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9,354,629 | 9 | 11 | 9. An apparatus comprising: a processor; and a memory storing machine-readable instructions that, when executed, cause the processor to implement: an editor useable to create a first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices, the first script comprising an interpretable system-level vendor-independent schema; and a compiler including: a parser to identify one or more first expressions based on grammatical relationships between the tokens contained in the first script; and an interpreter to: retrieve vendor-specific information associated with the process control system from a device database associated with the process control system; and form a second script based on the identified one or more first expressions and the retrieved vendor-specific information, the second script to configure the multiple process controllers and process control devices and structured in accordance with a first vendor-specific configuration language associated with the process control system. | 9. An apparatus comprising: a processor; and a memory storing machine-readable instructions that, when executed, cause the processor to implement: an editor useable to create a first script defining a physical topology and control of a process control system including multiple process controllers and process control devices, the first script including tokens that have a type and value to define attributes of the multiple process controllers and process control devices, the topology representing physical communicative couplings between the multiple process controllers and the process control devices, the first script comprising an interpretable system-level vendor-independent schema; and a compiler including: a parser to identify one or more first expressions based on grammatical relationships between the tokens contained in the first script; and an interpreter to: retrieve vendor-specific information associated with the process control system from a device database associated with the process control system; and form a second script based on the identified one or more first expressions and the retrieved vendor-specific information, the second script to configure the multiple process controllers and process control devices and structured in accordance with a first vendor-specific configuration language associated with the process control system. 11. The apparatus as defined in claim 9 , wherein the first script is constructed in accordance with an extensible markup language. | 0.849771 |
6,038,668 | 20 | 26 | 20. The system according to claim 16, wherein said portal further comprises: an extraction device for extracting the categorized data from said storage device. | 20. The system according to claim 16, wherein said portal further comprises: an extraction device for extracting the categorized data from said storage device. 26. The system according to claim 20, further comprising: an organizational manager for organizing said data based on a previously stored ontology of the organizational terms for storage in said storage device. | 0.759174 |
8,816,976 | 1 | 12 | 1. A touch-typable device for accepting desired textual input from a user comprising: said touch-typable device including a display; a movable keymask comprising of a plurality of dynamically assigned cells that are logically mapped to and activate with one or more keys of a text input keypad of said touch-typable device, wherein each of said plurality of dynamically assigned cells of said movable keymask superimposes over corresponds to textual input choices enabling said user to select said desired textual input choices through said plurality of cells of said movable keymask using said text input keypad of said touch-typable device, wherein said textual input choices are chosen after every user input from a set of likely and valid textual input choices, wherein said likely and valid input choices are selected based on one or a combination of previous textual input sequence, phoneme and syllabary patterns, statistical correlation between said previous textual input sequence and set of textual input choices, dictionary lookups, and usage patterns of said user. | 1. A touch-typable device for accepting desired textual input from a user comprising: said touch-typable device including a display; a movable keymask comprising of a plurality of dynamically assigned cells that are logically mapped to and activate with one or more keys of a text input keypad of said touch-typable device, wherein each of said plurality of dynamically assigned cells of said movable keymask superimposes over corresponds to textual input choices enabling said user to select said desired textual input choices through said plurality of cells of said movable keymask using said text input keypad of said touch-typable device, wherein said textual input choices are chosen after every user input from a set of likely and valid textual input choices, wherein said likely and valid input choices are selected based on one or a combination of previous textual input sequence, phoneme and syllabary patterns, statistical correlation between said previous textual input sequence and set of textual input choices, dictionary lookups, and usage patterns of said user. 12. The touch-typable device as claimed in claim 1 , wherein said touch-typable device comprises of one or more of mobile phone, personal handyphone system (PHS), car phones, personal digital assistant, surface computer, pocket beepers, ATM's, STB's, touchscreen kiosks, gaming consoles, and remote controls for display devices such as televisions. | 0.772251 |
10,019,487 | 7 | 8 | 7. A non-transitory computer-readable storage medium having executable computer code stored thereon, the code comprising a set of instructions that is executed by one or more processors to cause a computing device to: receive a search query from a user including a geographic area; provide a plurality of entities within the geographic area that match the search query; receive a selection of one of the plurality entities by the user; obtain a plurality of contacts from an asymmetric social graph for the user; determine one or more associations between one or more of the plurality of contacts and the selected entity, each association including a rating of the entity, a review of the entity, or a combination thereof; and display an indication of the entity with an indication of the one or more contacts and association information from the one or more associations between the one or more contacts and the selected entity. | 7. A non-transitory computer-readable storage medium having executable computer code stored thereon, the code comprising a set of instructions that is executed by one or more processors to cause a computing device to: receive a search query from a user including a geographic area; provide a plurality of entities within the geographic area that match the search query; receive a selection of one of the plurality entities by the user; obtain a plurality of contacts from an asymmetric social graph for the user; determine one or more associations between one or more of the plurality of contacts and the selected entity, each association including a rating of the entity, a review of the entity, or a combination thereof; and display an indication of the entity with an indication of the one or more contacts and association information from the one or more associations between the one or more contacts and the selected entity. 8. The computer-readable storage medium of claim 7 , wherein the set of instructions further causes the computing device to: display an indication of a relationship between the user and each of the one or more contacts with the display of the indication of the entity. | 0.755027 |
8,764,556 | 12 | 15 | 12. A system for providing sporting event odds and information, for sports books, in substantially real time where the sports books, gamblers and enthusiasts want real time odds and information on the sports books computer, the system comprising: a program executed by a computer that utilizes an Internet connection to provide real time sports bet odds and information for a plurality of sports games from a plurality of sport books, said real time sports bet odds and information being downloaded and stored on the computer, wherein the program is incapable of placing bets; the program generating a display of real time sports bet odds and information including a major line move alert indicating when a number of sport books change their odds for a bet for a sports game in the same direction with a user settable period of time; and the program allowing navigation of the display in order to acquire real time sports bet odds and information wherein the program generates a menu made up of various menus, and for any particular game or bet, the program being capable of visually cycling through odds for the plurality of sport books. | 12. A system for providing sporting event odds and information, for sports books, in substantially real time where the sports books, gamblers and enthusiasts want real time odds and information on the sports books computer, the system comprising: a program executed by a computer that utilizes an Internet connection to provide real time sports bet odds and information for a plurality of sports games from a plurality of sport books, said real time sports bet odds and information being downloaded and stored on the computer, wherein the program is incapable of placing bets; the program generating a display of real time sports bet odds and information including a major line move alert indicating when a number of sport books change their odds for a bet for a sports game in the same direction with a user settable period of time; and the program allowing navigation of the display in order to acquire real time sports bet odds and information wherein the program generates a menu made up of various menus, and for any particular game or bet, the program being capable of visually cycling through odds for the plurality of sport books. 15. The system of claim 12 wherein the program notifies the user when a predetermined amount of sports books' odds change within a predetermined amount of time. | 0.692308 |
7,844,603 | 14 | 17 | 14. A method performed by one or more server devices, the method comprising: providing, by a processor associated with the one or more server devices, an interface configured to facilitate composition of text by a first user; receiving, by one of the one or more server devices, a search query from the first user; initiating, by a processor associated with the one or more server devices, a search based on the search query; receiving, by a processor associated with the one or more server devices, results of the search; modifying, by a processor associated with the one or more server devices and in response to receiving the results of the search, a relevance order of the results of the search based on a type of a content creation application implemented by the interface; providing, by one of the one or more server devices, the results of the search in the interface using the modified relevance order, the provided results of the search each including a selection object; receiving, by one of the one or more server devices, a selection of one or more of the selection objects from the first user; incorporating, by a processor associated with the one or more server devices and in response to receiving the selection, the results of the search, that correspond to the one or more of the selection objects, into the text in the interface; providing, by one of the one or more server devices, the text and the incorporated results of the search to a second user; receiving, by one of the one or more server devices, a request to access one of the incorporated results from the second user; analyzing, by a processor associated with the one or server devices and in response to receiving the request, the request to access the one of the incorporated results from the second user; and adjusting, by a processor associated with the one or more server devices, a reputation score of the first user based on the analyzed request from the second user. | 14. A method performed by one or more server devices, the method comprising: providing, by a processor associated with the one or more server devices, an interface configured to facilitate composition of text by a first user; receiving, by one of the one or more server devices, a search query from the first user; initiating, by a processor associated with the one or more server devices, a search based on the search query; receiving, by a processor associated with the one or more server devices, results of the search; modifying, by a processor associated with the one or more server devices and in response to receiving the results of the search, a relevance order of the results of the search based on a type of a content creation application implemented by the interface; providing, by one of the one or more server devices, the results of the search in the interface using the modified relevance order, the provided results of the search each including a selection object; receiving, by one of the one or more server devices, a selection of one or more of the selection objects from the first user; incorporating, by a processor associated with the one or more server devices and in response to receiving the selection, the results of the search, that correspond to the one or more of the selection objects, into the text in the interface; providing, by one of the one or more server devices, the text and the incorporated results of the search to a second user; receiving, by one of the one or more server devices, a request to access one of the incorporated results from the second user; analyzing, by a processor associated with the one or server devices and in response to receiving the request, the request to access the one of the incorporated results from the second user; and adjusting, by a processor associated with the one or more server devices, a reputation score of the first user based on the analyzed request from the second user. 17. The method of claim 14 , where initiating the search includes transmitting the search query to a plurality of search services, the plurality of search services returning one or more search result types. | 0.540179 |
8,494,277 | 8 | 9 | 8. The computer system of claim 1 , wherein the handwriting comprises a sentence, and wherein the method further comprises: said processor dissecting the sentence into individual words. | 8. The computer system of claim 1 , wherein the handwriting comprises a sentence, and wherein the method further comprises: said processor dissecting the sentence into individual words. 9. The computer system of claim 8 , wherein said dissecting the sentence comprises identifying consecutive rows of white pixels in an image of the sentence and separating the sentence into the individual words based on the identified rows of white pixels. | 0.912069 |
6,122,661 | 39 | 40 | 39. A storage medium according to claim 37, further comprising: the presentation space buffer storing computer display information representing a plurality of computer displays; the display control receiving the presentation space data stream containing the computer display information representing the plurality of computer displays; and the host extension converting substantially the entire presentation space data stream containing the computer display information representing the plurality of computer displays into a single markup language document. | 39. A storage medium according to claim 37, further comprising: the presentation space buffer storing computer display information representing a plurality of computer displays; the display control receiving the presentation space data stream containing the computer display information representing the plurality of computer displays; and the host extension converting substantially the entire presentation space data stream containing the computer display information representing the plurality of computer displays into a single markup language document. 40. A storage medium according to claim 39, wherein the plurality of computer displays comprises a single session running on the host computer. | 0.954918 |
10,162,869 | 13 | 17 | 13. One or more memory devices having computer-executable instructions embodied thereon that, when executed, perform a method for providing a user interface, the method comprising: receiving a search query term; storing the search query term in a database, wherein the search query term is associated with a first identifier; generating a set of facets for the search query term; communicating for display the set of facets for the search query term; receiving a selected facet from the set of facets; storing the selected facet, wherein the selected facet is associated with a second identifier; matching the second identifier of the selected facet to the first identifier of the search query term, wherein the combination of operations of receiving the selected facet and matching the second identifier to the first identifier supports maintaining the state of the search query term corresponding to the set of facets when the selected facet corresponds to a facet in the set of facets of the search query term, wherein the selected facet that corresponds to the facet in the set of facets operates as an indication that the set of facets corresponding to the search query term will remain available on display, wherein maintaining comprises: (1) recalling the search query term from the database; and (2) re-generating the set of facets of the search query term; and communicating for display the set of facets. | 13. One or more memory devices having computer-executable instructions embodied thereon that, when executed, perform a method for providing a user interface, the method comprising: receiving a search query term; storing the search query term in a database, wherein the search query term is associated with a first identifier; generating a set of facets for the search query term; communicating for display the set of facets for the search query term; receiving a selected facet from the set of facets; storing the selected facet, wherein the selected facet is associated with a second identifier; matching the second identifier of the selected facet to the first identifier of the search query term, wherein the combination of operations of receiving the selected facet and matching the second identifier to the first identifier supports maintaining the state of the search query term corresponding to the set of facets when the selected facet corresponds to a facet in the set of facets of the search query term, wherein the selected facet that corresponds to the facet in the set of facets operates as an indication that the set of facets corresponding to the search query term will remain available on display, wherein maintaining comprises: (1) recalling the search query term from the database; and (2) re-generating the set of facets of the search query term; and communicating for display the set of facets. 17. The method of claim 13 , further comprising: receiving a selected sub facet; and maintaining the state of the search query term corresponding to the set of facets and the set of sub facets when the selected sub facet corresponds to the set of sub facets of the search query term. | 0.857359 |
8,433,698 | 16 | 22 | 16. A non-transitory computer-readable storage medium storing modules that, when executed by a processor, cause a computer to perform a method of searching for media objects associated with a search term, the method comprising: retrieving, based upon a received first search term, at least one web page including the first search term; analyzing a plurality of positional relationships between the first search term and additional terms within an individual one of the at least one web page; scoring each of the plurality of positional relationships; determining, based on the scoring, at least one additional search term, and retrieving, based on the at least one additional search term, at least one media object. | 16. A non-transitory computer-readable storage medium storing modules that, when executed by a processor, cause a computer to perform a method of searching for media objects associated with a search term, the method comprising: retrieving, based upon a received first search term, at least one web page including the first search term; analyzing a plurality of positional relationships between the first search term and additional terms within an individual one of the at least one web page; scoring each of the plurality of positional relationships; determining, based on the scoring, at least one additional search term, and retrieving, based on the at least one additional search term, at least one media object. 22. The non-transitory computer-readable storage medium of claim 16 , wherein the analyzing comprises generating a plurality of relationship vectors configured to represent relationships between the first search term and the additional terms. | 0.598007 |
8,527,279 | 6 | 10 | 6. A computer-implemented method comprising: accessing, by a computer system, information that identifies content that was previously requested by and displayed on a mobile computing device that is associated with a user, wherein the content comprises one or more web pages that were previously displayed on the mobile computing device; identifying, based at least in part on the content that was previously requested and displayed on the mobile computing device, a geographic location to which future voice input from the user is likely to relate; selecting, by the computer system and based at least in part on the identified geographic location, a first grammar from among a plurality of grammars, wherein the first grammar includes a vocabulary that is relevant to the geographic location; and outputting, by the computer system, information that identifies the first grammar, wherein the outputted information causes a grammar used to analyze voice input from the mobile computing device to be changed to the first grammar. | 6. A computer-implemented method comprising: accessing, by a computer system, information that identifies content that was previously requested by and displayed on a mobile computing device that is associated with a user, wherein the content comprises one or more web pages that were previously displayed on the mobile computing device; identifying, based at least in part on the content that was previously requested and displayed on the mobile computing device, a geographic location to which future voice input from the user is likely to relate; selecting, by the computer system and based at least in part on the identified geographic location, a first grammar from among a plurality of grammars, wherein the first grammar includes a vocabulary that is relevant to the geographic location; and outputting, by the computer system, information that identifies the first grammar, wherein the outputted information causes a grammar used to analyze voice input from the mobile computing device to be changed to the first grammar. 10. The computer-implemented method of claim 6 , wherein the geographic location is identified from the content based on the geographic location occurring in the content at least a threshold number of times. | 0.945698 |
10,013,643 | 1 | 6 | 1. A computer-implemented method for identifying information in an electronic document, comprising: obtaining a set of training documents for each template of a plurality of templates for the electronic document; extracting a first set of spatial attributes for at least a first label region and at least a first corresponding value region from the set, the first set of spatial attributes representing a position of at least the first label region and at least the first value region within the electronic document; training a classifier model based on the extracted first set of spatial attributes to generate a trained classifier model; segmenting, an image of the electronic document to obtain a second set of spatial attributes of candidate regions in the image, each of the candidate regions corresponding to a label or a value; identifying at least one candidate region from the candidate regions as a label to generate an identified label based on the obtained second set of spatial attributes using the trained classifier model without performing Optical Character Recognition (OCR); designating at least one of the candidate regions that is not identified as a label, as a designated value region; and performing OCR only on the designated value region to obtain at least one value corresponding to the identified label. | 1. A computer-implemented method for identifying information in an electronic document, comprising: obtaining a set of training documents for each template of a plurality of templates for the electronic document; extracting a first set of spatial attributes for at least a first label region and at least a first corresponding value region from the set, the first set of spatial attributes representing a position of at least the first label region and at least the first value region within the electronic document; training a classifier model based on the extracted first set of spatial attributes to generate a trained classifier model; segmenting, an image of the electronic document to obtain a second set of spatial attributes of candidate regions in the image, each of the candidate regions corresponding to a label or a value; identifying at least one candidate region from the candidate regions as a label to generate an identified label based on the obtained second set of spatial attributes using the trained classifier model without performing Optical Character Recognition (OCR); designating at least one of the candidate regions that is not identified as a label, as a designated value region; and performing OCR only on the designated value region to obtain at least one value corresponding to the identified label. 6. The method of claim 1 , wherein the spatial attributes comprises at least one of dimensions of each of the at least one label region and the at least one corresponding value region, position of each of the at least one label region and the at least one corresponding value region within the electronic document, or position of the at least one label region and the at least one corresponding value region relative to other regions in the electronic document. | 0.501082 |
10,127,022 | 46 | 47 | 46. A method of developing a dataflow program comprising: using a graphical user interface to specify a graphical representation of a dataflow program, the program comprising producer types, transducer types, and extractor types, wherein through the graphical user interface, a user can select and move the producer types, transducer types, and extractor types, represented using blocks, into various positions on a computer screen; using the graphical user interface, allowing the user to interconnect via interconnection links the blocks representing the producer types, transducer types, and extractor types; allowing the user to specify a specification of each of the blocks through the graphical user interface, wherein for a transducer type block, the user can specify an operation; automatically generating computer source code that corresponds to the dataflow program the user specified using the graphical user interface; allowing the user to view and edit the computer source code automatically generated in a textual interface; and allowing the user to specify generating of a computer package of code executable on a target hardware platform that is an implementation of the dataflow program specified by the user using the graphical user interface. | 46. A method of developing a dataflow program comprising: using a graphical user interface to specify a graphical representation of a dataflow program, the program comprising producer types, transducer types, and extractor types, wherein through the graphical user interface, a user can select and move the producer types, transducer types, and extractor types, represented using blocks, into various positions on a computer screen; using the graphical user interface, allowing the user to interconnect via interconnection links the blocks representing the producer types, transducer types, and extractor types; allowing the user to specify a specification of each of the blocks through the graphical user interface, wherein for a transducer type block, the user can specify an operation; automatically generating computer source code that corresponds to the dataflow program the user specified using the graphical user interface; allowing the user to view and edit the computer source code automatically generated in a textual interface; and allowing the user to specify generating of a computer package of code executable on a target hardware platform that is an implementation of the dataflow program specified by the user using the graphical user interface. 47. The method of claim 46 wherein the operation in a transducer block is a pattern matching operation, and the automatically generating computer source code implements the operation using a state machine reflecting a technique that processes data of an input stream of a producer without backtracking. | 0.897835 |
9,485,211 | 12 | 14 | 12. A mobile device for accessing a social networking website managed by a social networking website system, the mobile device comprising: a memory; a location determination circuitry that facilitates determination of a current location; a processing circuitry coupled to the memory and the location determination circuitry; a client that is executed by the processing circuitry, wherein the client, when operable, interacts with the social networking website, without conducting any upfront registration, without sharing any user profile and without need for invitations; the client determining the current location of the mobile device employing the location determination circuitry and processing circuitry; the client automatically registering the current location of the mobile device with the social networking website system, without employing invitations and explicit user acceptance to join them, whereby the social networking website system, in response, automatically assigns the user as a member of at least one social network selected by the social networking website system from a plurality of social networks based on the current location of the mobile device; and the client monitors the current location for the user, and communicates changes to the current location, to adjust the user's membership to the social networks and social groups based on changes to the current location. | 12. A mobile device for accessing a social networking website managed by a social networking website system, the mobile device comprising: a memory; a location determination circuitry that facilitates determination of a current location; a processing circuitry coupled to the memory and the location determination circuitry; a client that is executed by the processing circuitry, wherein the client, when operable, interacts with the social networking website, without conducting any upfront registration, without sharing any user profile and without need for invitations; the client determining the current location of the mobile device employing the location determination circuitry and processing circuitry; the client automatically registering the current location of the mobile device with the social networking website system, without employing invitations and explicit user acceptance to join them, whereby the social networking website system, in response, automatically assigns the user as a member of at least one social network selected by the social networking website system from a plurality of social networks based on the current location of the mobile device; and the client monitors the current location for the user, and communicates changes to the current location, to adjust the user's membership to the social networks and social groups based on changes to the current location. 14. The mobile device of claim 12 wherein the mobile device also receives assignment of a primary and a secondary language to the user for content and for user interaction screens presented. | 0.641509 |
