyze the selections by the plurality of users to determine frequency of requests for a particular section; and in response to the program instructions to determine that the frequency of requests for the particular section exceeds a threshold, program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to perform a remedial action for the particular selection. 21. The system of claim 20 , further comprising program instructions, stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, to determine results for remedial actions for any particular selections over the threshold and to store the results. | 0.5 |
7,721,214 | 1 | 2 | 1. An article comprising: a computer readable storage medium having stored thereon executable instructions that in response to being executed by one or more processors of a client-side computerized device operatively enable the one or more processors to: access information from an application layer interface; access a first parameter that is related to content, and a second parameter that identifies a linked set of documents; and in response to an input received through a single selectable feature of a user interface indicating a desire to advance to a next location within the linked set of documents that includes an instance of the content related to the first parameter: for a currently open document if the content is present in the currently open document, setting the next location to correspond to at least a portion of the currently open document in which the content is present; if the content is not present in the currently open document, identifying a next document within the linked set of documents in which the content is present, and setting the next location to correspond to at least a portion of the next document in which the content is present; and initiate display of the next location via a computer display monitor. | 1. An article comprising: a computer readable storage medium having stored thereon executable instructions that in response to being executed by one or more processors of a client-side computerized device operatively enable the one or more processors to: access information from an application layer interface; access a first parameter that is related to content, and a second parameter that identifies a linked set of documents; and in response to an input received through a single selectable feature of a user interface indicating a desire to advance to a next location within the linked set of documents that includes an instance of the content related to the first parameter: for a currently open document if the content is present in the currently open document, setting the next location to correspond to at least a portion of the currently open document in which the content is present; if the content is not present in the currently open document, identifying a next document within the linked set of documents in which the content is present, and setting the next location to correspond to at least a portion of the next document in which the content is present; and initiate display of the next location via a computer display monitor. 2. The article of claim 1 , wherein at least one of the first parameter and/or second parameter are accessed via a user interface that comprises an interactive menu. | 0.744582 |
9,430,561 | 14 | 15 | 14. A non-transitory computer-readable storage medium comprising: instructions for identifying a topic group of users of a social networking system that have expressed an affinity for a page of the social networking system that corresponds to a first topic; instructions for identifying a category that includes the first topic and a plurality of other topics; instructions for identifying a category group of users of the social networking system that have expressed an affinity for a page corresponding to at least one of the topics included in the category; instructions for identifying a plurality of candidate pages of the social networking system, each candidate page having a corresponding candidate topic; instructions for, for each candidate page of the plurality of pages of a social networking system computing a user interest measure quantifying an amount of interest expressed by users of the topic group in the topic corresponding to the candidate page, computing a category interest measure quantifying an amount of interest expressed by users of the category group in the topic corresponding to the candidate page, and computing a divergence measure based on the user interest measure and the category interest measure; instructions for generating, for the first topic, a topic profile based on the divergence measures; and instructions for storing the topic profile. | 14. A non-transitory computer-readable storage medium comprising: instructions for identifying a topic group of users of a social networking system that have expressed an affinity for a page of the social networking system that corresponds to a first topic; instructions for identifying a category that includes the first topic and a plurality of other topics; instructions for identifying a category group of users of the social networking system that have expressed an affinity for a page corresponding to at least one of the topics included in the category; instructions for identifying a plurality of candidate pages of the social networking system, each candidate page having a corresponding candidate topic; instructions for, for each candidate page of the plurality of pages of a social networking system computing a user interest measure quantifying an amount of interest expressed by users of the topic group in the topic corresponding to the candidate page, computing a category interest measure quantifying an amount of interest expressed by users of the category group in the topic corresponding to the candidate page, and computing a divergence measure based on the user interest measure and the category interest measure; instructions for generating, for the first topic, a topic profile based on the divergence measures; and instructions for storing the topic profile. 15. The non-transitory computer-readable storage medium of claim 14 , further comprising: instructions for computing a first topic affinity score for a first user not in the topic group by applying the topic profile to information of the social networking system about the first user; and instructions for predicting, based on the first topic affinity score, that the first user has an affinity for the first topic. | 0.5 |
9,665,563 | 1 | 12 | 1. An animation script generating device, comprising: a processor configured to execute instructions for an emotion extractor configured to identify, from a user profile database, a character corresponding to a generator of text-based data and user relationship information, the text-based data being analyzed to identify words, sentence elements, or any combination thereof in the text-based data, and the user relationship information indicating a relationship between the generator of the text-based data and a receiver of the text-based data, and extract a user emotion based on the text-based data and the user relationship information; a selector configured to select an action based on the extracted user emotion; and a script generator configured to generate an animation script by combining the text-based data with the extracted user emotion and the action, the generated animation script being configured for an input to a terminal that uses an animation outputting device to generate an animation based on the generated animation script, wherein the animation script is generated using a reference database, the reference database comprising a production database configured to store mapping information of at least one of a camera work and a background sound. | 1. An animation script generating device, comprising: a processor configured to execute instructions for an emotion extractor configured to identify, from a user profile database, a character corresponding to a generator of text-based data and user relationship information, the text-based data being analyzed to identify words, sentence elements, or any combination thereof in the text-based data, and the user relationship information indicating a relationship between the generator of the text-based data and a receiver of the text-based data, and extract a user emotion based on the text-based data and the user relationship information; a selector configured to select an action based on the extracted user emotion; and a script generator configured to generate an animation script by combining the text-based data with the extracted user emotion and the action, the generated animation script being configured for an input to a terminal that uses an animation outputting device to generate an animation based on the generated animation script, wherein the animation script is generated using a reference database, the reference database comprising a production database configured to store mapping information of at least one of a camera work and a background sound. 12. The animation script generating device of claim 1 , wherein the user relationship information is pre-stored in the user profile database, and wherein the animation script is generated using a reference database, the reference database comprising at least one of: an emotional vocabulary dictionary database configured to store mapping information of the emotion corresponding to the text-based data and the user relationship information; an emotional inference rule database configured to store mapping information of the inferred emotion corresponding to the text-based data and the user relationship information; and an action rule database configured to store mapping information of an action corresponding to at least one of the extracted emotion and the user relationship information. | 0.5 |
9,361,405 | 6 | 12 | 6. A system for a service recommendation service, comprising: Plurality of collaborative information participants interconnected via a communication network, each participant having zero or more data sources; A computing platform programmed with query services, each query service defining one or more queries operable on authorized portions of participant data sources, the computing platform comprising a hardware processor and instructions, the instructions, when executed by the hardware processor are to: determine a first set of queries that do not expose additional data items stored in a data source of a participant in a collaborative information system than are exposed by queries already implemented on a participants data source; Identify a first set of query services that are not authorized to involve the data source, but which use the first set of queries; Recommend the first set of identified the first set of query services to the participant; Determine a second set of queries implemented on the data source that are used by authorized queries services of the collaborative information system; Identify a second set of additional query services that are not authorized to involve the data source, but which could be authorized by using the additional queries; Observe data items stored in the data source from statements of the second set of query services; Determine, from the observed data items, additional queries that are not implemented on the data source, which search the observed data items; Identify additional query services that are not authorized to involve the data source, but which use the additional queries; and recommend the identified additional query services to the participant. | 6. A system for a service recommendation service, comprising: Plurality of collaborative information participants interconnected via a communication network, each participant having zero or more data sources; A computing platform programmed with query services, each query service defining one or more queries operable on authorized portions of participant data sources, the computing platform comprising a hardware processor and instructions, the instructions, when executed by the hardware processor are to: determine a first set of queries that do not expose additional data items stored in a data source of a participant in a collaborative information system than are exposed by queries already implemented on a participants data source; Identify a first set of query services that are not authorized to involve the data source, but which use the first set of queries; Recommend the first set of identified the first set of query services to the participant; Determine a second set of queries implemented on the data source that are used by authorized queries services of the collaborative information system; Identify a second set of additional query services that are not authorized to involve the data source, but which could be authorized by using the additional queries; Observe data items stored in the data source from statements of the second set of query services; Determine, from the observed data items, additional queries that are not implemented on the data source, which search the observed data items; Identify additional query services that are not authorized to involve the data source, but which use the additional queries; and recommend the identified additional query services to the participant. 12. The system of claim 6 , wherein determining additional query services includes comparing the additional queries to queries in service taxonomy model. | 0.897177 |
9,177,481 | 13 | 15 | 13. A system for determining a suitable landing area for an aircraft, comprising: a processor; and memory having instructions stored thereon that, when executed by the processor, cause the system to: receive signals indicative of terrain information for a terrain with a three-dimension (3D) perception system; receive signals indicative of image information for the terrain with a camera perception system, the image information separate from the terrain information; evaluate the terrain information and generate information indicative of a landing zone candidate region; co-register in a coordinate system the landing zone candidate region and the image information; segment image regions corresponding to the landing zone candidate regions to generate segmented regions; classify the segmented regions into semantic classes; determine contextual information from a contextual model and using the contextual information to detect an error in at least one semantic class; and ranking and prioritizing the semantic class. | 13. A system for determining a suitable landing area for an aircraft, comprising: a processor; and memory having instructions stored thereon that, when executed by the processor, cause the system to: receive signals indicative of terrain information for a terrain with a three-dimension (3D) perception system; receive signals indicative of image information for the terrain with a camera perception system, the image information separate from the terrain information; evaluate the terrain information and generate information indicative of a landing zone candidate region; co-register in a coordinate system the landing zone candidate region and the image information; segment image regions corresponding to the landing zone candidate regions to generate segmented regions; classify the segmented regions into semantic classes; determine contextual information from a contextual model and using the contextual information to detect an error in at least one semantic class; and ranking and prioritizing the semantic class. 15. The system of claim 13 , wherein the processor is configured to receive the terrain data as a 3D point cloud data. | 0.714976 |
