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8,527,507 | 1 | 6 | 1. A computer for providing a customizable ranking model, comprising: a processor; the processor executing a process, wherein the processor is adapted to: rank documents resulting from a search through the customizable ranking model; use context including language in the customizable ranking model to rank the documents; manage single terms in the context as compounds using custom word breaking rules; add single terms to a thesaurus for synonym expansion in a query; utilizing a locale identifier number for the customizable ranking model to represent a combination of: the language, a region, and a sort for the documents associated with a date, a time, a number, a currency, a formatting, a calendar preference, an input method, and a sorting preference of the documents; operating the language as a query dependent feature; represent the customizable ranking model through a schema written in a human-readable code; and employ a root level ranking model element with a query dependent features element and a query independent features element as child elements as a structure for the elements, wherein the query dependent features element has a child query dependent feature element including property identification, name, weight and length normalization attributes, and the query independent features element has a category feature element, a query independent feature element and a language feature element. | 1. A computer for providing a customizable ranking model, comprising: a processor; the processor executing a process, wherein the processor is adapted to: rank documents resulting from a search through the customizable ranking model; use context including language in the customizable ranking model to rank the documents; manage single terms in the context as compounds using custom word breaking rules; add single terms to a thesaurus for synonym expansion in a query; utilizing a locale identifier number for the customizable ranking model to represent a combination of: the language, a region, and a sort for the documents associated with a date, a time, a number, a currency, a formatting, a calendar preference, an input method, and a sorting preference of the documents; operating the language as a query dependent feature; represent the customizable ranking model through a schema written in a human-readable code; and employ a root level ranking model element with a query dependent features element and a query independent features element as child elements as a structure for the elements, wherein the query dependent features element has a child query dependent feature element including property identification, name, weight and length normalization attributes, and the query independent features element has a category feature element, a query independent feature element and a language feature element. 6. The computer of claim 1 , wherein the schema represents ranking model elements that describe at least one of a rational transform type and associated parameters or inverse rational transform type and associated parameters. | 0.850993 |
7,739,117 | 1 | 3 | 1. A computer-implemented method of automatically filling a form field in response to a speech utterance in a multimodal communications environment having a Web browser implementing a XHTML+VXML (X+V) markup language, the method comprising: parsing an X+V document to determine a synchronized voice field in a user profile domain, wherein a synchronized voice field refers to a form field that is filled by a synchronization of speech and graphic inputs, and a user profile domain refers to form fields that are to be filled with data corresponding to a user profile; for each determined synchronized voice field, dynamically generating at least one grammar corresponding to the form field at runtime, the at least one grammar being based on a user profile and comprising a semantic interpretation string; and creating an auto-fill event based upon the at least one grammar and responsive to the speech utterance, the auto-fill event causing the filling of the form field with data corresponding to the user profile and comprising at least some data not in the spoken utterance. | 1. A computer-implemented method of automatically filling a form field in response to a speech utterance in a multimodal communications environment having a Web browser implementing a XHTML+VXML (X+V) markup language, the method comprising: parsing an X+V document to determine a synchronized voice field in a user profile domain, wherein a synchronized voice field refers to a form field that is filled by a synchronization of speech and graphic inputs, and a user profile domain refers to form fields that are to be filled with data corresponding to a user profile; for each determined synchronized voice field, dynamically generating at least one grammar corresponding to the form field at runtime, the at least one grammar being based on a user profile and comprising a semantic interpretation string; and creating an auto-fill event based upon the at least one grammar and responsive to the speech utterance, the auto-fill event causing the filling of the form field with data corresponding to the user profile and comprising at least some data not in the spoken utterance. 3. The method of claim 1 , wherein the data which fills the form field includes information other than that contained within a speech-to-text conversion of the speech utterance. | 0.741228 |
8,214,349 | 31 | 32 | 31. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term; linking the content with the at least one term; and automatically associating the at least one term in the one or more source documents with at least one link; wherein the at least one link denotes an association between the at least one term and the linked content; wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents. | 31. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term; linking the content with the at least one term; and automatically associating the at least one term in the one or more source documents with at least one link; wherein the at least one link denotes an association between the at least one term and the linked content; wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents. 32. The method of claim 31 , wherein the one or more source documents are parsed at the one or more remote computers. | 0.590909 |
8,983,192 | 12 | 13 | 12. The computer-implemented method of claim 1 , further comprising: receiving a textual search query; and responsive to a volume of a digital video in a search result set of video data matching the textual search query having a verified label matching the search query, including the volume in a search result set of video data matching the search query. | 12. The computer-implemented method of claim 1 , further comprising: receiving a textual search query; and responsive to a volume of a digital video in a search result set of video data matching the textual search query having a verified label matching the search query, including the volume in a search result set of video data matching the search query. 13. The computer-implemented method of claim 12 , wherein the search result set includes a representation of the volume such that, when the representation is selected on a client device, playback of the video begins at a beginning frame of the volume. | 0.934805 |
8,875,306 | 17 | 19 | 17. A system for restricting the customizability of a base metadata document, the base metadata document defining one or more characteristics of at least a portion of a software application, the system comprising: a processor configured to: receive a type-level customization policy defined for a first object type of an object included in the base metadata document, the type-level customization policy indicating whether instances of objects having the object type may be customized by a first set of one or more users of the software application; receive an instance-level customization policy defined for the object included in the base metadata document, the instance-level customization policy indicating whether an instance of the object may be customized by a second set of one or more users of the software application; and enforce the type-level customization policy and the instance-level customization policy at runtime of the software application to create or update a customization, the customization defining modifications to the base metadata document, the enforcing comprising: determining whether the instance of the object may be customized by a current user, based on how the object is instantiated, the type-level customization policy, the instance-level customization policy, and a set of precedence rules for the type-level customization policy and the instance-level customization policy, wherein how the object is instantiated comprises whether the object is instantiated as the first object type or as a second object type that is based on the first object type, wherein the set of precedence rules for the type-level customization policy and the instance-level customization policy comprises one or more rules providing for a first case where the type-level customization policy and the instance-level customization policy apply without conflict, and one or more rules providing for a second case where the type-level customization policy and the instance-level customization policy apply with conflicting restrictions; determining whether a restriction of one of the type-level customization policy or the instance-level customization policy takes a higher precedence with respect to a conflicting restriction of the other of the type-level customization policy or the instance-level customization policy; wherein the customization is stored separately from the base metadata document, and wherein the customization is applied to the base metadata document to generate a customized metadata document used by the software application. | 17. A system for restricting the customizability of a base metadata document, the base metadata document defining one or more characteristics of at least a portion of a software application, the system comprising: a processor configured to: receive a type-level customization policy defined for a first object type of an object included in the base metadata document, the type-level customization policy indicating whether instances of objects having the object type may be customized by a first set of one or more users of the software application; receive an instance-level customization policy defined for the object included in the base metadata document, the instance-level customization policy indicating whether an instance of the object may be customized by a second set of one or more users of the software application; and enforce the type-level customization policy and the instance-level customization policy at runtime of the software application to create or update a customization, the customization defining modifications to the base metadata document, the enforcing comprising: determining whether the instance of the object may be customized by a current user, based on how the object is instantiated, the type-level customization policy, the instance-level customization policy, and a set of precedence rules for the type-level customization policy and the instance-level customization policy, wherein how the object is instantiated comprises whether the object is instantiated as the first object type or as a second object type that is based on the first object type, wherein the set of precedence rules for the type-level customization policy and the instance-level customization policy comprises one or more rules providing for a first case where the type-level customization policy and the instance-level customization policy apply without conflict, and one or more rules providing for a second case where the type-level customization policy and the instance-level customization policy apply with conflicting restrictions; determining whether a restriction of one of the type-level customization policy or the instance-level customization policy takes a higher precedence with respect to a conflicting restriction of the other of the type-level customization policy or the instance-level customization policy; wherein the customization is stored separately from the base metadata document, and wherein the customization is applied to the base metadata document to generate a customized metadata document used by the software application. 19. The system of claim 17 , wherein the base metadata document is an XML document, and wherein the object is an element or an attribute. | 0.874312 |
8,798,988 | 15 | 27 | 15. A computing system comprising: one or more computers; and a non-transitory computer-readable storage medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first collection of terms that are designated as cohyponyms, and that are in a first natural language; generating a second collection of terms by translating the terms of the first collection that are designated as cohyponyms from the first natural language to a second natural language; receiving a candidate pair of terms in the second natural language; determining, by one or more computers, that both candidate terms of the received pair are present in the second collection of terms; and determining to not revise a query that includes a first candidate term of the pair, to include a second candidate term of the pair, based at least on determining that both candidate terms of the pair are present in the second collection of terms. | 15. A computing system comprising: one or more computers; and a non-transitory computer-readable storage medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a first collection of terms that are designated as cohyponyms, and that are in a first natural language; generating a second collection of terms by translating the terms of the first collection that are designated as cohyponyms from the first natural language to a second natural language; receiving a candidate pair of terms in the second natural language; determining, by one or more computers, that both candidate terms of the received pair are present in the second collection of terms; and determining to not revise a query that includes a first candidate term of the pair, to include a second candidate term of the pair, based at least on determining that both candidate terms of the pair are present in the second collection of terms. 27. The computing system of claim 15 , wherein determining to not revise a query that includes a first candidate term of the pair, to include a second candidate term of the pair further comprises determining to not revise a query to include the second candidate term based on a threshold associated with the candidate pair of terms. | 0.501502 |
8,196,038 | 1 | 10 | 1. A computer-network system implemented by an online stationery/card service for a user to personalize and send non-electronic stationery/cards, the system comprising: a computer server configured to enable a graphical user interface for personalizing and sending non-electronic stationery/cards, the graphical user interface comprising: a reminder list comprised of a plurality of reminder entries, each of the reminder entries identifying an upcoming event including events generated based on a specified relationship between the user and one or more contacts stored in a contacts database of the user; a recommendation region comprising a plurality of stationery/card design recommendations, the recommendation region populated with stationery/card designs associated with a specified one or the one or more entries in the reminder list, including the events generated based on the specified relationship between the user and each of the contacts, wherein the reminder list is organized based on a specified prioritization scheme, with a highest priority event selected within the reminder list, wherein upon the user initially opening the GUI the recommendation region is automatically populated with stationery/card designs associated with the highest priority event in the reminder list; and a stationery/card personalization engine executed in response to the user selecting one of the stationery/card design recommendations from the recommendation region, the stationery personalization engine providing the end user with a set of personalization options related to the selected stationery/card design, and generating personalized stationery with the selected stationery/card design based on user input. | 1. A computer-network system implemented by an online stationery/card service for a user to personalize and send non-electronic stationery/cards, the system comprising: a computer server configured to enable a graphical user interface for personalizing and sending non-electronic stationery/cards, the graphical user interface comprising: a reminder list comprised of a plurality of reminder entries, each of the reminder entries identifying an upcoming event including events generated based on a specified relationship between the user and one or more contacts stored in a contacts database of the user; a recommendation region comprising a plurality of stationery/card design recommendations, the recommendation region populated with stationery/card designs associated with a specified one or the one or more entries in the reminder list, including the events generated based on the specified relationship between the user and each of the contacts, wherein the reminder list is organized based on a specified prioritization scheme, with a highest priority event selected within the reminder list, wherein upon the user initially opening the GUI the recommendation region is automatically populated with stationery/card designs associated with the highest priority event in the reminder list; and a stationery/card personalization engine executed in response to the user selecting one of the stationery/card design recommendations from the recommendation region, the stationery personalization engine providing the end user with a set of personalization options related to the selected stationery/card design, and generating personalized stationery with the selected stationery/card design based on user input. 10. The computer-network system as in claim 1 wherein the stationery/card contacts module identifies address information for each of a set of user-selected contacts to receive the personalized stationery. | 0.839117 |
7,664,778 | 7 | 8 | 7. An apparatus, comprising: means for populating a plurality of database query language statements and corresponding performance information as a plurality of first persistent database objects in a database; a processor configured for identifying one or more database query language statements from the plurality of database query language statements and performance information for the one or more data base query language statements, wherein the plurality of database query language statements are filtered based at least in part upon identification of the one or more high load database query language statements such that the set of the one or more high load query statements are identified by ranking and selecting the one or more database query language statements from the set of one or more high load query statements, in which at least one of the set of the one or more high load database query language statements are tuned by using at least a part of the performance information; means for persistently storing the one or more database query language statements and performance information as one or more second persistent database objects, wherein the performance information is used to tune one of the one or more database query language statements as at least some of the one or more second persistent database objects, the performance information comprises execution measurements and execution context corresponding to the one or more database query language statements, and the execution context comprises at least one of a user schema, a name of an application issuing a query language statement, an action of an application issuing a query language statement, a list of bind variables, and system environment information. | 7. An apparatus, comprising: means for populating a plurality of database query language statements and corresponding performance information as a plurality of first persistent database objects in a database; a processor configured for identifying one or more database query language statements from the plurality of database query language statements and performance information for the one or more data base query language statements, wherein the plurality of database query language statements are filtered based at least in part upon identification of the one or more high load database query language statements such that the set of the one or more high load query statements are identified by ranking and selecting the one or more database query language statements from the set of one or more high load query statements, in which at least one of the set of the one or more high load database query language statements are tuned by using at least a part of the performance information; means for persistently storing the one or more database query language statements and performance information as one or more second persistent database objects, wherein the performance information is used to tune one of the one or more database query language statements as at least some of the one or more second persistent database objects, the performance information comprises execution measurements and execution context corresponding to the one or more database query language statements, and the execution context comprises at least one of a user schema, a name of an application issuing a query language statement, an action of an application issuing a query language statement, a list of bind variables, and system environment information. 8. The apparatus of claim 7 , further comprising: means for filtering the statements based on the performance information. | 0.851942 |
7,868,789 | 12 | 13 | 12. The method of claim 8 , wherein the encode index comprises a cache-sensitive array trie index or a cache-sensitive prefix trie index. | 12. The method of claim 8 , wherein the encode index comprises a cache-sensitive array trie index or a cache-sensitive prefix trie index. 13. The method of claim 12 , wherein the cache-sensitive array trie index comprises: storing the plurality of string values in an array; propagating in preorder the plurality of string values to the shared-leaves structure via variable buffers at each cache-sensitive array trie node to populate the array only once per bulk; and generating the subset of the plurality of order-preserving integer codes for the corresponding subset of the plurality of string values in parallel. | 0.815871 |
8,831,403 | 11 | 15 | 11. Logic encoded in non-transitory media that includes code for execution and when executed by a processor is operable to perform operations, comprising: receiving a search query that includes one or more attributes; evaluating a plurality of video files, wherein when a specific search attribute is recognized in a particular video file, the particular video file may be divided into a plurality of video clips with at least one video clip having the recognized specific search attribute; identifying video clips within the video files that have one or more of the recognized specific search attributes; and creating a video report comprising a contiguous sequence of the identified video clips, wherein the video clips are stitched together according to a stitch criterion, wherein each video clip in the video report comprises an embedded links, which can be selected to access a corresponding video file that includes the particular video clip. | 11. Logic encoded in non-transitory media that includes code for execution and when executed by a processor is operable to perform operations, comprising: receiving a search query that includes one or more attributes; evaluating a plurality of video files, wherein when a specific search attribute is recognized in a particular video file, the particular video file may be divided into a plurality of video clips with at least one video clip having the recognized specific search attribute; identifying video clips within the video files that have one or more of the recognized specific search attributes; and creating a video report comprising a contiguous sequence of the identified video clips, wherein the video clips are stitched together according to a stitch criterion, wherein each video clip in the video report comprises an embedded links, which can be selected to access a corresponding video file that includes the particular video clip. 15. The logic of claim 11 , wherein the search query is a natural language query, or a customization form that includes predefined attributes. | 0.849257 |
9,183,466 | 11 | 12 | 11. The method according to claim 1 , wherein: the step of constructing the respective second lattice(s) includes determining a parameter of each respective second lattice using a lexicon having one or more lexicon parameter(s); the determining step includes determining a discrimination score for the video using at least one of the aggregate score(s); and the method further includes adjusting one or more of the lexicon parameter(s) using the determined discrimination score and repeating the constructing-second-lattice, constructing-aggregate-lattice, and determining steps using the lexicon having the adjusted parameter(s). | 11. The method according to claim 1 , wherein: the step of constructing the respective second lattice(s) includes determining a parameter of each respective second lattice using a lexicon having one or more lexicon parameter(s); the determining step includes determining a discrimination score for the video using at least one of the aggregate score(s); and the method further includes adjusting one or more of the lexicon parameter(s) using the determined discrimination score and repeating the constructing-second-lattice, constructing-aggregate-lattice, and determining steps using the lexicon having the adjusted parameter(s). 12. The method according to claim 11 , wherein the adjusting step includes adjusting the one or more of the parameter(s) substantially using a Baum-Welch algorithm. | 0.949662 |
9,721,563 | 3 | 4 | 3. The medium as in claim 2 , wherein the method further comprises: obtaining changes in the contacts database and processing, using the plurality of pronunciation guessers, the changes to update the extended phonetic dictionary based on the changes, wherein the obtaining of the changes occurs in response to the changes being made. | 3. The medium as in claim 2 , wherein the method further comprises: obtaining changes in the contacts database and processing, using the plurality of pronunciation guessers, the changes to update the extended phonetic dictionary based on the changes, wherein the obtaining of the changes occurs in response to the changes being made. 4. The medium as in claim 3 , wherein the plurality of pronunciation guessers comprise pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser. | 0.907517 |
8,924,198 | 10 | 14 | 10. A non-transitory computer readable medium configured to store instructions for searching a datastore of data objects, the instructions when executed by at least one processor cause the at least one processor to perform steps comprising: receiving a search query; identifying, from the datastore of data objects, a first data object that matches the search query; and generating a first sentence that includes a subject, verb and object, the object of the first sentence representing the first data object, the subject of the first sentence representing a second data object from the datastore that is related to the first data object; generating a second sentence that includes a subject, verb and object, the object of the second sentence representing the second data object, the subject of the second sentence representing a third data object from the datastore that is related to the second data object; outputting information corresponding to a user interface based on the first sentence and the second sentence, the first sentence and the second sentence organized in the user interface as a hierarchy of sentences that includes a plurality of levels, wherein the first sentence is in a subordinate level of the hierarchy and the second sentence is in a superior level of the hierarchy. | 10. A non-transitory computer readable medium configured to store instructions for searching a datastore of data objects, the instructions when executed by at least one processor cause the at least one processor to perform steps comprising: receiving a search query; identifying, from the datastore of data objects, a first data object that matches the search query; and generating a first sentence that includes a subject, verb and object, the object of the first sentence representing the first data object, the subject of the first sentence representing a second data object from the datastore that is related to the first data object; generating a second sentence that includes a subject, verb and object, the object of the second sentence representing the second data object, the subject of the second sentence representing a third data object from the datastore that is related to the second data object; outputting information corresponding to a user interface based on the first sentence and the second sentence, the first sentence and the second sentence organized in the user interface as a hierarchy of sentences that includes a plurality of levels, wherein the first sentence is in a subordinate level of the hierarchy and the second sentence is in a superior level of the hierarchy. 14. The computer readable medium of claim 10 , wherein generating the first sentence comprises generating the object of the first sentence to include at least one attribute of the first data object. | 0.573276 |
8,306,822 | 5 | 7 | 5. The method of claim 1 and further comprising: utilizing a user interface element to provide online help information that is associated with the portion of the text. | 5. The method of claim 1 and further comprising: utilizing a user interface element to provide online help information that is associated with the portion of the text. 7. The method of claim 5 , wherein providing the online help information includes providing an audible signal related to the portion of the text. | 0.944529 |