9,843,544 | 1 | 4 | 1. In an environment wherein electronic messages having written text may be sent with or without an attachment, a computer-implemented method for determining whether an electronic message should have an attachment, the method comprising: inspecting the written text in the electronic message to detect any words which are in a database of predetermined key terms; inspecting the written text to detect any phrases which are in the database of predetermined key terms; if a word which was detected in the written text is in a database of predetermined negative terms then disregarding the word which was detected; if a phrase which was detected in the written text is in the database of predetermined negative terms then disregarding the phrase which was detected; and if any word which was detected in the written text has not been disregarded, or if any phrase which was detected in the written text has not been disregarded, then providing a suggestion that the electronic message may need an attachment. | 1. In an environment wherein electronic messages having written text may be sent with or without an attachment, a computer-implemented method for determining whether an electronic message should have an attachment, the method comprising: inspecting the written text in the electronic message to detect any words which are in a database of predetermined key terms; inspecting the written text to detect any phrases which are in the database of predetermined key terms; if a word which was detected in the written text is in a database of predetermined negative terms then disregarding the word which was detected; if a phrase which was detected in the written text is in the database of predetermined negative terms then disregarding the phrase which was detected; and if any word which was detected in the written text has not been disregarded, or if any phrase which was detected in the written text has not been disregarded, then providing a suggestion that the electronic message may need an attachment. 4. The method of claim 1 wherein inspecting the written text to detect any words which are in the database of predetermined key terms comprises: accessing the database of predetermined key terms, the database comprising predetermined words; and inspecting the written text in the electronic message for at least one of the predetermined words. | 0.834139 |
7,877,377 | 9 | 10 | 9. A computer-readable program product comprising: (A) a query optimizer that analyzes a query, drops at least one tautological predicate from the query, and determines whether a corresponding access plan exists for the query with the at least one dropped tautological predicate, and if so, the query optimizer uses the corresponding access plan to execute the query, and if no corresponding access plan exists for the query with the at least one dropped tautological predicate, the query optimizer generates a corresponding access plan and uses the corresponding access plan to execute the query; and (B) recordable media bearing the query optimizer. | 9. A computer-readable program product comprising: (A) a query optimizer that analyzes a query, drops at least one tautological predicate from the query, and determines whether a corresponding access plan exists for the query with the at least one dropped tautological predicate, and if so, the query optimizer uses the corresponding access plan to execute the query, and if no corresponding access plan exists for the query with the at least one dropped tautological predicate, the query optimizer generates a corresponding access plan and uses the corresponding access plan to execute the query; and (B) recordable media bearing the query optimizer. 10. The program product of claim 9 wherein the query optimizer stores the generated access plan in a cache. | 0.911424 |
7,698,383 | 2 | 11 | 2. The method according to claim 1 , wherein a plurality of the data field definitions of the data component is shared between the at least one message component and the at least one data component as represented by the mapping. | 2. The method according to claim 1 , wherein a plurality of the data field definitions of the data component is shared between the at least one message component and the at least one data component as represented by the mapping. 11. The method according to claim 2 , wherein the structured definition language is XML based. | 0.968179 |
9,922,648 | 1 | 12 | 1. A computer-implemented method comprising: receiving, by a voice action system, data defining a new voice action that does not currently exist for a software application installed on one or more devices, the software application being different from said voice action system, the data indicating one or more operations for the software application to perform the new voice action and one or more trigger terms for triggering the new voice action, wherein the data defining the new voice action specifies a context, the context specifying a status of a user device or of the software application installed on the user device; generating, by the voice action system, a voice action passive data structure based at least on the data defining the new voice action, wherein the voice action passive data structure comprises data that, when received by the software application, causes the software application to perform the one or more operations to perform the new voice action; associating, by the voice action system, the voice action passive data structure with the context and with the one or more trigger terms for triggering the new voice action, wherein multiple voice action passive data structures are defined in the voice action system; receiving, by the voice action system, (i) user command utterance obtained by the user device, the user device having the software application installed, and (ii) current context information regarding the user device; identifying, using the current context information and not a transcription of the user command utterance, a set of candidate voice action passive data structures from the multiple voice action passive data structures of the voice action system, the set of candidate voice action passive data structures including the voice action passive data structure defined by the data and being identified based on respective contexts associated with the set of candidate voice action passive data structures; narrowing the identified set of candidate voice action passive data structures by comparing the transcription of the user command utterance with trigger terms of respective ones of the set of candidate voice action passive data structures; determining, by the voice action system, that the transcription of the user command utterance corresponds to the one or more trigger terms associated with the voice action passive data structure; and in response to the determination, providing, by the voice action system, the voice action passive data structure to the user device which is remote from the voice action system, thereby causing the software application installed on the user device to perform the one or more operations to perform the new voice action. | 1. A computer-implemented method comprising: receiving, by a voice action system, data defining a new voice action that does not currently exist for a software application installed on one or more devices, the software application being different from said voice action system, the data indicating one or more operations for the software application to perform the new voice action and one or more trigger terms for triggering the new voice action, wherein the data defining the new voice action specifies a context, the context specifying a status of a user device or of the software application installed on the user device; generating, by the voice action system, a voice action passive data structure based at least on the data defining the new voice action, wherein the voice action passive data structure comprises data that, when received by the software application, causes the software application to perform the one or more operations to perform the new voice action; associating, by the voice action system, the voice action passive data structure with the context and with the one or more trigger terms for triggering the new voice action, wherein multiple voice action passive data structures are defined in the voice action system; receiving, by the voice action system, (i) user command utterance obtained by the user device, the user device having the software application installed, and (ii) current context information regarding the user device; identifying, using the current context information and not a transcription of the user command utterance, a set of candidate voice action passive data structures from the multiple voice action passive data structures of the voice action system, the set of candidate voice action passive data structures including the voice action passive data structure defined by the data and being identified based on respective contexts associated with the set of candidate voice action passive data structures; narrowing the identified set of candidate voice action passive data structures by comparing the transcription of the user command utterance with trigger terms of respective ones of the set of candidate voice action passive data structures; determining, by the voice action system, that the transcription of the user command utterance corresponds to the one or more trigger terms associated with the voice action passive data structure; and in response to the determination, providing, by the voice action system, the voice action passive data structure to the user device which is remote from the voice action system, thereby causing the software application installed on the user device to perform the one or more operations to perform the new voice action. 12. The computer-implemented method of claim 1 , wherein generating the voice action passive data structure comprises determining that the one or more operations to perform the new voice action are capable of being performed by the software application. | 0.879867 |
8,924,213 | 2 | 3 | 2. A method of processing results of a recognition by an automatic speech recognition (ASR) system on a speech input, the results comprising a first recognition result identified by the ASR system as most likely to be a correct recognition result for the speech input, the results further comprising at least one alternative recognition result identified by the ASR system, the method comprising: determining whether the first recognition result includes a member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and whether the at least one alternative recognition result includes any of the at least one other member associated with the member in the set; and in response to determining that the first recognition result includes the member of the set of words or phrases and that the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, triggering an alert, wherein: the at least one alternative recognition result comprises a second recognition result; the member of the set is a first member of the set; the at least one other member of the set associated with the member comprises a second member of the set; the determining whether the first recognition result includes a member of the set and whether the at least one alternative recognition result includes any of the at least one other member comprises determining whether the ASR system recognized a segment of the speech input as the first member for the first recognition result and as the second member of the set for the second recognition result; and the determining whether the ASR system identified the segment of the speech input as the first member for the first recognition result and as the second member for the second recognition result comprises determining whether a time within the speech input associated with the first member for the first recognition result matches a time within the speech input associated with the second member of the set for the second recognition result. | 2. A method of processing results of a recognition by an automatic speech recognition (ASR) system on a speech input, the results comprising a first recognition result identified by the ASR system as most likely to be a correct recognition result for the speech input, the results further comprising at least one alternative recognition result identified by the ASR system, the method comprising: determining whether the first recognition result includes a member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and whether the at least one alternative recognition result includes any of the at least one other member associated with the member in the set; and in response to determining that the first recognition result includes the member of the set of words or phrases and that the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, triggering an alert, wherein: the at least one alternative recognition result comprises a second recognition result; the member of the set is a first member of the set; the at least one other member of the set associated with the member comprises a second member of the set; the determining whether the first recognition result includes a member of the set and whether the at least one alternative recognition result includes any of the at least one other member comprises determining whether the ASR system recognized a segment of the speech input as the first member for the first recognition result and as the second member of the set for the second recognition result; and the determining whether the ASR system identified the segment of the speech input as the first member for the first recognition result and as the second member for the second recognition result comprises determining whether a time within the speech input associated with the first member for the first recognition result matches a time within the speech input associated with the second member of the set for the second recognition result. 3. The method of claim 2 , wherein: a first member of the set is associated with a second member of the set with which the first member is acoustically-confusable and that, when substituted for the first member in a recognition result, changes a meaning of the recognition result; and the determining whether the first recognition result includes a member of the set and whether the at least one alternative recognition result includes any of the at least one other member comprises determining whether the first recognition result includes the first member and whether the at least one alternative recognition result includes the second member. | 0.634354 |
8,738,403 | 31 | 37 | 31. At least one non-transitory computer-readable storage medium encoded with a plurality of computer-executable instructions that, when executed, perform a method comprising: processing a free-form narration of a patient encounter provided by a clinician, using natural language understanding, to identify one or more options corresponding respectively to one or more clinical facts that could be extracted from the free-form narration of the patient encounter, the processing comprising analyzing the free-form narration to identify a set of one or more features of at least a portion of the free-form narration, correlating the set of features to one or more abstract semantic concepts, and generating computer-readable data that expresses the one or more abstract semantic concepts as the one or more clinical facts that could be extracted from the free-form narration; providing to a user the one or more options corresponding to the one or more clinical facts corresponding to the one or more abstract semantic concepts identified from the processing of the free-form narration; receiving from the user a selection of a first option of the one or more options, the first option corresponding to a first fact of the one or more clinical facts; and updating a textual representation of the free-form narration to identify the first fact as having been ascertained from the patient encounter. | 31. At least one non-transitory computer-readable storage medium encoded with a plurality of computer-executable instructions that, when executed, perform a method comprising: processing a free-form narration of a patient encounter provided by a clinician, using natural language understanding, to identify one or more options corresponding respectively to one or more clinical facts that could be extracted from the free-form narration of the patient encounter, the processing comprising analyzing the free-form narration to identify a set of one or more features of at least a portion of the free-form narration, correlating the set of features to one or more abstract semantic concepts, and generating computer-readable data that expresses the one or more abstract semantic concepts as the one or more clinical facts that could be extracted from the free-form narration; providing to a user the one or more options corresponding to the one or more clinical facts corresponding to the one or more abstract semantic concepts identified from the processing of the free-form narration; receiving from the user a selection of a first option of the one or more options, the first option corresponding to a first fact of the one or more clinical facts; and updating a textual representation of the free-form narration to identify the first fact as having been ascertained from the patient encounter. 37. The at least one computer-readable storage medium of claim 31 , wherein the providing comprises providing disambiguating options among facts. | 0.711155 |
8,874,929 | 7 | 9 | 7. The method of claim 6 , further comprising: encrypting the first key split and the third key split using a public key of a first asymmetric key pair belonging to the object service component; and encrypting the second key split and the fourth key split using a public key of a second asymmetric key pair belonging to the policy service. | 7. The method of claim 6 , further comprising: encrypting the first key split and the third key split using a public key of a first asymmetric key pair belonging to the object service component; and encrypting the second key split and the fourth key split using a public key of a second asymmetric key pair belonging to the policy service. 9. The method of claim 7 , further comprising: decrypting the encrypted first key split using a private key of the first asymmetric key pair belonging to the object service component. | 0.970244 |
10,127,212 | 11 | 17 | 11. A method performed by a computing system, the method comprising: monitoring deletions and insertions to copied text in multiple documents, the copied text having been copied from a previous document; determining that a same deletion and different insertions have been made to the copied text in at least a threshold number of documents, the threshold number being greater than one; and prompting the same deletion and a new insertion to be made to the copied text in a subsequent document based on the determination that the same deletion and different insertions have been made to the copied text in at least the threshold number of documents. | 11. A method performed by a computing system, the method comprising: monitoring deletions and insertions to copied text in multiple documents, the copied text having been copied from a previous document; determining that a same deletion and different insertions have been made to the copied text in at least a threshold number of documents, the threshold number being greater than one; and prompting the same deletion and a new insertion to be made to the copied text in a subsequent document based on the determination that the same deletion and different insertions have been made to the copied text in at least the threshold number of documents. 17. The method of claim 11 , wherein the same deletion and different insertions to the copied text includes deleting an original sequence of characters from the copied text and adding different new sequences of characters to the copied text. | 0.798831 |
8,935,166 | 1 | 11 | 1. A system comprising: a processor, and one or more memory components that stores a target application and a dictation application, wherein the dictation application provides a dictation application interface, to be displayed on a user computing device's display, which is: automatically sized and positioned over the target application interface to fully cover a text area of the target application interface so as to appear as if the dictation application interface is part of the target application interface; and adjusted to match the target application interface if the target application interface is moved, minimized, maximized, or resized; and wherein the dictation application further causes the system to, in response to receiving a user command to complete a dictation, automatically copy a converted audio dictation from the dictation application interface and insert it into the target application interface. | 1. A system comprising: a processor, and one or more memory components that stores a target application and a dictation application, wherein the dictation application provides a dictation application interface, to be displayed on a user computing device's display, which is: automatically sized and positioned over the target application interface to fully cover a text area of the target application interface so as to appear as if the dictation application interface is part of the target application interface; and adjusted to match the target application interface if the target application interface is moved, minimized, maximized, or resized; and wherein the dictation application further causes the system to, in response to receiving a user command to complete a dictation, automatically copy a converted audio dictation from the dictation application interface and insert it into the target application interface. 11. The system of claim 1 , wherein said dictation application receives an audio dictation and converts the audio dictation into text using the processor to perform, selected from the group consisting of: a local machine conversion of the audio dictation into text, a remote machine conversion of the audio dictation into text, a sending of the audio dictation to a transcriptionist for transcription, a sending of the audio dictation to a remote machine to be converted to text and then a sending of the converted audio dictation to a transcriptionist, and a local machine conversion and a sending of the audio dictation and a local machine converted text to the transcriptionist. | 0.500733 |
7,650,286 | 201 | 202 | 201. The method of claim 200 , wherein the contextual use for the required skill or experience-related phrase for each said at least one job requirement includes the contextual use of the associated said at least one implying skill or experience-related phrase. | 201. The method of claim 200 , wherein the contextual use for the required skill or experience-related phrase for each said at least one job requirement includes the contextual use of the associated said at least one implying skill or experience-related phrase. 202. The method of claim 201 , further comprising: when the experience range is zero: setting the term of experience to zero; and when the experience range is greater than zero: determining a start time for the experience range; determining an end time for the experience range; computing a time difference between the start time and the end time; and setting the term of experience to the time difference. | 0.916939 |
8,577,867 | 1 | 3 | 1. A method to expand a website, the method comprising: receiving a filter set comprising a plurality of filters for a website, wherein the filters are associated with a plurality of online messages such that a first online message may be tagged with a first filter to describe the first online message; receiving a user input corresponding to a second filter from a first user; determining, by a computer, a reputation associated with the first user; and adding, if the reputation associated with the first user is high, the second filter to the filter set for the website such that a second online message may be tagged with the second filter to describe the second online message. | 1. A method to expand a website, the method comprising: receiving a filter set comprising a plurality of filters for a website, wherein the filters are associated with a plurality of online messages such that a first online message may be tagged with a first filter to describe the first online message; receiving a user input corresponding to a second filter from a first user; determining, by a computer, a reputation associated with the first user; and adding, if the reputation associated with the first user is high, the second filter to the filter set for the website such that a second online message may be tagged with the second filter to describe the second online message. 3. The method as set forth in claim 1 , further comprising: displaying an online poll corresponding to the second filter on the website to one or more users with a high reputation. | 0.84456 |
10,049,147 | 39 | 40 | 39. The apparatus of claim 37 is configured to synchronize the designated document with a server. | 39. The apparatus of claim 37 is configured to synchronize the designated document with a server. 40. The apparatus of claim 39 is configured to perform at least one of: send the designated document itself to the server such that the at least one multimedia resource in the designated document is parsed and stored by the server; and send a characteristic value of the at least one multimedia resource in the designated document to the server; wherein: in the case if the at least one multimedia resource having the same characteristic value has already been stored in the server, the apparatus sends multimedia resources other than those at least one multimedia resource which has already been stored to the server; and in the case if the at least one multimedia resource having the same characteristic value has not been stored in the server, the apparatus sends the at least one multimedia resource to the server. | 0.89803 |
9,146,966 | 2 | 5 | 2. The method of claim 1 , comprising assigning a score to the query term proximity rule based on the click count, a skip count, and a fake skip count. | 2. The method of claim 1 , comprising assigning a score to the query term proximity rule based on the click count, a skip count, and a fake skip count. 5. The method of claim 2 , associating a first weight with the click count, a second weight with the skip count, and a third weight associated with the fake skip count. | 0.943813 |
8,977,949 | 2 | 4 | 2. An equivalence determination system comprising: a processor; an object extracting unit, executed on the processor, that extracts, from respective electronic documents in a set of electronic documents, at least one object which forms the electronic document and includes at least one of a text, a figure, and an equation; a specifying unit that specifies predetermined number of objects in the respective electronic documents based on density calculated by referring to the extracted objects; a judging unit that judges that plural electronic documents are similar based on the specified objects; a hash value calculation unit that calculates hash values of the objects specified by said specifying unit; and a feature word extraction unit that extracts a feature character string from the objects specified by said specifying unit, wherein said hash value calculation unit calculates a hash value based on the feature character string extracted by said feature word extraction unit, wherein said judging unit determines, by using the hash values calculated by said hash value calculation unit, whether the objects specified by said specifying unit match each other, wherein said specifying unit calculates, based on a density of the at least one object extracted by the object extracting unit, an improbability of modifying the at least one object, and specifies objects based on a calculation result, said feature word extraction unit extracts at least one feature word as the feature character string from the specified object by said specifying unit, said hash value calculation unit calculates a hash value of a character string obtained by concatenating feature words extracted by said feature word extraction unit, and registers identification information of corresponding electronic documents in a hash table, and said judging unit judges, based on a match between hash values, that the corresponding electronic documents are equivalent. | 2. An equivalence determination system comprising: a processor; an object extracting unit, executed on the processor, that extracts, from respective electronic documents in a set of electronic documents, at least one object which forms the electronic document and includes at least one of a text, a figure, and an equation; a specifying unit that specifies predetermined number of objects in the respective electronic documents based on density calculated by referring to the extracted objects; a judging unit that judges that plural electronic documents are similar based on the specified objects; a hash value calculation unit that calculates hash values of the objects specified by said specifying unit; and a feature word extraction unit that extracts a feature character string from the objects specified by said specifying unit, wherein said hash value calculation unit calculates a hash value based on the feature character string extracted by said feature word extraction unit, wherein said judging unit determines, by using the hash values calculated by said hash value calculation unit, whether the objects specified by said specifying unit match each other, wherein said specifying unit calculates, based on a density of the at least one object extracted by the object extracting unit, an improbability of modifying the at least one object, and specifies objects based on a calculation result, said feature word extraction unit extracts at least one feature word as the feature character string from the specified object by said specifying unit, said hash value calculation unit calculates a hash value of a character string obtained by concatenating feature words extracted by said feature word extraction unit, and registers identification information of corresponding electronic documents in a hash table, and said judging unit judges, based on a match between hash values, that the corresponding electronic documents are equivalent. 4. An equivalence determination system according to claim 2 , wherein said specifying unit calculates an improbability of modifying the object, based on the density of the object and a density of a peripheral object. | 0.889344 |
