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4,852,180 | 8 | 9 | 8. Apparatus for the recognition of speech, of the type comprising means for storing signals representing a model of the language to be recognized, said model being of the state-transitional type, each state being uniquely identified with a phonetic unit, each state having associated with it a portion of a transition matrix which describes which states can follow it and with what probability, each state having associated with it an observational density function assigning to each set of speech feature signals that my be observed in fluent speech a likelihood of being observed in association with that state, each state having associated with it a durational density function assigning to each duration it may have a likelihood of occurrence in fluent speech; means for storing signals representing lexical candidates, said lexical candidates being assemblages of phonetic units of the language in association with partial phonetic information of the type found in dictionaries; means for sequentially converting successive time frame portions of an utterance into signals representing respective sets of acoustic feature signals representative of the portions; and means for accessing the stored model and stored lexical candidates to obtain signals which represent sequences of the phonetic units, including means for selecting the optimum ones of such sequences to produce a selection signal representing recognition of the utterance, said apparatus being particularly characterized in that the accessing means includes means for assigning a phonetic unit signal and a phonetic duration signal from the stored model to one or more of said time frame portions of speech in response to one or more of said respective sets of acoustic feature signals, and means for maximizing independently of the stored lexical candidates the likelihoods of each phonetic unit and each phonetic duration jointly with the likelihood of observing said one or more of said respective sets of acoustic feature signals, said assigning means and maximizing means being adapted to operate recursively for all assignments and transitions over all time frames up to and including the present time frame; and said accessing means further includes means for retracing the actual maximization results by stepping through the phonetic determinations in a strict order to produce a proposed phonetic sequence for accessing the lexical candidates, and means for subsequently accessing the stored lexical candidates with the proposed phonetic sequence to obtain signals representing a set of proposed lexical candidates, from which signals a final selection signal can be obtained. | 8. Apparatus for the recognition of speech, of the type comprising means for storing signals representing a model of the language to be recognized, said model being of the state-transitional type, each state being uniquely identified with a phonetic unit, each state having associated with it a portion of a transition matrix which describes which states can follow it and with what probability, each state having associated with it an observational density function assigning to each set of speech feature signals that my be observed in fluent speech a likelihood of being observed in association with that state, each state having associated with it a durational density function assigning to each duration it may have a likelihood of occurrence in fluent speech; means for storing signals representing lexical candidates, said lexical candidates being assemblages of phonetic units of the language in association with partial phonetic information of the type found in dictionaries; means for sequentially converting successive time frame portions of an utterance into signals representing respective sets of acoustic feature signals representative of the portions; and means for accessing the stored model and stored lexical candidates to obtain signals which represent sequences of the phonetic units, including means for selecting the optimum ones of such sequences to produce a selection signal representing recognition of the utterance, said apparatus being particularly characterized in that the accessing means includes means for assigning a phonetic unit signal and a phonetic duration signal from the stored model to one or more of said time frame portions of speech in response to one or more of said respective sets of acoustic feature signals, and means for maximizing independently of the stored lexical candidates the likelihoods of each phonetic unit and each phonetic duration jointly with the likelihood of observing said one or more of said respective sets of acoustic feature signals, said assigning means and maximizing means being adapted to operate recursively for all assignments and transitions over all time frames up to and including the present time frame; and said accessing means further includes means for retracing the actual maximization results by stepping through the phonetic determinations in a strict order to produce a proposed phonetic sequence for accessing the lexical candidates, and means for subsequently accessing the stored lexical candidates with the proposed phonetic sequence to obtain signals representing a set of proposed lexical candidates, from which signals a final selection signal can be obtained. 9. Apparatus for the recognition of speech, of the type claimed in claim 8, said apparatus being further characterized in that the means for storing a model includes means for storing an ergodic model in which any state can occur after any other state, the model including examples of all such sequences and the corresponding transition probability signals. | 0.501397 |
10,078,626 | 12 | 14 | 12. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by at least one processor, configure the at least one processor to perform operations comprising: detecting a change in markup language data associated with a document object model (“DOM”) tree; based at least in part on the DOM tree, generating, in a headless browser without display in a graphical user interface, a single-hierarchical DOM array describing elements in the markup language data, wherein the elements are representative of presentation of the markup language elements; accessing two or more layout rules comprising a first layout rule and a second layout rule, wherein the first layout rule comprises a tolerance represented by a number of pixels specifying that two or more elements overlaying one another during presentation constitutes a layout error, wherein the tolerance is represented by a number of pixels, wherein the second layout rule comprises a number of layers permitted to an element based at least in part on a rendering capability of a device; determining a first application of the first layout rule to the DOM array; determining a second application of the second layout rule to the DOM array; determining that a layout error is not present in the second application; determining that layout error is present in the first application, wherein the layout error is represented by a first amount of pixels; determining a second amount of pixels by which the layout error exceeds the tolerance; generating a first verification result for one or more elements described in the markup language data; based at least in part on a failure in the first verification result and further based at least in part on the second amount of pixels, generating a notification and a corrective relocation recommendation including a third amount of pixels by which to displace the one or more elements, wherein the third amount of pixels is based at least in part on the second amount of pixels; and distributing the notification and the corrective relocation recommendation. | 12. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by at least one processor, configure the at least one processor to perform operations comprising: detecting a change in markup language data associated with a document object model (“DOM”) tree; based at least in part on the DOM tree, generating, in a headless browser without display in a graphical user interface, a single-hierarchical DOM array describing elements in the markup language data, wherein the elements are representative of presentation of the markup language elements; accessing two or more layout rules comprising a first layout rule and a second layout rule, wherein the first layout rule comprises a tolerance represented by a number of pixels specifying that two or more elements overlaying one another during presentation constitutes a layout error, wherein the tolerance is represented by a number of pixels, wherein the second layout rule comprises a number of layers permitted to an element based at least in part on a rendering capability of a device; determining a first application of the first layout rule to the DOM array; determining a second application of the second layout rule to the DOM array; determining that a layout error is not present in the second application; determining that layout error is present in the first application, wherein the layout error is represented by a first amount of pixels; determining a second amount of pixels by which the layout error exceeds the tolerance; generating a first verification result for one or more elements described in the markup language data; based at least in part on a failure in the first verification result and further based at least in part on the second amount of pixels, generating a notification and a corrective relocation recommendation including a third amount of pixels by which to displace the one or more elements, wherein the third amount of pixels is based at least in part on the second amount of pixels; and distributing the notification and the corrective relocation recommendation. 14. The non-transitory computer-readable media of claim 12 , the distributing the notification comprising sending data using a network interface. | 0.661215 |
9,158,493 | 1 | 6 | 1. A method comprising: presenting, in a page description language document reader application, a representation of a file packaged within a page description language document, wherein when packaged within the page description language document, the file is compressed in a compressed archive interleaved within the page description language document, and wherein the page description language is Portable Document Format; receiving, in the page description language document reader application, a selection of the packaged file to preview the file within the page description language document reader application; selecting a utility to open the packaged file as a function of a file type of the packaged file; and calling the selected utility to open, within a user interface of the page description language reader application, the packaged file with a reference to a location where the packaged file is located, wherein the utility is a web service accessed via a network interface device of a computing device on which the method is performed and configured to convert the package file from a first format to a second format compatible for viewing in the page description language document reader application. | 1. A method comprising: presenting, in a page description language document reader application, a representation of a file packaged within a page description language document, wherein when packaged within the page description language document, the file is compressed in a compressed archive interleaved within the page description language document, and wherein the page description language is Portable Document Format; receiving, in the page description language document reader application, a selection of the packaged file to preview the file within the page description language document reader application; selecting a utility to open the packaged file as a function of a file type of the packaged file; and calling the selected utility to open, within a user interface of the page description language reader application, the packaged file with a reference to a location where the packaged file is located, wherein the utility is a web service accessed via a network interface device of a computing device on which the method is performed and configured to convert the package file from a first format to a second format compatible for viewing in the page description language document reader application. 6. The method of claim 1 , wherein selecting the utility to open the packaged file as a function of a file type of the packaged file includes: determining if a computer application including a utility to preview files of the type of the packaged file is installed on the computing device on which the method is performed; if the computer application is installed, selecting the utility of the computer application when the computer application is not installed on the computing device on which the method is performed, calling the web service to generate a preview of the packaged file. | 0.544323 |
8,060,575 | 30 | 37 | 30. A computer-based system for transmitting an electronic document, comprising: an intermediate computer that is remote from a device sending a message, the intermediate computer including a memory storing instructions; and a processor configured to: execute the instructions to receive the message from the device, the message including a delivery address and a document, execute the instructions to determine that the document is to be cleansed of metadata according to a cleansing policy, execute the instructions to automatically create a cleansed version of the document by removing metadata from the document, execute the instructions to replace the document received with the message with the cleansed version of the document, and execute the instructions to send the message with the cleansed version of the document to the delivery address. | 30. A computer-based system for transmitting an electronic document, comprising: an intermediate computer that is remote from a device sending a message, the intermediate computer including a memory storing instructions; and a processor configured to: execute the instructions to receive the message from the device, the message including a delivery address and a document, execute the instructions to determine that the document is to be cleansed of metadata according to a cleansing policy, execute the instructions to automatically create a cleansed version of the document by removing metadata from the document, execute the instructions to replace the document received with the message with the cleansed version of the document, and execute the instructions to send the message with the cleansed version of the document to the delivery address. 37. The system of claim 30 , wherein the message includes an email message. | 0.925889 |
8,700,612 | 2 | 4 | 2. The computer-implemented method of claim 1 , wherein the search input is a token comprising a barcode, matrix barcode, or alphanumeric string. | 2. The computer-implemented method of claim 1 , wherein the search input is a token comprising a barcode, matrix barcode, or alphanumeric string. 4. The computer-implemented method of claim 2 , wherein the token defines a contextual relationship view to be displayed for the data of the first cell. | 0.981558 |
7,496,836 | 6 | 7 | 6. A computer-readable medium having executable instructions to cause a processor to perform a method comprising: displaying a set of hypertext template objects, the set comprising default and user-defined hypertext template objects; generating a hypertext object from multiple selected hypertext template objects; modifying a property value in response to input data, the property value associated with the selected hypertext template object; and regenerating the hypertext object using the modified property value. | 6. A computer-readable medium having executable instructions to cause a processor to perform a method comprising: displaying a set of hypertext template objects, the set comprising default and user-defined hypertext template objects; generating a hypertext object from multiple selected hypertext template objects; modifying a property value in response to input data, the property value associated with the selected hypertext template object; and regenerating the hypertext object using the modified property value. 7. The computer-readable medium of claim 6 , wherein the default and user defined hypertext template objects are displayed separately. | 0.72314 |
9,639,507 | 11 | 17 | 11. A computer program product for providing a net effect platform for developing and correcting screen scraping scripts comprising: a nontransitory computer readable medium; and computer program code, encoded on the computer readable medium, comprising computer readable instructions which, when executed via any set of one or more processors, perform the following: obtaining, by a process computing system from a user computing system under the control of a user, login data used to obtain data associated with an individual from a third party webpage provided by a webpage computing system, the obtained login data including at least an account number associated with the user; accessing, using some or all of the login data by the process computing system, the third party webpage; determining, by the process computing system following an attempt to access the third party webpage, that an error has occurred in retrieving data from the third party webpage; requesting, of the user through communication by the process computing system with the first computing system, that the user help identify and correct the cause of the error; generating, by the process computing system, default data associated with a third party webpage, the default data at least indicating the layout of the webpage; generating, by the process computing system using the default data, a mock-up of the third party webpage, the mock-up of the third party webpage including a reproduction of at least part of the third party webpage; providing, to the user computer system by the process computing system communicating with the user computer system, the mock-up of the third party webpage as an interactive interface, wherein the interactive interface configured to allows the individual to add, modify, correct, and/or rearrange the default data; obtaining, from the interactive interface, additions, modifications, corrections, and/or rearrangements of the default data associated with the third party webpage from the interactive interface, the additions, modifications, corrections, and/or rearrangements of the default data associated with the third party webpage at least including an additions, modifications, corrections, and/or rearrangements of the layout of the webpage; transforming the additions, modifications, corrections, and/or rearrangements of the default data associated with the third party webpage into correction data; transforming the correction data into parser scripts associated with the third party webpage; and using the login data and parser scripts associated with the third party webpage to obtain data associated with the individual from the third party webpage. | 11. A computer program product for providing a net effect platform for developing and correcting screen scraping scripts comprising: a nontransitory computer readable medium; and computer program code, encoded on the computer readable medium, comprising computer readable instructions which, when executed via any set of one or more processors, perform the following: obtaining, by a process computing system from a user computing system under the control of a user, login data used to obtain data associated with an individual from a third party webpage provided by a webpage computing system, the obtained login data including at least an account number associated with the user; accessing, using some or all of the login data by the process computing system, the third party webpage; determining, by the process computing system following an attempt to access the third party webpage, that an error has occurred in retrieving data from the third party webpage; requesting, of the user through communication by the process computing system with the first computing system, that the user help identify and correct the cause of the error; generating, by the process computing system, default data associated with a third party webpage, the default data at least indicating the layout of the webpage; generating, by the process computing system using the default data, a mock-up of the third party webpage, the mock-up of the third party webpage including a reproduction of at least part of the third party webpage; providing, to the user computer system by the process computing system communicating with the user computer system, the mock-up of the third party webpage as an interactive interface, wherein the interactive interface configured to allows the individual to add, modify, correct, and/or rearrange the default data; obtaining, from the interactive interface, additions, modifications, corrections, and/or rearrangements of the default data associated with the third party webpage from the interactive interface, the additions, modifications, corrections, and/or rearrangements of the default data associated with the third party webpage at least including an additions, modifications, corrections, and/or rearrangements of the layout of the webpage; transforming the additions, modifications, corrections, and/or rearrangements of the default data associated with the third party webpage into correction data; transforming the correction data into parser scripts associated with the third party webpage; and using the login data and parser scripts associated with the third party webpage to obtain data associated with the individual from the third party webpage. 17. The computer program product for providing a net effect platform for developing and correcting screen scraping scripts of claim 11 wherein the mock-up of the third party webpage is a Graphical User Interface (GUI). | 0.800366 |
10,164,848 | 11 | 15 | 11. A computer-readable storage medium storing computer-executable instructions that, when executed by a computer system, configure the computer system to perform operations comprising: receiving, from a user, seed input information and a network service identifier, the network service identifier comprising a uniform resource locator; parsing a programmatic interface schema associated with the network service identifier for metadata, the metadata including parameter information associated with the programmatic interface schema, the programmatic interface schema associated with rule information indicating an order of execution for an interface element of the programmatic interface schema with respect to other interface elements of the programmatic interface schema, the rule information specified by a service provider; determining, in response to receiving the seed input information and the network service identifier, input information for a network service associated with the network service identifier based at least in part on the metadata and the seed input information, the seed input information including a plurality of input permutations for the interface element of the programmatic interface schema; and invoking the interface element utilizing the input information to generate result information, the result information indicating functionality of the interface element of the network service with an input permutation of the plurality of input permutations. | 11. A computer-readable storage medium storing computer-executable instructions that, when executed by a computer system, configure the computer system to perform operations comprising: receiving, from a user, seed input information and a network service identifier, the network service identifier comprising a uniform resource locator; parsing a programmatic interface schema associated with the network service identifier for metadata, the metadata including parameter information associated with the programmatic interface schema, the programmatic interface schema associated with rule information indicating an order of execution for an interface element of the programmatic interface schema with respect to other interface elements of the programmatic interface schema, the rule information specified by a service provider; determining, in response to receiving the seed input information and the network service identifier, input information for a network service associated with the network service identifier based at least in part on the metadata and the seed input information, the seed input information including a plurality of input permutations for the interface element of the programmatic interface schema; and invoking the interface element utilizing the input information to generate result information, the result information indicating functionality of the interface element of the network service with an input permutation of the plurality of input permutations. 15. The computer-readable storage medium of claim 11 , further comprising parsing computer code associated with the network service identifier to determine the programmatic interface schema. | 0.736111 |
9,684,908 | 10 | 12 | 10. The server of claim 9 , wherein: the server further comprises a training content item set comprising at least one training content item; and the memory further stores instructions that, when executed by the processor, provide a comparison trainer that, for the respective training content items: examines the training content item to identify a training comparison question; using the training comparison question, generates a first comparison template; and adds the first comparison template to the comparison template set. | 10. The server of claim 9 , wherein: the server further comprises a training content item set comprising at least one training content item; and the memory further stores instructions that, when executed by the processor, provide a comparison trainer that, for the respective training content items: examines the training content item to identify a training comparison question; using the training comparison question, generates a first comparison template; and adds the first comparison template to the comparison template set. 12. The server of claim 10 , wherein: the comparison trainer further evaluates the respective training content items to identify a topic set comprising at least two topics having a relation in the training content item; and the comparison generator further identifies the at least two topics in the content item by identifying in the content item the topics of a topic set. | 0.819108 |
9,146,919 | 15 | 17 | 15. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a set of acceptable expressions, each acceptable expression being a string that identifies a value of a variable entity in a first natural language, each acceptable expression being associated with a canonical representation of the value identified by that expression; performing, sing a first machine translator that translates expressions from the first natural language to a second natural language, machine translation on each acceptable expression in the first natural language to obtain a translated expression of the acceptable expression in the second natural language; associating the canonical representation associated with each acceptable expression with the corresponding translated expression in the second natural language; providing a set of training data for training a second machine translator that translates expressions in the second natural language that each include a respective translated expression to expressions in the second natural language that each include a respective canonical representation, the set of training data comprising the translated expressions and the canonical representations that are associated with the translated expressions; and using the second machine translator to translate a particular expression that includes a particular translated expression into a particular translated expression that includes a particular canonical representation. | 15. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a set of acceptable expressions, each acceptable expression being a string that identifies a value of a variable entity in a first natural language, each acceptable expression being associated with a canonical representation of the value identified by that expression; performing, sing a first machine translator that translates expressions from the first natural language to a second natural language, machine translation on each acceptable expression in the first natural language to obtain a translated expression of the acceptable expression in the second natural language; associating the canonical representation associated with each acceptable expression with the corresponding translated expression in the second natural language; providing a set of training data for training a second machine translator that translates expressions in the second natural language that each include a respective translated expression to expressions in the second natural language that each include a respective canonical representation, the set of training data comprising the translated expressions and the canonical representations that are associated with the translated expressions; and using the second machine translator to translate a particular expression that includes a particular translated expression into a particular translated expression that includes a particular canonical representation. 17. The computer storage medium of claim 15 , wherein the operations further comprise: training the second machine translator, using the set of training data, to translate acceptable expressions for a value of the variable entity in the second natural language to corresponding canonical representations. | 0.754045 |
7,844,956 | 1 | 3 | 1. A computer-implemented method, executed by a central processing unit (CPU), for application-specific object-oriented processing of a markup by a model instance associated with a class Model and a plurality of element instances, each of said plurality of element instances associated with a class Element, said class Model is configured to process instances of said class Element, comprising the steps of: responding to a construct-element request, said construct-element request is a member function of said class Model, dispatched to said model instance, in which a tag name is provided, said tag name corresponding to a tagged element from said markup, constructing a new element instance, one of said plurality of element instances, according to application-specific requirements as determined according to said tag name, performing application-specific processing as required, and returning said constructed new element instance; responding to an accept-attribute request, said accept-attribute request is a member function of said class Element, dispatched to one of said plurality of element instances, in which an attribute is provided, said attribute corresponding to a markup attribute of a tagged element from said markup, and performing application-specific processing as required; responding to an accept-element request, said accept-element request is a member function of said class Element, dispatched to one of said plurality of element instances, in which a child element instances, one of said plurality of element instances, is provided, and performing application-specific processing as required; and responding to an accept-root-element request, said accept-root-element request is a member function of said class Model, dispatched to said model instance, in which a root element instance, one of said plurality of element instances, is provided, and performing application-specific processing as required. | 1. A computer-implemented method, executed by a central processing unit (CPU), for application-specific object-oriented processing of a markup by a model instance associated with a class Model and a plurality of element instances, each of said plurality of element instances associated with a class Element, said class Model is configured to process instances of said class Element, comprising the steps of: responding to a construct-element request, said construct-element request is a member function of said class Model, dispatched to said model instance, in which a tag name is provided, said tag name corresponding to a tagged element from said markup, constructing a new element instance, one of said plurality of element instances, according to application-specific requirements as determined according to said tag name, performing application-specific processing as required, and returning said constructed new element instance; responding to an accept-attribute request, said accept-attribute request is a member function of said class Element, dispatched to one of said plurality of element instances, in which an attribute is provided, said attribute corresponding to a markup attribute of a tagged element from said markup, and performing application-specific processing as required; responding to an accept-element request, said accept-element request is a member function of said class Element, dispatched to one of said plurality of element instances, in which a child element instances, one of said plurality of element instances, is provided, and performing application-specific processing as required; and responding to an accept-root-element request, said accept-root-element request is a member function of said class Model, dispatched to said model instance, in which a root element instance, one of said plurality of element instances, is provided, and performing application-specific processing as required. 3. The computer-implemented method of claim 1 , further comprising the step of: responding to a commit request, said commit request is a member function of said class Element, dispatched to one of said plurality of element instances, said commit request indicating that no further is for said accept-element request will be dispatched to the one of said plurality of element instances, and performing application-specific processing as required. | 0.750281 |