4,713,008 | 5 | 6 | 5. A method of teaching as in claim 4, comprising additional steps of: presenting to said student an operation comprising: articulating said language sound, and executing simultaneously a distinct gesture which comprises a meaningful relationship with said soniferous event, causing said student to duplicate said operation, whereby said student is given an additional, meaningful connection between said indicium and said language sound. | 5. A method of teaching as in claim 4, comprising additional steps of: presenting to said student an operation comprising: articulating said language sound, and executing simultaneously a distinct gesture which comprises a meaningful relationship with said soniferous event, causing said student to duplicate said operation, whereby said student is given an additional, meaningful connection between said indicium and said language sound. 6. A method of teaching as in claim 5 wherein said depiction comprises: a graphic depiction of said soniferous event. | 0.896277 |
9,870,572 | 1 | 5 | 1. A method of selecting an advertisement associated with a geographic location, comprising: receiving, using one or more processors, a request from a remote computer, the request identifying the geographic location from location signals associated with the remote computer, the location signals determined at the remote computer using an antenna for receiving location signals and associated software for determining the position of the remote computer based on the received location signals; determining, using the one or more processors, a listing associated with the geographic location and the request; determining, using the one or more processors, a number of previous users that selected the listing associated with the geographic location in response to the previous users providing a first search term; when the number of previous users exceeds a predetermined threshold, selecting, using the one or more processors, the first search term as one or more search terms associated with the geographic location; when the number of previous users does not exceed the predetermined threshold, determining, using the one or more processors, a number of listing categories associated with the geographic location; when the number of listing categories falls below a given threshold, selecting, using the one or more processors, the listing categories as the one or more search terms associated with the geographic location; when the number of listing categories does not fall below the given threshold, determining, using the one or more processors and without user input, a point of interest that is associated with the geographic location and selecting a title of the point of interest as the one or more search terms associated with the geographic location; determining, using the one or more processors, an advertisement based at least in part on the one or more search terms associated with the geographic location; and transmitting, using the one or more processors, the advertisement to an electronic display of the remote computer for display to the user in response to the request. | 1. A method of selecting an advertisement associated with a geographic location, comprising: receiving, using one or more processors, a request from a remote computer, the request identifying the geographic location from location signals associated with the remote computer, the location signals determined at the remote computer using an antenna for receiving location signals and associated software for determining the position of the remote computer based on the received location signals; determining, using the one or more processors, a listing associated with the geographic location and the request; determining, using the one or more processors, a number of previous users that selected the listing associated with the geographic location in response to the previous users providing a first search term; when the number of previous users exceeds a predetermined threshold, selecting, using the one or more processors, the first search term as one or more search terms associated with the geographic location; when the number of previous users does not exceed the predetermined threshold, determining, using the one or more processors, a number of listing categories associated with the geographic location; when the number of listing categories falls below a given threshold, selecting, using the one or more processors, the listing categories as the one or more search terms associated with the geographic location; when the number of listing categories does not fall below the given threshold, determining, using the one or more processors and without user input, a point of interest that is associated with the geographic location and selecting a title of the point of interest as the one or more search terms associated with the geographic location; determining, using the one or more processors, an advertisement based at least in part on the one or more search terms associated with the geographic location; and transmitting, using the one or more processors, the advertisement to an electronic display of the remote computer for display to the user in response to the request. 5. The method of claim 1 , wherein the geographic location comprises a street address. | 0.952009 |
9,852,728 | 15 | 18 | 15. A text to speech system comprising: one or more processors configured to identify a word or phrase as a named entity, the one or more processors further configured to identify a language of origin associated with the named entity and transliterate the named entity to a script associated with the language of origin, if the TTS system is operating in the language of origin, the one or more processors further configured to pass the transliterated script to the TTS system, and if the TTS system is not operating in the language of origin, the one or more processors further configured to generate a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter. | 15. A text to speech system comprising: one or more processors configured to identify a word or phrase as a named entity, the one or more processors further configured to identify a language of origin associated with the named entity and transliterate the named entity to a script associated with the language of origin, if the TTS system is operating in the language of origin, the one or more processors further configured to pass the transliterated script to the TTS system, and if the TTS system is not operating in the language of origin, the one or more processors further configured to generate a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter. 18. The system of claim 15 , wherein identifying a word or phrase as a named entity includes one or more of table lookup and contextual analysis. | 0.755068 |
9,697,255 | 1 | 10 | 1. An event processing system, comprising: an event bus configured to receive a stream of events, each said event having a predefined event type; an event processing agent including at least one first processor, the event processing agent being configured to execute predefined queries on the events, each said query conforming to a query language, the query language being enhanced via a semantic extension corresponding to an ontology; and an ontology management component in communication with the event processing agent, the ontology management component including: a first storage location storing mappings between concepts of the query language and concepts of the ontology that enhances the query language, and processing resources, including at least one second processor and a memory, configured to, when an enhanced query, defined in accordance with the query language enhanced via the semantic extension and to be executed on a received event by the event processing agent, includes references to ontology concepts using semantics extension enhancement in the enhanced query, generate, in accordance with the stored mapping between the concepts of the query language and the concepts of the ontology that enhances the query language, a translated query with the references to the ontology concepts in the enhanced query being translated into queries processable by the event processing agent in accordance with the query language without the semantic extension enhancement; wherein the concepts of the ontology are classes, and wherein the generating of the translated query comprises, for the enhanced query: retrieving a class definition for all referenced classes from a corresponding ontology; determining whether the referenced classes are marked as being handled; when the referenced classes are marked as being handled, transforming the respective class definition to the query language, and compiling the translated query; and when the referenced classes are not marked as being handled: when the respective class does not have a corresponding mapping, replacing the class with a union of all of its sub-classes, when the respective class has a corresponding mapping but no sub-classes, removing the reference to the class, and when the respective class has a corresponding mapping and any sub-classes, adding a union with all sub-classes to the class and marking the class as handled. | 1. An event processing system, comprising: an event bus configured to receive a stream of events, each said event having a predefined event type; an event processing agent including at least one first processor, the event processing agent being configured to execute predefined queries on the events, each said query conforming to a query language, the query language being enhanced via a semantic extension corresponding to an ontology; and an ontology management component in communication with the event processing agent, the ontology management component including: a first storage location storing mappings between concepts of the query language and concepts of the ontology that enhances the query language, and processing resources, including at least one second processor and a memory, configured to, when an enhanced query, defined in accordance with the query language enhanced via the semantic extension and to be executed on a received event by the event processing agent, includes references to ontology concepts using semantics extension enhancement in the enhanced query, generate, in accordance with the stored mapping between the concepts of the query language and the concepts of the ontology that enhances the query language, a translated query with the references to the ontology concepts in the enhanced query being translated into queries processable by the event processing agent in accordance with the query language without the semantic extension enhancement; wherein the concepts of the ontology are classes, and wherein the generating of the translated query comprises, for the enhanced query: retrieving a class definition for all referenced classes from a corresponding ontology; determining whether the referenced classes are marked as being handled; when the referenced classes are marked as being handled, transforming the respective class definition to the query language, and compiling the translated query; and when the referenced classes are not marked as being handled: when the respective class does not have a corresponding mapping, replacing the class with a union of all of its sub-classes, when the respective class has a corresponding mapping but no sub-classes, removing the reference to the class, and when the respective class has a corresponding mapping and any sub-classes, adding a union with all sub-classes to the class and marking the class as handled. 10. The system of claim 1 , wherein translated queries are free from, and lack any reference to, any ontology concepts. | 0.879065 |
8,542,927 | 1 | 18 | 1. A method, implemented by a computing device, comprising: receiving stroke information relating to a partially written East Asian character, the partially written East Asian character being composed of one or more radicals; identifying the one or more radicals contained in the partially written East Asian character via one or more trained hidden Markov models; selecting a radical in a prefix tree, wherein the prefix tree branches to East Asian characters as end states, the selecting comprising: calculating a best partial matching score between the one or more radicals contained in the partially written East Asian character and the radical in the prefix tree; and calculating a partial matching score for each character in the prefix tree based on the best partial matching score; identifying an East Asian character as an end state from the prefix tree based on the partial matching score; receiving user input to verify that the identified East Asian character is the end state for the partially written East Asian character; and replacing the received stroke information with the identified East Asian character verified by the user input. | 1. A method, implemented by a computing device, comprising: receiving stroke information relating to a partially written East Asian character, the partially written East Asian character being composed of one or more radicals; identifying the one or more radicals contained in the partially written East Asian character via one or more trained hidden Markov models; selecting a radical in a prefix tree, wherein the prefix tree branches to East Asian characters as end states, the selecting comprising: calculating a best partial matching score between the one or more radicals contained in the partially written East Asian character and the radical in the prefix tree; and calculating a partial matching score for each character in the prefix tree based on the best partial matching score; identifying an East Asian character as an end state from the prefix tree based on the partial matching score; receiving user input to verify that the identified East Asian character is the end state for the partially written East Asian character; and replacing the received stroke information with the identified East Asian character verified by the user input. 18. The method of claim 1 , the identifying the one or more radicals contained in the partially written East Asian character via one or more trained hidden Markov models further including employing a Multi-Space Probability Distribution (MSD). | 0.585324 |
10,049,663 | 1 | 10 | 1. A system for operating a digital assistant to explore media items, the system comprising: one or more processors; and memory having instructions stored thereon, the instructions, when executed by the one or more processors, cause the one or more processors to: receive, from a user, speech input representing a request for one or more media items; evaluate a text representation of the speech input against a set of rules to determine whether or not the speech input corresponds to a user intent of obtaining personalized recommendations for media items, wherein the evaluating includes determining an actionable intent node by analyzing words in the text representation against words of a vocabulary index associated with a plurality of actionable intent nodes, and wherein the set of rules includes a first rule that the actionable intent node corresponds to an actionable intent of obtaining personalized recommendations for media items and a second rule that one or more words in the text representation refers to the user; in accordance with a determination that the text representation satisfies the set of rules: obtain at least one media item from a user-specific corpus of media items, the user-specific corpus of media items generated according to inferred media preferences of the user; and provide the at least one media item from the user-specific corpus of media items; and in accordance with a determination that the text representation does not satisfy the set of rules: obtain at least one media item from a general corpus of media items, the general corpus of media items generated according to inferred media preferences of a plurality of users; and provide the at least one media item from the general corpus of media items. | 1. A system for operating a digital assistant to explore media items, the system comprising: one or more processors; and memory having instructions stored thereon, the instructions, when executed by the one or more processors, cause the one or more processors to: receive, from a user, speech input representing a request for one or more media items; evaluate a text representation of the speech input against a set of rules to determine whether or not the speech input corresponds to a user intent of obtaining personalized recommendations for media items, wherein the evaluating includes determining an actionable intent node by analyzing words in the text representation against words of a vocabulary index associated with a plurality of actionable intent nodes, and wherein the set of rules includes a first rule that the actionable intent node corresponds to an actionable intent of obtaining personalized recommendations for media items and a second rule that one or more words in the text representation refers to the user; in accordance with a determination that the text representation satisfies the set of rules: obtain at least one media item from a user-specific corpus of media items, the user-specific corpus of media items generated according to inferred media preferences of the user; and provide the at least one media item from the user-specific corpus of media items; and in accordance with a determination that the text representation does not satisfy the set of rules: obtain at least one media item from a general corpus of media items, the general corpus of media items generated according to inferred media preferences of a plurality of users; and provide the at least one media item from the general corpus of media items. 10. The system of claim 1 , wherein the instructions further cause the one or more processors to: determine whether the text representation defines an editorial list associated with a media establishment; and in accordance with the determination that the text representation satisfies the set of rules and that the text representation defines an editorial list associated with a media establishment, obtain the at least one media item from the user-specific corpus of media items based on the editorial list associated with the media establishment, wherein the at least one media item from the user-specific corpus of media items includes metadata indicating the editorial list associated with the media establishment. | 0.57715 |
8,478,777 | 6 | 9 | 6. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a search system, (i) a pixel map corresponding to one or more characters that have been drawn on a display of a client device and (ii) data identifying one or more other characters that were previously recognized by the search system using one or more other pixel maps; recognizing, by the search system, the one or more characters that correspond to the pixel map based on the received pixel map and the one or more other characters; formulating, by the search system, a search that includes the one or more characters and the one or more other characters as a query term; and communicating, by the search system, (i) one or more search results for the search, (ii) data identifying the one or more characters that correspond to the received pixel map, and (iii) data identifying the one or more other characters to the client device that were previously recognized by the search system using the one or more other pixel maps. | 6. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a search system, (i) a pixel map corresponding to one or more characters that have been drawn on a display of a client device and (ii) data identifying one or more other characters that were previously recognized by the search system using one or more other pixel maps; recognizing, by the search system, the one or more characters that correspond to the pixel map based on the received pixel map and the one or more other characters; formulating, by the search system, a search that includes the one or more characters and the one or more other characters as a query term; and communicating, by the search system, (i) one or more search results for the search, (ii) data identifying the one or more characters that correspond to the received pixel map, and (iii) data identifying the one or more other characters to the client device that were previously recognized by the search system using the one or more other pixel maps. 9. The system of claim 6 , wherein the search comprises an instant search. | 0.830275 |
7,949,941 | 44 | 49 | 44. The non-transitory computer-readable storage medium of claim 32 , wherein the determining further comprises: based at least in part on the structural description that constrains the set of one or more XML documents to the hierarchy of nodes that may be present in the set of one or more XML documents, constructing a corresponding sample document that represents the structure of the set of one or more XML documents; submitting the sample document to an XSLT engine for transformation based at least in part on the XSLT stylesheet and for tracing execution paths associated with the transformation, wherein the execution paths indicate, for particular nodes contained in the sample document, which particular transformation template to use to transform the corresponding particular node. | 44. The non-transitory computer-readable storage medium of claim 32 , wherein the determining further comprises: based at least in part on the structural description that constrains the set of one or more XML documents to the hierarchy of nodes that may be present in the set of one or more XML documents, constructing a corresponding sample document that represents the structure of the set of one or more XML documents; submitting the sample document to an XSLT engine for transformation based at least in part on the XSLT stylesheet and for tracing execution paths associated with the transformation, wherein the execution paths indicate, for particular nodes contained in the sample document, which particular transformation template to use to transform the corresponding particular node. 49. The non-transitory computer-readable storage medium of claim 44 , wherein constructing the sample document includes constructing the sample document using a data guide to which the set of one or more XML documents structurally conforms. | 0.928358 |
8,342,392 | 9 | 10 | 9. The method of claim 1 , further comprising: generating an encrypted passcode capable of being decrypted by the portable device, wherein the generating the image comprises including the encrypted passcode in the image. | 9. The method of claim 1 , further comprising: generating an encrypted passcode capable of being decrypted by the portable device, wherein the generating the image comprises including the encrypted passcode in the image. 10. The method of claim 9 , further comprising: extracting and decrypting, by the portable device, the encrypted passcode to yield a decrypted passcode; encrypting, by the portable device, the decrypted access code using the decrypted passcode. | 0.794958 |
8,677,262 | 1 | 2 | 1. A system, comprising: a memory that stores computer-executable instructions; and a processor that facilitates execution of the computer-executable instructions to at least: initiate a rendering of a visualization comprising a first display object and a second display object, wherein the first display object and the second display object are related to at least one hardware device; determine context information related to a user of an industrial automation system based on evidence information representing a set of evidence related to at least a role of the user and a state of the at least one hardware device within the industrial automation system; determine a first priority of the first display object and a second priority of the second display object based on a change in the context information, wherein the first priority is determined to be higher than the second priority; and initiate an update of the visualization to render the first display object more prominently than the second display object based on the first priority being higher than the second priority. | 1. A system, comprising: a memory that stores computer-executable instructions; and a processor that facilitates execution of the computer-executable instructions to at least: initiate a rendering of a visualization comprising a first display object and a second display object, wherein the first display object and the second display object are related to at least one hardware device; determine context information related to a user of an industrial automation system based on evidence information representing a set of evidence related to at least a role of the user and a state of the at least one hardware device within the industrial automation system; determine a first priority of the first display object and a second priority of the second display object based on a change in the context information, wherein the first priority is determined to be higher than the second priority; and initiate an update of the visualization to render the first display object more prominently than the second display object based on the first priority being higher than the second priority. 2. The system of claim 1 , wherein the update of the visualization comprises the first display object being rendered to be larger than the second display object. | 0.876911 |
9,317,201 | 10 | 17 | 10. A non-transitory computer-readable storage device comprising instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising: receiving an indication of at least two contacts at a region of a presence-sensitive screen that outputs virtual keyboard, the at least two contacts constituting a sequence of contacts and being associated with a predicted word and a probability for the predicted word; receiving an indication of a third contact at the region of the presence-sensitive screen; applying a probabilistic model based on a spatial location of the third contact and the predicted word, wherein the spatial location is based on a distance of the third contact from a location within the virtual spacebar key, the probabilistic model configured to interpret the third contact as at least (i) a selection of the predicted word, wherein the predicted word has a same number of characters as a number of contacts in the sequence of contacts, (ii) a selection of the predicted word, wherein the predicted word has a greater number of characters than the number of contacts in the sequence of contacts, and (iii) a user input of a non-space character; and updating an input buffer based on an interpretation of the third contact, the interpretation being based on the probabilistic model. | 10. A non-transitory computer-readable storage device comprising instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising: receiving an indication of at least two contacts at a region of a presence-sensitive screen that outputs virtual keyboard, the at least two contacts constituting a sequence of contacts and being associated with a predicted word and a probability for the predicted word; receiving an indication of a third contact at the region of the presence-sensitive screen; applying a probabilistic model based on a spatial location of the third contact and the predicted word, wherein the spatial location is based on a distance of the third contact from a location within the virtual spacebar key, the probabilistic model configured to interpret the third contact as at least (i) a selection of the predicted word, wherein the predicted word has a same number of characters as a number of contacts in the sequence of contacts, (ii) a selection of the predicted word, wherein the predicted word has a greater number of characters than the number of contacts in the sequence of contacts, and (iii) a user input of a non-space character; and updating an input buffer based on an interpretation of the third contact, the interpretation being based on the probabilistic model. 17. The non-transitory computer-readable storage device of claim 10 , wherein the probabilistic model interfaces with a language model that determines a probability that an input key is selected based on previous contacts in the sequence of contacts. | 0.631268 |
8,255,380 | 7 | 8 | 7. A computer method as claimed in claim 1 wherein the step of finding finds multiple experts per certain object, and the step of displaying includes listing the multiple experts. | 7. A computer method as claimed in claim 1 wherein the step of finding finds multiple experts per certain object, and the step of displaying includes listing the multiple experts. 8. A computer method as claimed in claim 7 wherein the listing is sorted in order of experts who have the most relevant expertise. | 0.946281 |
9,322,663 | 1 | 4 | 1. A computer-implemented method for identifying and presenting symbols to a user to navigate a route between an origin and a destination, the method comprising the following operations performed by at least one processor: obtaining information identifying an action associated with a maneuver in the route from the origin to the destination; determining, based on the information identifying the action associated with the maneuver, an action symbol for the maneuver; determining a road symbol based on at least road information identifying a road associated with the maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road associated with the maneuver; and generating an instruction to present a display to the user including the road symbol in a position adjacent to the action symbol, the presented road and action symbols conveying the maneuver to the user. | 1. A computer-implemented method for identifying and presenting symbols to a user to navigate a route between an origin and a destination, the method comprising the following operations performed by at least one processor: obtaining information identifying an action associated with a maneuver in the route from the origin to the destination; determining, based on the information identifying the action associated with the maneuver, an action symbol for the maneuver; determining a road symbol based on at least road information identifying a road associated with the maneuver, the road symbol having substantially the same appearance as a road sign used to mark the road associated with the maneuver; and generating an instruction to present a display to the user including the road symbol in a position adjacent to the action symbol, the presented road and action symbols conveying the maneuver to the user. 4. The method of claim 1 , wherein the determining comprises: obtaining, based on the information identifying the action, an image associated with the action symbol; obtaining information identifying one or more characteristics of the maneuver; and generating the action symbol for the maneuver, the action symbol comprising the obtained image and text corresponding to at least one of the maneuver characteristics. | 0.636602 |