8,156,099 | 26 | 27 | 26. The method of claim 25 , where splitting the search query into a plurality of splits is based on context information associated with a client device. | 26. The method of claim 25 , where splitting the search query into a plurality of splits is based on context information associated with a client device. 27. The method of claim 26 , where the context information is associated with map data displayed on the client device. | 0.973303 |
9,881,006 | 18 | 20 | 18. The one or more hardware processors of claim 15 wherein the metadata is collected by one of an API to a web-based metadata collection module or a by stand-alone metadata collection module. | 18. The one or more hardware processors of claim 15 wherein the metadata is collected by one of an API to a web-based metadata collection module or a by stand-alone metadata collection module. 20. The one or more hardware processors of claim 18 wherein measuring the structural similarity of the first item listing and the second item listing is based on a hypertext markup language (HTML) code of the item descriptions. | 0.952251 |
9,031,330 | 1 | 2 | 1. A method of identifying symbols including traffic pictograms for use with a Global Positioning Satellite (GPS) device, comprising: receiving image information from an imaging device, the image information including an image and a GPS location at which the image was captured; and processing the received image information in a database server located geographically remotely from the GPS location at which the image was captured to determine a meaning of the image at the location at which the image was captured, the processing comprising comparing the image with stored images or symbols in a database in the database server to determine whether the image matches a stored image or symbol in the database, the stored images or symbols including traffic pictograms and being associated with the GPS location at which the image was captured, and when a match is not determined based on the comparing, storing the image in the database. | 1. A method of identifying symbols including traffic pictograms for use with a Global Positioning Satellite (GPS) device, comprising: receiving image information from an imaging device, the image information including an image and a GPS location at which the image was captured; and processing the received image information in a database server located geographically remotely from the GPS location at which the image was captured to determine a meaning of the image at the location at which the image was captured, the processing comprising comparing the image with stored images or symbols in a database in the database server to determine whether the image matches a stored image or symbol in the database, the stored images or symbols including traffic pictograms and being associated with the GPS location at which the image was captured, and when a match is not determined based on the comparing, storing the image in the database. 2. The method of claim 1 , the comparing comprising at least one of (1) comparing an image appearance of the image with a stored image or symbol appearance and (2) comparing the GPS location at which the image was captured with a stored image or symbol GPS location. | 0.803545 |
4,839,822 | 14 | 15 | 14. The expert system of claim 13, wherein said computer displays graphical representations of said classifications of trauma. | 14. The expert system of claim 13, wherein said computer displays graphical representations of said classifications of trauma. 15. The expert system of claim 14, wherein said different types of trauma are orthopedic fractures. | 0.966026 |
7,571,383 | 5 | 6 | 5. The retrieval system according to claim 1 , wherein said concept retrieving section comprises: a higher concept acquiring section that acquires a retrieval statement higher concept that is a higher-layer concept of said retrieval statement concept if said retrieval statement concept does not match said document concept; and a generalized concept output section that outputs the document data as a retrieval result if said retrieval statement higher concept matches said document concept. | 5. The retrieval system according to claim 1 , wherein said concept retrieving section comprises: a higher concept acquiring section that acquires a retrieval statement higher concept that is a higher-layer concept of said retrieval statement concept if said retrieval statement concept does not match said document concept; and a generalized concept output section that outputs the document data as a retrieval result if said retrieval statement higher concept matches said document concept. 6. The retrieval system according to claim 5 , wherein said concept database stores each of said plurality of concepts as a node of said first or second hierarchical structure, said document data concept extracting section extracts said first document concept belonging to said first hierarchical structure and said second document concept belonging to said second hierarchical structure in association with said document data, said retrieval statement concept extracting section extracts said retrieval statement concept belonging to said first hierarchical structure and said second retrieval statement concept belonging to said second hierarchical structure in association with said retrieval statement, said higher concept acquiring section acquires said first retrieval statement higher concept that is a higher layer of said first retrieval statement concept and said second retrieval statement higher concept that is a higher layer of said second retrieval statement concept if said first retrieval statement concept does not match said first document concept and if said second retrieval statement concept does not match said second document concept, and said generalized concept output section outputs said first document data as a retrieval result if the number of said first document data in which said first retrieval statement higher concept is the same as said second retrieval statement concept and in which said first document concept is the same as said second document concept is smaller than that of said second document data in which said first retrieval statement higher concept is the same as said second retrieval statement concept and in which said first document concept is the same as said second document concept. | 0.936515 |
8,190,684 | 10 | 11 | 10. The method of claim 1 , further comprising, creating a second object to represent a request for the offering. | 10. The method of claim 1 , further comprising, creating a second object to represent a request for the offering. 11. The method of claim 10 , further comprising, matching the offering to the request for the offering. | 0.959734 |
9,465,780 | 13 | 17 | 13. A web document scrolling method of a user terminal device, the method comprising the steps of: (a) executing processes including a web application process and receiving a web document created in a web description language, by a processor unit; (b) parsing the web document and converting into a DOM tree data having a structure formed in a shape of a tree, by the processor unit; (c) creating a render tree data having a structure the same as that of the DOM tree data, in which non-output nodes excluding display output nodes corresponding to data that will be output on a display means are configured as void nodes, by the processor unit; and (d) loading the render tree data in video buffer memory and providing the render tree data to the web application process, by the processor unit. | 13. A web document scrolling method of a user terminal device, the method comprising the steps of: (a) executing processes including a web application process and receiving a web document created in a web description language, by a processor unit; (b) parsing the web document and converting into a DOM tree data having a structure formed in a shape of a tree, by the processor unit; (c) creating a render tree data having a structure the same as that of the DOM tree data, in which non-output nodes excluding display output nodes corresponding to data that will be output on a display means are configured as void nodes, by the processor unit; and (d) loading the render tree data in video buffer memory and providing the render tree data to the web application process, by the processor unit. 17. The method according to claim 13 , wherein in the step (d), if a request for changing the data that will be output on the display unit is received from the web application process, the processor unit replaces non-output nodes which do not output on the display unit any more among the display output nodes of the render tree data with void nodes, copies data that will be output on the display means among the DOM tree data to the render tree data, and then providing the render tree data to the web application process. | 0.725941 |
9,361,340 | 1 | 2 | 1. A computer program product, tangibly embodied in a non-transitory machine-readable medium, the computer program product containing instructions to configure a data processing apparatus to perform operations comprising: receiving a query for one or more data items stored in a database, wherein the query is associated with a query plan; determining whether to use at least one query operator that uses data having a format different from a storage model format of at least one of the data items stored in the database; and converting the format of the data used by the at least one query operator to another format that matches the storage model format of the at least one of the data items stored in the database, wherein a difference between the format of the data used by the at least one query operator and the storage model format of the at least one of the data items before conversion is one of the following: the format of the data used by the at least one query operator is a row-format and the storage model format of the at least one of the data items is a column-format; or the format of the data used by the at least one query operator is the column-format and the storage model of the at least one of the data items is the row-format, and wherein the at least one query operator includes at least one of a select operator, a project operator, an insert operator, a delete operator, or an update operator. | 1. A computer program product, tangibly embodied in a non-transitory machine-readable medium, the computer program product containing instructions to configure a data processing apparatus to perform operations comprising: receiving a query for one or more data items stored in a database, wherein the query is associated with a query plan; determining whether to use at least one query operator that uses data having a format different from a storage model format of at least one of the data items stored in the database; and converting the format of the data used by the at least one query operator to another format that matches the storage model format of the at least one of the data items stored in the database, wherein a difference between the format of the data used by the at least one query operator and the storage model format of the at least one of the data items before conversion is one of the following: the format of the data used by the at least one query operator is a row-format and the storage model format of the at least one of the data items is a column-format; or the format of the data used by the at least one query operator is the column-format and the storage model of the at least one of the data items is the row-format, and wherein the at least one query operator includes at least one of a select operator, a project operator, an insert operator, a delete operator, or an update operator. 2. The computer program product of claim 1 , wherein the converting further comprises at least one of the following: converting the format of the data used by a row query operator to the column-format; or converting the format of the data used by a column query operator to the row-format. | 0.610512 |
8,719,250 | 6 | 10 | 6. The method set forth in claim 5 wherein: the relational database system includes one or more optimization objects for optimizing queries on the RDF triples table; and in the step of obtaining results, the relational database management system uses the optimization objects to optimize the query on the RDF triples table. | 6. The method set forth in claim 5 wherein: the relational database system includes one or more optimization objects for optimizing queries on the RDF triples table; and in the step of obtaining results, the relational database management system uses the optimization objects to optimize the query on the RDF triples table. 10. The method set forth in claim 6 wherein: the RDF triples table includes a subject column whose values represent RDF subjects, a predicate column whose values represent RDF predicates, and an object column whose values represent RDF objects; and the query optimization objects include a subject-property matrix materialized join view which has a subject column and one or more predicate columns, the values in the predicate columns of a row of the join view being values of RDF objects which the RDF triples in the RDF triples table relate to the value in the row's subject column. | 0.686695 |
8,346,738 | 1 | 2 | 1. A computer-implemented method of verifying a data categorization in a categorization verification system, the method including executable instructions that perform actions comprising: determining, within a framework that supports queries, an accuracy of semantic relationships between data that is categorized in a data structure based on information received from a common knowledge repository comprising a set of common semantic relationships, the determining further comprising: parsing nodes of the categorized data in the data structure, wherein the data structure is a data tree structure comprising a set of nodes and a set of semantic relationships of the set of nodes; and sending a query to the common knowledge repository through the framework regarding the semantic relationships between each node in the data structure wherein the query performs an analysis of the semantic relationships between the set of nodes in the data structure and flags erroneous semantic relationships between the set of nodes; determining whether a category identifier of a node in the data structure is valid, wherein responsive to the category identifier of a parent node being valid, verifying a relationship between the parent and a child nodes of the data structure, and wherein responsive to the category identifier of a parent node not being valid, sending a query to the common knowledge repository to determine a general category for each child node; responsive to a determination of an incorrect categorization, flagging a semantic relationship within the data structure as potentially inaccurate; and reporting the potentially inaccurate categorization. | 1. A computer-implemented method of verifying a data categorization in a categorization verification system, the method including executable instructions that perform actions comprising: determining, within a framework that supports queries, an accuracy of semantic relationships between data that is categorized in a data structure based on information received from a common knowledge repository comprising a set of common semantic relationships, the determining further comprising: parsing nodes of the categorized data in the data structure, wherein the data structure is a data tree structure comprising a set of nodes and a set of semantic relationships of the set of nodes; and sending a query to the common knowledge repository through the framework regarding the semantic relationships between each node in the data structure wherein the query performs an analysis of the semantic relationships between the set of nodes in the data structure and flags erroneous semantic relationships between the set of nodes; determining whether a category identifier of a node in the data structure is valid, wherein responsive to the category identifier of a parent node being valid, verifying a relationship between the parent and a child nodes of the data structure, and wherein responsive to the category identifier of a parent node not being valid, sending a query to the common knowledge repository to determine a general category for each child node; responsive to a determination of an incorrect categorization, flagging a semantic relationship within the data structure as potentially inaccurate; and reporting the potentially inaccurate categorization. 2. The computer-implemented method of claim 1 , wherein the determining comprises sending a query to a common knowledge repository to verify a relationship between nodes in the data structure. | 0.54717 |
9,576,305 | 1 | 2 | 1. A system comprising: at least one hardware processor; a template builder, implemented by the at least one processor, to build comparative sentence templates, each comparative sentence template including at least two product name slots and a relationship phrase to define a relationship between the at least two product name slots, each comparative sentence template having a template weight as a function of the relationship defined between the at least two product name slots, wherein the comparative sentence templates are configured to create comparative sentences by respectively filling the at least two product name slots with at least two product names; an interface for receiving user input comprising the at least two product names; a search engine to retrieve product reviews from a data storage using the at least two product names, and to extract snippets from the product reviews using the comparative sentences, each snippet having a snippet weight equal to the template weight of the comparative sentence template corresponding to the comparative sentence used to extract the snippet; a linguistic analyzer to tag the product reviews, the linguistic analyzer including a tokenizing component to tokenize each product review into tokens; a review ranking device to rank each of the product reviews based on the snippet weights of the snippets thereof and a percentage of the tokens thereof that are adjectives or adverbs; and a display to present the ranked product reviews. | 1. A system comprising: at least one hardware processor; a template builder, implemented by the at least one processor, to build comparative sentence templates, each comparative sentence template including at least two product name slots and a relationship phrase to define a relationship between the at least two product name slots, each comparative sentence template having a template weight as a function of the relationship defined between the at least two product name slots, wherein the comparative sentence templates are configured to create comparative sentences by respectively filling the at least two product name slots with at least two product names; an interface for receiving user input comprising the at least two product names; a search engine to retrieve product reviews from a data storage using the at least two product names, and to extract snippets from the product reviews using the comparative sentences, each snippet having a snippet weight equal to the template weight of the comparative sentence template corresponding to the comparative sentence used to extract the snippet; a linguistic analyzer to tag the product reviews, the linguistic analyzer including a tokenizing component to tokenize each product review into tokens; a review ranking device to rank each of the product reviews based on the snippet weights of the snippets thereof and a percentage of the tokens thereof that are adjectives or adverbs; and a display to present the ranked product reviews. 2. The system of claim 1 , further comprising an aggregator to calculate a ranking score of each product review by aggregating snippet weights within each product review. | 0.681648 |
7,627,882 | 1 | 13 | 1. A device for generating a display of an electronic program guide on a screen, the device comprising: a receiver including a tuner for receiving an input stream, of television content and electronic program guide data, and separating the electronic program guide data from the input stream; a memory coupled to the tuner for storing the electronic program guide data separated from the input stream; display means for generating a display which combines a set of electronic program guide data including a plurality of program titles, and a plurality of organizational categories, each program title belonging to at least one of the organizational categories, the program titles arranged in the display so that program titles which belong to the same organizational categories are spatially adjacent and program titles which are not members of the same organizational categories are spatially separated, the organizational categories providing a first-level organization which defines overall content of the display and a second-level organization which defines the spatial separation of the program titles, where the organizational categories are used at any organizational level. | 1. A device for generating a display of an electronic program guide on a screen, the device comprising: a receiver including a tuner for receiving an input stream, of television content and electronic program guide data, and separating the electronic program guide data from the input stream; a memory coupled to the tuner for storing the electronic program guide data separated from the input stream; display means for generating a display which combines a set of electronic program guide data including a plurality of program titles, and a plurality of organizational categories, each program title belonging to at least one of the organizational categories, the program titles arranged in the display so that program titles which belong to the same organizational categories are spatially adjacent and program titles which are not members of the same organizational categories are spatially separated, the organizational categories providing a first-level organization which defines overall content of the display and a second-level organization which defines the spatial separation of the program titles, where the organizational categories are used at any organizational level. 13. The device of claim 1 , wherein a remote control is used to direct the receiver to perform an operational function, including signaling a recording device to record a specified television program, signaling the tuner to generate a display of a specified television program, and setting a reminder in memory to display the specified television program upon receiving the specified television program in the input stream, the operational function is performed by pressing a button on the remote control. | 0.545863 |
10,019,708 | 1 | 13 | 1. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store, the data store including processing information associated with one or more transaction phrase tokens, wherein the one or more transaction phrase tokens are associated with transaction accounts via the processing information, and wherein at least one transaction phrase token of the one or more transaction phrase tokens consists of an unambiguous set of characters selected in its entirety by a transaction phrase token holder; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the transaction phrase token processing service accesses the processing information associated with the selected transaction phrase token, wherein the processing information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the processing information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule. | 1. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store, the data store including processing information associated with one or more transaction phrase tokens, wherein the one or more transaction phrase tokens are associated with transaction accounts via the processing information, and wherein at least one transaction phrase token of the one or more transaction phrase tokens consists of an unambiguous set of characters selected in its entirety by a transaction phrase token holder; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the transaction phrase token processing service accesses the processing information associated with the selected transaction phrase token, wherein the processing information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the processing information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule. 13. The system as recited in claim 1 , wherein the set of characters corresponds to a set of one or more alphanumeric characters. | 0.867828 |
8,452,597 | 1 | 4 | 1. A method comprising: determining whether a mobile computing device is receiving operating power from an external power source, wherein the mobile computing device has a trigger word detection subroutine that is activatable by a user input and automatically in response to determining that the mobile computing device is receiving external power; and in response to determining that the mobile computing device is receiving operating power from the external power source, activating a trigger word detection subroutine, wherein the trigger word detection subroutine includes: receiving spoken input via a microphone of the mobile computing device, based on speech recognition performed on the spoken input, obtaining text, determining whether the text includes one or more trigger words associated with a voice command prompt application, and in response to determining that the text includes the one or more trigger words associated with the voice command prompt application, launching the voice command prompt application, wherein the voice command prompt application is configured to receive via the microphone additional spoken input that causes the mobile computing device to launch one or more other applications, and wherein launching the voice command prompt application comprises displaying a voice command prompt on the mobile computing device. | 1. A method comprising: determining whether a mobile computing device is receiving operating power from an external power source, wherein the mobile computing device has a trigger word detection subroutine that is activatable by a user input and automatically in response to determining that the mobile computing device is receiving external power; and in response to determining that the mobile computing device is receiving operating power from the external power source, activating a trigger word detection subroutine, wherein the trigger word detection subroutine includes: receiving spoken input via a microphone of the mobile computing device, based on speech recognition performed on the spoken input, obtaining text, determining whether the text includes one or more trigger words associated with a voice command prompt application, and in response to determining that the text includes the one or more trigger words associated with the voice command prompt application, launching the voice command prompt application, wherein the voice command prompt application is configured to receive via the microphone additional spoken input that causes the mobile computing device to launch one or more other applications, and wherein launching the voice command prompt application comprises displaying a voice command prompt on the mobile computing device. 4. The method of claim 1 , further comprising: receiving the user input; and activating the trigger word detection subroutine in response to receiving the user input regardless of whether the mobile computing device is receiving operating power from the external power source. | 0.718941 |
7,836,069 | 2 | 5 | 2. A computer program product residing on a computer readable media for generating a poet personality comprising instructions for causing a computer to: load a word processing program; receive a word provided by a user to the word processing program; display a plurality of poet windows in response to receiving the word, the poet windows including a finish word window, a finish line window; and a finish poem window corresponding to underlying models that represent pre-defined poet personalities; process the word in each of the plurality of poet windows with processing the word in the finish word window comprises instructions to: load an author analysis model; locate the word in the author analysis model; and generate a proposed word in conjunction with the author analysis model. | 2. A computer program product residing on a computer readable media for generating a poet personality comprising instructions for causing a computer to: load a word processing program; receive a word provided by a user to the word processing program; display a plurality of poet windows in response to receiving the word, the poet windows including a finish word window, a finish line window; and a finish poem window corresponding to underlying models that represent pre-defined poet personalities; process the word in each of the plurality of poet windows with processing the word in the finish word window comprises instructions to: load an author analysis model; locate the word in the author analysis model; and generate a proposed word in conjunction with the author analysis model. 5. The computer program product of claim 2 wherein processing the word in the finish word window comprises instructions to: choose a poet personality and a finish poem display to have the program provide a completed poem after the user types a word in the word processing program. | 0.746835 |