8,812,946 | 1 | 3 | 1. A computerized method for generating an online collaborative editable document to be rendered by a web browser, comprising: receiving, at a server, a raw online collaborative editable document, having one or more data objects including one or more graphical elements and one or more textual elements, wherein the raw online collaborative editable document is configured to be rendered in a graphical format in a web browser and the raw document includes one or more presentation slides, one or more spreadsheets, or one or more word-processing document pages; identifying, at the server, the one or more graphical elements from the raw document, and generating a graphical data file including the one or more identified graphical elements; identifying, at the server, the one or more textual elements from the raw document, and generating a textual data file including the one or more identified textual elements, wherein the textual data file includes Hypertext Markup Language (HTML) data and Cascading Style Sheets (CSS) data, wherein generating the textual data file including the one or more textual elements includes identifying the one or more textual elements in the document and generating the textual data file having HTML data and CSS data representative of content and appearance of only the one or more identified textual elements; identifying, at the server, alignment of the one or more graphical elements and alignment of the one or more textual elements; adding, at the server, HTML and CSS data to the textual data file to include the graphical data file, thereby generating a composite document, wherein the CSS data aligns graphical elements with textual elements matching the alignment of the one or more graphical elements and the one or more textual elements in the raw document; and wherein, when rendered by the web browser, the textual data file overlays the graphical data file such that alignment, content and appearance of one or more graphical elements and one or more textual elements of the composite document are the same as the alignment, content and appearance of the one or more graphical elements and the one or more textual elements of the raw document. | 1. A computerized method for generating an online collaborative editable document to be rendered by a web browser, comprising: receiving, at a server, a raw online collaborative editable document, having one or more data objects including one or more graphical elements and one or more textual elements, wherein the raw online collaborative editable document is configured to be rendered in a graphical format in a web browser and the raw document includes one or more presentation slides, one or more spreadsheets, or one or more word-processing document pages; identifying, at the server, the one or more graphical elements from the raw document, and generating a graphical data file including the one or more identified graphical elements; identifying, at the server, the one or more textual elements from the raw document, and generating a textual data file including the one or more identified textual elements, wherein the textual data file includes Hypertext Markup Language (HTML) data and Cascading Style Sheets (CSS) data, wherein generating the textual data file including the one or more textual elements includes identifying the one or more textual elements in the document and generating the textual data file having HTML data and CSS data representative of content and appearance of only the one or more identified textual elements; identifying, at the server, alignment of the one or more graphical elements and alignment of the one or more textual elements; adding, at the server, HTML and CSS data to the textual data file to include the graphical data file, thereby generating a composite document, wherein the CSS data aligns graphical elements with textual elements matching the alignment of the one or more graphical elements and the one or more textual elements in the raw document; and wherein, when rendered by the web browser, the textual data file overlays the graphical data file such that alignment, content and appearance of one or more graphical elements and one or more textual elements of the composite document are the same as the alignment, content and appearance of the one or more graphical elements and the one or more textual elements of the raw document. 3. The computerized method of claim 1 , wherein the graphical elements include non-textual elements including at least one of shapes, images, audio and video. | 0.712727 |
9,679,561 | 1 | 6 | 1. A method comprising: receiving speech from a user as part of a speech dialog between the user and a speech recognition service; identifying, based on the speech, a speech pattern of the user; identifying, based on the speech pattern of the user, a plurality of speech recognition models stored in a cloud computing storage environment, each speech recognition model of the plurality of speech recognition models being from a respective speech recognition domain; combining, via a processor, the plurality of speech recognition models, to yield a multi-domain combined speech recognition model; identifying in the speech a specific speech recognition domain, wherein the specific speech recognition domain does not match a specific speech recognition model in the plurality of speech recognition models; receiving sample data associated with the specific speech recognition domain, wherein the sample data is independent of the speech dialog between the user and the speech recognition service; when the sample data is more than a minimum threshold, generating a new domain-specific speech recognition model for the specific speech recognition domain; and when the sample data is less than the minimum threshold, modifying the multi-domain combined speech recognition model specifically to the specific speech recognition domain by weighting components of the multi-domain combined speech recognition model associated with the specific speech recognition domain to have more influence in recognition of the speech from the user. | 1. A method comprising: receiving speech from a user as part of a speech dialog between the user and a speech recognition service; identifying, based on the speech, a speech pattern of the user; identifying, based on the speech pattern of the user, a plurality of speech recognition models stored in a cloud computing storage environment, each speech recognition model of the plurality of speech recognition models being from a respective speech recognition domain; combining, via a processor, the plurality of speech recognition models, to yield a multi-domain combined speech recognition model; identifying in the speech a specific speech recognition domain, wherein the specific speech recognition domain does not match a specific speech recognition model in the plurality of speech recognition models; receiving sample data associated with the specific speech recognition domain, wherein the sample data is independent of the speech dialog between the user and the speech recognition service; when the sample data is more than a minimum threshold, generating a new domain-specific speech recognition model for the specific speech recognition domain; and when the sample data is less than the minimum threshold, modifying the multi-domain combined speech recognition model specifically to the specific speech recognition domain by weighting components of the multi-domain combined speech recognition model associated with the specific speech recognition domain to have more influence in recognition of the speech from the user. 6. The method of claim 1 , wherein the multi-domain combined speech recognition model and one of the plurality of speech recognition models are from different domains. | 0.680077 |
9,501,455 | 1 | 6 | 1. A method for processing data, the method comprising: receiving, at a data processing tool, at least one data file including at least partially unstructured data from at least one data source, wherein the at least partially unstructured data includes actual data from a main application; processing, by a processor, the at least partially unstructured data to generate at least partially structured data that includes tagged data, wherein the tagged data includes a tag inserted to precede at least one identified term of interest, and wherein processing the at least partially unstructured data comprises at least one of: processing the at least partially unstructured data using an associative memory application that tags the at least one term of interest based on a generated identification score exceeding a predetermined threshold where the score is determined based on the number of matching terms between a segment of unstructured text and a segment of text in the associative memory application; and processing the at least partially unstructured data using a regular expression processing program; transmitting the at least one data file including the at least partially structured data to the main application; incorporating the at least partially structured data into the main application based at least in part on the tagged data, wherein incorporating the at least partially structured data comprises at least one of including and excluding data based on at least one of existence, content and type of a tag; displaying, at a user interface, the at least partially structured data, wherein at least partially structured data includes at least one segment of misidentified data that is at least one of incorrectly tagged and incorrectly not tagged; receiving, at the user interface, a user selection of at least one segment of misidentified data; updating the misidentified data to form re-identified data; updating the associative memory application to include the re-identified data that includes data that has been correctly tagged or correctly not tagged; receiving, at the data processing tool, text segments generated by parsing the at least partially unstructured data into discrete text segments; identifying one or more of the text segments as boilerplate data based on a comparison between the text segments and strings of text in a column incorporated in an associative memory application, wherein the text segments need not exactly match the strings of text in the associative memory application; and incorporating data including text segments parsed from the at least partially structured data into the main application, wherein the text identified as boilerplate data is excluded from the data incorporated into the main application. | 1. A method for processing data, the method comprising: receiving, at a data processing tool, at least one data file including at least partially unstructured data from at least one data source, wherein the at least partially unstructured data includes actual data from a main application; processing, by a processor, the at least partially unstructured data to generate at least partially structured data that includes tagged data, wherein the tagged data includes a tag inserted to precede at least one identified term of interest, and wherein processing the at least partially unstructured data comprises at least one of: processing the at least partially unstructured data using an associative memory application that tags the at least one term of interest based on a generated identification score exceeding a predetermined threshold where the score is determined based on the number of matching terms between a segment of unstructured text and a segment of text in the associative memory application; and processing the at least partially unstructured data using a regular expression processing program; transmitting the at least one data file including the at least partially structured data to the main application; incorporating the at least partially structured data into the main application based at least in part on the tagged data, wherein incorporating the at least partially structured data comprises at least one of including and excluding data based on at least one of existence, content and type of a tag; displaying, at a user interface, the at least partially structured data, wherein at least partially structured data includes at least one segment of misidentified data that is at least one of incorrectly tagged and incorrectly not tagged; receiving, at the user interface, a user selection of at least one segment of misidentified data; updating the misidentified data to form re-identified data; updating the associative memory application to include the re-identified data that includes data that has been correctly tagged or correctly not tagged; receiving, at the data processing tool, text segments generated by parsing the at least partially unstructured data into discrete text segments; identifying one or more of the text segments as boilerplate data based on a comparison between the text segments and strings of text in a column incorporated in an associative memory application, wherein the text segments need not exactly match the strings of text in the associative memory application; and incorporating data including text segments parsed from the at least partially structured data into the main application, wherein the text identified as boilerplate data is excluded from the data incorporated into the main application. 6. The method according to claim 1 , further comprising: updating the data processing tool based on the at least one segment of misidentified data. | 0.884977 |
7,962,438 | 10 | 11 | 10. The system of claim 9 wherein the one or more relationships are established using a cluster analysis. | 10. The system of claim 9 wherein the one or more relationships are established using a cluster analysis. 11. The system of claim 10 wherein the cluster analysis further comprises a clustering algorithm. | 0.529126 |
7,885,426 | 5 | 6 | 5. The system of claim 1 wherein the copyright holder identifying module is further operable to identify copyrighted content and wherein the copyright holder is remunerated for copying of the copyrighted content. | 5. The system of claim 1 wherein the copyright holder identifying module is further operable to identify copyrighted content and wherein the copyright holder is remunerated for copying of the copyrighted content. 6. The system of claim 5 wherein the amount of remuneration is based on the number of copies made. | 0.824373 |
7,657,935 | 40 | 43 | 40. A system for detecting an occurrence of a violation of an email security policy of a computer system by transmission of selected email through said computer system comprising: a client comprising: (i) an email server configured to receive and transmit said selected email for one or more email accounts; (ii) a client database configured to store information relating to said selected email and a model derived from statistics relating to transmission behavior of prior emails transmitted through said computer system; and (iii) an analysis component configured to define a model for said selected email based on statistics relating to transmission behavior of said selected email, wherein the model is configured to group email addresses in said prior emails into one or more cliques based on the occurrence of said email addresses in common prior emails and compare said selected email model and said model derived from statistics relating to transmission behavior of said prior emails based on whether email addresses in said new email are members of more than one said clique; (iv) a communications component configured to transmit statistics relating to the selected email to a server. | 40. A system for detecting an occurrence of a violation of an email security policy of a computer system by transmission of selected email through said computer system comprising: a client comprising: (i) an email server configured to receive and transmit said selected email for one or more email accounts; (ii) a client database configured to store information relating to said selected email and a model derived from statistics relating to transmission behavior of prior emails transmitted through said computer system; and (iii) an analysis component configured to define a model for said selected email based on statistics relating to transmission behavior of said selected email, wherein the model is configured to group email addresses in said prior emails into one or more cliques based on the occurrence of said email addresses in common prior emails and compare said selected email model and said model derived from statistics relating to transmission behavior of said prior emails based on whether email addresses in said new email are members of more than one said clique; (iv) a communications component configured to transmit statistics relating to the selected email to a server. 43. The system as recited in claim 40 , wherein the client database is configured to store statistics relating to a classification of an email as violative of the email security policy of the computer system. | 0.610487 |