7,917,488 | 5 | 7 | 5. The one or more computer readable media of claim 1 , wherein the cross-lingual query generative probability between the search query (q c ) and a document (d e ) based on query translation is expressed in terms comprising: ∑ i , j μ ij f i ( q e , d e ) g j ( q c , q e ) , where q e is a translation of the search query q c in the second language, ƒ i (q e ,d e ) is a monolingual relevancy feature function used for estimating relevancy between q e as a search query in the second language and the document d e , g j (q c ,q e ) is a feature function associated with query translation between the search query q c and the translation search query q e , and μ ij is corresponding weight parameter, and i is a first index that represents at least one ƒ i (q e ,d e ), and j is a second index that represents at least one g j (q c ,q e ). | 5. The one or more computer readable media of claim 1 , wherein the cross-lingual query generative probability between the search query (q c ) and a document (d e ) based on query translation is expressed in terms comprising: ∑ i , j μ ij f i ( q e , d e ) g j ( q c , q e ) , where q e is a translation of the search query q c in the second language, ƒ i (q e ,d e ) is a monolingual relevancy feature function used for estimating relevancy between q e as a search query in the second language and the document d e , g j (q c ,q e ) is a feature function associated with query translation between the search query q c and the translation search query q e , and μ ij is corresponding weight parameter, and i is a first index that represents at least one ƒ i (q e ,d e ), and j is a second index that represents at least one g j (q c ,q e ). 7. The one or more computer readable media of claim 5 , wherein the feature function g j (q c ,q e ) is selected from a group of feature functions including bilingual dictionary-based score based on term-term cohesion, bidirectional translation score based on parallel corpora, frequency in Web mining snippets, and monolingual query suggestion-based feature. | 0.910874 |
8,458,164 | 34 | 35 | 34. The non-transitory computer storage medium of manufacture of claim 33 , wherein the program instructions for selecting further comprises program instructions for highlighting the two or more predicates. | 34. The non-transitory computer storage medium of manufacture of claim 33 , wherein the program instructions for selecting further comprises program instructions for highlighting the two or more predicates. 35. The non-transitory computer storage medium of manufacture of claim 34 , further comprising program instructions for selecting one or more of grouped predicates for ungrouping. | 0.93448 |
8,078,557 | 1 | 12 | 1. A system for identifying keywords in search results comprising: a processor; a memory coupled to the processor, wherein the memory includes instructions that when executed by the processor perform operations comprising: connecting a plurality of neurons as a bidirectional neural network, the neurons being associated with words and documents, the neurons associated with words forming a first layer, and the neurons associated with documents forming a second layer, each neuron having multiple inputs from other neurons, a single output connecting the neuron to other neurons, and a threshold function at the single output, wherein at least some of the neurons of the first layer have connections between them and represent keywords in the documents; displaying to a user, on a display device, words of the search query and additional keywords from the documents and identifying the neurons that correspond to keywords associated with at least one of the documents; and changing positions of the keywords on a display relative to each other based on input from the user, wherein the change in position of one keyword changes the position of other displayed keywords. | 1. A system for identifying keywords in search results comprising: a processor; a memory coupled to the processor, wherein the memory includes instructions that when executed by the processor perform operations comprising: connecting a plurality of neurons as a bidirectional neural network, the neurons being associated with words and documents, the neurons associated with words forming a first layer, and the neurons associated with documents forming a second layer, each neuron having multiple inputs from other neurons, a single output connecting the neuron to other neurons, and a threshold function at the single output, wherein at least some of the neurons of the first layer have connections between them and represent keywords in the documents; displaying to a user, on a display device, words of the search query and additional keywords from the documents and identifying the neurons that correspond to keywords associated with at least one of the documents; and changing positions of the keywords on a display relative to each other based on input from the user, wherein the change in position of one keyword changes the position of other displayed keywords. 12. The system of claim 1 , wherein the neural network is excited by a query that identifies a plurality of documents considered relevant by a user, and wherein the neural network outputs keywords associated with the plurality of documents. | 0.744136 |
9,483,138 | 1 | 8 | 1. A method, comprising: using a computer to perform: collecting information about a user manipulation of a stylus in relation to a tablet device associated with the computer; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, such that: the stylus gesture is one of a plurality of stylus gestures that are recognized by the computer to perform at least one of a plurality of actions in a graphics application that comprises a natural media painting application, at least some of the stylus gestures are mapped to user manipulation of the stylus at a distance from the tablet device, at least some of the stylus gestures involve contact of the stylus with the tablet device, and the stylus gestures include a brush switching gesture in which a proximity of the stylus to the tablet changes from a first position relative to the tablet to a second position that is further away from the tablet and with at least a rate of change that corresponds to the brush switching gesture, the first position being within a first pre-defined distance threshold relative the tablet and the second position being beyond a second pre-defined distance threshold, and switching between paintbrushes of a brush tool being performed responsive to recognition of the brush switching gesture; determining which of the plurality of actions to perform based on the recognized stylus gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions. | 1. A method, comprising: using a computer to perform: collecting information about a user manipulation of a stylus in relation to a tablet device associated with the computer; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, such that: the stylus gesture is one of a plurality of stylus gestures that are recognized by the computer to perform at least one of a plurality of actions in a graphics application that comprises a natural media painting application, at least some of the stylus gestures are mapped to user manipulation of the stylus at a distance from the tablet device, at least some of the stylus gestures involve contact of the stylus with the tablet device, and the stylus gestures include a brush switching gesture in which a proximity of the stylus to the tablet changes from a first position relative to the tablet to a second position that is further away from the tablet and with at least a rate of change that corresponds to the brush switching gesture, the first position being within a first pre-defined distance threshold relative the tablet and the second position being beyond a second pre-defined distance threshold, and switching between paintbrushes of a brush tool being performed responsive to recognition of the brush switching gesture; determining which of the plurality of actions to perform based on the recognized stylus gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions. 8. The method of claim 1 , wherein the plurality of stylus gestures includes shaking the stylus towards the tablet, shaking the stylus away from the tablet, and twisting the stylus about the major axis of the stylus; and wherein the action that is performed in response to recognition of shaking the stylus towards the tablet includes splattering paint; wherein the action that is performed in response to recognition of shaking the stylus away from the tablet includes cleaning the brush tool; and wherein the action that is performed in response to recognition of twisting the stylus includes homogenizing the colors of paint on the brush tool. | 0.604167 |
8,855,999 | 14 | 15 | 14. The non-transitory computer readable medium of claim 13 , wherein the expression used for evaluating the input string comprises one or more string comparisons. | 14. The non-transitory computer readable medium of claim 13 , wherein the expression used for evaluating the input string comprises one or more string comparisons. 15. The non-transitory computer readable medium of claim 14 , wherein two or more string comparisons are associated through a Boolean expression. | 0.941105 |
9,514,120 | 1 | 2 | 1. A method comprising: identifying, by a processing device, a potential typographical error in a work using an initial reference, wherein the work comprises a plurality of words; sending, by the processing device, data indicative of presence of the potential typographical error in the work to a plurality of users; receiving, by the processing device, feedback for the work from the plurality of users, the feedback comprising an indicator that specifies that the potential typographical error is an author-intended string for the work, wherein the author-intended string comprises at least one of an author-intended spelling of one or more words, an author-intended punctuation, an author-intended grammar, or an author-intended use of one or more foreign language words; combining, by the processing device, the feedback from the plurality of users for the work with feedback for a plurality of additional works to generate a combined feedback; sorting, by the processing device, the combined feedback based on one or more selected parameters associated with the work to generate a sorted feedback, wherein the one or more selected parameters comprises at least one of an author associated with the work, a title associated the work, a topic associated with the work, or a publisher associated with the work; determining, by the processing device and based on the sorted feedback, that the potential typographical error comprises an acceptable string; and updating, by the processing device, the initial reference to include the acceptable string. | 1. A method comprising: identifying, by a processing device, a potential typographical error in a work using an initial reference, wherein the work comprises a plurality of words; sending, by the processing device, data indicative of presence of the potential typographical error in the work to a plurality of users; receiving, by the processing device, feedback for the work from the plurality of users, the feedback comprising an indicator that specifies that the potential typographical error is an author-intended string for the work, wherein the author-intended string comprises at least one of an author-intended spelling of one or more words, an author-intended punctuation, an author-intended grammar, or an author-intended use of one or more foreign language words; combining, by the processing device, the feedback from the plurality of users for the work with feedback for a plurality of additional works to generate a combined feedback; sorting, by the processing device, the combined feedback based on one or more selected parameters associated with the work to generate a sorted feedback, wherein the one or more selected parameters comprises at least one of an author associated with the work, a title associated the work, a topic associated with the work, or a publisher associated with the work; determining, by the processing device and based on the sorted feedback, that the potential typographical error comprises an acceptable string; and updating, by the processing device, the initial reference to include the acceptable string. 2. The method of claim 1 , wherein determining that the potential typographical error comprises an acceptable string comprises: determining a percentage of the sorted feedback that identifies the potential typographical error as an author-intended string; determining that the percentage exceeds a threshold percentage; and identifying the potential typographical error as an acceptable string. | 0.736983 |
9,250,805 | 1 | 2 | 1. A method for entering a string of symbols, the method comprising: generating for display a sequence of symbols arranged in a row, wherein the symbols are grouped in groupings; monitoring user navigation between the groupings of symbols; determining a navigation pace based on the monitored user navigation, the navigation pace representing an interval of time taken by the user to navigate from a first grouping of symbols to a second grouping of symbols; receiving a user input to navigate to a third grouping of symbols; and selecting symbols for the third grouping of symbols based on the determined navigation pace in response to receiving the user input. | 1. A method for entering a string of symbols, the method comprising: generating for display a sequence of symbols arranged in a row, wherein the symbols are grouped in groupings; monitoring user navigation between the groupings of symbols; determining a navigation pace based on the monitored user navigation, the navigation pace representing an interval of time taken by the user to navigate from a first grouping of symbols to a second grouping of symbols; receiving a user input to navigate to a third grouping of symbols; and selecting symbols for the third grouping of symbols based on the determined navigation pace in response to receiving the user input. 2. The method of claim 1 , wherein selecting the symbols for the third grouping of symbols further comprises: selecting all but one of the symbols of the second grouping, when the navigation pace is determined to be at or below a threshold rate; and selecting at least one of: (i) a plurality of symbols, wherein each symbols of the plurality of symbols is not contained in the second grouping, and (ii) all but at least two of the symbols of the second grouping, when the navigation pace is determined to be above the threshold rate. | 0.664573 |
9,430,531 | 26 | 34 | 26. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information, and the personally identifiable information of the recipient comprises an e-mail address of the recipient; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. | 26. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information, and the personally identifiable information of the recipient comprises an e-mail address of the recipient; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. 34. The method of claim 26 wherein the plurality of activity data comprises activity data collected from an instant messaging application. | 0.870787 |
8,195,683 | 8 | 14 | 8. A machine-readable medium including instructions, which when executed by a machine cause the machine to perform operations comprising: receiving a search query including a token, the search query to be performed on data in a database stored on the machine-readable medium or a different machine-readable medium, the database including items of data that are represented by data strings; determining a synonym candidate for the token; adding the synonym candidate as a synonym for the token into an expansion dictionary in response to a determination that the number of data strings having the synonym candidate exceeds a threshold and a determination that the synonym candidate and the token are in a same category for a level of a tree hierarchy in the database, the tree hierarchy including a plurality of nodes having parent-child relationships; expanding the search query to include the synonym to form an expanded search query; and performing a search, using the expanded search query, for data in the database. | 8. A machine-readable medium including instructions, which when executed by a machine cause the machine to perform operations comprising: receiving a search query including a token, the search query to be performed on data in a database stored on the machine-readable medium or a different machine-readable medium, the database including items of data that are represented by data strings; determining a synonym candidate for the token; adding the synonym candidate as a synonym for the token into an expansion dictionary in response to a determination that the number of data strings having the synonym candidate exceeds a threshold and a determination that the synonym candidate and the token are in a same category for a level of a tree hierarchy in the database, the tree hierarchy including a plurality of nodes having parent-child relationships; expanding the search query to include the synonym to form an expanded search query; and performing a search, using the expanded search query, for data in the database. 14. The machine-readable medium of claim 8 , wherein the threshold is 15. | 0.878333 |
8,838,611 | 1 | 2 | 1. A document ranking system comprising: a content score calculating unit comprising a processor configured to calculate a content score of a first document with respect to each of at least one word contained in the first document; a contribution coefficient determining unit to determine a contribution coefficient of the first document indicative of the first document's contribution value to a second document with respect to a common word included in the first document and the second document; a contribution score calculating unit to calculate a contribution score of the first document based on the contribution coefficient of the first document; a storage device to store the content score and the contribution score; a ranking unit to rank the first document for the at least one word, based on the content score and the contribution score; and an accumulation coefficient calculating unit to calculate an accumulation coefficient of the first document, the accumulation coefficient corresponding to a contribution by the first document to the contribution score of the first document to the second document with respect to the common word, wherein the ranking unit is configured to apply the accumulation coefficient to the content score and the contribution score, or to apply the accumulation coefficient to the contribution score. | 1. A document ranking system comprising: a content score calculating unit comprising a processor configured to calculate a content score of a first document with respect to each of at least one word contained in the first document; a contribution coefficient determining unit to determine a contribution coefficient of the first document indicative of the first document's contribution value to a second document with respect to a common word included in the first document and the second document; a contribution score calculating unit to calculate a contribution score of the first document based on the contribution coefficient of the first document; a storage device to store the content score and the contribution score; a ranking unit to rank the first document for the at least one word, based on the content score and the contribution score; and an accumulation coefficient calculating unit to calculate an accumulation coefficient of the first document, the accumulation coefficient corresponding to a contribution by the first document to the contribution score of the first document to the second document with respect to the common word, wherein the ranking unit is configured to apply the accumulation coefficient to the content score and the contribution score, or to apply the accumulation coefficient to the contribution score. 2. The document ranking system of claim 1 , wherein the content score calculating unit is configured to calculate the content score based on relevance between content of the first document and the at least one word. | 0.755125 |
9,208,509 | 8 | 9 | 8. The computer program of claim 1 , further including storing the size of the working vocabulary of the user in the profile of the user. | 8. The computer program of claim 1 , further including storing the size of the working vocabulary of the user in the profile of the user. 9. The computer program of claim 8 , wherein the content is personalized by identifying the size of the working vocabulary of the user from the profile of the user. | 0.956705 |
8,930,376 | 24 | 26 | 24. A method for generating an abstract associated with a web page, comprising: obtaining a plurality of bookmarking tags collected via a bookmarking Web service associated with the web page from a database, wherein the bookmarking Web service is configured to allow users to store bookmarks associated with the web page and share the bookmarks with other users, and wherein each bookmarking tag in the plurality of bookmarking tags comprises a text descriptor assigned to the web page; determining a subject matter associated with the web page based on the plurality of bookmarking tags; dividing textual content of the web page into a series of fragments of the web page each of which is associated with a topic; applying a scoring function to each fragment in the series of fragments to calculate a score for each fragment, wherein the scoring function is based at least in part on a measure of similarity between the subject matter and the topic associated with the fragment; selecting one or more fragments in the series of fragments of the web page based on the score calculated for each fragment, wherein the one or more fragments have maximum scores among the series of fragments; and generating the abstract associated with the web page from the selected one or more fragments of the web page. | 24. A method for generating an abstract associated with a web page, comprising: obtaining a plurality of bookmarking tags collected via a bookmarking Web service associated with the web page from a database, wherein the bookmarking Web service is configured to allow users to store bookmarks associated with the web page and share the bookmarks with other users, and wherein each bookmarking tag in the plurality of bookmarking tags comprises a text descriptor assigned to the web page; determining a subject matter associated with the web page based on the plurality of bookmarking tags; dividing textual content of the web page into a series of fragments of the web page each of which is associated with a topic; applying a scoring function to each fragment in the series of fragments to calculate a score for each fragment, wherein the scoring function is based at least in part on a measure of similarity between the subject matter and the topic associated with the fragment; selecting one or more fragments in the series of fragments of the web page based on the score calculated for each fragment, wherein the one or more fragments have maximum scores among the series of fragments; and generating the abstract associated with the web page from the selected one or more fragments of the web page. 26. The method of claim 24 , wherein obtaining a plurality of bookmarking tags associated with the web page comprises: assigning bookmarking tags to the web page, wherein the assigned bookmarking tags are associated with one or more additional web pages that are deemed relevant to the web page. | 0.834083 |
6,163,785 | 26 | 27 | 26. A computer-based method for translating source language text to a foreign language, comprising the steps of: (1) entering input text in a source language into a text editor; (2) checking, via a language editor, said input text against a constrained source language; (3) providing to an author interactive feedback relating to said source input text if non-constrained source language is present in said source input text until said author modifies said source input text into a constrained source text, wherein said interactive feedback includes allowing said author to select, from a list of at least one synonym, a word or phrase to replace said non-constrained source language; (4) checking for syntactic grammatical errors and semantic ambiguities in said constrained source text; (5) providing interactive feedback to said author to remove said syntactic grammatical errors and said semantic ambiguities in said constrained source text to produce unambiguous constrained source text; and (6) translating, via a machine translation system, said unambiguous constrained source text into a target language; wherein steps (2) and (4) further include the step of communicating with a tripartite domain model (DM), wherein said tripartite DM provides predetermined domain knowledge and linguistic semantic knowledge about lexical units and their combinations, said tripartite domain model including, a kernel which contains lexical information that is required by said language editor and said a machine translation system, wherein said lexical information includes lexical items within said constrained source language along with associated semantic concepts, parts of speech, and morphological information, a language editor domain model which contains information that is required only by said language editor, wherein said information includes at least one of a set of synonyms for items not within said constrained source language, a dictionary of definitions of said lexical items, and a set of examples of using said lexical items, and a machine translation domain model which contains information which is required by only said machine translation system, said machine translation domain model includes a hierarchy of concepts used for unambiguous mapping and semantic verification in translation. | 26. A computer-based method for translating source language text to a foreign language, comprising the steps of: (1) entering input text in a source language into a text editor; (2) checking, via a language editor, said input text against a constrained source language; (3) providing to an author interactive feedback relating to said source input text if non-constrained source language is present in said source input text until said author modifies said source input text into a constrained source text, wherein said interactive feedback includes allowing said author to select, from a list of at least one synonym, a word or phrase to replace said non-constrained source language; (4) checking for syntactic grammatical errors and semantic ambiguities in said constrained source text; (5) providing interactive feedback to said author to remove said syntactic grammatical errors and said semantic ambiguities in said constrained source text to produce unambiguous constrained source text; and (6) translating, via a machine translation system, said unambiguous constrained source text into a target language; wherein steps (2) and (4) further include the step of communicating with a tripartite domain model (DM), wherein said tripartite DM provides predetermined domain knowledge and linguistic semantic knowledge about lexical units and their combinations, said tripartite domain model including, a kernel which contains lexical information that is required by said language editor and said a machine translation system, wherein said lexical information includes lexical items within said constrained source language along with associated semantic concepts, parts of speech, and morphological information, a language editor domain model which contains information that is required only by said language editor, wherein said information includes at least one of a set of synonyms for items not within said constrained source language, a dictionary of definitions of said lexical items, and a set of examples of using said lexical items, and a machine translation domain model which contains information which is required by only said machine translation system, said machine translation domain model includes a hierarchy of concepts used for unambiguous mapping and semantic verification in translation. 27. The method of claim 26, further comprising the step of marking with a tag a portion of said input text which has been rendered unambiguous constrained source text, wherein said tag indicates translatability. | 0.844624 |
5,386,494 | 24 | 27 | 24. An apparatus for controlling a speech recognition function comprising: (a) a data processing system having a speech recognition function and having a display, the data processing system for displaying at least one object and a moveable cursor on the display; (b) a speech recognition input device coupled to the data processing system for inputting spoken commands for the data processing system; and (c) a cursor control device coupled to the data processing system for controlling the moveable cursor displayed on the display in x and y directions simultaneously, the cursor control device including: (i) a first selector for selecting one of the at least one object displayed on the display, and (ii) a second selector separate from the first selector for activating and deactivating the speech recognition function of the data processing system. | 24. An apparatus for controlling a speech recognition function comprising: (a) a data processing system having a speech recognition function and having a display, the data processing system for displaying at least one object and a moveable cursor on the display; (b) a speech recognition input device coupled to the data processing system for inputting spoken commands for the data processing system; and (c) a cursor control device coupled to the data processing system for controlling the moveable cursor displayed on the display in x and y directions simultaneously, the cursor control device including: (i) a first selector for selecting one of the at least one object displayed on the display, and (ii) a second selector separate from the first selector for activating and deactivating the speech recognition function of the data processing system. 27. The apparatus of claim 24, wherein the first selector includes a pointer button, the cursor control device is for selecting the one object in response to user-manipulation of the pointer button, and the data processing system is for indicating on the display the selection of the one object. | 0.780832 |