8,577,899 | 9 | 16 | 9. A method for supporting curation of a new item in a searchable knowledge base, wherein the searchable knowledge base includes a plurality of items, said method comprising: mining one or more search queries of the searchable knowledge base, wherein each of the one or more search queries includes search results including a plurality of the plurality of items of the knowledge base, each item including a title identifying an issue and/or topic addressed by the item and further including a plurality of posts from users of the knowledge base system, each post relevant to the issue and/or topic of the item; re-running at least one of the one or more mined search queries against the searchable knowledge base using a keyword based search algorithm; determining one or more items of the plurality of items of the knowledge base using a processor, wherein each of the one or more items include a correlation value exceeding a threshold, wherein the correlation value for the each of the one or more items is based upon a frequency the each of the one or more items co-occur with the new item in search results of at least one of the at least one of the one or more search queries; and providing at least one of the one or more items to a curator, wherein the curator reviews the at least one of the one or more items; wherein the plurality of items of the knowledge base each correspond to a record of information on a specific issue or topic relevant to a topic covered by the knowledge base, and wherein the one or more mined search queries are saved within a history database, each of the saved search queries corresponding to a previously performed search of the searchable knowledge base, identifying the search terms of the previously performed search, and identifying items of the searchable knowledge base returned in response to the previously performed search. | 9. A method for supporting curation of a new item in a searchable knowledge base, wherein the searchable knowledge base includes a plurality of items, said method comprising: mining one or more search queries of the searchable knowledge base, wherein each of the one or more search queries includes search results including a plurality of the plurality of items of the knowledge base, each item including a title identifying an issue and/or topic addressed by the item and further including a plurality of posts from users of the knowledge base system, each post relevant to the issue and/or topic of the item; re-running at least one of the one or more mined search queries against the searchable knowledge base using a keyword based search algorithm; determining one or more items of the plurality of items of the knowledge base using a processor, wherein each of the one or more items include a correlation value exceeding a threshold, wherein the correlation value for the each of the one or more items is based upon a frequency the each of the one or more items co-occur with the new item in search results of at least one of the at least one of the one or more search queries; and providing at least one of the one or more items to a curator, wherein the curator reviews the at least one of the one or more items; wherein the plurality of items of the knowledge base each correspond to a record of information on a specific issue or topic relevant to a topic covered by the knowledge base, and wherein the one or more mined search queries are saved within a history database, each of the saved search queries corresponding to a previously performed search of the searchable knowledge base, identifying the search terms of the previously performed search, and identifying items of the searchable knowledge base returned in response to the previously performed search. 16. The method of claim 9 , wherein the correlation value for the each of the one or more items is further based upon a frequency with which terms of the each of the one or more items co-occur with terms of the new item. | 0.659443 |
7,668,798 | 4 | 5 | 4. The system according to claim 3 , wherein the query plan includes the server to join data from a first and a second information source to form a single new information source. | 4. The system according to claim 3 , wherein the query plan includes the server to join data from a first and a second information source to form a single new information source. 5. The system according to claim 4 , wherein the query plan includes the server to generate the new information source as a data table with a plurality of data columns, the plurality of data columns comprising data columns in the first and second information sources, and further comprising data columns corresponding to data table name of the first and second information sources. | 0.926019 |
9,514,111 | 15 | 16 | 15. A non-transitory computer-readable storage device storing a computer program, the program comprising instructions that when executed by a computing device cause the computing device to perform operations comprising: downloading, to the computing device, code that, when executed by the computing device, causes the computing device to perform second operations comprising: receiving, by the computing device, a user input; identifying, by the computing device, a set of cached autocomplete suggestions for the user input; requesting, by the computing device, a set of additional autocomplete suggestions for the user input over a network; after identifying the set of cached autocomplete suggestions, delaying, by the computing device, presentation of the set of cached autocomplete suggestions until an end of a timeout period; determining, by the computing device, that the set of additional autocomplete suggestions has not been received by the end of the timeout period; and in response to determining that the set of additional autocomplete suggestions has not been received by the end of the timeout period, presenting, by the computing device, at least a portion of the set of cached autocomplete suggestions. | 15. A non-transitory computer-readable storage device storing a computer program, the program comprising instructions that when executed by a computing device cause the computing device to perform operations comprising: downloading, to the computing device, code that, when executed by the computing device, causes the computing device to perform second operations comprising: receiving, by the computing device, a user input; identifying, by the computing device, a set of cached autocomplete suggestions for the user input; requesting, by the computing device, a set of additional autocomplete suggestions for the user input over a network; after identifying the set of cached autocomplete suggestions, delaying, by the computing device, presentation of the set of cached autocomplete suggestions until an end of a timeout period; determining, by the computing device, that the set of additional autocomplete suggestions has not been received by the end of the timeout period; and in response to determining that the set of additional autocomplete suggestions has not been received by the end of the timeout period, presenting, by the computing device, at least a portion of the set of cached autocomplete suggestions. 16. The non-transitory computer-readable storage device of claim 15 , wherein the second operations further comprise: receiving the additional autocomplete suggestions over the network after the end of the timeout period; and updating a user interface to display the received additional autocomplete suggestions. | 0.867234 |
7,716,470 | 24 | 29 | 24. A computer-readable medium comprising instructions for causing a programmable processor to: generate a boot code for a peripheral device from a program written in a high-level programming language; and generate a certificate that describes operation of the boot code from information gathered while generating the boot code, wherein the certificate includes the annotation defining the proof of security and safety for both (i) one or more blocks of code generated from a low-level programming language different from the high-level programming language and (ii) one or more corresponding blocks of the boot code resulting from translation of the one or more blocks of the code of the low-level programming language into the high-level programming language. | 24. A computer-readable medium comprising instructions for causing a programmable processor to: generate a boot code for a peripheral device from a program written in a high-level programming language; and generate a certificate that describes operation of the boot code from information gathered while generating the boot code, wherein the certificate includes the annotation defining the proof of security and safety for both (i) one or more blocks of code generated from a low-level programming language different from the high-level programming language and (ii) one or more corresponding blocks of the boot code resulting from translation of the one or more blocks of the code of the low-level programming language into the high-level programming language. 29. The computer-readable medium of claim 24 , wherein the boot code comprises boot firmware. | 0.908465 |
9,400,987 | 27 | 37 | 27. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by at least a processor of a computing device, perform the method comprising: receiving, over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, over the network, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating a dynamic webpage having content relating to the user context query. | 27. A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by at least a processor of a computing device, perform the method comprising: receiving, over a network, a user context query from a user, wherein the user context query is formatted as a parameter of a uniform resource locator (URL) and comprises at least one user context criteria; formulating a network data query based on the at least one user context criteria, said formulating comprises configuring the network data query based on user data relating to the querying user corresponding to a context of most interest to the user; identifying at least one entry from a plurality of entries in a context query bid database that relates to the at least one user context criteria based on the formulated network data query, wherein each of the plurality of entries comprises at least one bid context criteria, a bid amount, an identification of an advertiser, and an identification of at least one advertisement; selecting one of the identified at least one of the plurality of entries on the context query bid database, wherein the selected one of the plurality of entries on the context query bid database has the highest bid amount; retrieving, over the network, at least one entry from an advertisement database such that an identification of an advertiser and an identification of an advertisement on the at least one entry from the advertisement database matches the identification of the advertiser and the identification of the at least one advertisement on the selected one of the plurality of entries on the context query bid database, wherein each entry on the advertisement database comprises an identification of an advertiser, an identification of an advertisement, and at least one advertisement data object; and generating a dynamic webpage having content relating to the user context query. 37. The non-transitory computer-readable storage medium of claim 27 wherein the fee charged to the advertiser is selected from the list: cost-per-click (CPC) fee, cost-per-impression (CPM) fee. | 0.936513 |
9,489,940 | 23 | 24 | 23. A method performed on at least one processor for dynamically updating a group of similarly situated user profiles with new words, wherein the new words are not contained in a language model, the method comprising the steps of: polling a plurality of client devices to determine that at least one user has added at least one new word to a vocabulary on at least one of the plurality of client devices; pulling from the at least one of the plurality of client devices the at least one new word for the language model; evaluating the efficiency of the language model; determining that the language model is applicable to at least one similarly situated user based at least in part on the evaluated efficiency; transmitting over the communication link the new word to a destination user profile to automatically update the destination user profile, wherein the group of similarly situated user profiles is updated dynamically based on the new word, wherein the updated destination user profile is used to train and update a destination language model, wherein the destination language model is utilized, by a speech recognition engine, to transcribe speech into text, and wherein the transcribed text is displayed on a user device. | 23. A method performed on at least one processor for dynamically updating a group of similarly situated user profiles with new words, wherein the new words are not contained in a language model, the method comprising the steps of: polling a plurality of client devices to determine that at least one user has added at least one new word to a vocabulary on at least one of the plurality of client devices; pulling from the at least one of the plurality of client devices the at least one new word for the language model; evaluating the efficiency of the language model; determining that the language model is applicable to at least one similarly situated user based at least in part on the evaluated efficiency; transmitting over the communication link the new word to a destination user profile to automatically update the destination user profile, wherein the group of similarly situated user profiles is updated dynamically based on the new word, wherein the updated destination user profile is used to train and update a destination language model, wherein the destination language model is utilized, by a speech recognition engine, to transcribe speech into text, and wherein the transcribed text is displayed on a user device. 24. The method of claim 23 wherein the step of pulling from the at least one of the plurality of client devices the new word for the language model comprises pulling an audio file of a pronunciation of the new word. | 0.506881 |
9,208,214 | 15 | 16 | 15. A computer program product stored in a non-transitory computer readable medium, comprising computer instructions that, when executed by an information handling system, causes the information handling system to perform actions comprising: identifying an expansion clause within a Structured Query Language (SQL) statement, wherein the SQL statement identifies a relational database table; comparing one or more column attributes associated with the identified relational database table to one or more attributes included in the identified expansion clause; selecting one or more columns included in the relational database table based on the comparison; generating a plurality of SQL column selection statements, with each of the generated SQL column selection statements corresponding to a different one of the selected one or more columns; and including the generated SQL column selection statements in the SQL statement. | 15. A computer program product stored in a non-transitory computer readable medium, comprising computer instructions that, when executed by an information handling system, causes the information handling system to perform actions comprising: identifying an expansion clause within a Structured Query Language (SQL) statement, wherein the SQL statement identifies a relational database table; comparing one or more column attributes associated with the identified relational database table to one or more attributes included in the identified expansion clause; selecting one or more columns included in the relational database table based on the comparison; generating a plurality of SQL column selection statements, with each of the generated SQL column selection statements corresponding to a different one of the selected one or more columns; and including the generated SQL column selection statements in the SQL statement. 16. The computer program product of claim 15 wherein the column attributes are selected from the group consisting of a column name, a column data type, and a column data size, and wherein the comparing further comprises actions of: identifying a column attribute type, a wildcard character and a search string in one of the attributes included in the identified expression clause; and comparing the search string to a portion of the identified column attribute type based on a position of the wildcard character in relation to the search string. | 0.617275 |
8,311,792 | 13 | 14 | 13. The system of claim 8 , wherein the ranking the plurality of help postings and simulating user interactions uses the same ranking algorithm, wherein the ranking algorithm assigns a score to each of the plurality of help postings and test posting, and wherein the score is based on a popularity value and a seed value. | 13. The system of claim 8 , wherein the ranking the plurality of help postings and simulating user interactions uses the same ranking algorithm, wherein the ranking algorithm assigns a score to each of the plurality of help postings and test posting, and wherein the score is based on a popularity value and a seed value. 14. The system of claim 13 , wherein the popularity value is reduced over time using a deflation parameter value specifying a rate of reduction over time, and wherein the revised parameter values comprise the deflation parameter value. | 0.933125 |
9,031,384 | 5 | 6 | 5. The interesting section identifying device of claim 4 , wherein the detailed structure determining unit determines whether the detailed structure is included in an initial second unit section or a final second unit section of the interesting section candidate, and the interesting section identifying unit identifies a starting point of the interesting section by analyzing the initial second unit section when the detailed structure is determined to be included in the initial second unit section, and identifies an ending point of the interesting section by analyzing the final second unit section when the detailed structure is determined to be included in the final second unit section. | 5. The interesting section identifying device of claim 4 , wherein the detailed structure determining unit determines whether the detailed structure is included in an initial second unit section or a final second unit section of the interesting section candidate, and the interesting section identifying unit identifies a starting point of the interesting section by analyzing the initial second unit section when the detailed structure is determined to be included in the initial second unit section, and identifies an ending point of the interesting section by analyzing the final second unit section when the detailed structure is determined to be included in the final second unit section. 6. The interesting section identifying device of claim 5 , wherein when determining that the detailed structure is not included in the initial second unit section of the interesting section candidate, the detailed structure determining unit determines whether the detailed structure is included in a second unit section immediately before the interesting section candidate, and the interesting section identifying unit identifies the starting point of the interesting section by analyzing the second unit section immediately before the interesting section candidate when the detailed structure is determined to be included in the second unit section immediately before the interesting section candidate, and designates a starting point of the interesting section candidate as the starting point of the interesting section when the detailed structure is determined not to be included in the second unit section immediately before the interesting section candidate. | 0.826985 |
7,721,241 | 12 | 14 | 12. The method of claim 10 , further comprising retrieving characteristic data from the metadata text file and inserting the characteristic data into the opened electronic document, the characteristic data comprising performance characteristics of the components of the transformer. | 12. The method of claim 10 , further comprising retrieving characteristic data from the metadata text file and inserting the characteristic data into the opened electronic document, the characteristic data comprising performance characteristics of the components of the transformer. 14. The method of claim 12 , wherein the characteristic data comprises electrical characteristics of windings. | 0.939759 |
8,352,467 | 29 | 30 | 29. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: determining one or more trust relationships between a user and one or more entities based on a frequency with which the user visits one or more resources associated with the one or more entities; receiving a search query from the user; identifying one or more resources responsive to the search query associated with the user, wherein each of the resources is associated with one or more annotation label terms assigned by the one or more entities; determining whether a query label term matches any of the one or more annotation label terms; identifying, for each of the one or more annotation label terms matching the query label term, a trust rank of the entity that associated the annotation label term with the resource, each trust rank indicating a level of trust for annotation label terms that are assigned by the entity, and each trust rank being based on the determined one or more trust relationships that are based on the frequency with which the user visits the one or more resources; determining a relevance score of each of one or more resources that have the annotation label term based on the respective trust rank, the relevance score indicating a degree of relevance between the respective resource and the query term; ranking each of the one or more resources based on the respective relevance scores; and providing the ranking. | 29. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: determining one or more trust relationships between a user and one or more entities based on a frequency with which the user visits one or more resources associated with the one or more entities; receiving a search query from the user; identifying one or more resources responsive to the search query associated with the user, wherein each of the resources is associated with one or more annotation label terms assigned by the one or more entities; determining whether a query label term matches any of the one or more annotation label terms; identifying, for each of the one or more annotation label terms matching the query label term, a trust rank of the entity that associated the annotation label term with the resource, each trust rank indicating a level of trust for annotation label terms that are assigned by the entity, and each trust rank being based on the determined one or more trust relationships that are based on the frequency with which the user visits the one or more resources; determining a relevance score of each of one or more resources that have the annotation label term based on the respective trust rank, the relevance score indicating a degree of relevance between the respective resource and the query term; ranking each of the one or more resources based on the respective relevance scores; and providing the ranking. 30. The non-transitory computer storage medium of claim 29 , further comprising: annotating, with a name of the respective entity, indicia identifying each resource of the ranked search result set; and providing the indicia in a response to the search query. | 0.872781 |
8,856,051 | 10 | 11 | 10. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, actions of the computer program instructions comprising: accessing a set of digital objects; determining degrees of similarity between pairs of the objects; and for each object of a plurality of the objects, training a classifier for the object, the training comprising: forming, for the object, a training set comprising other ones of the objects based at least in part on the degrees of similarity; and training the classifier for the object based at least in part on features extracted from the objects in the training set; applying the trained classifier for a first one of the objects to a second one of the objects to determine a degree of similarity between the second one of the objects and the first one of the objects; and responsive to the degree of similarity being above a threshold value: based on the degree of similarity, reducing cluster weights derived from user-supplied textual metadata of the first one of the objects, thereby obtaining first reduced cluster weight metadata; and associating the first reduced cluster weight metadata as metadata of the second one of the objects. | 10. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, actions of the computer program instructions comprising: accessing a set of digital objects; determining degrees of similarity between pairs of the objects; and for each object of a plurality of the objects, training a classifier for the object, the training comprising: forming, for the object, a training set comprising other ones of the objects based at least in part on the degrees of similarity; and training the classifier for the object based at least in part on features extracted from the objects in the training set; applying the trained classifier for a first one of the objects to a second one of the objects to determine a degree of similarity between the second one of the objects and the first one of the objects; and responsive to the degree of similarity being above a threshold value: based on the degree of similarity, reducing cluster weights derived from user-supplied textual metadata of the first one of the objects, thereby obtaining first reduced cluster weight metadata; and associating the first reduced cluster weight metadata as metadata of the second one of the objects. 11. The non-transitory computer-readable storage medium of claim 10 , further comprising: applying the trained classifier for a third one of the objects to the second one of the objects to determine whether the third one of the objects is similar to the second one of the objects; and responsive to the third one of the objects being similar to the second one of the objects: based on a degree of similarity between the second and third objects, reducing cluster weights derived from user-supplied textual metadata of the third one of the objects, thereby obtaining second reduced cluster weight metadata; combining the second reduced cluster weight metadata with the first reduced cluster weight metadata values; and associating the combined reduced cluster weight metadata as metadata of the second one of the objects. | 0.500609 |
9,032,253 | 15 | 17 | 15. One or more non-transitory computer readable media storing computer readable instructions that, when executed, cause an information technology test system to: receive first frequently used data; receive project system criteria, wherein the project system criteria include criteria associated with testing an information technology system associated with a project; automatically identify and retrieve, from the received first frequently used data, a first portion of the first frequently used data associated with the project system criteria and configured to be used in testing the information technology system, wherein the first portion of the first frequently used data is identified based on information including at least one of the type of information technology system being tested and an operating system of the information technology system; receive a first test script associated with the information technology system, the first test script including a first data type for use in testing the information technology system and including one or more instructions for testing the information technology system, wherein the first data type includes customer data, deposit data, and loan data; create, based on the first test script, a testing environment for testing the information technology system, wherein the creation of the testing environment includes establishing and implementing instructions for testing the information technology system based on the first test script, developing tables based on the first test script, and establishing data protection parameters based on the first test script; automatically identify, based on the received first test script and the first data type, a second data type for use in testing the information technology system, the identifying of the second data type being based on a predefined relationship between the first data type and the second data type; receive data of the first data type and data of the second data type; execute the first test script to test the information technology system using the first portion of the first frequently used data, the received data of the first data type and the received data of the second data type; and modify the information technology system upon execution of the first test script. | 15. One or more non-transitory computer readable media storing computer readable instructions that, when executed, cause an information technology test system to: receive first frequently used data; receive project system criteria, wherein the project system criteria include criteria associated with testing an information technology system associated with a project; automatically identify and retrieve, from the received first frequently used data, a first portion of the first frequently used data associated with the project system criteria and configured to be used in testing the information technology system, wherein the first portion of the first frequently used data is identified based on information including at least one of the type of information technology system being tested and an operating system of the information technology system; receive a first test script associated with the information technology system, the first test script including a first data type for use in testing the information technology system and including one or more instructions for testing the information technology system, wherein the first data type includes customer data, deposit data, and loan data; create, based on the first test script, a testing environment for testing the information technology system, wherein the creation of the testing environment includes establishing and implementing instructions for testing the information technology system based on the first test script, developing tables based on the first test script, and establishing data protection parameters based on the first test script; automatically identify, based on the received first test script and the first data type, a second data type for use in testing the information technology system, the identifying of the second data type being based on a predefined relationship between the first data type and the second data type; receive data of the first data type and data of the second data type; execute the first test script to test the information technology system using the first portion of the first frequently used data, the received data of the first data type and the received data of the second data type; and modify the information technology system upon execution of the first test script. 17. The one or more non-transitory computer readable media of claim 15 , further including instructions that, when executed, cause the information technology test system to track a status of the execution of the instructions and communicate the status to a user. | 0.736948 |