9,323,743 | 1 | 4 | 1. A method for generating a situational analysis text by transforming data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a situational analysis text, the method comprising: assigning, at least one data channel on which an alert condition was identified, as a primary data channel; determining whether one or more data channels that are identified as related to the primary data channel are to be assigned as one or more related data channels, wherein the one or more related data channels are a subset of one or more monitored data channels; generating, using a natural language generation system that is configured to execute on a processor, a graph based at least on the data in the primary data channel, wherein at least a portion of data in the primary data channel comprises numerical data; and generating, using the natural language generation system that is configured to execute on the processor, the situational analysis text for display with the graph, the situational analysis text generated based at least on the data in the primary data channel, wherein the situational analysis text is configured to linguistically express contextual information related to the alert condition and the graph is configured to display numerical data in the primary data as a function of time, wherein at least a portion of the graph and at least a portion of the situational analysis text are generated in response to the identification of the alert condition. | 1. A method for generating a situational analysis text by transforming data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a situational analysis text, the method comprising: assigning, at least one data channel on which an alert condition was identified, as a primary data channel; determining whether one or more data channels that are identified as related to the primary data channel are to be assigned as one or more related data channels, wherein the one or more related data channels are a subset of one or more monitored data channels; generating, using a natural language generation system that is configured to execute on a processor, a graph based at least on the data in the primary data channel, wherein at least a portion of data in the primary data channel comprises numerical data; and generating, using the natural language generation system that is configured to execute on the processor, the situational analysis text for display with the graph, the situational analysis text generated based at least on the data in the primary data channel, wherein the situational analysis text is configured to linguistically express contextual information related to the alert condition and the graph is configured to display numerical data in the primary data as a function of time, wherein at least a portion of the graph and at least a portion of the situational analysis text are generated in response to the identification of the alert condition. 4. The method according to claim 1 , further comprising: determining one or more causes of the alert condition; and causing one or more related data channels to be selected that correspond to the one or more causes of the alert condition, wherein the situational analysis text is further configured to linguistically express the one or more causes of the alert condition. | 0.642582 |
9,336,769 | 1 | 3 | 1. A computer-implemented confidence measure calculation method of calculating a confidence measure of a target word string specified in a recognition result, the method comprising: a processor receiving the recognition result and the target word string; generating, with the processor, an alternative candidate word string in a position of the target word string; obtaining training data from a training data storage; training, with the processor, a classifier which is configured to discriminate between the target word string and the alternative candidate word string, using the training data; extracting a feature value representing an adjacent context in the position of the target word string; determining, with the processor, whether a true word string in the position of the target word string is the target word string or the alternative candidate word string by using the classifier and the feature value; and calculating, with the processor, a confidence measure of the target word string on the basis of the determination result and storing the confidence measure in a calculation result storage. | 1. A computer-implemented confidence measure calculation method of calculating a confidence measure of a target word string specified in a recognition result, the method comprising: a processor receiving the recognition result and the target word string; generating, with the processor, an alternative candidate word string in a position of the target word string; obtaining training data from a training data storage; training, with the processor, a classifier which is configured to discriminate between the target word string and the alternative candidate word string, using the training data; extracting a feature value representing an adjacent context in the position of the target word string; determining, with the processor, whether a true word string in the position of the target word string is the target word string or the alternative candidate word string by using the classifier and the feature value; and calculating, with the processor, a confidence measure of the target word string on the basis of the determination result and storing the confidence measure in a calculation result storage. 3. The method according to claim 1 , wherein the classifier is configured to output a posterior probability of classification result, and the posterior probability that the target word string is correct is used as the confidence measure of the target word string. | 0.723739 |
9,324,034 | 23 | 24 | 23. The server of claim 22 , wherein further comprising: means for applying the factors to the corpus of behavior vectors to generate a second family of classifier models that identify fewer data points as being relevant for enabling the mobile device to conclusively determine whether the mobile device behavior is not benign; and means for generating a mobile device classifier based on the second family of classifier models. | 23. The server of claim 22 , wherein further comprising: means for applying the factors to the corpus of behavior vectors to generate a second family of classifier models that identify fewer data points as being relevant for enabling the mobile device to conclusively determine whether the mobile device behavior is not benign; and means for generating a mobile device classifier based on the second family of classifier models. 24. The server of claim 23 , wherein further comprising: means for sending the generated mobile device classifier to a mobile computing device. | 0.5 |
8,463,786 | 2 | 5 | 2. The process of claim 1 , wherein the process action of accessing a set of topically related documents comprises an action of accessing documents identified in a prescribed number of the top ranking search results found in one or more searches based on a search query pertaining a topic of interest. | 2. The process of claim 1 , wherein the process action of accessing a set of topically related documents comprises an action of accessing documents identified in a prescribed number of the top ranking search results found in one or more searches based on a search query pertaining a topic of interest. 5. The process of claim 2 , wherein the search query is constructed using a Uniform Resource Locator (URL) corresponding to a user-supplied document or a document a user is accessing. | 0.5 |
9,544,254 | 1 | 14 | 1. A system, comprising: a one or more computing servers; a one or more network interfaces; non-transitory computer readable memory storing program code that when executed by the one or more computing servers is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; receive a verified phone address associated with the user, wherein the verification of the phone address comprises verification that a received set of digits is a valid phone address; based at least in part on the receipt of the verified phone address, create a user account wherein the verified phone address is associated with the user account; enable delivery of a voice message directed to the user to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the user to play the voice message via a web browser of a second computing device associated with the user; and in response to a voice message deletion instruction received via the web browser of the second computing device associated with the user, enable at least in part, synchronization of the deletion of the voice message stored on the first computing device associated with the user in cooperation with the software program on the first computing device associated with of the user. | 1. A system, comprising: a one or more computing servers; a one or more network interfaces; non-transitory computer readable memory storing program code that when executed by the one or more computing servers is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; receive a verified phone address associated with the user, wherein the verification of the phone address comprises verification that a received set of digits is a valid phone address; based at least in part on the receipt of the verified phone address, create a user account wherein the verified phone address is associated with the user account; enable delivery of a voice message directed to the user to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the user to play the voice message via a web browser of a second computing device associated with the user; and in response to a voice message deletion instruction received via the web browser of the second computing device associated with the user, enable at least in part, synchronization of the deletion of the voice message stored on the first computing device associated with the user in cooperation with the software program on the first computing device associated with of the user. 14. The system as defined in claim 1 , the system is further configured to: determine the country of origin of a valid phone address from the received set of digits. | 0.766289 |
9,411,899 | 2 | 3 | 2. The system of claim 1 , wherein the at least one navigation application is further configured to: cause the first different page to be displayed on the device; receive a user action on the first different page; and cause the current page to be displayed on the device in response to the user action. | 2. The system of claim 1 , wherein the at least one navigation application is further configured to: cause the first different page to be displayed on the device; receive a user action on the first different page; and cause the current page to be displayed on the device in response to the user action. 3. The system of claim 2 , wherein: the user action comprises a user action on one of the functional options of the first different page. | 0.5 |
7,558,841 | 2 | 3 | 2. The method of claim 1 , further comprising sending a status message to the user interface when the search response packet does not contain the at least one search result to the search query for data. | 2. The method of claim 1 , further comprising sending a status message to the user interface when the search response packet does not contain the at least one search result to the search query for data. 3. The method of claim 2 , wherein the status message comprises a notification that no results were returned for the search query for data. | 0.5 |
8,817,311 | 1 | 3 | 1. A method of rendering documents in a distributed system comprising a local client computer and a server computer, the method comprising: identifying a list of tasks to be performed in association with an input, wherein said list of tasks comprises one or more tasks for printing one or more documents; building one or more commands comprising instructions designed to, when executed on one of the local client computer or the server computer, accomplish said list of tasks; sizing said one or more commands in comparison to a threshold size, wherein those smaller than said threshold size are marked as small jobs and the others are marked as large jobs; in response to said one or more commands being marked a small job, rendering said one or more documents suitable for printing via said server computer executing said one or more commands associated with said small job, and sending said document to a printer associated with said local client computer; and in response to said one or more commands being marked a large job, sending said one or more commands associated with said large job to said local client computer for rendering and printing locally. | 1. A method of rendering documents in a distributed system comprising a local client computer and a server computer, the method comprising: identifying a list of tasks to be performed in association with an input, wherein said list of tasks comprises one or more tasks for printing one or more documents; building one or more commands comprising instructions designed to, when executed on one of the local client computer or the server computer, accomplish said list of tasks; sizing said one or more commands in comparison to a threshold size, wherein those smaller than said threshold size are marked as small jobs and the others are marked as large jobs; in response to said one or more commands being marked a small job, rendering said one or more documents suitable for printing via said server computer executing said one or more commands associated with said small job, and sending said document to a printer associated with said local client computer; and in response to said one or more commands being marked a large job, sending said one or more commands associated with said large job to said local client computer for rendering and printing locally. 3. The method of rendering documents of claim 1 , further comprising the step of: acquiring an input; and providing a user interface configured to receive said input from one or more input devices operated by a user at a facility. | 0.776699 |
7,734,996 | 1 | 3 | 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. 3. The documentation browsing apparatus according to claim 1 , comprising playback means for playing back voices or images; where in the correspondence generating means divides voices or images included in audio data or image data and a document included in document data into predetermined sections and generates correspondence between voices or images and a document for said each section; and wherein the document updating means generates, adds, corrects or deletes a document for said each section; and wherein said playback means plays back voices or images of a part associated with at least one section included in said document data among voices or images included in said audio data or said image data. | 0.5 |
8,519,871 | 19 | 21 | 19. A decoder for decoding an encoded sequence, the encoded sequence having been encoded in accordance with a context model, the decoder comprising: a processor; a memory; and a decoding application stored in memory and containing instructions for configuring the processor to read an ordered set of two or more consecutive phrases from the encoded sequence, a first of the phrases in the set containing at least part of one codeword, wherein the phrases are bit strings of a respective predetermined length, determine from the context model a probability estimate associated with the first of the phrases, identify, from the probability estimate of the first phrase, respective probability estimates associated with each of the other phrases in the set, entropy decode at least a portion of each of the two or more phrases of the set in parallel in accordance with their respective associated probability estimates to create decoded phrase bits, and update the context model based upon at least some of the decoded phrase bits, and wherein the respective probability estimates associated with each of the other phrases are determined without dependence upon decoding of the first of the phrases. | 19. A decoder for decoding an encoded sequence, the encoded sequence having been encoded in accordance with a context model, the decoder comprising: a processor; a memory; and a decoding application stored in memory and containing instructions for configuring the processor to read an ordered set of two or more consecutive phrases from the encoded sequence, a first of the phrases in the set containing at least part of one codeword, wherein the phrases are bit strings of a respective predetermined length, determine from the context model a probability estimate associated with the first of the phrases, identify, from the probability estimate of the first phrase, respective probability estimates associated with each of the other phrases in the set, entropy decode at least a portion of each of the two or more phrases of the set in parallel in accordance with their respective associated probability estimates to create decoded phrase bits, and update the context model based upon at least some of the decoded phrase bits, and wherein the respective probability estimates associated with each of the other phrases are determined without dependence upon decoding of the first of the phrases. 21. The decoder claimed in claim 19 , wherein one of the phrases in one set of phrases ends with a first portion of a split codeword, and wherein a phrase in a subsequent set of phrases in the encoded sequence starts with a second portion of the split codeword. | 0.5 |