6,081,774 | 9 | 10 | 9. The information retrieval system of claim 8, wherein said keyword builder further comprises: a topic prioritizer that prioritizes the normalized topics in said topic tree in accordance with the frequency of their occurrence and other indicators of their importance inferred from said token attributes; and a keyword processor for selecting topic records based on their assigned priority, and for normalizing said topics contained in said selected topic records, said topics inserted into said keyword list as said content-based data base keywords. | 9. The information retrieval system of claim 8, wherein said keyword builder further comprises: a topic prioritizer that prioritizes the normalized topics in said topic tree in accordance with the frequency of their occurrence and other indicators of their importance inferred from said token attributes; and a keyword processor for selecting topic records based on their assigned priority, and for normalizing said topics contained in said selected topic records, said topics inserted into said keyword list as said content-based data base keywords. 10. The information retrieval system of claim 9, wherein said linguistic array generator comprises: a token attribute generator for identifying and morphologically and syntactically characterizing said tokens and said sentence units in the said database files and for populating said a linguistic array with identified attributes; a syntactic tagger for supplementing said linguistic array with morphological, syntactic and linguistic data identifying a relative importance of each token in said array; and a parse filter for filtering tokens from said array that are likely not to assist in matching said query keywords with said database keywords. | 0.637835 |
9,412,367 | 10 | 17 | 10. Computerized information and display apparatus, comprising: a wireless network interface; processing apparatus in data communication with the network interface; a display device; a data interface in data communication with the processing apparatus and configured to transfer data between the computerized information and display apparatus and a portable electronic device placed in data communication with the data interface; and a storage apparatus comprising at least one computer program, said at least one program being configured to, when executed: obtain digitized speech generated based on speech received from a user, the digitized speech relating to a desired action which the user wishes to perform; and cause, based at least in part on the digitized speech, access of a network entity to cause performance of the desired action; wherein the computerized information and display apparatus is further configured to: receive information obtained via the access of the network entity via the wireless network interface; and provide at least a portion of the received information to the portable electronic device via the data interface; wherein the computerized information and display apparatus further comprises speech synthesis apparatus in data communication with the processing apparatus; and wherein the computerized information and display system is further configured to engage the user in an interactive dialogue, the dialogue comprising: (i) the speech is received from the user; (ii) at least one subsequent confirmatory or adaptive response to the speech generated audibly by at least the speech synthesis apparatus, the response based at least in part on the speech; and (iii) at least one subsequent speech input provided by the user after the response is audibly generated; wherein the computerized information and display apparatus is disposed within a land- mobile transport device capable of moving between locations, and further comprises: at least one infra-red radiation detection apparatus in data communication with at least a portion of the data processing apparatus and configured to cause the computerized information apparatus to generate a visually perceptible alert of the presence of a human in an area proximate to the transport device, the visually perceptible alert comprising a rendering on the display device showing at least a portion of the area; and a short-range wireless interface configured to obtain user-specific data from a portable user radio frequency device when the portable user radio frequency device is within sufficient range of the short-range interface, and provide the obtained data to the computerized information apparatus so as to enable one or more functions of the transport device, according to a previously supplied user preference or profile. | 10. Computerized information and display apparatus, comprising: a wireless network interface; processing apparatus in data communication with the network interface; a display device; a data interface in data communication with the processing apparatus and configured to transfer data between the computerized information and display apparatus and a portable electronic device placed in data communication with the data interface; and a storage apparatus comprising at least one computer program, said at least one program being configured to, when executed: obtain digitized speech generated based on speech received from a user, the digitized speech relating to a desired action which the user wishes to perform; and cause, based at least in part on the digitized speech, access of a network entity to cause performance of the desired action; wherein the computerized information and display apparatus is further configured to: receive information obtained via the access of the network entity via the wireless network interface; and provide at least a portion of the received information to the portable electronic device via the data interface; wherein the computerized information and display apparatus further comprises speech synthesis apparatus in data communication with the processing apparatus; and wherein the computerized information and display system is further configured to engage the user in an interactive dialogue, the dialogue comprising: (i) the speech is received from the user; (ii) at least one subsequent confirmatory or adaptive response to the speech generated audibly by at least the speech synthesis apparatus, the response based at least in part on the speech; and (iii) at least one subsequent speech input provided by the user after the response is audibly generated; wherein the computerized information and display apparatus is disposed within a land- mobile transport device capable of moving between locations, and further comprises: at least one infra-red radiation detection apparatus in data communication with at least a portion of the data processing apparatus and configured to cause the computerized information apparatus to generate a visually perceptible alert of the presence of a human in an area proximate to the transport device, the visually perceptible alert comprising a rendering on the display device showing at least a portion of the area; and a short-range wireless interface configured to obtain user-specific data from a portable user radio frequency device when the portable user radio frequency device is within sufficient range of the short-range interface, and provide the obtained data to the computerized information apparatus so as to enable one or more functions of the transport device, according to a previously supplied user preference or profile. 17. The computerized information and display apparatus of claim 10 , wherein the at least portion of the received information comprises a map image or map graphic of a geographic region, the map image or map graphic which is viewable on both a display of the portable electronic device and the display device of the host system; and wherein the at least portion of the received information further comprises directions to an organization or entity. | 0.913246 |
9,792,555 | 11 | 12 | 11. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executed by a fatigue life prediction processor to perform methods steps for probabilistic fatigue life prediction for a part of a turbine, the method comprising the steps of: in the fatigue life prediction processor, receiving a probability of detection model; in a fatigue life prediction processor, receiving an initial crack size probability density function (PDF) for the turbine part based on the received probability of detection model; in the fatigue life prediction processor, receiving probabilistic identification of model parameters; in the fatigue life prediction processor, receiving a model parameter PDF based on the received probabilistic identification of model parameters according to:
ƒ(ln C,m )˜MVN(μ (ln C,m) ,Σ (ln C,m) ), where MVN is a multivariate normal distribution, C and m are model parameters from fatigue testing data, μ (ln C,m) is a mean vector and Σ (ln C,m) is a covariance matrix; providing a crack growth model based on the received initial crack size PDF, the model parameter PDF and material/load factors; determining uncertainty propagation using an analytical or simulation-based method based on the crack growth model based on uncertainty of at least one of material properties, geometries, sensitivity of instruments, and loading of the turbine part; providing fatigue life prediction based on the uncertainty propagation and crack growth model; and implementing a maintenance plan for the turbine part based on the fatigue life prediction. | 11. A non-transitory program storage device readable by a computer, tangibly embodying a program of instructions executed by a fatigue life prediction processor to perform methods steps for probabilistic fatigue life prediction for a part of a turbine, the method comprising the steps of: in the fatigue life prediction processor, receiving a probability of detection model; in a fatigue life prediction processor, receiving an initial crack size probability density function (PDF) for the turbine part based on the received probability of detection model; in the fatigue life prediction processor, receiving probabilistic identification of model parameters; in the fatigue life prediction processor, receiving a model parameter PDF based on the received probabilistic identification of model parameters according to:
ƒ(ln C,m )˜MVN(μ (ln C,m) ,Σ (ln C,m) ), where MVN is a multivariate normal distribution, C and m are model parameters from fatigue testing data, μ (ln C,m) is a mean vector and Σ (ln C,m) is a covariance matrix; providing a crack growth model based on the received initial crack size PDF, the model parameter PDF and material/load factors; determining uncertainty propagation using an analytical or simulation-based method based on the crack growth model based on uncertainty of at least one of material properties, geometries, sensitivity of instruments, and loading of the turbine part; providing fatigue life prediction based on the uncertainty propagation and crack growth model; and implementing a maintenance plan for the turbine part based on the fatigue life prediction. 12. The computer readable program storage device according to claim 11 , wherein nondestructive examination (NDE) data and NDE sizing data is used in the probability of detection model. | 0.847107 |
9,747,267 | 4 | 5 | 4. A method as described in claim 1 , wherein the indicating of correspondence includes changing a visual characteristic of the second portion of the second document to differentiate the second portion of the second document from one or more other portions of the second document. | 4. A method as described in claim 1 , wherein the indicating of correspondence includes changing a visual characteristic of the second portion of the second document to differentiate the second portion of the second document from one or more other portions of the second document. 5. A method as described in claim 4 , wherein the changing does not include altering a visual characteristic of the first document. | 0.951192 |
9,355,174 | 3 | 4 | 3. The process of claim 1 , wherein the first plurality of factors further comprises a level of influence by a particular type of media categorization data associated with the first data and an identified integrity of the first source. | 3. The process of claim 1 , wherein the first plurality of factors further comprises a level of influence by a particular type of media categorization data associated with the first data and an identified integrity of the first source. 4. The process of claim 3 , wherein the identified integrity of the first source is based on a correlation between particular categories associated with the first data. | 0.952164 |
9,189,954 | 1 | 7 | 1. A radio device comprising a gesture pad that receives a gesture input, that distinguishes between a plurality of fingers used for a gesture, that recognizes the orientation of the distinguished finger, and that performs a function that is dependent on the distinguished finger and its orientation. | 1. A radio device comprising a gesture pad that receives a gesture input, that distinguishes between a plurality of fingers used for a gesture, that recognizes the orientation of the distinguished finger, and that performs a function that is dependent on the distinguished finger and its orientation. 7. The device of claim 1 , wherein the gesture input comprises pressing against the gesture pad with a finger. | 0.90161 |
8,548,973 | 1 | 2 | 1. A method comprising: extracting metadata attributes and associated attribute values from web search results, the web search results returned in response to a search request submitted by a user from a computer of the user to a web search engine, the search request comprising search criteria input by the user to the search engine, the search request input by the user using a user interface to the computer, the web search results comprising entries organized into a results list, each entry comprising data extracted from a data object searched by the web search engine and meeting the search criteria, the metadata attributes and associated attribute values extracted from the data objects corresponding to the entries of the results list, each metadata attribute comprising one or more associated attribute values, each metadata attribute comprising a category, each associated attribute value comprising value that corresponding to an associated metadata attribute, wherein the search request of the user does not include, in the search request, the metadata attribute and associated attribute values returned by the web search engine; prioritizing one or more of the extracted metadata attributes and the attribute values, wherein one or more of: the metadata attributes are prioritized based on a number of times attribute values of each metadata attribute occurs in the results list, wherein the metadata attributes are organized so a metadata attribute with a largest number of attribute value occurrences is displayed first in the display of metadata attributes to the user; and the metadata attributes are prioritized based on a number of occurrences for each metadata attribute and wherein presenting the metadata attributes to the user further comprises presenting a subset of metadata attributes to the user, the subset comprising metadata attributes occurring most often in the results list; presenting the prioritized extracted metadata attributes to a user for selection by the user, the prioritized extracted metadata attributes presented to the user on a portion of an electronic display displaying the web search results; receiving input from the user indicating a selected metadata attribute of the metadata attributes; presenting attribute values associated with the selected metadata attribute to the user for selection by the user, the extracted attribute values of the selected metadata attribute are presented to the user on a portion of an electronic display displaying the web search results; receiving input from the user indicating a selected attribute value of the attribute values associated with the selected metadata attribute; filtering the web search results based on the selected attribute value, wherein each entry in the filtered web search results comprises the selected attribute value; and displaying a filtered results list to the user, the filtered results list comprising the filtered web search results. | 1. A method comprising: extracting metadata attributes and associated attribute values from web search results, the web search results returned in response to a search request submitted by a user from a computer of the user to a web search engine, the search request comprising search criteria input by the user to the search engine, the search request input by the user using a user interface to the computer, the web search results comprising entries organized into a results list, each entry comprising data extracted from a data object searched by the web search engine and meeting the search criteria, the metadata attributes and associated attribute values extracted from the data objects corresponding to the entries of the results list, each metadata attribute comprising one or more associated attribute values, each metadata attribute comprising a category, each associated attribute value comprising value that corresponding to an associated metadata attribute, wherein the search request of the user does not include, in the search request, the metadata attribute and associated attribute values returned by the web search engine; prioritizing one or more of the extracted metadata attributes and the attribute values, wherein one or more of: the metadata attributes are prioritized based on a number of times attribute values of each metadata attribute occurs in the results list, wherein the metadata attributes are organized so a metadata attribute with a largest number of attribute value occurrences is displayed first in the display of metadata attributes to the user; and the metadata attributes are prioritized based on a number of occurrences for each metadata attribute and wherein presenting the metadata attributes to the user further comprises presenting a subset of metadata attributes to the user, the subset comprising metadata attributes occurring most often in the results list; presenting the prioritized extracted metadata attributes to a user for selection by the user, the prioritized extracted metadata attributes presented to the user on a portion of an electronic display displaying the web search results; receiving input from the user indicating a selected metadata attribute of the metadata attributes; presenting attribute values associated with the selected metadata attribute to the user for selection by the user, the extracted attribute values of the selected metadata attribute are presented to the user on a portion of an electronic display displaying the web search results; receiving input from the user indicating a selected attribute value of the attribute values associated with the selected metadata attribute; filtering the web search results based on the selected attribute value, wherein each entry in the filtered web search results comprises the selected attribute value; and displaying a filtered results list to the user, the filtered results list comprising the filtered web search results. 2. The method of claim 1 , wherein the selected metadata attribute comprises a first selected metadata attribute, the selected attribute value comprises a first selected attribute value, the filtered web search results comprise first filtered web search results, and displaying the filtered results list comprises displaying a first filtered results list, the method further comprising receiving input from the user indicating a second selected metadata attribute of the metadata attributes and receiving input from the user indicating a second selected attribute value, filtering the first filtered web search results based on the second selected attribute value to create second filtered web search results and displaying a second filtered results list to the user, the second filtered results list comprising the second filtered web search results. | 0.739117 |
10,157,231 | 1 | 4 | 1. A system for monitoring electronic interactions with unique items and identifying and analyzing significant attributes of the unique items, the system comprising: one or more computer readable storage devices configured to store a plurality of computer executable instructions; and one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the system to: generate user activity data by at least electronically communicating, over a computer network, with a plurality of user devices to receive monitoring data related to user interactions with unique items displayed by user interfaces of the plurality of user devices, wherein the monitoring data comprises position data related to a position of a unique item displayed by a user interface at a time of the user interaction; generate one or more driver models configured to enable identification of which of a plurality of attributes of a selected unique item are driver attributes and to enable determination of values associated with the driver attributes, the plurality of attributes comprising at least a condition attribute and a feature attribute, wherein generating the one or more driver models comprises: using the position data to reduce any position bias present in the monitoring data; and using one or more of the following methods: linear regression, non-linear regression, model trees, nearest neighbor analysis; receive selected item data, the selected item data being related to the plurality of attributes of the selected unique item; and apply one or more of the generated driver models to the selected item data to generate values associated with driver attributes of the selected unique item for use in generating recommendations of alternative unique items. | 1. A system for monitoring electronic interactions with unique items and identifying and analyzing significant attributes of the unique items, the system comprising: one or more computer readable storage devices configured to store a plurality of computer executable instructions; and one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the system to: generate user activity data by at least electronically communicating, over a computer network, with a plurality of user devices to receive monitoring data related to user interactions with unique items displayed by user interfaces of the plurality of user devices, wherein the monitoring data comprises position data related to a position of a unique item displayed by a user interface at a time of the user interaction; generate one or more driver models configured to enable identification of which of a plurality of attributes of a selected unique item are driver attributes and to enable determination of values associated with the driver attributes, the plurality of attributes comprising at least a condition attribute and a feature attribute, wherein generating the one or more driver models comprises: using the position data to reduce any position bias present in the monitoring data; and using one or more of the following methods: linear regression, non-linear regression, model trees, nearest neighbor analysis; receive selected item data, the selected item data being related to the plurality of attributes of the selected unique item; and apply one or more of the generated driver models to the selected item data to generate values associated with driver attributes of the selected unique item for use in generating recommendations of alternative unique items. 4. The system of claim 1 , wherein the generated values associated with the driver attributes of the selected unique item describe at least one of the following: an estimated price contribution of a driver attribute to an overall price of the selected unique item, a perceived value of a driver attribute, a level of desirability of a driver attribute. | 0.738872 |
5,546,145 | 1 | 16 | 1. In a photographic camera including an optical lens, a photographic filmstrip transport mechanism for advancing the filmstrip in a path of travel to and through an image frame exposure gate with respect to said optical lens, and an exposure system for making an exposure of the filmstrip image frame in the exposure gate, apparatus for recording a voice message composed by the camera user related to the exposure made or to be made for playback in conjunction with making prints from the photographic images captured in the image frames of the filmstrip to provide for the printing of the voice message therewith comprising: speech input means into which a camera user may speak words of the message to be stored with respect to the filmstrip image frames; sound processing means for processing the words spoken into the speech input means as voice digital data; means for providing reference voice digital data corresponding to a reference word vocabulary; speech recognition means for comparing the processed voice digital data to the reference voice digital data and recognizing processed voice digital data corresponding to the reference voice digital data while rejecting voice digital data not finding correspondence with the reference voice digital data; message memory means having memory locations related to each image frame of the filmstrip for storing recognized voice digital data; and means for storing the recognized voice digital data in said message memory means, wherein said means for providing reference voice digital data corresponding to a word vocabulary further comprises: first vocabulary memory means for storing a fixed vocabulary of words that cannot be altered by the user; and second vocabulary memory means for storing a adjustable vocabulary of words selected by the user, wherein said first vocabulary memory means comprises a read only memory stored with said fixed vocabulary from which said fixed vocabulary may be read by said speech recognition means; and said second vocabulary memory means comprises a read and write memory into which said adjustable vocabulary may be written in and from which said adjustable vocabulary may be read by said speech recognition means; and further comprising interface mean for receiving said adjustable vocabulary from an external source and for writing said adjustable vocabulary into said second vocabulary memory means. | 1. In a photographic camera including an optical lens, a photographic filmstrip transport mechanism for advancing the filmstrip in a path of travel to and through an image frame exposure gate with respect to said optical lens, and an exposure system for making an exposure of the filmstrip image frame in the exposure gate, apparatus for recording a voice message composed by the camera user related to the exposure made or to be made for playback in conjunction with making prints from the photographic images captured in the image frames of the filmstrip to provide for the printing of the voice message therewith comprising: speech input means into which a camera user may speak words of the message to be stored with respect to the filmstrip image frames; sound processing means for processing the words spoken into the speech input means as voice digital data; means for providing reference voice digital data corresponding to a reference word vocabulary; speech recognition means for comparing the processed voice digital data to the reference voice digital data and recognizing processed voice digital data corresponding to the reference voice digital data while rejecting voice digital data not finding correspondence with the reference voice digital data; message memory means having memory locations related to each image frame of the filmstrip for storing recognized voice digital data; and means for storing the recognized voice digital data in said message memory means, wherein said means for providing reference voice digital data corresponding to a word vocabulary further comprises: first vocabulary memory means for storing a fixed vocabulary of words that cannot be altered by the user; and second vocabulary memory means for storing a adjustable vocabulary of words selected by the user, wherein said first vocabulary memory means comprises a read only memory stored with said fixed vocabulary from which said fixed vocabulary may be read by said speech recognition means; and said second vocabulary memory means comprises a read and write memory into which said adjustable vocabulary may be written in and from which said adjustable vocabulary may be read by said speech recognition means; and further comprising interface mean for receiving said adjustable vocabulary from an external source and for writing said adjustable vocabulary into said second vocabulary memory means. 16. The recording apparatus of claim 1 further comprising: means for playing back and audibly reproducing the recognized and stored voice digital data; and means operable by the speaker to erase the stored voice digital data and repeat the speech input in an editing of the message to be printed in relation to the image frame. | 0.775103 |
8,510,117 | 7 | 9 | 7. An apparatus of speech enabled media sharing in a multimodal application, the apparatus including a multimodal application and a multimodal browser, a module of automated computing machinery operating on a multimodal device supporting multiple modes of user interaction, the modes of user interaction including a voice mode and one or more non-voice modes, wherein the voice mode includes accepting speech input from a user, digitizing the speech, and providing digitized speech to a speech engine, and wherein the non-voice mode includes accepting input from a user through physical user interaction with a user input device for the multimodal device; the apparatus comprising computer program instructions for parsing, by the multimodal browser, one or more markup documents of a multimodal application; identifying, by the multimodal browser, in the one or more markup documents a web resource for display in the multimodal browser; identifying metadata associated with each of the web resources identified in the one or more markup documents for simultaneous display in the multimodal browser; loading a disambiguating grammar including keywords selected in dependence upon the metadata associated with each of the web resources; loading, by the multimodal browser, a web resource sharing grammar that includes keywords for modes of resource sharing and keywords for targets for receipt of web resources; receiving, by the multimodal browser, a plurality of utterances matching keywords of the disambiguating grammar for at least two of the web resources, a keyword for a mode of resource sharing and a keyword for a target for receipt of the at least two of the web resources; and sending, by the multimodal browser, the web resources to the identified target for the web resources using the identified mode of resource sharing. | 7. An apparatus of speech enabled media sharing in a multimodal application, the apparatus including a multimodal application and a multimodal browser, a module of automated computing machinery operating on a multimodal device supporting multiple modes of user interaction, the modes of user interaction including a voice mode and one or more non-voice modes, wherein the voice mode includes accepting speech input from a user, digitizing the speech, and providing digitized speech to a speech engine, and wherein the non-voice mode includes accepting input from a user through physical user interaction with a user input device for the multimodal device; the apparatus comprising computer program instructions for parsing, by the multimodal browser, one or more markup documents of a multimodal application; identifying, by the multimodal browser, in the one or more markup documents a web resource for display in the multimodal browser; identifying metadata associated with each of the web resources identified in the one or more markup documents for simultaneous display in the multimodal browser; loading a disambiguating grammar including keywords selected in dependence upon the metadata associated with each of the web resources; loading, by the multimodal browser, a web resource sharing grammar that includes keywords for modes of resource sharing and keywords for targets for receipt of web resources; receiving, by the multimodal browser, a plurality of utterances matching keywords of the disambiguating grammar for at least two of the web resources, a keyword for a mode of resource sharing and a keyword for a target for receipt of the at least two of the web resources; and sending, by the multimodal browser, the web resources to the identified target for the web resources using the identified mode of resource sharing. 9. The apparatus of claim 7 wherein computer program instructions identifying, by the multimodal browser, in the one or more markup documents the web resources for display in the multimodal browser further comprises identifying, for at least one of the web resources, an element in the multimodal application containing metadata describing the location of the web resource. | 0.833184 |