9,268,856 | 9 | 10 | 9. A system for providing content, the system comprising: a search server configured to receive a user query and retrieve a first search result based on the user query; an extraction module configured to identify a category based on the user query; a template storage module configured to retrieve a template based on the category; a template creation module configured to: retrieve category-specific content based on instructions in the template; retrieve additional category-specific content based on an additional query generated based on the category-specific content; and create a template module presenting the category-specific content and the additional category-specific content in accordance with the instructions, wherein the search server is further configured to provide a search result page having the first search result and the template module in response to the user query. | 9. A system for providing content, the system comprising: a search server configured to receive a user query and retrieve a first search result based on the user query; an extraction module configured to identify a category based on the user query; a template storage module configured to retrieve a template based on the category; a template creation module configured to: retrieve category-specific content based on instructions in the template; retrieve additional category-specific content based on an additional query generated based on the category-specific content; and create a template module presenting the category-specific content and the additional category-specific content in accordance with the instructions, wherein the search server is further configured to provide a search result page having the first search result and the template module in response to the user query. 10. The system of claim 9 , wherein the template creation module is further configured to modify the template by replacing portions of the template with one or more terms of the user query, and wherein retrieving the category-specific content comprises retrieving the category-specific content based on instructions in the modified template. | 0.648454 |
7,899,843 | 5 | 10 | 5. A tangible computer-readable storage medium containing a program for exchanging information via annotations which, when executed by a processor, performs operations comprising: providing a first interface allowing a first user to view query results, select a first data object from the query results, and create an annotation with a scope encompassing selected first data object, whereby the annotation annotates the selected first data object with metadata describing the selected data object, and wherein the first user is authorized to view the first data object; providing an interface element allowing the first user to further associate the annotation with a second data object, whereby the annotation annotates both the selected first data object and the second data object, and wherein the first user is not authorized to view the second data object; providing a second interface allowing a second user to view second query results including the second data object, wherein the second user is authorized to view the second data object; and providing, in the second interface, an indication of the annotation to the second user. | 5. A tangible computer-readable storage medium containing a program for exchanging information via annotations which, when executed by a processor, performs operations comprising: providing a first interface allowing a first user to view query results, select a first data object from the query results, and create an annotation with a scope encompassing selected first data object, whereby the annotation annotates the selected first data object with metadata describing the selected data object, and wherein the first user is authorized to view the first data object; providing an interface element allowing the first user to further associate the annotation with a second data object, whereby the annotation annotates both the selected first data object and the second data object, and wherein the first user is not authorized to view the second data object; providing a second interface allowing a second user to view second query results including the second data object, wherein the second user is authorized to view the second data object; and providing, in the second interface, an indication of the annotation to the second user. 10. The tangible computer-readable storage medium of claim 5 , wherein the second query results do not contain the selected first data object described by the annotation. | 0.78803 |
8,150,843 | 6 | 7 | 6. The computer-implemented method of claim 5 , wherein each document in the re-ranked search results is tagged with the one or more search terms, and wherein the tags are stored for use in initially ordering search results responsive to subsequent search requests. | 6. The computer-implemented method of claim 5 , wherein each document in the re-ranked search results is tagged with the one or more search terms, and wherein the tags are stored for use in initially ordering search results responsive to subsequent search requests. 7. The computer-implemented method of claim 6 , wherein the user indication of each document comprises a user-specified numerical score indicating an extent to which the user finds the respective document to be relevant to the one or more search terms, and wherein the new statistical classifier is trained using the user-specified numerical scores. | 0.929238 |
8,699,796 | 1 | 10 | 1. A method of identifying sensitive expressions in images for a language with a large alphabet, the method to be performed using a computer and comprising: extracting an image from a computer-readable message; extracting image character-blocks from the image; predicting characters to which the character-blocks correspond using a multi-class learning model, wherein the multi-class learning model is trained using a derived list of sensitive characters which is a subset of the large alphabet; combining the predicted characters into string text; and searching the string text for matches with a predefined list of sensitive expressions in the language with the large alphabet. | 1. A method of identifying sensitive expressions in images for a language with a large alphabet, the method to be performed using a computer and comprising: extracting an image from a computer-readable message; extracting image character-blocks from the image; predicting characters to which the character-blocks correspond using a multi-class learning model, wherein the multi-class learning model is trained using a derived list of sensitive characters which is a subset of the large alphabet; combining the predicted characters into string text; and searching the string text for matches with a predefined list of sensitive expressions in the language with the large alphabet. 10. The method of claim 1 , wherein the derived list of sensitive characters has less than two hundred distinct characters. | 0.854953 |
9,972,073 | 10 | 14 | 10. At least one computing device operative in a digital medium environment to enhance picture vectorization by facilitating conversion of raster images to vector images based on spatially-localized user control, the computing device comprising: a segmentation module configured to segment a raster image into multiple segments, the raster image including multiple image features and corresponding to a picture having multiple semantic elements, each segment of the multiple segments based on at least one image feature of the multiple image features, the multiple image features of the raster image serving as a proxy for the multiple semantic elements of the picture; a localized user control module configured to: present a user interface feature to provide localized control of a vectorization of the picture, the localized control pertaining to a portion of the raster image; and detect a user control signal indicative of the portion of the raster image for which a localized vectorization characteristic is to be adjusted; and a vector image production module configured to produce a vector image corresponding to at least part of the picture based on the multiple segments and an adjusted localized vectorization characteristic. | 10. At least one computing device operative in a digital medium environment to enhance picture vectorization by facilitating conversion of raster images to vector images based on spatially-localized user control, the computing device comprising: a segmentation module configured to segment a raster image into multiple segments, the raster image including multiple image features and corresponding to a picture having multiple semantic elements, each segment of the multiple segments based on at least one image feature of the multiple image features, the multiple image features of the raster image serving as a proxy for the multiple semantic elements of the picture; a localized user control module configured to: present a user interface feature to provide localized control of a vectorization of the picture, the localized control pertaining to a portion of the raster image; and detect a user control signal indicative of the portion of the raster image for which a localized vectorization characteristic is to be adjusted; and a vector image production module configured to produce a vector image corresponding to at least part of the picture based on the multiple segments and an adjusted localized vectorization characteristic. 14. The computing device as described in claim 10 , wherein the localized user control module is configured to merge segments or to split a segment based on the indicated portion of the raster image and an intensity of an edge in a contour map corresponding to the picture of the raster image. | 0.812899 |
9,135,518 | 1 | 11 | 1. A method of analyzing a digital image to determine an unordered local descriptor describing the digital image, the method comprising: selecting a subset of feature points within multiple local extrema, wherein each feature point has an associated blur level and scale octave; creating a vector for each of the feature points, each feature point vector based on the normalized intensity values of a patch around the feature point, wherein the patch size is determined by the associated octave; dividing the patch into multiple overlapping patches, wherein each overlapping patch is represented by a vector; concatenating each overlapping patch vector by projecting the multiple overlapping patch vectors onto an eigen space; and creating an unordered local descriptor for the digital image, wherein the unordered local descriptor is a compact representation of feature points defining the digital image, and wherein the compact representation is a multi-vector descriptor formed from the concatenated patch vectors. | 1. A method of analyzing a digital image to determine an unordered local descriptor describing the digital image, the method comprising: selecting a subset of feature points within multiple local extrema, wherein each feature point has an associated blur level and scale octave; creating a vector for each of the feature points, each feature point vector based on the normalized intensity values of a patch around the feature point, wherein the patch size is determined by the associated octave; dividing the patch into multiple overlapping patches, wherein each overlapping patch is represented by a vector; concatenating each overlapping patch vector by projecting the multiple overlapping patch vectors onto an eigen space; and creating an unordered local descriptor for the digital image, wherein the unordered local descriptor is a compact representation of feature points defining the digital image, and wherein the compact representation is a multi-vector descriptor formed from the concatenated patch vectors. 11. The method of claim 1 , further comprising determining an orthogonal coordinate system based on the largest variance between each feature point vector. | 0.822654 |
8,751,240 | 1 | 2 | 1. A method, comprising: performing, via a server processor, automatic speech recognition on an utterance received from a first party in a conversation, to yield recognized speech; determining, via the server processor, a meaning of the utterance based, on the recognized speech; forming a query, by the server processor, indicating the meaning of the utterance and based on a plurality of searching resources; sending the query, by the server processor, based on the meaning of the query, to a plurality of relevant searching resources, in order to obtain first address links associated with search results of the plurality of relevant searching resources in response to the query, wherein the plurality of searching resources comprises a web-based search engine, local databases, and remote databases; sending the query to a device associated with a second party in the conversation for forwarding to at least one other relevant searching resource in order to obtain second address links; sending the first and second address links to the device; displaying the first and second address links on the device; selecting, by the second party, at least one address link from the first and second address links displayed relevant to the conversation and query; logging, the search results, a time and date of the query, the relevant searching resources searched during the conversation in response to the query, and the searching resources selected by the second party from the selected at least one address link to create a log; and presenting the log for analysis. | 1. A method, comprising: performing, via a server processor, automatic speech recognition on an utterance received from a first party in a conversation, to yield recognized speech; determining, via the server processor, a meaning of the utterance based, on the recognized speech; forming a query, by the server processor, indicating the meaning of the utterance and based on a plurality of searching resources; sending the query, by the server processor, based on the meaning of the query, to a plurality of relevant searching resources, in order to obtain first address links associated with search results of the plurality of relevant searching resources in response to the query, wherein the plurality of searching resources comprises a web-based search engine, local databases, and remote databases; sending the query to a device associated with a second party in the conversation for forwarding to at least one other relevant searching resource in order to obtain second address links; sending the first and second address links to the device; displaying the first and second address links on the device; selecting, by the second party, at least one address link from the first and second address links displayed relevant to the conversation and query; logging, the search results, a time and date of the query, the relevant searching resources searched during the conversation in response to the query, and the searching resources selected by the second party from the selected at least one address link to create a log; and presenting the log for analysis. 2. The method of claim 1 , wherein the utterance is from an ongoing call. | 0.905195 |
9,047,464 | 11 | 14 | 11. A computer program embedded in a non-transitory computer-readable storage medium, when executed by one or more processors, for securing a computer device, the computer program comprising: program instructions for receiving, by a security server, interaction data for a user interfacing with the computer device while the user is authenticated for accessing at least one computer resource, the interaction data including keyboard inputs, images taken of the user during the access and screen captures taken periodically; program instructions for performing optical character recognition (OCR) to identify text in the screen captures; program instructions for extracting semantic data from the interaction data and from the text in the screen captures, the semantic data identifying user activities associated with the interaction data; program instructions for generating a schema based on the extracted semantic data, the schema including tags that are descriptive of at least one of the identified user activity and the associated interaction data; program instructions for analyzing the schema based on a model to identify security threats associated with the user activities; program instructions for creating an alarm when non-conforming behavior for at least one user activity is detected, the alarm including a binding of the one or more user activities, one or more tags, keyboard inputs, and screen captures associated with the one or more user activities: and sending a command from the security server to terminate access to the at least one computer resource in response to the alarm. | 11. A computer program embedded in a non-transitory computer-readable storage medium, when executed by one or more processors, for securing a computer device, the computer program comprising: program instructions for receiving, by a security server, interaction data for a user interfacing with the computer device while the user is authenticated for accessing at least one computer resource, the interaction data including keyboard inputs, images taken of the user during the access and screen captures taken periodically; program instructions for performing optical character recognition (OCR) to identify text in the screen captures; program instructions for extracting semantic data from the interaction data and from the text in the screen captures, the semantic data identifying user activities associated with the interaction data; program instructions for generating a schema based on the extracted semantic data, the schema including tags that are descriptive of at least one of the identified user activity and the associated interaction data; program instructions for analyzing the schema based on a model to identify security threats associated with the user activities; program instructions for creating an alarm when non-conforming behavior for at least one user activity is detected, the alarm including a binding of the one or more user activities, one or more tags, keyboard inputs, and screen captures associated with the one or more user activities: and sending a command from the security server to terminate access to the at least one computer resource in response to the alarm. 14. The computer program as recited in claim 11 , wherein analyzing the schema includes generating a security score based on the model and the interaction data. | 0.74026 |
9,990,423 | 30 | 37 | 30. A computer-implemented system, comprising: one or more processors; one or more non-transitory computer readable storage media; computer readable instructions stored on the one or more non-transitory computer readable storage media which, when executed by the one or more processors, implement a first cluster configured to perform operations comprising: receiving, at a first cluster, a search query, the first cluster being a first data intake and query system; transmitting, through a firewall of either the first cluster or a cloud-based cluster, a request for information identifying a plurality of indexers of the cloud-based cluster, the cloud-based cluster being a second data intake and query system; in response to the request, obtaining, from the cloud-based cluster, the information identifying the plurality of indexers, wherein the first cluster and the cloud-based cluster each include at least one master node that is knowledgeable about active indexers within its respective cluster, and the information identifies the plurality of indexers based on the at least one master node of the cloud-based cluster identifying the active indexers; distributing the search query to the plurality of indexers of the cloud-based cluster and one or more indexers of the first cluster, said distributing using the obtained information identifying the plurality of indexers and being through the firewall; and receiving, at the first cluster, a response to the distributed search query from at least one of the plurality of indexers of the cloud-based cluster wherein each response from a respective indexer is produced by the respective indexer based on an evaluation, by the respective indexer, of the distributed search query. | 30. A computer-implemented system, comprising: one or more processors; one or more non-transitory computer readable storage media; computer readable instructions stored on the one or more non-transitory computer readable storage media which, when executed by the one or more processors, implement a first cluster configured to perform operations comprising: receiving, at a first cluster, a search query, the first cluster being a first data intake and query system; transmitting, through a firewall of either the first cluster or a cloud-based cluster, a request for information identifying a plurality of indexers of the cloud-based cluster, the cloud-based cluster being a second data intake and query system; in response to the request, obtaining, from the cloud-based cluster, the information identifying the plurality of indexers, wherein the first cluster and the cloud-based cluster each include at least one master node that is knowledgeable about active indexers within its respective cluster, and the information identifies the plurality of indexers based on the at least one master node of the cloud-based cluster identifying the active indexers; distributing the search query to the plurality of indexers of the cloud-based cluster and one or more indexers of the first cluster, said distributing using the obtained information identifying the plurality of indexers and being through the firewall; and receiving, at the first cluster, a response to the distributed search query from at least one of the plurality of indexers of the cloud-based cluster wherein each response from a respective indexer is produced by the respective indexer based on an evaluation, by the respective indexer, of the distributed search query. 37. The system as described in claim 30 , wherein the search query is configured to be used to wire data. | 0.868421 |
9,002,926 | 10 | 11 | 10. The method of claim 1 , wherein step E) further comprises the steps of: v) receiving, by the server computer, a selected available domain name from the user interface component; vi) rendering, by the server computer, a domain name registration web page configured to register the selected available domain name with a registrar; and vii) transmitting, by the server computer, the domain name registration page to the client computer. | 10. The method of claim 1 , wherein step E) further comprises the steps of: v) receiving, by the server computer, a selected available domain name from the user interface component; vi) rendering, by the server computer, a domain name registration web page configured to register the selected available domain name with a registrar; and vii) transmitting, by the server computer, the domain name registration page to the client computer. 11. The method of claim 10 , wherein: i) the selected available domain name includes at least one registrant data about a user that selected the selected available domain name; and ii) a rendering of the domain name registration web page comprises: a) the selected available domain name; and b) the at least one registrant data. | 0.92928 |
9,881,006 | 8 | 9 | 8. One or more computer-readable hardware storage device having embedded therein a set of instructions which, in response to being executed by one or more processors of a system, causes the system to execute operations comprising: receiving a first set of item listings for the sale of products or services in a first language and a second set of item listings for the sale of products or services in a second language, each of the item listings in the first and second sets of item listings comprising one or more descriptions and metadata identifying the products or services corresponding to the respective item listing; collecting the metadata from the first and second sets of item listings and aligning, using the collected metadata identifying the products or services, a first item listing of the first set of item listings with a second item listing of the second set of item listings in which the first item listing and the second item listing are aligned based on the first item listing and the second item listing being directed toward the same products or services; mapping the first item listing to the second item listing based on the aligning of the first item listing with the second item listing; fetching a first description of the first item listing and a second description of the second item listing; measuring the structural similarity of the fetched first description with respect to the fetched second description to assess whether the first description and the second description are likely to be translations of each other; and in response to the first description and the second description being structurally similar, forming the first description into a first sentence in the first language as a translation of the second description into the first language and forming the second description into a second sentence in the second language as a translation of the first description into the second language. | 8. One or more computer-readable hardware storage device having embedded therein a set of instructions which, in response to being executed by one or more processors of a system, causes the system to execute operations comprising: receiving a first set of item listings for the sale of products or services in a first language and a second set of item listings for the sale of products or services in a second language, each of the item listings in the first and second sets of item listings comprising one or more descriptions and metadata identifying the products or services corresponding to the respective item listing; collecting the metadata from the first and second sets of item listings and aligning, using the collected metadata identifying the products or services, a first item listing of the first set of item listings with a second item listing of the second set of item listings in which the first item listing and the second item listing are aligned based on the first item listing and the second item listing being directed toward the same products or services; mapping the first item listing to the second item listing based on the aligning of the first item listing with the second item listing; fetching a first description of the first item listing and a second description of the second item listing; measuring the structural similarity of the fetched first description with respect to the fetched second description to assess whether the first description and the second description are likely to be translations of each other; and in response to the first description and the second description being structurally similar, forming the first description into a first sentence in the first language as a translation of the second description into the first language and forming the second description into a second sentence in the second language as a translation of the first description into the second language. 9. The one or more computer-readable hardware storage device of claim 8 wherein the first sentence and the second sentence comprise parallel corpora, the operations further comprising using the parallel corpora to translate an item listing from the first language to the second language. | 0.773302 |
7,855,812 | 1 | 2 | 1. A cellular phone with scanning capability, comprising: an antenna for receiving and transmitting modulated wireless signals; received signal processing circuitry for demodulating the modulated wireless signals received by the antenna; output circuitry for transforming the demodulated signals into output data signals for presentation to a user; input circuitry for transforming input from the user into input data signals; input data signal processing circuitry for modulating the input data signals into modulated wireless signals for transmission by the antenna; scanner optics including an array of photosensing elements for detecting light reflected from scanned media; a motion sensor for detecting positional motion of the scanner optics relative to the scanned media; scanner control circuitry for generating light intensity data signals based on reflected light detected by the array of photosensing elements, and for generating positional data signals based on positional motion detected by the motion sensor circuitry; and scanner data signal processing circuitry for processing the light intensity data signals in coordination with the positional data signals to provide image data signals representative of the scanned media; wherein the scanner data signal processing circuitry and the input data signal processing circuitry are coupled and configured to enable transmission by the antenna of modulated wireless signals representative of the image data signals; the scanner data signal processing circuitry comprises circuitry configured with optical character recognition capability to provide image data signals representative of text data in the scanned media, and with text-to-speech conversion capability to convert the text data representative image data signals to voice audio signals representative of the text data in spoken form; and the input data processing circuitry comprises circuitry for modulating the voice audio signals for transmission of modulated wireless signals representing the spoken text data by the antenna. | 1. A cellular phone with scanning capability, comprising: an antenna for receiving and transmitting modulated wireless signals; received signal processing circuitry for demodulating the modulated wireless signals received by the antenna; output circuitry for transforming the demodulated signals into output data signals for presentation to a user; input circuitry for transforming input from the user into input data signals; input data signal processing circuitry for modulating the input data signals into modulated wireless signals for transmission by the antenna; scanner optics including an array of photosensing elements for detecting light reflected from scanned media; a motion sensor for detecting positional motion of the scanner optics relative to the scanned media; scanner control circuitry for generating light intensity data signals based on reflected light detected by the array of photosensing elements, and for generating positional data signals based on positional motion detected by the motion sensor circuitry; and scanner data signal processing circuitry for processing the light intensity data signals in coordination with the positional data signals to provide image data signals representative of the scanned media; wherein the scanner data signal processing circuitry and the input data signal processing circuitry are coupled and configured to enable transmission by the antenna of modulated wireless signals representative of the image data signals; the scanner data signal processing circuitry comprises circuitry configured with optical character recognition capability to provide image data signals representative of text data in the scanned media, and with text-to-speech conversion capability to convert the text data representative image data signals to voice audio signals representative of the text data in spoken form; and the input data processing circuitry comprises circuitry for modulating the voice audio signals for transmission of modulated wireless signals representing the spoken text data by the antenna. 2. The cellular phone of claim 1 , wherein the scanner data processing circuitry further includes circuitry configured with language translation capability to convert image data signals the text data representative to voice audio signals representative of the text data in spoken form, as spoken in a language different from the language of the text data. | 0.726923 |