10,068,583 | 1 | 2 | 1. An uncontrolled environment-based speech recognition system, the system comprising: one or more filters to each generate a set of processed audio data based on raw audio data received from one or more computing devices, the one or more filters applying filter processes to the raw audio data to generate the set of processed audio data, the one or more filters comprising at least one filter appropriate for the uncontrolled environment-based speech recognition system; a translator, operable by a processor, to provide a set of translation results for the raw audio data based on the set of processed audio data, each translation result being associated with at least one processed audio data and each translation result including a text data and a confidence level associated with that text data; and in response to receiving the set of translation results, a decision controller is automatically triggered by the processor to select the text data that represents the raw audio data, the decision controller is operable to: identify at least one translation result from the set of translation results that includes the text data associated with the confidence level that exceeds a confidence threshold; determine whether the identified at least one translation result comprises more than one translation result; in response to determining the identified at least one translation result comprises more than one translation result, determine an occurrence frequency for each text data of the identified at least one translation result and select the text data based on the occurrence frequency, the occurrence frequency representing a number of times that the text data appears in the set of translation results; and generate an output signal associated with the selection by the decision controller. | 1. An uncontrolled environment-based speech recognition system, the system comprising: one or more filters to each generate a set of processed audio data based on raw audio data received from one or more computing devices, the one or more filters applying filter processes to the raw audio data to generate the set of processed audio data, the one or more filters comprising at least one filter appropriate for the uncontrolled environment-based speech recognition system; a translator, operable by a processor, to provide a set of translation results for the raw audio data based on the set of processed audio data, each translation result being associated with at least one processed audio data and each translation result including a text data and a confidence level associated with that text data; and in response to receiving the set of translation results, a decision controller is automatically triggered by the processor to select the text data that represents the raw audio data, the decision controller is operable to: identify at least one translation result from the set of translation results that includes the text data associated with the confidence level that exceeds a confidence threshold; determine whether the identified at least one translation result comprises more than one translation result; in response to determining the identified at least one translation result comprises more than one translation result, determine an occurrence frequency for each text data of the identified at least one translation result and select the text data based on the occurrence frequency, the occurrence frequency representing a number of times that the text data appears in the set of translation results; and generate an output signal associated with the selection by the decision controller. 2. The speech recognition system of claim 1 , wherein the filter processes comprise at least two different filter processes. | 0.897858 |
9,436,287 | 18 | 20 | 18. A method for processing detected audio waveforms in a first mode and a second mode, comprising: detecting, by a microphone, one or more audio waveforms; time stamping the detected one or more audio waveforms; detecting, by a gesture detection sensor, one or more touchless gestures corresponding to one or more modes; time stamping a starting time and an ending time of each of the detected one or more touchless gestures; storing, in a buffer, the one or more audio waveforms and information regarding the one or more touchless gestures; and entering the second mode and selectively processing, by one or more processors coupled to the microphone, an audio waveform of the one or more audio waveforms in the second mode when a time stamp of the audio waveform is between a first time stamp of a first touchless gesture corresponding to the second mode detected by the gesture detection sensor and a second time stamp associated with one of the one or more touchless gestures. | 18. A method for processing detected audio waveforms in a first mode and a second mode, comprising: detecting, by a microphone, one or more audio waveforms; time stamping the detected one or more audio waveforms; detecting, by a gesture detection sensor, one or more touchless gestures corresponding to one or more modes; time stamping a starting time and an ending time of each of the detected one or more touchless gestures; storing, in a buffer, the one or more audio waveforms and information regarding the one or more touchless gestures; and entering the second mode and selectively processing, by one or more processors coupled to the microphone, an audio waveform of the one or more audio waveforms in the second mode when a time stamp of the audio waveform is between a first time stamp of a first touchless gesture corresponding to the second mode detected by the gesture detection sensor and a second time stamp associated with one of the one or more touchless gestures. 20. The method of claim 18 , further comprising processing the audio waveform in the first mode when a time stamp of the audio waveform is before the first time stamp or after the second time stamp. | 0.877171 |
8,972,432 | 13 | 18 | 13. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause data processing apparatus to perform operations comprising: providing a received input segment of text in a source language to be translated into a particular target language as a query to a search engine, the search engine searching an index of one or more collections of documents; receiving one or more candidate segments in the source language in response to the query; determining a similarity of each candidate segment to the received input segment; for one or more candidate segments in the source language having a determined similarity that exceeds a threshold similarity, providing a translated target segment corresponding to the respective candidate segment as a target language translation of the input segment; and for a candidate segment in the source language having a determined similarity that does not exceed the threshold similarity: identifying one or more subsegments of the input segment, providing each of the one or more subsegments of the input segment as a respective query to the search engine, and for each provided subsegment: receiving one or more candidate subsegments in the source language in response to the respective query, and determining a similarity of each candidate subsegment to the provided subsegment; using the similarity of the one or more candidate subsegments to determine one or more non-matching subsegments of the one or more subsegments; replacing the one or more non-matching subsegments with respective substitute subsegments in the source language to form a substitute candidate segment; and in response to determining that the substitute candidate segment has a similarity to the input segment exceeding the threshold similarity, providing a translated target segment in the target language corresponding to the substitute candidate segment in the source language as a target language translation of the input segment. | 13. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause data processing apparatus to perform operations comprising: providing a received input segment of text in a source language to be translated into a particular target language as a query to a search engine, the search engine searching an index of one or more collections of documents; receiving one or more candidate segments in the source language in response to the query; determining a similarity of each candidate segment to the received input segment; for one or more candidate segments in the source language having a determined similarity that exceeds a threshold similarity, providing a translated target segment corresponding to the respective candidate segment as a target language translation of the input segment; and for a candidate segment in the source language having a determined similarity that does not exceed the threshold similarity: identifying one or more subsegments of the input segment, providing each of the one or more subsegments of the input segment as a respective query to the search engine, and for each provided subsegment: receiving one or more candidate subsegments in the source language in response to the respective query, and determining a similarity of each candidate subsegment to the provided subsegment; using the similarity of the one or more candidate subsegments to determine one or more non-matching subsegments of the one or more subsegments; replacing the one or more non-matching subsegments with respective substitute subsegments in the source language to form a substitute candidate segment; and in response to determining that the substitute candidate segment has a similarity to the input segment exceeding the threshold similarity, providing a translated target segment in the target language corresponding to the substitute candidate segment in the source language as a target language translation of the input segment. 18. The computer program product of claim 13 , where providing the target segment corresponding to the candidate segment further includes: using alignment data for the candidate segment to identify a location of the corresponding target segment. | 0.608626 |
8,423,582 | 1 | 7 | 1. A computer-implemented method performed by one or more computer processors for database message building, comprising: displaying, through a user interface of a computer system, both an item window including structured data associated with at least one field of a record selected in a database and a message building window separate and distinct from the item window; receiving, from a user, unstructured data through the message building window and at least one selection of the structured data through the item window; and displaying a message in the message building window, the message including the unstructured data combined with a token representing the at least one selected structured data; wherein the message building window enables the user to publish the displayed message to an external source; and the receiving the at least one selection of the structured data through the item window further comprises: determining the user dragged the field in the item window to the message building window at a specific position; and populating the message building window with the token representing the selected structured data at the specified position. | 1. A computer-implemented method performed by one or more computer processors for database message building, comprising: displaying, through a user interface of a computer system, both an item window including structured data associated with at least one field of a record selected in a database and a message building window separate and distinct from the item window; receiving, from a user, unstructured data through the message building window and at least one selection of the structured data through the item window; and displaying a message in the message building window, the message including the unstructured data combined with a token representing the at least one selected structured data; wherein the message building window enables the user to publish the displayed message to an external source; and the receiving the at least one selection of the structured data through the item window further comprises: determining the user dragged the field in the item window to the message building window at a specific position; and populating the message building window with the token representing the selected structured data at the specified position. 7. The method of claim 1 , where displaying the message in the message building window further comprises: displaying a preset text string in the message building window; receiving input specifying an edit to the preset text string; and editing the preset text string based on the input. | 0.772655 |
7,478,142 | 27 | 28 | 27. A method for generating a first package such that an application may be automatically executed by a browser on a client computer, the method comprising: generating a first archive of files that include instructions and content needed to execute the application, the first archive including: an initial file that includes instructions for initiating execution of the application, the initial file being a markup language file, other files needed to execute the application, and a second package that includes a second manifest and a second archive of files, the second package being of the same type as the first package, and the second archive of files being of the same type of file structure as the first archive of files; generating a first manifest file that is associated with the first archive, the first manifest file including an initial file identifier that instructs the browser to process the initial file before processing other files in the first archive in order to initiate execution of the application; and encapsulating the first archive of files and the first manifest file within the first package. | 27. A method for generating a first package such that an application may be automatically executed by a browser on a client computer, the method comprising: generating a first archive of files that include instructions and content needed to execute the application, the first archive including: an initial file that includes instructions for initiating execution of the application, the initial file being a markup language file, other files needed to execute the application, and a second package that includes a second manifest and a second archive of files, the second package being of the same type as the first package, and the second archive of files being of the same type of file structure as the first archive of files; generating a first manifest file that is associated with the first archive, the first manifest file including an initial file identifier that instructs the browser to process the initial file before processing other files in the first archive in order to initiate execution of the application; and encapsulating the first archive of files and the first manifest file within the first package. 28. The method of claim 27 , wherein the instructions for initiating execution of the application from the initial file include instructions to process additional instructions from one or more of the other files in the first archive. | 0.594077 |