7,917,847 | 40 | 47 | 40. The method according to claim 39 , further comprising judging whether or not predetermined user operation is performed, wherein the predetermined user operation includes operation for canceling the switching of the onscreen representation, and wherein the switching of the onscreen representation if cancelled if it is judged by the judging that the predetermined user operation is performed, and the switching of the onscreen representation is performed if it is judged by the judging that the predetermined user operation is not performed. | 40. The method according to claim 39 , further comprising judging whether or not predetermined user operation is performed, wherein the predetermined user operation includes operation for canceling the switching of the onscreen representation, and wherein the switching of the onscreen representation if cancelled if it is judged by the judging that the predetermined user operation is performed, and the switching of the onscreen representation is performed if it is judged by the judging that the predetermined user operation is not performed. 47. The method according to claim 40 , wherein the operation for canceling the switching of the onscreen representation includes at least one of scrolling operation, storing operation and printing operation. | 0.905479 |
8,086,557 | 17 | 21 | 17. A system for providing a factuality assessment of a retrieved information source's statement comprising: memory which stores as software instructions: a query formulator for receiving a user's query which identifies an information source whose statements are to be retrieved and generates a query for retrieving documents from an associated source of documents which refer to the information source; a mapping component for mapping statements in the retrieved documents to their authors and identifying as an information source's statement, a statement that is mapped to an author which is compatible with the information source; a factuality determiner, which determines a factuality of the information source's statements, based on the content of the statement; and a processing component in communication with the memory, which executes the instructions. | 17. A system for providing a factuality assessment of a retrieved information source's statement comprising: memory which stores as software instructions: a query formulator for receiving a user's query which identifies an information source whose statements are to be retrieved and generates a query for retrieving documents from an associated source of documents which refer to the information source; a mapping component for mapping statements in the retrieved documents to their authors and identifying as an information source's statement, a statement that is mapped to an author which is compatible with the information source; a factuality determiner, which determines a factuality of the information source's statements, based on the content of the statement; and a processing component in communication with the memory, which executes the instructions. 21. The system of claim 17 , further comprising a lexicon accessible by the mapping component, in which text elements which are expressions of information transfer are indexed as such for identifying whether an expression for information transfer is present in a retrieved document. | 0.501767 |
9,275,641 | 1 | 2 | 1. A method, comprising: enabling a developer, by a first server comprising at least one processor and a memory storing processor-executable codes, to create a developer profile; receiving, by the first server, one or more developer example requests, wherein each of the developer example requests is associated with one or more phrases; determining, by the first server, one or more dialog system entities from the one or more example requests using a machine-learning technique, wherein the one or more dialog system entities are associated with the developer profile; determining, by the first server, one or more dialog system intents from the one or more developer example requests using a machine-learning technique, wherein the one or more dialog system intents are associated with the developer profile; associating, by the first server, the one or more dialog system entities with the one or more dialog system intents to form a custom dialog system engine; linking, by the first server, the custom dialog system engine with a dialog system interface using the developer profile, wherein the dialog system interface is provided on a client user device or a web server; receiving, by the first server or a second server, a user request from the dialog system interface, wherein the dialog system interface is installed on a user device or a third server; identifying, by the first server or the second server, the dialog system interface based on the user request; based on the identification of the dialog system interface, activating, by the first server or the second server, the custom dialog system engine and retrieving the one or more dialog system entities and the one or more dialog system intents; processing, by the first server or the second server, the user request by applying the one or more dialog system entities and the one or more dialog system intents; and generating, by the first server or the second server, a response to the user request based on the processing and sending the response to the dialog system interface. | 1. A method, comprising: enabling a developer, by a first server comprising at least one processor and a memory storing processor-executable codes, to create a developer profile; receiving, by the first server, one or more developer example requests, wherein each of the developer example requests is associated with one or more phrases; determining, by the first server, one or more dialog system entities from the one or more example requests using a machine-learning technique, wherein the one or more dialog system entities are associated with the developer profile; determining, by the first server, one or more dialog system intents from the one or more developer example requests using a machine-learning technique, wherein the one or more dialog system intents are associated with the developer profile; associating, by the first server, the one or more dialog system entities with the one or more dialog system intents to form a custom dialog system engine; linking, by the first server, the custom dialog system engine with a dialog system interface using the developer profile, wherein the dialog system interface is provided on a client user device or a web server; receiving, by the first server or a second server, a user request from the dialog system interface, wherein the dialog system interface is installed on a user device or a third server; identifying, by the first server or the second server, the dialog system interface based on the user request; based on the identification of the dialog system interface, activating, by the first server or the second server, the custom dialog system engine and retrieving the one or more dialog system entities and the one or more dialog system intents; processing, by the first server or the second server, the user request by applying the one or more dialog system entities and the one or more dialog system intents; and generating, by the first server or the second server, a response to the user request based on the processing and sending the response to the dialog system interface. 2. The method of claim 1 , wherein the one or more dialog system entities include one or more of the following: a keyword and at least one synonym to the keyword, a keyword and at least one definition of the keyword, and a list of keywords defining objects of one class. | 0.58589 |
9,128,981 | 1 | 6 | 1. A system for presenting social-network-provided outputs to a mobile-electronic-device user at a location associated with the user in response to the user's spoken request, comprising: a data input port configured to receive speech information from the mobile-electronic-device user; a memory configured to store a transcript of the spoken request and metadata associated with the spoken request comprising at least the location during the spoken request; an interface port to a social network database, configured to transmit a request to mine information of the social network database based on the transcript and the metadata, and to receive social network information from the social network database based on the transmitted request; at least one processor configured to transmit the request through the interface port dependent on at least the transcript and the metadata, to receive the social network information from the interface port; and a communication port configured to communicate at least a portion of the social-network information to the user, wherein the social network database comprises a plurality of social network records, the at least one processor being further configured to rank the received social network information comprising a plurality of received social network records dependent on at least one social network ranking factor, the communication port being further configured to output at least a portion of the social network records in a manner dependent on the at least one social network ranking factor. | 1. A system for presenting social-network-provided outputs to a mobile-electronic-device user at a location associated with the user in response to the user's spoken request, comprising: a data input port configured to receive speech information from the mobile-electronic-device user; a memory configured to store a transcript of the spoken request and metadata associated with the spoken request comprising at least the location during the spoken request; an interface port to a social network database, configured to transmit a request to mine information of the social network database based on the transcript and the metadata, and to receive social network information from the social network database based on the transmitted request; at least one processor configured to transmit the request through the interface port dependent on at least the transcript and the metadata, to receive the social network information from the interface port; and a communication port configured to communicate at least a portion of the social-network information to the user, wherein the social network database comprises a plurality of social network records, the at least one processor being further configured to rank the received social network information comprising a plurality of received social network records dependent on at least one social network ranking factor, the communication port being further configured to output at least a portion of the social network records in a manner dependent on the at least one social network ranking factor. 6. The system according to claim 1 , further comprising outputting the mined information based on a type of social information within a respective social network record. | 0.810538 |
6,078,746 | 8 | 9 | 8. A method in a computer system for interpreted selection of an operand for an operator during data entry of the nodes of an intentional program tree, the method comprising: receiving a sequence of tokens, each token indicating a computational construct corresponding to a node of the intentional program tree; adding a node to the intentional program tree for each token in the sequence; receiving an indication of a next token to be appended to the sequence of tokens; and when the next token represents an operator, identifying an operand of the operator according to predefined rules of operator precedence; and adding a node to the intentional program tree indicating the operator with the identified operand. | 8. A method in a computer system for interpreted selection of an operand for an operator during data entry of the nodes of an intentional program tree, the method comprising: receiving a sequence of tokens, each token indicating a computational construct corresponding to a node of the intentional program tree; adding a node to the intentional program tree for each token in the sequence; receiving an indication of a next token to be appended to the sequence of tokens; and when the next token represents an operator, identifying an operand of the operator according to predefined rules of operator precedence; and adding a node to the intentional program tree indicating the operator with the identified operand. 9. The method of claim 8 wherein the predefined rules of operator precedence are in accordance with the C programming language. | 0.86105 |
9,569,420 | 14 | 15 | 14. The information processing apparatus of claim 13 , wherein the CPU is further configured to assign a score to the keyword, based on at least the computed frequency. | 14. The information processing apparatus of claim 13 , wherein the CPU is further configured to assign a score to the keyword, based on at least the computed frequency. 15. The information processing apparatus of claim 14 , wherein the CPU is further configured to store, in the keyword database, at least one of the keyword meaning of the keyword, the score assigned to the keyword, a location of the keyword within the electronic document, or a portion of the obtained text data that includes the keyword. | 0.859518 |
7,490,092 | 165 | 166 | 165. A method of indexing and searching timed media files, as recited in claim 161 , wherein when at least two query information representations have been input, further comprises the step of calculating a merged virtual document that is relevant to all of the said at least two query information representations. | 165. A method of indexing and searching timed media files, as recited in claim 161 , wherein when at least two query information representations have been input, further comprises the step of calculating a merged virtual document that is relevant to all of the said at least two query information representations. 166. A method of indexing and searching timed media files, as recited in claim 165 , wherein said calculation of a merged virtual document includes the calculation of a relevant virtual document and a highly relevant virtual document. | 0.885182 |
10,142,269 | 1 | 4 | 1. A communications system, comprising: a processing device; a network interface; non-transitory computer readable memory that stores program code that when executed by the processing device is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; enable delivery of a voice message, directed to the user, to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the voice message to be played via a web browser of a second computing device associated with the user; enable the user to send a textual reply message, via the web browser of the second computing device associated with the user, to an originator of the voice message without the user entering an address of the originator of the voice message; and receive, via the network interface, a user voice message deletion instruction from the web browser of the second computing device associated with the user; in response to the user voice message deletion instruction received from the web browser of the second computing device associated with the user, enable the voice message to be deleted from a user interface presented by the browser, and in cooperation with the software program on the first computing device associated with of the user, enable deletion of the voice message on the first computing device associated with the user. | 1. A communications system, comprising: a processing device; a network interface; non-transitory computer readable memory that stores program code that when executed by the processing device is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; enable delivery of a voice message, directed to the user, to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the voice message to be played via a web browser of a second computing device associated with the user; enable the user to send a textual reply message, via the web browser of the second computing device associated with the user, to an originator of the voice message without the user entering an address of the originator of the voice message; and receive, via the network interface, a user voice message deletion instruction from the web browser of the second computing device associated with the user; in response to the user voice message deletion instruction received from the web browser of the second computing device associated with the user, enable the voice message to be deleted from a user interface presented by the browser, and in cooperation with the software program on the first computing device associated with of the user, enable deletion of the voice message on the first computing device associated with the user. 4. The communications system as defined in claim 1 , wherein the browser interface enables the user to send a textual reply message by receiving a text entry from a user and transmitting the received text entry over a data network to a computing device associated with the message originator. | 0.654846 |
9,053,179 | 7 | 13 | 7. A computer program product for providing a citation network viewer, the computer program product stored in one or more non-transitory computer-readable memory devices and readable by a computer, the computer program product comprising executable instructions that, when read and executed by the computer, causes the computer to: create a series of metadata files from a plurality of documents, wherein at least some of the documents have a citation and discuss at least one issue, the citations of the documents form a multi-dimensional network of citations, the at least one issue is represented by one of a headnote and a reason for citing, and the series of metadata files are created by: identifying at least a portion of citations, reasons-for-citing and headnotes associated with the identified citations from individual sentences of the plurality of documents; converting the identified reasons-for-citing and the identified headnotes in at least some of the documents of the plurality of documents into vectors; and establishing one or more semantic links between individual documents of the plurality of documents by pairing starting reasons-for-citing in citing documents with cited reasons-for-citing and headnotes in cited documents; create a sub-network of citations of documents that corresponds to a specific issue from the metadata files of the documents forming the multi-dimensional network; and provide for display an interactive user interface representing the sub-network, the interactive user interface comprising a plurality of icons, wherein: each icon represents an individual reason-for-citing or headnote within an individual document; each icon is linked to another icon by a line, the line indicating only a citation between documents represented by the linked icons; and the plurality of icons are hierarchically arranged. | 7. A computer program product for providing a citation network viewer, the computer program product stored in one or more non-transitory computer-readable memory devices and readable by a computer, the computer program product comprising executable instructions that, when read and executed by the computer, causes the computer to: create a series of metadata files from a plurality of documents, wherein at least some of the documents have a citation and discuss at least one issue, the citations of the documents form a multi-dimensional network of citations, the at least one issue is represented by one of a headnote and a reason for citing, and the series of metadata files are created by: identifying at least a portion of citations, reasons-for-citing and headnotes associated with the identified citations from individual sentences of the plurality of documents; converting the identified reasons-for-citing and the identified headnotes in at least some of the documents of the plurality of documents into vectors; and establishing one or more semantic links between individual documents of the plurality of documents by pairing starting reasons-for-citing in citing documents with cited reasons-for-citing and headnotes in cited documents; create a sub-network of citations of documents that corresponds to a specific issue from the metadata files of the documents forming the multi-dimensional network; and provide for display an interactive user interface representing the sub-network, the interactive user interface comprising a plurality of icons, wherein: each icon represents an individual reason-for-citing or headnote within an individual document; each icon is linked to another icon by a line, the line indicating only a citation between documents represented by the linked icons; and the plurality of icons are hierarchically arranged. 13. The computer program product as claimed in claim 7 , wherein the computer program product further comprises executable instructions that, when read by the computer, causes the computer to build vector metadata files for reasons-for-citing and headnotes in each document. | 0.86245 |
9,652,787 | 1 | 5 | 1. A system comprising: one or more processors of a machine; a first machine-readable medium storing a plurality of generative grammar models; and a second machine-readable medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising: receiving a request to generate a message; selecting a generative grammar model from the plurality of generative grammar models in response to receiving the request, the generative grammar model defining a message structure for the requested message, the message structure including a plurality of lexical slots, the generative grammar model specifying: a corpus of source data to populate each lexical slot in the plurality of lexical slots; and a grammatical constraint for each lexical slot-in the plurality of lexical slots; generating the message using the generative grammar model; verifying that the message adheres to a messaging standard of a social network platform; and causing the message to be published to one or more users through publication on the social network platform. | 1. A system comprising: one or more processors of a machine; a first machine-readable medium storing a plurality of generative grammar models; and a second machine-readable medium storing instructions that, when executed by the one or more processors, cause the machine to perform operations comprising: receiving a request to generate a message; selecting a generative grammar model from the plurality of generative grammar models in response to receiving the request, the generative grammar model defining a message structure for the requested message, the message structure including a plurality of lexical slots, the generative grammar model specifying: a corpus of source data to populate each lexical slot in the plurality of lexical slots; and a grammatical constraint for each lexical slot-in the plurality of lexical slots; generating the message using the generative grammar model; verifying that the message adheres to a messaging standard of a social network platform; and causing the message to be published to one or more users through publication on the social network platform. 5. The system of claim 1 , wherein the generating the message comprises: for each lexical slot in the plurality of lexical slots: accessing the corpus of source data corresponding to the lexical slot; extracting a term from the corpus of source data in accordance with the grammatical constraint corresponding to the lexical slot; and populating the lexical slot with the extracted term. | 0.501289 |
7,822,750 | 15 | 18 | 15. A computer-based method for comparing a plurality of data objects comprising the steps of: providing a plurality of first data objects; providing a plurality of second data objects; providing at least one third object; applying a topic model technique to the plurality of first data objects, the plurality of second data objects and the at least one third data object creating a topic model; the topic model technique further comprises pre-processing the plurality of first data object, the plurality of second data object and the at least one third data object whereby the data objects are normalized; grouping the plurality of second data objects creating a plurality of groupings; determining a first similarity of each of the plurality of first data objects and each of the plurality of groupings; determining a second similarity of the plurality of second data objects in each of the plurality of groupings; comparing the first similarity and the second similarity to determine a plurality of optimum similarities of the plurality of first data objects and the plurality of groupings; and representing the plurality of optimum similarities. | 15. A computer-based method for comparing a plurality of data objects comprising the steps of: providing a plurality of first data objects; providing a plurality of second data objects; providing at least one third object; applying a topic model technique to the plurality of first data objects, the plurality of second data objects and the at least one third data object creating a topic model; the topic model technique further comprises pre-processing the plurality of first data object, the plurality of second data object and the at least one third data object whereby the data objects are normalized; grouping the plurality of second data objects creating a plurality of groupings; determining a first similarity of each of the plurality of first data objects and each of the plurality of groupings; determining a second similarity of the plurality of second data objects in each of the plurality of groupings; comparing the first similarity and the second similarity to determine a plurality of optimum similarities of the plurality of first data objects and the plurality of groupings; and representing the plurality of optimum similarities. 18. The computer-based method of claim 15 wherein the step of determining the first similarity and the second similarity comprises applying at least one similarity metric. | 0.745536 |
9,495,415 | 1 | 13 | 1. A method comprising: receiving a plurality of data objects at a user device, said plurality of data objects including program guide data; parsing search data from the plurality of data objects at the user device to form a search index different than the program guide data, said search index comprising search string objects, token objects and word objects, said word objects each having a first word and a second word associated therewith, said search string objects each having at least one token identifier associated therewith; storing the search index within the user device separate from the program guide data; in response to a search query, searching the search index stored within the user device by identifying the word object from the search query alphabetically until a second space is entered in a user interface, and, after the second space is entered performing: identifying token objects from the word object, identifying a string object from the token object, and obtaining a token list having token objects and thereafter storing the token list to one of the token objects; generating search results from the search index; and displaying search results. | 1. A method comprising: receiving a plurality of data objects at a user device, said plurality of data objects including program guide data; parsing search data from the plurality of data objects at the user device to form a search index different than the program guide data, said search index comprising search string objects, token objects and word objects, said word objects each having a first word and a second word associated therewith, said search string objects each having at least one token identifier associated therewith; storing the search index within the user device separate from the program guide data; in response to a search query, searching the search index stored within the user device by identifying the word object from the search query alphabetically until a second space is entered in a user interface, and, after the second space is entered performing: identifying token objects from the word object, identifying a string object from the token object, and obtaining a token list having token objects and thereafter storing the token list to one of the token objects; generating search results from the search index; and displaying search results. 13. A method as recited in claim 1 further comprising weighting the search results with a relevance weight associated with a string object, wherein displaying the search results comprises displaying the search results in response to the relevance weight. | 0.820874 |
9,652,809 | 11 | 19 | 11. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method for associating an avatar with a user identity, the method comprising: detecting a selection by a user, the selection being at least one of an avatar selection and a wallpaper selection for use in an instant messaging environment, wherein the selected avatar or wallpaper comprise one or more attributes; inferring, using at least one processor, one or more user profile attributes for the user based on the detected user selection, wherein the inferred user profile attributes are not identical to the one or more attributes of the selected avatar or wallpaper; storing, the inferred user profile attributes in a user profile of the user, wherein the user profile is viewable by one or more other users within the instant messaging environment; accessing stored attributes for multiple avatars that are potential candidates for selection by the user to represent the user in a communications session; identifying a subset of less than all of the multiple avatars based on a comparison between the inferred user profile attributes located in the stored user profile and the accessed avatar attributes; and presenting the identified subset of avatars for selection by the user. | 11. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method for associating an avatar with a user identity, the method comprising: detecting a selection by a user, the selection being at least one of an avatar selection and a wallpaper selection for use in an instant messaging environment, wherein the selected avatar or wallpaper comprise one or more attributes; inferring, using at least one processor, one or more user profile attributes for the user based on the detected user selection, wherein the inferred user profile attributes are not identical to the one or more attributes of the selected avatar or wallpaper; storing, the inferred user profile attributes in a user profile of the user, wherein the user profile is viewable by one or more other users within the instant messaging environment; accessing stored attributes for multiple avatars that are potential candidates for selection by the user to represent the user in a communications session; identifying a subset of less than all of the multiple avatars based on a comparison between the inferred user profile attributes located in the stored user profile and the accessed avatar attributes; and presenting the identified subset of avatars for selection by the user. 19. The non-transitory computer-readable storage medium of claim 11 , wherein the method performed by the at least one processor further comprises: receiving a selection of one of the presented avatars in the subset; presenting avatar attributes associated with the selected avatar for selection by the user; receiving a selection of one or more of the presented avatar attributes; and associating the selected one or more avatar attributes with the selected avatar in the instant messaging environment. | 0.550089 |