7,966,177 | 13 | 14 | 13. A method according to claim 10 , comprising, if no agreeing reference combination of features is found in step d), changing a non-agreeing part of the sequence of features on the basis of a combination of features having as many feature agreements as possible, and executing steps c) to e) with the changed sequence of features. | 13. A method according to claim 10 , comprising, if no agreeing reference combination of features is found in step d), changing a non-agreeing part of the sequence of features on the basis of a combination of features having as many feature agreements as possible, and executing steps c) to e) with the changed sequence of features. 14. A method according to claim 13 , comprising changing the non-agreeing part of the sequence of features using a fuzzy logic in a manner that takes account of the similarity and sequence of the meaningful content defined in reference combinations of features, provided such similarity meets a predetermined requirement. | 0.877387 |
9,552,549 | 9 | 10 | 9. A system for a ranking approach to training deep neural networks for multilabel image annotation, comprising: one or more computers; storage coupled to the one or more computers on which is stored a training data set including training examples, a label corpus, and a semantic structure; and a machine learning system deployed on the one or more computers, the machine learning system comprising a neural network and a neural network trainer, the neural network adapted to receive the label corpus and training examples from the training data set, generate respective label scores for each of at least two labels in the label corpus for at least one training example from the training data set, and receive updated weights, and the neural network trainer adapted to determine an error of the neural network based on a semantic ranking loss of the label scores and to determine the semantic ranking loss according to:
J=Σ i=1 n Σ j=1 c+ Σ k=1 c− D ( y c+ j ,y c− k )max(0,ρ− x i W c+ j +x i W c− k ) where W is a ranking function of the neural network, n is the number of training examples, x i is an ith training example, c+ is the number of positive labels for the training example x i , c− is the number of negative labels for the training example x i , ρ is a margin for hinge loss, y c+ j is the jth positive label, y c− k is kth negative label, D(y c+ j , y c− k ) is a function that evaluates the semantic distance between two labels, y c+ j and y c− k , x i W c+ j is the label score given to the jth positive label when the ranking function W is used to evaluate the training example x i , and x i W c− k is the label score given to the kth negative label when the ranking function W is used to evaluate the training example x i . | 9. A system for a ranking approach to training deep neural networks for multilabel image annotation, comprising: one or more computers; storage coupled to the one or more computers on which is stored a training data set including training examples, a label corpus, and a semantic structure; and a machine learning system deployed on the one or more computers, the machine learning system comprising a neural network and a neural network trainer, the neural network adapted to receive the label corpus and training examples from the training data set, generate respective label scores for each of at least two labels in the label corpus for at least one training example from the training data set, and receive updated weights, and the neural network trainer adapted to determine an error of the neural network based on a semantic ranking loss of the label scores and to determine the semantic ranking loss according to:
J=Σ i=1 n Σ j=1 c+ Σ k=1 c− D ( y c+ j ,y c− k )max(0,ρ− x i W c+ j +x i W c− k ) where W is a ranking function of the neural network, n is the number of training examples, x i is an ith training example, c+ is the number of positive labels for the training example x i , c− is the number of negative labels for the training example x i , ρ is a margin for hinge loss, y c+ j is the jth positive label, y c− k is kth negative label, D(y c+ j , y c− k ) is a function that evaluates the semantic distance between two labels, y c+ j and y c− k , x i W c+ j is the label score given to the jth positive label when the ranking function W is used to evaluate the training example x i , and x i W c− k is the label score given to the kth negative label when the ranking function W is used to evaluate the training example x i . 10. The system of claim 9 , wherein the neural network trainer is further adapted to determine D(y c+ j , y c− k ) based on number of nodes traversed to travel between a leaf for the positive label y c+ j and a leaf for the negative label y c− k in a semantic tree. | 0.647606 |
8,732,630 | 24 | 27 | 24. A system for implementing pattern-based design enabled manufacturing of electronic circuit designs, comprising: at least one processor or at least one processor core that is at least to: detect an incompatible connection that interacts with a wire that is represented using digital signals in a digital modeling environment; represent a real-valued net of a built-in nettype in the digital modeling environment with 4-state logic signals in the digital modeling environment; correlate the real-valued net with a corresponding resolution function that is defined natively in the digital modeling environment; and coerce the incompatible connection to the wire in the digital modeling environment based at least in part upon the corresponding resolution function. | 24. A system for implementing pattern-based design enabled manufacturing of electronic circuit designs, comprising: at least one processor or at least one processor core that is at least to: detect an incompatible connection that interacts with a wire that is represented using digital signals in a digital modeling environment; represent a real-valued net of a built-in nettype in the digital modeling environment with 4-state logic signals in the digital modeling environment; correlate the real-valued net with a corresponding resolution function that is defined natively in the digital modeling environment; and coerce the incompatible connection to the wire in the digital modeling environment based at least in part upon the corresponding resolution function. 27. The system of claim 24 , in which the at least one processor or at least one processor core is further to: identify a first block; identify a Verilog-AMS block included in the first block in the digital modeling environment; identify a second block that is in the digital modeling environment and is included in the Verilog-AMS block; and coerce a Verilog-AMS wire to assume one or more properties of a net in the first block or the second block in the digital modeling environment, wherein the first block in the digital modeling environment, the second block in the digital modeling environment, and the Verilog-AMS block is interconnected with the Verilog-AMS wire. | 0.683318 |
5,404,422 | 1 | 8 | 1. A voice recognition apparatus capable of recognizing any word utterance by using a neural network, said apparatus comprising: means for inputting an input utterance and for outputting compressed feature variables of said input utterance, said input means including means for receiving said input utterance, means connected to said receiving means for amplifying said input utterance, means connected to said amplifying means for extracting said feature variables from an electrical signal, and means connected to said extracting means for compressing said feature variables; a word-head detecting section for detecting a front endpoint of said input utterance from said compressed feature variables, said word-head detecting section outputting said compressed feature variables if said front endpoint is detected as a start end of said input utterance, said word-head detecting section not outputting said compressed feature variables if said front endpoint is not detected; a first means connected to said input means for receiving said compressed feature variables output from said word-head detecting section and for outputting a value corresponding to a similarity in partial phoneme series of a specific word among vocabularies to be recognized with respect to said input utterance, said first means being capable of sound analyzing said input utterance so that feature values are generated and shifted in a time scale and an input frame is selected so as to maximize each of said output values output from said first means corresponding to a similarity among said shifted feature values, said first means including a plurality of event nets for receiving feature variables extracted from an input utterance, each of said event nets being arranged to shift said feature variables, within a predetermined range from a front endpoint positioned at any time, in accordance with time interval information obtained by analyzing speech samples of a plurality of persons and by selecting a location at which a maximum output is made possible among shifted locations of said feature variables so that a value, corresponding to a similarity between said partial phoneme series of said corresponding word to be recognized and said input utterance, is output; a second means, connected to said first means, for receiving all of said values output from said first means and for outputting a value corresponding to a similarity in said specific word with respect to said input utterance; a third means, connected to said second means, for receiving all of said values output from said second means and for outputting a value corresponding to a classification of voice recognition, in which said input utterance belongs, so as to output a value corresponding to a similarity between said input utterance and words to be recognized. | 1. A voice recognition apparatus capable of recognizing any word utterance by using a neural network, said apparatus comprising: means for inputting an input utterance and for outputting compressed feature variables of said input utterance, said input means including means for receiving said input utterance, means connected to said receiving means for amplifying said input utterance, means connected to said amplifying means for extracting said feature variables from an electrical signal, and means connected to said extracting means for compressing said feature variables; a word-head detecting section for detecting a front endpoint of said input utterance from said compressed feature variables, said word-head detecting section outputting said compressed feature variables if said front endpoint is detected as a start end of said input utterance, said word-head detecting section not outputting said compressed feature variables if said front endpoint is not detected; a first means connected to said input means for receiving said compressed feature variables output from said word-head detecting section and for outputting a value corresponding to a similarity in partial phoneme series of a specific word among vocabularies to be recognized with respect to said input utterance, said first means being capable of sound analyzing said input utterance so that feature values are generated and shifted in a time scale and an input frame is selected so as to maximize each of said output values output from said first means corresponding to a similarity among said shifted feature values, said first means including a plurality of event nets for receiving feature variables extracted from an input utterance, each of said event nets being arranged to shift said feature variables, within a predetermined range from a front endpoint positioned at any time, in accordance with time interval information obtained by analyzing speech samples of a plurality of persons and by selecting a location at which a maximum output is made possible among shifted locations of said feature variables so that a value, corresponding to a similarity between said partial phoneme series of said corresponding word to be recognized and said input utterance, is output; a second means, connected to said first means, for receiving all of said values output from said first means and for outputting a value corresponding to a similarity in said specific word with respect to said input utterance; a third means, connected to said second means, for receiving all of said values output from said second means and for outputting a value corresponding to a classification of voice recognition, in which said input utterance belongs, so as to output a value corresponding to a similarity between said input utterance and words to be recognized. 8. A voice recognition apparatus according to claim 1, wherein said apparatus uses a Dynamic Programming method for checking said similarity between said specific word and said input utterance, and a count of said word nets is equal to a count of said vocabularies to be recognized. | 0.617886 |
9,396,185 | 1 | 5 | 1. A method for providing a contextual description of an object, the method comprising: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt, wherein at least one of the preceding actions is performed on at least one electronic hardware component. | 1. A method for providing a contextual description of an object, the method comprising: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt, wherein at least one of the preceding actions is performed on at least one electronic hardware component. 5. The method of claim 1 wherein prior to combining the first pre-defined phrase template with the second pre-defined phrase template, the method comprises: considering a set of first object phrase templates associated with the first object type; considering a set of second object phrase templates associated with the second object type; selecting from the set of first object phrase templates at least one first object phrase template that refers to the second object type; and selecting from the set of second phrase templates at least one second object phrase template that refers to the first object type. | 0.727679 |
9,262,395 | 8 | 13 | 8. A method implemented on a computing device comprising one or more processors, the method comprising: receiving a first term as a name or description representing an object, wherein the object includes a physical or conceptual object, a topic, or an attribute associated with one or more objects, wherein the first term is received from a source including manual input from a user, or automatic input from a computing device, for automatically gathering information or knowledge about the object represented by the first term from unstructured data sources using a machine-based method; receiving a first group of text units comprising at least two words, or one or more phrases or sentences or paragraphs or documents, wherein at least half of the text units contain the first term or are from contents that contain the first term, and at least half of the text units contain one or more unspecified second terms each being different from the first term; for one or more text units containing the first term, identifying a grammatical attribute associated with the first term, wherein the grammatical attributes include at least a subject or a predicate of a sentence or part of a predicate, or a head or a modifier of a multi-word phrase, or a sub-component of a multi-word phrase, or parts of speech; for one or more second terms in the one or more text units that contain the first term, producing a first score value based on the grammatical attribute associated with the first term; selecting one or more second terms based on the first score value of the term; assembling the selected terms into a term set; attaching the term set to the first term to form a dataset, wherein the function of the selected terms includes representing terms associated with the first term, or representing properties associated with the object, or representing information about the object with information that is automatically gathered from unstructured text contents by using a machine-based method; and outputting the dataset as a form of information representation or knowledge representation for a specific object represented by the first term. | 8. A method implemented on a computing device comprising one or more processors, the method comprising: receiving a first term as a name or description representing an object, wherein the object includes a physical or conceptual object, a topic, or an attribute associated with one or more objects, wherein the first term is received from a source including manual input from a user, or automatic input from a computing device, for automatically gathering information or knowledge about the object represented by the first term from unstructured data sources using a machine-based method; receiving a first group of text units comprising at least two words, or one or more phrases or sentences or paragraphs or documents, wherein at least half of the text units contain the first term or are from contents that contain the first term, and at least half of the text units contain one or more unspecified second terms each being different from the first term; for one or more text units containing the first term, identifying a grammatical attribute associated with the first term, wherein the grammatical attributes include at least a subject or a predicate of a sentence or part of a predicate, or a head or a modifier of a multi-word phrase, or a sub-component of a multi-word phrase, or parts of speech; for one or more second terms in the one or more text units that contain the first term, producing a first score value based on the grammatical attribute associated with the first term; selecting one or more second terms based on the first score value of the term; assembling the selected terms into a term set; attaching the term set to the first term to form a dataset, wherein the function of the selected terms includes representing terms associated with the first term, or representing properties associated with the object, or representing information about the object with information that is automatically gathered from unstructured text contents by using a machine-based method; and outputting the dataset as a form of information representation or knowledge representation for a specific object represented by the first term. 13. The method of claim 8 , further comprising: determining a weighting co-efficient based on the grammatical attribute associated with the first term; and for the one or more second terms, determining the cumulative value based on the weighting co-efficient. | 0.859392 |
8,762,161 | 7 | 11 | 7. The method of claim 1 further comprising the step of extracting data from the at least one interaction. | 7. The method of claim 1 further comprising the step of extracting data from the at least one interaction. 11. The method of claim 7 wherein the data comprises an at least one item selected from the group consisting of: transcription data; spotted words; emotion indication; phonetic search result; textual analysis; Computer Telephony Integration; screen events; talkover data; and textual analysis. | 0.86778 |
8,447,603 | 1 | 3 | 1. A method of evaluating naturalness of speech utterances by using crowd wisdom models, the method comprising: presenting a plurality of human-testers with obtained speech utterances; receiving, for each presented speech utterance, a plurality of corresponding human-tester generated speech utterances being human repetitions of the presented speech utterance; generating, for each presented speech utterance, an utterance-specific scoring model that is based on the corresponding human-tester generated speech utterances, each scoring model being configured to estimate a level of speech naturalness for the presented speech utterance using at least crowd wisdom models; and deriving a speech naturalness score for each presented speech utterance by respectively applying the utterance-specific scoring model to each presented speech utterance, wherein at least one of: the presenting, the receiving, the generating, and the deriving is executed by at least one computer processor. | 1. A method of evaluating naturalness of speech utterances by using crowd wisdom models, the method comprising: presenting a plurality of human-testers with obtained speech utterances; receiving, for each presented speech utterance, a plurality of corresponding human-tester generated speech utterances being human repetitions of the presented speech utterance; generating, for each presented speech utterance, an utterance-specific scoring model that is based on the corresponding human-tester generated speech utterances, each scoring model being configured to estimate a level of speech naturalness for the presented speech utterance using at least crowd wisdom models; and deriving a speech naturalness score for each presented speech utterance by respectively applying the utterance-specific scoring model to each presented speech utterance, wherein at least one of: the presenting, the receiving, the generating, and the deriving is executed by at least one computer processor. 3. The method according to claim 1 , further comprising generating human tester-specific acoustic and prosodic models usable for measuring acoustic and prosodic distances between different human testers, and wherein the acoustic and prosodic distances are usable for performing similarity analysis of human testers. | 0.876664 |
9,483,552 | 1 | 3 | 1. A computer-implemented method comprising: receiving an unstructured document; receiving, via a user interface, information related to data fields of the received unstructured document; classifying, via a user interface, the received unstructured document into one of a plurality of document categories thereby specifying an associated document category, each document category of the plurality of document categories having a different associated rule set that defines a behavior with a corresponding set of operations to perform as related to a particular document in the document category, the set of operations including operations for dispatching the document after information is obtained from the data fields of the document; obtaining information from the document using the information related to data fields of the received unstructured document and the associated document category; storing portions of the information obtained from the document in a data set corresponding to the document; using a portion of the information obtained from the document to obtain an enterprise identifier corresponding to an intended recipient of the document; obtaining an enterprise record identified by the enterprise identifier and the information in the data set; using the data set and the enterprise identifier to dispatch the document to the intended recipient via an enterprise corresponding to the enterprise identifier; and using the data set and the associated document category to dispatch the document by performing the operations defined by the associated document category. | 1. A computer-implemented method comprising: receiving an unstructured document; receiving, via a user interface, information related to data fields of the received unstructured document; classifying, via a user interface, the received unstructured document into one of a plurality of document categories thereby specifying an associated document category, each document category of the plurality of document categories having a different associated rule set that defines a behavior with a corresponding set of operations to perform as related to a particular document in the document category, the set of operations including operations for dispatching the document after information is obtained from the data fields of the document; obtaining information from the document using the information related to data fields of the received unstructured document and the associated document category; storing portions of the information obtained from the document in a data set corresponding to the document; using a portion of the information obtained from the document to obtain an enterprise identifier corresponding to an intended recipient of the document; obtaining an enterprise record identified by the enterprise identifier and the information in the data set; using the data set and the enterprise identifier to dispatch the document to the intended recipient via an enterprise corresponding to the enterprise identifier; and using the data set and the associated document category to dispatch the document by performing the operations defined by the associated document category. 3. The computer-implemented method as claimed in claim 1 including reconciling dispatched documents with received documents. | 0.862222 |
9,244,536 | 27 | 28 | 27. The method of claim 23 , wherein the plurality of virtual punctuation mark keys comprises virtual punctuation mark keys respectively associated with a comma and a period. | 27. The method of claim 23 , wherein the plurality of virtual punctuation mark keys comprises virtual punctuation mark keys respectively associated with a comma and a period. 28. The method of claim 27 , wherein the plurality of virtual punctuation mark keys further comprises virtual punctuation mark keys respectively associated with an exclamation point and a semicolon. | 0.944476 |
8,515,212 | 1 | 6 | 1. A computer-implemented method, comprising: identifying a plurality of queries, each of the queries being a unique set of one or more query terms received by a search system as a query input; for each of the queries: selecting training images for training an image relevance model, the training images comprising: a first image having a first relevance measure, for the query, that satisfies a first relevance threshold; and a second image having a second relevance measure, for a different query in the plurality of queries, that satisfies a second relevance threshold; for each of the training images, identifying content feature values, each content feature value representing a characteristic of an aspect of the training image; and training the image relevance model to generate relevance measures of content feature values of images to the query based on the content feature values of the training images, wherein the image relevance model comprises a vector of weights corresponding to the content feature values, the training comprising: initializing the vector of weights to default values; generating a first training score based on the image relevance model and the content feature values of the first image; generating a second training score based on the image relevance model and the content feature values of the second image; comparing the first training score and the second training score; in response to a difference between the first training score and the second training score not satisfying a training score margin, adjusting values of the vector of weights; determining whether a training condition has occurred; and repeating the selecting training images, the generating the first training score, the generating the second training score and the comparing when the training condition has not occurred. | 1. A computer-implemented method, comprising: identifying a plurality of queries, each of the queries being a unique set of one or more query terms received by a search system as a query input; for each of the queries: selecting training images for training an image relevance model, the training images comprising: a first image having a first relevance measure, for the query, that satisfies a first relevance threshold; and a second image having a second relevance measure, for a different query in the plurality of queries, that satisfies a second relevance threshold; for each of the training images, identifying content feature values, each content feature value representing a characteristic of an aspect of the training image; and training the image relevance model to generate relevance measures of content feature values of images to the query based on the content feature values of the training images, wherein the image relevance model comprises a vector of weights corresponding to the content feature values, the training comprising: initializing the vector of weights to default values; generating a first training score based on the image relevance model and the content feature values of the first image; generating a second training score based on the image relevance model and the content feature values of the second image; comparing the first training score and the second training score; in response to a difference between the first training score and the second training score not satisfying a training score margin, adjusting values of the vector of weights; determining whether a training condition has occurred; and repeating the selecting training images, the generating the first training score, the generating the second training score and the comparing when the training condition has not occurred. 6. The method of claim 1 , further comprising: for each query: identifying a plurality of images; for each image: applying the image relevance model to content feature values of the image; and assigning an image relevance score to the image based on an application of the image relevance model to the content feature values, the image relevance score being a relevancy measure of the image to the query. | 0.501238 |