9,805,120 | 1 | 4 | 1. A computer-implemented method comprising: upon receiving a query, extracting features comprising language of the query, region of a user, both together called original language-region pair, and intent of the query, from the query; categorizing the intent of the query based on context of the query; receiving search results for the query for the original language-region pair; determining whether the query would benefit from issuing the query to another language-region pair based at least in part on the categorized intent and the features extracted from the query; and either: in response to determining that the query would benefit from being issued to another language-region pair: selecting another language-region pair; issuing the query to the other language-region pair; receiving search results for the other language-region pair; merging the search results for the original language-region pair with search results for the other language-region pair; and sending to end user equipment the merged search results; or in response to determining that the query would not benefit from being issued to another language-region pair, sending to end user equipment the search results for the query for the original language-region pair. | 1. A computer-implemented method comprising: upon receiving a query, extracting features comprising language of the query, region of a user, both together called original language-region pair, and intent of the query, from the query; categorizing the intent of the query based on context of the query; receiving search results for the query for the original language-region pair; determining whether the query would benefit from issuing the query to another language-region pair based at least in part on the categorized intent and the features extracted from the query; and either: in response to determining that the query would benefit from being issued to another language-region pair: selecting another language-region pair; issuing the query to the other language-region pair; receiving search results for the other language-region pair; merging the search results for the original language-region pair with search results for the other language-region pair; and sending to end user equipment the merged search results; or in response to determining that the query would not benefit from being issued to another language-region pair, sending to end user equipment the search results for the query for the original language-region pair. 4. The method of claim 1 , wherein receiving search results for the other language-region pair further comprises issuing the query to a ranker for the other language-region pair. | 0.721003 |
9,760,568 | 6 | 13 | 6. A system that enables users of a first environment to interact with a second environment, the system comprising: a memory configured to store instructions; a processor configured to execute the instructions to: enable a first user to navigate the first environment by controlling an avatar representing the first user; capture a first paralinguistic indicator made by the first user, the first paralinguistic indicator representing a first emotion of a first complexity compatible with the first environment; translate the first paralinguistic indicator into a second paralinguistic indicator different from the first paralinguistic indicator, wherein the second paralinguistic indicator is communicated to a second user of the second environment and represents a second emotion of a second complexity different from the first complexity and is compatible with the second environment; wherein at least one of the first complexity and the second complexity is defined as the co-occurrence of two or more emotions. | 6. A system that enables users of a first environment to interact with a second environment, the system comprising: a memory configured to store instructions; a processor configured to execute the instructions to: enable a first user to navigate the first environment by controlling an avatar representing the first user; capture a first paralinguistic indicator made by the first user, the first paralinguistic indicator representing a first emotion of a first complexity compatible with the first environment; translate the first paralinguistic indicator into a second paralinguistic indicator different from the first paralinguistic indicator, wherein the second paralinguistic indicator is communicated to a second user of the second environment and represents a second emotion of a second complexity different from the first complexity and is compatible with the second environment; wherein at least one of the first complexity and the second complexity is defined as the co-occurrence of two or more emotions. 13. The system of claim 6 , wherein the processor is further configured to execute the instructions to: enable the second user to provide preference information related to a description of activities taking place in a sub-portion of the virtual world environment; and provide the second user with the description of activities taking place in the sub-portion of the virtual world environment in accordance with the preference information. | 0.621762 |
9,100,319 | 1 | 13 | 1. A method comprising: receiving, by a network interface of a network device, a packet stream; identifying one or more packets within the packet stream that satisfy one or more conditions of a plurality of predefined conditions specified by a rule by pre-matching, by an acceleration device of the network device, the packet stream with the plurality of predefined conditions; identifying, by the acceleration device, for a full-match processing stage a candidate packet of the one or more packets that satisfies all of the plurality of predefined conditions by correlating the one or more satisfied conditions of the candidate packet; generating, by the acceleration device, for use by the full-match processing stage a matching token and a corresponding location of the matching token within the candidate packet for each of the plurality of predefined conditions; and determining, by a context-aware pattern matching and parsing (CPMP) processor of the acceleration device, whether the candidate packet meets the rule by performing the full-match processing stage including fetching and executing special purpose CPMP instructions to perform context-aware pattern matching processing on the packet, wherein the context-aware pattern matching processing includes one or more of string matching, regular expression matching and packet field value matching based on, for each of the plurality of predefined conditions, corresponding contextual information provided by the rule, the matching token and the corresponding location. | 1. A method comprising: receiving, by a network interface of a network device, a packet stream; identifying one or more packets within the packet stream that satisfy one or more conditions of a plurality of predefined conditions specified by a rule by pre-matching, by an acceleration device of the network device, the packet stream with the plurality of predefined conditions; identifying, by the acceleration device, for a full-match processing stage a candidate packet of the one or more packets that satisfies all of the plurality of predefined conditions by correlating the one or more satisfied conditions of the candidate packet; generating, by the acceleration device, for use by the full-match processing stage a matching token and a corresponding location of the matching token within the candidate packet for each of the plurality of predefined conditions; and determining, by a context-aware pattern matching and parsing (CPMP) processor of the acceleration device, whether the candidate packet meets the rule by performing the full-match processing stage including fetching and executing special purpose CPMP instructions to perform context-aware pattern matching processing on the packet, wherein the context-aware pattern matching processing includes one or more of string matching, regular expression matching and packet field value matching based on, for each of the plurality of predefined conditions, corresponding contextual information provided by the rule, the matching token and the corresponding location. 13. The method of claim 1 , wherein the special purpose CPMP instructions are fetched from an off-chip storage device. | 0.78777 |
9,842,162 | 5 | 10 | 5. A system, comprising: at least one computing device; and an item search application executable in the at least one computing device, wherein when executed the item search application causes the at least one computing device to at least: parse an unstructured search query to identify at least one category of a taxonomy of a collection of items generate a confidence score for each of the at least one category, each of the at least one category being associated with a confidence score, the confidence score being generated using a weighted combination of a plurality of factors, a first factor of the plurality of factors comprising a quality of text match of items in a respective category with the unstructured search query and a second factor of the plurality of factors comprising a number of refinements identified in the unstructured search query that are associated with the respective category, and data associated with the respective category comprising a description of the respective category, and the quality of text match being based at least in part on a frequency that at least a portion of the unstructured search query occurs within the description; identify at least one refinement from the unstructured search query by translating at least one keyword from the unstructured search query into at least one criterion for selecting items from the respective category of the at least one category, wherein the translation is configured to translate a plurality of synonyms into the at least one criterion; applying the at least one refinement to select a first pool of items from the respective category when the confidence score meets a threshold; applying the at least one refinement to select a second pool of items from the collection of items when no confidence score meets the threshold; and generate a network page listing at least a portion of the first or second pool of items that has been selected, the network page including a disambiguation tool when no confidence score meets the threshold, the disambiguation tool providing a user interface for selecting one category from the at least one category. | 5. A system, comprising: at least one computing device; and an item search application executable in the at least one computing device, wherein when executed the item search application causes the at least one computing device to at least: parse an unstructured search query to identify at least one category of a taxonomy of a collection of items generate a confidence score for each of the at least one category, each of the at least one category being associated with a confidence score, the confidence score being generated using a weighted combination of a plurality of factors, a first factor of the plurality of factors comprising a quality of text match of items in a respective category with the unstructured search query and a second factor of the plurality of factors comprising a number of refinements identified in the unstructured search query that are associated with the respective category, and data associated with the respective category comprising a description of the respective category, and the quality of text match being based at least in part on a frequency that at least a portion of the unstructured search query occurs within the description; identify at least one refinement from the unstructured search query by translating at least one keyword from the unstructured search query into at least one criterion for selecting items from the respective category of the at least one category, wherein the translation is configured to translate a plurality of synonyms into the at least one criterion; applying the at least one refinement to select a first pool of items from the respective category when the confidence score meets a threshold; applying the at least one refinement to select a second pool of items from the collection of items when no confidence score meets the threshold; and generate a network page listing at least a portion of the first or second pool of items that has been selected, the network page including a disambiguation tool when no confidence score meets the threshold, the disambiguation tool providing a user interface for selecting one category from the at least one category. 10. The system of claim 5 , wherein when executed the item search application further causes the at least one computing device to at least generate the confidence score for the respective category based at least in part on the at least one refinement. | 0.72658 |
8,793,121 | 15 | 16 | 15. The information processing apparatus according to claim 5 , wherein said sentence to be analyzed is given as an element of a set of sentences that includes multiple sentences; and said information processing apparatus further comprises an information search interface outputting such an element that a matching score acquired satisfies a search condition, among said elements of said set of sentences, as a search result in response to a search request. | 15. The information processing apparatus according to claim 5 , wherein said sentence to be analyzed is given as an element of a set of sentences that includes multiple sentences; and said information processing apparatus further comprises an information search interface outputting such an element that a matching score acquired satisfies a search condition, among said elements of said set of sentences, as a search result in response to a search request. 16. The information processing apparatus according to claim 15 , wherein said information search interface accepts said search condition. | 0.5 |
5,436,832 | 11 | 12 | 11. A guidance system as recited in claim 10 wherein said guidance command generating means includes means for combining a plurality of scaled output control membership functions into a guidance command. | 11. A guidance system as recited in claim 10 wherein said guidance command generating means includes means for combining a plurality of scaled output control membership functions into a guidance command. 12. A guidance system as recited in claim 11 wherein said guidance command generating means additionally comprises constraint means for limiting the range of guidance commands from said guidance command generating means. | 0.5 |
8,601,023 | 1 | 7 | 1. A computer implemented method performed by a processor, comprising: observing usage patterns by one or more users in an on-line community in connection with an on-line asset; identifying usefulness of the on-line asset by observing user implicit behaviors in connection with the usage patterns of the on-line asset and by extracting behavioral patterns from the user implicit behaviors; refining the identified on-line asset usefulness by context, wherein a context of the on-line asset is automatically detected based on one or more observed terms obtained by observing user implicit behaviors with respect to the identified on-line asset, wherein the identified on-line asset has a plurality of term vectors; assigning a term vector entry of a term vector of the plurality of term vectors that describes a degree to which the identified on-line asset has an affinity with the observed terms, wherein each term vector of the plurality of term vectors is associated with a different user of the one or more users; identifying for each user of the one or more users an expertise vector by identifying on-line assets with respect to which the each user has engaged in one or more of the user implicit behaviors; and generating the expertise vector by summing the plurality of term vectors for the identified on-line assets; receive query including query terms; obtaining search result documents; determining that at least one search result document is an identified on-line asset for an expert user of the one or more users; and ranking the at least one search result based on a relationship of the query terms to the expertise vector of the expert user. | 1. A computer implemented method performed by a processor, comprising: observing usage patterns by one or more users in an on-line community in connection with an on-line asset; identifying usefulness of the on-line asset by observing user implicit behaviors in connection with the usage patterns of the on-line asset and by extracting behavioral patterns from the user implicit behaviors; refining the identified on-line asset usefulness by context, wherein a context of the on-line asset is automatically detected based on one or more observed terms obtained by observing user implicit behaviors with respect to the identified on-line asset, wherein the identified on-line asset has a plurality of term vectors; assigning a term vector entry of a term vector of the plurality of term vectors that describes a degree to which the identified on-line asset has an affinity with the observed terms, wherein each term vector of the plurality of term vectors is associated with a different user of the one or more users; identifying for each user of the one or more users an expertise vector by identifying on-line assets with respect to which the each user has engaged in one or more of the user implicit behaviors; and generating the expertise vector by summing the plurality of term vectors for the identified on-line assets; receive query including query terms; obtaining search result documents; determining that at least one search result document is an identified on-line asset for an expert user of the one or more users; and ranking the at least one search result based on a relationship of the query terms to the expertise vector of the expert user. 7. The computer implemented method of claim 1 , further comprising: implicitly building context terms that describe what an asset concerns; and learning the context terms by watching how users implicitly use various terms to describe content through link usage and searches associated with successful usage of content. | 0.728669 |