8,775,933 | 4 | 8 | 4. The method as claimed in claim 1 , wherein the transformation of the document fragment of the source document is a changing a visual characteristic of the document fragment of the source document. | 4. The method as claimed in claim 1 , wherein the transformation of the document fragment of the source document is a changing a visual characteristic of the document fragment of the source document. 8. The method as claimed in claim 4 , wherein the changed visual characteristic of the document fragment is a three-dimensional effect. | 0.937092 |
7,634,456 | 26 | 27 | 26. The method of claim 25 , further comprising: generating, at the query optimizer, appropriate recommendations to improve performance based on rules in a knowledge base. | 26. The method of claim 25 , further comprising: generating, at the query optimizer, appropriate recommendations to improve performance based on rules in a knowledge base. 27. The method of claim 26 , wherein each recommendation includes a recommendation to make database schema changes. | 0.95476 |
8,721,339 | 1 | 13 | 1. A method for evaluating a point of originality in a single piece of writing through the identification of original content in the writing, the method comprising: (a) submitting the single piece of writing to a processing system; (b) inputting a first query term, wherein the first query terms is one of a single word or a compound phrase; (c) generating lexical terms from the first query terms; (d) constructing a first matrix of conceptual-semantic and lexical relationships based upon the lexical terms generated from the first query term; (e) searching the writing for terms which appear in the first matrix; and (f) computing an originality estimate value for each of the terms in the writing which match one or more terms in the first matrix, wherein the originality estimate value is based upon the lexical relationships between the terms in the writing and the terms in the first matrix; (g) computing a point of originality score; and (h) presenting the point of originality score on a timeline graph, wherein the timeline graph depicts the evolution of point of originality scores for a particular person over a period of time. | 1. A method for evaluating a point of originality in a single piece of writing through the identification of original content in the writing, the method comprising: (a) submitting the single piece of writing to a processing system; (b) inputting a first query term, wherein the first query terms is one of a single word or a compound phrase; (c) generating lexical terms from the first query terms; (d) constructing a first matrix of conceptual-semantic and lexical relationships based upon the lexical terms generated from the first query term; (e) searching the writing for terms which appear in the first matrix; and (f) computing an originality estimate value for each of the terms in the writing which match one or more terms in the first matrix, wherein the originality estimate value is based upon the lexical relationships between the terms in the writing and the terms in the first matrix; (g) computing a point of originality score; and (h) presenting the point of originality score on a timeline graph, wherein the timeline graph depicts the evolution of point of originality scores for a particular person over a period of time. 13. The method of claim 1 wherein the first matrix of conceptual-semantic and lexical relationships is generated by a lexical database, wherein the lexical database is substantially capable of arranging the query terms by noting the similarity between two words that don't have literally identical meanings. | 0.858395 |
8,397,157 | 1 | 9 | 1. A method comprising: accessing, in at least one of a memory device and a data storage device, a first data object and a second data object of a data structure, the data structure representing a page description language document that includes page description language document content and non-page description language document content included or referenced in data objects of the page description language document, the second data object being associated with the first data object; selecting, based on first content included in the first data object, a grammar rule included in a grammar, the grammar rule including a grammar rule item, the grammar being a descriptive specification composed of grammar rules used to computationally determine content types to facilitate selection of grammar rules suitable to translate electronic content to a desired form utilizing grammar rule items; based on second content included in the second data object, selecting the grammar rule item included in the grammar rule, the second content being non-page description language document content; based on the second content and the grammar rule item, executing instructions on a computer processor to generate a portion of a markup language document representation of the page description language document; and wherein the non-page description language document content is at least one of digital video, frames or sets of frames of digital video, digital audio, an animation, an image, and a media stream. | 1. A method comprising: accessing, in at least one of a memory device and a data storage device, a first data object and a second data object of a data structure, the data structure representing a page description language document that includes page description language document content and non-page description language document content included or referenced in data objects of the page description language document, the second data object being associated with the first data object; selecting, based on first content included in the first data object, a grammar rule included in a grammar, the grammar rule including a grammar rule item, the grammar being a descriptive specification composed of grammar rules used to computationally determine content types to facilitate selection of grammar rules suitable to translate electronic content to a desired form utilizing grammar rule items; based on second content included in the second data object, selecting the grammar rule item included in the grammar rule, the second content being non-page description language document content; based on the second content and the grammar rule item, executing instructions on a computer processor to generate a portion of a markup language document representation of the page description language document; and wherein the non-page description language document content is at least one of digital video, frames or sets of frames of digital video, digital audio, an animation, an image, and a media stream. 9. The method of claim 1 , wherein the grammar rule item includes output control instructions, and wherein the generating of the portion of the markup language document representation is according to the output control instructions. | 0.923584 |
10,069,971 | 1 | 5 | 1. A system comprising: one or more processors; memory; and one or more computer-executable instructions that are stored in the memory and that are executable by the one or more processors to: access audio signals of a conversation between a customer and a customer service (CS) agent; track attributes of the audio signals, one or more attributes of the attributes quantifying aspects of the conversation based at least in part on words spoken by the customer and the CS agent; determine that the one or more attributes include one or more pauses greater than a threshold amount of time; determine mood imagery based at least in part on the one or more attributes, the mood imagery indicating a first estimation of a state of mind of the customer during a first time period of the conversation; determine that the mood imagery includes a first facial expression, the first facial expression being selected from a plurality of facial expressions based at least in part on analyzing the one or more attributes and being associated with the first estimation of the state of mind of the customer; generate a first communication suggestion for the CS agent based at least in part on analyzing the conversation and the first estimation of the state of mind of the customer, the first communication suggestion including a first suggestion to at least one of decrease a rate of speech, or use a word or utterance less frequently; generate a first time series graph indicating a measured element associated with the one or more attributes, the one or more attributes including at least one of a volume, a pitch, or a speed of spoken words of at least the CS agent; generate a second time series graph indicating a score for the CS agent, the score based at least in part on aggregating the attributes, the attributes including the volume, the pitch, and the speed of the spoken words; and cause first visual output of the mood imagery, the first time series graph, the second time series graph, and the first communication suggestion for view by the CS agent, wherein the mood imagery includes the first facial expression being updated in real-time or near real-time based at least in part on a change of the first estimation of the state of mind of the customer. | 1. A system comprising: one or more processors; memory; and one or more computer-executable instructions that are stored in the memory and that are executable by the one or more processors to: access audio signals of a conversation between a customer and a customer service (CS) agent; track attributes of the audio signals, one or more attributes of the attributes quantifying aspects of the conversation based at least in part on words spoken by the customer and the CS agent; determine that the one or more attributes include one or more pauses greater than a threshold amount of time; determine mood imagery based at least in part on the one or more attributes, the mood imagery indicating a first estimation of a state of mind of the customer during a first time period of the conversation; determine that the mood imagery includes a first facial expression, the first facial expression being selected from a plurality of facial expressions based at least in part on analyzing the one or more attributes and being associated with the first estimation of the state of mind of the customer; generate a first communication suggestion for the CS agent based at least in part on analyzing the conversation and the first estimation of the state of mind of the customer, the first communication suggestion including a first suggestion to at least one of decrease a rate of speech, or use a word or utterance less frequently; generate a first time series graph indicating a measured element associated with the one or more attributes, the one or more attributes including at least one of a volume, a pitch, or a speed of spoken words of at least the CS agent; generate a second time series graph indicating a score for the CS agent, the score based at least in part on aggregating the attributes, the attributes including the volume, the pitch, and the speed of the spoken words; and cause first visual output of the mood imagery, the first time series graph, the second time series graph, and the first communication suggestion for view by the CS agent, wherein the mood imagery includes the first facial expression being updated in real-time or near real-time based at least in part on a change of the first estimation of the state of mind of the customer. 5. The system as recited in claim 1 , wherein the computer-executable instructions are further executable by the one or more processors to output a visual post-communication summary that is based at least in part on statistics generated from at least the one or more attributes of the conversation. | 0.809949 |
4,735,515 | 1 | 7 | 1. A printing apparatus, comprising: a processor of stored-program type with a data bus and an address bus for controlling the printing operation sequence of the apparatus; a keyboard for entering character codes; buffer means for storing a character code entered by said keyboard; a character generator connected to the output of said buffer means to be addressed by the character code stored in said buffer means for generating one of a group of character patterns, which corresponds to the addressed one, at the output thereof; a processor-accessible memory connected to the address bus of said processor to be addressed by an address signal issued from said processor and producing data at the addressed location on the data bus, said memory storing character patterns other than the group of character patterns; and means for generating a first selection signal when the character code stored in said buffer means corresponds to one of said group of character patterns and a second selection signal when the character code stored in said buffer means corresponds to one of said other character patterns; wherein said processor in response to the first selection signal directs said buffer means to address said character generator by the character code stored in said buffer means for generating one of said group of character patterns from said character generator, and in response to the second selection signal receives the character code stored in said buffer means to convert the received character code into an address signal and accesses said memory by the converted address signal through the address bus for generating one of said other character patterns on the data bus, wherein said processor does not participate in addressing said character generator for the first selection signal. | 1. A printing apparatus, comprising: a processor of stored-program type with a data bus and an address bus for controlling the printing operation sequence of the apparatus; a keyboard for entering character codes; buffer means for storing a character code entered by said keyboard; a character generator connected to the output of said buffer means to be addressed by the character code stored in said buffer means for generating one of a group of character patterns, which corresponds to the addressed one, at the output thereof; a processor-accessible memory connected to the address bus of said processor to be addressed by an address signal issued from said processor and producing data at the addressed location on the data bus, said memory storing character patterns other than the group of character patterns; and means for generating a first selection signal when the character code stored in said buffer means corresponds to one of said group of character patterns and a second selection signal when the character code stored in said buffer means corresponds to one of said other character patterns; wherein said processor in response to the first selection signal directs said buffer means to address said character generator by the character code stored in said buffer means for generating one of said group of character patterns from said character generator, and in response to the second selection signal receives the character code stored in said buffer means to convert the received character code into an address signal and accesses said memory by the converted address signal through the address bus for generating one of said other character patterns on the data bus, wherein said processor does not participate in addressing said character generator for the first selection signal. 7. A printing apparatus according to claim 1, wherein the processor-accessible memory stores the other character patterns which are not common to a plurality of countries. | 0.748529 |
8,327,255 | 20 | 22 | 20. The computer program product of claim 16 , wherein the executable viewer module in the bundle is further configured to provide a remote processor access to the one or more electronic transcript files and the one or more electronic exhibit files in the bundle over a network connection. | 20. The computer program product of claim 16 , wherein the executable viewer module in the bundle is further configured to provide a remote processor access to the one or more electronic transcript files and the one or more electronic exhibit files in the bundle over a network connection. 22. The computer program product of claim 20 , wherein the executable viewer module in the bundle is further configured to stream the one or more electronic transcript files and the one or more electronic transcript files in the bundle to the remote processor. | 0.930183 |
9,286,888 | 13 | 14 | 13. The recognition method of claim 12 , wherein the determining of whether the speech signal corresponds to the monosyllabic form or the polysyllabic form comprises: detecting a vowel and a consonant from the speech signal; calculating a number of combinations of the vowel and the consonant; and comparing the number of combinations to a predetermined number. | 13. The recognition method of claim 12 , wherein the determining of whether the speech signal corresponds to the monosyllabic form or the polysyllabic form comprises: detecting a vowel and a consonant from the speech signal; calculating a number of combinations of the vowel and the consonant; and comparing the number of combinations to a predetermined number. 14. The speech recognition method of claim 13 , wherein the detecting of the vowel and the consonant from the speech signal comprises: detecting the vowel and the consonant using at least one of an energy of the speech signal, a zero crossing rate of the speech signal, an auto-correlation function of the speech signal, a fundamental frequency of the speech signal, and a spectral tilt of the speech signal. | 0.870558 |
9,571,969 | 5 | 7 | 5. The mobile media communications system of claim 4 , further comprising: the communicating includes sending the one or more conflated query array and the composited data bundles (a) in reply to the query, and (b) also to at least one of an entity and a network site operator as part of one or more push notifications. | 5. The mobile media communications system of claim 4 , further comprising: the communicating includes sending the one or more conflated query array and the composited data bundles (a) in reply to the query, and (b) also to at least one of an entity and a network site operator as part of one or more push notifications. 7. The mobile media communications system of claim 5 , further comprising: a host network server in communication with the media server, the directory search monitor, and the faceting searcher, and configured to receive a response to the one or more push notifications from the network site operator, and to communicate the response to the entity. | 0.933218 |
9,858,260 | 1 | 10 | 1. A method for analyzing items using lexical analysis and filtering process comprising of: storing a plurality of items in a data storage unit, wherein said plurality of items are represented by source data and said source data is one of structured data and unstructured data; parsing the unstructured data of the source data to extract at least One textual data along with any available structured supporting information; parsing the structured data of the source data to extract a set of associated data in a tuple structure, said tuple structure being formed by each a subject being the conceptual information representing each item of said plurality of items, a predicate including information representing one or more categories of each item of said plurality of items, and an object including information representing the extracted data itself; processing the extracted data from each item of said plurality of items, wherein said extracted data is associated with an item of said plurality of items; processing the extracted data from each item of said plurality of items, wherein said extracted data is matched against a list of synonyms associated with said plurality of items; displaying a first group of said items based on said extracted data of said items on an electronic display presented in at least one of a tabular view and a geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data, wherein said first group of said items represents items having at least one common characteristic of said extracted data; mapping each of said plurality of items with at least one lexicon term, wherein said extracted data is analyzed to identify a match between said plurality of items and lexicon terms, wherein said lexicon terms are represented as a network of a plurality of nodes and each node of said plurality of nodes represents a lexicon term, which is subordinate to at least one of a parent node and a child node; mapping each of said plurality of items with at least one lexicon term based on an associated synonym, wherein said extracted data is analyzed to identify a match between said plurality of items and synonyms of said lexicon terms, wherein said lexicon terms are represented as said network of said plurality of nodes and each node of said plurality of nodes represents said lexicon term, said associated synonyms corresponding with at least one lexicon term identified at each node of said plurality of nodes; and displaying a second group of said items, wherein said second group of items represent said items mapped to a first matching lexicon term of said plurality of lexicon terms on said electronic display presented in at least one of said tabular view and said geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data. | 1. A method for analyzing items using lexical analysis and filtering process comprising of: storing a plurality of items in a data storage unit, wherein said plurality of items are represented by source data and said source data is one of structured data and unstructured data; parsing the unstructured data of the source data to extract at least One textual data along with any available structured supporting information; parsing the structured data of the source data to extract a set of associated data in a tuple structure, said tuple structure being formed by each a subject being the conceptual information representing each item of said plurality of items, a predicate including information representing one or more categories of each item of said plurality of items, and an object including information representing the extracted data itself; processing the extracted data from each item of said plurality of items, wherein said extracted data is associated with an item of said plurality of items; processing the extracted data from each item of said plurality of items, wherein said extracted data is matched against a list of synonyms associated with said plurality of items; displaying a first group of said items based on said extracted data of said items on an electronic display presented in at least one of a tabular view and a geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data, wherein said first group of said items represents items having at least one common characteristic of said extracted data; mapping each of said plurality of items with at least one lexicon term, wherein said extracted data is analyzed to identify a match between said plurality of items and lexicon terms, wherein said lexicon terms are represented as a network of a plurality of nodes and each node of said plurality of nodes represents a lexicon term, which is subordinate to at least one of a parent node and a child node; mapping each of said plurality of items with at least one lexicon term based on an associated synonym, wherein said extracted data is analyzed to identify a match between said plurality of items and synonyms of said lexicon terms, wherein said lexicon terms are represented as said network of said plurality of nodes and each node of said plurality of nodes represents said lexicon term, said associated synonyms corresponding with at least one lexicon term identified at each node of said plurality of nodes; and displaying a second group of said items, wherein said second group of items represent said items mapped to a first matching lexicon term of said plurality of lexicon terms on said electronic display presented in at least one of said tabular view and said geospatial view, wherein said electronic display is electrically connected to at least one processor in electronic communication with said source data. 10. The method for analyzing items using lexical analysis and filtering process of claim 1 , further comprising providing a report listing of an improvised explosive device (IED) as an item of said plurality of items. | 0.795669 |
6,122,617 | 1 | 3 | 1. A method of distributing information to an end-user in computer-readable textual form for subsequent conversion into audible form at an end-user location, the method comprising the steps of: receiving at a collection site an information item, wherein the information item includes data in computer-readable textual form, and wherein the data includes a portion that will cause the generation of improperly spoken speech therefrom by a text-to-speech synthesizer positioned at an end-user location; detecting at the collection site the portion of the data of the information item that will cause the generation of improperly spoken speech therefrom by the text-to-speech synthesizer; replacing at the collection site the detected portion of the data of the information item with replacement data in computer-readable textual form that will cause the generation of properly spoken speech therefrom by the text-to-speech synthesizer; and, transmitting the information item from the collection site through a data channel to the end-user location for subsequent conversion into audible form by the text-to-speech synthesizer at the end-user location, wherein the transmitted information item includes the replacement data. | 1. A method of distributing information to an end-user in computer-readable textual form for subsequent conversion into audible form at an end-user location, the method comprising the steps of: receiving at a collection site an information item, wherein the information item includes data in computer-readable textual form, and wherein the data includes a portion that will cause the generation of improperly spoken speech therefrom by a text-to-speech synthesizer positioned at an end-user location; detecting at the collection site the portion of the data of the information item that will cause the generation of improperly spoken speech therefrom by the text-to-speech synthesizer; replacing at the collection site the detected portion of the data of the information item with replacement data in computer-readable textual form that will cause the generation of properly spoken speech therefrom by the text-to-speech synthesizer; and, transmitting the information item from the collection site through a data channel to the end-user location for subsequent conversion into audible form by the text-to-speech synthesizer at the end-user location, wherein the transmitted information item includes the replacement data. 3. The method of claim 1, wherein the replacement data includes data in computer-readable textual form that corresponds to the detected portion of the data of the information item and that is intentionally misspelled to cause the generation of properly spoken speech therefrom by the text-to-speech synthesizer positioned at the end-user location. | 0.745974 |
8,612,297 | 10 | 11 | 10. A system including: a network-based commerce facility that includes one or more processors to present an input interface via a communications network, the input interface includes a plurality of input mechanisms to facilitate user input of comment information and categorization information, the plurality of input mechanisms include a first input mechanism and a second input mechanism, the first input mechanism to facilitate user input of comment information to pertain to a first event of a plurality of events and the second input mechanism to facilitate user input of categorization information that categorizes the comment information that pertains to the first event, the plurality of input mechanism further includes a third input mechanism and a fourth input mechanism, the third input mechanism facilitates user input of comment information that pertains to a second event of the plurality of events and the fourth input mechanism to facilitate user input of categorization information that pertains to a categorization of the comment information that pertains to the second event, the network-based commerce facility to determine whether the input interface includes comment information that is categorized; and a database to store the comment information and the categorization information. | 10. A system including: a network-based commerce facility that includes one or more processors to present an input interface via a communications network, the input interface includes a plurality of input mechanisms to facilitate user input of comment information and categorization information, the plurality of input mechanisms include a first input mechanism and a second input mechanism, the first input mechanism to facilitate user input of comment information to pertain to a first event of a plurality of events and the second input mechanism to facilitate user input of categorization information that categorizes the comment information that pertains to the first event, the plurality of input mechanism further includes a third input mechanism and a fourth input mechanism, the third input mechanism facilitates user input of comment information that pertains to a second event of the plurality of events and the fourth input mechanism to facilitate user input of categorization information that pertains to a categorization of the comment information that pertains to the second event, the network-based commerce facility to determine whether the input interface includes comment information that is categorized; and a database to store the comment information and the categorization information. 11. The system of claim 10 , wherein the network-based commerce facility is to use the user input received via the second input mechanism to determine whether the comment information, that pertains to the first event, is categorized. | 0.571691 |
8,935,681 | 16 | 17 | 16. The computer tool as claimed in claim 10 in which a user program comprises an obfuscator that generates from the image of the original plain text file an obfuscated output file which is intelligible to a specific software tool only. | 16. The computer tool as claimed in claim 10 in which a user program comprises an obfuscator that generates from the image of the original plain text file an obfuscated output file which is intelligible to a specific software tool only. 17. The computer tool as claimed in claim 16 in which the specific software tool is a compiler. | 0.972108 |