8,447,110 | 4 | 6 | 4. The processing system according to claim 1 , wherein: the microprocessor is further programmed to implement a runtime search unit for receiving a search query; narrowing down a set of pieces of document data by the search query; acquiring, from a time series of a keyword in the narrowed set of pieces of document data a time series of each keyword cluster in the narrowed set of pieces of document data; and performing a frequency analysis of the time series of the keyword cluster. | 4. The processing system according to claim 1 , wherein: the microprocessor is further programmed to implement a runtime search unit for receiving a search query; narrowing down a set of pieces of document data by the search query; acquiring, from a time series of a keyword in the narrowed set of pieces of document data a time series of each keyword cluster in the narrowed set of pieces of document data; and performing a frequency analysis of the time series of the keyword cluster. 6. The processing system according to claim 4 , wherein the runtime search unit: receives an instruction to perform a drill-down to a keyword cluster; and performs, for the keyword cluster to be subjected to drill-down, a time-series analysis of keywords in descending order of weight in the keyword cluster. | 0.847976 |
8,032,829 | 11 | 13 | 11. A computer storage medium having computer executable instructions for performing a method of transferring data from a financial program to a word processing program to view and modify financial documents in the word processing program comprising: selecting a template in a finance program wherein the template has a field related to the selected template; identifying an open field in the selected template that can be filled in with data from the finance program; selecting data stored by the finance program that is appropriate to fill in the open field in the selected template; communicating the selected data and the selected template to the word processing program; opening a document in the word processing program that displays the selected template and the selected data in the appropriate field as a word processing document; and allowing the changes made on word processing document to be communicated to the finance program. | 11. A computer storage medium having computer executable instructions for performing a method of transferring data from a financial program to a word processing program to view and modify financial documents in the word processing program comprising: selecting a template in a finance program wherein the template has a field related to the selected template; identifying an open field in the selected template that can be filled in with data from the finance program; selecting data stored by the finance program that is appropriate to fill in the open field in the selected template; communicating the selected data and the selected template to the word processing program; opening a document in the word processing program that displays the selected template and the selected data in the appropriate field as a word processing document; and allowing the changes made on word processing document to be communicated to the finance program. 13. The computer storage medium of claim 11 further comprising allowing a user to modify the word processing document. | 0.914616 |
9,626,703 | 8 | 9 | 8. The method of claim 1 , further comprising: receiving, at the computer system, a previous user input prior to the receipt of the user input, wherein the previous user input is related to the product or service; and storing, by the computer system, context information associated with the user based on information related to the previous user input, wherein determining the product or service as at least one product or service to be purchased on behalf of the user comprises determining, without further user input after the receipt of the user input, the product or service based on the natural language utterance and the context information related to the previous user input. | 8. The method of claim 1 , further comprising: receiving, at the computer system, a previous user input prior to the receipt of the user input, wherein the previous user input is related to the product or service; and storing, by the computer system, context information associated with the user based on information related to the previous user input, wherein determining the product or service as at least one product or service to be purchased on behalf of the user comprises determining, without further user input after the receipt of the user input, the product or service based on the natural language utterance and the context information related to the previous user input. 9. The method of claim 8 , further comprising: performing, by the computer system, speech recognition on the previous user input to recognize one or more words associated with the previous user input; and identifying, by the computer system, the product or service as at least one product or service related to the previous user input based on the one or more recognized words, wherein storing the context information comprises storing product information identifying the product or service based on the identification of the product or service as related to the previous user input such that the context information comprises the product information, and wherein determining the product or service as at least one product or service to be purchased on behalf of the user comprises determining, without further user input after the receipt of the user input, the product or service based on the natural language utterance and the product information. | 0.73655 |
9,384,185 | 7 | 8 | 7. The system according to claim 1 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: approximately normalise the first associated probability estimate and the second associated probability estimate by estimating a normalisation factor for the first associated probability estimate and the second associated probability estimate. | 7. The system according to claim 1 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to: approximately normalise the first associated probability estimate and the second associated probability estimate by estimating a normalisation factor for the first associated probability estimate and the second associated probability estimate. 8. The system according to claim 7 , further comprising a prior model configured to generate at least one third sequence prediction, wherein each of the at least one third sequence prediction comprises a third sequence and a third associated probability estimate. | 0.921958 |
8,595,621 | 17 | 20 | 17. A system for truncating character strings in a computing environment, comprising: a hardware processor; and a user interface device that uses the hardware processor for receiving a list including plural character strings, and truncating one or more of the character strings for generating a display list of unique character strings based on determining a truncation location within each string by: for each character string, comparing the string and corresponding Uniform Resource Identifier (URI), if the string is different from the URI, then truncating the beginning of the string, otherwise if the string matches the URI, then truncating the end of the string; wherein the user interface device uses the hardware processor to display the character strings of the display list in context with each other on a user interface. | 17. A system for truncating character strings in a computing environment, comprising: a hardware processor; and a user interface device that uses the hardware processor for receiving a list including plural character strings, and truncating one or more of the character strings for generating a display list of unique character strings based on determining a truncation location within each string by: for each character string, comparing the string and corresponding Uniform Resource Identifier (URI), if the string is different from the URI, then truncating the beginning of the string, otherwise if the string matches the URI, then truncating the end of the string; wherein the user interface device uses the hardware processor to display the character strings of the display list in context with each other on a user interface. 20. The system of claim 17 , wherein determining truncation location within each string includes: placing the original character strings to be displayed in an original list, creating a new END list from the strings by truncating each original string at the end of the string, scoring each truncated string in the END list for similarity to other strings in the END list, creating a new BEGIN list of strings by truncating each original string at the beginning of the string, scoring each truncated string in the BEGIN list for similarity to other strings in the BEGIN list, creating a new MIX list of strings from the best scoring truncated strings, scoring each string in the MIX list for similarity to other strings in the MIX list, summing the scores in each list to create a total score for each list, and selecting the list with the lowest score as the display list. | 0.500573 |
7,519,580 | 1 | 2 | 1. A method of displaying search information implemented in a computer infrastructure having computer executable code, comprising the steps of: submitting a query having one or more search criterion; displaying a summary result of the query in a search criteria control bar (SCCB) format, wherein the SCCB format includes each of the one or more search criterion having a first active control for editing the query with a one-click operation and a second active control for editing the query with another one-click operation; initiating a submission of another query when either the first or second active control is clicked to obtain another summary result in the SCCB format reflecting results of the another query based on which active control is clicked; displaying the summary result and the another summary result in the SCCB format, wherein the one or more search criterion includes at least any one of one or more category words or phrase each delimited by a set of category delimiters and one or more keywords or phrase each delimited by a set of keyword delimiters; displaying the one or more search criterion each having an associated filter option for removing a chosen search criterion from the one or more search criterion when the another query is initiated, the associated filter option being the second active control; and removing the chosen search criterion when the associated filter option is clicked and initiating the submission of the another query using any remaining one or more search criterion causing the results of the another query to be limited to the remaining one or more search criterion. | 1. A method of displaying search information implemented in a computer infrastructure having computer executable code, comprising the steps of: submitting a query having one or more search criterion; displaying a summary result of the query in a search criteria control bar (SCCB) format, wherein the SCCB format includes each of the one or more search criterion having a first active control for editing the query with a one-click operation and a second active control for editing the query with another one-click operation; initiating a submission of another query when either the first or second active control is clicked to obtain another summary result in the SCCB format reflecting results of the another query based on which active control is clicked; displaying the summary result and the another summary result in the SCCB format, wherein the one or more search criterion includes at least any one of one or more category words or phrase each delimited by a set of category delimiters and one or more keywords or phrase each delimited by a set of keyword delimiters; displaying the one or more search criterion each having an associated filter option for removing a chosen search criterion from the one or more search criterion when the another query is initiated, the associated filter option being the second active control; and removing the chosen search criterion when the associated filter option is clicked and initiating the submission of the another query using any remaining one or more search criterion causing the results of the another query to be limited to the remaining one or more search criterion. 2. The method of claim 1 , wherein the set of category delimiters is a set of brackets. | 0.72293 |
8,000,970 | 2 | 3 | 2. The method of claim 1 , further comprising: receiving a telephony service request, wherein said telephone service request is associated with a particular one of said service processors and specifies a location of said VXML data representing said telephony service. | 2. The method of claim 1 , further comprising: receiving a telephony service request, wherein said telephone service request is associated with a particular one of said service processors and specifies a location of said VXML data representing said telephony service. 3. The method of claim 2 , further comprising: determining an available VXML parser; and providing said specified location to said available VXML parser. | 0.974719 |
9,406,078 | 2 | 3 | 2. The method of claim 1 , wherein the conversational language processor comprises one or more domain agents, where a domain agent is configured to assist in: i) interpreting requests related to its domain; and ii) determining a response to the requests related to its domain. | 2. The method of claim 1 , wherein the conversational language processor comprises one or more domain agents, where a domain agent is configured to assist in: i) interpreting requests related to its domain; and ii) determining a response to the requests related to its domain. 3. The method of claim 2 , wherein the domain agents comprise an electronic commerce agent and selecting an advertisement comprises selecting an advertisement that corresponds to an electronic commerce opportunity. | 0.955657 |
8,266,585 | 1 | 9 | 1. In a software development system, a method for assisting a user in creating source code for a computer program in a high-level programming language, the method comprising: at a current user inputting location within a piece of said source code under development, detecting a need for assisting the user with input for the creation of the piece of source code; determining fitting source code elements suitable for input at said current inputting location; and providing to the user said list of fitting source code elements, wherein said determining the fitting source code elements includes determining for each fitting source code element a respective fitting probability of the source code element in the current inputting location, and wherein said providing to the user said list of fitting source code elements includes associating to each fitting source code element in the list an indication of the respective fitting probability, wherein said fitting probabilities include probabilities of software methods of a software class being invoked after other methods of the same software class. | 1. In a software development system, a method for assisting a user in creating source code for a computer program in a high-level programming language, the method comprising: at a current user inputting location within a piece of said source code under development, detecting a need for assisting the user with input for the creation of the piece of source code; determining fitting source code elements suitable for input at said current inputting location; and providing to the user said list of fitting source code elements, wherein said determining the fitting source code elements includes determining for each fitting source code element a respective fitting probability of the source code element in the current inputting location, and wherein said providing to the user said list of fitting source code elements includes associating to each fitting source code element in the list an indication of the respective fitting probability, wherein said fitting probabilities include probabilities of software methods of a software class being invoked after other methods of the same software class. 9. The method of claim 1 , using said fitting probabilities to predict a next software method to follow a current software method at said current user inputting location. | 0.671815 |
8,131,740 | 10 | 12 | 10. A computer-readable storage medium including a program, which when executed on a processor performs an operation for responding to a search request for non-avatar virtual objects present in an immersive virtual environment, comprising: receiving, from a user, a search query for non-avatar virtual objects of the virtual environment, wherein the search query includes one or more attribute conditions identifying characteristics of at least one non-avatar virtual object of the virtual environment, and wherein the search query includes at least one interaction condition describing the user's past interaction with non-avatar virtual objects of the virtual environment; determining a collection of non-avatar virtual objects present in the virtual environment satisfying the one or more attribute conditions of the search query; filtering the collection of non-avatar virtual objects, based on the one or more interaction conditions, to produce a set of search results responsive to the search query; and returning the set of search results to the user. | 10. A computer-readable storage medium including a program, which when executed on a processor performs an operation for responding to a search request for non-avatar virtual objects present in an immersive virtual environment, comprising: receiving, from a user, a search query for non-avatar virtual objects of the virtual environment, wherein the search query includes one or more attribute conditions identifying characteristics of at least one non-avatar virtual object of the virtual environment, and wherein the search query includes at least one interaction condition describing the user's past interaction with non-avatar virtual objects of the virtual environment; determining a collection of non-avatar virtual objects present in the virtual environment satisfying the one or more attribute conditions of the search query; filtering the collection of non-avatar virtual objects, based on the one or more interaction conditions, to produce a set of search results responsive to the search query; and returning the set of search results to the user. 12. The computer-readable storage medium of claim 10 , wherein the operation further comprises, prior to returning the set of search results to the user, ordering the search results based on the one or more interaction conditions. | 0.716749 |
9,177,013 | 6 | 8 | 6. The method of claim 1 further comprising: a. processing the electronic document to identify a second citation; b. generating a citation group comprising the first and second citations and a set of citation association data; c. adding an entry in a bibliography based on the citation group and the citation association data. | 6. The method of claim 1 further comprising: a. processing the electronic document to identify a second citation; b. generating a citation group comprising the first and second citations and a set of citation association data; c. adding an entry in a bibliography based on the citation group and the citation association data. 8. The method of claim 6 wherein the set of citation association data comprises a set of alphanumeric labels, the alphanumeric labels conforming to a set of bibliographic formatting rules. | 0.95634 |
10,013,480 | 1 | 3 | 1. A method comprising: identifying, by at least one computing device, a first plurality of buckets and assigning each message of a plurality of messages to one or more buckets of the first plurality based on topics of the plurality of messages, each of the one or more buckets having one or more assigned messages; creating, by the at least one computing device, a conversation graph comprising a plurality of nodes, each node corresponding to a bucket of the first plurality corresponding to a topic, and a plurality of directed edges, each directed edge connecting two buckets of the first plurality and indicating a transition direction from one bucket to the other bucket, the transition direction representing at least one transition of a plurality of transitions between the two buckets; defining, by the at least one computing device, one or more domains of interaction, each domain of interaction comprising a second plurality of buckets from the first plurality of buckets connected by the directed edges and representing a type of social resource exchange; and assigning, by the at least one computing device, each message of the plurality to at least one of the one or more domains of interaction, the assigning identifying at least one type of social resource exchange for each message. | 1. A method comprising: identifying, by at least one computing device, a first plurality of buckets and assigning each message of a plurality of messages to one or more buckets of the first plurality based on topics of the plurality of messages, each of the one or more buckets having one or more assigned messages; creating, by the at least one computing device, a conversation graph comprising a plurality of nodes, each node corresponding to a bucket of the first plurality corresponding to a topic, and a plurality of directed edges, each directed edge connecting two buckets of the first plurality and indicating a transition direction from one bucket to the other bucket, the transition direction representing at least one transition of a plurality of transitions between the two buckets; defining, by the at least one computing device, one or more domains of interaction, each domain of interaction comprising a second plurality of buckets from the first plurality of buckets connected by the directed edges and representing a type of social resource exchange; and assigning, by the at least one computing device, each message of the plurality to at least one of the one or more domains of interaction, the assigning identifying at least one type of social resource exchange for each message. 3. The method of claim 1 , at least one edge of the plurality representing more than one transition of the plurality. | 0.855556 |
7,840,604 | 13 | 19 | 13. A process for determining a user-specified scenario in order to add value to information, comprising: searching via a server, a collection of documents to find a document in the collection of documents relevant to a scenario, wherein the documents comprise chat dialogs, emails, blogs, and internet sites; processing the relevant documents to a scenario using one or more processors at the server to extract entities and relationships between the extracted entities, wherein the extracted entities comprise relevant nouns, magnitudes, numbers, or concepts contained within the text of the documents; setting influence values for a plurality of the extracted entities to indicate the amount of influence each of the plurality of the extracted entities has on another extracted entity to which an extracted relationship exists; associating a set of options with the plurality of the extracted entities; and populating a risk model comprising a plurality of nodes derived from the extracted entities, wherein at least one of the plurality of nodes is associated with an option from the set of options, the option including an associated value, the associated value usable for calculating an option value associated with a higher level node in the risk model; and rendering, for display at a user interface of one or more host computers in communication with the server, one or more of the plurality of extracted entities on a chart having two axes, a first axis indicating an amount of influence exerted on the extracted entities located on the chart as represented by the influence values, and the second axis indicating an amount of influence that the extracted entities located on the chart exert on other extracted entities, the amounts of influence being derived from the influence values. | 13. A process for determining a user-specified scenario in order to add value to information, comprising: searching via a server, a collection of documents to find a document in the collection of documents relevant to a scenario, wherein the documents comprise chat dialogs, emails, blogs, and internet sites; processing the relevant documents to a scenario using one or more processors at the server to extract entities and relationships between the extracted entities, wherein the extracted entities comprise relevant nouns, magnitudes, numbers, or concepts contained within the text of the documents; setting influence values for a plurality of the extracted entities to indicate the amount of influence each of the plurality of the extracted entities has on another extracted entity to which an extracted relationship exists; associating a set of options with the plurality of the extracted entities; and populating a risk model comprising a plurality of nodes derived from the extracted entities, wherein at least one of the plurality of nodes is associated with an option from the set of options, the option including an associated value, the associated value usable for calculating an option value associated with a higher level node in the risk model; and rendering, for display at a user interface of one or more host computers in communication with the server, one or more of the plurality of extracted entities on a chart having two axes, a first axis indicating an amount of influence exerted on the extracted entities located on the chart as represented by the influence values, and the second axis indicating an amount of influence that the extracted entities located on the chart exert on other extracted entities, the amounts of influence being derived from the influence values. 19. The process of claim 13 , wherein the selecting the extracted entities comprises graphically viewing the extracted entities and the extracted relationships. | 0.938509 |
9,842,161 | 13 | 17 | 13. A system for a user to curate a corpus of a cognitive computing system comprising: a computing system having a processor; a computer-readable memory device which is not a propagating signal per se; and program instructions embodied by the computer-readable memory device which, when executed, cause the processor to perform steps of: producing a parse tree illustration of one or more discrepancies and confidence factors detected between at least a portion of a first document and a second or more documents in a cognitive computing system corpus, wherein the portion and the second or more documents comprise natural language unstructured data, wherein the parse tree illustration comprises a structure of a cluster of documents encapsulating categorized previously-asked questions about the corpus, and wherein the confidence factors are previously-assigned by a cognitive computing system corresponding to the questions and the documents; reporting on a user interface device to a user the parse tree illustration; responsive to receipt of a user selection of an illustrated discrepancy in the parse tree, displaying by a computing system on a user interface device to a user a drill-down dialog which shows at least a text string for the portion of the first document and at least one conflicting text string from the second or more documents, and which provides at least one user-selectable administrative action option for handling the detected discrepancy; and responsive to receipt of a user selection of at least one of the administrative action options, performing by the computing system the administrative action, thereby handling the detected discrepancy to curate the corpus. | 13. A system for a user to curate a corpus of a cognitive computing system comprising: a computing system having a processor; a computer-readable memory device which is not a propagating signal per se; and program instructions embodied by the computer-readable memory device which, when executed, cause the processor to perform steps of: producing a parse tree illustration of one or more discrepancies and confidence factors detected between at least a portion of a first document and a second or more documents in a cognitive computing system corpus, wherein the portion and the second or more documents comprise natural language unstructured data, wherein the parse tree illustration comprises a structure of a cluster of documents encapsulating categorized previously-asked questions about the corpus, and wherein the confidence factors are previously-assigned by a cognitive computing system corresponding to the questions and the documents; reporting on a user interface device to a user the parse tree illustration; responsive to receipt of a user selection of an illustrated discrepancy in the parse tree, displaying by a computing system on a user interface device to a user a drill-down dialog which shows at least a text string for the portion of the first document and at least one conflicting text string from the second or more documents, and which provides at least one user-selectable administrative action option for handling the detected discrepancy; and responsive to receipt of a user selection of at least one of the administrative action options, performing by the computing system the administrative action, thereby handling the detected discrepancy to curate the corpus. 17. The system as set forth in claim 13 wherein the administrative action options comprise one or more actions selected from the group consisting of flagging the first document, removing the first document, replacing the first document, editing the first document, ignoring the discrepancy, flagging the second or more document, removing the second or more document, replacing the second or more document, and editing the second or more document. | 0.501119 |