7,613,688 | 5 | 6 | 5. A method as in claim 1 , further comprising identifying one or more structural elements of the query, wherein the one or more structural elements comprise a dimension, a structure, and a hierarchy. | 5. A method as in claim 1 , further comprising identifying one or more structural elements of the query, wherein the one or more structural elements comprise a dimension, a structure, and a hierarchy. 6. A method as in claim 5 , further comprising identifying combinations of structural elements, wherein the combinations of structural elements comprise any of dimension, structure, and hierarchy. | 0.5 |
8,150,842 | 9 | 10 | 9. The method of claim 8 , wherein the author can have a first alias relating to the first topic and associated with a first reputation score and can have a second alias relating to a second topic and associated with a second reputation score. | 9. The method of claim 8 , wherein the author can have a first alias relating to the first topic and associated with a first reputation score and can have a second alias relating to a second topic and associated with a second reputation score. 10. The method of claim 9 , wherein the first and second aliases are related to each other. | 0.5 |
10,055,476 | 1 | 19 | 1. A computer-implemented method for searching a collection of content, comprising: detecting at least one interaction with search result content, the search result content part of a collection of content provided through an electronic marketplace; detecting at least one fixed phrase based at least in part on the detected at least one interaction with the search result content, the search result content associated with a column in a relevance matrix, the relevance matrix maintained in a data store in a distributed environment that utilizes a plurality of network resources available over a network, the at least one fixed phrase associated with a row in the relevance matrix, the relevance matrix corresponding to a data structure of a content index that indexes the collection of content; determining a position in the relevance matrix corresponding to an intersection of the column and the row; retrieving at least one relevance score at the position to identify at least one determined relevance score for facilitating a search; and updating the content index based at least in part on the at least one interaction and the at least one determined relevance score, the at least one determined relevance score being included in another search of the content index upon updating the relevance matrix. | 1. A computer-implemented method for searching a collection of content, comprising: detecting at least one interaction with search result content, the search result content part of a collection of content provided through an electronic marketplace; detecting at least one fixed phrase based at least in part on the detected at least one interaction with the search result content, the search result content associated with a column in a relevance matrix, the relevance matrix maintained in a data store in a distributed environment that utilizes a plurality of network resources available over a network, the at least one fixed phrase associated with a row in the relevance matrix, the relevance matrix corresponding to a data structure of a content index that indexes the collection of content; determining a position in the relevance matrix corresponding to an intersection of the column and the row; retrieving at least one relevance score at the position to identify at least one determined relevance score for facilitating a search; and updating the content index based at least in part on the at least one interaction and the at least one determined relevance score, the at least one determined relevance score being included in another search of the content index upon updating the relevance matrix. 19. The computer-implemented method of claim 1 , further comprising: ranking items of content in the content index. | 0.885686 |
8,046,227 | 19 | 22 | 19. A development system for developing a dialog application for an interactive voice response system, and comprising: an application builder configured to process application specification data defining tasks performed by the dialog application, items of information needed for the tasks, and information created by executing the tasks to generate application definition data defining a dialog state machine, recognition grammars, and prompt grammars for the dialog application; a scenario generator configured to process the application definition data to a plurality of example interactions representative of interactions between said dialog application and a user of said dialog application, wherein the plurality of the example interactions includes at least one example of a possible prompt corresponding to each rule of a plurality of rules of the prompt grammars, and at least one example of a possible user response corresponding to each rule of a plurality of rules of the recognition grammars; a scenario editor including graphical user interface components for modifying said example interactions; one or more learning components configured to process the modified example interactions to update the recognition grammars, the prompt grammars, and the state machine; a code generator configured to generate the dialog application from the updated state machine, the updated recognition grammars, and the updated prompt grammars. | 19. A development system for developing a dialog application for an interactive voice response system, and comprising: an application builder configured to process application specification data defining tasks performed by the dialog application, items of information needed for the tasks, and information created by executing the tasks to generate application definition data defining a dialog state machine, recognition grammars, and prompt grammars for the dialog application; a scenario generator configured to process the application definition data to a plurality of example interactions representative of interactions between said dialog application and a user of said dialog application, wherein the plurality of the example interactions includes at least one example of a possible prompt corresponding to each rule of a plurality of rules of the prompt grammars, and at least one example of a possible user response corresponding to each rule of a plurality of rules of the recognition grammars; a scenario editor including graphical user interface components for modifying said example interactions; one or more learning components configured to process the modified example interactions to update the recognition grammars, the prompt grammars, and the state machine; a code generator configured to generate the dialog application from the updated state machine, the updated recognition grammars, and the updated prompt grammars. 22. A dialogue application generated by the development system of claim 19 . | 0.865724 |
9,348,429 | 1 | 7 | 1. A method for operating an electronic device having a display and a keyboard having a plurality of input members for receiving inputs, comprising: receiving an input of one or more characters by a first typing digit; detecting a first position of a non-typing digit while receiving the input by the first typing digit, wherein the non-typing digit is a digit other than the typing digit; determining a plurality of reference motion vectors that represent respective possible movements of the non-typing digit from the first position of the non-typing digit to a plurality of possible input members of the keyboard; detecting a second position of the non-typing digit at the end of multiple time points; generating an actual motion vector for the non-typing digit based on the first position and the second position of the non-typing digit; comparing the actual motion vector with the plurality of reference motion vectors; generating a set of word prediction candidates based on the input and the second position of the non-typing digit; weighting the word prediction candidates in the set; adjusting weights for word prediction candidates based on respective closeness between the actual motion vector with the plurality of reference motion vectors; and displaying select ones of the word prediction candidates based on the adjusted weights. | 1. A method for operating an electronic device having a display and a keyboard having a plurality of input members for receiving inputs, comprising: receiving an input of one or more characters by a first typing digit; detecting a first position of a non-typing digit while receiving the input by the first typing digit, wherein the non-typing digit is a digit other than the typing digit; determining a plurality of reference motion vectors that represent respective possible movements of the non-typing digit from the first position of the non-typing digit to a plurality of possible input members of the keyboard; detecting a second position of the non-typing digit at the end of multiple time points; generating an actual motion vector for the non-typing digit based on the first position and the second position of the non-typing digit; comparing the actual motion vector with the plurality of reference motion vectors; generating a set of word prediction candidates based on the input and the second position of the non-typing digit; weighting the word prediction candidates in the set; adjusting weights for word prediction candidates based on respective closeness between the actual motion vector with the plurality of reference motion vectors; and displaying select ones of the word prediction candidates based on the adjusted weights. 7. The method of claim 1 , wherein the non-typing digit is hovering above the keyboard and its position is sensed by capacitive sensors integrated with, situated above, or situated under the input members. | 0.838836 |
8,156,117 | 1 | 27 | 1. A system for storing, searching and retrieval of a plurality of information objects of an arbitrary application domain, comprising: a distributed computer system comprising one or a plurality of computing devices connected with each other by communication lines, a connected logical storage network, wherein each node is an active unit of storage (AUS) and connections between nodes of said network are formed by links of one active units of storage to others, wherein every active unit of storage resides on one of the computing devices of said distributed computer system and comprises: at least one of said plurality of information objects (IOs), each of which is represented in a tree-like structure, a list of links to a certain plurality of other active units of storage by means of which said AUS participates in the operation of the logical storage network, and an associated program agent that allows performing operations on said AUS in connection with searching, storing and retrieving information by user requests using said list of links, wherein a program agent of each active unit of storage compares the IO incorporated into it with the IO of any other AUS and based on the comparison results computes the value of metric distance between the compared IOs and the IOs are electronic documents in the form of XML documents. | 1. A system for storing, searching and retrieval of a plurality of information objects of an arbitrary application domain, comprising: a distributed computer system comprising one or a plurality of computing devices connected with each other by communication lines, a connected logical storage network, wherein each node is an active unit of storage (AUS) and connections between nodes of said network are formed by links of one active units of storage to others, wherein every active unit of storage resides on one of the computing devices of said distributed computer system and comprises: at least one of said plurality of information objects (IOs), each of which is represented in a tree-like structure, a list of links to a certain plurality of other active units of storage by means of which said AUS participates in the operation of the logical storage network, and an associated program agent that allows performing operations on said AUS in connection with searching, storing and retrieving information by user requests using said list of links, wherein a program agent of each active unit of storage compares the IO incorporated into it with the IO of any other AUS and based on the comparison results computes the value of metric distance between the compared IOs and the IOs are electronic documents in the form of XML documents. 27. A method for searching and retrieving information about objects of an arbitrary application domain in the system for storage and retrieval of a plurality of information objects according to claim 1 , comprising the steps of: a) generating a search mask comprising information relevant to the information to be retrieved from said system, and said search mask being an information object (IO) with a tree structure similar to the tree structure of information objects stored in said system, b) generating based on said search mask an active query object (AQO) comprising search criteria, c) comparing the AQO with IOs embedded in a each of the plurality of active units of storage on the logical storage network of said system, wherein moving from AUS to AUS following existing logical connections between them is performed in the direction of decreasing metric distance between the information objects incorporated into AUS, and d) retrieving an IO meeting the search criteria specified in the AQO. | 0.603325 |
8,976,115 | 12 | 13 | 12. The method of claim 11 , wherein the candidate linguistic object subcomponents comprise one of any number of letters or symbols near the direction entered. | 12. The method of claim 11 , wherein the candidate linguistic object subcomponents comprise one of any number of letters or symbols near the direction entered. 13. The method of claim 12 , further comprising utilizing a linguistic model to order said predicted linguistic objects according to likelihood of intended selection by the user wherein the order of said predicted linguistic objects is based either on a combination of weightings and the linguistic model, or the linguistic model comprises one or more of: frequency of occurrence of a linguistic object in formal or conversational written text; frequency of occurrence of a linguistic object when following a preceding linguistic object or linguistic objects; proper or common grammar of the surrounding sentence; application context of current linguistic object entry; and recency of use or repeated use of the linguistic object by the user or within an application program. | 0.5 |