7,587,664 | 1 | 9 | 1. A computer implemented method for profiling a user based on the user's activity, the method comprising: assigning one or more topics to each of a plurality of documents based at least in part upon content contained in the documents; maintaining an affinity variable associated with the user for each of one or more of the topics assigned to a document attributed to the user, wherein the affinity variable is a calculated value linking the user to each of the one or more topics assigned to the documents, the affinity variable being calculated using a mathematical function; determining whether a first affinity variable for the user for a given topic has reached a threshold; associating the user with the given topic for the first affinity variable which reaches the threshold; and updating the affinity variable for a first topic for each document created by the user to which the first topic is assigned to maintain the affinity variable, the maintaining including weighting each document created by the user based upon one or more factors including a number of documents to which the first topic is assigned, a period of time over which the documents were created by the user, and a closeness of each document to the first topic. | 1. A computer implemented method for profiling a user based on the user's activity, the method comprising: assigning one or more topics to each of a plurality of documents based at least in part upon content contained in the documents; maintaining an affinity variable associated with the user for each of one or more of the topics assigned to a document attributed to the user, wherein the affinity variable is a calculated value linking the user to each of the one or more topics assigned to the documents, the affinity variable being calculated using a mathematical function; determining whether a first affinity variable for the user for a given topic has reached a threshold; associating the user with the given topic for the first affinity variable which reaches the threshold; and updating the affinity variable for a first topic for each document created by the user to which the first topic is assigned to maintain the affinity variable, the maintaining including weighting each document created by the user based upon one or more factors including a number of documents to which the first topic is assigned, a period of time over which the documents were created by the user, and a closeness of each document to the first topic. 9. The method of claim 1 , comprising storing a content catalog accessible by a plurality of users, which content catalog contains topics associated with documents to which the topics are assigned, and wherein the step of associating the user with the given topic comprises associating the user with the given topic contained in the content catalog. | 0.595128 |
9,202,242 | 1 | 10 | 1. A method executed by a procurement catalog server and an enterprise procurement application coupled to one or more clients and one or more external sites over a network connection, the method comprising: determining a classification of items in an order procurement catalog retrieved from a procurement catalog database, the order procurement catalog allowing a user to order an item, the classification organizing a plurality of types of items in the classification amongst categories; arranging the categories as a plurality of nodes in a category hierarchy; tracing a path along the category hierarchy to determine an ancestral relationship between the plurality of nodes; analyzing a tracing direction of the path to identify adjacent nodes at a same level in the hierarchy; receiving, from the client over the network connection, a query for an item using the enterprise procurement application for the order procurement catalog, the enterprise procurement application configured to allow a user in an enterprise to order items from the order procurement catalog over the network using the client; determining a plurality of items for the query based upon the category in which the item is included, with said category including related items associated with nodes adjacent to the node to which the item is associated, wherein the plurality of items includes a first type of item and a second type of item, wherein the first type of item requires a different method of ordering from the second type of item; and displaying the plurality of items, including the related items, in response to the query for procurement by the user thereof. | 1. A method executed by a procurement catalog server and an enterprise procurement application coupled to one or more clients and one or more external sites over a network connection, the method comprising: determining a classification of items in an order procurement catalog retrieved from a procurement catalog database, the order procurement catalog allowing a user to order an item, the classification organizing a plurality of types of items in the classification amongst categories; arranging the categories as a plurality of nodes in a category hierarchy; tracing a path along the category hierarchy to determine an ancestral relationship between the plurality of nodes; analyzing a tracing direction of the path to identify adjacent nodes at a same level in the hierarchy; receiving, from the client over the network connection, a query for an item using the enterprise procurement application for the order procurement catalog, the enterprise procurement application configured to allow a user in an enterprise to order items from the order procurement catalog over the network using the client; determining a plurality of items for the query based upon the category in which the item is included, with said category including related items associated with nodes adjacent to the node to which the item is associated, wherein the plurality of items includes a first type of item and a second type of item, wherein the first type of item requires a different method of ordering from the second type of item; and displaying the plurality of items, including the related items, in response to the query for procurement by the user thereof. 10. The method of claim 1 , wherein the query comprises a search or browse for an item. | 0.815678 |
8,725,495 | 10 | 12 | 10. A system for processing data, comprising: an interface to a storage device configured to store a set of data; and a processor, communicating with the storage device via the interface, the processor being configured to: identify a set of seed words comprising words defined as either positive words or negative words; extract, from the set of data, adjectives linked to the set of seed words with “and”; extract, from the set of data, adjectives linked to the set of seed words with “but”; determine a first value indicating a first frequency with which the adjectives are linked to the set of seed words with “and”; determine a second value indicating a second frequency with which the adjectives are linked to the set of seed words with “but”; calculate a synonym score using an equation x ij =w ij + +Log(d ij + +1), wherein x ij corresponds to the synonym score, w ij + corresponds to a number of times that a word i and a word j appear to be synonyms, and d ij + corresponds to the first frequency; and calculate, by a processor, sentiment scores for each adjective of the set of data based on the synonym score and an antonym score calculated using the second value. | 10. A system for processing data, comprising: an interface to a storage device configured to store a set of data; and a processor, communicating with the storage device via the interface, the processor being configured to: identify a set of seed words comprising words defined as either positive words or negative words; extract, from the set of data, adjectives linked to the set of seed words with “and”; extract, from the set of data, adjectives linked to the set of seed words with “but”; determine a first value indicating a first frequency with which the adjectives are linked to the set of seed words with “and”; determine a second value indicating a second frequency with which the adjectives are linked to the set of seed words with “but”; calculate a synonym score using an equation x ij =w ij + +Log(d ij + +1), wherein x ij corresponds to the synonym score, w ij + corresponds to a number of times that a word i and a word j appear to be synonyms, and d ij + corresponds to the first frequency; and calculate, by a processor, sentiment scores for each adjective of the set of data based on the synonym score and an antonym score calculated using the second value. 12. The system of claim 10 , wherein the set of seed words comprises a positive set and a negative set. | 0.877381 |
8,381,299 | 43 | 45 | 43. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for outputting a dataset based upon anomaly detection, the method comprising: receiving a first training dataset having a plurality of n-grams that includes a first plurality of distinct training n-grams, wherein each of the first plurality of distinct training n-grams is a first size; receiving a second training dataset having a plurality of n-grams that includes a second plurality of distinct training n-grams, wherein each of the second plurality of distinct training n-grams is the first size; computing a first plurality of appearance frequencies, wherein each of the first plurality of appearance frequencies corresponds to one of the first plurality of distinct training n-grams; computing a first plurality of uniformities of distribution, wherein each of the first plurality of uniformities of distribution corresponds to one of the first plurality of distinct training n-grams; computing a second plurality of uniformities of distribution, wherein each of the second plurality of uniformities of distribution corresponds to one of the second plurality of distinct training n-grams; determining a first plurality of most-heavily weighted n-grams from the first plurality of distinct training n-grams using at least one of: the first plurality of appearance frequencies; the first plurality of uniformities of distribution; and the second plurality of uniformities of distribution; selecting a subset of the first plurality of most-heavily weighted n-grams, wherein the subset includes m n-grams and at least one of the n-grams in the subset is outside of the top m of the first plurality of most-heavily weighted n-grams; receiving an input dataset including first input n-grams wherein each of the plurality of first input n-grams is the first size; obtaining a subset of a second plurality of most-heavily weighted n-grams from the first input n-grams that correspond to the subset of the first plurality of distinct training n-grams; classifying the input dataset as containing an anomaly using the subset of the first plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams; and outputting a dataset based upon the classifying of the input dataset. | 43. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for outputting a dataset based upon anomaly detection, the method comprising: receiving a first training dataset having a plurality of n-grams that includes a first plurality of distinct training n-grams, wherein each of the first plurality of distinct training n-grams is a first size; receiving a second training dataset having a plurality of n-grams that includes a second plurality of distinct training n-grams, wherein each of the second plurality of distinct training n-grams is the first size; computing a first plurality of appearance frequencies, wherein each of the first plurality of appearance frequencies corresponds to one of the first plurality of distinct training n-grams; computing a first plurality of uniformities of distribution, wherein each of the first plurality of uniformities of distribution corresponds to one of the first plurality of distinct training n-grams; computing a second plurality of uniformities of distribution, wherein each of the second plurality of uniformities of distribution corresponds to one of the second plurality of distinct training n-grams; determining a first plurality of most-heavily weighted n-grams from the first plurality of distinct training n-grams using at least one of: the first plurality of appearance frequencies; the first plurality of uniformities of distribution; and the second plurality of uniformities of distribution; selecting a subset of the first plurality of most-heavily weighted n-grams, wherein the subset includes m n-grams and at least one of the n-grams in the subset is outside of the top m of the first plurality of most-heavily weighted n-grams; receiving an input dataset including first input n-grams wherein each of the plurality of first input n-grams is the first size; obtaining a subset of a second plurality of most-heavily weighted n-grams from the first input n-grams that correspond to the subset of the first plurality of distinct training n-grams; classifying the input dataset as containing an anomaly using the subset of the first plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams; and outputting a dataset based upon the classifying of the input dataset. 45. The medium of claim 43 , the method further comprising: receiving a third training dataset having a plurality of n-grams that includes a third plurality of distinct training n-grams, wherein each of the third plurality of distinct training n-grams is the first size and contains malicious code; computing a third plurality of uniformities of distribution, wherein each of the third plurality of uniformities of distribution corresponds to one of the third plurality of distinct training n-grams; and determining a third plurality of most-heavily weighted n-grams from the third plurality of distinct training n-grams using at least one of: the first plurality of appearance frequencies; the first plurality of uniformities of distribution; and the third plurality of uniformities of distribution; and classifying the input dataset as containing an anomaly using a subset of the third plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams. | 0.697892 |
9,595,055 | 16 | 17 | 16. The computer storage medium of claim 10 , wherein the computer-executable instructions, when executed by the processor, cause the processor to perform operations further comprising: accessing, by the processor, a social networking account associated with the user; obtaining, by the processor and from a fourth device associated with the social networking account, the feedback; generating, by the processor, feedback data comprising a summary of the feedback, wherein the summary indicates an aspect of the item and a summary of opinions relating to the aspect of the item; and providing, by the processor, the feedback data to the manufacturer to enable rapid prototyping by the manufacturer. | 16. The computer storage medium of claim 10 , wherein the computer-executable instructions, when executed by the processor, cause the processor to perform operations further comprising: accessing, by the processor, a social networking account associated with the user; obtaining, by the processor and from a fourth device associated with the social networking account, the feedback; generating, by the processor, feedback data comprising a summary of the feedback, wherein the summary indicates an aspect of the item and a summary of opinions relating to the aspect of the item; and providing, by the processor, the feedback data to the manufacturer to enable rapid prototyping by the manufacturer. 17. The computer storage medium of claim 16 , wherein the summary comprises an indication of demographics associated with the summary of the feedback, the demographics comprising a geographic location and an age. | 0.935247 |
7,568,171 | 46 | 47 | 46. The computer program product of claim 41 , wherein moving the element is based at least in part on whether the stroke intersects itself. | 46. The computer program product of claim 41 , wherein moving the element is based at least in part on whether the stroke intersects itself. 47. The computer program product of claim 46 , wherein whether the stroke intersects itself is used to determine whether the element generally faces a screen space. | 0.950986 |
9,489,373 | 1 | 5 | 1. One or more hardware computer-readable media having embodied thereon computer-usable instructions that, when executed, facilitate a method of segment extraction by a user for a machine learning system, the method comprising: storing a set of data items, wherein each data item includes a plurality of tokens; providing a segment extractor that is trainable to identify a segment within a data item as an example of a concept, wherein the segment includes a group of tokens; presenting on a user interface a concept hierarchy that represents the concept, wherein the concept hierarchy depicts a root node that corresponds to the concept and one or more child nodes that correspond to hierarchical sub-concepts that are constituent parts of the concept, wherein the child nodes depict respective labels that identify sub-concepts that correspond to the child nodes, wherein one or more of the child nodes are user-selectable for labeling tokens within the data item, and wherein selection of a child node within the concept hierarchy identifies the respective label that is utilized for labeling a token within the data item; receiving a user selection of a child node that corresponds to a selected sub-concept in the concept hierarchy; utilizing the segment extractor to select from the plurality of data items a first data item that is predicted to include an example of the concept associated with the concept hierarchy, wherein the example is represented by one or more of the tokens in the first data item; displaying the first data item, wherein displaying the first data item includes presenting a first set of one or more pre-labels that identify a first set of one or more tokens as predicted positive examples of the selected sub-concept; receiving a user selection of a first token in the displayed second data item that labels the first token as a positive or negative example of the selected sub-concept; replacing the first set of one or more pre-labels with a second set of one or more pre-labels that identify a second set of one or more tokens as predicted positive examples of the selected sub-concept; and based at least on the labeling of the first token as an example of the selected sub-concept, training the segment extractor. | 1. One or more hardware computer-readable media having embodied thereon computer-usable instructions that, when executed, facilitate a method of segment extraction by a user for a machine learning system, the method comprising: storing a set of data items, wherein each data item includes a plurality of tokens; providing a segment extractor that is trainable to identify a segment within a data item as an example of a concept, wherein the segment includes a group of tokens; presenting on a user interface a concept hierarchy that represents the concept, wherein the concept hierarchy depicts a root node that corresponds to the concept and one or more child nodes that correspond to hierarchical sub-concepts that are constituent parts of the concept, wherein the child nodes depict respective labels that identify sub-concepts that correspond to the child nodes, wherein one or more of the child nodes are user-selectable for labeling tokens within the data item, and wherein selection of a child node within the concept hierarchy identifies the respective label that is utilized for labeling a token within the data item; receiving a user selection of a child node that corresponds to a selected sub-concept in the concept hierarchy; utilizing the segment extractor to select from the plurality of data items a first data item that is predicted to include an example of the concept associated with the concept hierarchy, wherein the example is represented by one or more of the tokens in the first data item; displaying the first data item, wherein displaying the first data item includes presenting a first set of one or more pre-labels that identify a first set of one or more tokens as predicted positive examples of the selected sub-concept; receiving a user selection of a first token in the displayed second data item that labels the first token as a positive or negative example of the selected sub-concept; replacing the first set of one or more pre-labels with a second set of one or more pre-labels that identify a second set of one or more tokens as predicted positive examples of the selected sub-concept; and based at least on the labeling of the first token as an example of the selected sub-concept, training the segment extractor. 5. The media of claim 1 , the method further comprising dividing at least one of the displayed first data item or the displayed second data item into sections and indicating a section that includes the example of the concept. | 0.776786 |
5,473,326 | 6 | 7 | 6. The method of claim 5, further comprising the steps of: deleting said compared byte from the buffer and shifting the buffer bytes one position toward the oldest position to establish another oldest received byte and to open the newest byte position, and adding a new byte from said byte stream to the newest position upon completion of said comparison; comparing said another oldest byte against the bytes in the first comparison window and the second comparison window; substituting a pointer for the compared byte in the buffer if the compared byte matches a byte in a comparison window; outputting said substituted pointer into an output stream; and repeating said steps until all the bytes in the byte stream have been compared with the bytes in the comparison windows. | 6. The method of claim 5, further comprising the steps of: deleting said compared byte from the buffer and shifting the buffer bytes one position toward the oldest position to establish another oldest received byte and to open the newest byte position, and adding a new byte from said byte stream to the newest position upon completion of said comparison; comparing said another oldest byte against the bytes in the first comparison window and the second comparison window; substituting a pointer for the compared byte in the buffer if the compared byte matches a byte in a comparison window; outputting said substituted pointer into an output stream; and repeating said steps until all the bytes in the byte stream have been compared with the bytes in the comparison windows. 7. The method of claim 6, wherein the first comparison window includes bytes transferred from the byte stream and received by the first comparison window, arranged in a linear array of byte positions from an oldest received byte to a newest received byte; and wherein when a new byte is received by the first comparison window the oldest byte is deleted and the other first comparison window bytes are shifted toward the oldest byte position to open the newest byte for the newest byte position. | 0.676893 |
5,557,722 | 13 | 14 | 13. A computer-implemented method for randomly accessing and formatting a portion of an electronically published document having fixed text content and fixed structure defined by descriptive markup defining a plurality of hierarchical elements, wherein each element except a root element has an ancestor element and a type name, and at least one element has text content, the method using a memory storing a format specification for each type name utilized for elements in the electronically published document, wherein the format specification for a type name defines appearance of the text content of the elements in the electronically published document having the type name, and wherein the memory separately stores the electronically published document, the method comprising the steps, performed by the computer, of: receiving an indication of a starting point within the electronically published document; selecting a starting point element within the electronically published document according to the received indication of the starting point; selecting elements of the electronically published document beginning with the selected starting point element; identifying ancestor elements of the selected elements; and formatting the text content of each selected element according to a combination of format specification for the type names of ancestor elements identified for the selected element and for the type name of the selected element. | 13. A computer-implemented method for randomly accessing and formatting a portion of an electronically published document having fixed text content and fixed structure defined by descriptive markup defining a plurality of hierarchical elements, wherein each element except a root element has an ancestor element and a type name, and at least one element has text content, the method using a memory storing a format specification for each type name utilized for elements in the electronically published document, wherein the format specification for a type name defines appearance of the text content of the elements in the electronically published document having the type name, and wherein the memory separately stores the electronically published document, the method comprising the steps, performed by the computer, of: receiving an indication of a starting point within the electronically published document; selecting a starting point element within the electronically published document according to the received indication of the starting point; selecting elements of the electronically published document beginning with the selected starting point element; identifying ancestor elements of the selected elements; and formatting the text content of each selected element according to a combination of format specification for the type names of ancestor elements identified for the selected element and for the type name of the selected element. 14. A method as set forth in claim 13 wherein the step of formatting includes the steps of retrieving the format specifications for the type name of each ancestor element of the selected element in the electronically published document, and combining the format specifications for the type names of the ancestor elements with the format specification of the type name of the selected element. | 0.679739 |
9,712,578 | 1 | 6 | 1. A computer-implemented method comprising: receiving a plurality of content items posted on pages of a social networking system; determining, by a processor, from the plurality of content items, a subset of content items determined to be high quality content items, the determination of the high quality content items comprising: receiving a user interaction rate associated with each of the plurality of content items posted on the social networking system; responsive to the user interaction rate indicating a positive reaction to the content item, including the content item in the subset as a high quality content item, the user interaction rate indicated as positive reaction when the user interaction rate is higher than or equal to a threshold interaction rate; and responsive to the user interaction rate indicating a negative reaction to the content item, excluding the content item from the subset, the user interaction rate indicated as negative reaction when the user interaction rate is lower than the threshold interaction rate; and for each of the content items of the subset: extracting a first topic from the content item by analyzing terms and phrases of the content item, mapping, by the processor, the extracted first topic to one or more related pages of the social networking system, the one or more related pages include the extracted first topic, and for each of the one or more related pages: identifying a user of the social networking system connected to the related page, and providing the content item in a newsfeed for display to the user. | 1. A computer-implemented method comprising: receiving a plurality of content items posted on pages of a social networking system; determining, by a processor, from the plurality of content items, a subset of content items determined to be high quality content items, the determination of the high quality content items comprising: receiving a user interaction rate associated with each of the plurality of content items posted on the social networking system; responsive to the user interaction rate indicating a positive reaction to the content item, including the content item in the subset as a high quality content item, the user interaction rate indicated as positive reaction when the user interaction rate is higher than or equal to a threshold interaction rate; and responsive to the user interaction rate indicating a negative reaction to the content item, excluding the content item from the subset, the user interaction rate indicated as negative reaction when the user interaction rate is lower than the threshold interaction rate; and for each of the content items of the subset: extracting a first topic from the content item by analyzing terms and phrases of the content item, mapping, by the processor, the extracted first topic to one or more related pages of the social networking system, the one or more related pages include the extracted first topic, and for each of the one or more related pages: identifying a user of the social networking system connected to the related page, and providing the content item in a newsfeed for display to the user. 6. The method of claim 1 , wherein the determination of the high quality content items further comprises determining whether each of the plurality of content items is trending, wherein a content item is determined to be trending if the content item has an interaction rate higher than a threshold interaction rate. | 0.849617 |
8,849,843 | 10 | 12 | 10. The method of claim 7 , further comprising: facilitating user entry of content into a unstructured document being authored by a user through a graphical user interface presented to the user; and suggesting semantic labels for content entered to the unstructured document by the user based on the trends determined by the analysis module. | 10. The method of claim 7 , further comprising: facilitating user entry of content into a unstructured document being authored by a user through a graphical user interface presented to the user; and suggesting semantic labels for content entered to the unstructured document by the user based on the trends determined by the analysis module. 12. The method of claim 10 , wherein the semantic labels are tags. | 0.990451 |
8,248,632 | 1 | 3 | 1. A computer-implemented method for inserting dividers in a print job, said method comprising: compiling a plurality of individual files wherein said plurality of files comprises more than one file format by executing a program instruction in a data-processing system; and inserting at least one divider in-between each individual file among said plurality of files, wherein said file format of said individual files is preserved by executing a program instruction in a data-processing system, in order to thereafter generate a template comprising a print layout associated with said at least one divider and render a complete document comprising said individual files among said plurality of individual files in a preferred order with said at least one divider automatically inserted therein and including text strings thereof. | 1. A computer-implemented method for inserting dividers in a print job, said method comprising: compiling a plurality of individual files wherein said plurality of files comprises more than one file format by executing a program instruction in a data-processing system; and inserting at least one divider in-between each individual file among said plurality of files, wherein said file format of said individual files is preserved by executing a program instruction in a data-processing system, in order to thereafter generate a template comprising a print layout associated with said at least one divider and render a complete document comprising said individual files among said plurality of individual files in a preferred order with said at least one divider automatically inserted therein and including text strings thereof. 3. The method of claim 1 further comprising configuring said plurality of individual files to comprise files having different printer file formats, by executing a program instruction in a data-processing system. | 0.754651 |