9,122,497 | 1 | 4 | 1. A method of validating translated files for inclusion in an application being developed, the method comprising the steps of: a computer sending a translatable file having externalized content in a single base natural language to a plurality of other computers, wherein the externalized content is external to code of the application being developed; in response to a generation of a first translated file including a first translation of the externalized content into a natural language other than the base natural language by another computer included in the plurality of other computers, the computer receiving the first translated file from the other computer; in a simulation environment, a processor of the computer simulating a loading of the first translation of the externalized content into a user interface of the application at a runtime of the application and simulating a presentation of the first translation of the externalized content in the user interface at the runtime, by calling one or more functions included in the application, without an actual presentation of the first translation of the externalized content in the user interface, wherein an execution at the runtime of the one or more functions displays the externalized content in the user interface; the computer determining whether the simulating of the loading of the first translation of the externalized content into the user interface and the simulating of the presentation of the first translation of the externalized content in the user interface by the calling the one or more functions indicates an error condition that causes the application to stop running at the runtime; based in part on the error condition being indicated by the simulating of the loading of the first translation and the simulating of the presentation of the first translation, the computer: determining the first translation of the externalized content includes a syntax error that causes the error condition, generating a report including an identification of a portion of the first translation of the externalized content that includes the syntax error and an error message that is generated by the application at the runtime in response to the error condition, and initiating a correction of the syntax error by sending the report to the other computer, wherein the syntax error includes at least one of: (1) a first key included in the first translated file is not matched with exactly one corresponding first value in the first translated file, the first translated file being a first property file including first key-value pairs including the first key and the first value as one of the pairs; (2) a second key in the translatable file is not in the first translated file, the translatable file being a second property file including second key-value pairs, one of the second key-value pairs including the second key; and (3) one or more placeholders in the first translated file are not matched to respective one or more placeholders in the translatable file, the one or more placeholders in the first translated file and the one or more placeholders in the translatable file providing variable substitution by being filled in with actual values by the code of the application at the runtime; and based in part on the error condition being indicated by the simulating of the loading of the first translation and the simulating of the presentation of the first translation, subsequent to a completion by the other computer of the correction of the syntax error included in the first translation, and in response to a receipt by the computer of a second translation of the externalized content which includes the correction of the syntax error, the second translation included in a second translated file generated by the other computer: the computer simulating a loading of the second translation of the externalized content into the user interface of the application at the runtime and simulating a presentation of the second translation of the externalized content in the user interface at the runtime, by calling the one or more functions, without an actual presentation of the second translation of the externalized content in the user interface; and the computer determining whether the simulating of the loading of the second translation and the simulating of the presentation of the second translation by the calling the one or more functions indicates the error condition that causes the application to stop running at the runtime; and based in part on the error condition not being indicated by the simulating of the loading of the second translation and the simulating of the presentation of the second translation, the computer at the runtime presenting the second translation of the externalized content in the user interface without causing the application to stop running at the runtime. | 1. A method of validating translated files for inclusion in an application being developed, the method comprising the steps of: a computer sending a translatable file having externalized content in a single base natural language to a plurality of other computers, wherein the externalized content is external to code of the application being developed; in response to a generation of a first translated file including a first translation of the externalized content into a natural language other than the base natural language by another computer included in the plurality of other computers, the computer receiving the first translated file from the other computer; in a simulation environment, a processor of the computer simulating a loading of the first translation of the externalized content into a user interface of the application at a runtime of the application and simulating a presentation of the first translation of the externalized content in the user interface at the runtime, by calling one or more functions included in the application, without an actual presentation of the first translation of the externalized content in the user interface, wherein an execution at the runtime of the one or more functions displays the externalized content in the user interface; the computer determining whether the simulating of the loading of the first translation of the externalized content into the user interface and the simulating of the presentation of the first translation of the externalized content in the user interface by the calling the one or more functions indicates an error condition that causes the application to stop running at the runtime; based in part on the error condition being indicated by the simulating of the loading of the first translation and the simulating of the presentation of the first translation, the computer: determining the first translation of the externalized content includes a syntax error that causes the error condition, generating a report including an identification of a portion of the first translation of the externalized content that includes the syntax error and an error message that is generated by the application at the runtime in response to the error condition, and initiating a correction of the syntax error by sending the report to the other computer, wherein the syntax error includes at least one of: (1) a first key included in the first translated file is not matched with exactly one corresponding first value in the first translated file, the first translated file being a first property file including first key-value pairs including the first key and the first value as one of the pairs; (2) a second key in the translatable file is not in the first translated file, the translatable file being a second property file including second key-value pairs, one of the second key-value pairs including the second key; and (3) one or more placeholders in the first translated file are not matched to respective one or more placeholders in the translatable file, the one or more placeholders in the first translated file and the one or more placeholders in the translatable file providing variable substitution by being filled in with actual values by the code of the application at the runtime; and based in part on the error condition being indicated by the simulating of the loading of the first translation and the simulating of the presentation of the first translation, subsequent to a completion by the other computer of the correction of the syntax error included in the first translation, and in response to a receipt by the computer of a second translation of the externalized content which includes the correction of the syntax error, the second translation included in a second translated file generated by the other computer: the computer simulating a loading of the second translation of the externalized content into the user interface of the application at the runtime and simulating a presentation of the second translation of the externalized content in the user interface at the runtime, by calling the one or more functions, without an actual presentation of the second translation of the externalized content in the user interface; and the computer determining whether the simulating of the loading of the second translation and the simulating of the presentation of the second translation by the calling the one or more functions indicates the error condition that causes the application to stop running at the runtime; and based in part on the error condition not being indicated by the simulating of the loading of the second translation and the simulating of the presentation of the second translation, the computer at the runtime presenting the second translation of the externalized content in the user interface without causing the application to stop running at the runtime. 4. The method of claim 1 , further comprising the steps of: subsequent to the step of receiving the first translated file, the computer reformatting the first translated file to conform to requirements of the application; subsequent to the step of receiving the first translated file, the computer renaming the first translated file with a unique corresponding file name consisting of first, second and third portions, wherein the first portion of the file name indicates a language of the plurality of languages, the second portion of the file name indicates a country of a plurality of countries, and the third portion of the file name indicates a region of a plurality of regions, the region being within the country, and wherein the country and the region within the country together specify a variant of the language; the computer generating a file structure; and subsequent to the step of renaming, the computer storing the first translated file in a portion of the file structure identified by the first, second and third portions of the file name. | 0.673577 |
9,002,701 | 15 | 18 | 15. An electronic device comprising: an electronic document manager including at least a processor and memory configured to: receive search criteria for searching an electronic text; determine a current user position within the electronic text; determine text subgroups within the electronic text; select a text subgroup relating to the current user position within the electronic text and the search criteria; determine a similarity relationship between the search criteria and one or more text subgroups adjacent to the selected text subgroup; create a text cluster by associating the search criteria with the one or more adjacent text subgroups based on the determined similarity relationship to the search criteria; determine an activity indication of times when a user has read other text subgroups within the electronic text; determine a similarity relationship between the text cluster and the other text subgroups; link the text cluster to one of the other text subgroups based on the determined similarity relationship to the one of the other text subgroups; and a user interface configured to present a graphic representing the similarity relationship between the one of the other text subgroups and the text cluster based on the activity indication of times when the user read the other text subgroups. | 15. An electronic device comprising: an electronic document manager including at least a processor and memory configured to: receive search criteria for searching an electronic text; determine a current user position within the electronic text; determine text subgroups within the electronic text; select a text subgroup relating to the current user position within the electronic text and the search criteria; determine a similarity relationship between the search criteria and one or more text subgroups adjacent to the selected text subgroup; create a text cluster by associating the search criteria with the one or more adjacent text subgroups based on the determined similarity relationship to the search criteria; determine an activity indication of times when a user has read other text subgroups within the electronic text; determine a similarity relationship between the text cluster and the other text subgroups; link the text cluster to one of the other text subgroups based on the determined similarity relationship to the one of the other text subgroups; and a user interface configured to present a graphic representing the similarity relationship between the one of the other text subgroups and the text cluster based on the activity indication of times when the user read the other text subgroups. 18. The electronic device of claim 15 , wherein the electronic document manager is configured to: associate the graphic with the one of the other text subgroups; receive user input for selecting the graphic; and control the user interface to present content of the one of the other text subgroups associated with the selected graphic in response to receiving the user input. | 0.746955 |
8,473,491 | 16 | 17 | 16. A computer comprising: memory; a processor coupled to the memory, the processor being operable to: access a list of legitimate business titles stored in the memory, each legitimate business title including one or more words; generate a matrix of surprisingness values by: examining each legitimate business title to identify pairs of words occurring in that title; adding a count value to the matrix for each pair of words identified, such that the matrix includes a plurality of count values for different pairs of words occurring in the legitimate business titles; normalizing the plurality of count values for the matrix to generate the matrix of surprisingness values, where each surprisingness value of the matrix of surprisingness values indicates how unlikely a pair of words are to appear in a legitimate business title; store the matrix of surprisingness values in the memory; access a plurality of business listings stored in the memory, each business listing of the plurality of business listings associated with title data including one or more words; select a particular business listing of the plurality of business listings; determine a surprisingness value indicative of the surprisingness of the title included in the particular business listing based on the matrix of surprisingness values stored in the memory; and determine whether the particular business listing is legitimate based on whether the surprisingness value is less than a threshold value. | 16. A computer comprising: memory; a processor coupled to the memory, the processor being operable to: access a list of legitimate business titles stored in the memory, each legitimate business title including one or more words; generate a matrix of surprisingness values by: examining each legitimate business title to identify pairs of words occurring in that title; adding a count value to the matrix for each pair of words identified, such that the matrix includes a plurality of count values for different pairs of words occurring in the legitimate business titles; normalizing the plurality of count values for the matrix to generate the matrix of surprisingness values, where each surprisingness value of the matrix of surprisingness values indicates how unlikely a pair of words are to appear in a legitimate business title; store the matrix of surprisingness values in the memory; access a plurality of business listings stored in the memory, each business listing of the plurality of business listings associated with title data including one or more words; select a particular business listing of the plurality of business listings; determine a surprisingness value indicative of the surprisingness of the title included in the particular business listing based on the matrix of surprisingness values stored in the memory; and determine whether the particular business listing is legitimate based on whether the surprisingness value is less than a threshold value. 17. The computer of claim 16 , wherein the processor is further operable to determine that the particular business listing is fraudulent if the surprisingness value does not satisfy the threshold value. | 0.849478 |
9,165,011 | 11 | 12 | 11. The computer system of claim 7 , wherein the overall match score is calculated by a formula
[(qualification match score)+(availability match score)]/2=overall match score. | 11. The computer system of claim 7 , wherein the overall match score is calculated by a formula
[(qualification match score)+(availability match score)]/2=overall match score. 12. The computer system of claim 11 , wherein the availability match score is compared to an availability match score threshold. | 0.973888 |
10,104,233 | 12 | 16 | 12. A method of providing coaching assessment based on behavioral assessment data across one or more recorded communications, which comprises: analyzing, by a server, one or more communications between a customer and an agent, wherein the analysis comprises instructions that, when executed, apply a linguistic-based psychological behavioral model to separated voice data for the customer, the agent, or both, from each communication by analyzing behavioral characteristics of the customer, the agent, or both, based on the one or more communications; identifying one or more customer-agent interaction events based on the analyzed behavioral characteristics; and displaying a time-based graphic representation including a plurality of the identified customer-agent interaction events across a selected time interval based on one or more communications. | 12. A method of providing coaching assessment based on behavioral assessment data across one or more recorded communications, which comprises: analyzing, by a server, one or more communications between a customer and an agent, wherein the analysis comprises instructions that, when executed, apply a linguistic-based psychological behavioral model to separated voice data for the customer, the agent, or both, from each communication by analyzing behavioral characteristics of the customer, the agent, or both, based on the one or more communications; identifying one or more customer-agent interaction events based on the analyzed behavioral characteristics; and displaying a time-based graphic representation including a plurality of the identified customer-agent interaction events across a selected time interval based on one or more communications. 16. The method of claim 12 , wherein the displaying a time-based graphic representation comprises displaying a call statistics visual field selectable by a user to display statistics pertaining to the one or more customer-agent interaction events. | 0.791385 |
8,024,327 | 1 | 26 | 1. In an information retrieval system, a computer-implemented method for information processing, comprising: accessing, by a computer system, a set of documents obtained from the information retrieval system; establishing, automatically by the computer system, at least one identifying characteristic within the set of documents; analyzing, by the computer system, the set of documents to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; computing a value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; normalizing the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, and the act of normalizing the value includes an act of performing a computation on the value that accounts for the given size of the set of documents; and outputting a response derived from the normalized value. | 1. In an information retrieval system, a computer-implemented method for information processing, comprising: accessing, by a computer system, a set of documents obtained from the information retrieval system; establishing, automatically by the computer system, at least one identifying characteristic within the set of documents; analyzing, by the computer system, the set of documents to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; computing a value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; normalizing the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, and the act of normalizing the value includes an act of performing a computation on the value that accounts for the given size of the set of documents; and outputting a response derived from the normalized value. 26. The method according to claim 1 , wherein the act of computing the value of the function that measures distinctiveness further comprising acts of: determining a similarity measure; and inverting the sense of the similarity measure. | 0.815831 |
8,576,430 | 1 | 20 | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. | 1. A method for determining a print job schedule for a printing production facility having a set of availably printing resources, comprising: defining one or more scheduling classifications; receiving one or more print jobs, each print job having a print job description specified by a set of print job attributes; determining one or more scheduling classification corresponding to the received print jobs; using a processor to automatically determine the print job schedule for the received print jobs using an answer set programming language solver responsive to: the print job descriptions; a set of resource descriptions for the available printing resources; a set of scheduling rules, wherein the scheduling rules are answer set programming statements; and a historical decision database stored in a processor accessible memory, wherein the historical decision database stores an indication of previously successful decision frequencies as a function of scheduling classification; wherein the print job schedule assigns a time schedule and one or more printing resources for each of the received print jobs. 20. The method of claim 1 wherein the printing resources include printing device resources, finishing resources, consumable materials resources, or operator resources. | 0.625561 |
8,688,451 | 1 | 10 | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user via a microphone associated with an automatic speech recognition system; (b) processing the input speech using a first grammar to obtain parameter values of a first N-best list of vocabulary using at least one processor associated with the automatic speech recognition system; (c) comparing at least one parameter value of a top result of the first N-best list to at least one predetermined threshold value; and (d) subsequently processing the input speech using a second grammar to obtain parameter values of a second N-best list of vocabulary, if the compared at least one parameter value is below the at least one predetermined threshold value; (e) determining the input speech to be in-vocabulary, if any of the results of the first N-best list is also present within the second N-best list, but out-of vocabulary if any of the results of the first N-best list is not within the second N-best list; and (f) providing audible feedback to the user if the input speech is determined to be out-of-vocabulary. | 1. A speech recognition method comprising the steps of: (a) receiving input speech from a user via a microphone associated with an automatic speech recognition system; (b) processing the input speech using a first grammar to obtain parameter values of a first N-best list of vocabulary using at least one processor associated with the automatic speech recognition system; (c) comparing at least one parameter value of a top result of the first N-best list to at least one predetermined threshold value; and (d) subsequently processing the input speech using a second grammar to obtain parameter values of a second N-best list of vocabulary, if the compared at least one parameter value is below the at least one predetermined threshold value; (e) determining the input speech to be in-vocabulary, if any of the results of the first N-best list is also present within the second N-best list, but out-of vocabulary if any of the results of the first N-best list is not within the second N-best list; and (f) providing audible feedback to the user if the input speech is determined to be out-of-vocabulary. 10. The method of claim 1 , further comprising the step of creating the second grammar by generating a limited set of vocabulary that does not include triphones or pentaphones of words of the in-vocabulary first grammar. | 0.52381 |
9,338,018 | 16 | 20 | 16. The method of claim 15 , wherein defining the hierarchical structure of pricing models comprises setting a root pricing model for the set of billable items within the telephony communications platform system and setting a set of pricing sub-models that sparsely over-ride at least a portion of the root pricing model for a subset of the billable items in the telephony communication platform system. | 16. The method of claim 15 , wherein defining the hierarchical structure of pricing models comprises setting a root pricing model for the set of billable items within the telephony communications platform system and setting a set of pricing sub-models that sparsely over-ride at least a portion of the root pricing model for a subset of the billable items in the telephony communication platform system. 20. The method of claim 16 , wherein setting a set of pricing sub-model comprises setting at least one pricing sub-model that defines a tiered pricing function that is dependent on usage. | 0.981448 |
9,946,788 | 6 | 8 | 6. The system of claim 1 , wherein the at least one server is configured to: receive said URL for said web page from said web browser; and parse at least one of said URL and said content of said web page to generate said document feature vector of said URL or of said content of said web page. | 6. The system of claim 1 , wherein the at least one server is configured to: receive said URL for said web page from said web browser; and parse at least one of said URL and said content of said web page to generate said document feature vector of said URL or of said content of said web page. 8. The system of claim 6 , wherein the at least one server is configured to: generate said document feature vector of said URL or of said content of said web page prior to said receipt of said URL from said web browser; store said document feature vector of said URL or said content of said content of said web page in a database; and retrieve the document feature vector from said database in real time in response to said receipt of said URL from said web browser. | 0.818677 |
8,667,051 | 1 | 4 | 1. A method for communication processing, the method comprising: storing, by a client device, information records comprising a table of one or more keywords and associated operative functions, the table having at least one keyword programmed by a user of the client device; determining, by the client device, whether audio or text data of a broadcast includes one or more broadcasted keywords; and performing, by the client device, a series of the associated operative functions based on said one or more broadcasted keywords in response to determining that the one or more broadcasted keywords match one or more of the keywords in the table, while concurrently presenting output corresponding to said audio or text data during said broadcast, wherein the series of said associated operative functions comprises at least four of: placing a call using the one or more broadcasted keywords; comparing a performance history associated with the one or more broadcasted keywords; storing contact information derived from the one or more broadcasted keywords; determining a domain name having the one or more broadcasted keywords at least partially therein and generating a hyperlink from the domain name; searching a database device for advertising associated with the one or more broadcasted keywords; and performing an Internet search with the one or more broadcasted keywords. | 1. A method for communication processing, the method comprising: storing, by a client device, information records comprising a table of one or more keywords and associated operative functions, the table having at least one keyword programmed by a user of the client device; determining, by the client device, whether audio or text data of a broadcast includes one or more broadcasted keywords; and performing, by the client device, a series of the associated operative functions based on said one or more broadcasted keywords in response to determining that the one or more broadcasted keywords match one or more of the keywords in the table, while concurrently presenting output corresponding to said audio or text data during said broadcast, wherein the series of said associated operative functions comprises at least four of: placing a call using the one or more broadcasted keywords; comparing a performance history associated with the one or more broadcasted keywords; storing contact information derived from the one or more broadcasted keywords; determining a domain name having the one or more broadcasted keywords at least partially therein and generating a hyperlink from the domain name; searching a database device for advertising associated with the one or more broadcasted keywords; and performing an Internet search with the one or more broadcasted keywords. 4. The method, as set forth in claim 1 , wherein searching for advertising associated with the one or more broadcasted keywords comprises searching an advertising cache. | 0.837187 |
9,842,096 | 15 | 20 | 15. An apparatus comprising: a processor, and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive, by a natural language processing pipeline configured to execute in the data processing system, an input document to be ingested into a corpus; divide, by the natural language processing pipeline, the input document into a plurality of input passages; identify, by a filter component of the natural language processing pipeline, whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter, by the natural language processing pipeline, each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add, by the natural language processing pipeline, the filtered plurality of input passages into the corpus. | 15. An apparatus comprising: a processor, and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive, by a natural language processing pipeline configured to execute in the data processing system, an input document to be ingested into a corpus; divide, by the natural language processing pipeline, the input document into a plurality of input passages; identify, by a filter component of the natural language processing pipeline, whether each input passage is a nonsense passage based on a value of a metric determined according to a set of feature counts, wherein identifying whether a given input passage is a nonsense passage comprises: annotating, by an annotator in the natural language processing pipeline, the given input passage within the plurality of input passages with linguistic features to form an annotated passage; counting, by metric counters component in the natural language processing pipeline, a number of instances of each type of linguistic feature in the annotated passage to form a set of feature counts; determining, by the metric counters component of the natural language processing pipeline, a value for a metric based on the set of feature counts; and comparing, by a comparator component of the natural language processing pipeline, the value for the metric to a predetermined model threshold; filter, by the natural language processing pipeline, each input passage in the plurality of input passages based on whether the input passage is identified as a nonsense passage or not identified as a nonsense passage to form a filtered plurality of input passages; and add, by the natural language processing pipeline, the filtered plurality of input passages into the corpus. 20. The apparatus of claim 15 , wherein the metric and the predetermined model threshold are defined in a profile data structure. | 0.819832 |