9,413,864 | 7 | 8 | 7. A telephone device, comprising: a mute function, a microphone for sensing sound reaching the telephone device, a processor, a memory, a computer-readable storage device and program code stored on the storage device for execution by the processor via the memory, wherein the program code comprises: program instructions (i) to process, by voice recognition software while the mute function is active, sound detected by the microphone in the telephone device and (ii) to recognize and identify, while the mute function is active, one or more specific words as having been spoken by a specific person and not by another person, and in response, (iii) to activate, while the mute function is active, an alarm in the telephone device to communicate that the mute function is active, wherein the voice recognition software was trained, prior to the sound having been detected, to differentiate the one or more specific words spoken by the specific person from the same one or more specific words spoken by other people, wherein the program code further comprises: program instructions to ascertain, while the mute function is active, that a magnitude of an analog signal representing the detected sound exceeds a predetermined threshold, below which the detected sound is identified as being noise, as part of the identifying that the specific word is spoken by the specific person, wherein the program instructions to activate the alarm is responsive to both the program instructions to ascertain and the program instructions to identify the one or more specific words spoken by the specific person. | 7. A telephone device, comprising: a mute function, a microphone for sensing sound reaching the telephone device, a processor, a memory, a computer-readable storage device and program code stored on the storage device for execution by the processor via the memory, wherein the program code comprises: program instructions (i) to process, by voice recognition software while the mute function is active, sound detected by the microphone in the telephone device and (ii) to recognize and identify, while the mute function is active, one or more specific words as having been spoken by a specific person and not by another person, and in response, (iii) to activate, while the mute function is active, an alarm in the telephone device to communicate that the mute function is active, wherein the voice recognition software was trained, prior to the sound having been detected, to differentiate the one or more specific words spoken by the specific person from the same one or more specific words spoken by other people, wherein the program code further comprises: program instructions to ascertain, while the mute function is active, that a magnitude of an analog signal representing the detected sound exceeds a predetermined threshold, below which the detected sound is identified as being noise, as part of the identifying that the specific word is spoken by the specific person, wherein the program instructions to activate the alarm is responsive to both the program instructions to ascertain and the program instructions to identify the one or more specific words spoken by the specific person. 8. The telephone device of claim 7 , wherein the program code further comprises: program instructions to determine, while the mute function is active, that a magnitude of an analog signal representing another sound detected by the microphone does not exceed the predetermined threshold, and in response to deactivate the alarm. | 0.5 |
6,161,093 | 2 | 5 | 2. An information access system according to claim 1 wherein said terminal further includes speech synthesizing means for synthesizing speech from the phonetic signal information. | 2. An information access system according to claim 1 wherein said terminal further includes speech synthesizing means for synthesizing speech from the phonetic signal information. 5. An information access system according to claim 2 wherein the terminal further includes mark application means for applying a mark to a prescribed position of the synthesized sound outputted by the speech synthesizing means and further wherein the speech synthesizing means resynthesizes and outputs the synthesized sounds from the position of the applied mark. | 0.60262 |
10,134,297 | 9 | 10 | 9. A computer-implemented method of analyzing complexity of a document, comprising: receiving the document with a processing system, the document including a plurality of words; identifying, with the processing system, content words within the document based on parts of speech for the plurality of words; selecting, with the processing system, a plurality of pairs of the content words that appear in a same sentence or paragraph to form multiple groups of content words; determining, with the processing system, an association measure for each group of content words by determining how often the pair of content words in each group appears in a same sentence or paragraph in a corpus of documents; determining, with the processing system, a complexity score for the document based on the association measures determined for each group of content words, wherein determining the complexity of the document includes computing an average of the association measures included in the word association profile, wherein the average is inversely correlated to the complexity of the document. | 9. A computer-implemented method of analyzing complexity of a document, comprising: receiving the document with a processing system, the document including a plurality of words; identifying, with the processing system, content words within the document based on parts of speech for the plurality of words; selecting, with the processing system, a plurality of pairs of the content words that appear in a same sentence or paragraph to form multiple groups of content words; determining, with the processing system, an association measure for each group of content words by determining how often the pair of content words in each group appears in a same sentence or paragraph in a corpus of documents; determining, with the processing system, a complexity score for the document based on the association measures determined for each group of content words, wherein determining the complexity of the document includes computing an average of the association measures included in the word association profile, wherein the average is inversely correlated to the complexity of the document. 10. The computer-implemented method of claim 9 , wherein the complexity score of the document corresponds to a reading level of the document. | 0.5 |
9,471,283 | 1 | 4 | 1. A method comprising: generating a virtualized Application Programming Interface (API) implementation that simulates an API based upon narrative API documentation that comprises sentences that describe the API, wherein the generating is performed by processor circuitry, wherein generating the virtualized API implementation based upon narrative API documentation that comprises sentences that describe the API comprises: generating programming statements for the virtualized API implementation based upon parsing the narrative API documentation that comprises sentences that describe the API; and generating the virtualized API implementation based upon the programming statements for the virtualized API implementation, wherein generating programming statements for the virtualized API implementation based upon parsing the narrative API documentation that comprises sentences that describe the API comprises parsing the narrative API documentation using a domain-specific ontology for the API, wherein parsing the narrative API documentation using the domain-specific ontology for the API comprises: identifying parameters of the API from the narrative API documentation; and identifying normal and abnormal behaviors of the API from the narrative API documentation, wherein the identifying parameters of the API from the narrative API documentation comprises: identifying a type of a parameter; identifying syntactical constraints on a parameter; identifying range constraints on a parameter; identifying invariants of a parameter; identifying transforms of a parameter; and identifying semantic inferences of a parameter, and wherein the method further comprises: converting the parameters of the API and the normal and abnormal behaviors of the API into the programming statements for the virtualized API implementation. | 1. A method comprising: generating a virtualized Application Programming Interface (API) implementation that simulates an API based upon narrative API documentation that comprises sentences that describe the API, wherein the generating is performed by processor circuitry, wherein generating the virtualized API implementation based upon narrative API documentation that comprises sentences that describe the API comprises: generating programming statements for the virtualized API implementation based upon parsing the narrative API documentation that comprises sentences that describe the API; and generating the virtualized API implementation based upon the programming statements for the virtualized API implementation, wherein generating programming statements for the virtualized API implementation based upon parsing the narrative API documentation that comprises sentences that describe the API comprises parsing the narrative API documentation using a domain-specific ontology for the API, wherein parsing the narrative API documentation using the domain-specific ontology for the API comprises: identifying parameters of the API from the narrative API documentation; and identifying normal and abnormal behaviors of the API from the narrative API documentation, wherein the identifying parameters of the API from the narrative API documentation comprises: identifying a type of a parameter; identifying syntactical constraints on a parameter; identifying range constraints on a parameter; identifying invariants of a parameter; identifying transforms of a parameter; and identifying semantic inferences of a parameter, and wherein the method further comprises: converting the parameters of the API and the normal and abnormal behaviors of the API into the programming statements for the virtualized API implementation. 4. The method of claim 1 , wherein generating the virtualized API implementation based upon the programming statements for the API comprises: generating a data model of the virtualized API implementation. | 0.761682 |
9,251,704 | 4 | 5 | 4. The method of claim 1 , wherein the workload-reducing dialogue modification comprises a dialogue modification selected from a group consisting of: a switch to voice modality; breaking up compound prompts into items; a change to a yes/no prompt; and speeding up of a dialogue. | 4. The method of claim 1 , wherein the workload-reducing dialogue modification comprises a dialogue modification selected from a group consisting of: a switch to voice modality; breaking up compound prompts into items; a change to a yes/no prompt; and speeding up of a dialogue. 5. The method of claim 4 , wherein the speeding up of a dialogue act is in response to a predicted workload increase. | 0.5 |
9,104,353 | 8 | 10 | 8. A non-transitory computer-readable medium having a set of computer readable instructions that, when executed, cause a printing system to: receive a document including content to be printed; determine whether the document is confidential, based on a determination as to whether a text indicating that the document is confidential is present in the document; in response to a determination that the document is confidential, generate an authentication code corresponding to the document, wherein the authentication code is a code to be used by authorized users in a predefined group to verify that the authorized users are authorized to print the document; receive a request to print the document from a user; determine whether a document was marked confidential; request the user to provide an authentication code corresponding to the document in response to a determination that the document was marked confidential; verify whether the authentication code provided by the user is valid; and generate a print trigger to print the document in response to a verification that the authentication code provided by the user is valid. | 8. A non-transitory computer-readable medium having a set of computer readable instructions that, when executed, cause a printing system to: receive a document including content to be printed; determine whether the document is confidential, based on a determination as to whether a text indicating that the document is confidential is present in the document; in response to a determination that the document is confidential, generate an authentication code corresponding to the document, wherein the authentication code is a code to be used by authorized users in a predefined group to verify that the authorized users are authorized to print the document; receive a request to print the document from a user; determine whether a document was marked confidential; request the user to provide an authentication code corresponding to the document in response to a determination that the document was marked confidential; verify whether the authentication code provided by the user is valid; and generate a print trigger to print the document in response to a verification that the authentication code provided by the user is valid. 10. The non-transitory computer-readable medium as claimed in claim 8 , wherein the text indicating that the document is confidential is one of a handwritten code and a typewritten code. | 0.655556 |
8,719,353 | 10 | 26 | 10. A computerized method for creating multimedia files from user input data, the method comprising: receiving user input data representative of text and voice data in a user input receiver; storing user input data and other data which includes visualization data and advertising inserts in a persistent storage device; processing said user input data and comparing said user input with said other data by way of a computer under program control; associating said user input data with one or more visualizations which represent the meaning of said user input data based upon said comparison of said user input data with said other data by way of said computer under program control, and generating a multimedia file from said one or more visualizations and at least one of said advertising inserts under program control which conveys the meaning of said user input data, wherein said generating step includes the step of automatically selecting one or both of said advertising insert and said one or more visualizations. | 10. A computerized method for creating multimedia files from user input data, the method comprising: receiving user input data representative of text and voice data in a user input receiver; storing user input data and other data which includes visualization data and advertising inserts in a persistent storage device; processing said user input data and comparing said user input with said other data by way of a computer under program control; associating said user input data with one or more visualizations which represent the meaning of said user input data based upon said comparison of said user input data with said other data by way of said computer under program control, and generating a multimedia file from said one or more visualizations and at least one of said advertising inserts under program control which conveys the meaning of said user input data, wherein said generating step includes the step of automatically selecting one or both of said advertising insert and said one or more visualizations. 26. The computerized method as recited in claim 10 , wherein said storing step comprises: storing user input data and other data, wherein said other data includes other words used in the message stream. | 0.816697 |