8,290,778 | 3 | 5 | 3. The apparatus of claim 1 , wherein the at least one program is further configured to cause display of advertising that is contextually related to the organization or entity. | 3. The apparatus of claim 1 , wherein the at least one program is further configured to cause display of advertising that is contextually related to the organization or entity. 5. The apparatus of claim 3 , wherein the advertising is displayed substantially contemporaneous with a display of the graphical or visual representation of that location. | 0.945714 |
10,048,945 | 1 | 3 | 1. A method performed by a device having an operating system and a system library for enhancing operable functionality of a software program, comprising: receiving, by the device, a plurality of input source code files from the software program submitted by a developer; identifying, by the device, one or more candidate code snippets from the plurality of input source code files by comparing source code feature vectors for the plurality of input source code files to library function feature vectors for library functions stored in the system library to identify at least a first candidate code snippet which meets at least a first similarity threshold measure for a first library function stored in the system library, and removing one or more code snippets that do not meet a similarity threshold measure for library functions stored in the system library; identifying, by the device, at least a first validated code snippet from the one or more candidate code snippets that matches a first library function stored in the system memory on the basis of at least first and second matching metrics comprising implementing an input/output matching algorithm for selecting a candidate code snippet which generates the same output as the first library function when both are injected with a shared input; and presenting, to the developer, a library function recommendation comprising the first validated code snippet, the first library function, and instructions for replacing the first validated code snippet with the first library function. | 1. A method performed by a device having an operating system and a system library for enhancing operable functionality of a software program, comprising: receiving, by the device, a plurality of input source code files from the software program submitted by a developer; identifying, by the device, one or more candidate code snippets from the plurality of input source code files by comparing source code feature vectors for the plurality of input source code files to library function feature vectors for library functions stored in the system library to identify at least a first candidate code snippet which meets at least a first similarity threshold measure for a first library function stored in the system library, and removing one or more code snippets that do not meet a similarity threshold measure for library functions stored in the system library; identifying, by the device, at least a first validated code snippet from the one or more candidate code snippets that matches a first library function stored in the system memory on the basis of at least first and second matching metrics comprising implementing an input/output matching algorithm for selecting a candidate code snippet which generates the same output as the first library function when both are injected with a shared input; and presenting, to the developer, a library function recommendation comprising the first validated code snippet, the first library function, and instructions for replacing the first validated code snippet with the first library function. 3. The method of claim 1 , where identifying one or more candidate code snippets comprises pruning the plurality of input source code files by performing natural language processing analysis of the plurality of input source code files to keep each candidate code snippet which meets at least a first similarity threshold measure for a first library function stored in the system library. | 0.678037 |
10,073,861 | 15 | 18 | 15. A non-transitory computer readable medium storing instructions, which, when executed by a processor, perform an operation comprising: assigning each of a plurality of nodes of a graph to a distinct image, of a plurality of images including a first image and a second image, wherein the graph represents a story, wherein each node corresponds to a respective element of the story, wherein each node comprises: (i) an attribute and (ii) a predefined text of the respective element of the story, wherein a first edge of a plurality of edges of the graph specifies a constraint between the attributes of a first node and a second node of the plurality of nodes, wherein the plurality of nodes are assigned based on an attribute of each of the plurality of images and the attribute of each node, wherein the first and second nodes are assigned to the first and second images, respectively, based on the attributes of the first and second images satisfying the constraint specified by the first edge; and generating a visual depiction of the story, wherein the visual depiction comprises an ordered representation of each of the distinct images and the predefined text of each respective element of the story. | 15. A non-transitory computer readable medium storing instructions, which, when executed by a processor, perform an operation comprising: assigning each of a plurality of nodes of a graph to a distinct image, of a plurality of images including a first image and a second image, wherein the graph represents a story, wherein each node corresponds to a respective element of the story, wherein each node comprises: (i) an attribute and (ii) a predefined text of the respective element of the story, wherein a first edge of a plurality of edges of the graph specifies a constraint between the attributes of a first node and a second node of the plurality of nodes, wherein the plurality of nodes are assigned based on an attribute of each of the plurality of images and the attribute of each node, wherein the first and second nodes are assigned to the first and second images, respectively, based on the attributes of the first and second images satisfying the constraint specified by the first edge; and generating a visual depiction of the story, wherein the visual depiction comprises an ordered representation of each of the distinct images and the predefined text of each respective element of the story. 18. The computer-readable medium of claim 15 , wherein a third node of the plurality of nodes further specifies one or more permissive constraints for the attribute of the third node, wherein assigning each node to an image further comprises: identifying a first set of images having an attribute satisfying at least one of the permissive constraints of the attribute of the third node; upon determining that the first set of images comprises at least two images: computing a fitness score for each image in the first set of images, wherein the fitness score is based at least in part on: (i) a quality of each respective image in the first set of images, and (ii) a number of permissive constraints satisfied by the respective image in the first set of images; creating a priority queue comprising each node that has not been assigned to an image, including the third node, wherein the priority queue is ordered based at least in part on a number of images in a set of images matching a set of mandatory constraints for the respective node; extracting the third node from the priority queue; and assigning the third node to a first image from the first set of images for the third node, wherein the fitness score of the first image is the highest fitness score relative to the fitness scores of the remaining images in the set of images for the third node. | 0.500368 |
9,298,776 | 8 | 20 | 8. A method comprising: compiling historical data, the historical data comprising user behavior data based on actions performed by users; accessing listing data, the listing data including aspect data for each listing; joining the historical data with the listing data and a determined category of each listing to create a single table comprising joined data, the joined data including the historical data, the listing data, and the determined category for each listing; determining, using a processor of a machine, demand scores based on the joined data by aggregating over the joined data to define the demand scores; sorting the determined demand scores to determine at least one most relevant aspect name for a category; and in response to an indication that a user is creating a new listing within the category, providing a message to the user indicating the at least one most relevant aspect name for the category and suggesting the user provide an aspect value that corresponds to the at least one most relevant aspect name to be included in the new listing. | 8. A method comprising: compiling historical data, the historical data comprising user behavior data based on actions performed by users; accessing listing data, the listing data including aspect data for each listing; joining the historical data with the listing data and a determined category of each listing to create a single table comprising joined data, the joined data including the historical data, the listing data, and the determined category for each listing; determining, using a processor of a machine, demand scores based on the joined data by aggregating over the joined data to define the demand scores; sorting the determined demand scores to determine at least one most relevant aspect name for a category; and in response to an indication that a user is creating a new listing within the category, providing a message to the user indicating the at least one most relevant aspect name for the category and suggesting the user provide an aspect value that corresponds to the at least one most relevant aspect name to be included in the new listing. 20. The method of claim 8 , wherein the demand score is a function of action counts based on at least purchase related counts, the purchase related counts comprising one or more of a Buy-It-Now action, a bid action, or a best offer action. | 0.770633 |
8,700,612 | 15 | 25 | 15. A non-transitory computer-readable storage medium storing instructions that, when executed, cause a processing device to perform a method comprising: receiving a search input; selecting a first cell within a matrix of cells in response to the search input, wherein each cell within the matrix of cells includes searchable data, the first cell is selected based upon the first cell including searchable data related to the search input, and the first cell further includes a first link assigned a causal context relationship and providing a navigation link from the first cell to a causal context cell corresponding to the first cell, a second link assigned an inclusion contextual relationship and providing a navigation link from the first cell to an inclusion context cell corresponding to the first cell, a third link assigned a temporal contextual relationship and providing a navigation link from the first cell to a temporal context cell corresponding to the first cell, and fourth link assigned a spatial contextual relationship and providing a navigation link from the first cell to a spatial context cell corresponding to the first cell; displaying, in response to the search input, a portion of the searchable data of the first cell and first, second, third, and fourth selectable objects, the first selectable object corresponding to the first link, the second selectable object corresponding to the second link, the third selectable object corresponding to the third link, and the fourth selectable object corresponding to the fourth link; receiving selection of the first, second, third, or fourth of the plurality of selectable objects; and utilizing the corresponding link to display a context cell corresponding to the first cell, wherein selection of a first of the plurality of selectable objects results in the computer utilizing the first link to select and display the causal context cell corresponding to the first cell, the display of the causal context cell including displaying a subject of the first cell as causing or influencing one or more subjects of other cells or as being caused or influenced by one or more subjects of other cells, wherein selection of a second of the plurality of selectable objects results in the computer utilizing the second link to select and display the inclusion context cell corresponding to the first cell, the display of the inclusion context cell including displaying the subject of the first cell within a category along with subjects of other cells included within the category, wherein selection of a third of the plurality of selectable objects results in the computer utilizing the third link to select and display the temporal context cell corresponding to the first cell, the display of the temporal context cell including displaying the subject of the first cell within a timeline along with subjects of other cells of relevance within the timeline, wherein selection of a fourth of the plurality of selectable objects results in the computer utilizing the fourth link to select and display the spatial context cell corresponding to the first cell, the display of the spatial context cell including displaying a location corresponding to the subject of the first cell within a map, and when the received selection is of the first of the plurality of selectable objects, the method further comprising receiving a command to alter the zoom of the display of the corresponding portion of the data of the first cell and the first set of other data and, in response to the zoom command, adding or removing subjects that served as a cause of or influence upon the subject of the first cell, or adding or removing subjects that were caused or influenced by the subject of the first cell. | 15. A non-transitory computer-readable storage medium storing instructions that, when executed, cause a processing device to perform a method comprising: receiving a search input; selecting a first cell within a matrix of cells in response to the search input, wherein each cell within the matrix of cells includes searchable data, the first cell is selected based upon the first cell including searchable data related to the search input, and the first cell further includes a first link assigned a causal context relationship and providing a navigation link from the first cell to a causal context cell corresponding to the first cell, a second link assigned an inclusion contextual relationship and providing a navigation link from the first cell to an inclusion context cell corresponding to the first cell, a third link assigned a temporal contextual relationship and providing a navigation link from the first cell to a temporal context cell corresponding to the first cell, and fourth link assigned a spatial contextual relationship and providing a navigation link from the first cell to a spatial context cell corresponding to the first cell; displaying, in response to the search input, a portion of the searchable data of the first cell and first, second, third, and fourth selectable objects, the first selectable object corresponding to the first link, the second selectable object corresponding to the second link, the third selectable object corresponding to the third link, and the fourth selectable object corresponding to the fourth link; receiving selection of the first, second, third, or fourth of the plurality of selectable objects; and utilizing the corresponding link to display a context cell corresponding to the first cell, wherein selection of a first of the plurality of selectable objects results in the computer utilizing the first link to select and display the causal context cell corresponding to the first cell, the display of the causal context cell including displaying a subject of the first cell as causing or influencing one or more subjects of other cells or as being caused or influenced by one or more subjects of other cells, wherein selection of a second of the plurality of selectable objects results in the computer utilizing the second link to select and display the inclusion context cell corresponding to the first cell, the display of the inclusion context cell including displaying the subject of the first cell within a category along with subjects of other cells included within the category, wherein selection of a third of the plurality of selectable objects results in the computer utilizing the third link to select and display the temporal context cell corresponding to the first cell, the display of the temporal context cell including displaying the subject of the first cell within a timeline along with subjects of other cells of relevance within the timeline, wherein selection of a fourth of the plurality of selectable objects results in the computer utilizing the fourth link to select and display the spatial context cell corresponding to the first cell, the display of the spatial context cell including displaying a location corresponding to the subject of the first cell within a map, and when the received selection is of the first of the plurality of selectable objects, the method further comprising receiving a command to alter the zoom of the display of the corresponding portion of the data of the first cell and the first set of other data and, in response to the zoom command, adding or removing subjects that served as a cause of or influence upon the subject of the first cell, or adding or removing subjects that were caused or influenced by the subject of the first cell. 25. The non-transitory computer-readable medium of claim 15 , wherein the instructions, when executed, cause the processing device to perform a method further comprising: generating a plurality of tokens representing a plurality of cells within the matrix, contextual relationships, or zoom levels viewed by a user. | 0.692383 |
8,130,951 | 1 | 7 | 1. An image forming device comprising: one or more processors; and a memory communicatively coupled to the one or more processors, the memory storing instructions which, when processed by the one or more processors, causes: authenticating user data received by the image forming device, wherein the user data corresponds to a particular user; determining electronic document data to be processed, retrieving, from a plurality of user preference data, particular user preference data that is specific to the user data and which specifies one or more types of confidential information and one or more actions to be performed on each type of confidential information, processing the electronic document data to identify, in the electronic document data, confidential information of one or more types that match the one or more types of confidential information specified by the particular user preference data that is specific to the user data and which specifies the one or more types of confidential information and the one or more actions to be performed on each type of confidential information, and automatically processing the electronic document data based upon the particular user preference data that is specific to the user data and which specifies the one or more types of confidential information and the one or more actions to be performed on each type of confidential information and generating processed electronic document data by removing, from the electronic document data, the confidential information having one or more types that match the one or more types of confidential information specified by the particular user preference data and additional information adjacent to the confidential information. | 1. An image forming device comprising: one or more processors; and a memory communicatively coupled to the one or more processors, the memory storing instructions which, when processed by the one or more processors, causes: authenticating user data received by the image forming device, wherein the user data corresponds to a particular user; determining electronic document data to be processed, retrieving, from a plurality of user preference data, particular user preference data that is specific to the user data and which specifies one or more types of confidential information and one or more actions to be performed on each type of confidential information, processing the electronic document data to identify, in the electronic document data, confidential information of one or more types that match the one or more types of confidential information specified by the particular user preference data that is specific to the user data and which specifies the one or more types of confidential information and the one or more actions to be performed on each type of confidential information, and automatically processing the electronic document data based upon the particular user preference data that is specific to the user data and which specifies the one or more types of confidential information and the one or more actions to be performed on each type of confidential information and generating processed electronic document data by removing, from the electronic document data, the confidential information having one or more types that match the one or more types of confidential information specified by the particular user preference data and additional information adjacent to the confidential information. 7. The image forming device recited in claim 1 , wherein: the image forming device is a printer, and the printer further comprises a print processor configured to process print data received over a network and generate a printed version of an electronic document contained in the print data. | 0.761475 |
8,543,646 | 15 | 18 | 15. A computer program product to implement real-time communication for resource content, comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to receive, from a subscriber device, identification information of the subscriber device and an event topic, wherein the identification information comprises path information defining a topic path for receiving a notification event related to the selected event topic and the event topic selected by the subscriber device is a complex event topic set constituted by at least two separate event topics; computer readable program code configured to add the identification information of the subscriber device and the selected event topic to an event topic subscription search table; computer readable program code configured to determine, by the resource content publishing device, if new resource content is available, whether an event topic of the new resource content belongs to the complex event topic set; computer readable program code configured to create, by the resource content publishing device, if it is determined that the event topic of the new resource content belongs to the complex event topic set, a complex event by applying a predefined rule describing a relation between the separate events related to the complex event topic set onto the new resource content, so as to send the complex event to the subscriber device after obtaining the identification information of the subscriber device; computer readable program code configured to obtain, by the resource content publishing device, the identification information of a subscriber device subscribing to an event topic related to new resource content, where the identification information is obtained from the event topic subscription search table, if new resource content is available; and computer readable program code configured to send, by the resource content publishing device, a notification event comprising the new resource content to the subscriber device according to the identification information of the subscriber device. | 15. A computer program product to implement real-time communication for resource content, comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to receive, from a subscriber device, identification information of the subscriber device and an event topic, wherein the identification information comprises path information defining a topic path for receiving a notification event related to the selected event topic and the event topic selected by the subscriber device is a complex event topic set constituted by at least two separate event topics; computer readable program code configured to add the identification information of the subscriber device and the selected event topic to an event topic subscription search table; computer readable program code configured to determine, by the resource content publishing device, if new resource content is available, whether an event topic of the new resource content belongs to the complex event topic set; computer readable program code configured to create, by the resource content publishing device, if it is determined that the event topic of the new resource content belongs to the complex event topic set, a complex event by applying a predefined rule describing a relation between the separate events related to the complex event topic set onto the new resource content, so as to send the complex event to the subscriber device after obtaining the identification information of the subscriber device; computer readable program code configured to obtain, by the resource content publishing device, the identification information of a subscriber device subscribing to an event topic related to new resource content, where the identification information is obtained from the event topic subscription search table, if new resource content is available; and computer readable program code configured to send, by the resource content publishing device, a notification event comprising the new resource content to the subscriber device according to the identification information of the subscriber device. 18. The computer program product according to claim 15 , further comprising: computer readable program code configured to receive, by the resource content publishing device, a reversed event created by the subscriber device, the reversed event comprising reversed event content edited by the subscriber device that has been converted into feed information in RSS or Atom format. | 0.764633 |
8,103,110 | 1 | 2 | 1. A method for classifying text, comprising: receiving data containing text; parsing a plurality of tokens out of the text; generating a plurality of metatokens comprising information regarding the position of the plurality of tokens within the text from which the plurality of tokens were parsed; calculating a first probability that the data falls into a category based on the plurality of tokens; calculating a second probability that the data falls into the category based on the plurality of metatokens; determining a third probability that the data falls into the category based on the first probability and the second probability; comparing the third probability to a threshold value; and classifying the data into the certain category if the third probability is greater than the threshold value. | 1. A method for classifying text, comprising: receiving data containing text; parsing a plurality of tokens out of the text; generating a plurality of metatokens comprising information regarding the position of the plurality of tokens within the text from which the plurality of tokens were parsed; calculating a first probability that the data falls into a category based on the plurality of tokens; calculating a second probability that the data falls into the category based on the plurality of metatokens; determining a third probability that the data falls into the category based on the first probability and the second probability; comparing the third probability to a threshold value; and classifying the data into the certain category if the third probability is greater than the threshold value. 2. The method of claim 1 , wherein calculating the third probability further comprises using Bayes rules. | 0.79572 |
9,106,621 | 3 | 5 | 3. The method of claim 2 , wherein the attention types additionally includes “bcc.” | 3. The method of claim 2 , wherein the attention types additionally includes “bcc.” 5. The method of claim 3 , wherein the attention-rights rule defines that a recipient with the attention type “to” is to be granted view and edit rights only, and a recipient with the attention type “cc” or “bcc” is to be granted view right only. | 0.959566 |
8,265,925 | 17 | 20 | 17. Apparatus for textual exploration and discovery, wherein Subject-Verb-Object Structures (SVOS) are annotated in a grammatically encoded electronic text, and wherein said SVOS are used to identify semantic facets termed “Agent”, “Process” and “Object”, i.e. APOS, in a text span, wherein the system comprises: a processor; memory; and a) an acquisition module for collection of documents, and capable of formatting the documents to at least one common format, b) a segmentation module for the generation of Annotated Text Files (ATF), thus forming the Annotated Text Corpus, and c) a Disambiguation Module for text disambiguation, and d) a display unit for presenting said semantic facets “Agent”, “Process” and “Object” as index entries in respective window panes as contacts to said electronic text. | 17. Apparatus for textual exploration and discovery, wherein Subject-Verb-Object Structures (SVOS) are annotated in a grammatically encoded electronic text, and wherein said SVOS are used to identify semantic facets termed “Agent”, “Process” and “Object”, i.e. APOS, in a text span, wherein the system comprises: a processor; memory; and a) an acquisition module for collection of documents, and capable of formatting the documents to at least one common format, b) a segmentation module for the generation of Annotated Text Files (ATF), thus forming the Annotated Text Corpus, and c) a Disambiguation Module for text disambiguation, and d) a display unit for presenting said semantic facets “Agent”, “Process” and “Object” as index entries in respective window panes as contacts to said electronic text. 20. Apparatus according to claim 17 , wherein the module provides a documental link structure, for instance, a group of peripheral documents are linked to a central document, the central documents can be linked to each other, or peripheral documents associated with a central document may also be linked to another central document. | 0.501502 |
9,424,837 | 1 | 8 | 1. A method for configuring a speech recognition system, the method comprising: obtaining a speech sample from a user utilised to authenticate the user as part of an authentication process; processing the speech sample to train one or more generic acoustic model(s) for units of speech associated with the speech sample; storing the trained acoustic model(s) in a personalised acoustic model set for the user; selectively re-training the acoustic model(s) in the personalised model set based on additional speech samples provided by the user containing corresponding units of speech; responsive to determining that the user has accessed a speech recognition function, directing a speech recognition process to access the personalised model set for recognising subsequent user utterances; and further comprising determining a measure of quality for each of the stored acoustic models and wherein the acoustic modules are re-trained based on additional speech samples until the corresponding quality measure meets a predefined threshold. | 1. A method for configuring a speech recognition system, the method comprising: obtaining a speech sample from a user utilised to authenticate the user as part of an authentication process; processing the speech sample to train one or more generic acoustic model(s) for units of speech associated with the speech sample; storing the trained acoustic model(s) in a personalised acoustic model set for the user; selectively re-training the acoustic model(s) in the personalised model set based on additional speech samples provided by the user containing corresponding units of speech; responsive to determining that the user has accessed a speech recognition function, directing a speech recognition process to access the personalised model set for recognising subsequent user utterances; and further comprising determining a measure of quality for each of the stored acoustic models and wherein the acoustic modules are re-trained based on additional speech samples until the corresponding quality measure meets a predefined threshold. 8. A non-transitory computer readable medium implementing a computer program comprising one or more instructions for controlling a computer system to implement a method in accordance with claim 1 . | 0.567982 |