8,700,696 | 1 | 11 | 1. A method for promoting awareness of products and services of an advertising sponsor during at least one online event, the method implemented on a central website system comprising a plurality of services accessible to a plurality of users over the Internet, the method comprising: a. in response to receiving input at the central website system from a first user, processing, building, designing, loading, controlling, formatting, and/or setting up at least one online event, wherein the at least one online event is associated with at least one interest; b. in response to receiving a selection of the at least one interest by an advertising sponsor, releasing a list of online events comprising the at least one online event; c. in response to receiving a selection of the at least one online event from the list of online events, processing, building, designing, loading, controlling, formatting, and/or setting up at least one advertising display associated with the advertising sponsor, the at least one advertising display comprising at least one of: a panel, a banner, a button, a link, a navigation bar, a click-on area, a display, a bridge, online content, multimedia content, an exhibit, a demonstration, a presentation, a brochure, a video, a movie, a photograph, a still image, an audio recording, or any combination thereof; d. providing a plurality of control parameters to the at least one advertising sponsor, and responsive to a selection of at least one control parameter by the advertising sponsor, electronically setting, loading, inputting, placing, designing, and/or controlling at least one of: i) a preferred presentation location of the at least one advertising display, ii) at least one exposure factor associated with the at least one advertising display, iii) a specified presentation frequency of the at least one advertising display, iv) a packaging arrangement associated with the at least one advertising display, v) at least one fee option associated with the at least one advertising display, vi) at least one recognition factor associated with the at least one advertising display, or any combination thereof; e. receiving, from at least one second user at the central website system, a search for at least one interest associated with the at least one online event; f. storing, in the database at the central website system, the at least one interest in the profile record associated with the at least one second user; g. facilitating, at the central website system, participation by the first user and the at least one second user in the at least one online event associated with the at least one interest; h. based at least partially on an association between the at least one interest and the at least one advertising display, processing the at least one advertising display at the central website system; and i. during the at least one online event, releasing, from the central website system, to at least one of the first user and the at least one second user, at least a portion of the at least one advertising display. | 1. A method for promoting awareness of products and services of an advertising sponsor during at least one online event, the method implemented on a central website system comprising a plurality of services accessible to a plurality of users over the Internet, the method comprising: a. in response to receiving input at the central website system from a first user, processing, building, designing, loading, controlling, formatting, and/or setting up at least one online event, wherein the at least one online event is associated with at least one interest; b. in response to receiving a selection of the at least one interest by an advertising sponsor, releasing a list of online events comprising the at least one online event; c. in response to receiving a selection of the at least one online event from the list of online events, processing, building, designing, loading, controlling, formatting, and/or setting up at least one advertising display associated with the advertising sponsor, the at least one advertising display comprising at least one of: a panel, a banner, a button, a link, a navigation bar, a click-on area, a display, a bridge, online content, multimedia content, an exhibit, a demonstration, a presentation, a brochure, a video, a movie, a photograph, a still image, an audio recording, or any combination thereof; d. providing a plurality of control parameters to the at least one advertising sponsor, and responsive to a selection of at least one control parameter by the advertising sponsor, electronically setting, loading, inputting, placing, designing, and/or controlling at least one of: i) a preferred presentation location of the at least one advertising display, ii) at least one exposure factor associated with the at least one advertising display, iii) a specified presentation frequency of the at least one advertising display, iv) a packaging arrangement associated with the at least one advertising display, v) at least one fee option associated with the at least one advertising display, vi) at least one recognition factor associated with the at least one advertising display, or any combination thereof; e. receiving, from at least one second user at the central website system, a search for at least one interest associated with the at least one online event; f. storing, in the database at the central website system, the at least one interest in the profile record associated with the at least one second user; g. facilitating, at the central website system, participation by the first user and the at least one second user in the at least one online event associated with the at least one interest; h. based at least partially on an association between the at least one interest and the at least one advertising display, processing the at least one advertising display at the central website system; and i. during the at least one online event, releasing, from the central website system, to at least one of the first user and the at least one second user, at least a portion of the at least one advertising display. 11. The method according to claim 1 , further comprising broadcasting, from the central website system, using at least one of an audio streaming technique and a video streaming technique, to at least one of the first user and the at least one second user. | 0.73873 |
8,112,412 | 4 | 5 | 4. The method of claim 1 wherein identifying at least one executable file of the same specific category with an acceptable reputational score further comprises: examining categorization data pertaining to executable files in the database; and identifying categorization data in the database concerning at least one executable file with an acceptable reputational score, the identified categorization data comprising indications of extracted terms related to those of the executable file with the unacceptable reputational score. | 4. The method of claim 1 wherein identifying at least one executable file of the same specific category with an acceptable reputational score further comprises: examining categorization data pertaining to executable files in the database; and identifying categorization data in the database concerning at least one executable file with an acceptable reputational score, the identified categorization data comprising indications of extracted terms related to those of the executable file with the unacceptable reputational score. 5. The method of claim 4 wherein identifying at least one executable file of the same specific category with an acceptable reputational score, the identified categorization data comprising indications of extracted terms related to those of the executable file with the unacceptable reputational score, further comprises: applying at least one machine learning technique to categorization data corresponding to executable files in the database, to identify contextually related groups of terms pertaining to executable files with acceptable reputations. | 0.850163 |
10,089,072 | 1 | 4 | 1. An electronic device comprising: a microphone; one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: sampling, with the microphone at the electronic device, an audio input specifying a task, wherein the electronic device is a first electronic device; identifying, with the first electronic device, a confidence value indicative of a likelihood that the audio input was provided by a particular user; broadcasting a first set of one or more values based on the sampled audio input, wherein a first value of the first set of values is based on the confidence value; receiving a second set of one or more values from a second electronic device, wherein the second set of one or more values is based on the audio input; determining, with the first electronic device, whether a type of the first electronic device meets a requirement of the task; and in accordance with a determination that the type of the first electronic device meets the requirement of the task: determining whether the first electronic device is to respond to the audio input based on the first set of one or more values, the second set of one or more values, and the requirement of the task; in accordance with a determination that the first electronic device is to respond to the audio input, responding to the audio input; and in accordance with a determination that the first electronic device is not to respond to the audio input, foregoing responding to the audio input; and in accordance with a determination that the type of the first electronic device does not meet the requirement of the task, foregoing responding to the audio input with the first electronic device. | 1. An electronic device comprising: a microphone; one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: sampling, with the microphone at the electronic device, an audio input specifying a task, wherein the electronic device is a first electronic device; identifying, with the first electronic device, a confidence value indicative of a likelihood that the audio input was provided by a particular user; broadcasting a first set of one or more values based on the sampled audio input, wherein a first value of the first set of values is based on the confidence value; receiving a second set of one or more values from a second electronic device, wherein the second set of one or more values is based on the audio input; determining, with the first electronic device, whether a type of the first electronic device meets a requirement of the task; and in accordance with a determination that the type of the first electronic device meets the requirement of the task: determining whether the first electronic device is to respond to the audio input based on the first set of one or more values, the second set of one or more values, and the requirement of the task; in accordance with a determination that the first electronic device is to respond to the audio input, responding to the audio input; and in accordance with a determination that the first electronic device is not to respond to the audio input, foregoing responding to the audio input; and in accordance with a determination that the type of the first electronic device does not meet the requirement of the task, foregoing responding to the audio input with the first electronic device. 4. The electronic device of claim 1 , wherein the one or more programs further include instructions for: identifying, with the first electronic device, a state of the first electronic device, wherein a value of the first set of values is based on the identified state of the first electronic device. | 0.775526 |
10,135,680 | 15 | 20 | 15. A computer program product for configuring a computing system comprising: a computer readable storage medium having computer readable program code embodied therewith for execution on a processing system, the computer readable program code comprising computer readable program code configured to: analyze an environment specification document specifying a proposed configuration with changes to a full-stack environment for the computing system and describing an infrastructure, middleware, and application elements; correlate the environment specification document with an environment instantiated on the computing system from the environment specification document prior to the changes; monitor activity of the environment instantiated on the computing system; determine an impact of the changes in the proposed configuration on the environment instantiated on the computing system prior to implementing the changes, wherein the changes include rendering an application unavailable and the impact is based on usage information pertaining to the application obtained during the monitoring; and configure the computing system in accordance with the proposed configuration based on the determined impact. | 15. A computer program product for configuring a computing system comprising: a computer readable storage medium having computer readable program code embodied therewith for execution on a processing system, the computer readable program code comprising computer readable program code configured to: analyze an environment specification document specifying a proposed configuration with changes to a full-stack environment for the computing system and describing an infrastructure, middleware, and application elements; correlate the environment specification document with an environment instantiated on the computing system from the environment specification document prior to the changes; monitor activity of the environment instantiated on the computing system; determine an impact of the changes in the proposed configuration on the environment instantiated on the computing system prior to implementing the changes, wherein the changes include rendering an application unavailable and the impact is based on usage information pertaining to the application obtained during the monitoring; and configure the computing system in accordance with the proposed configuration based on the determined impact. 20. The computer program product of claim 15 , wherein determining an impact of the changes in the proposed configuration comprises: analyzing results accumulated from instantiations of prior proposed configurations to learn iteratively from the impacts from those prior proposed configurations; and determining the impact of the changes in the proposed configuration based on the accumulated learned impacts from the prior proposed configurations. | 0.61512 |
9,672,279 | 1 | 13 | 1. An apparatus comprising: a processing platform configured to implement a cluster labeling system for documents comprising unstructured text data from a service events database; the unstructured text data comprising unstructured service request summaries relating to respective service events; wherein the cluster labeling system comprises: a clustering module implementing a topic model generator and being configured to assign each of the documents to one or more of a plurality of clusters based at least in part on one or more topics identified from the unstructured text data using at least one topic model provided by the topic model generator; a visualization module comprising multiple view generators, the multiple view generators being configured to generate respective distinct visualizations of a selected one of the clusters; and a labeling interface permitting user entry of a label for the selected cluster; wherein the multiple view generators comprise at least: a bigram view generator configured to provide a visualization of a plurality of term pairs from the selected cluster; and a summarization view generator configured to provide a visualization of representative term sequences from the selected cluster; wherein the cluster labeling system is further configured to update the service events database to indicate a user-entered label for the selected cluster; and wherein the processing platform comprises one or more processing devices each comprising a processor coupled to a memory. | 1. An apparatus comprising: a processing platform configured to implement a cluster labeling system for documents comprising unstructured text data from a service events database; the unstructured text data comprising unstructured service request summaries relating to respective service events; wherein the cluster labeling system comprises: a clustering module implementing a topic model generator and being configured to assign each of the documents to one or more of a plurality of clusters based at least in part on one or more topics identified from the unstructured text data using at least one topic model provided by the topic model generator; a visualization module comprising multiple view generators, the multiple view generators being configured to generate respective distinct visualizations of a selected one of the clusters; and a labeling interface permitting user entry of a label for the selected cluster; wherein the multiple view generators comprise at least: a bigram view generator configured to provide a visualization of a plurality of term pairs from the selected cluster; and a summarization view generator configured to provide a visualization of representative term sequences from the selected cluster; wherein the cluster labeling system is further configured to update the service events database to indicate a user-entered label for the selected cluster; and wherein the processing platform comprises one or more processing devices each comprising a processor coupled to a memory. 13. An information processing system comprising the apparatus of claim 1 . | 0.92449 |
8,739,055 | 1 | 6 | 1. A method of correcting typographical errors displayed on a touch-sensitive display of a portable computing device, the method comprising: identifying a typographical error within text displayed on the display, the typographical error comprising an error within a word displayed on the display; upon identifying the typographical error, highlighting on the display the typographical error; detecting a gesture-based touch input selecting a cursor key from a virtual keyboard displayed on the display and displaying a cursor in response to the gesture-based touch input; detecting a change in a location of the gesture-based touch input, and in response, moving a location of an image of the cursor displayed on the display in correspondence with the gesture-based touch input; detecting a release of the gesture-based touch input; if the release of the gesture-based touch input is detected within a predefined region associated with a location of the typographical error, displaying on the display the cursor next to the typographical error; and responsive to the cursor being displayed next to the typographical error, replacing the typographical error with replacement text input from the virtual keyboard. | 1. A method of correcting typographical errors displayed on a touch-sensitive display of a portable computing device, the method comprising: identifying a typographical error within text displayed on the display, the typographical error comprising an error within a word displayed on the display; upon identifying the typographical error, highlighting on the display the typographical error; detecting a gesture-based touch input selecting a cursor key from a virtual keyboard displayed on the display and displaying a cursor in response to the gesture-based touch input; detecting a change in a location of the gesture-based touch input, and in response, moving a location of an image of the cursor displayed on the display in correspondence with the gesture-based touch input; detecting a release of the gesture-based touch input; if the release of the gesture-based touch input is detected within a predefined region associated with a location of the typographical error, displaying on the display the cursor next to the typographical error; and responsive to the cursor being displayed next to the typographical error, replacing the typographical error with replacement text input from the virtual keyboard. 6. The method of claim 1 , further comprising, if the release of the gesture-based touch input is detected outside of the predefined region associated with the location of the typographical error, removing the image of the cursor from the display. | 0.550909 |
8,296,152 | 1 | 12 | 1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification. | 1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification. 12. The method of claim 1 further comprising accessing an approved topics list associated with the first participant, and wherein determining, by the processing device, the at least one topic based on the at least one term further comprises determining the at least one topic based on the at least one term and the approved topics list. | 0.771117 |
9,514,737 | 1 | 4 | 1. A navigation apparatus including a voice receiver to receive an instruction by voice input, and a voice recognizer to carry out voice recognition of the instruction received by the voice receiver, the navigation apparatus comprising: a recognition vocabulary comprehension level decider to decide a user comprehension level of a recognition vocabulary for instructions recognizable by the voice recognizer, from at least one of correction operation frequency and time-out frequency in an operation of recognizing the instruction which is carried out during the voice recognition by the voice recognizer and corresponds to the instruction; an operational transition determiner to determine an operational transition from a plurality of potential operational transitions in accordance with a decision result of the recognition vocabulary comprehension level decider, each of the potential operational transitions including a different number of input steps by which the instruction is voice-recognized, such that different input steps correspond to different subsets of the recognition vocabulary for each potential operation transition that includes multiple input steps; and an operational transition provider to provide the operational transition determined by the operational transition determiner, wherein the operational transition determiner, when determining the operational transition in accordance with the decision result output from the recognition vocabulary comprehension level decider, switches the operational transition thereby limiting an input content per step by increasing the number of input steps in a specific operational transition, or reducing the number of input steps by increasing an amount of information capable of being input per step in the specific operational transition. | 1. A navigation apparatus including a voice receiver to receive an instruction by voice input, and a voice recognizer to carry out voice recognition of the instruction received by the voice receiver, the navigation apparatus comprising: a recognition vocabulary comprehension level decider to decide a user comprehension level of a recognition vocabulary for instructions recognizable by the voice recognizer, from at least one of correction operation frequency and time-out frequency in an operation of recognizing the instruction which is carried out during the voice recognition by the voice recognizer and corresponds to the instruction; an operational transition determiner to determine an operational transition from a plurality of potential operational transitions in accordance with a decision result of the recognition vocabulary comprehension level decider, each of the potential operational transitions including a different number of input steps by which the instruction is voice-recognized, such that different input steps correspond to different subsets of the recognition vocabulary for each potential operation transition that includes multiple input steps; and an operational transition provider to provide the operational transition determined by the operational transition determiner, wherein the operational transition determiner, when determining the operational transition in accordance with the decision result output from the recognition vocabulary comprehension level decider, switches the operational transition thereby limiting an input content per step by increasing the number of input steps in a specific operational transition, or reducing the number of input steps by increasing an amount of information capable of being input per step in the specific operational transition. 4. The navigation apparatus according to claim 1 , further comprising: a keyword extractor to extract a specific keyword from the content recognized by the voice recognizer, wherein the operational transition determiner determines the operational transition in accordance with the keyword in past utterance in the transition and the recognition vocabulary comprehension level. | 0.585903 |
10,134,050 | 17 | 25 | 17. A system for facilitating use of mobile devices to respond to questions submitted to a question and answer customer support system, to reduced unanswered questions maintained in the question and answer customer support system, the system comprising: at least one processor; and at least one memory coupled to the at least one processor, the at least one memory having stored therein instructions which, when executed by any set of the one or more processors, perform: training, using a computing system, predictive models using historical question and answer data, the training resulting in at least one predictive model configured to estimate, based on a received question, an expected answer length, determine whether an answer to the question is likely to include a web link, and determine whether a question answerer is more likely than not to have to perform research in order to answer the question; receiving, with a computing system having a processor and a memory, a first question from a user having a first type; determining that the received question is a first type of question and forming and sending a response to the user with recommendations for the user to reform the question into a different type; receiving a reformed first question from the user, the reformed question being the first question transformed into a second type of question; analyzing, using the one or more predictive models, the reformed first question with a question and answer customer support system of the computing system by determining one or more attributes of the reformed first question and determining that the reformed first question is a mobile device answerable question, because one or more of the determined one or more attributes of the reformed first question satisfy one or more mobile device question criteria; prioritizing, using the computing system, the answering of the reformed first question over the answering of questions that are not mobile device answerable questions; configuring multiple user interface elements, at least partially based on the one or more attributes of the reformed first question by at least prepopulating the user interface elements to include at least one proposed answer to the reformed first question; and providing the user interface elements with the question and answer customer support system for display in a user interface on the mobile device of a first question answerer. | 17. A system for facilitating use of mobile devices to respond to questions submitted to a question and answer customer support system, to reduced unanswered questions maintained in the question and answer customer support system, the system comprising: at least one processor; and at least one memory coupled to the at least one processor, the at least one memory having stored therein instructions which, when executed by any set of the one or more processors, perform: training, using a computing system, predictive models using historical question and answer data, the training resulting in at least one predictive model configured to estimate, based on a received question, an expected answer length, determine whether an answer to the question is likely to include a web link, and determine whether a question answerer is more likely than not to have to perform research in order to answer the question; receiving, with a computing system having a processor and a memory, a first question from a user having a first type; determining that the received question is a first type of question and forming and sending a response to the user with recommendations for the user to reform the question into a different type; receiving a reformed first question from the user, the reformed question being the first question transformed into a second type of question; analyzing, using the one or more predictive models, the reformed first question with a question and answer customer support system of the computing system by determining one or more attributes of the reformed first question and determining that the reformed first question is a mobile device answerable question, because one or more of the determined one or more attributes of the reformed first question satisfy one or more mobile device question criteria; prioritizing, using the computing system, the answering of the reformed first question over the answering of questions that are not mobile device answerable questions; configuring multiple user interface elements, at least partially based on the one or more attributes of the reformed first question by at least prepopulating the user interface elements to include at least one proposed answer to the reformed first question; and providing the user interface elements with the question and answer customer support system for display in a user interface on the mobile device of a first question answerer. 25. The system of claim 17 , wherein the question and answer customer support system is a component of a software system selected from a group of software systems consisting of: a computing system implemented tax preparation software system; a network accessed tax preparation software system; a web-based tax preparation software system; a cloud-based tax preparation software system; a computing system implemented business management software system; a network accessed business management software system; a web-based business management software system; a cloud-based business management software system; a computing system implemented accounting software system; a network accessed accounting software system; a web-based accounting software system; a cloud-based accounting software system; a computing system implemented financial management system; a network accessed financial management system; a web-based financial management system; and a cloud-based financial management system. | 0.500503 |