7,904,080 | 1 | 3 | 1. A method of processing digital mobile phone network data for analysis, the method comprising: inputting network data captured from a digital mobile phone network, said network data comprising data for a plurality of communications sessions over said network, said network data including a plurality of session related parameters; inputting query data for one or more queries, a query defining a statistic relating to one or more of said parameters, to be computed from said network data; operating with said query on said captured network data to determine one or more intermediate statistics; storing said one or more intermediate statistics in a data store for analysis; and displaying a result of said query in a Graphical User Interface (GUI), said GUI comprising a map having at least one clickable icon, said icon providing information on a result of said query from said statistic and, when clicked, the GUI providing information on data from which said statistic is computed. | 1. A method of processing digital mobile phone network data for analysis, the method comprising: inputting network data captured from a digital mobile phone network, said network data comprising data for a plurality of communications sessions over said network, said network data including a plurality of session related parameters; inputting query data for one or more queries, a query defining a statistic relating to one or more of said parameters, to be computed from said network data; operating with said query on said captured network data to determine one or more intermediate statistics; storing said one or more intermediate statistics in a data store for analysis; and displaying a result of said query in a Graphical User Interface (GUI), said GUI comprising a map having at least one clickable icon, said icon providing information on a result of said query from said statistic and, when clicked, the GUI providing information on data from which said statistic is computed. 3. A method according to claim 1 , wherein said icon, when repeatedly clicked, enables drill down to said session related parameters. | 0.8003 |
9,703,875 | 8 | 9 | 8. The system of claim 2 , wherein the user interface includes a presentation of a plurality of filter values for the third filter, wherein the plurality of filter values for the third filter is presented in a sequence that is ordered based on the filter context. | 8. The system of claim 2 , wherein the user interface includes a presentation of a plurality of filter values for the third filter, wherein the plurality of filter values for the third filter is presented in a sequence that is ordered based on the filter context. 9. The system of claim 8 , wherein the sequence is from a highest to lowest probability of the first filter co-occurring with the third filter in a listing that is randomly identified in the first plurality of listings. | 0.5 |
9,817,821 | 13 | 14 | 13. The system of claim 12 , wherein the processor is further configured to select a translation dictionary from a plurality of translation dictionaries, and wherein the selected translation dictionary is used in the generation of the second translation. | 13. The system of claim 12 , wherein the processor is further configured to select a translation dictionary from a plurality of translation dictionaries, and wherein the selected translation dictionary is used in the generation of the second translation. 14. The system of claim 13 , wherein the selection of the translation dictionary is based on a selected subject matter of the first portion. | 0.5 |
10,061,860 | 21 | 22 | 21. A computer system having at least one processor, storage, and a communication platform connected to a network, wherein the at least one processor is programmed to execute one or more computer program instructions which, when executed, cause the at least one processor to: adaptively assign a user to a user group selected from among a plurality of user groups based on a view distribution of the user, the adaptive assignment including detecting a change in the user's web browsing activities and reassigning the user to another user group of the plurality of user groups; generate a personalized template for the user based on the user's group assignment, wherein the view distribution is determined based on monitored web browsing activities of the user with respect to each portion of each of a plurality of web pages viewed by the user within a given web browsing session and comprises a list of numbers each of which represents a number of times the user viewed a respective portion of the plurality of web pages, and specify a layout of content generated such that space on the layout prioritizes a web page portion that received most views per the view distribution, wherein the prioritization includes allocating more space for content provided at the web page portion; interface with the user; analyze the user's view distribution; and search one or more pieces of content based on a query and arrange the one or more pieces of content for display to the user based on the personalized template; determine statistics associated with a plurality of users in the user group to which the user is assigned; update a record associated with a content provider in connection with the template based on the statistics; and receive a payment made in association with the template and computed based on the record. | 21. A computer system having at least one processor, storage, and a communication platform connected to a network, wherein the at least one processor is programmed to execute one or more computer program instructions which, when executed, cause the at least one processor to: adaptively assign a user to a user group selected from among a plurality of user groups based on a view distribution of the user, the adaptive assignment including detecting a change in the user's web browsing activities and reassigning the user to another user group of the plurality of user groups; generate a personalized template for the user based on the user's group assignment, wherein the view distribution is determined based on monitored web browsing activities of the user with respect to each portion of each of a plurality of web pages viewed by the user within a given web browsing session and comprises a list of numbers each of which represents a number of times the user viewed a respective portion of the plurality of web pages, and specify a layout of content generated such that space on the layout prioritizes a web page portion that received most views per the view distribution, wherein the prioritization includes allocating more space for content provided at the web page portion; interface with the user; analyze the user's view distribution; and search one or more pieces of content based on a query and arrange the one or more pieces of content for display to the user based on the personalized template; determine statistics associated with a plurality of users in the user group to which the user is assigned; update a record associated with a content provider in connection with the template based on the statistics; and receive a payment made in association with the template and computed based on the record. 22. The computer system of claim 21 , wherein the user shares the user's behavior with a plurality of users assigned to the user group, and wherein the reassignment comprises detection of the change in the user's web browsing activities such that a different personalized template is generated that prioritizes the space to a different web page portion, and wherein the content search platform is further configured to rearrange the one or more pieces of content for display to the user based on the different personalized template. | 0.5 |
9,087,132 | 1 | 5 | 1. A method of tying a geospatial location to a PIDF-LO file, comprising: receiving, at a physical network server, a Presence Information Data Format-Location Object (PIDF-LO) file; determining, at said physical network server, that said PIDF-LO file lacks geospatial location information identifying a specific physical zone; identifying a universal resource locator (URL) of XML content relating to a location relevant to said PIDF-LO compliant file; requesting said geospatial location information, through said physical network server; associating, at said physical network server, said geospatial location information with said XML content; and inserting, at said physical network server, said URL of XML content into said PIDF-LO file. | 1. A method of tying a geospatial location to a PIDF-LO file, comprising: receiving, at a physical network server, a Presence Information Data Format-Location Object (PIDF-LO) file; determining, at said physical network server, that said PIDF-LO file lacks geospatial location information identifying a specific physical zone; identifying a universal resource locator (URL) of XML content relating to a location relevant to said PIDF-LO compliant file; requesting said geospatial location information, through said physical network server; associating, at said physical network server, said geospatial location information with said XML content; and inserting, at said physical network server, said URL of XML content into said PIDF-LO file. 5. The method of tying a geospatial location to a PIDF-LO file according to claim 1 , wherein: said geospatial location information is defined using a coordinate based polygon system. | 0.610638 |
9,442,573 | 8 | 13 | 8. A handheld electronic device, comprising: a processor; and a memory, wherein the memory stores instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving data associated with one or more input key selections, wherein at least one of the input key selections is a delimiter input; determining a set of characters based, at least in part, on the received data; determining a known spelling substitution corresponding to a subset of the set of characters; determining that the spelling substitution does not correspond to a language object stored in memory; in response to determining that the spelling substitution does not correspond to the language object stored in memory, storing the spelling substitution in memory as one of the stored language objects; and outputting the set of characters based, at least in part, on the determination that the spelling substitution is stored in memory as one of the stored language objects. | 8. A handheld electronic device, comprising: a processor; and a memory, wherein the memory stores instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving data associated with one or more input key selections, wherein at least one of the input key selections is a delimiter input; determining a set of characters based, at least in part, on the received data; determining a known spelling substitution corresponding to a subset of the set of characters; determining that the spelling substitution does not correspond to a language object stored in memory; in response to determining that the spelling substitution does not correspond to the language object stored in memory, storing the spelling substitution in memory as one of the stored language objects; and outputting the set of characters based, at least in part, on the determination that the spelling substitution is stored in memory as one of the stored language objects. 13. The handheld device of claim 8 , wherein the instructions, when executed by the processor, further cause the handheld electronic device to perform operations comprising: failing to find a language object stored in memory corresponding to the set of characters and, responsive thereto, initiating the determination of the known spelling substitution. | 0.606027 |
9,811,935 | 7 | 10 | 7. An emotive information system for a user of an automotive vehicle, the system comprising: at least one sensor configured to detect at least one of audio and visual characteristics of the user; a computer configured to receive the detected information, receive information about an operating state of the vehicle, and generate data representing a simulated emotional state based on at least a portion of the received information; and an interface configured to convey the simulated emotional state to the user to prompt the user to pose a query regarding a cause of the simulated emotional state, wherein the computer is further configured to receive a query from the user regarding the simulated emotional state and generate data representing a response to the query including information about the cause of the simulated emotional state. | 7. An emotive information system for a user of an automotive vehicle, the system comprising: at least one sensor configured to detect at least one of audio and visual characteristics of the user; a computer configured to receive the detected information, receive information about an operating state of the vehicle, and generate data representing a simulated emotional state based on at least a portion of the received information; and an interface configured to convey the simulated emotional state to the user to prompt the user to pose a query regarding a cause of the simulated emotional state, wherein the computer is further configured to receive a query from the user regarding the simulated emotional state and generate data representing a response to the query including information about the cause of the simulated emotional state. 10. The system of claim 7 wherein the computer is further configured to determine whether a predetermined event has occurred and to initiate a spoken dialog with the user if the predetermined event has occurred. | 0.5 |
8,655,901 | 1 | 6 | 1. A method comprising: receiving a first query pattern, the query pattern identifying a particular rule to interpret a particular type of query, the query pattern being in a first language; identifying, with a system comprising one or more computing devices, a collection of queries in the first language matching the query pattern by determining which queries in a query log match the query pattern; segmenting a given query among the collection into one or more tokens in the first language, wherein each token includes one or more terms from the given query; annotating each query of the collection of queries with one or more labels identifying the parts of each query, wherein annotating each query of the collection of queries with one or more labels comprises: associating each of the one or more tokens with corresponding components of the first query pattern; and annotating the one or more tokens with labels for the corresponding components of the first query pattern; translating the collection of annotated queries in the first language into a translated collection of queries in a second language; and extracting a translated query pattern from the translated collection of queries, wherein for the given one of the plurality of queries, extracting a translated query pattern from the translated collection of queries comprises: determining, from an order in which the one or more tokens into which the given query was segmented in the first language are translated into the second language, an order in which labels for the components of the first query pattern correspond to translated terms of the given query; and extracting the translated query pattern from the order in which labels for the components of the first query pattern correspond to the translated terms of the given query pattern. | 1. A method comprising: receiving a first query pattern, the query pattern identifying a particular rule to interpret a particular type of query, the query pattern being in a first language; identifying, with a system comprising one or more computing devices, a collection of queries in the first language matching the query pattern by determining which queries in a query log match the query pattern; segmenting a given query among the collection into one or more tokens in the first language, wherein each token includes one or more terms from the given query; annotating each query of the collection of queries with one or more labels identifying the parts of each query, wherein annotating each query of the collection of queries with one or more labels comprises: associating each of the one or more tokens with corresponding components of the first query pattern; and annotating the one or more tokens with labels for the corresponding components of the first query pattern; translating the collection of annotated queries in the first language into a translated collection of queries in a second language; and extracting a translated query pattern from the translated collection of queries, wherein for the given one of the plurality of queries, extracting a translated query pattern from the translated collection of queries comprises: determining, from an order in which the one or more tokens into which the given query was segmented in the first language are translated into the second language, an order in which labels for the components of the first query pattern correspond to translated terms of the given query; and extracting the translated query pattern from the order in which labels for the components of the first query pattern correspond to the translated terms of the given query pattern. 6. The method of claim 1 , where annotating each query includes labeling portions of the query according to the first query pattern. | 0.671642 |
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