10,140,384 | 1 | 8 | 1. A method to dynamically modify at least one element of a user interface (UI) of a first electronic device, the method comprising: collating usage information of at least one data source associated with a user in the first electronic device, wherein each data source is at least one item used in the first electronic device or any application running on the first electronic device; categorizing the collated usage information into at least one knowledge cluster, wherein the categorizing includes extracting semantic content from the usage information and mapping the extracted semantic content to categorize the collated usage information into the at least one knowledge cluster using an incremental model; storing a knowledge graph including the at least one knowledge cluster in a form of at least one knowledge node in the knowledge graph and at least one link among the at least one knowledge node; and dynamically modifying the at least one element of the UI based on the knowledge graph, wherein the dynamically modifying includes identifying the at least one knowledge cluster from the knowledge graph and displaying the at least one identified knowledge cluster as the at least one element of the UI. | 1. A method to dynamically modify at least one element of a user interface (UI) of a first electronic device, the method comprising: collating usage information of at least one data source associated with a user in the first electronic device, wherein each data source is at least one item used in the first electronic device or any application running on the first electronic device; categorizing the collated usage information into at least one knowledge cluster, wherein the categorizing includes extracting semantic content from the usage information and mapping the extracted semantic content to categorize the collated usage information into the at least one knowledge cluster using an incremental model; storing a knowledge graph including the at least one knowledge cluster in a form of at least one knowledge node in the knowledge graph and at least one link among the at least one knowledge node; and dynamically modifying the at least one element of the UI based on the knowledge graph, wherein the dynamically modifying includes identifying the at least one knowledge cluster from the knowledge graph and displaying the at least one identified knowledge cluster as the at least one element of the UI. 8. The method of claim 1 , wherein the dynamic modifying of the at least one element of the UI based on the knowledge graph comprises: displaying one or more clusters on the UI according to one or more rules; and displaying a lower cluster or an upper cluster of the one or more clusters on the UI in response to a user's touch input. | 0.734076 |
9,916,345 | 11 | 15 | 11. A server comprising: one or more computing devices; a non-transitory computer readable medium; and instructions stored in the non-transitory computer readable medium, the instructions executable by the one or more computing devices to cause the server to perform functions comprising: receiving a search query comprising at least one descriptor for an object, wherein the at least one descriptor comprises an image of the object and wherein the object is associated with a given category of objects; comparing the at least one descriptor to contents of a three-dimensional (3D) object-data-model database, wherein the contents of the 3D object-data-model database include contents associated with the given category of objects, wherein the 3D object-data-model database further comprises a plurality of 3D object data models that describe the object, and wherein comparing the at least one descriptor to contents of the 3D object-data-model database comprises: based on a respective 3D object data model of the plurality of 3D object data models, generating a set of rendered images that correspond to the respective 3D object data model; comparing the image to the set of rendered images; and based on the comparison of the image to the set of rendered images, determining corresponding 3D object data models from the plurality of 3D object data models, and wherein the 3D object data models that describe the object comprise the corresponding 3D object data models; based on the comparison of the at least one descriptor to contents of the 3D object-data-model database, generating a search query result that comprises the corresponding 3D object data models retrieved from the 3D object-data model database that describe the object and associated images that describe the object; arranging in the search query result the associated images that describe the object, the corresponding 3D object data models, and the image of the object used to perform the search query, wherein the corresponding 3D object data models are arranged in the search query result in a manner such that the corresponding 3D object data models are moveable inline in the search query result; and providing the search query result. | 11. A server comprising: one or more computing devices; a non-transitory computer readable medium; and instructions stored in the non-transitory computer readable medium, the instructions executable by the one or more computing devices to cause the server to perform functions comprising: receiving a search query comprising at least one descriptor for an object, wherein the at least one descriptor comprises an image of the object and wherein the object is associated with a given category of objects; comparing the at least one descriptor to contents of a three-dimensional (3D) object-data-model database, wherein the contents of the 3D object-data-model database include contents associated with the given category of objects, wherein the 3D object-data-model database further comprises a plurality of 3D object data models that describe the object, and wherein comparing the at least one descriptor to contents of the 3D object-data-model database comprises: based on a respective 3D object data model of the plurality of 3D object data models, generating a set of rendered images that correspond to the respective 3D object data model; comparing the image to the set of rendered images; and based on the comparison of the image to the set of rendered images, determining corresponding 3D object data models from the plurality of 3D object data models, and wherein the 3D object data models that describe the object comprise the corresponding 3D object data models; based on the comparison of the at least one descriptor to contents of the 3D object-data-model database, generating a search query result that comprises the corresponding 3D object data models retrieved from the 3D object-data model database that describe the object and associated images that describe the object; arranging in the search query result the associated images that describe the object, the corresponding 3D object data models, and the image of the object used to perform the search query, wherein the corresponding 3D object data models are arranged in the search query result in a manner such that the corresponding 3D object data models are moveable inline in the search query result; and providing the search query result. 15. The server of claim 11 , wherein the at least one descriptor comprises a partial 3D object data model that describes a portion of the object, wherein the 3D object-data-model database comprises a plurality of 3D object data models that describe the object, and wherein the instructions are further executable by the processor to cause the server to perform functions comprising: comparing shape and appearance information of the partial 3D object data model to the plurality of 3D object data models; and based on the comparison of shape and appearance information of the partial 3D object data model to the plurality of 3D object data models, determining the corresponding 3D object data models from the plurality of 3D object data models, and wherein the 3D object data models that describe the object comprise the corresponding 3D object data models. | 0.500583 |
8,914,452 | 1 | 9 | 1. A computer implemented method for automatically generating a meeting digest of a set of meetings, the computer implemented method comprising: detecting, by a computer, a set of topics of interest to parties to the set of meetings utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings; receiving, by the computer, recorded meeting data corresponding to the set of meetings from a conferencing server that recorded contents of the set of meetings; extracting, by the computer, topic-related content associated with the set of topics of interest to the parties from the recorded meeting data corresponding to the set of meetings received from the conferencing server; and generating, by the computer, the meeting digest of the set of meetings using the topic-related content associated with the set of topics of interest to the parties extracted from the recorded meeting data corresponding to the set of meetings. | 1. A computer implemented method for automatically generating a meeting digest of a set of meetings, the computer implemented method comprising: detecting, by a computer, a set of topics of interest to parties to the set of meetings utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings; receiving, by the computer, recorded meeting data corresponding to the set of meetings from a conferencing server that recorded contents of the set of meetings; extracting, by the computer, topic-related content associated with the set of topics of interest to the parties from the recorded meeting data corresponding to the set of meetings received from the conferencing server; and generating, by the computer, the meeting digest of the set of meetings using the topic-related content associated with the set of topics of interest to the parties extracted from the recorded meeting data corresponding to the set of meetings. 9. The computer implemented method of claim 1 , wherein the meeting digest of the set of meetings includes at least one of keywords, selected video frames, snippets from email communications, snippets from instant messaging communications, snippets from chat room discussions, extracted audio content, speech to text extracted phrases, and extracted “to do” items associated with the recorded meeting data corresponding to the set of meetings. | 0.873861 |
7,627,882 | 39 | 41 | 39. A method of displaying an electronic program guide on a screen, the method comprising: receiving an input stream of television content and electronic program guide data; separating the electronic program guide data from the input stream; storing the electronic program guide data separated from the input stream; generating a display from the electronic program guide data, wherein the display includes a plurality of program titles, and a plurality of organizational categories, each program title belonging to at least one of the organizational categories; arranging the program titles 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; and utilizing organizational categories at any organizational level. | 39. A method of displaying an electronic program guide on a screen, the method comprising: receiving an input stream of television content and electronic program guide data; separating the electronic program guide data from the input stream; storing the electronic program guide data separated from the input stream; generating a display from the electronic program guide data, wherein the display includes a plurality of program titles, and a plurality of organizational categories, each program title belonging to at least one of the organizational categories; arranging the program titles 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; and utilizing organizational categories at any organizational level. 41. The method of claim 39 , wherein the program titles utilize different colors to represent the organizational categories. | 0.928074 |
10,013,729 | 8 | 12 | 8. A computer program product comprising a non-transitory computer-readable storage medium storing computer-executable code comprising instructions for: storing a plurality of events and user interactions performed by users of a social networking system with the plurality of events; associating a set of events of the plurality of events with a category; selecting a set of users associated with the set of events, comprising, for each event from the set of events: identifying users performing user interactions with the event, for each identified user, determining a measure of user interactions of the user with the event, wherein the measure of user interactions of the user with the event is based on a frequency of interaction of the user with the event, and including the user in the set of users, responsive to the measure of user interactions of the user with the event exceeding a threshold; selecting a set of candidate events associated with the set of users, based on user interactions of users from the set of users with the candidate events determining whether each candidate event is associated with the category based on keyword occurrences in content associated with each candidate event; and providing information describing a particular event to a user for performing an action, the information provided based on the category. | 8. A computer program product comprising a non-transitory computer-readable storage medium storing computer-executable code comprising instructions for: storing a plurality of events and user interactions performed by users of a social networking system with the plurality of events; associating a set of events of the plurality of events with a category; selecting a set of users associated with the set of events, comprising, for each event from the set of events: identifying users performing user interactions with the event, for each identified user, determining a measure of user interactions of the user with the event, wherein the measure of user interactions of the user with the event is based on a frequency of interaction of the user with the event, and including the user in the set of users, responsive to the measure of user interactions of the user with the event exceeding a threshold; selecting a set of candidate events associated with the set of users, based on user interactions of users from the set of users with the candidate events determining whether each candidate event is associated with the category based on keyword occurrences in content associated with each candidate event; and providing information describing a particular event to a user for performing an action, the information provided based on the category. 12. The computer program product of claim 8 , wherein the measure of user interactions of the user with the event is based on one of a number of interactions of the user with the event and a type of interactions of the user with the event. | 0.737939 |
9,099,090 | 11 | 12 | 11. The system of claim 7 , wherein the computing device is further configured to: generate, with the automatic speech recognition engine, additional first transcribed text corresponding to the first portion of the audio data; determine a confidence level for transcription accuracy of the additional first transcribed text; and select a portion of the additional first transcribed text with a second confidence level greater than the first confidence level. | 11. The system of claim 7 , wherein the computing device is further configured to: generate, with the automatic speech recognition engine, additional first transcribed text corresponding to the first portion of the audio data; determine a confidence level for transcription accuracy of the additional first transcribed text; and select a portion of the additional first transcribed text with a second confidence level greater than the first confidence level. 12. The system of claim 11 , wherein the computing device is further configured to transmit, to the first device, each of the additional first transcribed text. | 0.940785 |
7,552,098 | 2 | 3 | 2. The method of claim 1 , wherein prior to b), the method further comprises determining if at least two training data in the training data set are identical, and merging identical data. | 2. The method of claim 1 , wherein prior to b), the method further comprises determining if at least two training data in the training data set are identical, and merging identical data. 3. The method of claim 2 , wherein merging identical data includes: defining an order relationship for all data of the identical data; sorting all of the data by the defined ordered relationship; merging consecutive data that are equivalent; and re-weighting the merged consecutive data. | 0.862942 |
6,100,824 | 12 | 13 | 12. The method of claim 1, wherein encoding at least a portion of the remaining symbols in the message comprises: determining an efficiency parameter for the encoding of a portion of the remaining symbols; and encoding that portion only if the efficiency parameter exceeds a predetermined threshold. | 12. The method of claim 1, wherein encoding at least a portion of the remaining symbols in the message comprises: determining an efficiency parameter for the encoding of a portion of the remaining symbols; and encoding that portion only if the efficiency parameter exceeds a predetermined threshold. 13. The method of claim 12, wherein non-encoded symbols are represented in ASCII format when the efficiency parameter does not exceed the pre-determined threshold. | 0.938676 |
7,716,037 | 17 | 18 | 17. The computer readable storage medium of claim 15 , wherein said input is at least one of: a graphical user interface input, a gesture input, a text input in a source language, an image input, a spoken input in a source language, a pre-programmed phrase in a source language, or data retrieved from a database. | 17. The computer readable storage medium of claim 15 , wherein said input is at least one of: a graphical user interface input, a gesture input, a text input in a source language, an image input, a spoken input in a source language, a pre-programmed phrase in a source language, or data retrieved from a database. 18. The computer readable storage medium of claim 17 , wherein said data retrieved from a database relates to said second individual. | 0.937966 |
8,774,522 | 6 | 7 | 6. The method of claim 4 , wherein said plurality of scores for said next higher resolution version of said image comprise appearance scores, geometric scores and resolution context scores. | 6. The method of claim 4 , wherein said plurality of scores for said next higher resolution version of said image comprise appearance scores, geometric scores and resolution context scores. 7. The method of claim 6 , wherein said weighted average score for the next higher resolution version of the image is computed using the following formula divided by I: ∑ i W 1 ( A i ) + W 2 ( G i ) + W 3 ( R i ) wherein I represents the number of regions in the next higher resolution version of the image, i is a region index, Σ i denotes a summation from i=1 to i=I, A i represents appearance scores in region i, G i represents geometric scores in region i, R i represents resolution context scores in region i, and W 1 , W 2 and W 3 represent weights respectively assigned to the appearance scores, the geometric scores, and the resolution context scores. | 0.800418 |
8,032,517 | 1 | 12 | 1. A computer-aided method for the automatic evaluation of the similarity of two character strings that are stored in a computer or to which the computer has access by means of an interface, the method comprising: locating of associations in the character strings according to a rule stored in the computer; evaluating located associations according to a first rule stored in the computer, whereby cohesive associations—hereinafter also designated as association strings—are evaluated higher for the similarity of the character strings than non-cohesive associations; and deriving of a value, in particular a numerical value, as measure for the similarity of the two character strings from the evaluation of the sought associations according to a second rule stored in the computer, wherein the value for the similarity of the two character strings is constituted by the values of their not overlapping fragments, wherein a fragment is every association and any association string in the two character strings to be compared. | 1. A computer-aided method for the automatic evaluation of the similarity of two character strings that are stored in a computer or to which the computer has access by means of an interface, the method comprising: locating of associations in the character strings according to a rule stored in the computer; evaluating located associations according to a first rule stored in the computer, whereby cohesive associations—hereinafter also designated as association strings—are evaluated higher for the similarity of the character strings than non-cohesive associations; and deriving of a value, in particular a numerical value, as measure for the similarity of the two character strings from the evaluation of the sought associations according to a second rule stored in the computer, wherein the value for the similarity of the two character strings is constituted by the values of their not overlapping fragments, wherein a fragment is every association and any association string in the two character strings to be compared. 12. The method according to claim 1 , wherein the sum of the values of the fragments is added for the evaluation of the similarity of the character strings. | 0.891213 |
9,002,866 | 1 | 11 | 1. A system comprising: one or more computers including one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a query comprising three or more terms; identifying, from among the terms of the query, an entity name and two or more context terms; obtaining a plurality of candidate corrected spellings for the entity name; determining a respective count of co-occurrences of each context term with each candidate corrected spelling for the entity name, in a plurality of texts comprising: counting, as one co-occurrence, each distinct text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; or counting, as one co-occurrence, each distinct window of text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; determining a score for each candidate corrected spelling for the entity name based at least on the respective counts of co-occurrences of each context term with the respective candidate corrected spelling for the entity name, in the plurality of texts; selecting one or more of the candidate corrected spellings for the entity name based at least on the scores; and using the selected one or more candidate corrected spellings to generate a response to the query. | 1. A system comprising: one or more computers including one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a query comprising three or more terms; identifying, from among the terms of the query, an entity name and two or more context terms; obtaining a plurality of candidate corrected spellings for the entity name; determining a respective count of co-occurrences of each context term with each candidate corrected spelling for the entity name, in a plurality of texts comprising: counting, as one co-occurrence, each distinct text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; or counting, as one co-occurrence, each distinct window of text from the plurality of texts in which the context term and the candidate corrected spelling both appear at least once; determining a score for each candidate corrected spelling for the entity name based at least on the respective counts of co-occurrences of each context term with the respective candidate corrected spelling for the entity name, in the plurality of texts; selecting one or more of the candidate corrected spellings for the entity name based at least on the scores; and using the selected one or more candidate corrected spellings to generate a response to the query. 11. The system of claim 1 , wherein using the selected one or more candidate corrected spellings to generate a response to the query comprises: generating a spell-corrected query by replacing the entity name in the received query with the top-scoring candidate corrected spelling; and presenting the spell-corrected query and a user-selectable control that, when selected, causes the spell-corrected query to be submitted to a search engine. | 0.649444 |
7,750,891 | 90 | 95 | 90. A system for selectable input based upon motion of a pointing device in relation to a region having a plurality of selectable characters, comprising: means for tracking the motion of the pointing device in relation to the region, wherein the tracked motion defines a device path comprising at least two selected positions; means for determining which of the selected positions along the device path correspond to at least one of the selectable characters; and logic for determining a characteristic motion of the pointing device that corresponds to at least one of the selected positions along the device path corresponding to at least one of the selectable characters. | 90. A system for selectable input based upon motion of a pointing device in relation to a region having a plurality of selectable characters, comprising: means for tracking the motion of the pointing device in relation to the region, wherein the tracked motion defines a device path comprising at least two selected positions; means for determining which of the selected positions along the device path correspond to at least one of the selectable characters; and logic for determining a characteristic motion of the pointing device that corresponds to at least one of the selected positions along the device path corresponding to at least one of the selectable characters. 95. The system of claim 90 , wherein the region comprises a two-dimensional area. | 0.963514 |
5,495,603 | 4 | 5 | 4. The method of claim 3 wherein said plurality of file characteristics includes a file size designation and one or more file type designations. | 4. The method of claim 3 wherein said plurality of file characteristics includes a file size designation and one or more file type designations. 5. The method of claim 4 further including the step of: storing said selected file management class for said first file in said storage means. | 0.939264 |
8,897,618 | 17 | 20 | 17. A communication method comprising: recording an audio visual asset using a predetermined script wherein the predetermined script is converted into a variable final message compilation associable with a plurality of users; partitioning the audio visual asset into at least one audio visual segment such that the variable final message compilation is anticipated; editing the at least one audio visual segment by applying at least one of a naming paradigm and a data tagging system such that the at least one audio visual segment is accessible via an audio visual data tag and is exported to the variable final message compilation; overlaying the at least one audio visual segment with at least one audio visual variable; and compiling the variable final message compilation by uploading the at least one audio visual segment into a multimedia synthesis compiler such that the variable final message compilation is generated. | 17. A communication method comprising: recording an audio visual asset using a predetermined script wherein the predetermined script is converted into a variable final message compilation associable with a plurality of users; partitioning the audio visual asset into at least one audio visual segment such that the variable final message compilation is anticipated; editing the at least one audio visual segment by applying at least one of a naming paradigm and a data tagging system such that the at least one audio visual segment is accessible via an audio visual data tag and is exported to the variable final message compilation; overlaying the at least one audio visual segment with at least one audio visual variable; and compiling the variable final message compilation by uploading the at least one audio visual segment into a multimedia synthesis compiler such that the variable final message compilation is generated. 20. The method of claim 17 wherein a plurality of audio visual assets are recorded using the predetermined script. | 0.814332 |
10,013,415 | 23 | 26 | 23. A method comprising: periodically scanning a plurality of content sources to identify words and phrases being shared among one or more online communities of remote users as spots, wherein sharing of a word or a phrase as a spot by a remote user in an online community from among the one or more online communities of remote users is indicative of user interest in the word or the phrase; storing the spots along with information related to the spots, wherein the information related to the spots comprises at least one of identities of one or more remote users from among the one or more online communities of remote users sharing each spot, a contextual information associated with each one of the spots and online user comments associated with each one of the spots; determining at least one popularity-based metric for each spot from among the spots stored in the storage module; generating and periodically updating a spotting dictionary comprising at least a listing of popular spots based on the at least one popularity-based metric associated with each spot; provisioning the spotting dictionary to one or more remote users from among the one or more online communities of remote users; and facilitating creation of an interactive web-based application capable of residing natively in a user-device associated with the remote users, the web-based application comprising a plurality of user interfaces (UIs) configured to facilitate the sharing of the word or the phrase as the spot. | 23. A method comprising: periodically scanning a plurality of content sources to identify words and phrases being shared among one or more online communities of remote users as spots, wherein sharing of a word or a phrase as a spot by a remote user in an online community from among the one or more online communities of remote users is indicative of user interest in the word or the phrase; storing the spots along with information related to the spots, wherein the information related to the spots comprises at least one of identities of one or more remote users from among the one or more online communities of remote users sharing each spot, a contextual information associated with each one of the spots and online user comments associated with each one of the spots; determining at least one popularity-based metric for each spot from among the spots stored in the storage module; generating and periodically updating a spotting dictionary comprising at least a listing of popular spots based on the at least one popularity-based metric associated with each spot; provisioning the spotting dictionary to one or more remote users from among the one or more online communities of remote users; and facilitating creation of an interactive web-based application capable of residing natively in a user-device associated with the remote users, the web-based application comprising a plurality of user interfaces (UIs) configured to facilitate the sharing of the word or the phrase as the spot. 26. The method according to claim 23 , further comprising scanning one or more user linked accounts corresponding to a remote user from among the one or more online communities of remote users for detecting a presence of at least one pre-defined character embedded within online textual content, and, to extract a word or a phrase disposed substantially adjacent to at least one pre-defined character as a spot. | 0.868522 |
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