8,756,234 | 1 | 6 | 1. A computer method, comprising: processing automatically medical text in a medical report within a medical field using a computer, the processing comprising: identifying medical phrases contained within the medical text; extracting the medical phrases from the medical text; determining which of the medical phrases are valued medical phrases, a valued medical phrase includes content having a corresponding value in a lexicon of relevant terminology corresponding to the medical field, the valued medical phrase being either a medical finding or a medical recommendation; reducing each valued medical phrase to one or more medical codes in the medical field; the one or more medical codes being medical identifiers; and rendering in a first group medical codes corresponding to the medical finding; and rendering in a second group separate from the first group medical codes corresponding to the medical recommendation, wherein processing automatically the medical text in the medical report further comprises generating a lexicon-based hierarchical decision tree for the medical field by assigning each valued medical phrase to a location in the lexicon-based hierarchical decision tree. | 1. A computer method, comprising: processing automatically medical text in a medical report within a medical field using a computer, the processing comprising: identifying medical phrases contained within the medical text; extracting the medical phrases from the medical text; determining which of the medical phrases are valued medical phrases, a valued medical phrase includes content having a corresponding value in a lexicon of relevant terminology corresponding to the medical field, the valued medical phrase being either a medical finding or a medical recommendation; reducing each valued medical phrase to one or more medical codes in the medical field; the one or more medical codes being medical identifiers; and rendering in a first group medical codes corresponding to the medical finding; and rendering in a second group separate from the first group medical codes corresponding to the medical recommendation, wherein processing automatically the medical text in the medical report further comprises generating a lexicon-based hierarchical decision tree for the medical field by assigning each valued medical phrase to a location in the lexicon-based hierarchical decision tree. 6. The computer method of claim 1 , wherein processing automatically the medical text within the medical field using the computer comprises processing automatically the medical text within radiology. | 0.873087 |
9,131,019 | 12 | 14 | 12. A method comprising: presenting a plurality of prompts requesting information items associated with data describing characteristics of a user of a social networking system; logging, in a database, a plurality of responses from the user to the plurality of prompts; maintaining a profile for the user, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; obtaining a plurality of prompts associated with one or more information items from the set of unknown information items; determining, for each of the plurality of prompts associated with the one or more information items from the set of unknown information items, a response probability based at least in part on one or a combination of prompts previously presented to the user and the logged plurality of responses from the user, the response probability indicating a likelihood of receiving a response to a prompt when presented; determining a data acquisition value for each of a plurality of the unknown information items in the set of unknown information items, the data acquisition value of an unknown information item based at least in part on a value to the social networking system of associating data with the unknown information item and the determined response probability; selecting an unknown information item from the set of unknown information items based at least in part on the data acquisition values; and selecting a prompt associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more prompts associated with the selected unknown information item. | 12. A method comprising: presenting a plurality of prompts requesting information items associated with data describing characteristics of a user of a social networking system; logging, in a database, a plurality of responses from the user to the plurality of prompts; maintaining a profile for the user, the profile including one or more information items associated with data describing characteristics of the user and a set of unknown information items not associated with data; obtaining a plurality of prompts associated with one or more information items from the set of unknown information items; determining, for each of the plurality of prompts associated with the one or more information items from the set of unknown information items, a response probability based at least in part on one or a combination of prompts previously presented to the user and the logged plurality of responses from the user, the response probability indicating a likelihood of receiving a response to a prompt when presented; determining a data acquisition value for each of a plurality of the unknown information items in the set of unknown information items, the data acquisition value of an unknown information item based at least in part on a value to the social networking system of associating data with the unknown information item and the determined response probability; selecting an unknown information item from the set of unknown information items based at least in part on the data acquisition values; and selecting a prompt associated with the selected unknown information item for presentation to the user based at least in part on the response probabilities of one or more prompts associated with the selected unknown information item. 14. The method of claim 12 , wherein the probability of receiving data associated with the unknown information item is based at least in part on a historical response rate to requests for information by additional users connected to the user. | 0.864502 |
8,887,047 | 29 | 42 | 29. Non-transitory machine readable media that stores executable instructions, which, when executed by the one or more processing devices, are configured to cause the one or more processing devices to perform operations comprising: providing for display on a terminal a learning content input user interface configured to receive learning content; receiving learning content via the learning content input user interface and storing the received learning content in machine readable memory; providing for display on the terminal a framework user interface configured to receive a framework definition, wherein the framework definition defines an order of presentation to a learner with respect to learning content; receiving, independently of the received learning content, a framework definition via the framework user interface and storing the received framework definition in machine readable memory, wherein the framework definition specifies a presentation flow; providing for display on the terminal a style set user interface configured to receive a style definition, wherein the style definition defines an appearance of learning content, wherein the style set user interface enables the user to select from a plurality of protocols, including at least a version of HTML and a non-HTML protocol, which protocol is to be used in packaging rendered merged learning content and framework definition; receiving the style set definition via the style set user interface and storing the received style set definition in machine readable memory; providing for display on the terminal a protocol user interface configured to receive a protocol selection; receiving, independently of the received learning content, the protocol selection via the protocol user interface; receiving from the user a publishing instruction via a publishing user interface; at least partly in response to the received publishing instruction, accessing from machine readable memory the received learning content, the received framework definition, the received style set definition, and the received protocol selection: merging the received learning content and the received framework definition; rendering the merged the received learning content and the received framework definition in accordance with the received style set definition; and packaging the rendered merged learning content and framework definition in accordance with the selected protocol to provide a published learning document. | 29. Non-transitory machine readable media that stores executable instructions, which, when executed by the one or more processing devices, are configured to cause the one or more processing devices to perform operations comprising: providing for display on a terminal a learning content input user interface configured to receive learning content; receiving learning content via the learning content input user interface and storing the received learning content in machine readable memory; providing for display on the terminal a framework user interface configured to receive a framework definition, wherein the framework definition defines an order of presentation to a learner with respect to learning content; receiving, independently of the received learning content, a framework definition via the framework user interface and storing the received framework definition in machine readable memory, wherein the framework definition specifies a presentation flow; providing for display on the terminal a style set user interface configured to receive a style definition, wherein the style definition defines an appearance of learning content, wherein the style set user interface enables the user to select from a plurality of protocols, including at least a version of HTML and a non-HTML protocol, which protocol is to be used in packaging rendered merged learning content and framework definition; receiving the style set definition via the style set user interface and storing the received style set definition in machine readable memory; providing for display on the terminal a protocol user interface configured to receive a protocol selection; receiving, independently of the received learning content, the protocol selection via the protocol user interface; receiving from the user a publishing instruction via a publishing user interface; at least partly in response to the received publishing instruction, accessing from machine readable memory the received learning content, the received framework definition, the received style set definition, and the received protocol selection: merging the received learning content and the received framework definition; rendering the merged the received learning content and the received framework definition in accordance with the received style set definition; and packaging the rendered merged learning content and framework definition in accordance with the selected protocol to provide a published learning document. 42. The media as defined in claim 29 , the operations further comprising enabling the user to define at least a styles console, a framework console, and learning content console. | 0.874824 |
9,762,618 | 11 | 17 | 11. A non-transitory computer readable storage medium configured to store instructions, the instructions when executed by a processor cause the processor to: receive, at an authorizing Domain Name System (DNS) system, a redirected target domain DNS query from a receiving email system, the redirected target domain DNS query generated by the receiving email system based on parsing Sender Policy Framework (SPF) macro statements in an email domain validation record generated by an email domain owner system and published as a DNS TXT record at the DNS server of the email domain owner system, the redirected target domain DNS query including identifying information of a delivering email system, the identifying information comprising at least one of an extended HELO (EHLO) name and an (Internet Protocol) IP address of the delivering email system; extract the identifying information from the redirected target domain DNS query; determine an identify of the delivering email system from a list of delivering organizations based on the extracted identifying information by accessing a database that associates at least one of an EHLO name and an IP address with delivering organizations to determine the identity of the delivering email system based on the identifying information; generate, in response to a determination that the identified delivering email system is authorized to deliver email on behalf of the email domain owner system, a target validation record, the target validation record including one or more SPF rules indicating that the delivering email system is an authorized sender of email for the email domain owner system; and transmit the target validation record to the receiving email system. | 11. A non-transitory computer readable storage medium configured to store instructions, the instructions when executed by a processor cause the processor to: receive, at an authorizing Domain Name System (DNS) system, a redirected target domain DNS query from a receiving email system, the redirected target domain DNS query generated by the receiving email system based on parsing Sender Policy Framework (SPF) macro statements in an email domain validation record generated by an email domain owner system and published as a DNS TXT record at the DNS server of the email domain owner system, the redirected target domain DNS query including identifying information of a delivering email system, the identifying information comprising at least one of an extended HELO (EHLO) name and an (Internet Protocol) IP address of the delivering email system; extract the identifying information from the redirected target domain DNS query; determine an identify of the delivering email system from a list of delivering organizations based on the extracted identifying information by accessing a database that associates at least one of an EHLO name and an IP address with delivering organizations to determine the identity of the delivering email system based on the identifying information; generate, in response to a determination that the identified delivering email system is authorized to deliver email on behalf of the email domain owner system, a target validation record, the target validation record including one or more SPF rules indicating that the delivering email system is an authorized sender of email for the email domain owner system; and transmit the target validation record to the receiving email system. 17. The computer readable storage medium of claim 11 , configured to store further instructions to generate the target validation record, that when executed by the processor, causes the processor to: access a records database that stores one or more target validation records for authorized delivering email systems, each target validation record including one or more rules indicating that a delivering email system is an authorized sender for the email domain owner system. | 0.6875 |
8,775,468 | 3 | 4 | 3. The method of claim 2 , further comprising: prior to the storing, compiling each generated value expression. | 3. The method of claim 2 , further comprising: prior to the storing, compiling each generated value expression. 4. The method of claim 3 , wherein the compiling further comprises: receiving a query from the user, wherein the query requests access to a node in the structured document; executing the query; evaluating the value expression corresponding to the path associated with the requested node; displaying data associated with the requested node if the value expression grants access to the user; and hiding data associated with the requested node if the value expression denies access to the user. | 0.891993 |
9,251,246 | 7 | 9 | 7. A computer program product for defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: receiving a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving a data stream of non-dimensional data objects; applying a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects, a probability that one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; parsing the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; calculating a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. | 7. A computer program product for defining multiple context-based conformed dimensional data gravity wells on a context-based conformed dimensional data gravity wells membrane, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: receiving a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; associating one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; receiving a data stream of non-dimensional data objects; applying a dimension object to one of the non-dimensional data objects to define a conformed dimensional object; parsing the conformed dimensional object into a dimensional n-tuple, wherein the dimensional n-tuple comprises a pointer to one of the non-dimensional data objects, a probability that one of the non-dimensional data objects is uncorrupted, and a weighting factor of importance of the conformed dimensional object; parsing the synthetic context-based object into a context-based n-tuple, wherein the context-based n-tuple comprises a pointer to one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; calculating a virtual mass of a parsed synthetic context-based object based on a probability that the non-contextual data object has been associated with a correct context object; calculating a virtual mass of a parsed conformed dimensional object based on a probability that one of the non-dimensional data objects has come from a data source whose data has been predetermined to be appropriate for storage in a particular dimensional data gravity well; creating multiple context-based conformed dimensional data gravity well frameworks on a context-based conformed dimensional data gravity wells membrane, wherein each of the multiple context-based conformed dimensional data gravity well frameworks comprises at least one non-contextual data object, at least one context object, and at least one dimension object, and wherein the context-based conformed dimensional data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based conformed dimensional data gravity wells; transmitting multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects to the context-based conformed dimensional data gravity wells membrane; and defining multiple context-based conformed dimensional data gravity wells according to the virtual mass of multiple parsed synthetic context-based objects and the virtual mass of multiple parsed conformed dimensional objects that are pulled into each of the context-based conformed dimensional data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects and multiple parsed conformed dimensional objects is pulled into a particular context-based conformed dimensional data gravity well in response to values from its n-tuple matching said at least one context object or said at least one dimension object in said particular context-based conformed dimensional data gravity well. 9. The computer program product of claim 7 , wherein a particular data object is either a conformed dimensional object or a synthetic context-based object, and wherein the computer program product further comprises program code that is readable and executable by the processor to: determine a likelihood that a particular data object is pulled into an appropriate context-based conformed dimensional data gravity well according to a Bayesian probability formula of: P ( A ❘ B ) = P ( B ❘ A ) P ( A ) P ( B ) where: P(A|B) is the probability that a particular data object will be an appropriate populator of a particular context-based conformed dimensional data gravity well (A) given that (|) a predefined amount of conformed dimensional objects are applied to a data object in a conformed dimensional object or a predefined amount of context objects are applied to a data object in a synthetic context-based object (B); P(B|A) is a probability that a predefined amount of context-based or conformed dimensional objects are applied to the data object in the context-based or conformed dimensional object (B) given that (|) the data object is assigned to the particular context-based conformed dimensional data gravity well (A); P(A) is a probability that the particular object will be the appropriate populator of the particular context-based conformed dimensional data gravity well regardless of any other information; and P(B) is a probability that the particular object will have the predefined amount of context-based or conformed dimensional objects regardless of any other information. | 0.571008 |
9,021,008 | 21 | 24 | 21. A non-transitory computer readable medium having instructions stored thereon, which when executed on a computer system, perform a method for host computing devices, the method comprising: obtaining an instruction for execution of executable code, the executable code configured to elicit actions on a host computing device enabling evaluation of an operation of the host computing device; accessing the executable code from an executable code data store implemented in a non-volatile storage device; storing restoration information for the host computing device enabling restoration of the host computing device to a state prior to the execution of the executable code; causing execution of the executable code; determining whether the host computing device is to be restored to a state prior to the execution of the executable code based on a state after execution of the executable code; restoring the host computing device to a prior state using the restoration information in response to determining that the host computing device is to be restored to the state prior to the execution of the executable code without receiving a command from a user to restore the host computing device; obtaining information related to the execution of the executable code, the information comprising log information collected during execution of the executable code; and transmitting at least a portion of the information related to the execution of the executable code, wherein the executable code is further configured to elicit: a deletion of at least a percentage of data packets between the host computing device and one or more network components, a modification of communication channels between the host computing device and the one or more network components, and a reboot of the host computing device and the one or more network components. | 21. A non-transitory computer readable medium having instructions stored thereon, which when executed on a computer system, perform a method for host computing devices, the method comprising: obtaining an instruction for execution of executable code, the executable code configured to elicit actions on a host computing device enabling evaluation of an operation of the host computing device; accessing the executable code from an executable code data store implemented in a non-volatile storage device; storing restoration information for the host computing device enabling restoration of the host computing device to a state prior to the execution of the executable code; causing execution of the executable code; determining whether the host computing device is to be restored to a state prior to the execution of the executable code based on a state after execution of the executable code; restoring the host computing device to a prior state using the restoration information in response to determining that the host computing device is to be restored to the state prior to the execution of the executable code without receiving a command from a user to restore the host computing device; obtaining information related to the execution of the executable code, the information comprising log information collected during execution of the executable code; and transmitting at least a portion of the information related to the execution of the executable code, wherein the executable code is further configured to elicit: a deletion of at least a percentage of data packets between the host computing device and one or more network components, a modification of communication channels between the host computing device and the one or more network components, and a reboot of the host computing device and the one or more network components. 24. The non-transitory computer readable medium as recited in claim 21 , wherein the executable code is further configured to elicit the prevention of data packets between the host computing device and the one or more network components. | 0.943598 |
9,836,503 | 11 | 18 | 11. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a set of acts, the set of acts comprising: receiving a SQL database query language statement on a SQL database, wherein the SQL database query language statement comprises one or more SQL query clauses and a table function that transforms at least one SPARQL endpoint into a row source for the SQL database to integrate local relational data with non-local RDF data retrieved from the one or more SPARQL endpoints, and a SPARQL query string and at least one SPARQL endpoint of one or more SPARQL endpoints are embedded in the table function of SQL database query language statement; executing the SQL database query language statement including the table function on the SQL database to transform the at least one SPARQL endpoint into a row source for the SQL database, wherein during execution of the SQL database query language statement on the SQL database, executing the one or more SQL query clauses on the SQL database; sending at least the SPARQL query string embedded in the SQL database query language statement to the at least one SPARQL endpoint that is embedded in the SQL database query language statement, wherein the at least one SPARQL endpoint is identified by parsing at least the table function in the SQL database query language statement that has been executed; receiving query results from the at least one SPARQL endpoint, at least a portion of the query results corresponding to the non-local RDF data; converting the non-local RDF data into a relational data format to generate converted RDF data; and combining the converted RDF data with relational data from a local relational database. | 11. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a set of acts, the set of acts comprising: receiving a SQL database query language statement on a SQL database, wherein the SQL database query language statement comprises one or more SQL query clauses and a table function that transforms at least one SPARQL endpoint into a row source for the SQL database to integrate local relational data with non-local RDF data retrieved from the one or more SPARQL endpoints, and a SPARQL query string and at least one SPARQL endpoint of one or more SPARQL endpoints are embedded in the table function of SQL database query language statement; executing the SQL database query language statement including the table function on the SQL database to transform the at least one SPARQL endpoint into a row source for the SQL database, wherein during execution of the SQL database query language statement on the SQL database, executing the one or more SQL query clauses on the SQL database; sending at least the SPARQL query string embedded in the SQL database query language statement to the at least one SPARQL endpoint that is embedded in the SQL database query language statement, wherein the at least one SPARQL endpoint is identified by parsing at least the table function in the SQL database query language statement that has been executed; receiving query results from the at least one SPARQL endpoint, at least a portion of the query results corresponding to the non-local RDF data; converting the non-local RDF data into a relational data format to generate converted RDF data; and combining the converted RDF data with relational data from a local relational database. 18. The computer program product of claim 11 , further comprising instructions which, when executed by the processor, further cause the processor to execute the set of acts, and the set of acts further comprising parsing the SQL database query language statement to identify a proxy. | 0.583824 |