9,468,848 | 17 | 20 | 17. A computer-readable storage device for assigning a gesture dictionary, bearing computer-executable instructions that, when executed on a computer, cause the computer to perform operations comprising: determining a characteristic of a user that is independent of a motion or pose made by the user; correlating the characteristic of the user to a first gesture dictionary of a plurality of gesture dictionaries, each gesture dictionary of the plurality of gesture dictionaries identifying a set of input commands to the computer that may be invoked by a performance of a corresponding gesture; assigning the first gesture dictionary to the user, the first gesture dictionary corresponding to the characteristic; and processing captured data with the first gesture dictionary to identify whether a second motion or pose by the user in the captured data invokes an input command to the computer. | 17. A computer-readable storage device for assigning a gesture dictionary, bearing computer-executable instructions that, when executed on a computer, cause the computer to perform operations comprising: determining a characteristic of a user that is independent of a motion or pose made by the user; correlating the characteristic of the user to a first gesture dictionary of a plurality of gesture dictionaries, each gesture dictionary of the plurality of gesture dictionaries identifying a set of input commands to the computer that may be invoked by a performance of a corresponding gesture; assigning the first gesture dictionary to the user, the first gesture dictionary corresponding to the characteristic; and processing captured data with the first gesture dictionary to identify whether a second motion or pose by the user in the captured data invokes an input command to the computer. 20. The computer-readable storage device of claim 17 , wherein correlating the characteristic of the user to the first gesture dictionary comprises: correlating the characteristic of the user to a cluster of gesture dictionaries. | 0.696286 |
8,396,714 | 13 | 19 | 13. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors, cause the one or more processors to perform operations comprising: obtaining phonemes for a text string, the text string comprising at least a preceding word and a succeeding word to be concatenated; identifying a last letter of the preceding word to be concatenated, and identifying a first letter of the succeeding word to be concatenated; selecting a connector term and a connector term type based on the identified last letter and the identified first letter; and creating a modified text string for speech synthesis including the selected connector term and the selected connector type. | 13. A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors, cause the one or more processors to perform operations comprising: obtaining phonemes for a text string, the text string comprising at least a preceding word and a succeeding word to be concatenated; identifying a last letter of the preceding word to be concatenated, and identifying a first letter of the succeeding word to be concatenated; selecting a connector term and a connector term type based on the identified last letter and the identified first letter; and creating a modified text string for speech synthesis including the selected connector term and the selected connector type. 19. The computer-readable medium of claim 13 , wherein the operations further comprise: synthesizing a speech segment based on the modified text string; and combining the media asset with the synthesized speech segment into a single file. | 0.564103 |
8,219,615 | 2 | 6 | 2. The computer program product of claim 1 , wherein the computer program product is configured such that: each of the plurality of n-tuples includes only the first text representing the stock ticker symbol and the second text representing the company name corresponding to the stock ticker symbol, the indicating comprises displaying both the first text representing the stock ticker symbol and the second text representing the company name corresponding to the stock ticker symbol in the at least one of the plurality of n-tuples such that the first text precedes the second text, the indicating further comprises displaying multiple n-tuples in a vertically-oriented list directly beneath the stock-related field, the indicating further comprises visually emphasizing a subset of text in at least one of the text strings of each of the multiple n-tuples in the vertically-oriented list with the subset of text matching the at least portion of characters typed so far, and further comprising: computer code for allowing receipt of selection input initiated by the user selecting one of the multiple n-tuples from the vertically-oriented list; and computer code for using at least one of the text strings from the selected one of the multiple n-tuples in connection with the stock-related field. | 2. The computer program product of claim 1 , wherein the computer program product is configured such that: each of the plurality of n-tuples includes only the first text representing the stock ticker symbol and the second text representing the company name corresponding to the stock ticker symbol, the indicating comprises displaying both the first text representing the stock ticker symbol and the second text representing the company name corresponding to the stock ticker symbol in the at least one of the plurality of n-tuples such that the first text precedes the second text, the indicating further comprises displaying multiple n-tuples in a vertically-oriented list directly beneath the stock-related field, the indicating further comprises visually emphasizing a subset of text in at least one of the text strings of each of the multiple n-tuples in the vertically-oriented list with the subset of text matching the at least portion of characters typed so far, and further comprising: computer code for allowing receipt of selection input initiated by the user selecting one of the multiple n-tuples from the vertically-oriented list; and computer code for using at least one of the text strings from the selected one of the multiple n-tuples in connection with the stock-related field. 6. The computer program product of claim 2 , wherein the computer program product is operable such that first indicia is displayed with particular web content for use in connection with at least one aspect of the posting in association with the particular web content on the website in response to a selection thereof and an interface is displayed for allowing the user to type the new message, and further wherein the computer program product is operable such that the user is capable of posting the new message to both: the website which manages the particular web content and a different website which does not manage the particular web content. | 0.879599 |
9,749,693 | 1 | 8 | 1. A method comprising: generating for display a mosaic page including a plurality of cells; retrieving a user preference from a memory; comparing, using control circuitry, data, associated with each of a plurality of categories, with the user preference, wherein each of the plurality of categories describes a plurality of media assets; in response to determining, based on the comparison, that the data associated with a respective one of the plurality of categories matches the user preference, adding the respective one of the plurality of categories to a subset of categories; associating each cell of the plurality of cells, in which video is displayed, with a respective category of content of the subset of categories of content that match the user preference, such that a first of the plurality of cells displays a first video associated with a first of the plurality of categories and a second of the plurality of cells displays a second video associated with a second of the plurality of categories; determining, using control circuitry, for each respective cell of the plurality of cells, a respective media asset, from the plurality of media assets associated with the category associated with the respective cell, that is most relevant to the user based on the retrieved user preference wherein the plurality of media assets include the first and second videos; and generating for display the respective relevant media asset in each respective cell of the plurality of cells. | 1. A method comprising: generating for display a mosaic page including a plurality of cells; retrieving a user preference from a memory; comparing, using control circuitry, data, associated with each of a plurality of categories, with the user preference, wherein each of the plurality of categories describes a plurality of media assets; in response to determining, based on the comparison, that the data associated with a respective one of the plurality of categories matches the user preference, adding the respective one of the plurality of categories to a subset of categories; associating each cell of the plurality of cells, in which video is displayed, with a respective category of content of the subset of categories of content that match the user preference, such that a first of the plurality of cells displays a first video associated with a first of the plurality of categories and a second of the plurality of cells displays a second video associated with a second of the plurality of categories; determining, using control circuitry, for each respective cell of the plurality of cells, a respective media asset, from the plurality of media assets associated with the category associated with the respective cell, that is most relevant to the user based on the retrieved user preference wherein the plurality of media assets include the first and second videos; and generating for display the respective relevant media asset in each respective cell of the plurality of cells. 8. The method of claim 1 further comprising making information about the mosaic page on a first user device available on a second user device. | 0.853909 |
9,070,137 | 14 | 15 | 14. The non-transitory computer readable medium of claim 11 , wherein the obtaining data from the plurality of social media websites, comprises: crawling blog posts that contain at least one link to the client website and that appear on the plurality of social media websites to obtain crawled blog posts. | 14. The non-transitory computer readable medium of claim 11 , wherein the obtaining data from the plurality of social media websites, comprises: crawling blog posts that contain at least one link to the client website and that appear on the plurality of social media websites to obtain crawled blog posts. 15. The non-transitory computer readable medium of claim 14 , wherein the extracting the plurality of insights from the obtained data, resulting in extracted insights, comprises: extracting the plurality of insights from the crawled blog posts. | 0.892226 |
8,504,349 | 9 | 14 | 9. A computing device comprising: a console coupled with an input interface and a display interface, the console comprising computer-readable instructions for performing a word completion process, the word completion process comprising: creating a candidate list of words based on received user input at the input interface; presenting a first tier of nodes for display on the display interface, respective nodes comprising two or more characters and representing a plurality of words in the candidate list that begin with the two or more characters, respective nodes not comprising completed words; receiving input corresponding to a selection of a node presented in the first tier of nodes; and presenting a second tier of nodes for display on the display interface, respective nodes of the second tier of nodes comprising at least one additional character than the selected node and representing one or more words that begin with the two or more characters of the selected node. | 9. A computing device comprising: a console coupled with an input interface and a display interface, the console comprising computer-readable instructions for performing a word completion process, the word completion process comprising: creating a candidate list of words based on received user input at the input interface; presenting a first tier of nodes for display on the display interface, respective nodes comprising two or more characters and representing a plurality of words in the candidate list that begin with the two or more characters, respective nodes not comprising completed words; receiving input corresponding to a selection of a node presented in the first tier of nodes; and presenting a second tier of nodes for display on the display interface, respective nodes of the second tier of nodes comprising at least one additional character than the selected node and representing one or more words that begin with the two or more characters of the selected node. 14. The computing device of claim 9 , a first node in the first tier of nodes corresponding to a first group of words in the candidate list and a second node in the first tier of nodes corresponding to a second group of words in the candidate list, the first group of words not overlapping the second group of words. | 0.771346 |
8,250,169 | 14 | 16 | 14. A mobile client device comprising: display hardware that supports an interactive graphical user interface (GUI); and an active business client coupled to the display hardware, to provide a desktop widget operating platform on which to execute a desktop widget, the active business client to access business context data received from a server, the business context data describing a resource, a view, and actionable context data related to a business scenario, the business context data including an instance of at least one data object, the instance generated from a model of the data object and enriched with metadata identifying the business scenario, the business scenario providing an end business purpose for a work action, the business context data not specific to a particular user interface (UI) type, without UI model or UI pattern information in the business context data wherein the resource includes a functional resource used to perform the work action, wherein the view includes a metadata definition of a generic presentation form to be processed to render the business context data in a UI, wherein the actionable context data includes interactive content to perform the work action and cause an action at the server, and wherein the UI type includes interface hardware and associated drivers, the active business client having a controller layer at the mobile client device to process the business context data to determine a GUI component to generate to represent the business context data, the GUI component having GUI elements with interfaces to render the view on the business context data; and a view layer to generate the GUI component based on the business scenario, the GUI component being formatted to the specific GUI for the display hardware and based on a UI type available on the mobile client device and the controller layer, to render the view on the business context data from the generic presentation form to a format supported by the UI type available on the mobile client device, and render the GUI component in a desktop widget, provided on the display to provide access to the actionable context data on the client device, where an operation on the instance of the business context data is to cause the operation to be applied to the data at the server. | 14. A mobile client device comprising: display hardware that supports an interactive graphical user interface (GUI); and an active business client coupled to the display hardware, to provide a desktop widget operating platform on which to execute a desktop widget, the active business client to access business context data received from a server, the business context data describing a resource, a view, and actionable context data related to a business scenario, the business context data including an instance of at least one data object, the instance generated from a model of the data object and enriched with metadata identifying the business scenario, the business scenario providing an end business purpose for a work action, the business context data not specific to a particular user interface (UI) type, without UI model or UI pattern information in the business context data wherein the resource includes a functional resource used to perform the work action, wherein the view includes a metadata definition of a generic presentation form to be processed to render the business context data in a UI, wherein the actionable context data includes interactive content to perform the work action and cause an action at the server, and wherein the UI type includes interface hardware and associated drivers, the active business client having a controller layer at the mobile client device to process the business context data to determine a GUI component to generate to represent the business context data, the GUI component having GUI elements with interfaces to render the view on the business context data; and a view layer to generate the GUI component based on the business scenario, the GUI component being formatted to the specific GUI for the display hardware and based on a UI type available on the mobile client device and the controller layer, to render the view on the business context data from the generic presentation form to a format supported by the UI type available on the mobile client device, and render the GUI component in a desktop widget, provided on the display to provide access to the actionable context data on the client device, where an operation on the instance of the business context data is to cause the operation to be applied to the data at the server. 16. The client device of claim 14 , the view layer to generate and render a task detail toolbar customized to provide access to details of the actionable context data in the desktop widget. | 0.753264 |
8,103,503 | 1 | 7 | 1. A method for determining whether a user has correctly read a target sentence string, comprising: receiving a sentence array including component words of the target sentence string; using a computing device, processing the sentence array to generate a symbolic representation of the target sentence string, the symbolic representation including a subset of words selected from the component words of the target sentence string, the subset of words having fewer words than the sentence array; receiving user speech input; using the computing device, processing the user speech input to recognize in the user speech input each of the words in the subset of words in the symbolic representation of the target sentence string, the subset of words including a first word of the target sentence string, an intermediate word of the target sentence string, and a last word of the target sentence string, wherein the intermediate word is a random intermediate word randomly chosen from a plurality of intermediate words of the target sentence string; and upon recognizing the subset of words in the symbolic representation of the target sentence string, making a determination whether the user has correctly read the target sentence string. | 1. A method for determining whether a user has correctly read a target sentence string, comprising: receiving a sentence array including component words of the target sentence string; using a computing device, processing the sentence array to generate a symbolic representation of the target sentence string, the symbolic representation including a subset of words selected from the component words of the target sentence string, the subset of words having fewer words than the sentence array; receiving user speech input; using the computing device, processing the user speech input to recognize in the user speech input each of the words in the subset of words in the symbolic representation of the target sentence string, the subset of words including a first word of the target sentence string, an intermediate word of the target sentence string, and a last word of the target sentence string, wherein the intermediate word is a random intermediate word randomly chosen from a plurality of intermediate words of the target sentence string; and upon recognizing the subset of words in the symbolic representation of the target sentence string, making a determination whether the user has correctly read the target sentence string. 7. The method of claim 1 , further including displaying a text of the target sentence string in a display to be read by the user. | 0.891231 |
7,743,015 | 8 | 9 | 8. A storage device storing a program for causing a computer to perform a method for processing data, the method comprising: storing data indicative of a replication time in the OLAP database, the data indicative of the replication time being replicated from the relational database at the replication time, wherein the OLAP database is a database for storage of a replication of the transaction data in an OLAP cube, the OLAP database having a plurality of OLAP cubes and structural cube definition data for the OLAP cubes; reading an actual time from a time reference and determining the replication time using the actual time and a replication time scheme; receiving a request for data stored in the OLAP database, the request specifying at least a first time interval and a name of the OLAP cube in the OLAP database, wherein the first time interval includes an upper limit and a lower limit; reading, after receiving the request, OLAP cube data from a OLAP cube associated with the name, the OLAP cube data being associated with a first portion of the data in the request; storing the OLAP cube data in a random access memory; electronically generating a query for a relational database storing up-to-date transaction data when the upper limit of the first time interval specified in the request is more recent than the replication time, wherein the query specifies a second time interval that includes a lower limit given by the replication time and an upper limit given by the upper limit of the first time interval, and the query is associated with a second portion of the data in the request; electronically receiving replication data from the relational database in response to the query; storing the replication data in the random access memory; and generating an output as a response to the request using the OLAP cube data and the replication data stored in the random access memory. | 8. A storage device storing a program for causing a computer to perform a method for processing data, the method comprising: storing data indicative of a replication time in the OLAP database, the data indicative of the replication time being replicated from the relational database at the replication time, wherein the OLAP database is a database for storage of a replication of the transaction data in an OLAP cube, the OLAP database having a plurality of OLAP cubes and structural cube definition data for the OLAP cubes; reading an actual time from a time reference and determining the replication time using the actual time and a replication time scheme; receiving a request for data stored in the OLAP database, the request specifying at least a first time interval and a name of the OLAP cube in the OLAP database, wherein the first time interval includes an upper limit and a lower limit; reading, after receiving the request, OLAP cube data from a OLAP cube associated with the name, the OLAP cube data being associated with a first portion of the data in the request; storing the OLAP cube data in a random access memory; electronically generating a query for a relational database storing up-to-date transaction data when the upper limit of the first time interval specified in the request is more recent than the replication time, wherein the query specifies a second time interval that includes a lower limit given by the replication time and an upper limit given by the upper limit of the first time interval, and the query is associated with a second portion of the data in the request; electronically receiving replication data from the relational database in response to the query; storing the replication data in the random access memory; and generating an output as a response to the request using the OLAP cube data and the replication data stored in the random access memory. 9. The storage device of claim 8 , wherein the OLAP database includes a plurality of OLAP cubes and structural cube definition data for each of the plurality of the OLAP cubes. | 0.502825 |
8,744,989 | 9 | 18 | 9. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: determining a current value of a respective approval metric for each of a plurality of content submissions; determining a statistical confidence interval for the respective approval metric of each content submission, wherein an upper bound and a lower bound of the statistical confidence interval each departs from the current value of the respective approval metric by a decreasing amount with an increasing sample size of favorability indications associated with each content submission, wherein each favorability indication indicates either positive or negative favorability; generating a priority ranking of the plurality of content submissions according to the upper bound of the statistical confidence interval calculated for each of the content submissions; and selecting first one or more content submissions in the priority ranking as featured submissions for presentation in order to elicit additional favorability indications according to respective ranks of the first one or more content submissions in the priority ranking. | 9. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: determining a current value of a respective approval metric for each of a plurality of content submissions; determining a statistical confidence interval for the respective approval metric of each content submission, wherein an upper bound and a lower bound of the statistical confidence interval each departs from the current value of the respective approval metric by a decreasing amount with an increasing sample size of favorability indications associated with each content submission, wherein each favorability indication indicates either positive or negative favorability; generating a priority ranking of the plurality of content submissions according to the upper bound of the statistical confidence interval calculated for each of the content submissions; and selecting first one or more content submissions in the priority ranking as featured submissions for presentation in order to elicit additional favorability indications according to respective ranks of the first one or more content submissions in the priority ranking. 18. The computer-readable medium of claim 9 , wherein the operations further comprise: generating an approval ranking of the plurality of content submissions according to the lower bound of the statistical confidence interval determined for each of the content submissions; and selecting second one or more content submissions in the approval ranking as popular content submissions among the plurality of content submissions according to respective ranks of the second one or more content submissions in the approval ranking. | 0.675926 |
7,970,213 | 1 | 5 | 1. A computer-implemented method for improving recognition of text present in an image, the method comprising: under the control of one or more computer systems configured with executable instructions, obtaining multiple processed versions of an image of a text, wherein the multiple processed versions of the image are obtained by applying different operators to the image; obtaining characters and location information of the characters in the text from each of the multiple processed versions of the image, wherein the location information comprises pixel coordinates of the characters in the text; and editing the text based on the obtained location information of the characters to improve the recognition of the text in the image by removing, for each two adjacent words in the text, a space between a first word and a second word based on a horizontal distance between an end of the first word and a beginning of the second word. | 1. A computer-implemented method for improving recognition of text present in an image, the method comprising: under the control of one or more computer systems configured with executable instructions, obtaining multiple processed versions of an image of a text, wherein the multiple processed versions of the image are obtained by applying different operators to the image; obtaining characters and location information of the characters in the text from each of the multiple processed versions of the image, wherein the location information comprises pixel coordinates of the characters in the text; and editing the text based on the obtained location information of the characters to improve the recognition of the text in the image by removing, for each two adjacent words in the text, a space between a first word and a second word based on a horizontal distance between an end of the first word and a beginning of the second word. 5. The computer-implemented method of claim 1 , wherein editing the text further comprises joining a first word and a second word that have been detected as separate entities, based on a vertical alignment between the first word and the second word and based on a horizontal distance between the end of the first word and the beginning of the second word. | 0.717357 |
9,170,738 | 11 | 13 | 11. A system for managing storage space of media assets stored on a storage device, the system comprising: a user input device configured to receive a selection; a storage device configured to store at least one media asset; and control circuitry, coupled to the user input device and the storage device, configured to: store a media asset on the storage device; access the stored media asset from the storage device; detect a first segment within the stored media asset; receive a selection of an editing tool; generate an edited first segment based on the selected editing tool and the first segment, wherein the edited first segment is a transformation of the first segment; compare an amount of storage space available in the storage device to a storage space requirement, wherein a result of the comparing is based on storage space of the storage device occupied by the stored media asset when the comparing occurs; and store the edited first segment to replace the first segment within the stored media asset on the storage device in response to determining, based on the result, that the amount of storage space does not satisfy the storage space requirement by deleting the first segment from the storage device and storing the edited first segment on the storage device. | 11. A system for managing storage space of media assets stored on a storage device, the system comprising: a user input device configured to receive a selection; a storage device configured to store at least one media asset; and control circuitry, coupled to the user input device and the storage device, configured to: store a media asset on the storage device; access the stored media asset from the storage device; detect a first segment within the stored media asset; receive a selection of an editing tool; generate an edited first segment based on the selected editing tool and the first segment, wherein the edited first segment is a transformation of the first segment; compare an amount of storage space available in the storage device to a storage space requirement, wherein a result of the comparing is based on storage space of the storage device occupied by the stored media asset when the comparing occurs; and store the edited first segment to replace the first segment within the stored media asset on the storage device in response to determining, based on the result, that the amount of storage space does not satisfy the storage space requirement by deleting the first segment from the storage device and storing the edited first segment on the storage device. 13. The system of claim 11 , wherein the transformation comprises removing a portion of the first segment. | 0.849003 |
8,620,959 | 5 | 6 | 5. A computer database system for multi-model integration comprising: one or more remote client computers, each having remote client-side components provided therein, said remote client-side components comprising: a multi-model manager for constructing a multi-model for a system from individual constituent models created in a diverse set of domain-specific modeling languages (DSMLs); one or more connectors for providing interaction between the multi-model manager and each model's DSML interface; an execution automation engine; a sandbox for providing a local copy of a multi-model repository; and a version control system client; and a server connected to the one or more remote client computers via a communication medium, the server comprising: a processing unit; and a data storage for storing a multi-model database of a product system and accessible by the processing unit, said multi-model database comprising: a plurality of artifacts that define the multi-model database; and a multi-model repository that holds said artifacts under version control, wherein said artifacts comprise: a models data dataset, wherein each model represents a discrete aspect of the product system; a model registry dataset containing a list of the models in the multi-model database; a model attributes dataset corresponding to each of the models; a model interfaces dataset representing a tuple corresponding to each of the models, wherein said tuple contains a mapping operation and said model attributes; a model attribute constraints dataset associated with the input and output attributes, wherein said attribute constraints are triggers on the value of the associated attribute; a model data editing tools dataset; a notifications dataset associated with each of the models for informing the models of defined events; and a multi-model execution control dataset. | 5. A computer database system for multi-model integration comprising: one or more remote client computers, each having remote client-side components provided therein, said remote client-side components comprising: a multi-model manager for constructing a multi-model for a system from individual constituent models created in a diverse set of domain-specific modeling languages (DSMLs); one or more connectors for providing interaction between the multi-model manager and each model's DSML interface; an execution automation engine; a sandbox for providing a local copy of a multi-model repository; and a version control system client; and a server connected to the one or more remote client computers via a communication medium, the server comprising: a processing unit; and a data storage for storing a multi-model database of a product system and accessible by the processing unit, said multi-model database comprising: a plurality of artifacts that define the multi-model database; and a multi-model repository that holds said artifacts under version control, wherein said artifacts comprise: a models data dataset, wherein each model represents a discrete aspect of the product system; a model registry dataset containing a list of the models in the multi-model database; a model attributes dataset corresponding to each of the models; a model interfaces dataset representing a tuple corresponding to each of the models, wherein said tuple contains a mapping operation and said model attributes; a model attribute constraints dataset associated with the input and output attributes, wherein said attribute constraints are triggers on the value of the associated attribute; a model data editing tools dataset; a notifications dataset associated with each of the models for informing the models of defined events; and a multi-model execution control dataset. 6. The computer database system of claim 5 , wherein the multi-model repository incorporates version control system operations. | 0.736515 |
9,189,471 | 1 | 11 | 1. An emotion recognition apparatus comprising: at least one processor; a sampling unit of the at least one processor configured to extract, from input data for emotion recognition, sampling data corresponding to a time period, wherein the input data comprises a facial image of a user, a voice of the user, text input by the user, a temperature of the user, a location of the user, or a kind of an application being used by the user; a data segment creator of the at least one processor configured to accumulatively segment the sampling data, based on one or more predetermined time-domain windows, to form a plurality of data segments, wherein each of the data segments subsequent to a first data segment, among the plurality of data segments, includes portions of the sampling data from a current sampling time period and all previous sampling time periods; an emotional segment creator of the at least one processor configured to create a plurality of emotional segments that comprise a plurality of emotions corresponding to each of the respective data segments; and an emotion deciding unit of the at least one processor comprising a complex emotion deciding unit configured to decide at least two of the emotional segments as the user's complex emotion. | 1. An emotion recognition apparatus comprising: at least one processor; a sampling unit of the at least one processor configured to extract, from input data for emotion recognition, sampling data corresponding to a time period, wherein the input data comprises a facial image of a user, a voice of the user, text input by the user, a temperature of the user, a location of the user, or a kind of an application being used by the user; a data segment creator of the at least one processor configured to accumulatively segment the sampling data, based on one or more predetermined time-domain windows, to form a plurality of data segments, wherein each of the data segments subsequent to a first data segment, among the plurality of data segments, includes portions of the sampling data from a current sampling time period and all previous sampling time periods; an emotional segment creator of the at least one processor configured to create a plurality of emotional segments that comprise a plurality of emotions corresponding to each of the respective data segments; and an emotion deciding unit of the at least one processor comprising a complex emotion deciding unit configured to decide at least two of the emotional segments as the user's complex emotion. 11. The emotion recognition apparatus of claim 1 , wherein the emotion deciding unit further comprises a changed emotion deciding unit configured to decide a time-ordered arrangement of the emotional segments as the changed emotion. | 0.758333 |
7,543,189 | 7 | 9 | 7. A computer readable medium for automated testing of an application program, comprising: a test script having test commands in a first language, the application program having a second language that is different from the first language; and a tester process for providing translations of the test commands in the second language, the tester process employing translations used in the application program itself and comparing test commands in the first language to converted test commands in the second language by accessing supporting files of the application program supporting program examination in plural languages and having translations to the second language, the supporting files being prior established files of the application program and the supporting files having resource name and URL for the second language. | 7. A computer readable medium for automated testing of an application program, comprising: a test script having test commands in a first language, the application program having a second language that is different from the first language; and a tester process for providing translations of the test commands in the second language, the tester process employing translations used in the application program itself and comparing test commands in the first language to converted test commands in the second language by accessing supporting files of the application program supporting program examination in plural languages and having translations to the second language, the supporting files being prior established files of the application program and the supporting files having resource name and URL for the second language. 9. The computer readable medium as claimed in claim 7 wherein the application program is multilingual and the second language is locale-specific. | 0.854418 |
7,499,591 | 25 | 27 | 25. A document classifier comprising: a plurality of classifier engines; means for generating a metric for each classifier engine; means for comparing said metrics; and means for classifying a document using output from one or more of said classifier engines in response to said means for comparing; wherein said means for generating a metric generates, for each classifier engine, a list of probabilities of said document being classified by each classifier engine into each one of a group of possible classes, and wherein said means for comparing sums said probabilities for each class and identifies the class with the largest sum of probabilities, wherein said means for generating a metric further generates a precision value for each classifier engine, and wherein said means for comparing identifies a highest precision value and a second highest precision value and determines if said highest precision value is greater than said second highest precision value by a predetermined amount, and wherein said means for classifying classifies said document using output from the classifier engine having said highest precision value to classify said document if said highest precision value is greater than said second highest precision value by a predetermined amount and classifies said document into the class with the largest sum of probabilities if said highest precision value is not greater than said second highest precision value by a predetermined amount. | 25. A document classifier comprising: a plurality of classifier engines; means for generating a metric for each classifier engine; means for comparing said metrics; and means for classifying a document using output from one or more of said classifier engines in response to said means for comparing; wherein said means for generating a metric generates, for each classifier engine, a list of probabilities of said document being classified by each classifier engine into each one of a group of possible classes, and wherein said means for comparing sums said probabilities for each class and identifies the class with the largest sum of probabilities, wherein said means for generating a metric further generates a precision value for each classifier engine, and wherein said means for comparing identifies a highest precision value and a second highest precision value and determines if said highest precision value is greater than said second highest precision value by a predetermined amount, and wherein said means for classifying classifies said document using output from the classifier engine having said highest precision value to classify said document if said highest precision value is greater than said second highest precision value by a predetermined amount and classifies said document into the class with the largest sum of probabilities if said highest precision value is not greater than said second highest precision value by a predetermined amount. 27. The document classifier of claim 25 further comprising means for transforming said probabilities for each class. | 0.623377 |
9,984,165 | 8 | 10 | 8. The method of claim 1 wherein the probability of a pre-computed priced travel recommendation i being valid at a time t after a previous collection of the pre-computed priced travel recommendation i is given by e −λt , wherein λ i denotes a decrease rate of the probability of the pre-collected search result i being valid and t i denotes a time since a last re-computation of the pre-computed priced travel recommendation i. | 8. The method of claim 1 wherein the probability of a pre-computed priced travel recommendation i being valid at a time t after a previous collection of the pre-computed priced travel recommendation i is given by e −λt , wherein λ i denotes a decrease rate of the probability of the pre-collected search result i being valid and t i denotes a time since a last re-computation of the pre-computed priced travel recommendation i. 10. The method of claim 8 wherein a value of λ i is derived from re-computations of the pre-computed priced travel recommendation i. | 0.971588 |
8,572,572 | 9 | 11 | 9. A computer program product for software development, the computer program product comprising: a computer-readable storage memory having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to implement a text editor with which a programmer is able to create source code computer readable program code configured to store a plurality of patterns in a first database, each pattern representing a programming error; computer readable program code configured to store a plurality of corrections in a second database, each correction representing a code that corrects a corresponding programming error; computer readable program code configured to dynamically evaluate the source code as the programmer creates the source code by periodically comparing the source code with the plurality of patterns; computer readable program code configured to, responsive to matching a segment of the source code with one of said patterns, provide at least one correction; and computer readable program code configured to, responsive to the programmer selecting the at least one correction, cause the text editor to change the source code to conform to the correction. | 9. A computer program product for software development, the computer program product comprising: a computer-readable storage memory having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to implement a text editor with which a programmer is able to create source code computer readable program code configured to store a plurality of patterns in a first database, each pattern representing a programming error; computer readable program code configured to store a plurality of corrections in a second database, each correction representing a code that corrects a corresponding programming error; computer readable program code configured to dynamically evaluate the source code as the programmer creates the source code by periodically comparing the source code with the plurality of patterns; computer readable program code configured to, responsive to matching a segment of the source code with one of said patterns, provide at least one correction; and computer readable program code configured to, responsive to the programmer selecting the at least one correction, cause the text editor to change the source code to conform to the correction. 11. The computer program product of claim 9 further comprising: computer readable program code configured to monitor the operator's activity such that the comparison of the source code with the plurality of patterns occurs when the programmer inserts a new line into the source code. | 0.501761 |
7,596,753 | 5 | 9 | 5. A computer implemented method for facilitating input of text by an associated user using a dialog box on a screen of a display device that is connected to said computer, the method comprising: (i) initializing a memory as empty; (ii) displaying a text entry section of a dialog box on the screen of the display device; (iii) counting entries stored previously in the memory; (iv) displaying a drop-down list selection button on the screen of the display device only if the counting produces a value greater than zero; (v) receiving a typed text entry from the associated user via the text entry section of the dialog box; (vi) updating the memory by adding a new entry corresponding to the typed text entry; and (vii) repeating the displaying (ii), counting (iii), and displaying (iv) at least once. | 5. A computer implemented method for facilitating input of text by an associated user using a dialog box on a screen of a display device that is connected to said computer, the method comprising: (i) initializing a memory as empty; (ii) displaying a text entry section of a dialog box on the screen of the display device; (iii) counting entries stored previously in the memory; (iv) displaying a drop-down list selection button on the screen of the display device only if the counting produces a value greater than zero; (v) receiving a typed text entry from the associated user via the text entry section of the dialog box; (vi) updating the memory by adding a new entry corresponding to the typed text entry; and (vii) repeating the displaying (ii), counting (iii), and displaying (iv) at least once. 9. The method according to claim 5 , wherein the step of displaying the drop-down list selection button includes: displaying a drop-down arrow button on the screen of the display device in association with the dialog box. | 0.824881 |
8,423,546 | 12 | 13 | 12. A computer program product for use at a computer system, the computer program product for implementing a method for identifying key phrases within a document, the computer program product comprising one or more computer storage devices having stored thereon computer-executable instructions that, when executed at a processor, cause the computer system to perform the method, including the following: access a document; calculate the frequency of occurrence of a plurality of different textual phrases within the document, each textual phrase including one or more individual words of a specified language, and output a list that contains at least some of the textual phrases together with the frequency of occurrence of output phrases within the document; access a language model for the specified language, the language model defining expected frequencies of occurrence at least for individual words of the specified language; for each textual phrase in the output list, determine the expected frequency of each such textual phrase by using the expected frequencies of at least some of the individual words of the language model to interpolate from the expected frequencies of said at least some individual words the expected frequency of each such textual phrase contained in said list; for each textual phrase in the output list compute a cross-entropy value computed from the frequency of occurrence of the textual phrase within the document and the determined expected frequency of occurrence of the textual phrase within the language model; select a specified number of key textual phrases based on the computed cross-entropy values; and populate a key phrase data structure with data representative of each of the selected specified number of key textual phrases. | 12. A computer program product for use at a computer system, the computer program product for implementing a method for identifying key phrases within a document, the computer program product comprising one or more computer storage devices having stored thereon computer-executable instructions that, when executed at a processor, cause the computer system to perform the method, including the following: access a document; calculate the frequency of occurrence of a plurality of different textual phrases within the document, each textual phrase including one or more individual words of a specified language, and output a list that contains at least some of the textual phrases together with the frequency of occurrence of output phrases within the document; access a language model for the specified language, the language model defining expected frequencies of occurrence at least for individual words of the specified language; for each textual phrase in the output list, determine the expected frequency of each such textual phrase by using the expected frequencies of at least some of the individual words of the language model to interpolate from the expected frequencies of said at least some individual words the expected frequency of each such textual phrase contained in said list; for each textual phrase in the output list compute a cross-entropy value computed from the frequency of occurrence of the textual phrase within the document and the determined expected frequency of occurrence of the textual phrase within the language model; select a specified number of key textual phrases based on the computed cross-entropy values; and populate a key phrase data structure with data representative of each of the selected specified number of key textual phrases. 13. The computer program product as recited in claim 12 , further comprising computer-executable instructions that, when executed, cause the computer system to: enter one or more search terms into a search engine, the search terms related to textual phrases included in the document; receive results from the search engine, the results including documents that include the one or more search terms; and generate the language model from the results returned from the search engine. | 0.50104 |
8,843,580 | 1 | 8 | 1. A computer-implemented method of criteria-based message publication control and feedback in a publish/subscribe messaging environment, comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic and classification criteria, the classification criteria specifying requirements for determining whether publication of the message is successful; consulting, by the message broker, a subscription registry to locate registered subscriptions of a plurality of message subscribers that have registered with the message broker to receive published messages having the topic, each of the registered subscriptions further specifying subscriber classification information pertaining to the topic; selecting, by the message broker from the located subscriptions, each of at least one of the located subscriptions for which the registered subscriber classification information matches the classification criteria associated with the message, wherein the registered subscriber classification information for at least one of the located subscriptions does not match the classification criteria associated with the message; identifying, for each of the at least one selected subscription, the subscriber that registered the selected subscription; sending the message, by the message broker, to the each identified subscriber; comparing, by the message broker, the subscriber classification information in the at least one selected subscription to the classification criteria associated with the message to determine whether the requirements specified in the classification criteria are met by the at least one selected subscription; and responsive to determining, by the comparing, that the requirements are not met, performing controlled failure handling, the controlled failure handling comprising: responsive to determining that a mode of failure handling applicable for the message indicates a warning mode, sending the message, by the message broker, to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting and warning the message publisher that publication of the message was not successful; and responsive to determining that the mode of failure handling indicates a failure mode, notifying the message publisher that publication of the message failed while omitting the sending of the message to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting. | 1. A computer-implemented method of criteria-based message publication control and feedback in a publish/subscribe messaging environment, comprising: receiving, at a message broker, a message published by a message publisher, the message having associated therewith a topic and classification criteria, the classification criteria specifying requirements for determining whether publication of the message is successful; consulting, by the message broker, a subscription registry to locate registered subscriptions of a plurality of message subscribers that have registered with the message broker to receive published messages having the topic, each of the registered subscriptions further specifying subscriber classification information pertaining to the topic; selecting, by the message broker from the located subscriptions, each of at least one of the located subscriptions for which the registered subscriber classification information matches the classification criteria associated with the message, wherein the registered subscriber classification information for at least one of the located subscriptions does not match the classification criteria associated with the message; identifying, for each of the at least one selected subscription, the subscriber that registered the selected subscription; sending the message, by the message broker, to the each identified subscriber; comparing, by the message broker, the subscriber classification information in the at least one selected subscription to the classification criteria associated with the message to determine whether the requirements specified in the classification criteria are met by the at least one selected subscription; and responsive to determining, by the comparing, that the requirements are not met, performing controlled failure handling, the controlled failure handling comprising: responsive to determining that a mode of failure handling applicable for the message indicates a warning mode, sending the message, by the message broker, to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting and warning the message publisher that publication of the message was not successful; and responsive to determining that the mode of failure handling indicates a failure mode, notifying the message publisher that publication of the message failed while omitting the sending of the message to each of the message subscribers that registered one of the located subscriptions which was not selected by the selecting. 8. The method according to claim 1 , wherein the warning mode is selectively activated. | 0.964948 |
8,868,558 | 13 | 18 | 13. A computing device, comprising: a processor; a storage medium for tangibly storing thereon modules for execution by the processor, the modules comprising: a query input module that receives the user query comprising at least one keyword; a query analysis module that analyzes the user query, extracts the at least one keyword from the user query; a quote search engine that generates results responsive to the user query from a quote index based on the at least one keyword, the quote index comprising indexed quotes attributable to people, the quote index also comprising unique identifiers for attributes of the quotes that match at least one keyword identified from the user query, wherein the results comprise a plurality of quotes comprising quotes including the at least one keyword and quotes that have the at least one keyword as a respective attribute in the quote index; a timeline module that generates a timeline for the plurality of quotes, the timeline maps indications of respective sources of the quotes to respective times of publication of the sources, the timeline further configured to display one of the quotes in response to user selection of the indication corresponding to the respective source; and a presentation module for displaying the generated results on a display of a computing device. | 13. A computing device, comprising: a processor; a storage medium for tangibly storing thereon modules for execution by the processor, the modules comprising: a query input module that receives the user query comprising at least one keyword; a query analysis module that analyzes the user query, extracts the at least one keyword from the user query; a quote search engine that generates results responsive to the user query from a quote index based on the at least one keyword, the quote index comprising indexed quotes attributable to people, the quote index also comprising unique identifiers for attributes of the quotes that match at least one keyword identified from the user query, wherein the results comprise a plurality of quotes comprising quotes including the at least one keyword and quotes that have the at least one keyword as a respective attribute in the quote index; a timeline module that generates a timeline for the plurality of quotes, the timeline maps indications of respective sources of the quotes to respective times of publication of the sources, the timeline further configured to display one of the quotes in response to user selection of the indication corresponding to the respective source; and a presentation module for displaying the generated results on a display of a computing device. 18. The computing device of claim 13 , further comprising the quote index. | 0.819512 |
9,530,409 | 1 | 10 | 1. A method operable on an electronic device, comprising: during media playback, detecting an event; initiating output of a first indication of the event, wherein the first indication is a first audio overlay on top of the media playback and indicates that speech recognition is available for a predefined period of time; determining an event type from a plurality of event types, wherein each of the plurality of event types is associated with a set of speech commands; determining a set of speech commands associated with the event type; executing a speech recognition application to process speech commands associated with the event and to provide options to the user for controlling the electronic device, wherein executing the speech recognition application includes initiating a speech recognition engine using the set of speech commands associated with the event type; initiating output of a second indication of a state of readiness to process speech commands in association with the event, wherein the second indication is an audio overlay on top of the media playback; identifying a recognized speech command from a set of expected speech commands using custom speech recognition grammar based on the event; and in response to identifying the recognized speech command: pausing the media playback; and executing the recognized speech command. | 1. A method operable on an electronic device, comprising: during media playback, detecting an event; initiating output of a first indication of the event, wherein the first indication is a first audio overlay on top of the media playback and indicates that speech recognition is available for a predefined period of time; determining an event type from a plurality of event types, wherein each of the plurality of event types is associated with a set of speech commands; determining a set of speech commands associated with the event type; executing a speech recognition application to process speech commands associated with the event and to provide options to the user for controlling the electronic device, wherein executing the speech recognition application includes initiating a speech recognition engine using the set of speech commands associated with the event type; initiating output of a second indication of a state of readiness to process speech commands in association with the event, wherein the second indication is an audio overlay on top of the media playback; identifying a recognized speech command from a set of expected speech commands using custom speech recognition grammar based on the event; and in response to identifying the recognized speech command: pausing the media playback; and executing the recognized speech command. 10. The method of claim 1 , wherein the indication of the event indicates at least one of the speech commands. | 0.895437 |
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