7,568,171 | 25 | 38 | 25. A computer program product for posing a computer-animated three-dimensional model in a three-dimensional scene space, the model including a plurality of elements, the computer program product comprising a computer-readable medium containing computer program code for performing operations comprising: receiving a stroke drawn in a two-dimensional screen space by a user, the stroke having a starting point, an ending point, and a direction; associating the stroke with an element of the model, wherein the element has an axis of finite length that defines a position of the element in scene space; defining a first projection line in scene space which extends from a camera position and passes through the starting point of the stroke; defining a second projection line in scene space which extends from the camera position and passes through the ending point of the stroke; moving the element in the scene space based on the stroke, wherein the amount of the movement of the element in the scene space is determined by a three dimensional transformation which positions the element axis as intersecting both the first projection line and the second projection line, and the direction of the movement of the element in the scene space is determined based on the direction of the stroke; and displaying the moved element in a three-dimensional scene space. | 25. A computer program product for posing a computer-animated three-dimensional model in a three-dimensional scene space, the model including a plurality of elements, the computer program product comprising a computer-readable medium containing computer program code for performing operations comprising: receiving a stroke drawn in a two-dimensional screen space by a user, the stroke having a starting point, an ending point, and a direction; associating the stroke with an element of the model, wherein the element has an axis of finite length that defines a position of the element in scene space; defining a first projection line in scene space which extends from a camera position and passes through the starting point of the stroke; defining a second projection line in scene space which extends from the camera position and passes through the ending point of the stroke; moving the element in the scene space based on the stroke, wherein the amount of the movement of the element in the scene space is determined by a three dimensional transformation which positions the element axis as intersecting both the first projection line and the second projection line, and the direction of the movement of the element in the scene space is determined based on the direction of the stroke; and displaying the moved element in a three-dimensional scene space. 38. The computer program product of claim 25 , the computer-readable medium further containing computer program code for performing the operations: receiving a placement stroke to place the model in the scene space, the model including a placement module having a number of reference points; and placing the model at a location in the scene space at which a projection of at least some of the reference points onto screen space correspond to the stroke. | 0.501101 |
9,779,363 | 1 | 4 | 1. A computer-implemented method of disambiguating personal names, the method comprising: for each of multiple personal names, categorizing the personal name as being: famous; or non-famous and: common; or uncommon; and using the computer to: extract a first personal name identified in an electronic content item, wherein multiple people have the first personal name; if the first personal name is non-famous and common, execute a first model to identify, among the multiple people, one person to whom the electronic content item refers; if the first personal name is non-famous and uncommon, execute a second model, different from the first model, to identify the one person; and transmit the electronic content item to a user that requested content items that reference the one person. | 1. A computer-implemented method of disambiguating personal names, the method comprising: for each of multiple personal names, categorizing the personal name as being: famous; or non-famous and: common; or uncommon; and using the computer to: extract a first personal name identified in an electronic content item, wherein multiple people have the first personal name; if the first personal name is non-famous and common, execute a first model to identify, among the multiple people, one person to whom the electronic content item refers; if the first personal name is non-famous and uncommon, execute a second model, different from the first model, to identify the one person; and transmit the electronic content item to a user that requested content items that reference the one person. 4. The method of claim 1 , wherein executing a model comprises, for each person in the multiple people: generating a corresponding feature vector comprising: a set of name features derived from occurrences of the personal name in the electronic content item; and a set of affiliation features derived from occurrences of names of affiliations of the person in the electronic content item; applying the model to the person's corresponding feature vector; and receiving as output from the model an indication as to whether the personal name refers to the person. | 0.565891 |
8,346,557 | 21 | 22 | 21. A system comprising: a memory; and a computing device configured to: load an electronic representation of a document; receive a user-based selection of a first portion of words in the document, at least of portion of the document being displayed in a user interface on a display device, the document being pre-associated with a first voice model; apply, in response to the user-based selection of the first portion of words, a first set of indicia to the user-selected first portion of words in the document; and overwrite the pre-association of the first voice model, by the one or more computers, with a second, different voice model for the first portion of words. | 21. A system comprising: a memory; and a computing device configured to: load an electronic representation of a document; receive a user-based selection of a first portion of words in the document, at least of portion of the document being displayed in a user interface on a display device, the document being pre-associated with a first voice model; apply, in response to the user-based selection of the first portion of words, a first set of indicia to the user-selected first portion of words in the document; and overwrite the pre-association of the first voice model, by the one or more computers, with a second, different voice model for the first portion of words. 22. The system of claim 21 , wherein the computing device is further configured: narrate the words in the first portion of words using the second voice model and narrate at least some of the other words in the document using the first voice model. | 0.751008 |
8,006,268 | 1 | 2 | 1. A method implemented by a client device having a processor executing instructions stored in computer-readable storage media, the method comprising: receiving video signals broadcast on a multiplexed channel of a broadcast network; extracting from the received video signals a closed captioning stream of textual data; creating an active list comprising a plurality of first search terms by presenting a plurality of questions at a user interface to be answered by a viewer to develop the first search terms for creating the active list; creating a passive list comprising a plurality of second search terms by: monitoring closed captioning textual data during receipt of one or more previously received closed captioning streams of textual data of received video signals that the viewer has viewed or recorded, extracting words and phrases as potential search terms from the closed captioning textual data, and automatically selecting the plurality of second search terms from the potential search terms based on a recentness and a frequency of occurrence of the extracted words and phrases; searching the stream of textual data for occurrences of textual data matching one or more of the first search terms in the active list or one or more of the second search terms in the passive list, the searching comprising: storing content programming corresponding to the received video signals in a buffer; comparing, by the processor, the closed captioning stream of textual data to both the active list and the passive list; determining whether a number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds a threshold number, wherein the number of matches is based on a combination, over a period of time, of a number of hits with respect to the first search terms in the active list and a number of hits with respect to the second search terms in the passive list; and applying a greater weight to the first search terms in the active list than a weight applied to the second search terms in the passive list when counting the number of matches; when the number of matches of the first search terms of the active list and the second search terms of the passive list does not exceed the threshold number after a predetermined period of time, ceasing to search a first closed captioning stream of textual data from a first channel before an end of the first closed captioning stream is reached, deleting the corresponding content programming from the buffer, and searching instead a second closed captioning stream of textual data from a second channel; and notifying the viewer when the number of matches exceeds the threshold number that content programming determined to be of interest to the viewer has been located. | 1. A method implemented by a client device having a processor executing instructions stored in computer-readable storage media, the method comprising: receiving video signals broadcast on a multiplexed channel of a broadcast network; extracting from the received video signals a closed captioning stream of textual data; creating an active list comprising a plurality of first search terms by presenting a plurality of questions at a user interface to be answered by a viewer to develop the first search terms for creating the active list; creating a passive list comprising a plurality of second search terms by: monitoring closed captioning textual data during receipt of one or more previously received closed captioning streams of textual data of received video signals that the viewer has viewed or recorded, extracting words and phrases as potential search terms from the closed captioning textual data, and automatically selecting the plurality of second search terms from the potential search terms based on a recentness and a frequency of occurrence of the extracted words and phrases; searching the stream of textual data for occurrences of textual data matching one or more of the first search terms in the active list or one or more of the second search terms in the passive list, the searching comprising: storing content programming corresponding to the received video signals in a buffer; comparing, by the processor, the closed captioning stream of textual data to both the active list and the passive list; determining whether a number of matches of the first search terms of the active list and the second search terms of the passive list with the textual data exceeds a threshold number, wherein the number of matches is based on a combination, over a period of time, of a number of hits with respect to the first search terms in the active list and a number of hits with respect to the second search terms in the passive list; and applying a greater weight to the first search terms in the active list than a weight applied to the second search terms in the passive list when counting the number of matches; when the number of matches of the first search terms of the active list and the second search terms of the passive list does not exceed the threshold number after a predetermined period of time, ceasing to search a first closed captioning stream of textual data from a first channel before an end of the first closed captioning stream is reached, deleting the corresponding content programming from the buffer, and searching instead a second closed captioning stream of textual data from a second channel; and notifying the viewer when the number of matches exceeds the threshold number that content programming determined to be of interest to the viewer has been located. 2. The method according to claim 1 , wherein creating the active list is further based on a word omission list provided by a third party. | 0.920901 |
9,047,642 | 1 | 2 | 1. A system to facilitate conducting a social choice survey of members of an online community associated with a computer network, the system comprising: a computer accessible to the computer network, the computer defining a social choice administrator server, the social choice administrator server having a memory coupled to a processor; operational instructions stored in the memory of the social choice administrator server that, when executed by the processor of the social choice administrator server, cause the social choice administrator server to selectively perform the operations of: generate a first user interface on a computer display associated with a survey administrator, prompt the survey administrator with the first user interface to define the social choice survey type selected from a slider bar survey, a yes/no survey, a drag and drop survey, and a select one survey, receive the social choice survey defined by the survey administrator with the first user interface, prompt the survey administrator with the first user interface to define a group of participants from the members of the online community to participate in the social choice survey, wherein the group of participants consists of friends of a single user on a social media website, receive the group of participants defined by the survey administrator with the first user interface, generate a second user interface on a computer display associated with each of the participants, the second user interface providing an interactive portion to receive a participant's response to the social choice survey and being posted on each participant's social media account on the social media website, receive and register each of the participants' responses to the social choice survey collected with the second user interface, prompt the survey administrator to view and to select a progress of the social choice survey, in response to the selection of the progress of the social choice survey, generate a display of the progress of the social choice survey, including at least one of a list of participants who have participated in the social choice survey and a list of participants who have not participated in the social choice survey, amalgamate the participants' responses to the social choice survey to thereby determine a result of the social choice survey, and show the result of the social choice survey on a computer display of the survey administrator. | 1. A system to facilitate conducting a social choice survey of members of an online community associated with a computer network, the system comprising: a computer accessible to the computer network, the computer defining a social choice administrator server, the social choice administrator server having a memory coupled to a processor; operational instructions stored in the memory of the social choice administrator server that, when executed by the processor of the social choice administrator server, cause the social choice administrator server to selectively perform the operations of: generate a first user interface on a computer display associated with a survey administrator, prompt the survey administrator with the first user interface to define the social choice survey type selected from a slider bar survey, a yes/no survey, a drag and drop survey, and a select one survey, receive the social choice survey defined by the survey administrator with the first user interface, prompt the survey administrator with the first user interface to define a group of participants from the members of the online community to participate in the social choice survey, wherein the group of participants consists of friends of a single user on a social media website, receive the group of participants defined by the survey administrator with the first user interface, generate a second user interface on a computer display associated with each of the participants, the second user interface providing an interactive portion to receive a participant's response to the social choice survey and being posted on each participant's social media account on the social media website, receive and register each of the participants' responses to the social choice survey collected with the second user interface, prompt the survey administrator to view and to select a progress of the social choice survey, in response to the selection of the progress of the social choice survey, generate a display of the progress of the social choice survey, including at least one of a list of participants who have participated in the social choice survey and a list of participants who have not participated in the social choice survey, amalgamate the participants' responses to the social choice survey to thereby determine a result of the social choice survey, and show the result of the social choice survey on a computer display of the survey administrator. 2. The system of claim 1 , wherein the operational instructions, that, when executed by the processor, cause the social choice administrator server to further perform the operations of: sending an electronic message over the computer network to each of the participants in the group of participants, the electronic message indicating that the participant has been selected to participate in the social choice survey. | 0.501199 |
7,664,778 | 15 | 16 | 15. The medium of claim 14 , wherein the computer program, when executed, further performs the method comprising: identifying a portion of the filtered statements as resource intensive statements. | 15. The medium of claim 14 , wherein the computer program, when executed, further performs the method comprising: identifying a portion of the filtered statements as resource intensive statements. 16. The medium of claim 15 , wherein the computer program, when executed, further performs the method comprising: storing the resource intensive statements and the performance information for each resource intensive statement as a second persistent database object. | 0.93226 |
8,160,873 | 32 | 33 | 32. The apparatus of claim 29 , wherein said signal-to-noise ratio calculator determines a vector of speech power estimates from said first vector of frequency spectral speech components, said estimated vector of frequency spectral noise components and said vector of noise suppression coefficients, and wherein said suppression coefficient corrector calculates a vector of first section correction factors by using said vector of estimated frequency spectral noise components and said a vector of speech power estimates and said a vector of speech power estimates, combines the vector of the first section correction factors with a vector of second section correction factors to product a vector of combined correction factors, and corrects said vector of noise suppression coefficients with said vector of combined correction factors. | 32. The apparatus of claim 29 , wherein said signal-to-noise ratio calculator determines a vector of speech power estimates from said first vector of frequency spectral speech components, said estimated vector of frequency spectral noise components and said vector of noise suppression coefficients, and wherein said suppression coefficient corrector calculates a vector of first section correction factors by using said vector of estimated frequency spectral noise components and said a vector of speech power estimates and said a vector of speech power estimates, combines the vector of the first section correction factors with a vector of second section correction factors to product a vector of combined correction factors, and corrects said vector of noise suppression coefficients with said vector of combined correction factors. 33. The apparatus of claim 32 , wherein said suppression coefficient corrector combines said vector of first correction factors and said vector of second correction factors according to pF V +(1−p)F U , where p represents said speech-versus-noise relationship and F U and F V represent said first and second correction factors, respectively. | 0.842567 |
9,555,710 | 1 | 6 | 1. A system for filtering data, comprising: a computing device including a processor and a memory storage device, the processor being configured to execute a query module operatively coupled to a data module and to a display module; wherein the data module is configured to access vehicle data in a database according to a query input; wherein the display module is operatively coupled to the data module and is configured to display the vehicle data in a graphical user interface; and wherein the query module is operatively coupled to the data module and to the display module, and the query module is configured to generate the query input according to an interactive list of filter statements, each filter statement in the interactive list of filter statements being selectable from a group of filter types, the group of filter types being configured to dynamically update in response to at least one selection from the group of filter types. | 1. A system for filtering data, comprising: a computing device including a processor and a memory storage device, the processor being configured to execute a query module operatively coupled to a data module and to a display module; wherein the data module is configured to access vehicle data in a database according to a query input; wherein the display module is operatively coupled to the data module and is configured to display the vehicle data in a graphical user interface; and wherein the query module is operatively coupled to the data module and to the display module, and the query module is configured to generate the query input according to an interactive list of filter statements, each filter statement in the interactive list of filter statements being selectable from a group of filter types, the group of filter types being configured to dynamically update in response to at least one selection from the group of filter types. 6. The system as recited in claim 1 , wherein the graphical user interface is operable to cause the interactive list of filter statements to update in response to a user interaction. | 0.862121 |
9,811,750 | 13 | 14 | 13. The electronic device of claim 12 , wherein the controller is further configured to recognize the character information using a character recognizer, wherein the character recognizer is determined according to the pre-recognized information of the first area. | 13. The electronic device of claim 12 , wherein the controller is further configured to recognize the character information using a character recognizer, wherein the character recognizer is determined according to the pre-recognized information of the first area. 14. The electronic device of claim 13 , wherein the character recognizer for the first area is different from a character recognizer for the second area, and wherein the second area has different pre-recognized information from the first character. | 0.865655 |
9,232,205 | 8 | 9 | 8. The information processing device according to claim 1 , wherein the learning means performs dimension reduction to reduce a dimension of the image feature amount and the text feature amount, and learns the annotation model by using the multi-stream including the image feature amount and the text feature amount after the dimension reduction as the annotation sequence. | 8. The information processing device according to claim 1 , wherein the learning means performs dimension reduction to reduce a dimension of the image feature amount and the text feature amount, and learns the annotation model by using the multi-stream including the image feature amount and the text feature amount after the dimension reduction as the annotation sequence. 9. The information processing device according to claim 8 , wherein the learning means obtains basis space data of a basis space for image of which dimension is lower than the dimension of the image feature amount for mapping the image feature amount by using the image feature amount, performs the dimension reduction of the image feature amount based on the basis space data of the basis space for image, obtains basis space data of a basis space for text of which dimension is lower than the dimension of the text feature amount for mapping the text feature amount by using the text feature amount, and performs the dimension reduction of the text feature amount based on the basis space data of the basis space for text. | 0.873912 |
8,788,566 | 1 | 7 | 1. A method for enforcing context model based Service-Oriented Architecture (SOA) policies, comprising: gathering, via a policy engine device, instance documents related to policy enforcement according to a business requirement, where the instance documents are instantiated from corresponding schema documents; generating an instantiated context model comprising references to the gathered instance documents from a context model definition; generating a policy set to be enforced via the instantiated context model according to the gathered instance documents; determining an enforcement sequence of policies in the policy set; applying the policies to the instantiated context model according to the enforcement sequence; and providing context model-based forward chaining, comprising: determining whether the instantiated context model should be updated; if the instantiated context model should be updated: updating the instantiated context model with at least one updated instance document comprising: executing an updating operation to create the at least one updated instance document; detecting and resolving a conflict caused by the updating operation; generating the updated instantiated context model according to the at least one updated instance document and the instantiated context model; and re-applying the policies to only the at least one updated instance document within the updated instantiated context model according to the enforcement sequence. | 1. A method for enforcing context model based Service-Oriented Architecture (SOA) policies, comprising: gathering, via a policy engine device, instance documents related to policy enforcement according to a business requirement, where the instance documents are instantiated from corresponding schema documents; generating an instantiated context model comprising references to the gathered instance documents from a context model definition; generating a policy set to be enforced via the instantiated context model according to the gathered instance documents; determining an enforcement sequence of policies in the policy set; applying the policies to the instantiated context model according to the enforcement sequence; and providing context model-based forward chaining, comprising: determining whether the instantiated context model should be updated; if the instantiated context model should be updated: updating the instantiated context model with at least one updated instance document comprising: executing an updating operation to create the at least one updated instance document; detecting and resolving a conflict caused by the updating operation; generating the updated instantiated context model according to the at least one updated instance document and the instantiated context model; and re-applying the policies to only the at least one updated instance document within the updated instantiated context model according to the enforcement sequence. 7. The method according to claim 1 , where generating a policy set to be enforced via the instantiated context model according to the gathered instance documents comprises: determining policies related to the gathered instance documents; and collecting the determined policies to generate the policy set. | 0.853423 |
8,554,541 | 1 | 11 | 1. A virtual pet system, comprising: a virtual pet client device including a processor coupled to a memory storing instructions for execution by the processor and a question and answer (Q&A) server device including a processor coupled to a memory storing instructions for execution by the processor, wherein the virtual pet client device is to receive a sentence in natural language and send the sentence and an ID of a pet owner to the Q&A server device; the Q&A server device is to receive the sentence in natural language, process the sentence through natural language comprehension, obtain language characteristics of the pet owner from a pet owner language information base according to the ID of the pet owner, generate an answer in natural language based on a result of natural language comprehensions, reasoning knowledge, and the language characteristics of the pet owner, and send the answer in natural language to the virtual pet client device; wherein the language characteristics of the pet owner include language tips and expression manners. | 1. A virtual pet system, comprising: a virtual pet client device including a processor coupled to a memory storing instructions for execution by the processor and a question and answer (Q&A) server device including a processor coupled to a memory storing instructions for execution by the processor, wherein the virtual pet client device is to receive a sentence in natural language and send the sentence and an ID of a pet owner to the Q&A server device; the Q&A server device is to receive the sentence in natural language, process the sentence through natural language comprehension, obtain language characteristics of the pet owner from a pet owner language information base according to the ID of the pet owner, generate an answer in natural language based on a result of natural language comprehensions, reasoning knowledge, and the language characteristics of the pet owner, and send the answer in natural language to the virtual pet client device; wherein the language characteristics of the pet owner include language tips and expression manners. 11. The virtual pet system of claim 1 , wherein the virtual pet client device is included in an instant messenger, a mobile communication terminal, a fixed communication terminal or a network interface. | 0.86693 |
8,429,157 | 12 | 16 | 12. The system of claim 10 , further comprising: one or more web graph machines having stored thereon a web graph, the one or more web graph machines coupled with the search engine, wherein the web graph contains a plurality of interlinked web documents each represented by a node (u 1 , u 2 , . . . u n ); and wherein the search engine retrieves values of one or more operators from the one or more web graph machines based on the relative linking within the web graph of the one or more organic search results, the plurality of sponsored search results, and any of the plurality of web documents, each of which corresponds to a node in the web graph. | 12. The system of claim 10 , further comprising: one or more web graph machines having stored thereon a web graph, the one or more web graph machines coupled with the search engine, wherein the web graph contains a plurality of interlinked web documents each represented by a node (u 1 , u 2 , . . . u n ); and wherein the search engine retrieves values of one or more operators from the one or more web graph machines based on the relative linking within the web graph of the one or more organic search results, the plurality of sponsored search results, and any of the plurality of web documents, each of which corresponds to a node in the web graph. 16. The system of claim 12 , wherein the operator comprises NumPaths, which is a function, f(u 1 ,u 2 ), that provides a number of distinct paths between the nodes u 1 and u 2 . | 0.92716 |
7,565,630 | 19 | 20 | 19. The method of claim 1 , wherein ranking the set of documents comprises: ranking the set of documents in response to a degree of influence of the search customization profile. | 19. The method of claim 1 , wherein ranking the set of documents comprises: ranking the set of documents in response to a degree of influence of the search customization profile. 20. The method of claim 19 , wherein ranking the set of documents comprises: weighting an information retrieval score of each document by the degree of influence of the search customization profile. | 0.943654 |
8,296,279 | 1 | 26 | 1. A computer-implemented method, comprising: identifying a search query comprising one or more search terms; identifying an index for a word, wherein the word or a substring of the word matches one of the one or more search terms of the search query, and wherein the index comprises: one or more substrings of the word, wherein each substring includes one or more but not all characters included in the word; one or more inclusive strings corresponding to the one or more substrings, each of the one or more inclusive strings comprising the corresponding substring and at least one more character included in the word; and two or more word objects, wherein each of the one or more substrings correspond to at least one of the two or more word objects, and the two or more word objects identify content that includes at least one substring of the word; and using the index to identify one or more search results for the search query based on the two or more word objects; wherein the word object is a location of a web page in which the word occurs. | 1. A computer-implemented method, comprising: identifying a search query comprising one or more search terms; identifying an index for a word, wherein the word or a substring of the word matches one of the one or more search terms of the search query, and wherein the index comprises: one or more substrings of the word, wherein each substring includes one or more but not all characters included in the word; one or more inclusive strings corresponding to the one or more substrings, each of the one or more inclusive strings comprising the corresponding substring and at least one more character included in the word; and two or more word objects, wherein each of the one or more substrings correspond to at least one of the two or more word objects, and the two or more word objects identify content that includes at least one substring of the word; and using the index to identify one or more search results for the search query based on the two or more word objects; wherein the word object is a location of a web page in which the word occurs. 26. The method of claim 1 , wherein: the one or more substrings comprises a plurality of substrings and the two or more word objects comprise a plurality of word objects; the one search term matches a first substring of the plurality of substrings of the word; and the one or more search results include content identified by one or more word objects of the plurality of word objects, and the one or more word objects correspond to the first substring and one or more substrings that match the one or more inclusive strings that correspond to the first substring. | 0.500887 |
8,943,481 | 16 | 18 | 16. An apparatus comprising: one or more data processors; and a memory, coupled to the processor that includes code stored therein and executable by the one or more first data processors to configure a computer system into a machine to: obtain a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; perform a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; perform a second transformation of the framework to generate a first presentation style for the first grammar level; obtain the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and apply the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application. | 16. An apparatus comprising: one or more data processors; and a memory, coupled to the processor that includes code stored therein and executable by the one or more first data processors to configure a computer system into a machine to: obtain a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to a user interface application, wherein the user interface application is incompatible with the first grammar level; perform a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; perform a second transformation of the framework to generate a first presentation style for the first grammar level; obtain the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and apply the first set of rules and the first presentation style to the binding specification to generate output binding specifications in a second grammar level compatible with the user interface application. 18. The computer readable medium of claim 16 , wherein the first transformation is in accordance with a third presentation style. | 0.835459 |
7,606,428 | 2 | 5 | 2. The computer readable medium of claim 1 , wherein the diTexture element in the depthimage node schema defines an SFDepthTextureNode node schema including PointTexture and SimpleTexture as elements. | 2. The computer readable medium of claim 1 , wherein the diTexture element in the depthimage node schema defines an SFDepthTextureNode node schema including PointTexture and SimpleTexture as elements. 5. The computer readable medium of claim 2 , wherein the XMT schema further comprises an octreeimage node schema, which defines at least one of octree, octreeResolution, and voxelImageIndex as an attribute name and defines images as an element including SFDepthImageNodeType as a node group, wherein attribute types defined in the octreeimage node schema include SFInt32, MFInt32, and MFInt32, respectively. | 0.870629 |
10,061,985 | 1 | 6 | 1. A method comprising: by one or more computing devices, accessing a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; by one or more computing devices, accessing a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; by one or more computing devices, accessing a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; by one or more computing devices, determining a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and by one or more computing devices, determining a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object. | 1. A method comprising: by one or more computing devices, accessing a first feature vector representing a video-content object corresponding to a node in a social graph of a social-networking system, wherein: the video-content object comprises frames and audio and is associated with text; the first feature vector is based on one or more of the frames of the video-content object; and the social graph comprises a plurality of nodes and edges connecting the nodes; by one or more computing devices, accessing a second feature vector representing the video-content object, wherein the second feature vector is based on at least some of the text; by one or more computing devices, accessing a third feature vector representing the video-content object, wherein the third feature vector is based on one or more portions of the audio; by one or more computing devices, determining a fourth feature vector representing the video-content object, wherein the fourth feature vector is based on a combination of the first, second, and third feature vectors; and by one or more computing devices, determining a context of the video-content object based on the fourth feature vector and social-graph information based at least in part on one or more nodes or edges connected to the node corresponding to the video-content object. 6. The method of claim 1 , further comprising: by one or more computing devices, receiving, a query associated with the video-content object from a client device of a user of the social-networking system; by one or more computing devices, identifying one or more objects matching the query; by one or more computing devices, for each identified object, accessing a feature vector representing the identified object; by one or more computing devices, ranking each identified object based on a similarity metric between the feature vector representing the video-content object and the feature vector representing the identified object; and by one or more computing devices, sending, to the client system in response to the query, one or more search results corresponding to one or more of the identified objects, respectively, each identified object corresponding to a search result having a rank greater than a threshold rank. | 0.50054 |
9,477,763 | 12 | 22 | 12. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: receiving input from a user via a web address bar to navigate to a web site; navigating to the web site; storing information about the web site in a file unless predetermined characteristics of actions performed by the user on the web site once the user has navigated to the web site are present; repeating the navigating and storing steps for each requested web site; determining web sites associated with a search query of the user as the search query is being entered by the user into a search area of a visibly displayed user interface of an application program executed by the computing device, the search area separate from the web address bar, the associated web sites being sites that have been previously navigated to by the user, the determining step comprising obtaining the web sites associated with the search query from a data structure previously generated by the computing device from the file, the data structure comprising parsed entries of Uniform Resource Locators (URLs) associated with the previously navigated web sites; and based on the determining step, causing web site links corresponding to the associated web sites to be visibly displayed on a display of the computing device as the search query is being entered, the web site links comprising, in addition to the URLs associated with the previously navigated web sites, information previously collected for the web sites and available via a network, the information comprising a timestamp of a most recent visit to the previously navigated web sites by the user, the predetermined characteristics of actions performed by the user selected from a group of characteristics consisting of the user selecting a new window or tab within a predetermined amount of time after navigating to the web site, and detecting a new navigation request not associated with the web site within a predetermined amount of time after navigating to the web site, wherein the obtaining the web sites associated with the search query from a data structure further comprises: for each Uniform Resource Locator (URL) entry associated with a web site, adding an entry to the data structure for each search term associated with the URL, for each URL entry associated with a web site, parsing a title of the entry into tokens, for each URL entry associated with a web site, tokenizing its domain name into a plurality of words, for the each URL entry having its domain name tokenized, adding the plurality of words to the data structure for the URL, for each URL entry having a filename, tokenizing the filename, and adding the filename to the data structure for the each URL entry having the filename. | 12. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: receiving input from a user via a web address bar to navigate to a web site; navigating to the web site; storing information about the web site in a file unless predetermined characteristics of actions performed by the user on the web site once the user has navigated to the web site are present; repeating the navigating and storing steps for each requested web site; determining web sites associated with a search query of the user as the search query is being entered by the user into a search area of a visibly displayed user interface of an application program executed by the computing device, the search area separate from the web address bar, the associated web sites being sites that have been previously navigated to by the user, the determining step comprising obtaining the web sites associated with the search query from a data structure previously generated by the computing device from the file, the data structure comprising parsed entries of Uniform Resource Locators (URLs) associated with the previously navigated web sites; and based on the determining step, causing web site links corresponding to the associated web sites to be visibly displayed on a display of the computing device as the search query is being entered, the web site links comprising, in addition to the URLs associated with the previously navigated web sites, information previously collected for the web sites and available via a network, the information comprising a timestamp of a most recent visit to the previously navigated web sites by the user, the predetermined characteristics of actions performed by the user selected from a group of characteristics consisting of the user selecting a new window or tab within a predetermined amount of time after navigating to the web site, and detecting a new navigation request not associated with the web site within a predetermined amount of time after navigating to the web site, wherein the obtaining the web sites associated with the search query from a data structure further comprises: for each Uniform Resource Locator (URL) entry associated with a web site, adding an entry to the data structure for each search term associated with the URL, for each URL entry associated with a web site, parsing a title of the entry into tokens, for each URL entry associated with a web site, tokenizing its domain name into a plurality of words, for the each URL entry having its domain name tokenized, adding the plurality of words to the data structure for the URL, for each URL entry having a filename, tokenizing the filename, and adding the filename to the data structure for the each URL entry having the filename. 22. The non-transitory computer readable storage medium of claim 12 wherein the receiving input from a user to navigate to a web site further comprises receiving a web search result choice from a user to navigate to the web site. | 0.502174 |
8,038,537 | 26 | 27 | 26. A non-transitory computer-readable medium having computer executable instructions stored thereon for performing operations for evaluating a game outcome on a gaming machine, the operations comprising: receiving a game rules script, the game rules script comprising text defining a set of displayable game elements used in the wagering game, the text further defining one or more rules to determine a set of winning outcomes in terms of one or more of the set of displayable game elements; parsing the games rules script into a game rules data structure; generating a game outcome, the game outcome including selected elements of the set of displayable game elements; and determining if the game outcome matches at least one winning outcome in the set of winning outcomes in accordance with evaluation of the selected elements against the one or more rules provided by the game rules data structure by repeating, until all rules are compared: comparing the selected elements against the one or more rules provided by the game rules data structure; and removing a matching rule from the one or more rules and removing matching elements from the selected elements responsive to matching of the matching elements and the matching rule. | 26. A non-transitory computer-readable medium having computer executable instructions stored thereon for performing operations for evaluating a game outcome on a gaming machine, the operations comprising: receiving a game rules script, the game rules script comprising text defining a set of displayable game elements used in the wagering game, the text further defining one or more rules to determine a set of winning outcomes in terms of one or more of the set of displayable game elements; parsing the games rules script into a game rules data structure; generating a game outcome, the game outcome including selected elements of the set of displayable game elements; and determining if the game outcome matches at least one winning outcome in the set of winning outcomes in accordance with evaluation of the selected elements against the one or more rules provided by the game rules data structure by repeating, until all rules are compared: comparing the selected elements against the one or more rules provided by the game rules data structure; and removing a matching rule from the one or more rules and removing matching elements from the selected elements responsive to matching of the matching elements and the matching rule. 27. The non-transitory computer-readable medium of claim 26 , wherein the set of winning outcomes comprise winning outcomes for a card game. | 0.812834 |
7,962,477 | 17 | 18 | 17. The storage medium of claim 15 , wherein the operations further comprise: ranking the mobile search results and the generic search results in an order, the ranking being based on the respective search result quality scores; and removing one or more duplicates from the order. | 17. The storage medium of claim 15 , wherein the operations further comprise: ranking the mobile search results and the generic search results in an order, the ranking being based on the respective search result quality scores; and removing one or more duplicates from the order. 18. The storage medium of claim 17 , wherein removing the one or more duplicates comprises: identifying a specific mobile search result that identifies a first uniform resource locator; identifying a specific generic search result that identifies a second uniform resource locator, the second uniform resource locator being the same as the first uniform resource locator; removing the specific generic search result from the order; and if the specific generic search result had a higher rank than the specific mobile search result, moving the specific mobile search result to the position in the order that the specific generic search result occupied. | 0.815998 |
8,335,694 | 20 | 21 | 20. The method of claim 19 , further comprising: converting prose reports into gesture-based reports, using said computer system; and comparing reports between different users in a standardized reporting format. | 20. The method of claim 19 , further comprising: converting prose reports into gesture-based reports, using said computer system; and comparing reports between different users in a standardized reporting format. 21. The method of claim 20 , further comprising: tracking a frequency, using said computer system, of each individual gesture or symbol used with said gesture-based reporting method, by said user, to create a statistical profile of commonly used gestures or symbols. | 0.92321 |
9,224,041 | 9 | 15 | 9. An organizational table identifier comprising: a selector comprising computer hardware configured to select text fragment pairs associated with an organizational table from text fragments of a document based on textual similarity; a classifier comprising computer hardware wherein the classifier is trained to classify an input text fragment pair as associated with the organizational table or not associated with the organizational table based on one or more features of the text fragment pair including at least one text formatting feature, the classifier being trained using a set of positive training examples comprising some or all of the text fragment pairs of the document selected by the selector; and a re-selector comprising computer hardware configured to reselect text fragment pairs associated with the organizational table of the document from the text fragments of the document using the classifier. | 9. An organizational table identifier comprising: a selector comprising computer hardware configured to select text fragment pairs associated with an organizational table from text fragments of a document based on textual similarity; a classifier comprising computer hardware wherein the classifier is trained to classify an input text fragment pair as associated with the organizational table or not associated with the organizational table based on one or more features of the text fragment pair including at least one text formatting feature, the classifier being trained using a set of positive training examples comprising some or all of the text fragment pairs of the document selected by the selector; and a re-selector comprising computer hardware configured to reselect text fragment pairs associated with the organizational table of the document from the text fragments of the document using the classifier. 15. The organizational table identifier as set forth in claim 9 , wherein the classifier is trained using the set of positive training examples comprising some or all of the text fragment pairs selected by the selector and a set of negative training examples comprising some or all of the text fragment pairs of the document other than the text fragment pairs selected by the selector. | 0.501295 |
9,477,749 | 33 | 34 | 33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. | 33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. 34. The non-transitory computer readable storage medium of claim 33 , wherein the one or more causal features comprise at least one of a lexical feature, a grammatical feature, and a semantic feature. | 0.904031 |
7,996,383 | 5 | 6 | 5. The search engine of claim 3 , wherein the index comprises a matrix of term units, wherein each term unit is a set of characters that is separated by a space from another term unit; and the Duplicate Blocker module operates to locate duplicate term units within the index. | 5. The search engine of claim 3 , wherein the index comprises a matrix of term units, wherein each term unit is a set of characters that is separated by a space from another term unit; and the Duplicate Blocker module operates to locate duplicate term units within the index. 6. The search engine of claim 5 , wherein the Duplicate Blocker module operates to locate duplicate term units without grammatical form. | 0.928346 |
8,589,324 | 8 | 10 | 8. A computer-implemented method of incrementally finding and presenting one or more items in response to keystrokes entered by a user on an input device having at least one layout of keys, each key having at least one corresponding alphanumeric symbol, the method comprising: providing access to a database stored in a computer memory, the database containing a catalog of items and corresponding descriptive terms that characterize the items, wherein the items include at least one of content items and data items; determining a layout of keys present on the input device; receiving a sequence of incremental keystrokes from the user; in response to each incremental keystroke of the sequence of incremental keystrokes, building a string corresponding to the sequence, each entry in the string having the alphanumeric symbol associated with the corresponding keystroke of the sequence of incremental keystrokes; in response to each incremental keystroke of the sequence of incremental keystrokes, mapping the string to the database to find the most likely items corresponding to the sequence of incremental keystrokes, the mapping being in accordance with a defined error model, the error model providing for at least one suggested correction in the string wherein at least one keystroke of the sequence of incremental keystrokes is replaced by at least one alphanumeric symbol, and wherein the at least one alphanumeric symbol that replaces the at least one keystroke of the sequence of incremental keystrokes includes an alphanumeric symbol associated with a keystroke other than the keystroke being replaced; and in response to each incremental keystroke of the sequence of incremental keystrokes, ordering and presenting the most likely items on a display device in accordance with defined ordering criteria such that the user-interface system receives ambiguous entries from the user and presents the most likely matching items in response to the entries. | 8. A computer-implemented method of incrementally finding and presenting one or more items in response to keystrokes entered by a user on an input device having at least one layout of keys, each key having at least one corresponding alphanumeric symbol, the method comprising: providing access to a database stored in a computer memory, the database containing a catalog of items and corresponding descriptive terms that characterize the items, wherein the items include at least one of content items and data items; determining a layout of keys present on the input device; receiving a sequence of incremental keystrokes from the user; in response to each incremental keystroke of the sequence of incremental keystrokes, building a string corresponding to the sequence, each entry in the string having the alphanumeric symbol associated with the corresponding keystroke of the sequence of incremental keystrokes; in response to each incremental keystroke of the sequence of incremental keystrokes, mapping the string to the database to find the most likely items corresponding to the sequence of incremental keystrokes, the mapping being in accordance with a defined error model, the error model providing for at least one suggested correction in the string wherein at least one keystroke of the sequence of incremental keystrokes is replaced by at least one alphanumeric symbol, and wherein the at least one alphanumeric symbol that replaces the at least one keystroke of the sequence of incremental keystrokes includes an alphanumeric symbol associated with a keystroke other than the keystroke being replaced; and in response to each incremental keystroke of the sequence of incremental keystrokes, ordering and presenting the most likely items on a display device in accordance with defined ordering criteria such that the user-interface system receives ambiguous entries from the user and presents the most likely matching items in response to the entries. 10. The method of claim 8 , wherein the error model providing for at least one suggested correction in the string corrects typographic errors corresponding to incremental user entries, and wherein the suggested corrections are derived by removing characters in the string resulting from one or more accidentally pressed keys. | 0.587563 |
9,690,861 | 17 | 18 | 17. The computer program product according to claim 15 , said method further comprising: identifying a first set of medical concepts from said unstructured data in said EMR; identifying a second set of medical concepts from said structured data in said EMR; and identifying clinically relevant semantic relationships in a medical ontology between medical concepts in said first set of medical concepts and said second set of medical concepts. | 17. The computer program product according to claim 15 , said method further comprising: identifying a first set of medical concepts from said unstructured data in said EMR; identifying a second set of medical concepts from said structured data in said EMR; and identifying clinically relevant semantic relationships in a medical ontology between medical concepts in said first set of medical concepts and said second set of medical concepts. 18. The computer program product according to claim 17 , said identifying clinically relevant semantic relationships in said medical ontology between medical concepts in said first set of medical concepts and second set of medical concepts further comprising: identifying causation of medical conditions and treatments for medical conditions based on said medical concepts. | 0.856096 |
9,195,716 | 1 | 2 | 1. An apparatus, comprising: a processor circuit; a character set converter application operative on the processor circuit to receive a search string over a network from a requesting device, the search string comprised of one or more first character set characters, and convert the first character set characters of the search string to one or more second character set characters, the second character set different from the first character set; an index server operative to execute a search on the second character set search string to obtain one or more ranked individual search results, the search executed against a search database comprised of first and second character set characters; and a ranking application operative on the index server to compare any first character set characters in the ranked individual search results to the first character set characters in the search string, and sub-rank the ranked individual search results based on a match strength between the first character set characters of the search string and the first character set characters of the individual search results. | 1. An apparatus, comprising: a processor circuit; a character set converter application operative on the processor circuit to receive a search string over a network from a requesting device, the search string comprised of one or more first character set characters, and convert the first character set characters of the search string to one or more second character set characters, the second character set different from the first character set; an index server operative to execute a search on the second character set search string to obtain one or more ranked individual search results, the search executed against a search database comprised of first and second character set characters; and a ranking application operative on the index server to compare any first character set characters in the ranked individual search results to the first character set characters in the search string, and sub-rank the ranked individual search results based on a match strength between the first character set characters of the search string and the first character set characters of the individual search results. 2. The apparatus of claim 1 , the first character set and the second character set comprising any one of a Roman character set, a Chinese character set, a Japanese character set, a Russian character set, a Korean character set, a European character set, and an Arabic character set. | 0.780374 |
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